Search Results (5,346)

Early chronic pancreatitis (ECP) represents a potentially reversible stage in the natural history of chronic pancreatic disease. Timely diagnosis of ECP offers a possibility for intervention, yet its diagnosis remains challenging due to nonspecific symptoms, lack of standardized criteria, and the limited diagnostic sensitivity of conventional tools. This review aims to synthesize recent advancements in the understanding, detection, and management of ECP, with a focus on innovation in imaging techniques and biomarker profiling. The goal is to facilitate earlier diagnosis and more effective patient stratification. We reviewed the literature from the past five years, including original studies, meta-analyses, and expert consensus statements, to address the current evidence across genetic, inflammatory, imaging, and biochemical domains relevant to ECP. Endoscopic ultrasound and advanced magnetic resonance techniques offer high sensitivity in detecting early parenchymal changes, although inter-observer variability and lack of standardization persist. Biomarker discovery has focused on inflammatory (IL-6, sCD163), fibrotic (TGF-β1, TIMP-1), and oxidative markers, as well as novel candidates like microRNAs. Genetic predisposition (PRSS1, SPINK1, CTRC, CPA1, CLDN2) significantly influences disease onset and progression and could enable selection of high-risk individuals. Therefore, diagnosing ECP should involve a multidisciplinary precision-based approach integrating clinical, radiologic, molecular, serologic, and genetic data for individualized risk stratification. Full article

Schizophrenia is a prevailing yet severely debilitating psychiatric disorder characterized by a convoluted etiology. Although antipsychotics have been available for over half a century, they primarily mitigate symptoms rather than providing definitive care. This limitation suggests that the neurotransmitter systems targeted by these medications are not the root cause of the disorder. Ongoing research seeks to elucidate the cellular, molecular, and circuitry pathways that contribute to the development of schizophrenia. Unfortunately, its precise pathogenesis remains incompletely understood. Accumulating evidence implicates dysregulated neurogenesis and aberrant neurodevelopmental processes as key contributors to disease progression. Recent advances in proteomics and imaging technology have facilitated the emergence of novel models of schizophrenia, emphasizing the roles of neuroinflammation, sex steroids, and cortisol. This paper aims to organize and map the intercorrelations and potential causal effects between various mechanistic models to gain deeper insight on how these mechanisms contribute to the cause, risks, and symptoms of the disorder. Furthermore, we discuss the potential therapeutic strategies that target these pathological pathways. Elucidating these mechanisms may ultimately advance our understanding of schizophrenia’s etiological foundations and guide the development of curative interventions. Full article

Jets and outflows are key components of low-mass star formation, regulating accretion and shaping the surrounding molecular clouds. These flows, traced by molecular species at (sub)millimeter wavelengths (e.g., CO, SiO, SO, H₂CO, and CH₃OH) and by atomic, ionized, and molecular lines in the infrared (e.g., H₂, [Fe II], [S I]), originate from protostellar accretion disks deeply embedded within dusty envelopes. Jets play a crucial role in removing angular momentum from the disk, thereby enabling continued mass accretion, while directly preserving a record of the protostar’s outflow history and potentially providing indirect insights into its accretion history. Recent advances in high-resolution, high-sensitivity observations, particularly with the James Webb Space Telescope (JWST) in the infrared and the Atacama Large Millimeter/submillimeter Array (ALMA) at (sub)millimeter wavelengths, have revolutionized studies of protostellar jets and outflows. These instruments provide complementary views of warm, shock-excited gas and cold molecular component of the jet–outflow system. In this review, we discuss the current status of observational studies that reveal detailed structures, kinematics, and chemical compositions of protostellar jets and outflows. Recent analyses of mass-loss rates, velocities, rotation, molecular abundances, and magnetic fields provide critical insights into jet launching mechanisms, disk evolution, and the potential formation of binary systems and planets. The synergy of JWST’s infrared sensitivity and ALMA’s high-resolution imaging is advancing our understanding of jets and outflows. Future large-scale, high-resolution surveys with these facilities are expected to drive major breakthroughs in outflow research. Full article

Background/Objectives: Bladder cancer is characterized by high recurrence and progression rates, posing a challenge to current diagnostic and treatment strategies. This review aims to provide a comprehensive overview of emerging technologies, including novel PET tracers, AI-assisted cystoscopy, theragnostics, and molecular biomarkers. Methods: We performed a narrative review of the recent literature focusing on innovations in imaging, AI, theragnostics, and biomarker research relevant to bladder cancer diagnosis and management. Results: Several novel PET tracers, such as 68Ga-PSMA and fibroblast activation protein inhibitor (FAPI), demonstrated potential in improving detection sensitivity. AI-enhanced cystoscopy has shown promise in real-time lesion detection, while theragnostic agents enable combined diagnostic and therapeutic applications. Advances in molecular biomarkers, including circulating Tumor DNA (ctDNA) and gene expression signatures, offer new avenues for patient stratification and monitoring. Conclusions: Integration of advanced imaging, AI, theragnostics, and biomarker analysis may transform bladder cancer management, supporting personalized and more effective care strategies. Full article

Mesoporous silica nanoparticles have been synthesized through sol–gel synthesis in basic conditions. Gemini surfactants having urea in the headgroups were used as pore-forming agents. The effect of the spacer length of the surfactant on the particle morphology was studied on the sub-micrometer and nanometer scales using nitrogen porosimetry, small-angle X-ray scattering (SAXS), ultra-small-angle neutron scattering, and scanning and transmission electron microscopy (SEM, TEM). Depending on the spacer, spherical and/or cylindrical nanoparticles formed in different proportions, as revealed by statistical analysis of SEM micrographs. All prepared materials showed the hexagonal pore structure characteristic of the MCM-41 molecular sieves, with the exception of the sample prepared using the gemini surfactant with the shortest spacer length. The influence of the spacer length on the lattice parameter of the pore network, as well as the average size of the ordered domains, has been assessed by SAXS and TEM. Detailed analysis of the TEM images revealed a spread of the lattice parameter in a range of 10–20%. The broadening of the diffraction peaks was shown to be due to the combination of the effects of the finite domain size and the variance of the lattice parameter across the crystalline domains. The structural differences between the silica gels synthesized with the different surfactants were related to the variation of the micelle morphologies, reported in previous light scattering and small-angle scattering experiments. No connection could be revealed between the micelle shape and size and the pore sizes, showing that surfactants with a broad range of spacer lengths can equally well be used for the preparation of MCM-41 materials. Full article

Neuroaxonal damage underlies permanent disability in various neurological conditions, both neuroautoimmune and neurodegenerative. It is crucial to accurately quantify and monitor axonal injury using biomarkers to evaluate disease progression and treatment effectiveness and offer prognostic insights. Neurofilaments (NFs), and especially neurofilament light chain (NfL), show promise for this purpose, as their levels increase with neuroaxonal damage in both cerebrospinal fluid and blood, independent of specific causal pathways. Recent advances in ultrasensitive immunoassays enable the reliable detection of NFs in blood, transforming them from research tools into clinically applicable measures. In multiple sclerosis (MS), serum NfL correlates with disease activity, treatment response, and long-term disability, and may complement MRI in monitoring subclinical progression. In MS, NfL is primarily emerging as a marker of disease activity and treatment response; in amyotrophic lateral sclerosis (ALS), it has progressed further, being integrated into clinical trials as a pharmacodynamic endpoint and considered by regulatory agencies as a drug development tool. Additionally, NFs are increasingly being investigated in Alzheimer’s disease, frontotemporal dementia, and other neurodegenerative disorders, though their disease specificity is limited. Ongoing challenges include older and novel assay harmonization, normative range interpretation, biological and analytical variability, and integration with other molecular and imaging biomarkers. This critical narrative review synthesizes the existing literature on NFs as diagnostic, prognostic, predictive, and pharmacodynamic biomarkers and discusses their role in therapeutic development and precision medicine in neuroautoimmune and neurodegenerative diseases. Full article

Background: Immune checkpoint inhibitors (ICIs) are effective against various advanced and metastatic cancers, but patient responses vary and can change over time, complicating treatment prediction. Therefore, better tools for patient stratification, response prediction, and response assessment are needed. This study presents the development and clinical translation of a fluorescently labelled ICI tracer pair used to perform multispectral fluorescent molecular imaging and simultaneously gain spatial and temporal insight in both programmed death ligand 1 (PD-L1) and programmed death receptor 1 (PD-1) expression. Methods: We conjugated the anti-PD-L1 antibody durvalumab to IRDye 680LT and the anti-PD-1 antibody nivolumab to IRDye 800CW. Tracers were developed and optimized for conjugation efficiency and purity to allow use in clinical trials. Stability was tested up to 12 months. An extended single-dose toxicity study in mice was performed for durvalumab-680LT and the unconjugated IRDye 680LT to demonstrate safety for first-in-human administration. Results: Durvalumab-680LT and nivolumab-800CW were successfully conjugated and purified. Conjugation optimization resulted in a robust production with labelling efficiencies of ≥88%. Long-term stability study of both tracers showed all parameters within end of shelf-life specifications for at least 12 months at 2–8 °C. No toxic effects were observed in doses up to 1000x the intended human dose for both IRDye 680LT and durvalumab-680LT, which are therefore considered safe for first-in-human use. Conclusions: We succeeded in the development and clinical translation of two novel fluorescent ICI tracers, durvalumab-680LT and nivolumab-800CW. Moreover, we demonstrated for the first time the safety of IRDye 680LT and durvalumab-680LT, enabling first-in-human use. Together, this makes durvalumab-680LT and nivolumab-800CW suitable for phase I/II clinical trials. Full article

Nanomaterials are increasingly used in the development of detection systems for various disease biomarkers as tools for reliable early diagnosis, which is a key factor in reducing mortality and increasing treatment effectiveness. The use of quantum dot–antibody conjugates allows for optical detection of various disease markers in biological fluids, tissues, and individual cells with high sensitivity and specificity. The sensitivity and specificity of detection are determined not only by the outstanding optical properties of fluorescent quantum dots but also by the type of antibodies used for binding target analytes and the methods of their conjugation with quantum dots. This review deals with methods of site-specific and site-nonspecific conjugation of quantum dots with antibodies, including full-length and single-domain antibodies, as well as antibody fragments, with a special focus on their structural features and active moieties used for binding to their targets. The review includes examples of successful applications of quantum dot–conjugated antibodies in diagnosis, environment monitoring, and food safety assessment. We also discuss the prospects of further research in this field, including new conjugation methods and issues related to the stability and specificity of probes. The review provides a comprehensive analysis of the current methods and achievements in antibody conjugation from the viewpoint of subsequent analyte detection, highlighting the importance of further research for improving the existing technologies. Full article

Arrhythmogenic cardiomyopathy (ACM; MIM #107970) is a primitive heart muscle disease characterized by progressive myocardial loss and fibrosis or fibrofatty replacement, predisposing patients to ventricular arrhythmias, sudden cardiac death, and heart failure. Despite advances in imaging and genetics, early diagnosis remains challenging due to incomplete penetrance, variable phenotypic expressivity, and the fact that fatal arrhythmic events may often occur in the early stages of the disease. In this context, the identification of reliable biomarkers could enhance diagnostic accuracy, support risk stratification, and guide clinical management. This narrative review examines the current landscape of potential and emerging biomarkers in ACM, including troponins, natriuretic peptides, inflammatory proteins, microRNAs, fibrosis-related markers, and other molecules. Several of these biomarkers have demonstrated associations with disease severity, arrhythmic burden, or structural progression, although their routine clinical utility remains limited. The increasing relevance of genetic testing and non-invasive tissue characterization—particularly through cardiac imaging techniques—should also be emphasized as part of a multimodal diagnostic strategy in which biomarkers may play a complementary role. Although no single biomarker currently meets the criteria for a standalone diagnostic application, ongoing research into multi-marker panels and novel molecular targets offers promising perspectives. In conclusion, the integration of circulating biomarkers with imaging findings, genetic data, and clinical parameters may open new avenues for improving early detection and supporting personalized therapeutic strategies in patients with suspected ACM. Full article

Background/Objectives: Breast cancer (BC) is the most commonly diagnosed cancer in women and the leading cause of cancer-related deaths globally. Molecular subtyping is crucial for prognosis and treatment planning, with immunohistochemistry (IHC) being the most commonly used method. However, IHC has limitations, including observer variability, a lack of standardization, and a lack of reproducibility. Gene expression profiling is considered the ground truth for molecular subtyping; unfortunately, this is expensive and inaccessible to many institutions. This study investigates the potential of an artificial intelligence (AI) model to predict BC molecular subtypes directly from hematoxylin and eosin (H&E)-stained whole-slide images (WSIs). Methods: A pretrained deep learning framework based on multiple-instance learning (MIL) was validated on the Stavanger Breast Cancer (SBC) dataset, consisting of 538 BC cases. Three classification tasks were assessed, including two-class [triple negative BC (TNBC) vs. non-TNBC], three-class (luminal vs. HER2-positive vs. TNBC), and four-class (luminal A vs. luminal B vs. HER2-positive vs. TNBC) groups. Performance metrics were used for the evaluation of the AI model. Results: The AI model demonstrated strong performance in distinguishing TNBC from non-TNBC (AUC = 0.823, accuracy = 0.833, F1-score = 0.824). However, performance declined with an increasing number of classes. Conclusions: The study highlights the potential of AI in BC molecular subtyping from H&E WSIs, offering an easily applicable and standardized method to IHC. Future improvements should focus on optimizing multi-class classification and validating AI-based methods against gene expression analyses for enhanced clinical applicability. Full article

This study, motivated by the pronounced fluid loss characteristics of water-based fracturing fluids, developed a fluid–solid coupling model to investigate water-based fracturing in geological reservoirs. The model was further employed to analyse the effects of multiple factors on fracture propagation and the seepage capacity of water-based fracturing fluids. Moreover, the underlying mechanisms of fracture propagation and seepage enhancement were elucidated from a microscopic molecular perspective. The results obtained that the high apparent viscosity of water-based fracturing fluids not only enhances the fracturing efficiency of reservoir rocks but also results in a reduced seepage volume (−17 mL) in low-permeability reservoirs. Furthermore, the reservoir porosity (+2.5%) exhibits a clear inverse proportional relationship with fracturing efficiency (−0.9 m), while the seepage volume (+7 mL) of water-based fracturing fluids continues to increase. The strength and quantity of hydrogen bonds between molecules in water-based fracturing fluid, influenced by external factors, directly affect fluid seepage. The seepage behaviour of water-based fracturing fluids in geological reservoirs, together with the influence of reservoir conditions on fracture propagation, provides valuable reference data for rock fracturing and reservoir stimulation. However, the absence of data analysis and microscopic images of microscopic molecular dynamics constitutes a challenging problem that demands attention. Full article

Senescence is a dynamic, multifaceted process implicated in tissue aging, organ dysfunction, and intricately associated with numerous chronic diseases. As senescent cells accumulate, they drive inflammation, fibrosis, and metabolic disruption through the senescence-associated secretory phenotype (SASP). Despite its clinical relevance, senescence remains challenging to detect non-invasively due to its heterogeneous nature and the lack of universal biomarkers. Recent advances in the development of specific imaging probes for positron emission tomography (PET) enable in vivo visualization of senescence-associated pathways across key organs, such as the lung, heart, kidney, and metabolic processes. For instance, [¹⁸F]FPyGal, a β-galactosidase-targeted tracer, has demonstrated selective accumulation in senescent cells in both preclinical and early clinical studies, while FAP-targeted radioligands are emerging as tools for imaging fibrotic remodeling in the lung, liver, kidney, and myocardium. This review examines a new generation of PET radioligands targeting hallmark features of senescence, with the potential to track and measure the process, the ability to be translated into clinical interventions for early diagnosis, and longitudinal monitoring of senescence-driven pathologies. By integrating organ-specific imaging biomarkers with molecular insights, PET probes are poised to transform our ability to manage and treat age-related diseases through personalized approaches. Full article

Background: Primary spinal gliomas are rare in the pediatric population. Separately, FGFR1 genomic aberrations are also uncommon in spinal cord tumors. We report a case of a previously well adolescent who presented with progressive symptoms secondary to an intramedullary tumor with unique radiological and molecular characteristics. Case Presentation: A previously well 17-year-old male presented with worsening mid-back pain associated with lower limb long-tract signs. Magnetic resonance imaging (MRI) of his neuro-axis reported a long-segment intramedullary lesion with enhancing foci and a multi-septate syrinx containing hemorrhagic components from C4 to T12. The largest enhancement focus was centered at T7. Additional MRI sequences observed no intracranial involvement or vascular anomaly. He underwent an emergent laminoplasty and excision of the thoracic lesion. Intraoperative findings demonstrated a soft, grayish intramedullary tumor associated with extensive hematomyelia that had multiple septations. Active fenestration of the latter revealed blood products in various stages of resolution. Postoperatively, the patient recovered well, with neurological improvement. Final histology reported a circumscribed low-grade glial neoplasm. Further molecular interrogation via next-generation sequencing panels showed FGFR1 p.K656E and V561M alterations. The unique features of this case are presented and discussed in corroboration with a focused literature review. Conclusions: We highlight an interesting case of an intramedullary tumor with unusual radiological and pathological findings. Emphasis is on the importance of tissue sampling in corroboration with genomic investigations to guide clinical management. Full article

The accurate classification of pancreatic cystic lesions remains clinically challenging due to overlapping imaging features and variable malignant potential. Mucinous cystic neoplasms, in particular, require early identification given their premalignant nature. RNA profiling presents a promising alternative to current diagnostic limitations—a molecular lens sharpened by AI-driven pattern recognition. This study aimed to evaluate the diagnostic potential of RNA signatures for differentiating pancreatic cyst subtypes and to clarify their roles in their pathophysiology. The study included 31 patients with pancreatic lesions who underwent endoscopic ultrasound-guided fine-needle aspiration. RNA was extracted from cyst fluid, tissue, and peripheral blood. Expression of 17 target genes was analyzed using qPCR. Gene expression patterns were compared across mucinous cystic neoplasms, serous cystic neoplasms, pseudocysts, adenocarcinoma, and chronic pancreatitis cohorts. Diagnostic accuracy was evaluated via ROC analysis. Mucinous cysts exhibited significant overexpression of MUC1, ITGA2, ELOVL6, and MUC5AC genes compared to serous cysts and pseudocysts. PKM gene expression correlated with increasing malignant potential. In blood plasma, only MUC1, MUC4, and PYGL were elevated in adenocarcinoma compared to mucinous neoplasms. We identified a distinct RNA signature that can distinguish mucinous cystic neoplasms from benign cystic lesions (serous cysts and pseudocysts), which could be useful for guiding patient management and improving clinical outcomes. Validation in broader cohorts is essential for clinical implementation. Full article