cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29633884.v1
title: Social determinants of health and age-related differences in all-cause mortality: evidence from National Health and Nutrition Examination Survey

description: Unfavorable social determinants of health (SDoH) are linked to higher risks of poor health, but evidence on their age-specific distribution and association with all-cause mortality are limited. We analyzed NHANES data (2003–2018) from 14,604 participants, stratified by age and cumulative unfavorable SDoH. The association between SDoH and all-cause mortality was assessed using Kaplan–Meier curves, Cox regression models, and restricted cubic spline (RCS) analysis. Among 14,604 participants, 1,835 deaths (8.78%) were recorded. Kaplan–Meier curve analysis showed lower survival rates in the middle and high SDoH groups compared to the low SDoH group. RCS analysis showed a nonlinear relationship between SDoH and all-cause mortality. Cox regression analysis revealed that higher SDoH scores were significantly associated with increased all-cause mortality across all age groups. After full adjustment, each unit increase in SDoH score was linked to a 21% higher mortality risk in young group, 28% in middle-aged group, and 13% in the elderly. Compared to those with low SDoH, individuals in the high SDoH group had the greatest mortality risk in the middle-aged group (HR: 3.10). Distinct SDoH patterns emerged across ages: employment status, food security, and health insurance status were key in young group; middle-aged group were affected by a broader range of SDoH components, while the elderly showed weaker but still significant associations. SDoH characteristics differ across age groups, and unfavorable SDoH are strongly associated with higher all-cause mortality, with age-specific variations. Targeted interventions are needed to address each age group’s unique health needs.
DOI: 10.6084/m9.figshare.30111232
title: Association of subclinical thyroid dysfunction with the risk of vertebral fracture: a meta-analysis of prospective cohort studies

description: Subclinical thyroid dysfunction (STD) is associated with an elevated risk of non-vertebral fractures. However, whether STD is associated with the risk of vertebral fracture remains controversial. This study aimed to determine the relationship between STD and the risk of vertebral fracture using a meta-analysis approach. PubMed, Embase, and the Cochrane Library databases were searched for eligible studies published until March 01, 2025. Only prospective cohort studies that reported effect estimates with 95% confidence intervals (CIs) of vertebral fractures in participants with subclinical hyperthyroidism (SCH) and subclinical hypothyroidism (SH) compared to those with euthyroidism were included. A random-effects model was used to pool risk ratios (RRs), and analyses accounted for key covariates, including demographic factors, lifestyle variables, and disease history where reported. Ten prospective cohort studies involving 61,219 individuals were included in this meta-analysis. SCH was associated with an increased risk of vertebral fracture (RR: 2.20; 95% CI: 1.60–3.02; <i>p</i> &lt; 0.001). Moreover, the risk of vertebral fracture in individuals with SH was higher than that in those with euthyroidism (RR, 1.22; 95% CI: 1.01–1.49; <i>p</i> = 0.044). The pooled conclusions for the association between SCH and vertebral fracture risk were robust, whereas the significant association between SH and vertebral fracture was variable. The relationship between SH and vertebral fracture risk was affected by the median age of individuals (<i>p</i> = 0.047). Our study found that SCH was an independent risk factor for vertebral fracture, and that SH may increase the risk of vertebral fracture. Clinically, these findings support the need for regular monitoring of thyroid function, particularly in older adults, to identify individuals with STD who may benefit from targeted interventions to reduce vertebral fracture risk. We performed a systematic review and meta-analysis of prospective cohort studies to determine the relationship between subclinical thyroid dysfunction and risk of vertebral fractures. Subclinical hyperthyroidism (SCH) and hypothyroidism (SH) are associated with an elevated risk of vertebral fractures. The association between SCH and the risk of vertebral fracture was robust, whereas the median age of participants could affect the association between SH and the risk of vertebral fracture.
DOI: 10.6084/m9.figshare.30111232.v1
title: Association of subclinical thyroid dysfunction with the risk of vertebral fracture: a meta-analysis of prospective cohort studies

description: Subclinical thyroid dysfunction (STD) is associated with an elevated risk of non-vertebral fractures. However, whether STD is associated with the risk of vertebral fracture remains controversial. This study aimed to determine the relationship between STD and the risk of vertebral fracture using a meta-analysis approach. PubMed, Embase, and the Cochrane Library databases were searched for eligible studies published until March 01, 2025. Only prospective cohort studies that reported effect estimates with 95% confidence intervals (CIs) of vertebral fractures in participants with subclinical hyperthyroidism (SCH) and subclinical hypothyroidism (SH) compared to those with euthyroidism were included. A random-effects model was used to pool risk ratios (RRs), and analyses accounted for key covariates, including demographic factors, lifestyle variables, and disease history where reported. Ten prospective cohort studies involving 61,219 individuals were included in this meta-analysis. SCH was associated with an increased risk of vertebral fracture (RR: 2.20; 95% CI: 1.60–3.02; <i>p</i> &lt; 0.001). Moreover, the risk of vertebral fracture in individuals with SH was higher than that in those with euthyroidism (RR, 1.22; 95% CI: 1.01–1.49; <i>p</i> = 0.044). The pooled conclusions for the association between SCH and vertebral fracture risk were robust, whereas the significant association between SH and vertebral fracture was variable. The relationship between SH and vertebral fracture risk was affected by the median age of individuals (<i>p</i> = 0.047). Our study found that SCH was an independent risk factor for vertebral fracture, and that SH may increase the risk of vertebral fracture. Clinically, these findings support the need for regular monitoring of thyroid function, particularly in older adults, to identify individuals with STD who may benefit from targeted interventions to reduce vertebral fracture risk. We performed a systematic review and meta-analysis of prospective cohort studies to determine the relationship between subclinical thyroid dysfunction and risk of vertebral fractures. Subclinical hyperthyroidism (SCH) and hypothyroidism (SH) are associated with an elevated risk of vertebral fractures. The association between SCH and the risk of vertebral fracture was robust, whereas the median age of participants could affect the association between SH and the risk of vertebral fracture.
DOI: 10.6084/m9.figshare.27991426
title: Development and application of an uncapped mRNA platform

description: A novel uncapped mRNA platform was developed. Five lipid nanoparticle (LNP)-encapsulated mRNA constructs were made to evaluate several aspects of our platform, including transfection efficiency and durability <i>in vitro</i> and <i>in vivo</i> and the activation of humoral and cellular immunity in several animal models. The constructs were eGFP-mRNA-LNP (for enhanced green fluorescence mRNA), Fluc-mRNA-LNP (for firefly luciferase mRNA), S<sup>δT</sup>-mRNA-LNP (for Delta strain SARS-CoV-2 spike protein trimer mRNA), gD<sup>ED</sup>-mRNA-LNP (for truncated glycoprotein D mRNA coding ectodomain from herpes simplex virus type 2 (HSV2)) and gD<sup>FR</sup>-mRNA-LNP (for truncated HSV2 glycoprotein D mRNA coding amino acids 1–400). Quantifiable target protein expression was achieved <i>in vitro</i> and <i>in vivo</i> with eGFP- and Fluc-mRNA-LNP. S<sup>δT</sup>-mRNA-LNP, gD<sup>ED</sup>-mRNA-LNP and gD<sup>FR</sup>-mRNA-LNP induced both humoral and cellular immune responses comparable to those obtained by previously reported capped mRNA-LNP constructs. Notably, S<sup>δT</sup>-mRNA-LNP elicited neutralizing antibodies in hamsters against the Omicron and Delta strains. Additionally, gD<sup>ED</sup>-mRNA-LNP and gD<sup>FR</sup>-mRNA-LNP induced potent neutralizing antibodies in rabbits and mice. The mRNA constructs with uridine triphosphate (UTP) outperformed those with N1-methylpseudouridine triphosphate (N1mψTP) in the induction of antibodies via S<sup>δT</sup>-mRNA-LNP. Our uncapped, process-simplified and economical mRNA platform may have broad utility in vaccines and protein replacement drugs.KEY MESSAGESThe mRNA platform described in our paper uses internal ribosome entry site (IRES) (Rapid, Amplified, Capless and Economical, RACE; Register as BH-RACE platform) instead of caps and uridine triphosphate (UTP) instead of N1-methylpseudouridine triphosphate (N1mψTP) to synthesize mRNA.Through the self-developed packaging instrument and lipid nanoparticle (LNP) delivery system, mRNA can be expressed in cells more efficiently, quickly and economically.Particularly exciting is that potent neutralizing antibodies against Delta and Omicron real viruses were induced with the new coronavirus S protein mRNA vaccine from the BH-RACE platform. The mRNA platform described in our paper uses internal ribosome entry site (IRES) (Rapid, Amplified, Capless and Economical, RACE; Register as BH-RACE platform) instead of caps and uridine triphosphate (UTP) instead of N1-methylpseudouridine triphosphate (N1mψTP) to synthesize mRNA. Through the self-developed packaging instrument and lipid nanoparticle (LNP) delivery system, mRNA can be expressed in cells more efficiently, quickly and economically. Particularly exciting is that potent neutralizing antibodies against Delta and Omicron real viruses were induced with the new coronavirus S protein mRNA vaccine from the BH-RACE platform.
DOI: 10.6084/m9.figshare.27991426.v1
title: Development and application of an uncapped mRNA platform

description: A novel uncapped mRNA platform was developed. Five lipid nanoparticle (LNP)-encapsulated mRNA constructs were made to evaluate several aspects of our platform, including transfection efficiency and durability <i>in vitro</i> and <i>in vivo</i> and the activation of humoral and cellular immunity in several animal models. The constructs were eGFP-mRNA-LNP (for enhanced green fluorescence mRNA), Fluc-mRNA-LNP (for firefly luciferase mRNA), S<sup>δT</sup>-mRNA-LNP (for Delta strain SARS-CoV-2 spike protein trimer mRNA), gD<sup>ED</sup>-mRNA-LNP (for truncated glycoprotein D mRNA coding ectodomain from herpes simplex virus type 2 (HSV2)) and gD<sup>FR</sup>-mRNA-LNP (for truncated HSV2 glycoprotein D mRNA coding amino acids 1–400). Quantifiable target protein expression was achieved <i>in vitro</i> and <i>in vivo</i> with eGFP- and Fluc-mRNA-LNP. S<sup>δT</sup>-mRNA-LNP, gD<sup>ED</sup>-mRNA-LNP and gD<sup>FR</sup>-mRNA-LNP induced both humoral and cellular immune responses comparable to those obtained by previously reported capped mRNA-LNP constructs. Notably, S<sup>δT</sup>-mRNA-LNP elicited neutralizing antibodies in hamsters against the Omicron and Delta strains. Additionally, gD<sup>ED</sup>-mRNA-LNP and gD<sup>FR</sup>-mRNA-LNP induced potent neutralizing antibodies in rabbits and mice. The mRNA constructs with uridine triphosphate (UTP) outperformed those with N1-methylpseudouridine triphosphate (N1mψTP) in the induction of antibodies via S<sup>δT</sup>-mRNA-LNP. Our uncapped, process-simplified and economical mRNA platform may have broad utility in vaccines and protein replacement drugs.KEY MESSAGESThe mRNA platform described in our paper uses internal ribosome entry site (IRES) (Rapid, Amplified, Capless and Economical, RACE; Register as BH-RACE platform) instead of caps and uridine triphosphate (UTP) instead of N1-methylpseudouridine triphosphate (N1mψTP) to synthesize mRNA.Through the self-developed packaging instrument and lipid nanoparticle (LNP) delivery system, mRNA can be expressed in cells more efficiently, quickly and economically.Particularly exciting is that potent neutralizing antibodies against Delta and Omicron real viruses were induced with the new coronavirus S protein mRNA vaccine from the BH-RACE platform. The mRNA platform described in our paper uses internal ribosome entry site (IRES) (Rapid, Amplified, Capless and Economical, RACE; Register as BH-RACE platform) instead of caps and uridine triphosphate (UTP) instead of N1-methylpseudouridine triphosphate (N1mψTP) to synthesize mRNA. Through the self-developed packaging instrument and lipid nanoparticle (LNP) delivery system, mRNA can be expressed in cells more efficiently, quickly and economically. Particularly exciting is that potent neutralizing antibodies against Delta and Omicron real viruses were induced with the new coronavirus S protein mRNA vaccine from the BH-RACE platform.
DOI: 10.6084/m9.figshare.28194973
title: Identification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms

description: We aimed at identifying acute phase biomarkers in Severe Fever with Thrombocytopenia Syndrome (SFTS), and to establish a model to predict mortality outcomes. A retrospective analysis was conducted on multicenter clinical data. Group-based trajectory modeling (GBTM) was utilized to demonstrate the overall trend of laboratory indicators and their correlation with mortality. Six different machine learning algorithms were employed to develop prognostic models based on the clinical features during the acute phase, which were reduced using Lasso regression. Seven indicators (ALT, AST, BUN, LDH, a-HBDH, DD, and PLT) at 7-10 days post-onset and their change slopes were found to be crucial during disease progression. These, along with other clinical features, were reduced to 8 variables using Lasso regression for model construction. The random forest model demonstrated the best performance in both internal validation (AUC: 0.961) and external validation (AUC: 0.948). Decision Curve Analysis indicated a good balance between model benefits and risks. a-HBDH and its change slope along with central nervous symptom manifestations within 7-10 days after onset accurately predicted mortality in SFTS. Various algorithms provided a comprehensive overview of disease progression and constructed more stable and efficient models.
DOI: 10.6084/m9.figshare.28194973.v1
title: Identification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms

description: We aimed at identifying acute phase biomarkers in Severe Fever with Thrombocytopenia Syndrome (SFTS), and to establish a model to predict mortality outcomes. A retrospective analysis was conducted on multicenter clinical data. Group-based trajectory modeling (GBTM) was utilized to demonstrate the overall trend of laboratory indicators and their correlation with mortality. Six different machine learning algorithms were employed to develop prognostic models based on the clinical features during the acute phase, which were reduced using Lasso regression. Seven indicators (ALT, AST, BUN, LDH, a-HBDH, DD, and PLT) at 7-10 days post-onset and their change slopes were found to be crucial during disease progression. These, along with other clinical features, were reduced to 8 variables using Lasso regression for model construction. The random forest model demonstrated the best performance in both internal validation (AUC: 0.961) and external validation (AUC: 0.948). Decision Curve Analysis indicated a good balance between model benefits and risks. a-HBDH and its change slope along with central nervous symptom manifestations within 7-10 days after onset accurately predicted mortality in SFTS. Various algorithms provided a comprehensive overview of disease progression and constructed more stable and efficient models.
DOI: 10.6084/m9.figshare.29945558
title: Anoikis-related genes predicts prognosis and therapeutic response in renal cell carcinoma

description: Metastasis represents the primary cause of cancer-related mortality, with a high incidence observed in renal cell carcinoma (RCC). Anoikis, a specialized form of apoptosis, plays a crucial role in preventing displaced cells from adhering to new extracellular matrices (ECM), thus inhibiting their aberrant growth. Notably, cancer cells, especially metastatic ones, exhibit resistance to anoikis. However, the exact mechanisms of anoikis resistance in RCC are not well understood. This study integrates bioinformatics, single-cell RNA sequencing and experimental validation to investigate the role of anoikis-related genes (ARG) in RCC, with a focus on MMP9. RNA-seq data from 518 RCC patients and 71 healthy controls (TCGA-KIRC) and external validation cohorts (E-MTAB-1980, GSE22541) were analyzed to construct an ARG-based prognostic model. Single-cell RNA sequencing (scRNA-seq, GSE159115) was used to assess tumour heterogeneity, while <i>in vitro</i> experiments in RCC cell lines validated MMP9’s impact on anoikis resistance, migration and invasion. We collected all RNA-seq and single-cell RNA-seq (scRNA-seq) data from multiple online databases and utilized these datasets to develop a novel ARG-based prognostic model called ARGs. Using Cox regression and machine learning, our model achieved a 5-year area under curve (AUC) of 0.79, surpassing existing models in predictive performance. Enrichment analysis revealed distinct immune and metabolic landscapes between ARGs high- and low-risk groups. At the single-cell level, tumour cells were categorized based on ARG expression, revealing heterogeneous anoikis resistance mechanisms. MMP9 was identified as a key prognostic gene (HR = 1.5, <i>p</i> = 0.016) associated with anoikis resistance and RCC metastasis. Functional assays confirmed that MMP9 knockdown increased anoikis by 59% and significantly reduced wound-healing migration by about 30% and transwell invasion by 50%, reinforcing its role in RCC progression. Targeting anoikis-related genes, particularly MMP9, enhances anoikis sensitivity and reduces RCC invasiveness, offering a potential therapeutic strategy to mitigate metastasis and improve clinical outcomes.
DOI: 10.6084/m9.figshare.29945558.v1
title: Anoikis-related genes predicts prognosis and therapeutic response in renal cell carcinoma

description: Metastasis represents the primary cause of cancer-related mortality, with a high incidence observed in renal cell carcinoma (RCC). Anoikis, a specialized form of apoptosis, plays a crucial role in preventing displaced cells from adhering to new extracellular matrices (ECM), thus inhibiting their aberrant growth. Notably, cancer cells, especially metastatic ones, exhibit resistance to anoikis. However, the exact mechanisms of anoikis resistance in RCC are not well understood. This study integrates bioinformatics, single-cell RNA sequencing and experimental validation to investigate the role of anoikis-related genes (ARG) in RCC, with a focus on MMP9. RNA-seq data from 518 RCC patients and 71 healthy controls (TCGA-KIRC) and external validation cohorts (E-MTAB-1980, GSE22541) were analyzed to construct an ARG-based prognostic model. Single-cell RNA sequencing (scRNA-seq, GSE159115) was used to assess tumour heterogeneity, while <i>in vitro</i> experiments in RCC cell lines validated MMP9’s impact on anoikis resistance, migration and invasion. We collected all RNA-seq and single-cell RNA-seq (scRNA-seq) data from multiple online databases and utilized these datasets to develop a novel ARG-based prognostic model called ARGs. Using Cox regression and machine learning, our model achieved a 5-year area under curve (AUC) of 0.79, surpassing existing models in predictive performance. Enrichment analysis revealed distinct immune and metabolic landscapes between ARGs high- and low-risk groups. At the single-cell level, tumour cells were categorized based on ARG expression, revealing heterogeneous anoikis resistance mechanisms. MMP9 was identified as a key prognostic gene (HR = 1.5, <i>p</i> = 0.016) associated with anoikis resistance and RCC metastasis. Functional assays confirmed that MMP9 knockdown increased anoikis by 59% and significantly reduced wound-healing migration by about 30% and transwell invasion by 50%, reinforcing its role in RCC progression. Targeting anoikis-related genes, particularly MMP9, enhances anoikis sensitivity and reduces RCC invasiveness, offering a potential therapeutic strategy to mitigate metastasis and improve clinical outcomes.
DOI: 10.6084/m9.figshare.29334471
title: Risk factors for periprosthetic femoral fractures following hip arthroplasty: a systematic review and meta-analysis

description: Periprosthetic femoral fracture (PPFF) is a serious complication following hip arthroplasty. The objective of this study was to determine the risk factors for PPFF following hip arthroplasty from existing studies. A comprehensive systematic search was performed in 4 databases: Pubmed, Embase, Web of Science, and Cochrane Library. The last search was carried out on 26th July 2024. We focused on identifying risk factors for PPFF following hip arthroplasty. Study eligibility required PPFF as an outcome and reporting of associated risk factors. Quality assessment was performed using the Newcastle-Ottawa Scale (NOS), with evidence certainty evaluated via Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). Meta-analyses employed both fixed-effect and random-effects models to pool odds ratios for identified risk factors. Out of 1553 articles, 36 studies published between 2006 and 2024 were included. Risk factors associated with increased incidence of PPFF ranges from very Low to High. High-quality evidence supported the use of uncemented stems (Odds Ratio [OR]: 3.36, 95% Confidence Interval [95% CI]: 3.02–3.74), major teaching hospital (OR: 2.04, 95% CI: 1.37–3.05). Moderate-quality evidence: female gender (OR: 1.60, 95% CI: 1.43–1.78), morbid obesity (OR: 1.44, 95% CI: 1.01–2.16), higher Deyo-Charlson index (OR: 1.44, 95% CI: 1.18–1.77), rheumatoid arthritis (OR: 1.89, 95% CI: 1.16–3.06), femoral Dorr type C (OR: 4.23, 95% CI: 2.82–6.33). Low evidence: age &gt; 70 years (OR: 1.67, 95% CI: 1.19–2.34), revision hip arthroplasty (OR: 2.60, 95% CI: 1.59–4.27). BMI &gt; 30 and history of hip surgery are not the risk (very low). Diagonized as osteoarthritis before surgery is a protective factor (OR:0.51, 95%CI: 0.40–0.65, quality = High). This meta-analysis provided some low-to-high evidence about the risk of PPFF following hip arthroplasty. It’s recommended that clinicians consider these risk factors when evaluating patients for hip arthroplasty and take steps to mitigate their impact, like optimizing patients health preoperatively, using cemented stems, and monitoring high-risk patients closely.