cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26840938
title: Prognostic impact of body composition in hepatocellular carcinoma patients with immunotherapy

description: This study aims to examine the possible relationship between body composition parameters, sarcopenia, and clinical outcomes in hepatocellular carcinoma (HCC) patients who received immune checkpoint inhibitor (ICI) treatment. Three online databases, including Embase, PubMed, and the Cochrane Library, were thoroughly searched for literature describing the relationship between body composition parameters, sarcopenia, and outcomes of ICI-treated HCC patients from the start of each database to 21 January 2024. The Newcastle-Ottawa Scale was used to rate the quality of the studies. The assessed outcomes included hazard ratio (HR) for OS and PFS, as well as odds ratio (OR) for ORR and DCR. This analysis included a total of 15 articles with a combined patient cohort of 1543 individuals. The results demonstrated that HCC patients with low skeletal muscle index (SMI) had significantly inferior OS (HR: 1.68, <i>p</i> &lt; 0.001), PFS (HR: 1.45, <i>p</i> &lt; 0.001), ORR (OR: 0.64, <i>p</i> = 0.044), and DCR (OR: 0.58, <i>p</i> = 0.009) compared to those with high SMI. The presence of sarcopenia in HCC patients was significantly related to poorer OS (HR: 1.63, <i>p</i> &lt; 0.001) and PFS (HR: 1.48, <i>p</i> &lt; 0.001), as well as a lower ORR (OR: 0.64, <i>p</i> = 0.020) and DCR (OR: 0.58, <i>p</i> = 0.007) in comparison to those without sarcopenia. Subgroup analysis demonstrated that these findings were consistent with the multivariate analysis. Moreover, high subcutaneous adipose index (SAI) levels were associated with better OS (HR: 0.46, <i>p</i> = 0.001) and PFS (HR: 0.68, <i>p</i> = 0.021) than those with low SAI levels. The presence of sarcopenia and low SMI in HCC patients undergoing treatment with ICIs was found to be related to inferior treatment response and reduced long-term effectiveness.
DOI: 10.6084/m9.figshare.26840938.v1
title: Prognostic impact of body composition in hepatocellular carcinoma patients with immunotherapy

description: This study aims to examine the possible relationship between body composition parameters, sarcopenia, and clinical outcomes in hepatocellular carcinoma (HCC) patients who received immune checkpoint inhibitor (ICI) treatment. Three online databases, including Embase, PubMed, and the Cochrane Library, were thoroughly searched for literature describing the relationship between body composition parameters, sarcopenia, and outcomes of ICI-treated HCC patients from the start of each database to 21 January 2024. The Newcastle-Ottawa Scale was used to rate the quality of the studies. The assessed outcomes included hazard ratio (HR) for OS and PFS, as well as odds ratio (OR) for ORR and DCR. This analysis included a total of 15 articles with a combined patient cohort of 1543 individuals. The results demonstrated that HCC patients with low skeletal muscle index (SMI) had significantly inferior OS (HR: 1.68, <i>p</i> &lt; 0.001), PFS (HR: 1.45, <i>p</i> &lt; 0.001), ORR (OR: 0.64, <i>p</i> = 0.044), and DCR (OR: 0.58, <i>p</i> = 0.009) compared to those with high SMI. The presence of sarcopenia in HCC patients was significantly related to poorer OS (HR: 1.63, <i>p</i> &lt; 0.001) and PFS (HR: 1.48, <i>p</i> &lt; 0.001), as well as a lower ORR (OR: 0.64, <i>p</i> = 0.020) and DCR (OR: 0.58, <i>p</i> = 0.007) in comparison to those without sarcopenia. Subgroup analysis demonstrated that these findings were consistent with the multivariate analysis. Moreover, high subcutaneous adipose index (SAI) levels were associated with better OS (HR: 0.46, <i>p</i> = 0.001) and PFS (HR: 0.68, <i>p</i> = 0.021) than those with low SAI levels. The presence of sarcopenia and low SMI in HCC patients undergoing treatment with ICIs was found to be related to inferior treatment response and reduced long-term effectiveness.
DOI: 10.6084/m9.figshare.27828906
title: The impact of using ChatGPT on academic writing among medical undergraduates

description: ChatGPT is widely used for writing tasks, yet its effects on medical students’ academic writing remain underexplored. This study aims to elucidate ChatGPT’s impact on academic writing efficiency and quality among medical students, while also evaluating students’ attitudes towards its use in academic writing. We collected systematic reviews from 130 third-year medical students and administered a questionnaire to assess ChatGPT usage and student attitudes. Three independent reviewers graded the papers using EASE guidelines, and statistical analysis compared articles generated with or without ChatGPT assistance across various parameters, with rigorous quality control ensuring survey reliability and validity. In this study, 33 students (25.8%) utilized ChatGPT for writing (ChatGPT group) and 95 (74.2%) did not (Control group). The ChatGPT group exhibited significantly higher daily technology use and prior experience with ChatGPT (<i>p</i> &lt; 0.05). Writing time was significantly reduced in the ChatGPT group (<i>p</i> = 0.04), with 69.7% completing tasks within 2–3 days compared to 48.4% in the control group. They also achieved higher article quality scores (<i>p</i> &lt; 0.0001) with improvements in completeness, credibility, and scientific content. Self-assessment indicated enhanced writing skills (<i>p</i> &lt; 0.01), confidence (<i>p</i> &lt; 0.001), satisfaction (<i>p</i> &lt; 0.001) and a positive attitude toward its future use in the ChatGPT group. Integrating ChatGPT in medical academic writing, with proper guidance, improves efficiency and quality, illustrating artificial intelligence’s potential in shaping medical education methodologies.
DOI: 10.6084/m9.figshare.27828906.v1
title: The impact of using ChatGPT on academic writing among medical undergraduates

description: ChatGPT is widely used for writing tasks, yet its effects on medical students’ academic writing remain underexplored. This study aims to elucidate ChatGPT’s impact on academic writing efficiency and quality among medical students, while also evaluating students’ attitudes towards its use in academic writing. We collected systematic reviews from 130 third-year medical students and administered a questionnaire to assess ChatGPT usage and student attitudes. Three independent reviewers graded the papers using EASE guidelines, and statistical analysis compared articles generated with or without ChatGPT assistance across various parameters, with rigorous quality control ensuring survey reliability and validity. In this study, 33 students (25.8%) utilized ChatGPT for writing (ChatGPT group) and 95 (74.2%) did not (Control group). The ChatGPT group exhibited significantly higher daily technology use and prior experience with ChatGPT (<i>p</i> &lt; 0.05). Writing time was significantly reduced in the ChatGPT group (<i>p</i> = 0.04), with 69.7% completing tasks within 2–3 days compared to 48.4% in the control group. They also achieved higher article quality scores (<i>p</i> &lt; 0.0001) with improvements in completeness, credibility, and scientific content. Self-assessment indicated enhanced writing skills (<i>p</i> &lt; 0.01), confidence (<i>p</i> &lt; 0.001), satisfaction (<i>p</i> &lt; 0.001) and a positive attitude toward its future use in the ChatGPT group. Integrating ChatGPT in medical academic writing, with proper guidance, improves efficiency and quality, illustrating artificial intelligence’s potential in shaping medical education methodologies.
DOI: 10.6084/m9.figshare.27203122
title: Necroptosis-based glioblastoma prognostic subtypes: implications for TME remodeling and therapy response

description: Glioblastoma (GBM) is an aggressive primary brain tumor with a high recurrence rate and poor prognosis. Necroptosis, a pathological hallmark of GBM, is poorly understood in terms of its role in prognosis, tumor microenvironment (TME) alteration, and immunotherapy. We assessed the expression of 55 necroptosis-related genes in GBM and normal brain tissues. We identified necroptosis-stratified clusters using Uni-Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression to establish the 10-gene Glioblastoma Necroptosis Index (GNI). GNI demonstrated significant prognostic efficacy in the TCGA dataset (<i>n</i> = 160) and internal validation dataset (<i>n</i> = 345) and in external validation cohorts (<i>n</i> = 591). The GNI-high subgroup displayed a mesenchymal phenotype, lacking the IDH1 mutation, and MGMT methylation. This subgroup was characterized by significant enrichment in inflammatory and humoral immune pathways with prominent cell adhesion molecules (CD44 and ICAM1), inflammatory cytokines (TGFB1, IL1B, and IL10), and chemokines (CX3CL1, CXCL9, and CCL5). The TME in this subgroup showed elevated infiltration of M0 macrophages, neutrophils, mast cells, and regulatory T cells. GNI-related genes appeared to limit macrophage polarization, as confirmed by immunohistochemistry and flow cytometry. The top 30% high-risk score subset exhibited increased CD8 T cell infiltration and enhanced cytolytic activity. GNI showed promise in predicting responses to immunotherapy and targeted treatment. Our study highlights the role of necroptosis-related genes in glioblastoma (GBM) and their effects on the tumor microenvironment and patient prognosis. TheGNI demonstrates potential as a prognostic marker and provides insights into immune characteristics and treatment responsiveness.
DOI: 10.6084/m9.figshare.27203122.v1
title: Necroptosis-based glioblastoma prognostic subtypes: implications for TME remodeling and therapy response

description: Glioblastoma (GBM) is an aggressive primary brain tumor with a high recurrence rate and poor prognosis. Necroptosis, a pathological hallmark of GBM, is poorly understood in terms of its role in prognosis, tumor microenvironment (TME) alteration, and immunotherapy. We assessed the expression of 55 necroptosis-related genes in GBM and normal brain tissues. We identified necroptosis-stratified clusters using Uni-Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression to establish the 10-gene Glioblastoma Necroptosis Index (GNI). GNI demonstrated significant prognostic efficacy in the TCGA dataset (<i>n</i> = 160) and internal validation dataset (<i>n</i> = 345) and in external validation cohorts (<i>n</i> = 591). The GNI-high subgroup displayed a mesenchymal phenotype, lacking the IDH1 mutation, and MGMT methylation. This subgroup was characterized by significant enrichment in inflammatory and humoral immune pathways with prominent cell adhesion molecules (CD44 and ICAM1), inflammatory cytokines (TGFB1, IL1B, and IL10), and chemokines (CX3CL1, CXCL9, and CCL5). The TME in this subgroup showed elevated infiltration of M0 macrophages, neutrophils, mast cells, and regulatory T cells. GNI-related genes appeared to limit macrophage polarization, as confirmed by immunohistochemistry and flow cytometry. The top 30% high-risk score subset exhibited increased CD8 T cell infiltration and enhanced cytolytic activity. GNI showed promise in predicting responses to immunotherapy and targeted treatment. Our study highlights the role of necroptosis-related genes in glioblastoma (GBM) and their effects on the tumor microenvironment and patient prognosis. TheGNI demonstrates potential as a prognostic marker and provides insights into immune characteristics and treatment responsiveness.
DOI: 10.6084/m9.figshare.25236920
title: Analysis of airway structural parameters in Han Chinese adults: a prospective cross-sectional study

description: Establishing reference ranges for central airway parameters and exploring their influencing factors in Han Chinese non-smoking adults. This prospective cross-sectional study was conducted on Han Chinese non-smoking adults who underwent chest CT scans at the Tongzhou Campus of Dongzhimen Hospital Affiliated with the Beijing University of Chinese Medicine between September 2022 and November 2022. The SYNAPSE 3D image analysis software was utilized, enabling the extraction of critical parameters such as central airway length, airway wall thickness (AWT), airway lumen area (ALA), and subcarinal angle (SCA). Pearson’s correlation coefficient analysis and multiple linear regression analysis methods were employed to evaluate the relationship between central airway parameters and age, sex, weight, and height. The study encompassed 888 Han Chinese non-smoking adults, comprising 456 females and 432 males. Significant sex differences were noted in central airway length, AWT, and ALA, with measurements in males exceeding those in females (<i>p</i> &lt; 0.01) with no significant difference in SCA. Correlation analyses unveiled relationships between central airway parameters and age, sex, weight, and height. During multiple linear regression analyses, no conclusive evidence emerged to demonstrate the independent or combined explanatory or predictive capacity of the aforementioned variables for central airway length and SCA. Although sex has a significant impact on AWT and ALA, its capability in explanation or prediction remains limited. The conclusions drawn from the primary analysis receive reinforcement from the outcomes of sensitivity analyses. Establishing the distribution range of central airway parameters in non-smoking Han Chinese adults. It observed significant sex differences in these parameters, except for the SCA. However, the study found that the predictive or explanatory power of age, sex, weight, and height for central airway parameters was either limited or non-significant.
DOI: 10.6084/m9.figshare.25236920.v1
title: Analysis of airway structural parameters in Han Chinese adults: a prospective cross-sectional study

description: Establishing reference ranges for central airway parameters and exploring their influencing factors in Han Chinese non-smoking adults. This prospective cross-sectional study was conducted on Han Chinese non-smoking adults who underwent chest CT scans at the Tongzhou Campus of Dongzhimen Hospital Affiliated with the Beijing University of Chinese Medicine between September 2022 and November 2022. The SYNAPSE 3D image analysis software was utilized, enabling the extraction of critical parameters such as central airway length, airway wall thickness (AWT), airway lumen area (ALA), and subcarinal angle (SCA). Pearson’s correlation coefficient analysis and multiple linear regression analysis methods were employed to evaluate the relationship between central airway parameters and age, sex, weight, and height. The study encompassed 888 Han Chinese non-smoking adults, comprising 456 females and 432 males. Significant sex differences were noted in central airway length, AWT, and ALA, with measurements in males exceeding those in females (<i>p</i> &lt; 0.01) with no significant difference in SCA. Correlation analyses unveiled relationships between central airway parameters and age, sex, weight, and height. During multiple linear regression analyses, no conclusive evidence emerged to demonstrate the independent or combined explanatory or predictive capacity of the aforementioned variables for central airway length and SCA. Although sex has a significant impact on AWT and ALA, its capability in explanation or prediction remains limited. The conclusions drawn from the primary analysis receive reinforcement from the outcomes of sensitivity analyses. Establishing the distribution range of central airway parameters in non-smoking Han Chinese adults. It observed significant sex differences in these parameters, except for the SCA. However, the study found that the predictive or explanatory power of age, sex, weight, and height for central airway parameters was either limited or non-significant.
DOI: 10.6084/m9.figshare.27066892
title: Prevalence of human papillomavirus and cervical lesions among elderly women: an unignored challenge to cervical cancer prevention

description: The prevalence of human papillomavirus (HPV) genotype and cervical neoplasia in women older than 64 years, who are outside the age demographic of cervical cancer screening in China, has been under-researched. This study conducts a retrospective analysis of women from a tertiary hospital in Guangzhou, with the aim to offer valuable insights for cervical cancer prevention and control in elderly women. The study incorporated 876 women, all aged 64 and above. In this age bracket, the prevalence rate of any HPV genotype was found to be 19.27%. The top six HR HPV genotypes were HPV 16, HPV 52, HPV 58, HPV 31, HPV 33, and HPV 18. The persistence rate of any HPV type over a 24-month period in this age group was as high as 33.33%. Among women over 64, around 16.47% of HPV-positive patients were diagnosed with cervical cancer. HPV 58 infection was the most substantial risk factor for histological CIN2+ (OR 3.556; 95% CI, 1.107–11.415; <i>p</i> = 0.032) in women over 64 years of age with HPV-positive/NILM status. In conclusion, the burden of HPV infection is significant among women over 64 years in Guangzhou. Re-evaluation of cervical cancer screening strategies for women after the age of 64 is imperative. Moreover, the HPV 16/18/52/58 genotype model could serve as an alternative triage approach to identify histological CIN2+ among elderly women with HPV-positive/NILM status. Elderly women exhibit an elevated risk of contracting HPV infection and developing cervical lesions.HPV 58 is notably associated with the progression of CIN2+ among women aged above 64 years with HPV-positive/NILM status.HPV 16/18/52/58 genotype model presents an alternative triage approach for identifying CIN2+ among women aged above 64 years with HPV-positive/NILM status. Elderly women exhibit an elevated risk of contracting HPV infection and developing cervical lesions. HPV 58 is notably associated with the progression of CIN2+ among women aged above 64 years with HPV-positive/NILM status. HPV 16/18/52/58 genotype model presents an alternative triage approach for identifying CIN2+ among women aged above 64 years with HPV-positive/NILM status.
DOI: 10.6084/m9.figshare.27066892.v1
title: Prevalence of human papillomavirus and cervical lesions among elderly women: an unignored challenge to cervical cancer prevention

description: The prevalence of human papillomavirus (HPV) genotype and cervical neoplasia in women older than 64 years, who are outside the age demographic of cervical cancer screening in China, has been under-researched. This study conducts a retrospective analysis of women from a tertiary hospital in Guangzhou, with the aim to offer valuable insights for cervical cancer prevention and control in elderly women. The study incorporated 876 women, all aged 64 and above. In this age bracket, the prevalence rate of any HPV genotype was found to be 19.27%. The top six HR HPV genotypes were HPV 16, HPV 52, HPV 58, HPV 31, HPV 33, and HPV 18. The persistence rate of any HPV type over a 24-month period in this age group was as high as 33.33%. Among women over 64, around 16.47% of HPV-positive patients were diagnosed with cervical cancer. HPV 58 infection was the most substantial risk factor for histological CIN2+ (OR 3.556; 95% CI, 1.107–11.415; <i>p</i> = 0.032) in women over 64 years of age with HPV-positive/NILM status. In conclusion, the burden of HPV infection is significant among women over 64 years in Guangzhou. Re-evaluation of cervical cancer screening strategies for women after the age of 64 is imperative. Moreover, the HPV 16/18/52/58 genotype model could serve as an alternative triage approach to identify histological CIN2+ among elderly women with HPV-positive/NILM status. Elderly women exhibit an elevated risk of contracting HPV infection and developing cervical lesions.HPV 58 is notably associated with the progression of CIN2+ among women aged above 64 years with HPV-positive/NILM status.HPV 16/18/52/58 genotype model presents an alternative triage approach for identifying CIN2+ among women aged above 64 years with HPV-positive/NILM status. Elderly women exhibit an elevated risk of contracting HPV infection and developing cervical lesions. HPV 58 is notably associated with the progression of CIN2+ among women aged above 64 years with HPV-positive/NILM status. HPV 16/18/52/58 genotype model presents an alternative triage approach for identifying CIN2+ among women aged above 64 years with HPV-positive/NILM status.
DOI: 10.6084/m9.figshare.27186317
title: Diagnostic accuracy of exhaled nitric oxide for the non-invasive identification of patients with fibrotic metabolic dysfunction-associated steatohepatitis

description: Fibrotic metabolic dysfunction-associated steatohepatitis (MASH) is a condition at risk of progressing to advanced liver disease. We examined whether an innovative exhaled nitric oxide (eNO) breath test (BT) can accurately diagnose fibrotic MASH without requiring blood tests. One hundred and forty-seven patients with MASH were recruited, and all tests were undertaken within 1 week of recruitment. With fibrotic MASH (NAS ≥ 4 and fibrosis stage ≥ 2) as the main outcome indicator, the diagnostic efficacy of eNO in identifying fibrotic MASH was compared to other validated models for advanced fibrosis requiring venesection, namely FAST, Agile 3<sup>+</sup>, and FIB-4 scores. The mean age was 40.36 ± 12.28 years, 73.5% were men. Mean body mass index was 28.83 ± 4.31 kg/m<sup>2</sup>. The proportion of fibrotic MASH was 29.25%. The area under the receiver operating curve for eNO in diagnosing fibrotic MASH was 0.737 [95% CI 0.650–0.823], which was comparable to FAST (0.751 [0.656–0.846]), Agile 3<sup>+</sup> (0.764 [0.670–0.858]), and FIB-4 (0.721 [0.620-0.821]) (all DeLong test <i>p</i> &gt; 0.05). A cut-off of eNO &lt;8.5 ppb gave a sensitivity of 86.0% and a negative predictive value of 88.5% for ruling-out fibrotic MASH. A cut-off of eNO &gt;13.5 ppb provided a specificity of 91.3% and a positive predictive value of 65.4% for ruling-in fibrotic MASH. Sensitivity analyses demonstrated that the diagnostic efficacy of eNO was similar across characteristics such as age. Moreover, adding vibration-controlled transient elastography-LSM (liver stiffness measurement) reduced the uncertainty interval from 46.9% to 39.5%. The eNO-BT is a promising simple test for non-invasively identifying fibrotic MASH, and its performance is further improved by adding LSM measurement.