cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26893598.v1
title: Assessment of <i>LINC-PINT</i> genetic polymorphisms and esophageal squamous cell carcinoma risk in the Hainan Han population

description: Esophageal squamous cell carcinoma (ESCC) is a malignant tumor with high incidence and mortality rates worldwide. This study aimed to investigate the correlation between <i>LINC-PINT</i> polymorphisms and ESCC risk in the Hainan Han population. A total of 391 patients with ESCC and 452 healthy controls were enrolled to evaluate the effect of <i>LINC-PINT</i> SNPs (single nucleotide polymorphisms) on ESCC susceptibility. Associations were evaluated by calculating odds ratios (OR) and 95% confidence intervals (CIs). Multifactor dimensionality reduction analysis was performed to explore the association between SNP-SNP interactions and ESCC susceptibility. We further determined the correlation between clinical indicators and SNP in patients with ESCC. Our study showed that rs157916 (OR 0.63, <i>p</i> = 0.011) and rs157928 (OR 0.80, <i>p</i> = 0.021) were associated with a decreased risk of ESCC. Stratified analysis indicated that rs157916 could decrease the risk of ESCC in people aged &gt;64 years, in males, and non-drinkers (OR 0.58, <i>p</i> = 0.042; OR 0.58, <i>p</i> = 0.010; OR 0.62, <i>p</i> = 0.025, respectively). Rs16873842 was related to a decreased risk of ESCC in males (OR 0.70, <i>p</i> = 0.015). Rs7801029 was associated with ESCC risk in females (OR 0.39, <i>p</i> = 0.033) and non-drinkers (OR 0.68, <i>p</i> = 0.040). Rs7781295 decreased the ESCC risk in smokers (OR 0.58, <i>p</i> = 0.046) and drinkers (OR 0.58, <i>p</i> = 0.046). In addition, rs157928 played a protective role in ESCC risk in females (OR 0.39, <i>p</i> = 0.033) and non-smokers (OR 0.32, <i>p</i> = 0.006). Additionally, the best predictive model for ESCC was a combination of rs157916, rs16873842, rs7801029, rs7781295, rs28662387, and rs157928. Our study revealed that <i>LINC-PINT</i> polymorphisms were associated with ESCC risk.
DOI: 10.6084/m9.figshare.27186174
title: Stable or at least once HER2-low status during neoadjuvant chemotherapy confers survival benefit in patients with breast cancer

description: Temporal heterogeneity in human epidermal growth factor receptor 2 (HER2) status may be associated with the prognosis of breast cancer. We aimed to clarify the relationship of HER2-low transition during neoadjuvant therapy with survival outcomes under the new classification of HER2 status. This retrospective study was conducted based on the prospective database of breast cancer patients treated with neoadjuvant therapy from September 2013 to August 2020. This analysis enrolled 185 patients, including 44 patients with HER2-zero tumours, 93 patients with HER2-low tumours and 48 patients with HER2-positive tumours after neoadjuvant therapy. Nearly, 57.6% of HER2-zero tumours turned into HER2-low tumours after neoadjuvant therapy, while 25.0% of HER2-low patients changed to HER2-zero or HER2-positive tumours. We found that at least once diagnosis as HER2-low breast cancer was related to hormone receptor status (<i>p</i> &lt; .001) and Ki-67 expression (<i>p</i> = .036). Patients ever diagnosed as HER2-low tumours had favourable clinicopathological features (less Ki-67 expression, lower pathological staging, etc.) as well as significantly better locoregional relapse-free survival (LRFS; <i>p</i> = .007) and overall survival (OS; <i>p</i> = .026) compared with those never exhibiting HER2-low expression. Furthermore, the 6-year OS rates were 94.2% (95% confidence interval (CI) 83.1–98.1), 88.7% (74.4–95.2) and 78.1% (65.4–86.6) for patients with stable, once and none HER2-low expression, respectively (adjusted HR, 0.514 [95%CI, 0.294–0.897], <i>p</i> = .019). Our study first indicated in patients across all expression levels of HER2 that stable or at least once HER2-low status may confer favourable attributes including less malignant biological behaviour and long-term survival benefit for breast cancer receiving neoadjuvant therapy. Stable or at least once HER2-low status may confer favourable attributes including less malignant biological behaviour and long-term survival benefit for breast cancer receiving neoadjuvant therapy.HER2-low expression was highly instable during disease evolution from primary lesion to residual tumour and was associated with hormone receptor status, which warrants HER2 re-test in residual lesion, especially for patients with HER2-zero disease at initial diagnosis, so as to give a clear picture of not only prognostic significance but also treatment availability. Stable or at least once HER2-low status may confer favourable attributes including less malignant biological behaviour and long-term survival benefit for breast cancer receiving neoadjuvant therapy. HER2-low expression was highly instable during disease evolution from primary lesion to residual tumour and was associated with hormone receptor status, which warrants HER2 re-test in residual lesion, especially for patients with HER2-zero disease at initial diagnosis, so as to give a clear picture of not only prognostic significance but also treatment availability.
DOI: 10.6084/m9.figshare.27186174.v1
title: Stable or at least once HER2-low status during neoadjuvant chemotherapy confers survival benefit in patients with breast cancer

description: Temporal heterogeneity in human epidermal growth factor receptor 2 (HER2) status may be associated with the prognosis of breast cancer. We aimed to clarify the relationship of HER2-low transition during neoadjuvant therapy with survival outcomes under the new classification of HER2 status. This retrospective study was conducted based on the prospective database of breast cancer patients treated with neoadjuvant therapy from September 2013 to August 2020. This analysis enrolled 185 patients, including 44 patients with HER2-zero tumours, 93 patients with HER2-low tumours and 48 patients with HER2-positive tumours after neoadjuvant therapy. Nearly, 57.6% of HER2-zero tumours turned into HER2-low tumours after neoadjuvant therapy, while 25.0% of HER2-low patients changed to HER2-zero or HER2-positive tumours. We found that at least once diagnosis as HER2-low breast cancer was related to hormone receptor status (<i>p</i> &lt; .001) and Ki-67 expression (<i>p</i> = .036). Patients ever diagnosed as HER2-low tumours had favourable clinicopathological features (less Ki-67 expression, lower pathological staging, etc.) as well as significantly better locoregional relapse-free survival (LRFS; <i>p</i> = .007) and overall survival (OS; <i>p</i> = .026) compared with those never exhibiting HER2-low expression. Furthermore, the 6-year OS rates were 94.2% (95% confidence interval (CI) 83.1–98.1), 88.7% (74.4–95.2) and 78.1% (65.4–86.6) for patients with stable, once and none HER2-low expression, respectively (adjusted HR, 0.514 [95%CI, 0.294–0.897], <i>p</i> = .019). Our study first indicated in patients across all expression levels of HER2 that stable or at least once HER2-low status may confer favourable attributes including less malignant biological behaviour and long-term survival benefit for breast cancer receiving neoadjuvant therapy. Stable or at least once HER2-low status may confer favourable attributes including less malignant biological behaviour and long-term survival benefit for breast cancer receiving neoadjuvant therapy.HER2-low expression was highly instable during disease evolution from primary lesion to residual tumour and was associated with hormone receptor status, which warrants HER2 re-test in residual lesion, especially for patients with HER2-zero disease at initial diagnosis, so as to give a clear picture of not only prognostic significance but also treatment availability. Stable or at least once HER2-low status may confer favourable attributes including less malignant biological behaviour and long-term survival benefit for breast cancer receiving neoadjuvant therapy. HER2-low expression was highly instable during disease evolution from primary lesion to residual tumour and was associated with hormone receptor status, which warrants HER2 re-test in residual lesion, especially for patients with HER2-zero disease at initial diagnosis, so as to give a clear picture of not only prognostic significance but also treatment availability.
DOI: 10.6084/m9.figshare.27097711
title: Evidence and potential mechanism of action of indigo naturalis and its active components in the treatment of psoriasis

description: Indigo naturalis is effective against psoriasis. Indigo, indirubin and tryptanthrin, the main active components of indigo naturalis, have anti-inflammatory properties. To evaluate the efficacy and safety of indigo naturalis and its active components in the treatment of psoriasis. Seven databases were searched for studies of indigo naturalis and its active components for the treatment of psoriasis. The findings demonstrated a higher response rate in the Chinese herbal medicine (CHM) formula groups than in the control group for Psoriasis Area and Severity Index 60 (PASI60) (Rate difference [RD] = 0.22, <i>p</i> &lt; .0001). Among all adverse events, only the incidence of gastrointestinal adverse reactions was higher in the CHM formula group than in the control group (RD = 0.09, <i>p</i> &lt; .0001). In preclinical <i>in vivo</i> studies, indirubin showed better performance in improving the phenotype of psoriasis-like mice compared to that in controls, including the PASI score (mean difference [MD] = −3.58, <i>p</i> &lt; .0001), epidermal thickness (MD = −29.13, <i>p</i> &lt; .0001), interleukin-(IL) 17 A mRNA expression (MD = −2.27, <i>p</i> = .0066) and IL-23 mRNA (MD = −5.36, <i>p</i> = .01). Indigo naturalis combined with conventional treatments is useful for treating psoriasis. Indigo naturalis display anti-proliferative, anti-inflammatory and anti-angiogenic effects by regulating the TAK1, JAK3/STAT3, Wnt/β-catenin, Akt/PKB, FAK and AP-1/c-Jun pathway. Indigo naturalis, a Chinese herb and its main active components, indigo, indirubin and tryptanthrin are effective in treating psoriasis.Indigo naturalis, indirubin, indigo and tryptanthrin have anti-proliferative, anti-inflammatory and anti-angiogenic effects via regulating the TAK1, JAK3/STAT3, Wnt/β-catenin, Akt/PKB, FAK and AP-1/c-Jun pathways. Indigo naturalis, a Chinese herb and its main active components, indigo, indirubin and tryptanthrin are effective in treating psoriasis. Indigo naturalis, indirubin, indigo and tryptanthrin have anti-proliferative, anti-inflammatory and anti-angiogenic effects via regulating the TAK1, JAK3/STAT3, Wnt/β-catenin, Akt/PKB, FAK and AP-1/c-Jun pathways.
DOI: 10.6084/m9.figshare.27097711.v1
title: Evidence and potential mechanism of action of indigo naturalis and its active components in the treatment of psoriasis

description: Indigo naturalis is effective against psoriasis. Indigo, indirubin and tryptanthrin, the main active components of indigo naturalis, have anti-inflammatory properties. To evaluate the efficacy and safety of indigo naturalis and its active components in the treatment of psoriasis. Seven databases were searched for studies of indigo naturalis and its active components for the treatment of psoriasis. The findings demonstrated a higher response rate in the Chinese herbal medicine (CHM) formula groups than in the control group for Psoriasis Area and Severity Index 60 (PASI60) (Rate difference [RD] = 0.22, <i>p</i> &lt; .0001). Among all adverse events, only the incidence of gastrointestinal adverse reactions was higher in the CHM formula group than in the control group (RD = 0.09, <i>p</i> &lt; .0001). In preclinical <i>in vivo</i> studies, indirubin showed better performance in improving the phenotype of psoriasis-like mice compared to that in controls, including the PASI score (mean difference [MD] = −3.58, <i>p</i> &lt; .0001), epidermal thickness (MD = −29.13, <i>p</i> &lt; .0001), interleukin-(IL) 17 A mRNA expression (MD = −2.27, <i>p</i> = .0066) and IL-23 mRNA (MD = −5.36, <i>p</i> = .01). Indigo naturalis combined with conventional treatments is useful for treating psoriasis. Indigo naturalis display anti-proliferative, anti-inflammatory and anti-angiogenic effects by regulating the TAK1, JAK3/STAT3, Wnt/β-catenin, Akt/PKB, FAK and AP-1/c-Jun pathway. Indigo naturalis, a Chinese herb and its main active components, indigo, indirubin and tryptanthrin are effective in treating psoriasis.Indigo naturalis, indirubin, indigo and tryptanthrin have anti-proliferative, anti-inflammatory and anti-angiogenic effects via regulating the TAK1, JAK3/STAT3, Wnt/β-catenin, Akt/PKB, FAK and AP-1/c-Jun pathways. Indigo naturalis, a Chinese herb and its main active components, indigo, indirubin and tryptanthrin are effective in treating psoriasis. Indigo naturalis, indirubin, indigo and tryptanthrin have anti-proliferative, anti-inflammatory and anti-angiogenic effects via regulating the TAK1, JAK3/STAT3, Wnt/β-catenin, Akt/PKB, FAK and AP-1/c-Jun pathways.
DOI: 10.6084/m9.figshare.27125358
title: Integrating cellular experiments, single-cell sequencing, and machine learning to identify endoplasmic reticulum stress biomarkers in idiopathic pulmonary fibrosis

description: Idiopathic Pulmonary Fibrosis (IPF) presents a severe respiratory challenge with a poor prognosis due to the lack of reliable biomarkers. Recent evidence suggests that Endoplasmic Reticulum Stress (ERS) may be associated with IPF pathogenesis. This study focuses on uncovering ERS-associated biomarkers for IPF. Sequencing data from diverse datasets were analyzed, utilizing differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Endoplasmic Reticulum Stress (ERS)-related genes were extracted from the GeneCards database. Hub genes were identified through Protein-Protein Interaction (PPI) analysis. Diagnostic and prognostic models were developed using machine learning algorithms and validated across both training and validation sets. Additionally, techniques such as Cell-type Identification by Estimating Relative Subsets of RNA Transcripts and single-cell RNA sequencing were employed to identify potential IPF-related cells. These findings were further investigated to elucidate their underlying mechanisms through <i>in vitro</i> experiments. Differentially expressed genes, WGCNA-identified blue module genes, and ERS-related genes extracted from the GeneCards database were intersected, and the resulting genes were used to construct diagnostic and prognostic models. Validation using multiple datasets indicated that both the diagnostic and prognostic models possess strong predictive capabilities. PPI analysis highlighted SPP1 as a potential hub gene in IPF. Moreover, M2 macrophages were found in higher quantities in the lung tissue of IPF patients, with a significant increase in SPP1-expressing M2 macrophages compared to the control group. <i>In vitro</i> experiments demonstrated that exogenous SPP1 inhibited the proliferation and migration of M2 macrophages and promoted apoptosis within a certain concentration range. This study identifies ERS-related biomarkers in IPF, highlighting SPP1 and M2 macrophages. The resulting diagnostic and prognostic models offer strong predictive capabilities, unveiling new therapeutic avenues.
DOI: 10.6084/m9.figshare.27125358.v1
title: Integrating cellular experiments, single-cell sequencing, and machine learning to identify endoplasmic reticulum stress biomarkers in idiopathic pulmonary fibrosis

description: Idiopathic Pulmonary Fibrosis (IPF) presents a severe respiratory challenge with a poor prognosis due to the lack of reliable biomarkers. Recent evidence suggests that Endoplasmic Reticulum Stress (ERS) may be associated with IPF pathogenesis. This study focuses on uncovering ERS-associated biomarkers for IPF. Sequencing data from diverse datasets were analyzed, utilizing differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Endoplasmic Reticulum Stress (ERS)-related genes were extracted from the GeneCards database. Hub genes were identified through Protein-Protein Interaction (PPI) analysis. Diagnostic and prognostic models were developed using machine learning algorithms and validated across both training and validation sets. Additionally, techniques such as Cell-type Identification by Estimating Relative Subsets of RNA Transcripts and single-cell RNA sequencing were employed to identify potential IPF-related cells. These findings were further investigated to elucidate their underlying mechanisms through <i>in vitro</i> experiments. Differentially expressed genes, WGCNA-identified blue module genes, and ERS-related genes extracted from the GeneCards database were intersected, and the resulting genes were used to construct diagnostic and prognostic models. Validation using multiple datasets indicated that both the diagnostic and prognostic models possess strong predictive capabilities. PPI analysis highlighted SPP1 as a potential hub gene in IPF. Moreover, M2 macrophages were found in higher quantities in the lung tissue of IPF patients, with a significant increase in SPP1-expressing M2 macrophages compared to the control group. <i>In vitro</i> experiments demonstrated that exogenous SPP1 inhibited the proliferation and migration of M2 macrophages and promoted apoptosis within a certain concentration range. This study identifies ERS-related biomarkers in IPF, highlighting SPP1 and M2 macrophages. The resulting diagnostic and prognostic models offer strong predictive capabilities, unveiling new therapeutic avenues.
DOI: 10.6084/m9.figshare.25567188
title: Identification of pathogen composition in a Chinese population with iatrogenic and native vertebral osteomyelitis by using mNGS

description: Early antimicrobial therapy is crucial regarding the prognosis of vertebral osteomyelitis, but early pathogen diagnosis remains challenging. In this study, we aimed to differentiate the types of pathogens in iatrogenic vertebral osteomyelitis (IVO) and native vertebral osteomyelitis (NVO) to guide early antibiotic treatment. A total of 145 patients, who had confirmed spinal infection and underwent metagenomic next-generation sequencing (mNGS) testing, were included, with 114 in the NVO group and 31 in the IVO group. Using mNGS, we detected and classified 53 pathogens in the 31 patients in the IVO group and 169 pathogens in the 114 patients in the NVO group. To further distinguish IVO from NVO, we employed machine learning algorithms to select serum biomarkers and developed a nomogram model. The results revealed that the proportion of the Actinobacteria phylum in the NVO group was approximately 28.40%, which was significantly higher than the 15.09% in the IVO group. Conversely, the proportion of the Firmicutes phylum (39.62%) in the IVO group was markedly increased compared to the 21.30% in the NVO group. Further genus-level classification demonstrated that Staphylococcus was the most common pathogen in the IVO group, whereas Mycobacterium was predominant in the NVO group. Through LASSO regression and random forest algorithms, we identified 5 serum biomarkers including percentage of basophils (BASO%), percentage of monocytes (Mono%), platelet volume (PCT), globulin (G), activated partial thromboplastin time (APTT) for distinguishing IVO from NVO. Based on these biomarkers, we established a nomogram model capable of accurately discriminating between the two conditions. The results of this study hold promise in providing valuable guidance to clinical practitioners for the differential diagnosis and early antimicrobial treatment of vertebral osteomyelitis.
DOI: 10.6084/m9.figshare.25567188.v1
title: Identification of pathogen composition in a Chinese population with iatrogenic and native vertebral osteomyelitis by using mNGS

description: Early antimicrobial therapy is crucial regarding the prognosis of vertebral osteomyelitis, but early pathogen diagnosis remains challenging. In this study, we aimed to differentiate the types of pathogens in iatrogenic vertebral osteomyelitis (IVO) and native vertebral osteomyelitis (NVO) to guide early antibiotic treatment. A total of 145 patients, who had confirmed spinal infection and underwent metagenomic next-generation sequencing (mNGS) testing, were included, with 114 in the NVO group and 31 in the IVO group. Using mNGS, we detected and classified 53 pathogens in the 31 patients in the IVO group and 169 pathogens in the 114 patients in the NVO group. To further distinguish IVO from NVO, we employed machine learning algorithms to select serum biomarkers and developed a nomogram model. The results revealed that the proportion of the Actinobacteria phylum in the NVO group was approximately 28.40%, which was significantly higher than the 15.09% in the IVO group. Conversely, the proportion of the Firmicutes phylum (39.62%) in the IVO group was markedly increased compared to the 21.30% in the NVO group. Further genus-level classification demonstrated that Staphylococcus was the most common pathogen in the IVO group, whereas Mycobacterium was predominant in the NVO group. Through LASSO regression and random forest algorithms, we identified 5 serum biomarkers including percentage of basophils (BASO%), percentage of monocytes (Mono%), platelet volume (PCT), globulin (G), activated partial thromboplastin time (APTT) for distinguishing IVO from NVO. Based on these biomarkers, we established a nomogram model capable of accurately discriminating between the two conditions. The results of this study hold promise in providing valuable guidance to clinical practitioners for the differential diagnosis and early antimicrobial treatment of vertebral osteomyelitis.
DOI: 10.6084/m9.figshare.26531508.v1
title: Benefits of intensive lipid-lowering therapies in patients with acute coronary syndrome: a systematic review and meta-analysis

description: Previous meta-analyses have investigated the efficacy of lipid-lowering therapies for atherosclerotic cardiovascular disease; however, few have focused on patients with acute coronary syndrome (ACS). This meta-analysis aimed to compare the benefits of intensive lipid-lowering therapy with those of background statin therapy in patients with ACS. Searches were performed on PubMed, Embase, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases for articles published until April 13, 2023. Randomized controlled trials that compared intensive lipid-lowering therapies and background statin therapies in patients with prior ACS and recorded the outcome of three-point major cardiovascular events (MACE) were included. The risk ratio (RR) with 95% confidence interval (CI) was used as a measure of primary and secondary outcomes. Nine trials involving 38,640 patients with ACS were identified. Pooled results suggested that intensive lipid-lowering therapies are associated with a reduction in the risk of three-point MACE (RR, 0.88; 95% CI, 0.83–0.94; <i>p</i> &lt; 0.001), recurrent ACS (RR, 0.82; 95% CI, 0.71–0.96; <i>p</i> = 0.013), nonfatal myocardial infarction (MI) (RR, 0.87; 95% CI, 0.81–0.93; <i>p</i> &lt; 0.001), stroke (RR, 0.83; 95% CI, 0.73–0.94; <i>p</i> = 0.003), and unstable angina-related hospitalization (RR, 0.57; 95% CI, 0.33–0.99; <i>p</i> = 0.046), but not all-cause mortality (RR, 0.94; 95% CI, 0.82–1.07; <i>p</i> = 0.329), cardiovascular disease-related mortality (RR, 0.96; 95% CI, 0.88–1.06; <i>p</i> = 0.457) or coronary revascularization (RR, 0.89; 95% CI, 0.79–1.00; <i>p</i> = 0.057). Intensive lipid-lowering therapies may reduce the risk of three-point MACE, recurrent ACS, nonfatal MI, stroke, and hospitalization for unstable angina in patients with ACS undergoing background statin therapy. These results may assist in clinical decision-making for the secondary prevention of cardiovascular events to initiate intensive lipid-lowering therapies immediately after ACS.