The NIH Common Fund Data Ecosystem (CFDE) program was established to facilitate data accessibility and interoperability across multiple Common Fund (CF) programs, promote collaborations and accelerate discoveries by combining diverse data types from different CF programs. The CFDE Data Resource Center (DRC) was tasked with developing two web-based portals: an Information Portal to serve information about the CFDE, and a Data Portal to host harmonized metadata and processed data contributed by participating CF Data Coordination Centers (DCCs) and other sources. To achieve these goals, the CFDE DRC developed the CFDE Workbench, a web-based platform that hosts processed data, metadata, tools, use cases, and analyses developed by the CFDE. The Cross-Cut Metadata Model (C2M2) and several other processed data are hosted by the CFDE Workbench, including set libraries (XMTs), Knowledge Graph (KG) assertions, and attribute tables. These processed data formats make information derived from CF programs more findable, accessible, interoperable, and reusable (FAIR), and artificial intelligence (AI)-ready for cross-DCC knowledge discovery. Besides serving data, metadata, and code assets, the CFDE Workbench has also developed several tools that utilize these resources to enable cross-CF-program knowledge discovery use cases. Overall, the CFDE Workbench is a platform that consolidates efforts toward making CF resources harmonized, FAIR, and AI-ready. The CFDE Workbench website is available from https://cfde.cloud.
Background: The Metabolomics Workbench (MW) is a public scientific data repository consisting of experimental data and metadata from metabolomics studies collected with mass spectroscopy (MS) and nuclear magnetic resonance (NMR) analyses. Although not as rapidly as in the past, MW has steadily evolved, updating its mwTab and JSON deposition text file formats and its web-based infrastructure. However, the growth of MW has been exponential since its inception in 2013 and continues to be exponential, with the number of datasets hosted on the repository increasing by 50% since April 2024. As part of regular maintenance to keep up with changes to the mwTab file format and an earnest effort to use MW datasets in meta-analyses, the mwtab Python package has been updated. Methods: Updates include better error handling for batch processing, better parsing to read more files without error, and extensive improvements to the validation capabilities of the package. These updates also required our mwFileStatusWebsite to be updated and improved. Results: We used the enhanced validation features of the mwtab package to evaluate all available datasets in MW to facilitate improved curation, FAIRness of the repository, and reuse for meta-analyses. Conclusions: Version 2.0.0 of the mwtab Python package is now officially released and freely available on GitHub and the Python Package Index (PyPI) under a Clear Berkeley Software Distribution (BSD) license, with documentation available on GitHub. The updated mwFileStatusWebsite is also officially in its 2.0.0 version.
The Metabolomics Workbench (MW) is a public scientific data repository consisting of experimental data and metadata from metabolomics studies collected with mass spectroscopy (MS) and nuclear magnetic resonance (NMR) analyses. Although not as rapidly as in the past, MW has steadily evolved; updating its mwTab and JSON deposition text file formats and its web-based infrastructure. However, the growth of MW has been exponential since its inception in 2013 and continues to be exponential, with the number of datasets hosted on the repository increasing by 50% since April 2024. As part of regular maintenance to keep up with changes to the mwTab file format and an earnest effort to use MW datasets in meta-analyses, the mwtab Python package has been updated. Updates include better error handling for batch processing, better parsing to read more files without error, and extensive improvements to the validation capabilities of the package. These updates also required our mwFileStatusWebsite to be updated and improved. We used the enhanced validation features of the mwtab package to evaluate all available datasets in MW to facilitate improved curation, FAIRness of the repository, and reuse for meta-analyses. Version 2.0.0 of the mwtab Python package is now officially released and freely available on GitHub and the Python Package Index (PyPI) under a Clear Berkeley Software Distribution (BSD) license with documentation available on GitHub. The updated mwFileStatusWebsite is also officially in its 2.0.0 version and is still available at https://moseleybioinformaticslab.github.io/mwFileStatusWebsite/.
The high economic losses and the lack of effective and safe vaccines against African swine fever (ASF) indicate the need for further in-depth studies of the virus genome, its changes and the circulation of genetic lineages. Whole genome sequencing of virus isolates is best suited for this purpose. Whole-genome analysis of African swine fever virus (ASFV) isolates obtained in the Lipetsk, Penza and Tambov regions in 2016-2021 and identification of additional diversity markers within the genetic lineage. Domestic pig tissue samples were analyzed using whole-genome sequencing and Sanger sequencing. The following programs were used for sequence assembly: CLC Genomics Workbench 22, Trimmomatic v. 0.39, SPAdes v. 4.2.0, BWA-MEM v. 0.7.17-r1188 and bcftools v.1. 22. The phylogenetic tree was constructed in MEGA11 based on the alignment in MAFFT v. 7.526 with 67 genomes from GenBank. Based on the presence of MGF 360-10L III polymorphism, the analyzed isolates belong to the CVR-V variant of the Russia genetic lineage of the Georgia 2007 clade. Based on the order of formation of MGF 360-10L III and CVR-V, any sequences carrying CVR-V belong to the same genetic lineage. A 12-nucleotide insertion CAGTCTATAAGA was detected, forming a tandem duplication in IGR MGF 360-13L - MGF 360-14L, and polymorphisms in IGR C62L - C962R and in genes D1133L and Q706L were proposed as having phylogenetic potential for differentiation ASFV strains in the central regions of Russia. The proposed new potential diversity markers have a resolving power for ASFV strains from Central Russia. Введение. Большой экономический ущерб и отсутствие действенных и безопасных вакцин против африканской чумы (АЧС) указывают на необходимость продолжения углубленного изучения генома вируса АЧС, его изменений и циркуляции генетических линий. Для этого наилучшим образом подходит полногеномное секвенирование изолятов вируса. Цель работы. Полногеномный анализ изолятов вируса АЧС, полученных на территории Липецкой, Пензенской и Тамбовской областей в 2016–2021 гг., и выявление дополнительных маркеров разнообразия в пределах генетической линии. Материалы и методы. Образцы тканей домашних свиней исследовали с помощью полногеномного секвенирования и секвенирования по Сэнгеру. Для сборки последовательностей использовали программы CLC Genomics Workbench 22, Trimmomatic v. 0.39, SPAdes v. 4.2.0, BWA-MEM v. 0.7.17-r1188 и bcftools v. 1.22. Филогенетическое древо строили в программе MEGA11 на основе выравнивания в MAFFT v. 7.526 с 67 геномами из GenBank. Результаты. На основании присутствия полиморфизма MGF 360-10L III проанализированные изоляты относились к варианту CVR-V генетической линии «Россия» клады Georgia 2007. Исходя из очередности образования MGF 360-10L III и CVR-V, любые последовательности, несущие CVR-V, принадлежат к этой же генетической линии. Была обнаружена инсерция в 12 нуклеотидов CAGTCTATAAGA, образующая тандемную дупликацию в IGR MGF 360-13L – MGF 360-14L, и предложены полиморфизмы в IGR C62L – C962R и в генах D1133L и Q706L, имеющие филогенетический потенциал для дифференцировки штаммов вируса АЧС в центральных регионах России. Заключение. Предложенные к использованию новые вероятные маркеры разнообразия обладают разрешающей способностью в отношении штаммов вируса АЧС из Центральной России.
Acceleration measurement plays a significant role in various fields, such as resource exploration, national defense and military affairs, safety production, and disaster prevention and mitigation. In response to the current problems of low sensitivity and poor lateral anti-interference ability of optical fiber acceleration sensors, a Michelson interference type optical fiber acceleration sensor based on push-pull structure is proposed. First, a push-pull structure sensor model is established and its theoretical analysis is conducted; second, the sensor is analyzed for static stress and modal analysis using the ANSYS Workbench; and finally, the sensor prototype is fabricated and a sensing system is built, and its performance is tested through a vibration testing system. The results show that the sensor's natural frequency is 72 Hz, the sensitivity is 51.58 dB (re: 0 dB = 1 rad/g), the linearity is 99.68%, and the lateral anti-interference degree reaches 221 227.74 dB (re: 0 dB = 1 rad/g). Compared with existing similar sensors, its lateral interference resistance has increased by ∼10.8% and its sensitivity has been significantly enhanced. The research results provide a reference for the development of Michelson interference type optical fiber acceleration sensors.
The flexible positioning platform is a critical structural component in the ultra-high acceleration macro-micro motion platform, enabling precise positioning across multiple scales. However, under high-frequency start-stop cycles and prolonged multi-condition operation, it is prone to fatigue damage induced by random vibrations, which poses a threat to system reliability. This study proposes a method for evaluating and optimizing the platform's performance under random vibration based on power spectral density (PSD) analysis. In accordance with the IEC 60068-2-64 standard, representative load spectra from Tables A.8 and A.6 were selected as excitation inputs. Frequency-domain analyses of stress, strain, and displacement were conducted using ANSYS Workbench 2022R1 in conjunction with the nCode platform, incorporating the Gaussian three-sigma probability interval. The results reveal that stress and deformation are highly concentrated in the hinge region, indicating a structural vulnerability. Fatigue life predictions were carried out using the Dirlik method and Miner's linear damage rule under various PSD loading conditions. The findings demonstrate that hinge stiffness is a key factor influencing vibration resistance and service life. This research provides theoretical support for the design optimization of flexible structures operating in complex random vibration environments.
Eucommiae Cortex (EC), a traditional Chinese medicinal herb, has been utilized to treat osteoarthritis (OA). The therapeutic efficacy of EC can be augmented by combining it with ginger juice. OA is often linked to metabolic disorders, with lactate accumulation contributing to its progression. Notably, the concentration of coniferyl aldehyde (CFA) markedly increases during the processing of EC with ginger juice. This study seeks to investigate whether CFA ameliorates OA via lactylation and to develop a non-invasive machine-learning model for the rapid diagnosis of OA utilizing lactate and other metabolic markers. Differences in the chemical composition of EC before and after processing with ginger were investigated using an untargeted metabolomics strategy and database integration. Active components were screened using network pharmacology to examine CFA's effect on inflammation in tumor necrosis factor-α (TNF-α) -induced C28/I2 and primary mouse chondrocytes. Biomarkers and molecular mechanisms were identified using metabolomics, interpretable machine learning, and RNA sequencing. In-cell western blotting and expression correlation analysis confirmed the correlation between inflammation and H3 histone lactylation improvement in C28/I2 cells treated with CFA. Molecular docking analysis identified targets, and the overexpression (oe) and silencing (si) of ALDOA validated the inhibitory effect of CFA on lactylation. The in vivo efficacy of CFA was assessed using a mouse destabilization of the medial meniscus (DMM) model of OA. CFA, a principal component in G-EC, exhibited significant anti-inflammatory effects both in vitro and in vivo. A non-invasive diagnostic model utilizing machine learning was developed by analyzing 44 OA urine samples from the Metabolomics Workbench database. This model employed SHapley Additive exPlanations in conjunction with a random forest algorithm and identified lactate as a significant potential diagnostic metabolite for OA. Metabolomic analysis of C28/I2 cells indicated that CFA influences the glycolysis pathway. This study identified the basis for the synergistic effect of ginger juice on EC and supported the scientific rationale for G-EC processing. In this study, CFA improved OA by affecting glycolysis and modulating lactylation at the H3K23la site of H3 histones, highlighting the critical role of CFA in its anti-OA effects. A non-invasive diagnostic model for OA was developed, which facilitated the rapid prediction of OA risk in patients, and interpretable machine-learning methodologies enabled the analysis of key metabolic markers.
This study compares the biomechanical performance of InterTan nails of three lengths (180 mm, 240 mm, and 320 mm) in treating AO/OTA 31A2.3 comminuted intertrochanteric fractures, which are highly unstable and prone to fixation failure. The research question focuses on identifying the nail length that optimizes stress distribution, displacement, and strain to enhance fracture healing and reduce failure risk, thereby providing a theoretical foundation for clinical decision-making. Femoral CT images from a healthy 24-year-old male were used to reconstruct cortical and cancellous bone models in Mimics Research 21.0 and Geomagic Wrap 2021. A complete femur and AO/OTA 31A2.3 fracture model were constructed in SolidWorks 2022. InterTan models (180 mm, 240 mm, and 320 mm) were assembled with the fracture model, and finite element analysis (FEA) was performed in Ansys Workbench 18.0 under three loading conditions (standing, walking, and stair descent) to evaluate stress, deformation, and failure risk. Stress concentrated at the nail-screw junction and proximal aperture, with the 180 mm nail exhibiting the highest stress, the 320 mm nail the lowest, and the 240 mm nail intermediate values. Displacement increased with nail length under dynamic loads, whereas the 180 mm nail minimized displacement during standing. The 240 mm nail showed the lowest strain during standing but the highest during stair descent. Differences in stress and displacement were statistically significant (P < 0.05). The 320 mm nail optimizes stress distribution, micromotion, and strain, thereby reducing failure risk and promoting healing. These findings align with biological osteosynthesis principles and support personalized treatment strategies.
We previously reported alarmingly high carriage rates of Streptococcus pneumoniae (SP) serotype 19F and serogroup 6 isolates, which were not susceptible to multiple beta-lactams among children under five years of age in Vietnam. Multilocus sequence typing analysis revealed the predominance of two major lineages, ST320 and ST13223, among serotype 19F and serogroup 6 isolates, respectively. Investigating the association between nonsusceptible genotypes and clinical outcomes could help optimize patient care or lead to the development of new diagnostic tests. We performed WGS on SP isolates randomly selected from the two major lineages and their related strains. FASTQ quality control and de novo assembly were performed using CLC Genomics Workbench ver. 7.5.1. Draft genome sequences were annotated using DFAST (DDBJ Fast Annotation and Submission Tool), which revealed the serogroups/serotypes and the sequences of the three major penicillin-binding protein genes and the sequence types. Draft sequences were aligned using MUMmer ver. 3.23, and putative recombination events and phylogenetic relationships excluding recombination regions were identified using Gubbins ver. 2.4.1. Finally, the association between a detected nonsusceptible genotype and the duration of hospital stay was evaluated in patients with acute respiratory infection. WGS analysis (serotype 19F/ST320, n = 22; serogroup 6/ST13223, n = 13; and isolates closely related to ST13223, n = 4) revealed substantial differences in genomic diversity and antimicrobial susceptibility between serogroup 6/ST13223 and serotype 19F/ST320 isolates, particularly the recombination-prone nature of serogroup 6/ST13223. Among the 23 recombination events observed in serogroup 6/ST13223, only those spanning the pbp2x region (15.5 kb and 6.4 kb) were associated with high MICs for multiple beta-lactams. A subset of ST13223 isolates and all ST320 isolates carried the identical pbp2x allele 16, which was significantly associated with a lack of susceptibility to the combination of penicillin, cefotaxime, and meropenem (p < 0.0001; odds ratio 11.5; 95% confidence interval [CI] 3.35-39.3). No significant association was demonstrated between the presence of this pbp2x allele and prolonged hospitalization (p = 0.6123). We revealed that the widespread nonsusceptibility to multiple beta-lactams among SP isolates circulating in central Vietnam was primarily driven by the dynamics of the pbp2x gene. However, the nonsusceptible pbp2x allele had little effect on clinical outcome.
Carnitines are a structurally diverse class of metabolites formed by conjugation of L-carnitine with fatty acids, amino acids, xenobiotics, and microbial metabolites. They play roles in transport, mitochondrial and peroxisomal metabolism, detoxification, and systemic signaling, yet their chemical diversity remains incompletely defined. We applied a pan-repository data mining strategy of LC-MS/MS data across GNPS/MassIVE, MetaboLights, and Metabolomics Workbench using MassQL diagnostic fragment ion filtering to systematically extract acylcarnitine spectra. This yielded a library of 34,222 unique MS/MS spectra representing 2,857 atomic compositions, corresponding to 3,872,050 detections. These datasets provide an MS/MS library for annotation, discovery, and contextualization of acylcarnitines, enabling identification of previously unknown carnitines, such as dihydroferulic acid conjugated carnitines and supporting future exploration of this metabolite class across host metabolism, diet, microbial activity, pharmacological exposures, and metabolic dysregulation.
This study presents a novel control strategy to improve the performance analysis of a DFIG-based wind power system. The main objective is to improve the quality of the produced energy, reduce the THD and enhance the system stability. The proposed method employs the RTO algorithm combined with the super-twisting control, applied within a sliding mode control. Although the latter is frequently applied in wind system control, it has major drawbacks, including a high THD, mainly caused by the chattering phenomenon. The proposed control strategy aims to mitigate this phenomenon while ensuring better robustness against variations in system parameters. The simulation results confirm the effectiveness of the proposed controller, using Matlab/Simulink environment, and experimental tests conducted on a workbench using the dSPACE-DS1104-board. The results from both simulations and experimental tests demonstrate the superior performance of the proposed controller compared to conventional techniques, with current THD below 3%, active and reactive power tracking errors reduced to 0.11%, and overall efficiency reaching 98.88%. The online version contains supplementary material available at 10.1038/s41598-026-42956-4.
This study aimed to evaluate the initial tooth displacement pattern and periodontal ligament (PDL) stress across the maxillary arch, from 0.25-mm intrusion of the maxillary right central incisor (UR1) with clear aligner therapy (CAT) under ideal retention, using finite element method (FEM). A 3D FEM model of the maxillary dentition, PDL, and alveolar bone was reconstructed from CBCT data in Mimics Research 21.0 (Materialise, Leuven, Belgium). A 0.7-mm scalloped aligner was generated in 3-matic Research 13.0. UR1 was extruded 0.25mm, and the aligner was seated onto this geometry to create an interference-fit activation. Materials were defined as linear elastic and isotropic; aligner-tooth contacts were set as bonded to simulate ideal retention. Tooth displacement and von Mises stress were computed in ANSYS Workbench 2025 R1 (ANSYS Inc., Canonsburg, PA, USA) using global and tooth-specific local axes. UR1 showed primary intrusion with mild distal-lingual tipping. Adjacent incisors, canines, and premolars exhibited slight extrusion; molars showed minimal intrusion with distal tipping. All teeth displayed a distal displacement trend. Lingual tipping occurred anteriorly and buccal tipping posteriorly. UR1 had the highest PDL stress (441.462kPa), concentrated apically. Anchorage teeth showed cervical stress consistent with tipping. UR1 achieved ∼52% of the programmed intrusion. A 0.25-mm intrusion step generated light force (about 0.163N), producing 0.13-mm intrusion (52%) with mild distal-lingual tipping of UR1. The anchorage teeth were slightly extruded and tipped distally. PDL stress was concentrated apically on UR1 and cervically on adjacent teeth. Interpretation based on tooth-specific local axes in FEM studies enhances the identification of subtle, clinically relevant side effects beyond the primary movement pattern.
Hypertension is a chronic condition and a leading risk factor for cardiovascular disease, stroke, and premature mortality worldwide. While blood pressure (BP) monitoring-via clinical, home, or ambulatory measurements-remains the primary diagnostic tool, each method is limited by variability, device inaccuracy, and difficulties in detecting atypical BP patterns such as masked or white-coat hypertension. These challenges underscore the need for innovative, complementary diagnostic approaches. This systematic review and meta-analysis aims to synthesize current evidence on the role of metabolomic profiling in the detection and understanding of hypertension. Specifically, it seeks to evaluate whether metabolomics can identify preclinical metabolic signatures, improve diagnostic accuracy, and elucidate pathophysiological mechanisms underlying hypertension, thereby complementing traditional BP monitoring. A systematic search will be conducted in PubMed, Embase, Web of Science, Scopus, and CENTRAL from inception to the present supplemented with manual screening of metabolomics repositories (MetaboLights and Metabolomics Workbench) to ensure comprehensive coverage. This systematic review will include studies involving adults (aged ≥18 years) that investigate metabolomic biomarkers in hypertension using validated analytical platforms such as nuclear magnetic resonance spectroscopy, gas chromatography-mass spectrometry, or liquid chromatography-mass spectrometry. Eligible studies must stratify participants into hypertensive, prehypertensive, or normotensive groups and report associations between metabolites and BP measurements. Two independent reviewers will conduct study selection, data extraction, and risk-of-bias assessment using version 2 of the Cochrane risk-of-bias tool for randomized trials and the Risk of Bias in Nonrandomized Studies of Interventions and Risk of Bias in Nonrandomized Studies of Exposures tools, with evidence certainty evaluated via the Grading of Recommendations Assessment, Development, and Evaluation framework. A meta-analysis will be performed where possible using random-effects models and subgroup analyses to address heterogeneity. Database search, screening, and data extraction are ongoing as of January 2026. The results will summarize metabolomic profiles (such as stearidonate and hexadecadienoate), diagnostic accuracy metrics (eg, area under the curve and sensitivity), and metabolic pathways associated with hypertension once data synthesis is completed. The systematic review and meta-analysis is expected to be published in August 2026. This review will identify metabolites showing consistent hypertension associations and document methodological requirements for clinical translation, including standardization of sample collection, analytical platforms, and data processing. The findings will inform longitudinal validation studies and establish evidence-based pathways for potential applications in hypertension risk assessment and clinical trial design. Validation of consistently identified metabolite-hypertension associations in independent, prospective cohorts will be critical for establishing causality and assessing the temporal stability of metabolomic signatures. The review will also identify methodological gaps requiring standardization, such as sample collection protocols, analytical platform harmonization, and data processing procedures, which must be addressed before metabolomic findings can be translated into clinical applications.
This study used three-dimensional (3D) finite-element analysis (FEA) to investigate the effect of different implant placement strategies on the biomechanical behavior of implant-supported maxillary overdentures, and provide an initial guide to clinical treatment. For an edentulous maxilla, six different implant-supported overdenture models with various implant placement strategies were created using CATIA software. The reference model (5R-3R-3L-5L) featured symmetrical implant placement in the canine and second premolar regions bilaterally. Five additional models incorporated asymmetrical implant placement strategies: 5R-3R-1L-3L, 5R-2R-3L-5L, 5R-4R-3L-5L, 4R-3R-3L-5L, and 6R-3R-3L-5L. All models had identical bone properties, prosthetic components, material characteristics, and loading conditions. The geometric models were analyzed using ANSYS 24.0 Workbench software. The maximum principal stress for bone, and stress distribution patterns were analyzed, and the performance of the models was compared with the symmetrical reference model. The quantitative and qualitative results showed that the implant placement strategy significantly influenced the magnitude and distribution of stress. The symmetrical implant placement strategy demonstrated the most favorable stress distribution, with the lowest maximum stress values in positions 5 R (2.69 MPa), 3 R (2.25 MPa), 3 L (2.16 MPa), and 5 L (3.24 MPa). Placement of implants in the anterior region resulted in stress concentration in the anterior region with maximum stress values at positions 5 R (3.24 MPa), 3 L (3.96 MPa), 1 L (5.09 MPa), and 3 L (5.57 MPa). Asymmetrical implant placement strategies with increased anteroposterior distribution and more posterior placement also demonstrated favorable biomechanical performance. Certain asymmetrical patterns induced fulcrum effects, leading to heterogeneous stress distribution. The symmetrical (5R-3R-3L-5L) implant placement may provide a more uniform stress distribution, which may enhance peri-implant bone preservation and long-term implant stability. Implant placement in the canine region should be prioritized, while mesially-positioned implants warrant clinical caution due to higher stress levels in bilaterally symmetrical implant placement strategies.
Strongyloides stercoralis (S. stercoralis), the etiological agent of strongyloidiasis, is a medically important intestinal nematode that can cause life-threatening disseminated infections, particularly in immunocompromised individuals. Despite its clinical significance, limited information is available on the genetic diversity, population structure, and phylogenetic relationships of this parasite, especially in endemic regions. Therefore, generating molecular data from different geographic areas is essential for better understanding transmission patterns and epidemiology. In the present study, the intraspecies genetic diversity of S. stercoralis isolates obtained from humans in endemic regions of Iran was investigated by using mitochondrial and nuclear genetic markers. Fecal samples were collected from infected individuals in four provinces of Iran and examined using standard parasitological methods. Molecular analysis was performed through polymerase chain reaction amplification of the mitochondrial cytochrome c oxidase subunit 1 (Cox1) gene and the nuclear 18S recombinant DNA [rDNA] hypervariable regions (HVR I and IV). The obtained sequences were analyzed and aligned using Chromas (Technelysium Pty Ltd, Brisbane, Australia), BioEdit (Tom Hall, North California State University, NC), and CLC Genomics Workbench 11 (QIAGEN Sciences Inc., Germantown, MD), compared with reference sequences from GenBank, and phylogenetic trees were constructed using MEGA version 7.0 (MEGA Software GmbH, Dortmund, Germany). Haplotype networks were visualized with PopART version 1.7 (University of Otago, Dunedin, New Zealand). Analysis of 40 human isolates revealed 13 Cox1 haplotypes, of which 11 were newly identified in the present study. Notably, one haplotype clustered closely with dog-derived isolates from Japan and Cambodia. Isolates from Hormozgan Province formed distinct clades compared with other regions. Furthermore, 18S rDNA analysis revealed shared HVR-I and HVR-IV haplotypes between human and canine isolates, suggesting zoonotic transmission. Overall, the findings reveal considerable genetic diversity and regional differentiation of S. stercoralis in Iran, highlighting the need for broader multigene studies to clarify transmission dynamics and support effective control strategies.
Informal caregiving is a major driver of the societal impact of Alzheimer's disease (AD) and has important implications for caregiver health, workforce participation, and gender equity. While prior research indicates that female informal caregivers of people living with AD experience greater physical and psychological burden than their male counterparts, most studies are limited to single-country contexts, and little is known about gender differences in nonmedical societal costs. To address these gaps, we examined caregiver-gender differences in informal care costs and caregiver burden associated with AD across seven countries. We conducted a cross-sectional analysis of harmonized baseline data from community-dwelling individuals with clinically diagnosed AD and their informal caregivers in four cohort studies: GERAS-EU (France, Germany, United Kingdom), GERAS-II (Italy, Spain), GERAS-JP (Japan), and GERAS-US (United States), accessed via the AD Data Initiative's AD Workbench. Monthly informal care costs (e.g., costs of caregiver time and missing work) were derived using the Resource Utilization in Dementia Questionnaire and quantified in US dollars. Caregiver burden was assessed using the Zarit Burden Interview (ZBI) questionnaire (total score: 0-88). We estimated caregiver-gender differences in informal care costs using two-part models (logistic regression followed by gamma regression) and differences in ZBI using linear regression. All models were adjusted for care recipient and caregiver characteristics and country. Secondary analyses stratified the models by disease severity, caregiver employment status, and country. Among 3,318 caregivers (66.2% women; mean age 63.1 ± 13.8 years), female caregivers had higher monthly informal care costs than male caregivers (adjusted mean difference: 191.8 USD; 95% CI: 27.4 to 356.1; P=.02) and greater burden (adjusted mean difference in ZBI: 4.0 points; 95% CI: 2.6 to 5.3; P<.001). Gender-disparity patterns were significant or directionally consistent in most stratified analyses and were also consistently observed in sensitivity analyses using an imputed dataset. Across seven countries, women providing informal care for people living with AD experienced higher costs and greater burden than men, highlighting gender-disparity in unpaid care. These findings support public health and policy efforts to strengthen caregiver supports (e.g., workplace accommodations and tailored caregiver support programs) to reduce burden and productivity loss, particularly for women.
Quantitative structure-activity relationship (QSAR) models are central to computer-aided drug discovery and predictive toxicology, but practical adoption is often impeded by ad-hoc tooling, inconsistent validation protocols, and poor reproducibility. We introduce ProQSAR, a modular, reproducible workbench that formalizes end-to-end QSAR development while permitting independent use of each component. ProQSAR composes interchangeable modules for standardization, feature generation, splitting (including scaffold- and cluster-aware splits), preprocessing, outlier handling, scaling, feature selection, model training and tuning, statistical comparison, conformal calibration, and applicability-domain assessment. The pipeline can run end-to-end to produce versioned artifact bundles (serialized models) and analyst-oriented reports suitable for deployment and audit. On representative MoleculeNet benchmarks evaluated under Bemis-Murcko scaffold split, ProQSAR attains state-of-the-art descriptor-based performance: the lowest mean RMSE across the regression suite (ESOL, FreeSolv, Lipophilicity; mean RMSE 0.658 ± 0.11 ), including a substantial improvement on FreeSolv (RMSE 0.494 vs. 0.731 for a leading graph method). On quantum mechanical benchmarks, ProQSAR demonstrated superior performance on the single-task dataset QM7 and maintained competitive results on the multi-task QM8 dataset. For classification, ProQSAR achieves the top ROC-AUC on ClinTox (91.4%) while remaining competitive across other benchmark (overall classification average 70.4 ± 11.6 ). Crucially, all predictions are accompanied by cross-conformal prediction and explicit applicability-domain flags that identify out-of-distribution entries, enabling calibrated and decision support. ProQSAR is released on PyPI, Conda, and Docker Hub; all releases embed full provenance (parameters, package versions, checksums) to ensure reproducibility. ProQSAR (i) enforces best-practice, group-aware validation together with formal statistical comparisons across models, (ii) integrates calibrated uncertainty quantification (cross-conformal prediction) and applicability-domain diagnostics for interpretable, risk-aware predictions, and (iii) exposes both a composable developer API and a one-click pipeline that generates deployment-ready artifacts and human-readable reports, demonstrated on representative benchmarks.
This study develops a finite element analysis method to define the 3-dimensional (3D) zone of center of resistance (ZCR) position for maxillary central incisors and first molars and validates its applicability under different alveolar bone levels. Cone-beam computed tomography scans from 40 patients were grouped: group 1 (maxillary central incisors, no bone loss), group 2 (maxillary central incisors, bone loss), group 3 (maxillary first molars, no bone loss), and group 4 (maxillary first molars, bone loss). The 3D models of teeth, a simulated 0.2-mm-thick PDL, and alveolar bone were reconstructed using Mimics software (Materialise, Leuven, Belgium) and imported into ANSYS Workbench (ANSYS Inc, Canonsburg, Pa) to calculate the tooth axis of rotation (resistance axis). A 5-step method defined the ZCR: (1) set the crown center as origin, (2) apply pure 3 N·mm couples at the crown center along the x-, y-, and z-axes, (3) find the resistance axes using displacement data, (4) use an algorithm to find best point filtering (1%-3%) where axes meet; fit a sphere to these points to get the ZCR center and radius, and (5) verify the accuracy by measuring rotation angles after applying forces at the center of the ZCR, and the 1 and 2 times radius in the 3 directions. Optimal filtering percentages averaged 2.23% (group 1), 2.10% (group 2), 1.33% (group 3), and 1.63% (group 4). Alveolar resorption reduced the ZCR height. The central incisors decreased from 59.17% (standard deviation [SD]: 1.01) to 45.19% (SD: 1.61), whereas first molars decreased from 53.76% (SD: 3.03) to 46.76% (SD: 2.02) of root length. The ZCR radius decreased with alveolar bone loss-central incisors (from 0.55 to 0.49 mm) and first molars (from 0.58 to 0.48 mm). Forces applied at the center of the ZCR minimized rotation angles (x/y-axis: 0.12°; z-axis: 0.09°). Rotation increased significantly when forces were applied beyond the sphere, reaching 1.92° at twice the radius. The finite element analysis method accurately and efficiently defined the 3D ZCR position and extent in central incisors and first molars. Alveolar bone loss induced apical displacement and a reduction in the ZCR extent.
The Chinese stag beetle (Dorcus hopei Saunders) is highly mobile. Its ability to land steadily on complex surfaces offers bionic inspiration for research on the landing systems of flapping-wing micro air vehicles (FWMAVs). In this paper, the foreleg structure of this beetle was studied using Micro-CT 3D reconstruction technology. The nanomechanical properties of its foreleg were investigated by nanoindentation. The role of the torsional behavior in material properties during the landing process was clarified. It was found that the Young's modulus (Er) and nano-hardness (H) at seven representative positions of the foreleg (from the femur to the pretarsus) all showed a trend of first increasing, then decreasing, and then increasing again, which indicates that the biomaterials of the beetle's foreleg have adaptability in redistributing the landing load. Based on this, three foreleg models were established using the Ansys Workbench 2024R1 software to simulate the torsional performance of the foreleg during transient landing impact motion. The results showed that the beetle's foreleg exhibits decent mechanical properties with equivalent stress distribution and torsional resistance. To further study its torsional resistance, three-unit element section models were designed and investigated. The results demonstrated that the foreleg's cross-sectional structure offers significant advantages in resisting torsional deformation and enabling stable landing. This study provides bio-inspiration for the development of FWMAVs landing systems. STATEMENT OF SIGNIFICANCE: This study provides a significant advancement in bio-inspired engineering by systematically unraveling the mechanoadaptive biomaterial strategy and torsion-resistant structural architecture of the Chinese stag beetle's foreleg, Dorcus hopei Saunders. We move beyond qualitative observation to establish a quantitative structure-property-performance relationship, first revealing a unique spatial gradient in nanomechanical properties (Young's modulus and hardness) along the foreleg. This gradient is identified as a key biological mechanism for optimal landing load redistribution. Furthermore, through bio-inspired computational models, we demonstrate that the foreleg's specific cross-sectional configuration confers torsional stability. These findings offer a foundational, data-driven design framework for overcoming a critical challenge in flapping-wing micro air vehicle (FWMAV) development-achieving controlled and stable landing on complex surfaces. Our work thereby bridges functional biology and advanced robotics, paving the way for a new generation of impact-resistant and agile micro-aerial systems.
With the high prevalence of periodontitis, tooth rotation resulting from periodontal damage can be corrected through orthodontic treatment; however, the biomechanical complexity of tooth movement in compromised periodontal tissues, combined with the inherently low rotation accuracy of clear aligners, present significant challenges to tooth rotational control. This finite element study aimed to explore appropriate attachment configurations for tooth rotation under periodontally compromised conditions. Based on cone beam computed tomography data of a patient, three-dimensional finite element models of the upper dental arch, periodontal ligament (PDL), alveolar bone, aligners, and attachments were created. The right maxillary second premolar(A5) was targeted as the rotated tooth with a 30°clockwise rotation. Simulations were conducted with varying alveolar bone loss levels (0/2/4/6 mm) and attachment configurations (none, vertical/horizontal rectangular, and vertical elliptical). A 1° aligner activation angle was applied, and finite element analysis was performed for 16 conditions to assess tooth displacement, periodontal ligament stress, and aligner condition by Ansys Workbench. All groups achieved counterclockwise rotation of the A5, but exhibited concomitant tipping and intrusion. PDL von Mises stress peaked in the lingual cervical region and exceeded apical values. The vertical ellipsoid attachment produced the greatest rotational displacement and highest cervical periodontal ligament stress. The horizontal rectangular attachment showed a more favorable center of rotation with comparatively large rotational displacement and cervical periodontal ligament stress. The vertical rectangular attachment yielded lower cervical periodontal ligament stress and reduced anchorage loss, but smaller rotational displacement and more pronounced undesired displacement. Increasing alveolar bone loss shifted the center of rotation and increased displacement, accompanied by greater undesired biomechanical effects, anchorage loss, and periodontal ligament stress. The horizontal rectangular attachment showed a condition-specific mechanical trade-off within this framework; therefore, clinical extrapolation should be cautious and supported by patient-specific in vivo validation. Treatment planning for rotational movements should consider periodontal support, with close periodontal monitoring and biomechanically informed attachment selection to reduce unintended movements and periodontal loading. The online version contains supplementary material available at 10.1186/s12903-026-08200-1.