cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30060651
title: Osteoporosis screening and major osteoporotic fracture prediction by cranial computed tomography-derived Hounsfield units: a multi-center study on opportunistic osteoporosis screening

description: The incidence of osteoporosis and osteoporotic fragility fractures is increasing due to demographic changes. Therefore, early diagnosis is desirable in order to preserve bone health and prevent low-trauma fractures. Opportunistic screening for osteoporosis by frequently performed computed tomography scans could offer a potential solution. Cranial computed tomography is often performed in potential high-risk patients for osteoporosis due to frequent falls in older ages. The aim of this study was to examine the potential value of opportunistic osteoporosis screening by cranial computed tomography-derived Hounsfield units in the overall clinical context, including sustained major osteoporotic fractures, pre-existing diseases and lifestyle factors. This retrospective multi-center study was conducted at the Vienna Healthcare Group, an association of the main clinics of the City of Vienna, Austria. The records of patients who received both a cranial computed tomography and a dual energy X-ray absorptiometry within one year were reviewed. The cranial computed tomography scans were assessed by two observers, and the mean Hounsfield Units were calculated for the frontal bone. In total, 311 patients were analyzed. Hounsfield units significantly correlated with the T scores at the lumbar spine, total hip and femoral neck, and significant differences in Hounsfield units between patients with normal bone mineral density, osteopenia and osteoporosis were observed. These relationships remained significant in the geriatric subgroup. For the lumbar spine, 606 Hounsfield units were calculated as optimal cutoff value for the prediction of osteoporosis. Patients with sustained major osteoporotic fractures had significantly lower Hounsfield units (650) compared to patients without history of major osteoporotic fracture (715). Cranial computed tomography-derived Hounsfield units may assist to detect patients with densitometric osteoporosis and with major osteoporotic fractures at earlier stages, thereby facilitating early treatment and future fracture prevention.
DOI: 10.6084/m9.figshare.30060651.v1
title: Osteoporosis screening and major osteoporotic fracture prediction by cranial computed tomography-derived Hounsfield units: a multi-center study on opportunistic osteoporosis screening

description: The incidence of osteoporosis and osteoporotic fragility fractures is increasing due to demographic changes. Therefore, early diagnosis is desirable in order to preserve bone health and prevent low-trauma fractures. Opportunistic screening for osteoporosis by frequently performed computed tomography scans could offer a potential solution. Cranial computed tomography is often performed in potential high-risk patients for osteoporosis due to frequent falls in older ages. The aim of this study was to examine the potential value of opportunistic osteoporosis screening by cranial computed tomography-derived Hounsfield units in the overall clinical context, including sustained major osteoporotic fractures, pre-existing diseases and lifestyle factors. This retrospective multi-center study was conducted at the Vienna Healthcare Group, an association of the main clinics of the City of Vienna, Austria. The records of patients who received both a cranial computed tomography and a dual energy X-ray absorptiometry within one year were reviewed. The cranial computed tomography scans were assessed by two observers, and the mean Hounsfield Units were calculated for the frontal bone. In total, 311 patients were analyzed. Hounsfield units significantly correlated with the T scores at the lumbar spine, total hip and femoral neck, and significant differences in Hounsfield units between patients with normal bone mineral density, osteopenia and osteoporosis were observed. These relationships remained significant in the geriatric subgroup. For the lumbar spine, 606 Hounsfield units were calculated as optimal cutoff value for the prediction of osteoporosis. Patients with sustained major osteoporotic fractures had significantly lower Hounsfield units (650) compared to patients without history of major osteoporotic fracture (715). Cranial computed tomography-derived Hounsfield units may assist to detect patients with densitometric osteoporosis and with major osteoporotic fractures at earlier stages, thereby facilitating early treatment and future fracture prevention.
DOI: 10.6084/m9.figshare.30928067
title: Corticotropin-releasing hormone inhibits autophagy by suppressing PTEN to promote apoptosis in dermal papilla cells

description: Stress-related hair loss is on the rise, largely due to escalating levels of stress-related corticotropin-releasing hormone (CRH) through poorly defined mechanisms. CRH-mediated activation of corticotropin-releasing hormone receptors (CRHRs) on dermal papilla cells (DPCs) is a likely cause of stress-related hair loss. The aim of the study is to elucidate the key mechanisms of alopecia caused by CRH and provide potential new targets for the treatment of stress-related hair loss. 4D label-free quantitative proteomics of DPCs and the chronic unpredictable mild stress mouse (CUMS) model were used to explore the relationship and mechanism between CRH, DPCs and hair regeneration. CRH initially downregulated PTEN to suppress autophagy, leading to DPC apoptosis. Overexpression of PTEN enhanced autophagy and mitigated CRH-dependent DPC apoptosis. CRH inhibited PTEN and activated the PI3K/AKT/mTOR pathway, whereas rapamycin inhibited this pathway and activated autophagy, consequently lowering apoptosis, suggesting that increased susceptibility to apoptosis is caused by decreased autophagy. CUMS-induced hair growth disruption is accompanied by an increase in CRHRs and a decrease in PTEN levels within the dermal papilla. Intracutaneous injection of CRH impeded hair regeneration and decreased PTEN in mice, concurrent with inhibition of autophagy and increased apoptosis. These findings indicate that PTEN loss coupled with PI3K/AKT/mTOR-mediated autophagy inhibition and apoptosis in DPCs is a key mechanism of stress-related hair loss induced by CRH and suggests that topical activation of PTEN or enhancement of autophagy, e.g. through rapamycin, may have a therapeutic effect on stress-induced hair loss disorders such as alopecia.
DOI: 10.6084/m9.figshare.30928067.v1
title: Corticotropin-releasing hormone inhibits autophagy by suppressing PTEN to promote apoptosis in dermal papilla cells

description: Stress-related hair loss is on the rise, largely due to escalating levels of stress-related corticotropin-releasing hormone (CRH) through poorly defined mechanisms. CRH-mediated activation of corticotropin-releasing hormone receptors (CRHRs) on dermal papilla cells (DPCs) is a likely cause of stress-related hair loss. The aim of the study is to elucidate the key mechanisms of alopecia caused by CRH and provide potential new targets for the treatment of stress-related hair loss. 4D label-free quantitative proteomics of DPCs and the chronic unpredictable mild stress mouse (CUMS) model were used to explore the relationship and mechanism between CRH, DPCs and hair regeneration. CRH initially downregulated PTEN to suppress autophagy, leading to DPC apoptosis. Overexpression of PTEN enhanced autophagy and mitigated CRH-dependent DPC apoptosis. CRH inhibited PTEN and activated the PI3K/AKT/mTOR pathway, whereas rapamycin inhibited this pathway and activated autophagy, consequently lowering apoptosis, suggesting that increased susceptibility to apoptosis is caused by decreased autophagy. CUMS-induced hair growth disruption is accompanied by an increase in CRHRs and a decrease in PTEN levels within the dermal papilla. Intracutaneous injection of CRH impeded hair regeneration and decreased PTEN in mice, concurrent with inhibition of autophagy and increased apoptosis. These findings indicate that PTEN loss coupled with PI3K/AKT/mTOR-mediated autophagy inhibition and apoptosis in DPCs is a key mechanism of stress-related hair loss induced by CRH and suggests that topical activation of PTEN or enhancement of autophagy, e.g. through rapamycin, may have a therapeutic effect on stress-induced hair loss disorders such as alopecia.
DOI: 10.6084/m9.figshare.29640438
title: Identifying patterns of high intraoperative blood pressure variability in noncardiac surgery using explainable machine learning: a retrospective cohort study

description: High intraoperative blood pressure variability (HIBPV) is significantly associated with postoperative adverse complications. However, practical tools to characterize perioperative factors associated with HIBPV remain limited. This study aimed to develop explainable supervised machine learning (ML) models to classify patients with HIBPV and to identify structural perioperative patterns associated with HIBPV through model interpretation. This retrospective cohort study analyzed 47,520 noncardiac surgery cases from Beijing Tsinghua Changgung Hospital. We applied four ML algorithms—Extreme Gradient Boosting (XGBoost), Random Forest (RF), Light Gradient Boosting Machine (LightGBM), and Logistic Regression (LR)—to classify patients with or without HIBPV. The overall population and each age subgroup (pediatric, adult, elderly) underwent independent 70/30 train-test splits for model development. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC). SHapley Additive exPlanations (SHAP) values were used to interpret model outputs and assess feature importance. Among 47,520 noncardiac surgeries, 1,996 (4.2%) were classified as HIBPV. XGBoost and RF achieved the best performance, with AUROC values of 0.85 (95% confidence intervals (CI): 0.84–0.86) and 0.84 (95% CI: 0.82–0.85). Intraoperative average heart rate (HR) and bispectral index (BIS) were the most influential variables. In patients aged 50 ∼ 70, higher sevoflurane dosage was associated with reduced HIBPV risk. Among hypertensive patients, elevated intraoperative blood calcium (&gt;1.10 mmol/L) was associated with increased HIBPV risk. The models enabled accurate classification of HIBPV cases and highlighted key discriminative perioperative variables through SHAP-based interpretation. Intraoperative HR and BIS were significant contributing factors. Moreover, interactions between sevoflurane and age and between hypertension and calcium levels may inform individualized hemodynamic management strategies.
DOI: 10.6084/m9.figshare.29640438.v1
title: Identifying patterns of high intraoperative blood pressure variability in noncardiac surgery using explainable machine learning: a retrospective cohort study

description: High intraoperative blood pressure variability (HIBPV) is significantly associated with postoperative adverse complications. However, practical tools to characterize perioperative factors associated with HIBPV remain limited. This study aimed to develop explainable supervised machine learning (ML) models to classify patients with HIBPV and to identify structural perioperative patterns associated with HIBPV through model interpretation. This retrospective cohort study analyzed 47,520 noncardiac surgery cases from Beijing Tsinghua Changgung Hospital. We applied four ML algorithms—Extreme Gradient Boosting (XGBoost), Random Forest (RF), Light Gradient Boosting Machine (LightGBM), and Logistic Regression (LR)—to classify patients with or without HIBPV. The overall population and each age subgroup (pediatric, adult, elderly) underwent independent 70/30 train-test splits for model development. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC). SHapley Additive exPlanations (SHAP) values were used to interpret model outputs and assess feature importance. Among 47,520 noncardiac surgeries, 1,996 (4.2%) were classified as HIBPV. XGBoost and RF achieved the best performance, with AUROC values of 0.85 (95% confidence intervals (CI): 0.84–0.86) and 0.84 (95% CI: 0.82–0.85). Intraoperative average heart rate (HR) and bispectral index (BIS) were the most influential variables. In patients aged 50 ∼ 70, higher sevoflurane dosage was associated with reduced HIBPV risk. Among hypertensive patients, elevated intraoperative blood calcium (&gt;1.10 mmol/L) was associated with increased HIBPV risk. The models enabled accurate classification of HIBPV cases and highlighted key discriminative perioperative variables through SHAP-based interpretation. Intraoperative HR and BIS were significant contributing factors. Moreover, interactions between sevoflurane and age and between hypertension and calcium levels may inform individualized hemodynamic management strategies.
DOI: 10.6084/m9.figshare.28188708
title: Construction of a novel radioresistance-related signature for prediction of prognosis, immune microenvironment and anti-tumour drug sensitivity in non-small cell lung cancer

description: Non-small cell lung cancer (NSCLC) is a fatal disease, and radioresistance is an important factor leading to treatment failure and disease progression. The objective of this research was to detect radioresistance-related genes (RRRGs) with prognostic value in NSCLC. The weighted gene coexpression network analysis (WGCNA) and differentially expressed genes (DEGs) analysis were performed to identify RRRGs using expression profiles from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO) regression and random survival forest (RSF) were used to screen for prognostically relevant RRRGs. Multivariate Cox regression was used to construct a risk score model. Then, Immune landscape and drug sensitivity were evaluated. The biological functions exerted by the key gene <i>LBH</i> were verified by <i>in vitro</i> experiments. Ninety-nine RRRGs were screened by intersecting the results of DEGs and WGCNA, then 11 hub RRRGs associated with survival were identified using machine learning algorithms (LASSO and RSF). Subsequently, an eight-gene (<i>APOBEC3B, DOCK4, IER5L, LBH, LY6K, RERG, RMDN2</i> and <i>TSPAN2</i>) risk score model was established and demonstrated to be an independent prognostic factor in NSCLC on the basis of Cox regression analysis. The immune landscape and sensitivity to anti-tumour drugs showed significant disparities between patients categorized into different risk score subgroups. <i>In vitro</i> experiments indicated that overexpression of <i>LBH</i> enhanced the radiosensitivity of A549 cells, and knockdown <i>LBH</i> reversed the cytotoxicity induced by X-rays. Our study developed an eight-gene risk score model with potential clinical value that can be adopted for choice of drug treatment and prognostic prediction. Its clinical routine use may assist clinicians in selecting more rational practices for individuals, which is important for improving the prognosis of NSCLC patients. These findings also provide references for the development of potential therapeutic targets. An eight-gene (<i>APOBEC3B, DOCK4, IER5L, LBH, LY6K, RERG, RMDN2,</i> and <i>TSPAN2</i>) risk score model that can predict the clinical prognosis of NSCLC patients was developed and validated.NSCLC patients in the low-risk score group had a higher degree of immune cell infiltration and were more sensitive to anti-tumor drugs.Overexpression of LBH inhibited the malignant phenotype of A549 cells and increased their sensitivity to X-rays. An eight-gene (<i>APOBEC3B, DOCK4, IER5L, LBH, LY6K, RERG, RMDN2,</i> and <i>TSPAN2</i>) risk score model that can predict the clinical prognosis of NSCLC patients was developed and validated. NSCLC patients in the low-risk score group had a higher degree of immune cell infiltration and were more sensitive to anti-tumor drugs. Overexpression of LBH inhibited the malignant phenotype of A549 cells and increased their sensitivity to X-rays.
DOI: 10.6084/m9.figshare.28188708.v1
title: Construction of a novel radioresistance-related signature for prediction of prognosis, immune microenvironment and anti-tumour drug sensitivity in non-small cell lung cancer

description: Non-small cell lung cancer (NSCLC) is a fatal disease, and radioresistance is an important factor leading to treatment failure and disease progression. The objective of this research was to detect radioresistance-related genes (RRRGs) with prognostic value in NSCLC. The weighted gene coexpression network analysis (WGCNA) and differentially expressed genes (DEGs) analysis were performed to identify RRRGs using expression profiles from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO) regression and random survival forest (RSF) were used to screen for prognostically relevant RRRGs. Multivariate Cox regression was used to construct a risk score model. Then, Immune landscape and drug sensitivity were evaluated. The biological functions exerted by the key gene <i>LBH</i> were verified by <i>in vitro</i> experiments. Ninety-nine RRRGs were screened by intersecting the results of DEGs and WGCNA, then 11 hub RRRGs associated with survival were identified using machine learning algorithms (LASSO and RSF). Subsequently, an eight-gene (<i>APOBEC3B, DOCK4, IER5L, LBH, LY6K, RERG, RMDN2</i> and <i>TSPAN2</i>) risk score model was established and demonstrated to be an independent prognostic factor in NSCLC on the basis of Cox regression analysis. The immune landscape and sensitivity to anti-tumour drugs showed significant disparities between patients categorized into different risk score subgroups. <i>In vitro</i> experiments indicated that overexpression of <i>LBH</i> enhanced the radiosensitivity of A549 cells, and knockdown <i>LBH</i> reversed the cytotoxicity induced by X-rays. Our study developed an eight-gene risk score model with potential clinical value that can be adopted for choice of drug treatment and prognostic prediction. Its clinical routine use may assist clinicians in selecting more rational practices for individuals, which is important for improving the prognosis of NSCLC patients. These findings also provide references for the development of potential therapeutic targets. An eight-gene (<i>APOBEC3B, DOCK4, IER5L, LBH, LY6K, RERG, RMDN2,</i> and <i>TSPAN2</i>) risk score model that can predict the clinical prognosis of NSCLC patients was developed and validated.NSCLC patients in the low-risk score group had a higher degree of immune cell infiltration and were more sensitive to anti-tumor drugs.Overexpression of LBH inhibited the malignant phenotype of A549 cells and increased their sensitivity to X-rays. An eight-gene (<i>APOBEC3B, DOCK4, IER5L, LBH, LY6K, RERG, RMDN2,</i> and <i>TSPAN2</i>) risk score model that can predict the clinical prognosis of NSCLC patients was developed and validated. NSCLC patients in the low-risk score group had a higher degree of immune cell infiltration and were more sensitive to anti-tumor drugs. Overexpression of LBH inhibited the malignant phenotype of A549 cells and increased their sensitivity to X-rays.
DOI: 10.6084/m9.figshare.30900259
title: Gait differences after ACL reconstruction versus healthy controls: a three-level meta-analysis of kinematics, kinetics, and spatiotemporal parameters

description: This meta-analysis was designed to evaluate whether individuals following ACL reconstruction exhibit normalized gait biomechanics when compared to healthy controls. This review was conducted across five databases: PubMed, Embase, The Cochrane Library, Web of Science and EBSCOhost-SportDiscus, yielding a total of 5,251 records, with 21 qualified studies (52 independent samples from 861 participants; based on available data, the mean age was 26.5 ± 4.3 years and 51.3% were female) eligible for quantitative synthesis following rigorous screening. A three-level meta-analysis model was implemented to address effect size dependencies. Six gait parameters were analyzed, including kinematic variables (peak knee flexion and extension angles during stance), kinetic variables (peak external knee flexion and extension moments during stance) and spatiotemporal variables (stride length and walking speed). Among the six gait parameters that were analyzed, only the peak knee extension angle during stance (<i>k</i> = 9, <i>d</i> = 0.83, 95% CI: 0.26–1.40, I<sup>2</sup> = 77.53%, <i>p</i> = 0.01) showed a significant difference between ACL reconstruction patients and healthy controls. However, peak knee flexion angle, peak external knee flexion and extension moments during stance, stride length and walking speed were not significantly different between groups (<i>p</i> &gt; 0.05). Meta-regression identified a significant time-dependent improvement only for knee extension angle (<i>F</i> = 5.656, <i>p</i> = 0.049), while postoperative duration had no significant effect on other outcomes. This meta-analysis shows that the majority of gait parameters during stance, including peak knee flexion angle, external knee flexion and extension moments, stride length and walking speed, do not differ significantly between individuals with ACL reconstruction and healthy controls. Only peak knee extension angle remained impaired, though it showed signs of improvement over time. Persistent knee extension deficits emphasize the need for targeted quadriceps and knee control training as a key focus for long-term ACLR rehabilitation. Most stance-phase gait parameters normalize after anterior cruciate ligament surgery.Knee extension angle remains impaired but improves gradually with recovery time.Long-term rehabilitation should target knee extension control to restore function. Most stance-phase gait parameters normalize after anterior cruciate ligament surgery. Knee extension angle remains impaired but improves gradually with recovery time. Long-term rehabilitation should target knee extension control to restore function.