Search Results (8,512)

Expanding the capacity of Matrix-Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) beyond species identification to strain typing becomes a new challenge in clinical microbiology. This study demonstrated a specific identification of Streptococcus agalactiae sequence type 1 (ST1) by a manual decision tree and automatically ranking from the newly added MTPPs library, which has not been previously reported. The mass spectra of 25 STs (277 isolates) were generated. The presence and absence of specific peaks were combined to create a decision tree for manual identification. Three peaks at 3127, 5914, and 6252 in combination with m/z 3368 and 6281 were used for primary identification of ST1. However, to differentiate ST1 and ST314, five additional peaks were required. For the automatic system, the MTPP of all isolates was divided into three training–testing ratios of 40:60, 50:50, and 60:40. All categories revealed excellent accuracy rates of above 90% for ST1 identification. The 60:40 group showed the highest overall performance, in which sensitivity was observed at 83.9 to 96.8%, and specificity reached up to 100.0% for both the top two and the top three matches. In conclusion, we propose that the MTPP from MALDI-TOF is a potential model for speedy bacterial typing, crucial in epidemiology, prevention, and patient management. Full article

This literature review examines the relationship between the number and type of deficiencies identified during Port State Control (PSC) inspections and a ship’s overall risk. The main objective is to synthesise the current academic evidence, detailing the analytical methodologies employed and highlighting key research contributions. The selection of literature has focused on peer-reviewed articles and relevant doctoral theses addressing detention risk prediction, accident risk and ship risk profiling. The findings indicate a consistent correlation between PSC deficiencies and ship risk, although the nature and strength of this correlation may vary depending on the type of risk considered and the specific deficiencies. A methodological evolution is observed in the field, from descriptive statistical analyses and regressions towards more complex predictive models, such as Machine Learning (ML) and Bayesian Networks (BNs). This transition reflects a search for greater accuracy in risk assessment, going beyond simple numerical correlation to improve the selection of ships for inspection. Multivariate statistical techniques, on the other hand, focus on the identification of risk patterns and the evaluation of the PSC system. The conclusions underline the importance of deficiencies as indicators of risk, the need for differentiated inspection approaches and the persistent challenges related to data quality and model interpretability. Full article

The palo prieto (Lysiloma divaricata) is a tree with grayish bark and pinnate leaves that is native to Mexico. This tree can reach heights close to 15 m and is a source of phytochemical compounds, including polyphenols. The optimized extraction method is important for preserving phytochemical compounds, particularly gallic acid. In general, solid-liquid extraction methods are the most commonly used methods for obtaining phytochemical compounds from Lysiloma divaricata. Herein, we report the results of a complex experimental design in which different parts of the plant (leaf, stem, and fruit) were used to investigate their antioxidant activities and gallic acid contents. In this design, we included variations in the type of solvent, time, and temperature. This method yields an extract rich in phytochemical components that may exhibit significant antioxidant activity, making it suitable for isolating natural antioxidant compounds. For these compounds, bromatological analysis, quantification of phenolic content, and identification and quantification of phytochemical compounds via UPLC-MS/MS identified 27 compounds, with gallic epicatechin, catechin, kaemferol-3-glucoside, procyanidin B1, and gallic acid as the major compounds. For the quantification of gallic acid by HPLC, the highest concentration of gallic acid was detected in the water-leaf-40 °C-90 min fraction. In addition, antioxidant activity via 1,1-diphenyl-1,2-picrylhydrazyl (DPPH), 2,2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and ferric reducing antioxidant power (FRAP) was studied, and color measurements were performed. Additionally, the antioxidant activity of the fruit samples was evaluated via the DPPH method with an ethanol/water ratio of 30:70 % v/v at 60 °C for 60 min, which resulted in the highest percentage of inhibition. There was no significant difference in the antioxidant activity when ABTS was used between the samples. For the antioxidant activity determined via FRAP, the leaf sample exhibited the most significant activity when ethanol was used as the solvent at 50 °C for 90 min, with a value of 195,861 ± 44.20 µM eq Trolox/g DM. The phenol compounds of Lysiloma divaricata are promising sources of natural antimicrobials and antioxidants for potential applications in food packaging. Full article

The 2 × 25 kV flexible traction power supply system (FTPSS), using a three-phase-single-phase converter as its power source, effectively addresses the challenges of neutral section transitions and power quality issues inherent in traditional power supply systems (TPSSs). However, the bidirectional fault current and low short-circuit current characteristics degrade the effectiveness of traditional TPSS protection schemes. This paper analyzes the fault characteristics of FTPSS and proposes a fault identification method based on empirical wavelet transform (EWT) and 1-sequence faulty energy. First, a composite sequence network model is developed to reveal the characteristics of three typical fault types, including ground faults and inter-line short circuits. The 1-sequence differential faulty energy is then calculated. Since the 1-sequence component is unaffected by the leakage impedance of autotransformers (ATs), the proposed method uses this feature to distinguish the TPSS faults from disturbances caused by electric multiple units (EMUs). Second, EWT is used to decompose the 1-sequence faulty energy, and relevant components are selected by permutation entropy. The fault variance derived from these components enables reliable identification of TPSS faults, effectively avoiding misjudgment caused by AT excitation inrush or harmonic disturbances from EMUs. Finally, real-time digital simulator experimental results verify the effectiveness of the proposed method. The fault identification method possesses high tolerance to transition impedance performance and does not require synchronized current measurements from both sides of the TPSS. Full article

Sea–rail intermodal transport offers high efficiency and environmental benefits, yet its development in China remains limited. Existing studies have mainly assessed the macro-level benefits of sea–rail intermodal transport policies, but rigorous evidence on whether incentive policies work and how their effects differ across policy types remains scarce, which limits evidence-based policy design and efficient allocation between subsidies and capacity expansion. To address this gap, a dual-policy identification framework was established that combines a multi-period difference-in-differences model with event study analysis and used station–month data from China to assess the independent effects, underlying mechanisms, and spatiotemporal heterogeneity of railway freight price subsidies and freight train expansion on container throughput. The results indicate that both policies significantly increased container throughput. Railway freight price subsidies exhibited stronger and more persistent effects with a certain lag, whereas freight train expansion produced rapid but short-lived responses. The impacts of both policies were more pronounced in short-distance transport, but weakened or even turned negative over longer distances. Moreover, the number of participating entities served as a key mediating pathway, while information sharing positively moderates policy impacts. This study makes theoretical contributions to the identification of heterogeneity, mechanism analysis, and spatiotemporal characterization of SRIT incentive policy effects, while offering refined and actionable guidance for SRIT policy optimization. Full article

Background/Objectives: Glioblastomas are a part of adult-type diffuse gliomas, the most common and most aggressive primary brain tumors in adults (glioblastoma, IDH-wildtype). The identification of the genetic factors associated with glioblastoma could be an important contribution to the diagnosis and early prevention of this disease. We compiled data from the global literature and analyzed clinically relevant variants implicated in glioblastoma risk. Methods: PubMed, Web of Science, and Scopus were used as databases. Associations between the SNPs and glioblastoma risk were calculated as a measure of pooled odds ratios (ORs) and 95% confidence intervals. Pearson’s analysis was used for epidemiological correlation (only p-values less than 0.05 were statistically significant), and data were obtained from the World Health Organization platform and the 1000 Genomes Project. Statistical analysis was performed using Review Manager (RevMan) 5.4 and BioEstat 5.0. Results: CCDC26 rs891835 G/T, G/G, and G/T-G/G genotypes were analyzed and determined to increase glioblastoma risk (G/T OR = 1.96, 95% CI: 1.38–2.77, p = 0.0002, I² = 0%; G/G OR = 1.33, 95% CI: 0.46–3.85, p = 0.60, I² = 0%; G/T − G/G OR = 1.96, 95% CI: 1.39–2.76, p = 0.0001, I² = 0%). Epidemiological correlation also demonstrated that the higher the frequency of the CCDC26 rs891835 variant, the higher the incidence of that variant in the European population. Conclusions: CCDC26 rs891835 may serve as a predictive biomarker for glioblastoma, IDH-wildtype risk and may influence higher glioblastoma incidence rates in the European population. Full article

This study proposes a novel quality control method combining fuzzy logic and threshold discrimination for processing X-band dual-polarization radar data from Beijing. The method effectively eliminates non-precipitation echoes, including electromagnetic interference, clear-air echoes, and ground clutter through five key steps: (1) Identifying electromagnetic interference using continuity of reflectivity across adjacent elevation angles, radial mean correlation coefficient, and differential reflectivity; (2) Preserving precipitation data in ground clutter-mixed regions by jointly utilizing the difference in reflectivity before and after clutter suppression by the signal processor, and characteristic value proportions; (3) Developing a fuzzy logic algorithm with six parameters (e.g., reflectivity texture, depolarization ratio) for ground clutter and clear-air echoes removal; (4) Filtering echoes with missing dual-polarization variables using cross-elevation mean reflectivity, mean correlation coefficient, and valid range bin proportion; (5) Removing residual noise via radial/azimuthal reflectivity continuity analysis. Validation with 635 PPI scans demonstrates high identification accuracy across echo types: 93.5% for electromagnetic interference, 98.4% for ground clutter, 97.7% for clear-air echoes, and 98.2% for precipitation echoes. Full article

The present work aims at completing our previous comprehensive study on Ko-Kutani ware through the analysis, for the first time ever, of the renowned Hakuji bowl (white porcelain shallow bowl) excavated at the Noborigama kiln site in Kaga. The bowl had never been made available for such a purpose prior to this study owing to its absolute rarity, exceptional importance and fragile condition. Its shape and potting techniques, along with its materials, enabled both a direct comparison with the magnificent Ko-Kutani masterpieces belonging to the Ishikawa Prefectural Museum of Art collection and the groundbreaking identification of a definitive firing timeline marked by two distinct production stages: the Pre-Hakuji and Post-Hakuji phases. The crucial influence of the Hakuji bowl on Ko-Kutani production as a whole has been revealed for the first time ever, providing unprecedented and definitive evidence of the origin of the renowned and iconic porcelains. In consideration of the strict requirements and the absolute prohibition to sample or even touch any of the works of art, portable Energy-Dispersive X-Ray Fluorescence spectroscopy (pED-XRF) was selected as the most suitable technique for the type of materials to be investigated. Full article

In this study, a novel pattern recognition method named boosting–partial least squares–discriminant analysis (Boosting-PLS-DA) was developed for the non-destructive and accurate origin identification of food and medicine homologous substances (FMHSs). Taking Gastrodia elata, Aurantii Fructus Immaturus, and Angelica dahurica as examples, spectra of FMHSs from different origins were obtained by portable near-infrared (NIR) spectroscopy without destroying the samples. The identification models were developed with Boosting-PLS-DA, compared with principal component analysis (PCA) and partial least squares–discriminant analysis (PLS-DA) models. The model performances were evaluated using the validation set and an external validation set obtained one month later. The results showed that the Boosting-PLS-DA method can obtain the best results. For the analysis of Aurantii Fructus Immaturus and Angelica dahurica, 100% accuracies of the validation sets and external validation sets were obtained using Boosting-PLS-DA models. For the analysis of Gastrodia elata, Boosting-PLS-DA models showed significant improvements in external validation set accuracies compared to PLS-DA, reducing the risk of overfitting. Boosting-PLS-DA method combines the high robustness of ensemble learning with the strong discriminative capability of discriminant analysis. The generalizability will be further validated with a sufficiently large external validation set and more types of FMHSs. Full article

Background: Periprosthetic joint infection (PJI) is one of the most serious complications following total joint arthroplasty. The debridement, antibiotics, irrigation, and implant retention (DAIR) procedure is commonly employed to treat acute, early-stage infections, but its success is highly variable, influenced by factors such as pathogen virulence and antibiotic susceptibility profiles. This study aimed to evaluate the impact of pathogens responsible for these infections on the outcome of DAIR. Methods: This retrospective, single-center study analyzed the microbiological profiles of 116 patients (66 hips and 50 knees) treated for acute periprosthetic joint infections (PJIs) with DAIR between 2018 and 2022. Acute PJI was defined as a duration of symptom less than three weeks, according to the criteria established by the Tsukayama and Izakovicova classification. Preoperative joint aspirations, intraoperatively collected tissue samples, and sonication of the exchanged mobile parts were analyzed for each case. We differentiated between monomicrobial PJI, polymicrobial PJI (defined as the identification of more than one microorganism from preoperative joint fluid aspiration or intraoperative samples), and difficult-to-treat (DTT) pathogens. Results: In this cohort, the following pathogen profiles were identified: culture-negative cases accounted for 11.1% of infections, while 64.2% were attributed to Gram-positive bacteria, 19.8% to Gram-negative bacteria, and 4.9% to fungal pathogens. Among the identified microorganisms, coagulase-negative staphylococci (CNS) were the most frequently detected, exhibiting a notable oxacillin resistance rate of 52.9% and rifampicin resistance rate of 28.7%. Additionally, no significant difference in revision-free implant survival was found between patients with DTT pathogens and/or polymicrobial PJI and those without such infections. Conclusions: This study highlights that pathogens in prosthetic joint infections (PJIs) do not solely determine outcomes, as patient-specific factors (comorbidities, implant type) may also play a key role. Regional variations in pathogens and antibiotic resistance patterns should guide empirical therapy. For instance, this study found a high reliance on vancomycin due to high oxacillin resistance in CNS, the most frequent causative pathogen. Full article

Enzyme-based biosensors have emerged as a transformative technology, leveraging the specificity and catalytic efficiency of enzymes across various domains, including medical diagnostics, environmental monitoring, food safety, and industrial processes. These biosensors integrate biological recognition elements with advanced transduction mechanisms to provide highly sensitive, selective, and portable solutions for real-time analysis. This review explores the key components, detection mechanisms, applications, and future trends in enzyme-based biosensors. Artificial enzymes, such as nanozymes, play a crucial role in enhancing enzyme-based biosensors by mimicking natural enzyme activity while offering improved stability, cost-effectiveness, and scalability. Their integration can significantly boost sensor performance by increasing the catalytic efficiency and durability. Additionally, lab-on-a-chip and microfluidic devices enable the miniaturization of biosensors, allowing for the development of compact, portable devices that require minimal sample volumes for complex diagnostic tests. The functionality of enzyme-based biosensors is built on three essential components: enzymes as biocatalysts, transducers, and immobilization techniques. Enzymes serve as the biological recognition elements, catalyzing specific reactions with target molecules to produce detectable signals. Transducers, including electrochemical, optical, thermal, and mass-sensitive types, convert these biochemical reactions into measurable outputs. Effective immobilization strategies, such as physical adsorption, covalent bonding, and entrapment, enhance the enzyme stability and reusability, enabling consistent performance. In medical diagnostics, they are widely used for glucose monitoring, cholesterol detection, and biomarker identification. Environmental monitoring benefits from these biosensors by detecting pollutants like pesticides, heavy metals, and nerve agents. The food industry employs them for quality control and contamination monitoring. Their advantages include high sensitivity, rapid response times, cost-effectiveness, and adaptability to field applications. Enzyme-based biosensors face challenges such as enzyme instability, interference from biological matrices, and limited operational lifespans. Addressing these issues involves innovations like the use of synthetic enzymes, advanced immobilization techniques, and the integration of nanomaterials, such as graphene and carbon nanotubes. These advancements enhance the enzyme stability, improve sensitivity, and reduce detection limits, making the technology more robust and scalable. Full article

Q-type C2H2 zinc finger protein (ZFP) transcription factors, a plant-specific subfamily of C2H2 ZFP, have been implicated in regulating abiotic stress responses, growth, and developmental processes in plants. Rapeseed (Brassica napus L.) is a crucial oil crop widely used for the production of high-quality vegetable oil, animal feed, and biodiesel. Compared with studies on Q-type C2H2-ZFP genes in other plant species, systematic research has not been performed in B. napus. In this study, a comprehensive genome-wide analysis of Q-type C2H2-ZFPs in B. napus was conducted. A total of 216 Q-type C2H2-ZFP genes were identified, exhibiting extensive and uneven distribution across the 19 chromosomes. Phylogenetic analysis, based on homologs from Arabidopsis, classified these genes into eight distinct subfamilies, with each containing one to three conserved “QALGGH” motifs. Each subfamily exhibited similar motif compositions and gene structures. Evolutionary studies revealed that segmental duplication events played a crucial role in the expansion of the BnaQ-type C2H2-ZFP gene family. Expression pattern analysis in different tissues and under abiotic stress identified BnaA03g09250D, BnaC09g35160D, BnaC03g11570D, and BnaA10g25850D as candidate genes involved in the response to freezing stress. Overexpression of BnaC09g35160D provided preliminary evidence that it enhances freezing tolerance in plants. This comprehensive study of Q-type C2H2-ZFPs in B. napus will enhance our understanding of the BnaQ-type C2H2-ZFP gene family and provide valuable insights for further functional investigations of BnaC09g35160D. Full article

The use of immune checkpoint inhibitors (ICIs) has increased exponentially in recent years, leading to a significant impact on cancer patient survival. However, their administration can trigger immune-mediated adverse effects, notably pulmonary toxicity, which is a potentially serious complication. ICI-induced pneumonitis has a variable incidence ranging from 5 to 19% and usually appears in the first few months of treatment. The diagnosis requires a high index of suspicion, especially in patients with risk factors (elderly male smokers with squamous cell lung cancer, previous respiratory or autoimmune disease, and receiving combination treatment with other ICIs or chemo-radiotherapy). Chest computed tomography (CT) is a key test, allowing the identification of different radiological patterns. This study can be completed with bronchoscopy with bronchoalveolar lavage (BAL) to rule out infection or tumour progression. In general terms, treatment is based on discontinuing the causative drug, with or without the initiation of systemic corticosteroids, escalating to immunosuppressants depending on the severity and/or refractoriness of the condition. This paper provides an updated narrative review of ICI pulmonary toxicity, addressing its pathophysiology, different types of lung damage, diagnostic and therapeutic algorithms, and the emerging role of biomarkers such as KL-6 or IL-6. This article emphasises the need for a multidisciplinary approach and further prospective studies to optimise the management and prognosis of this immune-mediated complication. Full article

Leptospirosis is a worldwide zoonosis caused by pathogenic Leptospira spp. with small rodents serving as the main reservoir. In Croatia, the serogroup Pomona has been detected most frequently, but its genomic diversity remains insufficiently characterized. This study presents the first whole genome sequencing analysis of 48 Croatian Leptospira spp. isolates collected from small rodents over a 14-year period. Serological typing confirmed that all the isolates belonged to the serogroup Pomona. Genomic analysis assigned them to L. kirschneri based on high genomic similarity using average nucleotide identity (ANI). The isolates were assigned to ST-98 using traditional multilocus sequence typing (MLST), while cgMLST identified seven genotype clusters, many of which showed geographic structuring. Phylogenetic analyses based on single nucleotide polymorphisms (SNPs) supported this structure and revealed a monophyletic clade of Croatian isolates distinct from other global L. kirschneri strains. Serological typing, MLST, and phylogenetic clustering support classification of the isolates as L. kirschneri, serogroup Pomona, most likely serovar Mozdok, although serovar Tsaratsovo cannot be excluded. These results indicate the existence of a geographically restricted and potentially host-adapted lineage of L. kirschneri in Croatia. The integration of ecological, serological, and genomic data in this study emphasizes the value of whole genome sequencing for understanding the population biology of Leptospira spp. serogroup Pomona. Moreover, it supports targeted, country-specific surveillance and control strategies for leptospirosis through the identification of circulating serovars and species in reservoir hosts, in line with a One Health approach. Full article

This article is devoted to the design of a real-time gain scheduling (adaptive) proportional–integral (PI) controller for the displacement volume regulation of a swash plate-type axial piston pump. The pump is intended for open circuit hydraulic drive applications without “secondary control”. In this type of pump, the displacement volume depends on the swash plate swivel angle. The swash plate is actuated by a hydraulic-driven mechanism. The classical control device is a hydro-mechanical type, which can realize different control laws (by pressure, flow rate, or power). In the present development, it is replaced by an electro-hydraulic proportional spool valve, which controls the swash plate-actuating mechanism. The designed digital gain scheduling controller evaluates control signal values applied to the proportional valve. The digital controller is based on the new linear parameter-varying mathematical model. This model is estimated and validated from experimental data for various loading modes by an identification procedure. The controller is implemented by a rapid prototyping system, and various real-time loading experiments are performed. The obtained results with the gain scheduling PI controller are compared with those obtained by other classical PI controllers. The developed control system achieves appropriate control performance for a wide working mode of the axial piston pump. The comparison analyses of the experimental results showed the advantages of the adaptive PI controller and confirmed the possibility for its implementation in a real-time control system of different types of variable displacement pumps. Full article