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22 pages, 332 KB  
Review
Passive AI Detection of Stress and Burnout Among Frontline Workers
by Rajib Rana, Niall Higgins, Terry Stedman, Sonja March, Daniel F. Gucciardi, Prabal D. Barua and Rohina Joshi
Nurs. Rep. 2025, 15(11), 373; https://doi.org/10.3390/nursrep15110373 (registering DOI) - 22 Oct 2025
Abstract
Background: Burnout is a widespread concern across frontline professions, with healthcare, education, and emergency services workers experiencing particularly high rates of stress and emotional exhaustion. Passive artificial intelligence (AI) technologies may provide novel means to monitor and predict burnout risk using data [...] Read more.
Background: Burnout is a widespread concern across frontline professions, with healthcare, education, and emergency services workers experiencing particularly high rates of stress and emotional exhaustion. Passive artificial intelligence (AI) technologies may provide novel means to monitor and predict burnout risk using data collected continuously and non-invasively. Objective: This review aims to synthesize recent evidence on passive AI approaches for detecting stress and burnout among frontline workers, identify key physiological and behavioral biomarkers, and highlight current limitations in implementation, validation, and generalizability. Methods: A narrative review of peer-reviewed literature was conducted across multiple databases and digital libraries, including PubMed, IEEE Xplore, Scopus, ACM Digital Library, and Web of Science. Eligible studies applied passive AI methods to infer stress or burnout in individuals in frontline roles. Only studies using passive data (e.g., wearables, Electronic Health Record (EHR) logs) and involving healthcare, education, emergency response, or retail workers were included. Studies focusing exclusively on self-reported or active measures were excluded. Results: Recent evidence indicates that biometric data (e.g., heart rate variability, skin conductance, sleep) from wearables are most frequently used and moderately predictive of stress, with reported accuracies often ranging from 75 to 95%. Workflow interaction logs (e.g., EHR usage patterns) and communication metrics (e.g., email timing and sentiment) show promise but remain underexplored. Organizational network analysis and ambient computing remain largely conceptual in nature. Few studies have examined cross-sector or long-term data, and limited work addresses the generalizability of demographic or cultural findings. Challenges persist in data standardization, privacy, ethical oversight, and integration with clinical or operational workflows. Conclusions: Passive AI systems offer significant promise for proactive burnout detection among frontline workers. However, current studies are limited by small sample sizes, short durations, and sector-specific focus. Future work should prioritize longitudinal, multi-sector validation, address inclusivity and bias, and establish ethical frameworks to support deployment in real-world settings. Full article
11 pages, 901 KB  
Article
How Does Age at Diagnosis Influence Multiple Myeloma Survival? Empirical Evidence
by Michael O. Lawanson, Ernest Griffin, Daniel Berleant, Phillip Farmer, Ragen Hodge, Carolina Schinke, Cody Ashby and Michael A. Bauer
Healthcare 2025, 13(20), 2637; https://doi.org/10.3390/healthcare13202637 - 20 Oct 2025
Abstract
Background/Objectives: Disparities in multiple myeloma (MM) survival occur based on factors like genetics, age, race, income level, and access to healthcare. The impact of age at diagnosis on MM survival is not fully understood and continues to draw research attention. This study explores [...] Read more.
Background/Objectives: Disparities in multiple myeloma (MM) survival occur based on factors like genetics, age, race, income level, and access to healthcare. The impact of age at diagnosis on MM survival is not fully understood and continues to draw research attention. This study explores the link between age at diagnosis and survival outcomes using data from the University of Arkansas Medical Sciences Myeloma Center Database (MMDB). Methods: Kaplan–Meier curves and Cox models were used to analyze the data. The log-transformed age variable strongly predicted survival. Results: The analysis found survival curves showing that patients in lower age brackets tend to have better survival profiles. Thus, for example, those in the oldest category (>70) showed the steepest decline, while the youngest age category (under 40) had better survival. Spline functions identified a non-linear relationship between age and survival. The likelihood ratio test, Wald test, and log-rank score test confirmed that the overall model was statistically significant, indicating that the spline-based approach effectively captured the relationship between age and survival. Further analysis using a stratified Cox model by age group showed significant risk differences. Patients aged 50–59, 60–69, and over 70 all had higher risks of death compared to younger patients, with those over 70 having a 3.3 times greater risk. Conclusions: In conclusion, the study confirmed that age at diagnosis has a significant association with survival outcomes for MM patients. Full article
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16 pages, 4194 KB  
Article
A Wearable Monitor to Detect Tripping During Daily Life in Children with Intoeing Gait
by Warren Smith, Zahra Najafi and Anita Bagley
Sensors 2025, 25(20), 6437; https://doi.org/10.3390/s25206437 - 17 Oct 2025
Viewed by 279
Abstract
Children with intoeing gait are at increased risk of tripping and consequent injury, reduced mobility, and psychological issues. Quantification of tripping is needed outside the gait lab during daily life for improved clinical assessment and treatment evaluation and to enrich the database for [...] Read more.
Children with intoeing gait are at increased risk of tripping and consequent injury, reduced mobility, and psychological issues. Quantification of tripping is needed outside the gait lab during daily life for improved clinical assessment and treatment evaluation and to enrich the database for artificial intelligence (AI) learning. This paper presents the development of a low-cost, wearable tripping monitor to log a child’s Tripping Hazard Events (THEs) and steps taken during two weeks of everyday activity. A combination of sensors results in a high probability of THE detection, even during rapid gait, while guarding against false positives and minimizing power and therefore monitor size. A THE is logged when the feet come closer than a predefined threshold during the intoeing foot swing phase. Foot proximity is determined by a Radio Frequency Identification (RFID) reader in “sniffer” mode on the intoeing foot and a target of passive Near-Field Communication (NFC) tags on the contralateral foot. A Force Sensitive Resistor (FSR) in the intoeing shoe sets a time window for sniffing during gait and enables step counting. Data are stored in 15 min epochs. Laboratory testing and an IRB-approved human participant study validated system performance and identified the need for improved mechanical robustness, prompting a redesign of the monitor. A custom Python (version 3.10.13)-based Graphical User Interface (GUI) lets clinicians initiate recording sessions and view time records of THEs and steps. The monitor’s flexible design supports broader applications to real-world activity detection. Full article
(This article belongs to the Special Issue Artificial Intelligence and Sensor-Based Gait Recognition)
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14 pages, 1627 KB  
Article
Molecular Subtypes and Survival Patterns in Female Breast Cancer: Insights from a 12-Year Cohort
by Ionut Marcel Cobec, Ingolf Juhasz-Böss, Peter Seropian, Sarah Huwer, Vlad Bogdan Varzaru, Andreas Rempen and Aurica Elisabeta Moatar
Medicina 2025, 61(10), 1858; https://doi.org/10.3390/medicina61101858 - 16 Oct 2025
Viewed by 138
Abstract
Background and Objectives: Breast cancer is one of the most common cancers in women and the most common cause of cancer death. Hormone receptors, specifically the estrogen receptor (ER) and progesterone receptor (PR), as well as human epidermal growth factor receptor-2 (Her2), are [...] Read more.
Background and Objectives: Breast cancer is one of the most common cancers in women and the most common cause of cancer death. Hormone receptors, specifically the estrogen receptor (ER) and progesterone receptor (PR), as well as human epidermal growth factor receptor-2 (Her2), are tumor-specific markers used to guide breast cancer therapy. The purpose of this study is to evaluate the impact of tumor biology, including ER, PR, and Her2 expression, on survival in female breast cancer. Materials and Methods: This retrospective cohort study represents an analysis of 2016 female breast cancer cases using anonymized data. We reviewed cases of female breast cancer diagnosed from 1 January 2010 to 31 December 2021, in the Clinic of Obstetrics and Gynecology, Diakoneo Diak Klinikum Schwäbisch Hall, Germany. Data on clinical, pathology, immunohistochemistry, and follow-up characteristics were retrieved from the clinic’s database. To interpret the data, we used the software IBM SPSS Statistics 20, and, to account for multiple comparisons, we used a Bonferroni-adjusted significance level of 0.004. In the survival analysis, the Kaplan–Meier method and the log-rank test of equality of survival distributions were applied. Results: Among 2016 female breast cancer cases, 84.5% (1703/2016) were hormone receptor (HR)-positive. The 5-year overall survival was 0.873 (95% CI (0.851, 0.895); 99.6% CI (0.841, 0.905)) for HR-positive patients and 0.760 (95% CI (0.713, 0.807); 99.6% CI (0.691, 0.829)) for HR-negative patients (p < 0.001). Statistically significant differences were observed among HR+/HER2+, HR+/HER2−, HR−/HER2+, and triple-negative subtypes (p = 0.003). When comparing survival distributions based solely on HER2 expression (positive vs. negative), no statistically significant difference was observed (p = 0.29). Conclusions: Statistically significant differences in unadjusted overall survival distributions were observed among breast cancer molecular subtypes. HR-positive breast cancers demonstrated better overall survival than HR-negative cancers, while no statistically significant difference in unadjusted survival was observed between HER2-positive and HER2-negative groups. Full article
(This article belongs to the Special Issue New Developments in Diagnosis and Management of Breast Cancer)
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23 pages, 11431 KB  
Article
Characterisation of Nearby Ultracool Dwarf Candidates with OSIRIS/GTC: First Detection of Balmer Line Emission from the Dwarf Carbon Star LSR J2105+2514
by Antoaneta Antonova, Peter Pessev, Valeri Golev and Dinko Dimitrov
Universe 2025, 11(10), 340; https://doi.org/10.3390/universe11100340 - 14 Oct 2025
Viewed by 121
Abstract
Based on low-resolution OSIRIS/GTC optical spectra, we assign spectral classes to 38 poorly studied ultracool/brown dwarf candidates from the 2MASS database. For almost all of the targets, this is the first optical spectral classification. For the dwarfs showing Hα emission, we calculate [...] Read more.
Based on low-resolution OSIRIS/GTC optical spectra, we assign spectral classes to 38 poorly studied ultracool/brown dwarf candidates from the 2MASS database. For almost all of the targets, this is the first optical spectral classification. For the dwarfs showing Hα emission, we calculate the ratio of Hα to bolometric luminosity, which is the most common characteristic of magnetic activity in cool stars. For the others, we give 3σ upper limits. We also include estimates of the effective temperatures and log g and distances from Gaia based on a comparison with models. For one of our targets—LSR J2105+2514, previously classified as a dwarf carbon star—we confirm this classification and report Hα and Hβ line emission in the spectrum for the first time. Dwarf carbon stars (dC) are low-mass main sequence stars that have undergone mass-transfer binary evolution. The Balmer line emission from these objects most likely indicates coronal activity of the dwarf, which in turn may be due to either intrinsic magnetic activity or spin-up from accretion or tidal locking. Full article
(This article belongs to the Special Issue Magnetic Fields and Activity in Stars: Origins and Evolution)
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34 pages, 1837 KB  
Article
Lead Exposure and Bladder Cancer: Molecular Insights from TCGA RNA-Seq and Toxicogenomic Integration
by Gözde Öztan, Halim İşsever, Tuğçe İşsever and Levent Şahin
Cancers 2025, 17(20), 3291; https://doi.org/10.3390/cancers17203291 - 10 Oct 2025
Viewed by 411
Abstract
Background/Objectives: Bladder cancer (BC) carries a substantial global burden. Although lead (Pb) exposure has been linked to cancer, its molecular impact on bladder tumors remains unclear. We asked whether Pb-responsive transcriptional programs are present and clinically relevant in BC by integrating toxicogenomic resources [...] Read more.
Background/Objectives: Bladder cancer (BC) carries a substantial global burden. Although lead (Pb) exposure has been linked to cancer, its molecular impact on bladder tumors remains unclear. We asked whether Pb-responsive transcriptional programs are present and clinically relevant in BC by integrating toxicogenomic resources with tumor transcriptomes and whether a composite lead-response score has prognostic value. Methods: Differential expression was performed on TCGA bladder urothelial carcinoma (BLCA) RNA-seq data (tumor vs. normal). Lead-associated genes were curated from the Comparative Toxicogenomics Database (CTD) and tested for over-representation among BLCA differentially expressed genes (DEGs) using a hypergeometric framework, with a stricter |log2FC| ≥ 1 sensitivity. A tumor-level lead-response score was derived from the Pb–DEG overlap. Associations with overall survival (OS) were assessed using Cox models adjusted for age, sex, and pathological stage; secondary endpoints included PFI/DFI/DSS. Results: Lead-associated genes were significantly enriched among BLCA DEGs (background M = 20,530; K = 2618; n = 11,436; k = 1595; p = 4.21 × 10−9), and enrichment persisted under |log2FC| ≥ 1 (n = 4275; k = 698; p = 9.86 × 10−15). Pathway over-representation highlighted synaptic/neuronal-like adhesion and transmission, MAPK-centered signaling, and cell-cycle control. Among top candidates, AQP12B was independently prognostic for OS (HR per 1 SD increase = 0.76; 95% CI 0.63–0.92; p = 0.0038; N = 404). The composite lead-response score showed a directionally protective but non-significant association in multivariable OS models (HR per 1 SD = 0.93; 95% CI 0.81–1.05; p = 0.244), while median-split Kaplan–Meier (KM) curves separated (p = 0.045). Conclusions: Lead-responsive transcriptional programs are detectable in BLCA and intersect adhesion, MAPK signaling, and cell-cycle pathways. AQP12B emerges as a plausible prognostic marker, and a composite lead-response score warrants external validation for risk stratification and clinical translation. Full article
(This article belongs to the Section Molecular Cancer Biology)
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12 pages, 1107 KB  
Article
Stenting Versus Endoscopic Vacuum Therapy for Anastomotic Leakage After Esophago-Gastric Surgery
by Carlo Galdino Riva, Stefano Siboni, Matteo Capuzzo, Francesca Senzani, Lorenzo Cusmai, Daniele Bernardi, Pamela Milito, Andrea Lovece, Eleonora Vico, Marco Sozzi and Emanuele Luigi Giuseppe Asti
J. Clin. Med. 2025, 14(19), 7075; https://doi.org/10.3390/jcm14197075 - 7 Oct 2025
Viewed by 373
Abstract
Background: Anastomotic leakage (AL) is a major complication after esophago-gastric surgery, with incidence rates of 11–21% and mortality up to 14%. Early intervention is essential to reduce morbidity. Endoscopic treatments have advanced, with self-expandable metal stents (SEMSs) as the traditional standard (success ~90%), [...] Read more.
Background: Anastomotic leakage (AL) is a major complication after esophago-gastric surgery, with incidence rates of 11–21% and mortality up to 14%. Early intervention is essential to reduce morbidity. Endoscopic treatments have advanced, with self-expandable metal stents (SEMSs) as the traditional standard (success ~90%), but they carry risks like migration, stenosis, and need for drainage. Endoscopic vacuum therapy (EVT), applying negative pressure to drain secretions and promote healing, has shown success rates of 66–100%. Limited comparative data exists from small retrospective studies. This study compares SEMS and EVT for safety and efficacy in AL management. Methods: A retrospective case–control study from a prospective database at our institution was performed (March 2012–2025). We included patients with AL post-esophageal/gastric surgery treated endoscopically (SEMS or EVT). We excluded patients treated with conservative or surgical management. Demographics, comorbidities, oncology, surgery type, leak details, treatments, and outcomes were collected. Primary outcome was complete healing of the leak, while secondary outcomes were time to success, number of procedures needed, hospital stay, complications, mortality. Results: From 592 resections, we extracted 68 AL (11.5%), 45 of which met the inclusion criteria (22 SEMS, 23 EVT). Groups were similar demographically, but SEMS had more respiratory issues (43% vs. 8.7%, p = 0.018). SEMS were used more after esophagectomy (86.4% vs. 56.5%, p = 0.004); EVT was performed mostly after gastrectomy (34.7% vs. 9.1%, p = 0.009). Success rate was 86.4% for SEMS vs. 95.6% for EVT (p = 1.000). Complications were significantly lower in EVT (8.3% vs. 50%, p = 0.001; SEMS: 36.4% migrations, 18.2% stenoses). Leak onset time, modality of diagnosis, and leak size were comparable among the groups. Need for jejunostomy was higher in EVT (43.5% vs. 9.1%, p = 0.015), while chest drains in SEMS (63.7% vs. 13.1%, p < 0.001). Hospital stays (33–38 days, p = 0.864) and mortality (22.7% vs. 8.7%, p = 0.225) were similar. No differences were observed in terms of long-term mortality (log-rank p = 0.815). Conclusions: SEMS and EVT are both effective for AL after esophago-gastric surgery. EVT offers fewer complications and shorter treatment, so it is favored especially for esophago-jejunal leaks. Full article
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12 pages, 601 KB  
Article
Oncotype DX Recurrence Score Predicts Survival in Invasive Micropapillary Breast Carcinoma: A National Cancer Database Analysis
by Ali J. Haider, Mohummad Kazmi, Kyle Chang, Waqar M. Haque, Efstathia Polychronopoulou, Jonathon S. Cummock, Sandra S. Hatch, Andrew M. Farach, Upendra Parvathaneni, E. Brian Butler and Bin S. Teh
Curr. Oncol. 2025, 32(10), 559; https://doi.org/10.3390/curroncol32100559 - 5 Oct 2025
Viewed by 485
Abstract
(1) Background: Invasive micropapillary carcinoma (IMPC) is a rare, aggressive breast cancer subtype marked by high lymph node metastasis rates. While Oncotype DX recurrence score (RS) offers prognostic information for patients with hormone-receptor-positive (HR+) breast cancer, its utility in IMPC—a histology with distinct [...] Read more.
(1) Background: Invasive micropapillary carcinoma (IMPC) is a rare, aggressive breast cancer subtype marked by high lymph node metastasis rates. While Oncotype DX recurrence score (RS) offers prognostic information for patients with hormone-receptor-positive (HR+) breast cancer, its utility in IMPC—a histology with distinct biologic behavior—remains unvalidated. This study evaluates whether Oncotype DX offers prognostic information with respect to overall survival (OS) in non-metastatic, early-stage patients with IMPC of the breast. (2) Methods: The National Cancer Database (2004–2020) was queried to select for women with ER+/HER2−, T1-T2N0-N1 IMPC who underwent Oncotype DX testing and received no neoadjuvant therapy. Patients were stratified by RS: low (≤11), intermediate (12–25), and high (>25). Kaplan–Meier survival curves and log-rank tests compared 5-year OS between groups. Multivariable Cox proportional hazards models assessed RS as an independent predictor, adjusting for age, race, comorbidities, grade, radiation, and insurance status. (3) Results: A total of 1325 women met the selection criteria. The cohort demonstrated significant survival disparities by RS (log-rank p = 0.017). Five-year OS rates were 97.5%, 97.5%, and 93.7% for low, intermediate, and high-risk patients, respectively. Adjusted multivariate analysis confirmed RS as an independent prognosticator: low (HR = 0.31, 95% CI: 0.15–0.75) and intermediate (HR = 0.32, 95% CI: 0.15–0.75) scores correlated with reduced mortality versus high RS. Omission of radiation therapy (HR = 2.68, 95% CI: 1.05–6.86) and higher comorbidity burden (0 comorbidities vs. ≥2: HR = 0.25, 95% CI: 0.10–0.61) were significantly associated with worse survival. (4) Conclusions: Oncotype DX is predictive for OS in IMPC, with high RS (>25) portending poorer outcomes. The survival detriment associated with RT omission aligns with prior studies demonstrating RT benefit in higher-risk cohorts. These findings validate RS as a prognostic tool in IMPC and underscore its potential to refine adjuvant therapy, particularly RT utilization. Future studies should explore RS-driven treatment personalization in IMPC, including comorbidity management and adjuvant radiation to improve outcomes in this distinct patient population. Full article
(This article belongs to the Section Breast Cancer)
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20 pages, 1644 KB  
Article
P-HNSW: Crash-Consistent HNSW for Vector Databases on Persistent Memory
by Haena Lee, Taeyoon Park, Yedam Na and Wook-Hee Kim
Appl. Sci. 2025, 15(19), 10554; https://doi.org/10.3390/app151910554 - 29 Sep 2025
Viewed by 566
Abstract
The rapid growth of Large Language Models (LLMs) has generated massive amounts of high-dimensional feature vectors extracted from diverse datasets. Efficient storage and retrieval of such data are critical for enabling accurate and fast query responses. Vector databases (Vector DBs) provide efficient storage [...] Read more.
The rapid growth of Large Language Models (LLMs) has generated massive amounts of high-dimensional feature vectors extracted from diverse datasets. Efficient storage and retrieval of such data are critical for enabling accurate and fast query responses. Vector databases (Vector DBs) provide efficient storage and retrieval for high-dimensional vectors. These systems rely on Approximate Nearest Neighbor Search (ANNS) indexes, such as HNSW, to handle large-scale data efficiently. However, the original HNSW is implemented on DRAM, which is both costly and vulnerable to crashes. Therefore, we propose P-HNSW, a crash-consistent HNSW on persistent memory. To guarantee crash consistency, P-HNSW introduces two logs, NLog and NlistLog. We describe the logging process during the operation and the recovery process in the event of system crashes. Our experimental results demonstrate that the overhead of the proposed logging mechanism is negligible, while P-HNSW achieves superior performance compared with SSD-based recovery mechanisms. Full article
(This article belongs to the Special Issue Resource Management for Emerging Computing Systems)
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12 pages, 633 KB  
Article
Increased Susceptibility to Salmonella Infection in Systemic Lupus Erythematosus Compared with Other Systemic Autoimmune Diseases: Insights from a Retrospective Cohort Study from the Largest Health Care System in Taiwan
by Chen-Ying Wei, Han-Hua Yu, Pei-Yi Cheng and Yen-Fu Chen
Life 2025, 15(10), 1522; https://doi.org/10.3390/life15101522 - 26 Sep 2025
Viewed by 400
Abstract
Systemic lupus erythematosus (SLE) and other systemic autoimmune rheumatic diseases (SARDs) require long-term immunosuppressive therapy, placing patients at increased risk of infection. Salmonella species are particularly concerning due to their invasiveness and potential link to autoimmune activation, notably in SLE. This study aimed [...] Read more.
Systemic lupus erythematosus (SLE) and other systemic autoimmune rheumatic diseases (SARDs) require long-term immunosuppressive therapy, placing patients at increased risk of infection. Salmonella species are particularly concerning due to their invasiveness and potential link to autoimmune activation, notably in SLE. This study aimed to compare the risk of culture-confirmed Salmonella infection between SLE and other SARDs, based on data from the Chang Gung Research Database between 2005 and 2020. After propensity score matching, 3537 patients per group were analyzed. Patients with SLE had a higher incidence of Salmonella infection compared with those with other SARDs (0.54 vs. 0.17 per 1000 person-years), with a significantly greater cumulative incidence (log-rank p < 0.01). The adjusted hazard ratio (HR) for Salmonella infection in SLE was 2.47 (95% confidence interval (CI): 0.95–6.38), and the competing risk model confirmed a significant association (sub-distribution HR 2.58, 95% CI: 1.06–6.29, p = 0.04). Among SLE patients, lymphopenia was the only independent predictor of Salmonella infection (adjusted HR 3.98, 95% CI: 1.83–8.68, p < 0.001). Bloodstream infections were most common (70%), and serogroup D was the predominant strain (80%). These results suggest patients with SLE face higher Salmonella risk than other SARDs, especially those with lymphopenia, underscoring the need for targeted surveillance and preventive strategies. Full article
(This article belongs to the Section Physiology and Pathology)
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21 pages, 4076 KB  
Article
Comparative Transcriptomics of Olfactory Rosettes Reveals Expression Divergence and Adaptive Evolution in Herbivorous and Carnivorous Xenocyprididae Fishes
by Hua Xue, Hailong Gu, Liu Yang, Jingchen Chen and Wenqiao Tang
Animals 2025, 15(18), 2741; https://doi.org/10.3390/ani15182741 - 19 Sep 2025
Viewed by 400
Abstract
Olfaction plays a crucial role in fish feeding behaviors and ecological adaptation. However, systematic studies on its transcriptional regulation and molecular evolutionary mechanisms in herbivorous and carnivorous fishes remain scarce. In this study, we analyzed four Xenocyprididae species: two herbivorous (Ctenopharyngodon idella [...] Read more.
Olfaction plays a crucial role in fish feeding behaviors and ecological adaptation. However, systematic studies on its transcriptional regulation and molecular evolutionary mechanisms in herbivorous and carnivorous fishes remain scarce. In this study, we analyzed four Xenocyprididae species: two herbivorous (Ctenopharyngodon idella and Megalobrama amblycephala) and two carnivorous (Elopichthys bambusa and Culter alburnus), using olfactory rosette transcriptome sequencing and cross-species comparisons. The number of unigenes per species ranged from 40,229 to 42,405, with BUSCO completeness exceeding 89.2%. Functional annotation was performed using six major databases. Olfactory-related candidate genes were identified based on Pfam domains (7tm_4) and KEGG pathways (ko04740), revealing 8–19 olfactory receptor genes per species. These candidate genes were predominantly enriched in the olfactory transduction and neuroactive ligand–receptor interaction pathways. A total of 3681 single-copy orthologous genes were identified, and their expression profiles exhibited clear interspecific divergence without forming strict clustering by dietary type. High-threshold differentially expressed trend genes (|log2FC| ≥ 4) were enriched in pathways related to RNA processing, metabolite transport, and xenobiotic metabolism, suggesting that the olfactory system may participate in diverse adaptive responses. Ka/Ks analysis indicated that most homologous genes were under purifying selection, with only 0.87–2.07% showing positive selection. These positively selected genes were enriched in pathways related to immune response and neural regulation, implying potential roles in adaptive evolution associated with ecological behavior. Furthermore, the olfactory-related gene oard1 exhibited Ka/Ks > 1 in the E. bambusa vs. C. idella comparison. qRT-PCR validation confirmed the reliability of the RNA-Seq data. This work is the first to integrate two complementary indicators—expression trends and evolutionary rates—to systematically investigate the transcriptional regulation and molecular evolution of the olfactory system in Xenocyprididae species under the context of dietary differentiation, providing valuable reference data for understanding the perceptual basis of dietary adaptation in freshwater fish. Full article
(This article belongs to the Section Aquatic Animals)
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19 pages, 3450 KB  
Article
De  Novo Transcriptome Sequencing and Profiling of Ovarian Development of Argas persicus Along the Trophogonic Cycle
by Fen Yan, Deyong Duan, Jinzhu Meng and Tianyin Cheng
Genes 2025, 16(9), 1107; https://doi.org/10.3390/genes16091107 - 19 Sep 2025
Viewed by 430
Abstract
BackgroundArgas persicus is a hematophagous ectoparasite of poultry and is the vector of several agents infectious to poultry. This study aims to explore the key genes affecting the ovarian development of A. persicus. Methods: RNA-seq was performed on the [...] Read more.
BackgroundArgas persicus is a hematophagous ectoparasite of poultry and is the vector of several agents infectious to poultry. This study aims to explore the key genes affecting the ovarian development of A. persicus. Methods: RNA-seq was performed on the ovaries of A. persicus before blood-feeding, on the day of engorgement, and 6 days post-engorgement. Utilizing the threshold padj < 0.05 and|log2(foldchange)| > 1, differentially expressed genes were identified, and hub genes were determined by constructing protein–protein interaction (PPI) networks. Results: A total of 1008 differentially expressed genes were obtained during the feeding period, including 448 up-regulated and 560 down-regulated genes. Further, 2179 differentially expressed genes were screened in the preoviposition stage, including 1957 up-regulated and 222 down-regulated genes. These genes are mainly annotated in functions such as peptidase activity (especially serine protease activity), protein folding, protein assembly, and cell component assembly, and enriched in pathways such as protein processing in endoplasmic reticulum, lysosome, glutathione metabolism, and sphingolipid metabolism. In addition, some proteins that are closely related to ovarian development, including heat shock protein 70, protein disulfide isomerase, paramyosin, troponin I, hexosaminidase, serine protease, Kunitz serine protease inhibitors, and vitellogenin, were obtained. Conclusions: These findings fill the gap in the biological data for the ovarian development of soft ticks, provide a reference database for subsequent proteomics research, and offer fundamental support for the screening and development of candidate antigens for anti-tick vaccines. Full article
(This article belongs to the Section Animal Genetics and Genomics)
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22 pages, 8608 KB  
Article
Variability in Wood Quality and Moisture Content Measured by an Industrial X-Ray Scanner Across 700,000 Sawlogs of Picea abies, Abies alba, and Pinus sylvestris
by Tojo Ravoajanahary, Romain Rémond, Renaud Daquitaine, Enrico Ursella and Jean-Michel Leban
Forests 2025, 16(9), 1457; https://doi.org/10.3390/f16091457 - 12 Sep 2025
Viewed by 437
Abstract
Evaluating sawlog quality is vital for both forest managers and wood processors. While external traits, such as tree form, branch architecture and visible growth features can be evaluated through visual inspection, many key wood quality indicators remain hidden, such as knot type and [...] Read more.
Evaluating sawlog quality is vital for both forest managers and wood processors. While external traits, such as tree form, branch architecture and visible growth features can be evaluated through visual inspection, many key wood quality indicators remain hidden, such as knot type and distribution, or the heartwood-to-sapwood ratio. This highlights the need for technologies capable of “seeing through” logs. Today, X-ray scanners in sawmills enable comprehensive, continuous, non-destructive assessment of internal stem structure at large scale. This study leveraged a newly compiled database of approximately 726,000 scanned logs to characterize variability in knot distribution and sapwood proportion across three major European softwood species and estimate the moisture content. The analysis highlights inter-and intra-species differences. Sapwood proportion decreased with sawlog diameter in spruce and silver fir but remained high in pine. Pine also presented significantly larger and more variable knots. Between March and August, we observed a seasonal trend in sapwood moisture content, affecting fresh density, while heartwood moisture content remained stable. These findings provide valuable information to support decision-making processes, linking tree characteristics to wood qualities and guiding forest management. Full article
(This article belongs to the Section Wood Science and Forest Products)
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15 pages, 2457 KB  
Systematic Review
Electrocautery vs. Cold Cutting in Modified Radical Mastectomy: A Systematic Review and Meta-Analysis
by Dennis Cicio, Alin Gheorghe Balta, Teodora Livia Homorozan, Vladimir Ciornei, Octav Marius Russu, Horea Rares Benea and Mihai Pavel
J. Clin. Med. 2025, 14(18), 6437; https://doi.org/10.3390/jcm14186437 - 12 Sep 2025
Viewed by 1263
Abstract
Background and Objectives: Modified radical mastectomy (MRM) is a common surgical procedure, with outcomes that are influenced by the instruments used in the operation. This meta-analysis aimed to compare “cold cutting” or “traditional” techniques and monopolar or bipolar electrocautery. Materials and Methods: A [...] Read more.
Background and Objectives: Modified radical mastectomy (MRM) is a common surgical procedure, with outcomes that are influenced by the instruments used in the operation. This meta-analysis aimed to compare “cold cutting” or “traditional” techniques and monopolar or bipolar electrocautery. Materials and Methods: A comprehensive search of five databases was conducted, with only studies of adult patients undergoing MRM in clearly defined groups selected. Data from 12 RCTs and 3 cohort studies summarizing 1372 participants was extracted and then synthesized using random-effects models. Risk of Bias was assessed for each of the included studies using the RoB-2 or ROBINS-I tool. Results: Scalpel or scissor use in dissection and flap raising was associated with a significantly lower risk of seroma formation (LogOR = −0.90, 95% CI: −1.26 to −0.54, p < 0.01). Conversely, electrocautery demonstrated advantages including reduced operative time (MD = −13.14 min, 95% CI: −19.58 to −6.70, p < 0.01) and decreased intraoperative blood loss (MD = −171.60 mL, 95% CI: −259.35 to −84.41, p < 0.01). No statistically significant differences were observed in total drain output (MD = −16.45 mL, 95% CI: −170.96 to 138.06, p = 0.83) or duration of drainage (MD = 0.41 days, 95% CI: −0.41 to 1.23, p = 0.32). Similarly, rates of infection, ecchymosis, and flap necrosis did not differ significantly between techniques. Conclusions: Electrocautery should be employed in patients who benefit from a shorter operative time and lower blood loss, while patients in better clinical condition should benefit from cold cutting techniques. Data on patient-reported outcomes and wound cytokine levels were sparse and inconsistent. This meta-analysis was registered in PROSPERO (ID: CRD420251059886). Full article
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Article
Next-Generation Predictive Microbiology: A Software Platform Combining Two-Step, One-Step and Machine Learning Modelling
by Fatih Tarlak, Büşra Betül Şimşek, Melissa Şahin and Fernando Pérez-Rodríguez
Foods 2025, 14(18), 3158; https://doi.org/10.3390/foods14183158 - 10 Sep 2025
Viewed by 715
Abstract
Microbial growth and inhibition are complex biological processes influenced by diverse environmental and chemical factors, posing challenges for accurate modelling and prediction. Traditional mechanistic models often struggle to capture the nonlinear and multidimensional interactions inherent in real-world food systems, especially when multiple environmental [...] Read more.
Microbial growth and inhibition are complex biological processes influenced by diverse environmental and chemical factors, posing challenges for accurate modelling and prediction. Traditional mechanistic models often struggle to capture the nonlinear and multidimensional interactions inherent in real-world food systems, especially when multiple environmental variables and inhibitors are involved. This study presents the development of a novel, dynamic software platform that integrates classical predictive microbiology models—including both one-step and two-step frameworks—with advanced machine learning (ML) methods such as Support Vector Regression, Random Forest Regression, and Gaussian Process Regression. Uniquely, this platform enables direct comparisons between two-step and one-step modelling approaches across four widely used growth models (modified Gompertz, Logistic, Baranyi, and Huang) and three inhibition models (Log-Linear, Log-Linear + Tail, and Weibull), offering unprecedented flexibility for model evaluation and selection. Furthermore, the platform incorporates ML-based modelling for both microbial growth and inhibition, expanding predictive capabilities beyond traditional parametric frameworks. Validation against experimental and literature datasets demonstrated the platform’s high predictive accuracy and robustness, with machine learning models, particularly Gaussian Process Regression and Random Forest Regression, outperforming classical models. This versatile platform provides a powerful, data-driven decision-support tool for researchers, industry professionals, and regulatory bodies in areas such as food safety management, shelf-life estimation, antimicrobial testing, and environmental monitoring. Future work will focus on further optimization, integration with large public microbial databases, and expanding applications in emerging fields of predictive microbiology. Full article
(This article belongs to the Section Food Microbiology)
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