Editor’s Choice Articles

Background: The long-term prognosis of current treatments for anal sphincter incontinence (ASI) is poor. Here, we explored the efficacy of tissue adipose stromal vascular fraction SVF (tSVF) on ASI and compared it to that of cellular SVF (cSVF). We then investigated possible mechanisms. Methods: Rat cSVF and tSVF were isolated and labeled with DIL. One day after modeling, three groups received phosphate-buffered saline (PBS), cSVF, tSVF, respectively. The control group received nil modeling nor any treatments. The effect was assessed by function test for anal pressure and electromyography, and staining for fiber content, proliferation and differentiation at day 5 and day 10. Results: cSVF injection resulted in faster healing than tSVF. The cSVF group showed significant improvement on anal pressure on day 10. For the electromyography test, cSVF showed significant improvement for the frequencies on day 10, and for the peak values on both time points, while tSVF showed significant improvement for the peak values on day 10. The two SVF both alleviated fibrosis. Immunofluorescence tracing identified differentiation of some injected cells towards myosatellite cells and smooth muscle cells in both SVF groups. For all the tests, the tSVF group tends to have similar or lower effects than the cSVF group with no significant difference. Conclusion: cSVF and tSVF are both safe and effective in treating ASI, while the effect of cSVF is slighter higher than tSVF. Full article

Hypertension is a chronic condition that is one of the prominent reasons behind cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the deterioration in a health condition could even result in mortality. If it can be detected early, with proper treatment, undesirable outcomes can be avoided. Until now, the gold standard is the invasive way of measuring blood pressure (BP) using a catheter. Additionally, the cuff-based and noninvasive methods are too cumbersome or inconvenient for frequent measurement of BP. With the advancement of sensor technology, signal processing techniques, and machine learning algorithms, researchers are trying to find the perfect relationships between biomedical signals and changes in BP. This paper is a literature review of the studies conducted on the cuffless noninvasive measurement of BP using biomedical signals. Relevant articles were selected using specific criteria, then traditional techniques for BP measurement were discussed along with a motivation for cuffless measurement use of biomedical signals and machine learning algorithms. The review focused on the progression of different noninvasive cuffless techniques rather than comparing performance among different studies. The literature survey concluded that the use of deep learning proved to be the most accurate among all the cuffless measurement techniques. On the other side, this accuracy has several disadvantages, such as lack of interpretability, computationally extensive, standard validation protocol, and lack of collaboration with health professionals. Additionally, the continuing work by researchers is progressing with a potential solution for these challenges. Finally, future research directions have been provided to encounter the challenges. Full article

Electrospun polymeric matrices have long been investigated as constructs for use in regenerative medicine, yet relatively few have been commercialized for human clinical use. In 2017, a novel electrospun matrix, composed of two synthetic biocompatible polymers, polyglactin 910 (PLGA 10:90) and polydioxanone (PDO) of varying pore and fiber sizes (i.e., hybrid-scale) was developed and cleared by the FDA for human clinical use. The present review aims to explain the mechanism of action and review the preclinical and clinical results to summarize the efficacy of the matrix across multiple use cases within the wound care setting, including an assessment of over 150 wounds of varying etiologies treated with the synthetic matrix. Clinical data demonstrated effective use of the synthetic hybrid-scale fiber matrix across a variety of wound etiologies, including diabetic foot and venous leg ulcers, pressure ulcers, burns, and surgical wounds. This review represents a comprehensive clinical demonstration of a synthetic, electrospun, hybrid-scale matrix and illustrates its value and versatility across multiple wound etiologies. Full article

Kidney–ureter–bladder (KUB) imaging is a radiological examination with a low cost, low radiation, and convenience. Although emergency room clinicians can arrange KUB images easily as a first-line examination for patients with suspicious urolithiasis, interpreting the KUB images correctly is difficult for inexperienced clinicians. Obtaining a formal radiology report immediately after a KUB imaging examination can also be challenging. Recently, artificial-intelligence-based computer-aided diagnosis (CAD) systems have been developed to help clinicians who are not experts make correct diagnoses for further treatment more effectively. Therefore, in this study, we proposed a CAD system for KUB imaging based on a deep learning model designed to help first-line emergency room clinicians diagnose urolithiasis accurately. A total of 355 KUB images were retrospectively collected from 104 patients who were diagnosed with urolithiasis at Kaohsiung Chang Gung Memorial Hospital. Then, we trained a deep learning model with a ResNet architecture to classify KUB images in terms of the presence or absence of kidney stones with this dataset of pre-processed images. Finally, we tuned the parameters and tested the model experimentally. The results show that the accuracy, sensitivity, specificity, and F1-measure of the model were 0.977, 0.953, 1, and 0.976 on the validation set and 0.982, 0.964, 1, and 0.982 on the testing set, respectively. Moreover, the results demonstrate that the proposed model performed well compared to the existing CNN-based methods and was able to detect urolithiasis in KUB images successfully. We expect the proposed approach to help emergency room clinicians make accurate diagnoses and reduce unnecessary radiation exposure from computed tomography (CT) scans, along with the associated medical costs. Full article

Cell and gene therapies (CGT) have reached new therapeutic targets but have noticeably high prices. Solutions to reduce production costs might be found in CGT storage and transportation since they typically involve cryopreservation, which is a heavily burdened process. Encapsulation at hypothermic temperatures (e.g., 2–8 °C) could be a feasible alternative. Adipose tissue-derived mesenchymal stromal cells (MSC(AT)) expanded using fetal bovine serum (FBS)- (MSC-FBS) or human platelet lysate (HPL)-supplemented mediums (MSC-HPL) were encapsulated in alginate beads for 30 min, 5 days, and 12 days. After bead release, cell recovery and viability were determined to assess encapsulation performance. MSC identity was verified by flow cytometry, and a set of assays was performed to evaluate functionality. MSC(AT) were able to survive encapsulated for a standard transportation period of 5 days, with recovery values of 56 ± 5% for MSC-FBS and 77 ± 6% for MSC-HPL (which is a negligible drop compared to earlier timepoints). Importantly, MSC function did not suffer from encapsulation, with recovered cells showing robust differentiation potential, expression of immunomodulatory molecules, and hematopoietic support capacity. MSC(AT) encapsulation was proven possible for a remarkable 12 day period. There is currently no solution to completely replace cryopreservation in CGT logistics and supply chain, although encapsulation has shown potential to act as a serious competitor. Full article

A 3D tumor spheroid has been increasingly applied in pharmaceutical development for its simulation of the tumor structure and microenvironment. The embedded-culture of a tumor spheroid within a hydrogel microenvironment could help to improve the mimicking of in vivo cell growth and the development of 3D models for tumor invasiveness evaluation, which could enhance its drug efficiency prediction together with cell viability detection. NCI-H23 spheroids and CT-26 spheroids, from a non–small cell lung cancer and colorectal cancer cell line, respectively, together with extracellular matrix were generated for evaluating their sensitivity to AMG510 (a KRAS^G12C inhibitor) under normoxia and hypoxia conditions, which were created by an on-stage environmental chamber. Results demonstrated that NCI-H23, the KRAS^G12C moderate expression cell line, only mildly responded to AMG510 treatment in normal 2D and 3D cultures and could be clearly evaluated by our system in hypoxia conditions, while the negative control CT-26 (G12D-mutant) spheroid exhibited no significant response to AMG510 treatment. In summary, our system, together with a controlled microenvironment and imaging methodology, provided an easily assessable and effective methodology for 3D in vitro drug efficiency testing and screenings. Full article

Successful surgery on drug-resistant epilepsy patients (DRE) needs precise localization of the seizure onset zone (SOZ). Previous studies analyzing this issue still face limitations, such as inadequate analysis of features, low sensitivity and limited generality. Our study proposed an innovative and effective SOZ localization method based on multiple epileptogenic biomarkers (spike and HFOs), and analysis of single-contact (MEBM-SC) to address the above problems. We extracted contacts epileptic features from signal distributions and signal energy based on machine learning and end-to-end deep learning. Among them, a normalized pathological ripple rate was designed to reduce the disturbance of physiological ripple and enhance the performance of SOZ localization. Then, a feature selection algorithm based on Shapley value and hypothetical testing (ShapHT+) was used to limit interference from irrelevant features. Moreover, an attention mechanism and a focal loss algorithm were used on the classifier to learn significant features and overcome the unbalance of SOZ/nSOZ contacts. Finally, we provided an SOZ prediction and visualization on magnetic resonance imaging (MRI). Ten patients with DRE were selected to verify our method. The experiment performed cross-validation and revealed that MEBM-SC obtains higher sensitivity. Additionally, the spike has better sensitivity while HFOs have better specificity, and the combination of these biomarkers can achieve the best performance. The study confirmed that MEBM-SC can increase the sensitivity and accuracy of SOZ localization and help clinicians to perform a precise and reliable preoperative evaluation based on interictal SEEG. Full article

The attention on orthopedic biomaterials has shifted from their direct osteogenic properties to their osteoimmunomodulation, especially the modulation of macrophage polarization. Presently, advanced technologies endow polyetheretherketone (PEEK) with good osteoimmunomodulation by modifying PEEK surface characteristics or incorporating bioactive substances with regulating macrophage polarization. Recent studies have demonstrated that the fabrication of a hydrophilic surface and the incorporation of bioactive substances into PEEK (e.g., zinc, calcium, and phosphate) are good strategies to promote osteogenesis by enhancing the polarization of M2 macrophages. Furthermore, the modification by other osteoimmunomodulatory composites (e.g., lncRNA-MM2P, IL-4, IL-10, and chitosan) and their controlled and desired release may make PEEK an optimal bio-activated implant for regulating and balancing the osteogenic system and immune system. The purpose of this review is to comprehensively evaluate the potential of bio-activated PEEK in polarizing macrophages into M2 phenotype to improve osteogenesis. For this objective, we retrieved and discussed different kinds of bio-activated PEEK regarding improving osteogenesis through modulating macrophage polarization. Meanwhile, the relevant challenges and outlook were presented. We hope that this review can shed light on the development of bio-activated PEEK with more favorable osteoimmunomodulation. Full article

A recently introduced model-based deep learning (MoDL) technique successfully incorporates convolutional neural network (CNN)-based regularizers into physics-based parallel imaging reconstruction using a small number of network parameters. Wave-controlled aliasing in parallel imaging (CAIPI) is an emerging parallel imaging method that accelerates imaging acquisition by employing sinusoidal gradients in the phase- and slice/partition-encoding directions during the readout to take better advantage of 3D coil sensitivity profiles. We propose wave-encoded MoDL (wave-MoDL) combining the wave-encoding strategy with unrolled network constraints for highly accelerated 3D imaging while enforcing data consistency. We extend wave-MoDL to reconstruct multicontrast data with CAIPI sampling patterns to leverage similarity between multiple images to improve the reconstruction quality. We further exploit this to enable rapid quantitative imaging using an interleaved look-locker acquisition sequence with T₂ preparation pulse (3D-QALAS). Wave-MoDL enables a 40 s MPRAGE acquisition at 1 mm resolution at 16-fold acceleration. For quantitative imaging, wave-MoDL permits a 1:50 min acquisition for T₁, T₂, and proton density mapping at 1 mm resolution at 12-fold acceleration, from which contrast-weighted images can be synthesized as well. In conclusion, wave-MoDL allows rapid MR acquisition and high-fidelity image reconstruction and may facilitate clinical and neuroscientific applications by incorporating unrolled neural networks into wave-CAIPI reconstruction. Full article

With advances in portable and wearable devices, it should be possible to analyze and interpret the collected biosignals from those devices to tailor a psychological intervention to help patients. This study focuses on detecting anxiety by using a portable device that collects electrocardiogram (ECG) and respiration (RSP) signals. The feature extraction focused on heart-rate variability (HRV) and breathing-rate variability (BRV). We show that a significant change in these signals occurred between the non-anxiety-induced and anxiety-induced states. The HRV biomarkers were the mean heart rate (MHR; $\overline{p}$ = 0.04), the standard deviation of the heart rate (SD; $\overline{p}$ = 0.01), and the standard deviation of NN intervals (SDNN; $\overline{p}$ = 0.03) for ECG signals, and the mean breath rate (MBR; $\overline{p}$ = 0.002), the standard deviation of the breath rate (SD; $\overline{p}$ < 0.0001), the root mean square of successive differences (RMSSD; $\overline{p}$ < 0.0001) and SDNN ($\overline{p}$ < 0.0001) for RSP signals. This work extends the existing literature on the relationship between stress and HRV/BRV by being the first to introduce a transitional phase. It contributes to systematically processing mental and emotional impulse data in humans measured via ECG and RSP signals. On the basis of these identified biomarkers, artificial-intelligence or machine-learning algorithms, and rule-based classification, the automated biosignal-based psychological assessment of patients could be within reach. This creates a broad basis for detecting and evaluating psychological abnormalities in individuals upon which future psychological treatment methods could be built using portable and wearable devices. Full article

Robotic patients show great potential for helping to improve medical palpation training, as they can provide feedback that cannot be obtained in a real patient. They provide information about internal organ deformation that can significantly enhance palpation training by giving medical trainees visual insight based on the pressure they apply for palpation. This can be achieved by using computational models of abdomen mechanics. However, such models are computationally expensive, and thus unable to provide real-time predictions. In this work, we proposed an innovative surrogate model of abdomen mechanics by using machine learning (ML) and finite element (FE) modelling to virtually render internal tissue deformation in real time. We first developed a new high-fidelity FE model of the abdomen mechanics from computerized tomography (CT) images. We performed palpation simulations to produce a large database of stress distribution on the liver edge, an area of interest in most examinations. We then used artificial neural networks (ANNs) to develop the surrogate model and demonstrated its application in an experimental palpation platform. Our FE simulations took 1.5 h to predict stress distribution for each palpation while this only took a fraction of a second for the surrogate model. Our results show that our artificial neural network (ANN) surrogate has an accuracy of 92.6%. We also showed that the surrogate model is able to use the experimental input of palpation location and force to provide real-time projections onto the robotics platform. This enhanced robotics platform has the potential to be used as a training simulator for trainees to hone their palpation skills. Full article

The management and definitive treatment of segmental bone defects in the setting of acute trauma, fracture non-union, revision joint arthroplasty, and tumor surgery are challenging clinical problems with no consistently satisfactory solution. Orthopaedic surgeons are developing novel strategies to treat these problems, including three-dimensional (3D) printing combined with growth factors and/or cells. This article reviews the current strategies for management of segmental bone loss in orthopaedic surgery, including graft selection, bone graft substitutes, and operative techniques. Furthermore, we highlight 3D printing as a technology that may serve a major role in the management of segmental defects. The optimization of a 3D-printed scaffold design through printing technique, material selection, and scaffold geometry, as well as biologic additives to enhance bone regeneration and incorporation could change the treatment paradigm for these difficult bone repair problems. Full article

Point-of-care (POC) tests for the diagnosis of diseases are critical to the improvement of the standard of living, especially for resource-limited areas or countries. In recent years, nanobiosensors based on noble metal nanoparticles (NM NPs) have emerged as a class of effective and versatile POC testing technology. The unique features of NM NPs ensure great performance of associated POC nanobiosensors. In particular, NM NPs offer various signal transduction principles, such as plasmonics, catalysis, photothermal effect, and so on. Significantly, the detectable signal from NM NPs can be tuned and optimized by controlling the physicochemical parameters (e.g., size, shape, and elemental composition) of NPs. In this article, we introduce the inherent merits of NM NPs that make them attractive for POC testing, discuss recent advancement of NM NPs-based POC tests, highlight their social impacts, and provide perspectives on challenges and opportunities in the field. We hope the review and insights provided in this article can inspire new fundamental and applied research in this emerging field. Full article

Adenovirus (Ad) is a widely studied viral vector for cancer therapy as it can be engineered to cause selective lysis of cancer cells. However, Ad delivery is limited in treating cancers that do not have coxsackievirus and adenovirus receptors (CAR). To overcome this challenge, Ad-encapsulated liposomes were developed that enhance the delivery of Ads and increase therapeutic efficacy. Cationic empty liposomes were manufactured first, to which an anionic Ad were added, which resulted in encapsulated Ad liposomes through charge interaction. Optimization of the liposome formula was carried out with series of formulation variables experiments using an extrusion process, which is ideal for laboratory-scale small batches. Later, the optimized formulation was manufactured with a homogenization technique—A high shear rotor-stator blending, that is ideal for large-scale manufacturing and is in compliance with Good Manufacturing Practices (GMP). Comparative in vitro transduction, physicochemical characterization, long-term storage stability at different temperature conditions, and in vivo animal studies were performed. Ad encapsulated liposomes transduced CAR deficient cells 100-fold more efficiently than the unencapsulated Ad (p ≤ 0.0001) in vitro, and 4-fold higher in tumors injected in nude mice in vivo. Both extrusion and homogenization performed similarly–with equivalent in vitro and in vivo transduction efficiencies, physicochemical characterization, and long-term storage stability. Thus, two Ad encapsulated liposomes preparation methods used herein, i.e., extrusion vs. homogenization were equivalent in terms of enhanced Ad performance and long-term storage stability; this will, hopefully, facilitate translation to the clinic. Full article

Cervical cancer, a common chronic disease, is one of the most prevalent and curable cancers among women. Pap smear images are a popular technique for screening cervical cancer. This study proposes a computer-aided diagnosis for cervical cancer utilizing the novel Cervical Net deep learning (DL) structures and feature fusion with Shuffle Net structural features. Image acquisition and enhancement, feature extraction and selection, as well as classification are the main steps in our cervical cancer screening system. Automated features are extracted using pre-trained convolutional neural networks (CNN) fused with a novel Cervical Net structure in which 544 resultant features are obtained. To minimize dimensionality and select the most important features, principal component analysis (PCA) is used as well as canonical correlation analysis (CCA) to obtain the best discriminant features for five classes of Pap smear images. Here, five different machine learning (ML) algorithms are fed into these features. The proposed strategy achieved the best accuracy ever obtained using a support vector machine (SVM), in which fused features between Cervical Net and Shuffle Net is 99.1% for all classes. Full article

Despite a significant advance in the pathophysiological understanding of peripheral nerve damage, the successful treatment of large nerve defects remains an unmet medical need. In this article, axon growth guidance for peripheral nerve regeneration was systematically reviewed and discussed mainly from the engineering perspective. In addition, the common approaches to surgery, bioengineering approaches to emerging technologies such as optogenetic stimulation and magnetic stimulation for functional recovery were discussed, along with their pros and cons. Additionally, clear future perspectives of axon guidance and nerve regeneration were addressed. Full article

Gliomas are the most common type of primary brain tumors and one of the highest causes of mortality worldwide. Accurate grading of gliomas is of immense importance to administer proper treatment plans. In this paper, we develop a comprehensive non-invasive multimodal magnetic resonance (MR)-based computer-aided diagnostic (CAD) system to precisely differentiate between different grades of gliomas (Grades: I, II, III, and IV). A total of 99 patients with gliomas (M = 49, F = 50, age range = 1–79 years) were included after providing their informed consent to participate in this study. The proposed imaging-based glioma grading (GG-CAD) system utilizes three different MR imaging modalities, namely; contrast-enhanced T1-MR, T2-MR known as fluid-attenuated inversion-recovery (FLAIR), and diffusion-weighted (DW-MR) to extract the following imaging features: (i) morphological features based on constructing the histogram of oriented gradients (HOG) and estimating the glioma volume, (ii) first and second orders textural features by constructing histogram, gray-level run length matrix (GLRLM), and gray-level co-occurrence matrix (GLCM), (iii) functional features by estimating voxel-wise apparent diffusion coefficients (ADC) and contrast-enhancement slope. These features are then integrated together and processed using a Gini impurity-based selection approach to find the optimal set of significant features. The reduced significant features are then fed to a multi-layer perceptron artificial neural networks (MLP-ANN) classification model to obtain the final diagnosis of a glioma tumor as Grade I, II, III, or IV. The GG-CAD system was evaluated on the enrolled 99 gliomas (Grade I = 13, Grade II = 22, Grade III = 22, and Grade IV = 42) using a leave-one-subject-out (LOSO) and k-fold stratified (with k = 5 and 10) cross-validation approach. The GG-CAD achieved 0.96 ± 0.02 quadratic-weighted Cohen’s kappa and 95.8% ± 1.9% overall diagnostic accuracy at LOSO and an outstanding diagnostic performance at k = 10 and 5. Alternative classifiers, including RFs and SVM${}_{lin}$ produced inferior results compared to the proposed MLP-ANN GG-CAD system. These findings demonstrate the feasibility of the proposed CAD system as a novel tool to objectively characterize gliomas using the comprehensive extracted and selected imaging features. The developed GG-CAD system holds promise to be used as a non-invasive diagnostic tool for Precise Grading of Glioma. Full article

The aim of this study was to assess the condylar volume in adult patients with different skeletal classes and vertical patterns using cone-beam computed tomography (CBCT). CBCT scans of 146 condyles from 73 patients (mean age 30 ± 12 years old; 49 female, 24 male) were selected from the archive of the Department of Dentistry and Maxillofacial Surgery of Fondazione IRCCS Ca’ Granda, Milan, Italy, and retrospectively analyzed. The following inclusion criteria were used: adult patients; CBCT performed with the same protocol (0.4 mm slice thickness, 16 × 22 cm field of view, 20 s scan time); no systemic diseases; and no previous orthodontic treatments. Three-dimensional cephalometric tracings were performed for each patient, the mandibular condyles were segmented and the relevant volumes calculated using Mimics Materialize 20.0^® software (Materialise, Leuven, Belgium). Right and left variables were analyzed together using random-intercept linear regression models. No significant association between condylar volumes and skeletal class was found. On the other hand, in relation to vertical patterns, the mean values of the mandibular condyle volumes in hyperdivergent subjects (688 mm³) with a post-rotation growth pattern (625 mm³) were smaller than in hypodivergent patients (812 mm³) with a horizontal growth pattern (900 mm³). Patients with an increased divergence angle had smaller condylar volumes than subjects with normal or decreased mandibular plane divergence. This relationship may help the clinician when planning orthodontic treatment. Full article

We carry out a critical assessment of machine learning and deep learning models for the classification of skin tumors. Machine learning (ML) algorithms tested in this work include logistic regression, linear discriminant analysis, k-nearest neighbors classifier, decision tree classifier and Gaussian naive Bayes, while deep learning (DL) models employed are either based on a custom Convolutional Neural Network model, or leverage transfer learning via the use of pre-trained models (VGG16, Xception and ResNet50). We find that DL models, with accuracies up to 0.88, all outperform ML models. ML models exhibit accuracies below 0.72, which can be increased to up to 0.75 with ensemble learning. To further assess the performance of DL models, we test them on a larger and more imbalanced dataset. Metrics, such as the F-score and accuracy, indicate that, after fine-tuning, pre-trained models perform extremely well for skin tumor classification. This is most notably the case for VGG16, which exhibits an F-score of 0.88 and an accuracy of 0.88 on the smaller database, and metrics of 0.70 and 0.88, respectively, on the larger database. Full article

Despite a massive global preventative effort, heart failure remains the major cause of death globally. The number of patients requiring a heart transplant, the eventual last treatment option, far outnumbers the available donor hearts, leaving many to deteriorate or die on the transplant waiting list. Treating heart failure by transplanting a 3D bioprinted patient-specific cardiac patch to the infarcted region on the myocardium has been investigated as a potential future treatment. To date, several studies have created cardiac patches using 3D bioprinting; however, testing the concept is still at a pre-clinical stage. A handful of clinical studies have been conducted. However, moving from animal studies to human trials will require an increase in research in this area. This review covers key elements to the design of a patient-specific cardiac patch, divided into general areas of biological design and 3D modelling. It will make recommendations on incorporating anatomical considerations and high-definition motion data into the process of 3D-bioprinting a patient-specific cardiac patch. Full article

Allogeneic cell therapy products, such as therapeutic cells derived from pluripotent stem cells (PSCs), have amazing potential to treat a wide variety of diseases and vast numbers of patients globally. However, there are various challenges related to manufacturing PSCs in single-use bioreactors, particularly at larger volumetric scales. This manuscript addresses these challenges and presents potential solutions to alleviate the anticipated bottlenecks for commercial-scale manufacturing of high-quality therapeutic cells derived from PSCs. Full article

The ever-increasing use of plastics, their fossil origin, and especially their persistence in nature have started a wave of new innovations in materials that are renewable, offer the functionalities of plastics, and are biodegradable. One such class of biopolymers, polyhydroxyalkanoates (PHAs), are biosynthesized by numerous microorganisms through the conversion of carbon-rich renewable resources. PHA homo- and heteropolyesters are intracellular products of secondary microbial metabolism. When isolated from microbial biomass, PHA biopolymers mimic the functionalities of many of the top-selling plastics of petrochemical origin, but biodegrade in soil, freshwater, and marine environments, and are both industrial- and home-compostable. Only a handful of PHA biopolymers have been studied in-depth, and five of these reliably match the desired material properties of established fossil plastics. Realizing the positive attributes of PHA biopolymers, several established chemical companies and numerous start-ups, brand owners, and converters have begun to produce and use PHA in a variety of industrial and consumer applications, in what can be described as the emergence of the “PHA industry”. While this positive industrial and commercial relevance of PHA can hardly be described as the first wave in its commercial development, it is nonetheless a very serious one with over 25 companies and start-ups and 30+ brand owners announcing partnerships in PHA production and use. The combined product portfolio of the producing companies is restricted to five types of PHA, namely poly(3-hydroxybutyrate), poly(4-hydroxybutyrate), poly(3-hydroxybutyrate-co-3-hydroxyvalerate), poly(3-hydroxybutyrate-co-4-hydroxybutyrate), and poly(3-hydroxybutyrate-co-3-hydroxyhexanoate), even though PHAs as a class of polymers offer the potential to generate almost limitless combinations of polymers beneficial to humankind. To date, by varying the co-monomer type and content in these PHA biopolymers, their properties emulate those of the seven top-selling fossil plastics, representing 230 million t of annual plastics production. Capacity expansions of 1.5 million t over the next 5 years have been announced. Policymakers worldwide have taken notice and are encouraging industry to adopt biodegradable and compostable material solutions. This wave of commercialization of PHAs in single-use and in durable applications holds the potential to make the decisive quantum leap in reducing plastic pollution, the depletion of fossil resources, and the emission of greenhouse gases and thus fighting climate change. This review presents setbacks and success stories of the past 40 years and the current commercialization wave of PHA biopolymers, their properties, and their fields of application. Full article

Mesenchymal stem cells (MSCs) are primary candidates in tissue engineering and stem cell therapies due to their intriguing regenerative and immunomodulatory potential. Their ability to self-assemble into three-dimensional (3D) aggregates further improves some of their therapeutic properties, e.g., differentiation potential, secretion of cytokines, and homing capacity after administration. However, high hydrodynamic shear forces and the resulting mechanical stresses within commercially available dynamic cultivation systems can decrease their regenerative properties. Cells embedded within a polymer matrix, however, lack cell-to-cell interactions found in their physiological environment. Here, we present a “semi scaffold-free” approach to protect the cells from high shear forces by a physical barrier, but still allow formation of a 3D structure with in vivo-like cell-to-cell contacts. We highlight a relatively simple method to create core–shell capsules by inverse gelation. The capsules consist of an outer barrier made from sodium alginate, which allows for nutrient and waste diffusion and an inner compartment for direct cell-cell interactions. Next to capsule characterization, a harvesting procedure was established and viability and proliferation of human adipose-derived MSCs were investigated. In the future, this encapsulation and cultivation technique might be used for MSC-expansion in scalable dynamic bioreactor systems, facilitating downstream procedures, such as cell harvest and differentiation into mature tissue grafts. Full article

As medicine advances and physicians are able to provide patients with innovative solutions, including placement of temporary or permanent medical devices that drastically improve quality of life of the patient, there is the persistent, recurring problem of chronic bacterial infection, including osteomyelitis. Osteomyelitis can manifest as a result of traumatic or contaminated wounds or implant-associated infections. This bacterial infection can persist as a result of inadequate treatment regimens or the presence of biofilm on implanted medical devices. One strategy to mitigate these concerns is the use of implantable medical devices that simultaneously act as local drug delivery devices (DDDs). This classification of device has the potential to prevent or aid in clearing chronic bacterial infection by delivering effective doses of antibiotics to the area of interest and can be engineered to simultaneously aid in tissue regeneration. This review will provide a background on bacterial infection and current therapies as well as current and prospective implantable DDDs, with a particular emphasis on local DDDs to combat bacterial osteomyelitis. Full article

Lumbar disc herniation is one of the most common degenerative spinal conditions resulting in lower back pain and sciatica. Surgical treatment options include microdiscectomy, lumbar fusion, total disc replacement, and other minimally invasive approaches. At present, microdiscectomy procedures are the most used technique; however, the annulus fibrosus is left with a defect that without treatment may contribute to high reherniation rates and changes in the biomechanics of the lumbar spine. This paper aims to review current commercially available products that mechanically close the annulus including the AnchorKnot^® suture-passing device and the Barricaid^® annular closure device. Previous studies and reviews have focused mainly on a biomimetic biomaterials approach and have described some mechanical and biological requirements for an active annular repair/regeneration strategy but are still far away from clinical implementation. Therefore, in this paper we aim to create a design specification for a mechanical annular closure strategy by identifying the most important mechanical and biological design parameters, including consideration of material selection, preclinical testing requirements, and requirements for clinical implementation. Full article

Organ on chip (OOC) has emerged as a major technological breakthrough and distinct model system revolutionizing biomedical research and drug discovery by recapitulating the crucial structural and functional complexity of human organs in vitro. OOC are rapidly emerging as powerful tools for oncology research. Indeed, Cancer on chip (COC) can ideally reproduce certain key aspects of the tumor microenvironment (TME), such as biochemical gradients and niche factors, dynamic cell–cell and cell–matrix interactions, and complex tissue structures composed of tumor and stromal cells. Here, we review the state of the art in COC models with a focus on the microphysiological systems that host multicellular 3D tissue engineering models and can help elucidate the complex biology of TME and cancer growth and progression. Finally, some examples of microengineered tumor models integrated with multi-organ microdevices to study disease progression in different tissues will be presented. Full article

Since the introduction of Nickel-Titanium alloy as the material of choice for the manufacturing of endodontic rotary instruments, the success rate of the root canal therapies has been significantly increased. This success mainly arises from the properties of the Nickel-Titanium alloy: the biocompatibility, the superelasticity and the shape memory effect. Those characteristics have led to a reduction in time of endodontic treatments, a simplification of instrumentation procedures and an increase of predictability and effectiveness of endodontic treatments. Nevertheless, the intracanal separation of Nickel-Titanium rotary instruments is still a major concern of endodontists, with a consequent possible reduction in the outcome rate. As thoroughly demonstrated, the two main causes of intracanal separation of endodontic instruments are the cyclic fatigue and the torsional loads. As results, in order to reduce the percentage of intracanal separation research and manufacturers have been focused on the parameters that directly or indirectly influence mechanical properties of endodontic rotary instruments. This review describes the current state of the art regarding the Nickel-Titanium alloy in endodontics, the mechanical behavior of endodontic rotary instruments and the relative stresses acting on them during intracanal instrumentation, highlighting the limitation of the current literature. Full article

Stroke is the biggest cause of adult disability and the third biggest cause of death in the US. Stroke is a medical emergency, and the treatment given in the early hours is important in shaping the patient’s long-term recovery and prognosis. Despite the fact that substantial attention has been dedicated to this complex and difficult issue in healthcare, novel strategies such as operation research-based approaches have hardly been used to deal with the difficult challenges associated with stroke. This study proposes a novel approach with data envelopment analysis (DEA) and multi-objective linear programming (MOLP) in hospitals that provide stroke care services to select the most efficient approach, which will be a new experiment in literature perception. DEA and MOLP are widely used for performance evaluation and efficiency measurement. Despite their similarities and common concepts, the two disciplines have evolved separately. The generalised DEA (GDEA) cannot incorporate the preferences of decision-makers (DMs) preferences and historical efficiency data. In contrast, MOLP can incorporate the DM’s preferences into the decision-making process. We transform the GDEA model into MOLP through the max-ordering approach to (i) solve the problem interactively; (ii) use the step method (STEM) and consider DM’s preferences; (iii) eliminate the need for predetermined preference information; and (iv) apply the most preferred solution (MPS) to identify the most efficient approach. A case study of hospitals that provide stroke care services is taken as an example to illustrate the potential application of the proposed approach method. Full article

Maximizing the value of each available data point in bioprocess development is essential in order to reduce the time-to-market, lower the number of expensive wet-lab experiments, and maximize process understanding. Advanced in silico methods are increasingly being investigated to accomplish these goals. Within this contribution, we propose a novel integrated process model procedure to maximize the use of development data to optimize the Stage 1 process validation work flow. We generate an integrated process model based on available data and apply two innovative Monte Carlo simulation-based parameter sensitivity analysis linearization techniques to automate two quality by design activities: determining risk assessment severity rankings and establishing preliminary control strategies for critical process parameters. These procedures are assessed in a case study for proof of concept on a candidate monoclonal antibody bioprocess after process development, but prior to process characterization. The evaluation was successful in returning results that were used to support Stage I process validation milestones and demonstrated the potential to reduce the investigated parameters by up to 24% in process characterization, while simultaneously setting up a strategy for iterative updates of risk assessments and process controls throughout the process life-cycle to ensure a robust and efficient drug supply. Full article

Cheese whey (CW) can be an excellent carbon source for polyhydroxyalkanoates (PHA)-producing bacteria. Most studies have used CW, which contains high amounts of lactose, however, there are no reports using raw CW, which has a relatively low amount of lactose. Therefore, in the present study, PHA production was evaluated in a two-stage process using the CW that contains low amounts of lactose. In first stage, the carbon source existing in CW was converted into acetic acid using the bacteria, Acetobacter pasteurianus C1, which was isolated from food waste. In the second stage, acetic acid produced in the first stage was converted into PHA using the bacteria, Bacillus sp. CYR-1. Under the condition of without the pretreatment of CW, acetic acid produced from CW was diluted at different folds and used for the production of PHA. Strain CYR-1 incubated with 10-fold diluted CW containing 5.7 g/L of acetic acid showed the higher PHA production (240.6 mg/L), whereas strain CYR-1 incubated with four-fold diluted CW containing 12.3 g/L of acetic acid showed 126 mg/L of PHA. After removing the excess protein present in CW, PHA production was further enhanced by 3.26 times (411 mg/L) at a four-fold dilution containing 11.3 g/L of acetic acid. Based on Fourier transform infrared spectroscopy (FT-IR), and ¹H and ¹³C nuclear magnetic resonance (NMR) analyses, it was confirmed that the PHA produced from the two-stage process is poly-β-hydroxybutyrate (PHB). All bands appearing in the FT-IR spectrum and the chemical shifts of NMR nearly matched with those of standard PHB. Based on these studies, we concluded that a two-stage process using Acetobacter pasteurianus C1 and Bacillus sp. CYR-1 would be applicable for the production of PHB using CW containing a low amount of lactose. Full article

Morphological and functional skin alterations secondary to the action of ionizing radiation are well documented. In addition to its application in the medical field, ionizing radiation represents a public health problem for diagnostic and therapeutic purposes due to the potential risk of exposure to unexpected events, such as nuclear accidents or malicious acts. With regard to the use of ionizing radiations in the medical field, today, they constitute a fundamental therapeutic method for various neoplastic pathologies. Therefore, the onset of adverse skin events induced by radiation represents a widespread and not negligible problem, affecting 95% of patients undergoing radiotherapy. A systematic literature search was performed from July 2021 up to August 2021 using PubMed, Embase, and Cochrane databases. Articles were screened by title, abstract and full text as needed. A manual search among the references of the included papers was also performed. This systematic review describes the various skin reactions that can arise following exposure to ionizing radiation and which significantly impact the quality of life, especially in cancer patients. Full article

Augmented Reality (AR) headsets have become the most ergonomic and efficient visualization devices to support complex manual tasks performed under direct vision. Their ability to provide hands-free interaction with the augmented scene makes them perfect for manual procedures such as surgery. This study demonstrates the reliability of an AR head-mounted display (HMD), conceived for surgical guidance, in navigating in-depth high-precision manual tasks guided by a 3D ultrasound imaging system. The integration between the AR visualization system and the ultrasound imaging system provides the surgeon with real-time intra-operative information on unexposed soft tissues that are spatially registered with the surrounding anatomic structures. The efficacy of the AR guiding system was quantitatively assessed with an in vitro study simulating a biopsy intervention aimed at determining the level of accuracy achievable. In the experiments, 10 subjects were asked to perform the biopsy on four spherical lesions of decreasing sizes (10, 7, 5, and 3 mm). The experimental results showed that 80% of the subjects were able to successfully perform the biopsy on the 5 mm lesion, with a 2.5 mm system accuracy. The results confirmed that the proposed integrated system can be used for navigation during in-depth high-precision manual tasks. Full article

Nanoparticles have recently emerged as valuable tools in biomedical imaging techniques. Here PEGylated and fluorinated nanocapsules based on poly(3-hydroxyalkanoate) containing a liquid core of perfluorooctyl bromide PFOB were formulated by an emulsion-evaporation process as potential ¹⁹F MRI imaging agents. Unsaturated poly(hydroxyalkanoate), PHAU, was produced by marine bacteria using coprah oil and undecenoic acid as substrates. PHA-g-(F; PEG) was prepared by two successive controlled thiol-ene reactions from PHAU with firstly three fluorinated thiols having from 3 up to 17 fluorine atoms and secondly with PEG-SH. The resulting PHA-g-(F; PEG)-based PFOB nanocapsules, with a diameter close to 250–300 nm, are shown to be visible in ¹⁹F MRI with an acquisition time of 15 min. The results showed that PFOB-nanocapsules based on PHA-g-(F; PEG) have the potential to be used as novel contrast agents for ¹⁹F MRI. Full article

Vaccination is of paramount importance to global health. With the advent of the more recent pandemics, the urgency to expand the range has become even more evident. However, the potential limited availability and affordability of vaccines to resource low- and middle-income countries has created a need for solutions that will ensure cost-effective vaccine production methods for these countries. Pichia pastoris (P. pastoris) (also known as Komagataella phaffii) is one of the most promising candidates for expression of heterologous proteins in vaccines development. It combines the speed and ease of highly efficient prokaryotic platforms with some key capabilities of mammalian systems, potentially reducing manufacturing costs. This review will examine the latest developments in P. pastoris from cell engineering and design to industrial production systems with focus on vaccine development and with reference to specific key case studies. Full article

The cornea comprises a pool of self-regenerating epithelial cells that are crucial to preserving clarity and visibility. Limbal epithelial stem cells (LESCs), which live in a specialized stem cell niche (SCN), are crucial for the survival of the human corneal epithelium. They live at the bottom of the limbal crypts, in a physically enclosed microenvironment with a number of neighboring niche cells. Scientists also simplified features of these diverse microenvironments for more analysis in situ by designing and recreating features of different SCNs. Recent methods for regenerating the corneal epithelium after serious trauma, including burns and allergic assaults, focus mainly on regenerating the LESCs. Mesenchymal stem cells, which can transform into self-renewing and skeletal tissues, hold immense interest for tissue engineering and innovative medicinal exploration. This review summarizes all types of LESCs, identity and location of the human epithelial stem cells (HESCs), reconstruction of LSCN and artificial stem cells for self-renewal. Full article

Pesticides are chemical compounds used to eliminate pests; among them, herbicides are compounds particularly toxic to weeds, and this property is exploited to protect the crops from unwanted plants. Pesticides are used to protect and maximize the yield and quality of crops. The excessive use of these chemicals and their persistence in the environment have generated serious problems, namely pollution of soil, water, and, to a lower extent, air, causing harmful effects to the ecosystem and along the food chain. About soil pollution, the residual concentration of pesticides is often over the limits allowed by the regulations. Where this occurs, the challenge is to reduce the amount of these chemicals and obtain agricultural soils suitable for growing ecofriendly crops. The microbial metabolism of indigenous microorganisms can be exploited for degradation since bioremediation is an ecofriendly, cost-effective, rather efficient method compared to the physical and chemical ones. Several biodegradation techniques are available, based on bacterial, fungal, or enzymatic degradation. The removal efficiencies of these processes depend on the type of pollutant and the chemical and physical conditions of the soil. The regulation on the use of pesticides is strictly connected to their environmental impacts. Nowadays, every country can adopt regulations to restrict the consumption of pesticides, prohibit the most harmful ones, and define the admissible concentrations in the soil. However, this variability implies that each country has a different perception of the toxicology of these compounds, inducing different market values of the grown crops. This review aims to give a picture of the bioremediation of soils polluted with commercial pesticides, considering the features that characterize the main and most used ones, namely their classification and their toxicity, together with some elements of legislation into force around the world. Full article

Thermoresponsive hydrogel-based wound dressings with an incorporated antimicrobial agent can be fabricated employing 3D printing technology. A novel printable ink containing poly(N-isopropylacrylamide) (PNIPAAm) precursors, sodium alginate (ALG), methylcellulose (MC) that is laden with a mixture of octenidine dihydrochloride and 2-phenoxyethanol (Octenisept^®, OCT) possess accurate printability and shape fidelity. This study also provides the protocol of ink’s use for the 3D printing of hydrogel scaffolds. The hydrogel’s physicochemical properties and drug release profiles from the hydrogel specimens to the external solution have been determined at two temperatures (20 and 37 °C). The release test showed a sustained OCT delivery into ultrapure water and the PBS solution. The temperature-responsive hydrogel exhibited antimicrobial activity against Staphylococcus aureus, Candida albicans, and Pseudomonas aeruginosa and demonstrated non-cytotoxicity towards fibroblasts. The thermoresponsive behavior along with biocompatibility, antimicrobial activity, and controlled drug release make this hydrogel a promising class of materials for wound dressing applications. Full article

Normal wound healing progresses through inflammatory, proliferative and remodeling phases in response to tissue injury. Collagen, a key component of the extracellular matrix, plays critical roles in the regulation of the phases of wound healing either in its native, fibrillar conformation or as soluble components in the wound milieu. Impairments in any of these phases stall the wound in a chronic, non-healing state that typically requires some form of intervention to guide the process back to completion. Key factors in the hostile environment of a chronic wound are persistent inflammation, increased destruction of ECM components caused by elevated metalloproteinases and other enzymes and improper activation of soluble mediators of the wound healing process. Collagen, being central in the regulation of several of these processes, has been utilized as an adjunct wound therapy to promote healing. In this work the significance of collagen in different biological processes relevant to wound healing are reviewed and a summary of the current literature on the use of collagen-based products in wound care is provided. Full article

After the initiation of the current outbreak, humans’ lives have been profoundly impacted by COVID-19. During the first months, no rapid and reliable detecting tool was readily available to sufficiently respond to the requirement of massive testing. In this situation, when the development of an effective vaccine requires at least a few months, it is crucial to be prepared by developing and commercializing affordable, accurate, rapid and adaptable biosensors not only to fight Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) but also to be armed to avoid the pandemic in the earliest stages in the future. The COVID-19 diagnostic tools are categorized into two main groups of Nucleic Acid (NA)-based and protein-based tests. To date, nucleic acid-based detection has been announced as the gold-standard strategy for coronavirus detection; however, protein-based tests are promising alternatives for rapid and large-scale screening of susceptible groups. In this review, we discuss the current protein-based biosensing tools, the research advances and the potential protein-detecting strategies for COVID-19 detection. This narrative review aims to highlight the importance of the diagnostic tests, encourage the academic research groups and the companies to eliminate the shortcomings of the current techniques and step forward to mass-producing reliable point-of-care (POC) and point-of-need (PON) adaptable diagnostic tools for large-scale screening in the future outbreaks. Full article

The novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused respiratory infection, resulting in more than two million deaths globally and hospitalizing thousands of people by March 2021. A considerable percentage of the SARS-CoV-2 positive patients are asymptomatic or pre-symptomatic carriers, facilitating the viral spread in the community by their social activities. Hence, it is critical to have access to commercialized diagnostic tests to detect the infection in the earliest stages, monitor the disease, and follow up the patients. Various technologies have been proposed to develop more promising assays and move toward the mass production of fast, reliable, cost-effective, and portable PoC diagnostic tests for COVID-19 detection. Not only COVID-19 but also many other pathogens will be able to spread and attach to human bodies in the future. These technologies enable the fast identification of high-risk individuals during future hazards to support the public in such outbreaks. This paper provides a comprehensive review of current technologies, the progress in the development of molecular diagnostic tests, and the potential strategies to facilitate innovative developments in unprecedented pandemics. Full article

Protein/peptide-based hydrogel biomaterial inks with the ability to incorporate various cells and mimic the extracellular matrix’s function are promising candidates for 3D printing and biomaterials engineering. This is because proteins contain multiple functional groups as reactive sites for enzymatic, chemical modification or physical gelation or cross-linking, which is essential for the filament formation and printing processes in general. The primary mechanism in the protein gelation process is the unfolding of its native structure and its aggregation into a gel network. This network is then stabilized through both noncovalent and covalent cross-link. Diverse proteins and polypeptides can be obtained from humans, animals, or plants or can be synthetically engineered. In this review, we describe the major proteins that have been used for 3D printing, highlight their physicochemical properties in relation to 3D printing and their various tissue engineering application are discussed. Full article

Collagen is a key component of the extracellular matrix (ECM) in organs and tissues throughout the body and is used for many tissue engineering applications. Electrospinning of collagen can produce scaffolds in a wide variety of shapes, fiber diameters and porosities to match that of the native ECM. This systematic review aims to pool data from available manuscripts on electrospun collagen and tissue engineering to provide insight into the connection between source material, solvent, crosslinking method and functional outcomes. D-banding was most often observed in electrospun collagen formed using collagen type I isolated from calfskin, often isolated within the laboratory, with short solution solubilization times. All physical and chemical methods of crosslinking utilized imparted resistance to degradation and increased strength. Cytotoxicity was observed at high concentrations of crosslinking agents and when abbreviated rinsing protocols were utilized. Collagen and collagen-based scaffolds were capable of forming engineered tissues in vitro and in vivo with high similarity to the native structures. Full article

While Deep Neural Networks (DNNs) and Transfer Learning (TL) have greatly contributed to several medical and clinical disciplines, the application to multivariate physiological datasets is still limited. Current examples mainly focus on one physiological signal and can only utilise applications that are customised for that specific measure, thus it limits the possibility of transferring the trained DNN to other domains. In this study, we composed a dataset ($n=813$) of six different types of physiological signals (Electrocardiogram, Electrodermal activity, Electromyogram, Photoplethysmogram, Respiration and Acceleration). Signals were collected from 232 subjects using four different acquisition devices. We used a DNN to classify the type of physiological signal and to demonstrate how the TL approach allows the exploitation of the efficiency of DNNs in other domains. After the DNN was trained to optimally classify the type of signal, the features that were automatically extracted by the DNN were used to classify the type of device used for the acquisition using a Support Vector Machine. The dataset, the code and the trained parameters of the DNN are made publicly available to encourage the adoption of DNN and TL in applications with multivariate physiological signals. Full article

In recent years, biopolymers have been attracting the attention of researchers and specialists from different fields, including biotechnology, material science, engineering, and medicine. The reason is the possibility of combining sustainability with scientific and technological progress. This is an extremely broad research topic, and a distinction has to be made among different classes and types of biopolymers. Polyhydroxyalkanoate (PHA) is a particular family of polyesters, synthetized by microorganisms under unbalanced growth conditions, making them both bio-based and biodegradable polymers with a thermoplastic behavior. Recently, PHAs were used more intensively in biomedical applications because of their tunable mechanical properties, cytocompatibility, adhesion for cells, and controllable biodegradability. Similarly, the 3D-printing technologies show increasing potential in this particular field of application, due to their advantages in tailor-made design, rapid prototyping, and manufacturing of complex structures. In this review, first, the synthesis and the production of PHAs are described, and different production techniques of medical implants are compared. Then, an overview is given on the most recent and relevant medical applications of PHA for drug delivery, vessel stenting, and tissue engineering. A special focus is reserved for the innovations brought by the introduction of additive manufacturing in this field, as compared to the traditional techniques. All of these advances are expected to have important scientific and commercial applications in the near future. Full article

Neurodegenerative diseases (NDDs) are incurable and debilitating conditions that result in progressive degeneration and/or death of nerve cells in the central nervous system (CNS). Identification of viable therapeutic targets and new treatments for CNS disorders and in particular, for NDDs is a major challenge in the field of drug discovery. These difficulties can be attributed to the diversity of cells involved, extreme complexity of the neural circuits, the limited capacity for tissue regeneration, and our incomplete understanding of the underlying pathological processes. Drug discovery is a complex and multidisciplinary process. The screening attrition rate in current drug discovery protocols mean that only one viable drug may arise from millions of screened compounds resulting in the need to improve discovery technologies and protocols to address the multiple causes of attrition. This has identified the need to screen larger libraries where the use of efficient high-throughput screening (HTS) becomes key in the discovery process. HTS can investigate hundreds of thousands of compounds per day. However, if fewer compounds could be screened without compromising the probability of success, the cost and time would be largely reduced. To that end, recent advances in computer-aided design, in silico libraries, and molecular docking software combined with the upscaling of cell-based platforms have evolved to improve screening efficiency with higher predictability and clinical applicability. We review, here, the increasing role of HTS in contemporary drug discovery processes, in particular for NDDs, and evaluate the criteria underlying its successful application. We also discuss the requirement of HTS for novel NDD therapies and examine the major current challenges in validating new drug targets and developing new treatments for NDDs. Full article

The most prevalent form of bioprinting—extrusion bioprinting—can generate structures from a diverse range of materials and viscosities. It can create personalized tissues that aid in drug testing and cancer research when used in combination with natural bioinks. This paper reviews natural bioinks and their properties and functions in hard and soft tissue engineering applications. It discusses agarose, alginate, cellulose, chitosan, collagen, decellularized extracellular matrix, dextran, fibrin, gelatin, gellan gum, hyaluronic acid, Matrigel, and silk. Multi-component bioinks are considered as a way to address the shortfalls of individual biomaterials. The mechanical, rheological, and cross-linking properties along with the cytocompatibility, cell viability, and printability of the bioinks are detailed as well. Future avenues for research into natural bioinks are then presented. Full article

The coronavirus disease 19 (COVID-19) pandemic is having a dramatic impact on society and healthcare systems. In this complex scenario, lung computerized tomography (CT) may play an important prognostic role. However, datasets released so far present limitations that hamper the development of tools for quantitative analysis. In this paper, we present an open-source lung CT dataset comprising information on 50 COVID-19-positive patients. The CT volumes are provided along with (i) an automatic threshold-based annotation obtained with a Gaussian mixture model (GMM) and (ii) a scoring provided by an expert radiologist. This score was found to significantly correlate with the presence of ground glass opacities and the consolidation found with GMM. The dataset is freely available in an ITK-based file format under the CC BY-NC 4.0 license. The code for GMM fitting is publicly available, as well. We believe that our dataset will provide a unique opportunity for researchers working in the field of medical image analysis, and hope that its release will lay the foundations for the successfully implementation of algorithms to support clinicians in facing the COVID-19 pandemic. Full article

Clustered regularly interspaced short palindromic repeat (CRISPR/Cas) proteins can be designed to bind specified DNA and RNA sequences and hold great promise for the accurate detection of nucleic acids for diagnostics. We integrated commercially available reagents into a CRISPR/Cas9-based lateral flow assay that can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences with single-base specificity. This approach requires minimal equipment and represents a simplified platform for field-based deployment. We also developed a rapid, multiplex fluorescence CRISPR/Cas9 nuclease cleavage assay capable of detecting and differentiating SARS-CoV-2, influenza A and B, and respiratory syncytial virus in a single reaction. Our findings provide proof-of-principle for CRISPR/Cas9 point-of-care diagnosis as well as a scalable fluorescent platform for identifying respiratory viral pathogens with overlapping symptomology. Full article

Engineered in vitro models of skeletal muscle are essential for efficiently screening drug safety and efficacy. However, conventional culture substrates poorly replicate physical features of native muscle and do not support long-term culture, which limits tissue maturity. Micromolded gelatin hydrogels cross-linked with microbial transglutaminase (gelatin-MTG hydrogels) have previously been shown to induce C21C2 myotube alignment and improve culture longevity. However, several properties of gelatin-MTG hydrogels have not been systematically characterized, such as changes in elastic modulus during incubation in culture-like conditions and their ability to support sarcomere maturation. In this study, various gelatin-MTG hydrogels were fabricated and incubated in ambient or culture-like conditions. Elastic modulus, mass, and transmittance were measured over a one- or two-week period. Compared to hydrogels in phosphate buffered saline (PBS) or ambient air, hydrogels in Dulbecco’s Modified Eagle Medium (DMEM) and 5% CO₂ demonstrated the most stable elastic modulus. A subset of gelatin-MTG hydrogels was micromolded and seeded with C2C12 or primary chick myoblasts, which aligned and fused into multinucleated myotubes with relatively mature sarcomeres. These data are important for fabricating gelatin-MTG hydrogels with predictable and stable mechanical properties and highlight their advantages as culture substrates for engineering relatively mature and stable muscle tissues. Full article

Since their first synthesis in the late 1960s, collagen mimetic peptides (CMPs) have been used as a molecular tool to study collagen, and as an approach to develop novel collagen mimetic biomaterials. Collagen, a major extracellular matrix (ECM) protein, plays vital roles in many physiological and pathogenic processes. Applications of CMPs have advanced our understanding of the structure and molecular properties of a collagen triple helix—the building block of collagen—and the interactions of collagen with important molecular ligands. The accumulating knowledge is also paving the way for developing novel CMPs for biomedical applications. Indeed, for the past 50 years, CMP research has been a fast-growing, far-reaching interdisciplinary field. The major development and achievement of CMPs were documented in a few detailed reviews around 2010. Here, we provided a brief overview of what we have learned about CMPs—their potential and their limitations. We focused on more recent developments in producing heterotrimeric CMPs, and CMPs that can form collagen-like higher order molecular assemblies. We also expanded the traditional view of CMPs to include larger designed peptides produced using recombinant systems. Studies using recombinant peptides have provided new insights on collagens and promoted progress in the development of collagen mimetic fibrillar self-assemblies. Full article