bluuebunny/crossref_metadata_2025_split huggingface dataset:
Endogenous testosterone density associates with predictors of tumor upgrading and disease progression in the low through favorable intermediate prostate cancer risk categories: analysis of risk factors and clinical implications
Authors: Porcaro Antonio B. , Bianchi Alberto , Gallina Sebastian , Ditonno Francesco , Ornaghi Paola I. , Serafin Emanuele , Tafuri Alessandro , Panunzio Andrea , Cerrato Clara , Vidiri Stefano , D’Aietti Damiano , Mazzucato Giovanni , Rizzetto Riccardo , Amigoni Nelia , De Marco Vincenzo , Migliorini Filippo , Zecchini Antoniolli Stefano , Brunelli Matteo , Siracusano Salvatore , Cerruto Maria Angela , Antonelli Alessandro 
Published: June 2023

Abstract
Background
The study aimed to test the hypothesis that endogenous testosterone density (ETD), in the low through favorable intermediate PCa risk classes patients undergoing surgery, might be associated with disease progression.

Materials and methods
ETD, PSAD, and percentage of biopsy positive cores density (BPCD) were calculated in relation to prostate volume (PV). Tumor load density (TLD) was estimated as the tumor load (TL) ratio to prostate weight. ET was considered low if < 230 ng/dL. Tumor upgrading (ISUP > 2), upstaging (pT > 2) and their related features were investigated.

Results
433 patients were included, 249 (57.5%) from the favorable intermediate-risk class. Upgrading occurred in 168 (38.8%) cases and upstaging in 62 (14.3%). ETD above the median (9.9 ng/(dL x mL)), was discriminated by PSAD (AUC = 0.719; 95% CI: 0.671–0.766; p < 0.0001), BPCD (AUC = 0.721; 95% CI: 0.673–0.768; p < 0.0001), TLD (AUC = 0.674; 95% CI: 0.624–0.724; p < 0.0001) with accuracy improved by the multivariable model (AUC = 0.798; 95% CI: 0.724–0.811; p < 0.0001). In linear multivariable models as ETD increased, so did TLD (rc = 0.019; 95% CI: 0.014; 0.025; p < 0.0001), further increased by low ET (rc = 0.097; 95% CI: 0.017; 0.176; p = 0.017). After adjusting for clinical and pathological features, ETD correlated with TLD above the first quartile. Disease progression occurred in 43 (11.9%) patients, independently predicted by PSAD (hazard ratio, HR = 99.906; 95% CI: 6.519–1531.133; p = 0.001) and tumor upgrading (HR = 3.586; 95% CI: 3.586–6.863; p < 0.0001).

Conclusions
ETD was associated with unfavorable PCa, and men with tumor upgrading were at increased risk of disease progression. ETD was related to predictors of PCa progression and could provide pivotal biological information about aggressive disease.
Comprehensive analysis of KLF2 as a prognostic biomarker associated with fibrosis and immune infiltration in advanced hepatocellular carcinoma
Authors: Chen Xue-Qin , Ma Jie , Xu Di , Xiang Zuo-Lin 
Published: June 2023

Abstract
Purpose
Most Hepatocellular carcinoma (HCC) patients are in advanced or metastatic stage at the time of diagnosis. Prognosis for advanced HCC patients is dismal. This study was based on our previous microarray results, and aimed to explore the promising diagnostic and prognostic markers for advanced HCC by focusing on the important function of KLF2.

Methods
The Cancer Genome Atlas (TCGA), Cancer Genome Consortium database (ICGC), and the Gene Expression Comprehensive Database (GEO) provided the raw data of this study research. The cBioPortal platform, CeDR Atlas platform, and the Human Protein Atlas (HPA) website were applied to analyze the mutational landscape and single-cell sequencing data of KLF2. Basing on the results of single-cell sequencing analyses, we further explored the molecular mechanism of KLF2 regulation in the fibrosis and immune infiltration of HCC.

Results
Decreased KLF2 expression was discovered to be mainly regulated by hypermethylation, and indicated a poor prognosis of HCC. Single-cell level expression analyses revealed KLF2 was highly expressed in immune cells and fibroblasts. The function enrichment analysis of KLF2 targets indicated the crucial association between KLF2 and tumor matrix. 33-genes related with cancer associated fibroblasts (CAFs) were collected to identify the significant association of KLF2 with fibrosis. And SPP1 was validated as a promising prognostic and diagnostic marker for advanced HCC patients. CXCR6 CD8+ T cells were noted as a predominant proportion in the immune microenvironment, and T cell receptor CD3D was discovered to be a potential therapeutic biomarker for HCC immunotherapy.

Conclusion
This study identified that KLF2 is an important factor promoting HCC progression by affecting the fibrosis and immune infiltration, highlighting its great potential as a novel prognostic biomarker for advanced HCC.
Multiomics data analyses to identify SLC25A17 as a novel biomarker to predict the prognosis and immune microenvironment in head and neck squamous cell carcinoma
Authors: Shi Yunbin , Huang Juntao , Hu Yi , Shen Yi 
Published: June 2023

Abstract
Objective
This study aims to explore the predictive value of SLC25A17 in the prognosis and tumor microenvironment (TME) of patients with head and neck squamous cell carcinoma (HNSCC) and to provide ideas for individual clinical treatment.

Methods
A pancancer analysis of the differential expression of SLC25A17 among different tumors was first conducted via the TIMER 2.0 database. Subsequently, the expression of SLC25A17 and related clinical information of HNSCC patients were obtained from the TCGA database, and patients were divided into two groups according to the median value of SLC25A17 expression. K‒M survival analysis was conducted to compare the overall survival (OS) and progression-free survival (PFS) between the groups. The Wilcoxon test was used to compare the distribution of SLC25A17 in different clinical characteristics, and univariate Cox and multivariate Cox analyses were performed to analyze independent prognostic factors to establish a predictive nomogram. Calibration curves were generated to verify the reliability of predicting 1-year, 3-year and 5-year survival rates and another cohort (GSE65858) was used for external validation. Gene set enrichment analysis was conducted to compare the enriched pathways, and the immune microenvironment was assessed using the CIBERSORT and estimate packages. Furthermore, the expression levels of SLC25A17 in immune cells were also analyzed with single-cell RNA-seq via the TISCH. Moreover, the immunotherapeutic response and chemotherapy drug sensitivity were compared between the two groups to guide precise treatment. The TIDE database was applied to predict the possibility of immune escape in the TCGA-HNSC cohort.

Results
Compared with normal samples, the expression of SLC25A17 was much higher in HNSCC tumor samples. For patients with high SLC25A17 expression, the OS and PFS were shorter than those with low SLC25A17 expression, indicating a worse prognosis. The expression of SLC25A17 varied in different clinical features. Univariate Cox and multivariate COX analyses showed that SLC25A17, age, and lymph node metastasis are independent prognostic risk factors for HNSCC, and the survival prediction model based on these factors had reliable predictive value. Patients in the low-expression group exhibited more immune cell infiltration, higher TME scores, higher IPS scores and lower TIDE scores than those in the high-expression groups, suggesting better immunotherapeutic response with lower SLC25A17 expression. Moreover, patients in the high-expression group were more sensitive to chemotherapy.

Conclusions
SLC25A17 can effectively predict the prognosis of HNSCC patients and could be a precise individual-targeted indicator for the treatment of HNSCC patients.
The complete chloroplast genome of Ulmus mianzhuensis with insights into structural variations, adaptive evolution, and phylogenetic relationships of Ulmus (Ulmaceae)
Authors: Lin Nan , Liu Rui , Wang Yakun , Guo Peng , Wang Yihan , Liu Yanpei , Shang Fude 
Published: June 2023

Abstract
Background
Ulmus mianzhuensis is an endemic tree species in China with high ornamental and economic value. Currently, little is known regarding its genomic architecture, phylogenetic position, or adaptive evolution. Here, we sequenced the complete chloroplast genome (cp genome) of U. mianzhuensis and further compared the variations in gene organization and structure within Ulmus species to define their genomic evolution, then reconstructed the phylogenomic relationship of 31 related Ulmus species to explore the systematic position of U. mianzhuensis and the utility of cp genome for resolving phylogenetics among Ulmus species.

Results
Our results revealed that all the Ulmus species exhibited a typical quadripartite structure, with a large single copy (LSC) region of 87,170 − 88,408 bp, a small single copy (SSC) region of 18,650 − 19,038 bp and an inverted repeat (IR) region of 26,288 − 26,546 bp. Within Ulmus species, gene structure and content of cp genomes were highly conserved, although slight variations were found in the boundary of SC/IR regions. Moreover, genome-wide sliding window analysis uncovered the variability of ndhC-trnV-UAC, ndhF-rpl32, and psbI-trnS-GCU were higher among 31 Ulmus that may be useful for the population genetics and potential DNA barcodes. Two genes (rps15 and atpF) were further detected under a positive selection of Ulmus species. Comparative phylogenetic analysis based on the cp genome and protein-coding genes revealed consistent topology that U. mianzhuensis is a sister group to U. parvifolia (sect. Microptelea) with a relatively low-level nucleotide variation of the cp genome. Additionally, our analyses also found that the traditional taxonomic system of five sections in Ulmus is not supported by the current phylogenomic topology with a nested evolutionary relationship between sections.

Conclusions
Features of the cp genome length, GC content, organization, and gene order were highly conserved within Ulmus. Furthermore, molecular evidence from the low variation of the cp genome suggested that U. mianzhuensis should be merged into U. parvifolia and regarded as a subspecies of U. parvifolia. Overall, we demonstrated that the cp genome provides valuable information for understanding the genetic variation and phylogenetic relationship in Ulmus.
A scoping review of statistical methods in studies of biomarker-related treatment heterogeneity for breast cancer
Authors: Sollfrank L , Linn SC , Hauptmann M , Jóźwiak K 
Published: June 2023

AbstractBackgroundMany scientific papers are published each year and substantial resources are spent to develop biomarker-based tests for precision oncology. However, only a handful of tests is currently used in daily clinical practice, since development is challenging. In this situation, the application of adequate statistical methods is essential, but little is known about the scope of methods used.MethodsA PubMed search identified clinical studies among women with breast cancer comparing at least two different treatment groups, one of which chemotherapy or endocrine treatment, by levels of at least one biomarker. Studies presenting original data published in 2019 in one of 15 selected journals were eligible for this review. Clinical and statistical characteristics were extracted by three reviewers and a selection of characteristics for each study was reported.ResultsOf 164 studies identified by the query, 31 were eligible. Over 70 different biomarkers were evaluated. Twenty-two studies (71%) evaluated multiplicative interaction between treatment and biomarker. Twenty-eight studies (90%) evaluated either the treatment effect in biomarker subgroups or the biomarker effect in treatment subgroups. Eight studies (26%) reported results for one predictive biomarker analysis, while the majority performed multiple evaluations, either for several biomarkers, outcomes and/or subpopulations. Twenty-one studies (68%) claimed to have found significant differences in treatment effects by biomarker level. Fourteen studies (45%) mentioned that the study was not designed to evaluate treatment effect heterogeneity.ConclusionsMost studies evaluated treatment heterogeneity via separate analyses of biomarker-specific treatment effects and/or multiplicative interaction analysis. There is a need for the application of more efficient statistical methods to evaluate treatment heterogeneity in clinical studies.
Do outcomes for patients with hospital-acquired Acute Kidney Injury (H-AKI) vary across specialties in England?
Authors: Magadi Winnie , Peracha Javeria , McKane William S , Savino Manuela , Braddon Fiona , Steenkamp Retha , Nitsch Dorothea 
Published: June 2023

Abstract
Background
Acute Kidney Injury (AKI) is a common and serious clinical syndrome. There is increasing recognition of heterogeneity in observed AKI across different clinical settings. In this analysis we have utilised a large national dataset to outline, for the first time, differences in burden of hospital acquired AKI (H-AKI) and mortality risk across different treatment specialities in the English National Health Service (NHS).

Methods
A retrospective observational study was conducted using a large national dataset of patients who triggered a biochemical AKI alert in England during 2019. This dataset was enriched through linkage with NHS hospitals administrative and mortality data. Episodes of H-AKI were identified and attributed to the speciality of the supervising consultant during the hospitalisation episode in which the H-AKI alert was generated. Associations between speciality and death in hospital or within 30 days of discharge (30-day mortality) was modelled using logistic regression, adjusting for patient age, sex, ethnicity, socioeconomic status, AKI severity, season and method of admission.

Results
In total, 93,196 episodes of H-AKI were studied. The largest number of patients with H-AKI were observed under general medicine (21.9%), care of the elderly (18.9%) and general surgery (11.2%). Despite adjusting for differences in patient case-mix, 30-day mortality risk was consistently lower for patients in surgical specialities compared to general medicine, including general surgery (OR 0.65, 95% CI 0.61 to 0.7) and trauma and orthopaedics (OR 0.52, 95% CI 0.48 to 0.56). Mortality risk was highest in critical care (OR 1.78, 95% CI 1.56 to 2.03) and oncology (OR 1.74, CI 1.54 to 1.96).

Conclusions
Significant differences were identified in the burden of H-AKI and associated mortality risk for patients across different specialities in the English NHS. This work can help inform future service delivery and quality improvement activity for patients with AKI across the NHS.
Comparing the effects of mHealth app use and face-to-face training on the clinical and laboratory parameters of dietary and fluid intake adherence in hemodialysis patients: a randomized clinical trial
Authors: Torabikhah Mohsen , Farsi Zahra , Sajadi Seyedeh Azam 
Published: June 2023

AbstractBackgroundNumerous factors are likely to result in poor treatment adherence, which is one of the important factors contributing to increased complications and the low efficacy of hemodialysis (HD), particularly inadequate knowledge of patients. This study aimed to compare the effects of a mobile health (mHealth) app (the Di Care app) use and face-to-face training on the clinical and laboratory parameters of dietary and fluid intake adherence in patients undergoing HD.MethodsThis single-blinded, two-stage/two-group randomized clinical trial was fulfilled in 2021-22 in Iran. Seventy HD patients were recruited, using the convenience sampling method, and were then randomized into two groups: mHealth (n = 35) and face-to-face training (n = 35). ​ The patients in both groups received the same educational materials via the Di Care app and face-to-face training for one month. Before and 12 weeks after the intervention, the mean interdialytic weight gain (IDWG), potassium (K), phosphorus (P), total cholesterol (TC), triglyceride (TG), albumin (AL), and ferritin (FER) levels were measured and compared. The data were analyzed using the SPSS via descriptive statistics (mean, SD, frequency, and percentage) and analytical tests (independent-samplest-test, paired-samplest-test, Wilcoxon signed-rank test, Mann-Whitney U test, Chi-square test, and Fisher’s exact test).Results​Prior to the intervention, the mean IDWG and the K, P, TC, TG, AL, and FER levels, were not significantly different in both groups (p > 0.05). The mean IDWG (p < 0.0001), and the K (p = 0.001), P (p = 0.003), TC/TG (p < 0.0001), and FER (p = 0.038) levels in the HD patients in the mHealth group decreased. ​As well, the mean IDWG (p < 0.0001), and the K (p < 0.0001) and AL (p < 0.0001) levels showed a descending trend in the face-to-face group. The fall in the mean IDWG (p = 0.001) and the TG level (p = 0.034) in the patients in the mHealth group was significantly greater than that in the face-to-face group.ConclusionsThe Di Care app use and the face-to-face training could improve dietary and fluid intake adherence in patients. However, mHealth could have more effect on the laboratory parameters than face-to-face training, largely reducing the IDWG.Trial registrationThis study was registered in the Iranian Registry of Clinical Trials (No. ID IRCT20171216037895N5).
The associations of ferritin, serum lipid and plasma glucose levels across pregnancy in women with gestational diabetes mellitus and newborn birth weight
Authors: Ji Jing , Wu Pei , Li Guohua , He Zhangya , Wang Shanshan , Yu Wenlu , Li Chao , Mi Yang , Luo Xiaoqin 
Published: June 2023

Abstract
Background
Women with gestational diabetes mellitus (GDM) are at greater risk of abnormal birth weight. Since the level of biochemical indicators could often affect the intrauterine growth and development of the fetus, it is of great practical significance to understand the changes of biochemical levels across pregnancy in women with GDM and to find out the indicators that play an important role in predicting birth weight.

Methods
The data source of this study was from the Xi'an Longitudinal Mother–Child Cohort study (XAMC), in which women with GDM with normal and high pre-pregnancy body mass index (BMI) and their newborns between January 1st and March 31st in 2018 were included. The data of ferritin, serum lipid profile and fasting plasma glucose (FPG) of mothers in the three trimesters of pregnancy, as well as birth weight of newborns were all collected from medical records. Multiple linear regression and multivariate logistic regression analyses were used to explore the association of the biochemical indexes and birth weight. A P value < 0.05 was considered statistically significant.

Results
A total of 782 mother-infant pairs were finally included and divided into normal weight group (NG) (n = 530, 67.8%) and overweight/obesity group (OG) (n = 252, 32.2%) according to maternal pre-pregnancy BMI. The level of ferritin in both NG and OG decreased during pregnancy (P for trend < 0.001 for all), whereas the levels of total cholesterol (TC), high density cholesterol (HDL-C), low density cholesterol (LDL-C) and triglycerides (TG) all showed an upward trend (P for trend < 0.05 for all). The levels of FPG in the two groups remained in a relatively stable during the whole pregnancy even though it was higher in OG during the 2nd and 3rd trimesters, whilst HbAlc levels in NG women increased (P for trend = 0.043) during pregnancy. Meanwhile, the risk of macrosomia and large-for-gestational-age (LGA) increased with the increase of FPG level (P for trend < 0.05). Multivariate logistic regression analyses results showed that only FPG level in the 3rd trimester was correlated with birth weight, with birth weight increased by 44.9 g for each SD increase in FPG level.

Conclusion
Maternal FPG in the 3rd trimester is an independent predictor of newborn birth weight, and a higher level of that is associated with an increased risk of macrosomia and LGA.
The coagulation-related genes for prognosis and tumor microenvironment in pancreatic ductal adenocarcinoma
Authors: Wang Di , Cui Song-ping , Chen Qing , Ren Zhang-yong , Lyu Shao-cheng , Zhao Xin , Lang Ren 
Published: June 2023

Abstract
Background
Pancreatic ductal adenocarcinoma (PDAC) is a malignancy characterized by challenging early diagnosis and poor prognosis. It is believed that coagulation has an impact on the tumor microenvironment of PDAC. The aim of this study is to further distinguish coagulation-related genes and investigate immune infiltration in PDAC.

Methods
We gathered two subtypes of coagulation-related genes from the KEGG database, and acquired transcriptome sequencing data and clinical information on PDAC from The Cancer Genome Atlas (TCGA) database. Using an unsupervised clustering method, we categorized patients into distinct clusters. We investigated the mutation frequency to explore genomic features and performed enrichment analysis, utilizing Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) to explore pathways. CIBERSORT was used to analyze the relationship between tumor immune infiltration and the two clusters. A prognostic model was created for risk stratification, and a nomogram was established to assist in determining the risk score. The response to immunotherapy was assessed using the IMvigor210 cohort. Finally, PDAC patients were recruited, and experimental samples were collected to validate the infiltration of neutrophils using immunohistochemistry. In addition, and identify the ITGA2 expression and function were identified by analyzing single cell sequencing data.

Results
Two coagulation-related clusters were established based on the coagulation pathways present in PDAC patients. Functional enrichment analysis revealed different pathways in the two clusters. Approximately 49.4% of PDAC patients experienced DNA mutation in coagulation-related genes. Patients in the two clusters displayed significant differences in terms of immune cell infiltration, immune checkpoint, tumor microenvironment and TMB. We developed a 4-gene prognostic stratified model through LASSO analysis. Based on the risk score, the nomogram can accurately predict the prognosis in PDAC patients. We identified ITGA2 as a hub gene, which linked to poor overall survival (OS) and short disease-free survival (DFS). Single-cell sequencing analysis demonstrated that ITGA2 was expressed by ductal cells in PDAC.

Conclusions
Our study demonstrated the correlation between coagulation-related genes and the tumor immune microenvironment. The stratified model can predict the prognosis and calculate the benefits of drug therapy, thus providing the recommendations for clinical personalized treatment.