Genetic correlation and Mendelian randomization analyses support causal relationships between dietary habits and age at menarche.

Dietary habits are essential in the mean age at menarche (AAM). However, the causal relationship between these factors remains unclear. Therefore, this study aimed to elucidate the genetic relationship between dietary habits and AAM. Genetic summary statistics for dietary habits were obtained from the UK Biobank. GWAS summary data for AAM was obtained from the ReproGen Consortium. Linkage disequilibrium score regression was used to test genetic correlations between dietary habits and AAM. The Mendelian randomization (MR) analyses used the inverse-variance weighted method. Genetic correlations with AAM were identified for 29 candi-date dietary habits, such as milk type (skimmed, semi-skimmed, full cream; coefficient = 0.2704, Pldsc = 1.13 × 10-14). MR evaluations revealed that 19 dietary habits were associated with AAM, including bread type (white vs. any other; OR 1.71, 95% CI 1.28-2.29, Pmr = 3.20 × 10-4), tablespoons of cooked vegetables (OR 0.437, 95% CI 0.29-0.67; Pmr = 1.30 × 10-4), and cups of coffee per day (OR 0.72, 95% CI 0.57-0.92, Pmr = 8.31 × 10-3). These results were observed to be stable under the sensitivity analysis. Our study provides potential insights into the genetic mechanisms underlying AAM and evidence that dietary habits are associated with AAM.

The association between C-reactive protein and coronary artery calcification: a systematic review and meta-analysis.

BACKGROUND: While coronary artery calcification (CAC) is recognized as a reliable marker for coronary atherosclerosis, the relationship between the concentration of C-reactive protein (CRP) and the incidence and progression of CAC remains controversial. METHOD: PubMed, Embase, Web of Science, and Scopus were systematically searched to identify relevant observational studies until October 2023. The methodological quality of the included studies was evaluated using the Newcastle-Ottawa Scale (NOS). A random-effects meta-analysis was employed to calculate pooled odd ratios (OR) and corresponding 95% confidence intervals, considering heterogeneity among the studies. RESULTS: Out of the 2545 records, 42 cross-sectional and 9 cohort studies were included in the systematic review. The meta-analysis on 12 eligible cross-sectional studies revealed no significant association between CAC and CRP [pooled OR: 1.03 (1.00, 1.06)]. Additionally, an insignificant association was found between CAC and CRP through meta-analysis on three eligible cohort studies [pooled OR: 1.05 (0.95, 1.15)] with no considerable heterogeneity across studies. Sensitivity analyses indicated that the meta-analysis models were robust. There was no evidence of publication bias. CONCLUSION: Based on the meta-analysis findings, elevated levels of CRP did not emerge as a valuable prognostic maker for CAC incidence and progression prediction.

Paradigm Shifts in Vascular Surgery: Analysis of the Top 100 Innovative and Disruptive Academic Publications.

BACKGROUND: Disruption score (DS) is a novel bibliometric created to identify research that shifts paradigms, which may be overlooked by citation count (CC). We analyzed the most disruptive, compared to the most cited, literature in vascular surgery, and hypothesized that DS and CC would not correlate. METHODS: A PubMed search identified vascular surgery publications from 1954 to 2014. The publications were linked to the iCite NIH tool and DS algorithm to identify the top 100 studies by CC and DS, respectively. The publications were reviewed for study focus, design, and contribution, and subsequently compared. RESULTS: A total of 56,640 publications were identified. The top 100 DS papers were frequently published in J Vasc Sur (43%) and Eur J Vasc Endovasc Surg (13%). The top 100 CC papers were frequently published in N Engl J Med (32%) and J Vasc Sur (20%). The most cited article is the fifth most disruptive; the most disruptive article is not in the top 100 cited papers. The DS papers had a higher mean DS than the CC papers (.17 vs .0001, P < .0001). The CC papers had a higher mean CC than the DS papers (866 vs 188, P < .0001). DS and CC are weakly correlated metrics (r = .22, P = .03). DISCUSSION: DS was weakly correlated with CC and captured a unique subset of literature that created paradigm shifts in vascular surgery. DS should be utilized as an adjunct to CC to avoid overlooking impactful research and influential researchers, and to measure true academic productivity.

A practical guide to estimating treatment effects in patients with rheumatic diseases using real-world data.

OBJECTIVE: Randomized controlled trials are considered the gold standard in study methodology. However, due to their study design and inclusion criteria, these studies may not capture the heterogeneity of real-world patient populations. In contrast, the lack of randomization and the presence of both measured and unmeasured confounding factors could bias the estimated treatment effect when using observational data. While causal inference methods allow for the estimation of treatment effects, their mathematical complexity may hinder their application in clinical research. METHODS: We present a practical, nontechnical guide using a common statistical package (Stata) and a motivational simulated dataset that mirrors real-world observational data from patients with rheumatic diseases. We demonstrate regression analysis, regression adjustment, inverse-probability weighting, propensity score (PS) matching and two robust estimation methods. RESULTS: Although the methods applied to control for confounding factors produced similar results, the commonly used one-to-one PS matching method could yield biased results if not thoroughly assessed. CONCLUSION: The guide we propose aims to facilitate the use of readily available methods in a common statistical package. It may contribute to robust and transparent epidemiological and statistical methods, thereby enhancing effectiveness research using observational data in rheumatology.

The survival effect of neoadjuvant therapy and neoadjuvant plus adjuvant therapy on pancreatic ductal adenocarcinoma patients with different TNM stages: a propensity score matching analysis based on the SEER database.

BACKGROUND: Adjuvant therapy (AT) and neoadjuvant therapy (NAT) are standard treatments for pancreatic ductal adenocarcinoma (PDAC) depending on the status of the disease. However, whether AT improves survival after NAT and radical resection in all TNM stages remains unclear. RESEARCH DESIGN AND METHODS: We utilized the Surveillance, Epidemiology, and End Results (SEER) database (2010-2019) for PDAC patients who underwent radical surgery and applied Pearson's chi-square test, multivariate and univariate Cox regression, Kaplan-Meier plot, Log-rank tests, and propensity score matching (PSM) for analysis. RESULTS: Given PSM after enrolling 13,868 PDAC patients, significant differences in survival were identified between AT and neoadjuvant therapy plus adjuvant therapy (NATAT) (p = 0.023) as well as between NAT and NATAT (p < 0.001). According to the AJCC 8th TNM stage, a survival advantage associated with NATAT was exclusively observed in stage III and IV disease, except for T4N0M0. Some stage IV patients receiving NATAT exhibited comparable survival to their counterparts without metastasis. CONCLUSIONS: In this retrospective cohort study, we demonstrated that patients harboring tumors in late TNM stages, including N2 resectable PDAC, might have better survival from NATAT, and that certain patients with M1 disease might still benefit from comprehensive systemic therapy and radical resection.

Complications after peripherally inserted central catheter versus central venous catheter implantation in intensive care unit: propensity score analysis using a nationwide database.

BACKGROUND: It remains unclear whether peripherally inserted central catheters (PICCs) are superior to central venous catheters (CVCs); therefore, we compared post-implantation complications between CVC and PICC groups. RESEARCH DESIGN AND METHODS: Patients who received CVCs or PICCs between April 2010 and March 2018 were identified from the Diagnosis Procedure Combination database, a national inpatient database in Japan. The outcomes of interest included catheter infection, pulmonary embolism, deep vein thrombosis, and phlebitis. Propensity score overlap weighting was used to balance patient backgrounds. Outcomes were compared using logistic regression analyses. RESULTS: We identified 164,185 eligible patients, including 161,605 (98.4%) and 2,580 (1.6%) in the CVC and PICC groups, respectively. The PICC group was more likely to have overall complications (odds ratio [OR], 1.70; 95% confidence interval [CI], 1.32-2.19), pulmonary embolism (OR, 2.32; 95% CI, 1.38-3.89), deep vein thrombosis (OR, 1.86; 95% CI, 1.16-2.99), and phlebitis (OR, 1.72; 95% CI, 1.27-2.32) than the CVC group. There was no significant intergroup difference in catheter infection (OR, 1.09; 95% CI, 0.39-3.04). CONCLUSIONS: Patients with PICCs had a significantly greater incidence of complications than did those with CVCs. Further research is necessary to explore the factors contributing to these complications.

Exploring the role of coagulation-related genes in renal cell carcinoma: Implications for tumor microenvironment and prognostic biomarkers.

PURPOSE: Clear cell renal cell carcinoma (ccRCC) frequently progresses to advanced stages due to tumor thrombus (TTs) formation. In this study, we aimed to investigate the role of coagulation-related pathway activation in the progression of ccRCC. METHODS: Consensus clustering was used to identify coagulation-related molecular clusters of ccRCC patients from The Cancer Genome Atlas Program (TCGA) database. The function of coagulation and its correlation with the immune microenvironment were investigated. Protein-protein interactions and differential expression analysis were used to identify the key gene, which was verified by external experiments. The coagulation-associated risk score was constructed by cox proportional hazards regression. RESULTS: Notable disparities were detected in immune characteristics, prognostic differentiation and drug sensitivity between two coagulation-related clusters. Through the integration of clinical stage significance and protein-protein interactions, the key gene MMP9 was screened and it was significantly correlated with CD4+T cells, CD8+T cells and Treg cells. A coagulation-related risk score prognostic model was developed in the Cancer Genome Atlas (TCGA) cohort for risk stratification and prognosis prediction. The prognostic predictive values of the coagulation-related risk score were further authenticated in both TCGA-KIRC and E-MTAB-1980 cohorts. CONCLUSION: There is an obvious correlation between the coagulation and the tumor microenvironment in ccRCC. As a key coagulation-related gene, MMP9 may promote the progression of renal cell carcinoma by influencing immune infiltration of CD8+T cells and Treg cells. Additionally, the risk score could be used as a durable prognostic biomarker, which could assist in clinical decision making for ccRCC patients.

Clinical utility of the Borg dyspnoea score in 6-minute walk tests in interstitial lung disease: A systematic review.

BACKGROUND: Exertional dyspnoea, a cardinal symptom in interstitial lung disease (ILD), can be objectively measured during a 6-min walk test (6MWT) using the Borg Dyspnoea Score (BDS). However, the clinical utility of this measurement is unclear. The purpose of this systematic review was to determine the association between 6MWT BDS and prognosis (mortality and lung transplantation), other 6MWT variables and measures of pulmonary function. METHODS: MEDLINE, EMBASE, Cochrane and SCOPUS databases were used to identify studies reporting an association between post-6MWT BDS and the relevant outcomes in adults with ILD. Language was limited to English. Study quality was assessed using the Quality in Prognosis Study risk of bias tool. A narrative synthesis for each outcome was performed. RESULTS: Ten full-text studies (n = 518) were included. Four studies had high overall risk of bias. Two studies (n = 127) reported prognosis and both found that higher 6MWT BDS was associated with increased all-cause mortality. However, the certainty of evidence was very low due to study design and likely publication bias. Higher post-6MWT BDS may be associated with shorter, or no effect on 6MWD; and lower pulmonary function. There was insufficient evidence that BDS correlated with 6MWT oxygen saturation. CONCLUSIONS: Post-6MWT BDS has a potential role as a predictor of all-cause mortality in ILD, 6MWD and lower pulmonary function. Larger studies designed to confirm these relationships and assess the independent association between the 6MWT BDS and clinical outcomes are required.

Predictability of noninvasive liver fibrosis score for cardiac events in patients with nonalcoholic fatty liver disease.

BACKGROUND AND AIMS: Patients with nonalcoholic fatty liver disease (NAFLD) have a higher risk of cardiac events. However, although the severity of liver fibrosis is related to worsening prognosis in patients with NAFLD, it is unclear whether the noninvasive liver fibrosis score has a predictive value for cardiac events. METHODS AND RESULTS: We evaluated 4071 patients with NAFLD diagnosed using ultrasonography. Liver fibrosis was assessed and divided into three groups based on the Fibrosis-4 (FIB4) index and NAFLD fibrosis score (NFS). The primary outcome of this study was major adverse cardiac events (MACE), including cardiac death, nonfatal myocardial infarction, and revascularization due to coronary artery disease. The median age of the evaluated patients was 61 (52-69) years, and 2201 (54.1%) were male. During the median follow-up period of 6.6 years, 179 (4.4%) patients experienced MACE. Kaplan-Meier survival analysis demonstrated that MACE increased progressively with the FIB4 index (log-rank, p < 0.001) and NFS (log-rank, p < 0.001). Multivariable analysis showed that the higher the FIB4 index, the higher the risk for MACE (low group as reference vs. intermediate group, hazard ratio [HR]: 1.860 [95% confidence interval (CI), 1.326-2.610; p < 0.001]; vs. high group, HR:3.325 [95% CI, 2.017-5.479; p < 0.001]), as well as NFS (low NFS group as reference vs. intermediate group, HR: 1.938 [95% CI, 1.391-2.699; p < 0.001]; vs. high group, HR: 3.492 [95% CI, 1.997-6.105; p < 0.001]). CONCLUSIONS: The FIB4 index and NFS are associated with the probability of MACE in patients with NAFLD. CLINICAL TRIALS: The study design was approved by the ethics review board of Ogaki Municipal Hospital (approval number: 20221124-12, registration date: November 28th, 2022). https://www.ogaki-mh.jp/chiken/kenkyu.html.

Assessment of Genomic Diversity and Selective Pressures in Crossbred Dairy Cattle of Pakistan.

Improving the low productivity levels of native cattle breeds in smallholder farming systems is a pressing concern in Pakistan. Crossbreeding high milk-yielding holstein friesian (HF) breed with the adaptability and heat tolerance of Sahiwal cattle has resulted in offspring that are well-suited to local conditions and exhibit improved milk yield. The exploration of how desirable traits in crossbred dairy cattle are selected has not yet been investigated. This study aims to provide the first overview of the selective pressures on the genome of crossbred dairy cattle in Pakistan. A total of eighty-one crossbred, thirty-two HF and twenty-four Sahiwal cattle were genotyped, and additional SNP genotype data for HF and Sahiwal were collected from a public database to equate the sample size in each group. Within-breed selection signatures in crossbreds were investigated using the integrated haplotype score. Crossbreds were also compared to each of their parental breeds to discover between-population signatures of selection using two approaches: cross-population extended haplotype homozygosity and fixation index. We identified several overlapping genes associated with production, immunity, and adaptation traits, including U6, TMEM41B, B4GALT7, 5S_rRNA, RBM27, POU4F3, NSD1, PRELID1, RGS14, SLC34A1, TMED9, B4GALT7, OR2AK3, OR2T16, OR2T60, OR2L3, and CTNNA1. Our results suggest that regions responsible for milk traits have generally experienced stronger selective pressure than others.

Post-selection Inference in Multiverse Analysis (PIMA): An Inferential Framework Based on the Sign Flipping Score Test.

When analyzing data, researchers make some choices that are either arbitrary, based on subjective beliefs about the data-generating process, or for which equally justifiable alternative choices could have been made. This wide range of data-analytic choices can be abused and has been one of the underlying causes of the replication crisis in several fields. Recently, the introduction of multiverse analysis provides researchers with a method to evaluate the stability of the results across reasonable choices that could be made when analyzing data. Multiverse analysis is confined to a descriptive role, lacking a proper and comprehensive inferential procedure. Recently, specification curve analysis adds an inferential procedure to multiverse analysis, but this approach is limited to simple cases related to the linear model, and only allows researchers to infer whether at least one specification rejects the null hypothesis, but not which specifications should be selected. In this paper, we present a Post-selection Inference approach to Multiverse Analysis (PIMA) which is a flexible and general inferential approach that considers for all possible models, i.e., the multiverse of reasonable analyses. The approach allows for a wide range of data specifications (i.e., preprocessing) and any generalized linear model; it allows testing the null hypothesis that a given predictor is not associated with the outcome, by combining information from all reasonable models of multiverse analysis, and provides strong control of the family-wise error rate allowing researchers to claim that the null hypothesis can be rejected for any specification that shows a significant effect. The inferential proposal is based on a conditional resampling procedure. We formally prove that the Type I error rate is controlled, and compute the statistical power of the test through a simulation study. Finally, we apply the PIMA procedure to the analysis of a real dataset on the self-reported hesitancy for the COronaVIrus Disease 2019 (COVID-19) vaccine before and after the 2020 lockdown in Italy. We conclude with practical recommendations to be considered when implementing the proposed procedure.

A population-based propensity score matching analysis of risk factors and the impact on survival associated with refusal of cancer-directed surgery in patients with prostate cancer.

Cancer-directed surgeries (CDS) play a crucial role in prostate cancer (PCa) management along with possible survival and therapeutic benefits. However, barriers such as socioeconomic factors may affect patients' decision of refusing recommended CDS. This study aimed to uncover risk factors and the impact on survival associated with CDS refusal. We retrospectively reviewed the Surveillance, Epidemiology, and End Results database for patients diagnosed with PCa between 2000 and 2019. Multiple sociodemographic and clinical characteristics were extracted to assess predictors for physicians' surgical recommendations and patients' surgical refusal, respectively. Propensity score matching was performed to balance the covariates. The impact of surgical refusal on mortality risk was also investigated. A total of 185,540 patients were included. The physician's recommendation of CDS was significantly influenced by the patient's age, race, income, home location, diagnosis year, Gleason score, prostate-specific antigen (PSA), and TNM stage. About 5.6% PCa patients refused CDS, most of whom were older, non-White race, lack of partners, living outside of metropolitan areas, with higher PSA or lower clinical TNM stage. Patients who refused CDS had an increased risk of cancer-specific mortality and overall mortality than those who performed CDS. Physicians may weigh a host of sociodemographic and clinical factors prior to making a CDS recommendation. Patients' refusal of recommended CDS affected survival and was potentially modifiable by certain sociodemographic factors. Physicians should fully consider the hindrances behind patients' CDS refusal to improve patient-doctor shared decision-making, guide patients toward the best alternative and achieve better outcomes.

Gender differences in diet quality and the association between diet quality and BMI: an analysis in young Australian adults who completed the Healthy Eating Quiz.

BACKGROUND: Many young adults report poor diet quality. However, research evaluating whether young adult males and females differ in diet quality is limited. Additionally, although diet quality has a known inverse association with body mass index (BMI), it is unclear whether this association is observed in young adults and whether it varies by gender. The present study aimed to evaluate gender differences in diet quality in young adults, as well as the associations between diet quality and BMI. METHODS: Data collected via the Healthy Eating Quiz (HEQ) in respondents aged 18-35 years between July 2019 and December 2021 were analysed, including demographics, and diet quality calculated using the Australian Recommended Food Score (ARFS). Differences in characteristics were analysed using a two-sample t-test, chi-squared and one-way analysis of covariance. Linear regressions were performed to estimate associations between diet quality and BMI. An interaction term was included in the model to test differences between genders. RESULTS: The respondents (n = 28,969) were predominantly female (70.8%) with a mean ± SD age of 25.9 ± 5.0 years and BMI of 24.6 ± 5.2 kg/m2. The mean ± SD ARFS was significantly different between females and males (33.1 ± 8.6 vs. 31.4 ± 9.3 points out of 70; p < 0.001). Diet quality had a small, significant inverse association with BMI in both genders. The interaction effect between diet quality score and gender in predicting BMI was significant (p < 0.001), suggesting the impact of diet quality on BMI varies by gender, with lower diet quality more strongly associated with higher BMI in females compared to males. CONCLUSION: Interventions that target young adults are needed to improve diet quality and its potential contribution to BMI status. As a result of the small observed effect sizes, caution should be applied in interpreting these findings.

Segmental differences in daytime changes of leg volume.

BACKGROUND: The aim of our study was to comparatively assess volume changes related to daily occupation of the whole leg (WLv), of the lower leg (LLv) and of the upper leg (ULv) in subject with no venous and lymphatic disorders. METHOD: WLv, LLv, and Ulv were evaluated by water displacement volumetry (WDV) in the morning and in the evening in 20 healthy subjects. RESULTS: In the legs with occupational edema (OE), WLv increased by 7.07%, LLv by 5.25%, and ULv by 9.80%. In legs without clear OE, WLv increased by 2.41%, LLv by 1.35, and ULv by 3.38%. CONCLUSIONS: Surprisingly, the increase of ULv was greater than that of LLv. An evening increase in the leg volume also occurred in legs with no clear OE. In our series, a clinically evident OE was related to an increase of the WLv, LLv, and ULv greater than 5.83%, 8.68%, and 1.88%, respectively.

Empowering Expecting Women to Obtain High-Quality Healthcare in Pakistan: An Evaluation of Khyber Pakhtunkhwa's Conditional Cash Transfer Program.

Maternal mortality, largely stemming from complications during pregnancy and childbirth, impacts poor expecting women with limited healthcare access in rural Pakistan. Conditional Cash Transfers (CCTs), commonly implemented in developing nations, are designed to improve the well-being of vulnerable populations by focusing on health and education. A CCT initiative named Chief Minister's Special Initiative for Mother and Child Health (CM-SIMCH) was launched in Khyber Pakhtunkhwa (KP), one of the less-developed provinces of Pakistan, to empower expecting women to access quality healthcare. This study investigates the factors influencing CM-SIMCH program participation and assesses its impact on the health of expecting women by analyzing health-seeking hospital visits in KP, Pakistan. The study utilizes the Propensity Score Matching (PSM) technique to analyze cross-sectional data obtained from 303 expecting women residing in the Nowshera district of KP. The PSM allows for a balanced comparison of participants who received the CM-SIMCH transfers with those who did not, assessing its impact on maternal healthcare access and outcomes. Empirical results show that factors such as education and family system positively influence the participation of expecting women in the CM-SIMCH program, whereas travel costs exert a negative effect. The intervention leads to a notable increase in hospital visits among these women, contributing to improved health outcomes in KP. This underscores the program's potential effectiveness in addressing maternal healthcare challenges and enhancing healthcare access for vulnerable women in less-developed areas. Therefore, empirical evidence supports the CM-SIMCH program's potential to promote maternal health and improve healthcare access in KP. The study recommends government intervention in health sector as a strategic imperative to empower women and enhance infant health.

A Data-Driven Computational Framework for Assessing the Risk of Placental Exposure to Environmental Chemicals.

A computational framework based on placental gene networks was proposed in this work to improve the accuracy of the placental exposure risk assessment of environmental compounds. The framework quantitatively characterizes the ability of compounds to cross the placental barrier by systematically considering the interaction and pathway-level information on multiple placental transporters. As a result, probability scores were generated for 307 compounds crossing the placental barrier based on this framework. These scores were then used to categorize the compounds into different levels of transplacental transport range, creating a gradient partition. These probability scores not only facilitated a more intuitive understanding of a compound's ability to cross the placental barrier but also provided valuable information for predicting potential placental disruptors. Compounds with probability scores greater than 90% were considered to have significant transplacental transport potential, whereas those with probability scores less than 80% were classified as unlikely to cross the placental barrier. Furthermore, external validation set results showed that the probability score could accurately predict the compounds known to cross the placental barrier. In conclusion, the computational framework proposed in this study enhances the intuitive understanding of the ability of compounds to cross the placental barrier and opens up new avenues for assessing the placental exposure risk of compounds.

Automated osteoporosis classification and T-score prediction using hip radiographs via deep learning algorithm.

Background: Despite being the gold standard for diagnosing osteoporosis, dual-energy X-ray absorptiometry (DXA) is an underutilized screening tool for osteoporosis. Objectives: This study proposed and validated a controllable feature layer of a convolutional neural network (CNN) model with a preprocessing image algorithm to classify osteoporosis and predict T-score on the proximal hip region via simple hip radiographs. Design: This was a single-center, retrospective study. Methods: An image dataset of 3460 unilateral hip images from 1730 patients (age ⩾50 years) was retrospectively collected with matched DXA assessment for T-score for the targeted proximal hip regions to train (2473 unilateral hip images from 1430 patients) and test (497 unilateral hip images from 300 patients) the proposed CNN model. All images were processed with a fully automated CNN model, X1AI-Osteo. Results: The proposed screening tool illustrated a better performance (sensitivity: 97.2%; specificity: 95.6%; positive predictive value: 95.7%; negative predictive value: 97.1%; area under the curve: 0.96) than the open-sourced CNN models in predicting osteoporosis. Moreover, when combining variables, including age, body mass index, and sex as features in the training metric, there was high consistency in the T-score on the targeted hip regions between the proposed CNN model and the DXA (r = 0.996, p < 0.001). Conclusion: The proposed CNN model may identify osteoporosis and predict T-scores on the targeted hip regions from simple hip radiographs with high accuracy, highlighting the future application for population-based opportunistic osteoporosis screening with low cost and high adaptability for a broader population at risk. Trial registration: TMU-JIRB N201909036.

Identification of exosome-related gene signature as a promising diagnostic and therapeutic tool for breast cancer.

Background: Exosomes are promising tools for the development of new diagnostic and therapeutic approaches. Exosomes possess the ability to activate signaling pathways that contribute to the remodeling of the tumor microenvironment, angiogenesis, and the regulation of immune responses. We aimed to develop a prognostic score based on exosomes derived from breast cancer. Materials and methods: Training was conducted on the TCGA-BRCA dataset, while validation was conducted on GSE20685, GSE5764, GSE7904, and GSE29431. A total of 121 genes related to exosomes were retrieved from the ExoBCD database. The Cox proportional hazards model is used to develop risk score model. The GSVA package was utilized to analyze single-sample gene sets and identify exosome signatures, while the WGCNA package was utilized to identify gene modules associated with clinical outcomes. The clusterProfiler and GSVA R packages facilitated gene set enrichment and variation analyses. Furthermore, CIBERSORT quantified immune infiltration, and a correlation between gene expression and drug sensitivity was assessed using the TIDE algorithm. Results: An exosome-related prognostic score was established using the following selected genes: ABCC9, PIGR, CXCL13, DOK7, CD24, and IVL. Various immune cells that promote cancer immune evasion were associated with a high-risk prognostic score, which was an independent predictor of outcome. High-risk and low-risk groups exhibited significantly different infiltration abundances (p < 0.05). By conducting a sensitivity comparison, we found that patients with high-risk scores exhibited more favorable responses to immunotherapy than those with low-risk scores. Conclusion: The exosome-related gene signature exhibits outstanding performance in predicting the prognosis and cancer status of patients with breast cancer and guiding immunotherapy.

Association of ADAMTS13 activity with cerebral deep medullary vein: A community-based cross-sectional study.

Objectives: This study aims to investigate whether circulating ADAMTS13 activity can offer insights into the mechanism of pathophysiological changes in deep medullary veins (DMVs). Methods: This study was conducted on a community cohort of elderly individuals in Shanghai. Plasma von Willebrand factor (VWF) levels and ADAMTS13 activity were measured. A validated DMV score described the overall burden of DMV on the brain. Through ordinal regression models, we investigated the correlation between VWF levels, ADAMTS13 activity, and increasing severity of DMV score while adjusting for demographics and cardiovascular risk factors. Results: The study enrolled 262 subjects according to the inclusion criteria. The mean VWF level (1.35 ± 0.25) was higher in the DMV group than in the group without DMV (1.25 ± 0.30) (p = 0.025), and ADAMTS13 activity (83.76 ± 7.96) was relatively lower. After adjusting for age, sex, alcohol consumption, smoking, hypertension, and diabetes, reduced ADAMTS13 activity [ß = -7.78; 95 % CI (-10.21, -5.35) p < 0.01] was associated with DMV. Moreover, correlation analysis indicated that ADAMTS13 activity was negatively correlated with the DMV score (Kendall's tau-b = -0.53, p < 0.001). Discussion: In summary, there was an inverse correlation observed between ADAMTS13 activity and the DMV score, which may provide some clinical clues for exploring the potential pathogenesis of DMV.

Prediction of Reproductive Outcomes of Intracytoplasmic Sperm Injection Cycles Using a Multivariate Scoring System.

Background: Prediction of in vitro fertilisation (IVF)/intracytoplasmic sperm injection (ICSI) success is crucial in counselling patients about their real chance of getting a live birth before commencing treatment. A multivariate scoring system proposed by Younis et al., 2010, was amongst the predictive models used to evaluate IVF/ICSI success. The score entitles basal endocrine, clinical and sonographic parameters. Aims: The objective of this study is to assess the predictability of the Younis multivariate score for pregnancy outcomes in ICSI cycles. Settings and Design: This prospective observational cohort study (NCT03846388) included patients who pursued IVF or ICSI in a tertiary infertility unit between February 2019 and December 2021. Materials and Methods: The score variables were age, body mass index, antral follicle count, basal follicle-stimulating hormone (FSH), basal FSH/luteinising hormone ratio, infertility duration, number of previous cancellations and mean ovarian volume. For each woman included in the study, Younis multivariate score was calculated. Then, we correlate the different reproductive outcomes with score levels to validate the score predictability. A score of ≤14 was defined as a low score based on the previous study's results. Statistical Analysis Used: The student's t-test and Mann-Whitney test were used to compare numerical variables, whereas categorical variables were analysed using the Chi-square test. A receiver operating curve (ROC) and a multivariate logistic regression model were used to investigate the predictability of the Younis scoring model for cycle outcomes. Results: Two hundred ninety-two ICSI-ET cycles were analysed. Of the total cohort, 143 (48.97%) women included showed a low score (≤14), whereas 149 (51.03%) women showed a high score (>14). Women with low scores had significantly higher pregnancy and live birth rates compared to women with high scores (60.1% vs. 7.4%, respectively, P < 0.001; 44.7% vs. 6.7%, respectively, P < 0.001). The area under the curve (AUC) in the ROC curve analysis showed a higher predictability for the scoring system for live birth rate with an AUC of 0.796, with a sensitivity of 86.5% and specificity of 63.8% when using a cut-off level of ≤14. For pregnancy prediction, the AUC was 0.829, with a sensitivity of 88.66% and a specificity of 70.77% when using the same cut-off. Women who have a low score have a high chance of having frozen embryos. Likewise, women who have a high score have a very high chance of cycle cancellation. Conclusions: The Younis multivariate score can be used for the prediction of ICSI cycle outcomes and to calculate the chance of cycle cancellation, pregnancy and take-home baby before ICSI.