[A simulation study of the reliability and accuracy of Cox-TEL method for estimating hazard ratio and difference in proportions for long-term survival data containing cured patients].

OBJECTIVE: To explore the applicable conditions of the Cox-TEL (Cox PH-Taylor expansion adjustment for long-term survival data) method for analysis of survival data that contain cured patients. METHODS: The simulated survival data method based on Weibull distribution was used to simulate and generate the survival data with different cure rates, censored rates, and cure rate differences. The Cox-TEL method was used for analysis of the generated simulation data, and its performance was evaluated by calculating its type Ⅰ error and power. RESULTS: Almost all the type Ⅰ error of the hazard ratios (HRs) obtained by the Cox-TEL method under different conditions were slightly greater than 0.05, and this method showed a good test power for estimating the HRs for data with a large sample size and a large difference in proportions (DPs). For the data of cured patients, the type Ⅰ error of the DPs obtained by the Cox-TEL method was well around 0.05, and its test power was robust in most of the scenarios. CONCLUSION: The Cox-TEL method is effective for analyzing data of uncured patients and obtaining reliable HRs for most of the survival data with a sample size, a low censored rates, and a large difference in cure rates. The method is capable of accurately estimating the DPs regardless of the sample size, censored rates, or the cure rates.

Unraveling the Influence of Social, Economic, and Demographic Factors in Texas on Breast Cancer Survival.

Background: According to the Centers for Disease Control (CDC), breast cancer is the second most common cancer among women in the United States. Affected people are financially challenged due to the high out-of-pocket cost of breast cancer treatment, as it is the most expensive treatment. Using a 16-year cohort study of breast cancer survival data in Texas, we investigate the factors that might explain why some breast cancer patients live longer than others. Methods: Performing a survival analysis consisting of the log-rank test, a survival time regression, and Cox proportional hazards regression, we explore the breast cancer survivors' specific attributes to identify the main determinants of survival time. Results: Analyses show that the factors: stage, grade, primary site of the cancer, number of cancers each patient has, histology of the cancer, age, race, and income are among the main variables that enlighten why some breast cancer survivors live much longer than others. For instance, compared to White non-Hispanics, Black non-Hispanics have a shorter length of survival with a hazard ratio of (1.282). The best prognostic for White non-Hispanics, Hispanics (all races), and Black non-Hispanics is a woman aged between 40 to 49 years old, diagnosed with localized stage and grade one with Axillary tail of breast as a primary site with only one cancer and with a household income of 75,000.00 and over. Conclusion: Policymakers should promote early diagnosis and screening and better assist the older and the poor to improve the survival time for breast cancer patients.

Survival Analysis Without Sharing of Individual Patient Data by Using a Gaussian Copula.

Cox regression and Kaplan-Meier estimations are often needed in clinical research and this requires access to individual patient data (IPD). However, IPD cannot always be shared because of privacy or proprietary restrictions, which complicates the making of such estimations. We propose a method that generates pseudodata replacing the IPD by only sharing non-disclosive aggregates such as IPD marginal moments and a correlation matrix. Such aggregates are collected by a central computer and input as parameters to a Gaussian copula (GC) that generates the pseudodata. Survival inferences are computed on the pseudodata as if it were the IPD. Using practical examples we demonstrate the utility of the method, via the amount of IPD inferential content recoverable by the GC. We compare GC to a summary-based meta-analysis and an IPD bootstrap distributed across several centers. Other pseudodata approaches are also considered. In the empirical results, GC approximates the utility of the IPD bootstrap although it might yield more conservative inferences and it might have limitations in subgroup analyses. Overall, GC avoids many legal problems related to IPD privacy or property while enabling approximation of common IPD survival analyses otherwise difficult to conduct. Sharing more IPD aggregates than is currently practiced could facilitate "second purpose"-research and relax concerns regarding IPD access.

A simple Cox approach to estimating risk ratios without sharing individual-level data in multi-site studies.

Epidemiologic studies frequently use risk ratios to quantify associations between exposures and binary outcomes. When the data are physically stored at multiple data partners, it can be challenging to perform individual-level analysis if data cannot be pooled centrally due to privacy constraints. Existing methods either require multiple file transfers between each data partner and an analysis center (e.g., distributed regression) or only provide approximate estimation of the risk ratio (e.g., meta-analysis). Here we develop a practical method that requires a single transfer of eight summary-level quantities from each data partner. Our approach leverages an existing risk-set method and software originally developed for Cox regression. Sharing only summary-level information, the proposed method provides risk ratio estimates and confidence intervals identical to those that would be provided - if individual-level data were pooled - by the modified Poisson regression. We justify the method theoretically, confirm its performance using simulated data, and implement it in a distributed analysis of COVID-19 data from the U.S. Food and Drug Administration's Sentinel System.

Surgical treatment of atrial fibrillation in elderly patients undergoing high risk cardiac surgery.

BACKGROUND: Evaluating outcomes of concurrent Cox-Maze procedures in elderly patients undergoing high-risk cardiac surgery. MEHODS: We retrospectively identified patients aged over 70 years with Atrial Fibrillation (AF) from 2011 to 2017 who had two or more other cardiac procedures. They were subdivided into two groups: 1. Cox-Maze IV AF ablation. 2. No-Surgical AF treatment. A propensity match score was used to generate a homogeneous cohort and to eliminate confounding variables. Heart rhythm was assessed from Holter reports or 12-lead ECG. Follow-up data was collected through telephone consultations and medical records. RESULTS: There were 239 patients. Median follow up was 61 months. 70 patients had Cox-Maze IV procedures (29.3%). Demographic, intra- and post-operative outcomes were similar between groups although duration of pre-operative AF was shorter in Cox-Maze group (p = 0.001). There was no significant 30-day mortality difference in propensity matched cohorts (n = 84. P = 0.078). Sinus rhythm at annual and latest follow-up was 84.9% and 80.0% respectively in Maze group - 160 patients (66.9%) were alive at long-term follow-up with good survival outcomes in Cox Maze group. There was a high proportion of patients in NYHA 1 status in Cox-Maze group. No differences observed in freedom from stroke (p = 0.80) or permanent pacemaker (p = 0.33) between the groups. CONCLUSIONS: Surgical ablation is beneficial in elderly patients undergoing high-risk surgery - promoting excellent long-term freedom from AF and symptomatic / prognostic benefits, without added risk. Therefore, surgical risk should not be reason to deny benefits of concomitant AF-ablation. CLINICAL TRIAL REGISTRATION: Not required.

The relationship between serum anion gap levels and short-, medium-, and long-term all-cause mortality in ICU patients with congestive heart failure: a retrospective cohort study.

BACKGROUND: There hasn't been research done on the connection between serum anion gap (AG) levels and long-, medium-, and short-term all-cause mortality in congestive heart failure (CHF) patients. This study aims to investigate the association between serum anion gap levels and all-cause mortality in CHF patients after adjusting for other covariates. METHODS: For each patient, we gather demographic information, comorbidities, laboratory results, vital signs, and scoring data using the ICU (Intensive Care Unit) Admission Scoring System from the MIMIC-III database. The connection between baseline AG and long-, medium-, and short-term all-cause mortality in critically ill congestive heart failure patients was investigated using Kaplan-Meier survival curves, subgroup analysis, restricted cubic spline, and Cox proportional risk analysis. RESULTS: 4840 patients with congestive heart failure in total were included in this study. With a mean age of 72.5 years, these patients had a gender split of 2567 males and 2273 females. After adjusting for other covariates, a multiple regression analysis revealed that, in critically ill patients with congestive heart failure, all-cause mortality increased significantly with rising AG levels. In the fully adjusted model, we discovered that AG levels were strongly correlated with 4-year, 365-day, 90-day, and 30-day all-cause mortality in congestive heart failure patients with HRs (95% CI) of 1.06 (1.04, 1.08); 1.08 (1.05, 1.10); and 1.08 (1.05, 1.11) (p-value < 0.05). Our subgroup analysis's findings demonstrated a high level of consistency and reliability. K-M survival curves demonstrate that high serum AG levels are associated with a lower survival probability. CONCLUSION: Our research showed the association between CHF patients' all-cause mortality and anion gap levels was non-linear. Elevated anion gap levels are associated with an increased risk of long-, medium-, and short-term all-cause death in patients with congestive heart failure. Continuous monitoring of changes in AG levels may have a clinical predictive role.

Hepatic arterial infusion chemotherapy plus camrelizumab and apatinib for advanced hepatocellular carcinoma.

BACKGROUND AND AIMS: There is limited information on combination of hepatic arterial infusion chemotherapy (HAIC) and systemic therapy for advanced hepatocellular carcinoma (Ad-HCC). We aim to compare the efficacy and safety of HAIC plus camrelizumab (a PD-1 inhibitor) and apatinib (an VEGFR-2 inhibitor) versus camrelizumab and apatinib for Ad-HCC. METHODS: From April 2019 to October 2022, 416 patients with Ad-HCC who received either HAIC plus camrelizumab and apatinib (TRIPLET protocol, n = 207) or camrelizumab and apatinib (C-A protocol, n = 209) were reviewed retrospectively. The propensity score matching (PSM) was used to reduce selective bias. Overall survival (OS) and progression-free survival (PFS) were compared using the Kaplan-Meier method with the log-rank test. Cox regression analyses of independent prognostic factors were evaluated. RESULTS: After PSM 1:1, 109 patients were assigned to two groups. The median OS of not reached in the TRIPLET group was significantly longer than that of 19.9 months in the C-A group (p < 0.001), while in the TRIPLET group, the median PFS of 11.5 months was significantly longer than that of 9.6 months in the C-A group (p < 0.001). Multivariate analyses showed that the factors significantly affected the OS were CTP grade, tumor number > 3, and TRIPLET treatment (p < 0.001). Grade 3/4 adverse events occurred at a rate of 82.1% vs. 71.3% in TRIPLET and C-A groups, respectively. CONCLUSION: The TRIPLET protocol has promising survival benefits in the management of patients with Ad-HCC, with acceptable safety. TRAIL REGISTRATION: The study has been retrospectively registered at Chinese Clinical Trial Registry ( https://www.chictr.org.cn/ , ChiCTR2300075828).

Nonlinear association between PD-L1 expression levels and the risk of postoperative recurrence in non-small cell lung cancer.

Accurate prediction of postoperative recurrence is important for optimizing the treatment strategies for non-small cell lung cancer (NSCLC). Previous studies identified the PD-L1 expression in NSCLC as a risk factor for postoperative recurrence. This study aimed to examine the contribution of PD-L1 expression to predicting postoperative recurrence using machine learning. The clinical data of 647 patients with NSCLC who underwent surgical resection were collected and stratified into training (80%), validation (10%), and testing (10%) datasets. Machine learning models were trained on the training data using clinical parameters including PD-L1 expression. The top-performing model was assessed on the test data using the SHAP analysis and partial dependence plots to quantify the contribution of the PD-L1 expression. Multivariate Cox proportional hazards model was used to validate the association between PD-L1 expression and postoperative recurrence. The random forest model demonstrated the highest predictive performance with the SHAP analysis, highlighting PD-L1 expression as an important feature, and the multivariate Cox analysis indicated a significant increase in the risk of postoperative recurrence with each increment in PD-L1 expression. These findings suggest that variations in PD-L1 expression may provide valuable information for clinical decision-making regarding lung cancer treatment strategies.

Molecular based identification and phylogenetic relationship of the leech Hirudinaria manillensis from India by using mitochondrial cytochrome c oxidase subunit I gene.

BACKGROUND: A molecular approach for the identification of unknown species by the using mitochondrial cox1 gene is an effective and reliable as compared with morphological-based identification. Hirudinaria manillensis referred to as Asian Buffalo Leech, is found in South Asia and traditionally used as medicine owing to its medicinal properties. METHODS AND RESULTS: The study aimed to isolate and identify the leech species using cox1 gene sequencing and their phylogenetic relationships. The nucleotide sequences of cytochrome c oxidase subunit I (cox1) mitochondrial genes were analyzed for species identification and the phylogenetic relationship of crucial therapeutic leech Hirudinaria manillensis. The isolated DNA from the leech sample was amplified with cox1 gene-specific primers. BLAST results with the H. manillensis sequence showed 89.24% homology with H. manillensis and phylogenetic tree analysis revealed the genetic relationship with other GenBank submitted sequences. CONCLUSION: The present study concluded that the cox1 gene could be an effective way to identify the leech H. manillensis and provided sufficient phylogenetic information to distinguish H. manillensis indicating a significant mtDNA-based approach to species identification.

Heart proteomic profiling discovers MYH6 and COX5B as biomarkers for sudden unexplained death.

Sudden unexplained death (SUD) is not uncommon in forensic pathology. Yet, diagnosis of SUD remains challenging due to lack of specific biomarkers. This study aimed to screen differentially expressed proteins (DEPs) and validate their usefulness as diagnostic biomarkers for SUD cases. We designed a three-phase investigation, where in the discovery phase, formalin-fixed paraffin-embedded (FFPE) heart specimens were screened through label-free proteomic analysis of cases dying from SUD, mechanical injury and carbon monoxide (CO) intoxication. A total of 26 proteins were identified to be DEPs for the SUD cases after rigorous criterion. Bioinformatics and Adaboost-recursive feature elimination (RFE) analysis further revealed that three of the 26 proteins (MYH6, COX5B and TNNT2) were potential discriminative biomarkers. In the training phase, MYH6 and COX5B were verified to be true DEPs in cardiac tissues from 29 independent SUD cases as compared with a serial of control cases (n = 42). Receiver operating characteristic (ROC) analysis illustrated that combination of MYH6 and COX5B achieved optimal diagnostic sensitivity (89.7 %) and specificity (84.4 %), with area under the curve (AUC) being 0.91. A diagnostic software based on the logistic regression formula derived from the training phase was then constructed. In the validation phase, the diagnostic software was applied to eight authentic SUD cases, seven (87.5 %) of which were accurately recognized. Our study provides a valid strategy towards practical diagnosis of SUD by integrating cardiac MYH6 and COX5B as dual diagnostic biomarkers.

The potential therapeutic effects of exosomes derived from bone marrow mesenchymal stem cells on ileum injury of a rat sepsis model (histological and immunohistochemical study).

Sepsis denotes a serious high mortality concern. The study was designed to evaluate the effect of mesenchymal stem cell exosomes (MSC-exosomes) on the evolution of the animal model of sepsis. In this study, 36 rats were distributed into three groups, (I) controls, (II) LPS-treated, and (III) LPS+MSC-EVs. Sepsis was simulated by administering E. coli-LPS to the laboratory animals. Group III was given MSC-exosomes four hours after the LPS injection. Forty-eight hours later rats were sacrificed. Ileum samples were excised, and processed for the histological assessment, immunohistochemical identification of CD44, and inducible nitric oxide synthase (iNOS). Ileum homogenate was used to estimate tumor necrosis factor α (TNF α) besides Cyclooxygenase-2 (COX 2). PCR was used for the detection of interleukin 1α (IL­1α), and interleukin 17 (IL­17). Statistical and morphometrical analysis was done. The LPS-treated group showed increased TNF-α, IL­1α, IL­17, and decreased COX 2. LPS administration led to cytoplasmic vacuolization of enterocytes, an increase in the vasculature, and cellular infiltrations invaded the lamina propria. There was a significant rise in goblet cells and the proportion of collagen fibers. Ultrastructurally, the enterocytes displayed nuclear irregularity, rough endoplasmic reticulum (rER) dilatation, and increased mitochondria number. Sepsis induces a significant increase in iNOS and a decrease in CD44 immune expressions. LPS+MSC-EVs group restored normal ileum structure and revealed a significant elevation in CD44 and a reduction in iNOS immunoreactions. LPS-sepsis induced an obvious ileum inflammatory deterioration ameliorated by MSC-exosomes, mostly through their antioxidant, anti-inflammatory, and anti-apoptotic properties.

Polygenic hazard score models for the prediction of Alzheimer's free survival using the lasso for Cox's proportional hazards model.

The prediction of the susceptibility of an individual to a certain disease is an important and timely research area. An established technique is to estimate the risk of an individual with the help of an integrated risk model, that is, a polygenic risk score with added epidemiological covariates. However, integrated risk models do not capture any time dependence, and may provide a point estimate of the relative risk with respect to a reference population. The aim of this work is twofold. First, we explore and advocate the idea of predicting the time-dependent hazard and survival (defined as disease-free time) of an individual for the onset of a disease. This provides a practitioner with a much more differentiated view of absolute survival as a function of time. Second, to compute the time-dependent risk of an individual, we use published methodology to fit a Cox's proportional hazard model to data from a genetic SNP study of time to Alzheimer's disease (AD) onset, using the lasso to incorporate further epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status, 10 leading principal components, and selected genomic loci. We apply the lasso for Cox's proportional hazards to a data set of 6792 AD patients (composed of 4102 cases and 2690 controls) and 87 covariates. We demonstrate that fitting a lasso model for Cox's proportional hazards allows one to obtain more accurate survival curves than with state-of-the-art (likelihood-based) methods. Moreover, the methodology allows one to obtain personalized survival curves for a patient, thus giving a much more differentiated view of the expected progression of a disease than the view offered by integrated risk models. The runtime to compute personalized survival curves is under a minute for the entire data set of AD patients, thus enabling it to handle datasets with 60,000-100,000 subjects in less than 1 h.

A constrained optimum adaptive design for dose finding in early phase clinical trials.

Recently, interest has grown in the development of dose-finding methods that consider both toxicity and efficacy as endpoints. Along with responses on these, the incorporation of pharmacokinetic (PK) data can be beneficial in terms of patients' safety and can also increase the efficiency of the design for finding the best dose for the next phase. In this paper, the maximum concentration (Cmax) is used as the PK measure guiding the dose selection. The ethically attractive approach, which is based on the probability of efficacy, is used as a dose optimisation criterion. At each stage of an adaptive trial, that dose is selected for which the criterion is maximised, subject to the constraints imposed on the Cmax and the probability of toxicity. The inter-patient variability of the PK model parameters is considered, and population D-optimal sampling time points for measuring the concentration of a drug in the blood are calculated. The method is illustrated with a one-compartment PK model with first-order absorption, with the parameters being assumed to be random. The Cox model for bivariate binary responses is employed to model the dose-response outcomes. The results of a simulation study for several plausible dose-response scenarios show a significant gain in the efficiency of the design, as well as a reduction in the proportion of toxic responses.

Efficacy of Rhamnus utilis Decne. Aqueous extract in mice with acute alcoholic liver injury and metabolomic study.

Rhamnus utilis Decne. (Family Rhamnaceae Juss.) leaf is commonly prepared as a anti-inflammatory herbal medicine and used for tea production. To investigate the mechanism of Rhamnus utilis Decne. aqueous extract (RDAE) against acute alcoholic liver disease (ALD) in mice. The ALD mouse (Male ICR) model was induced via intragastric administration of 52 % alcohol. Mice in each group were treated by gavage once daily with the RDAE (1.12, 2.25, 4.500 g/kg). The expression of proteins involved in the MAPKs/NF-κB/COX-2-iNOS pathway was measured by western blotting. Non-targeted metabolomics was used to determine metabolic profiles and critical pathways, while targeted metabolomics validated key amino acid metabolites. After administration of RDAE, the body mass of mice was significantly increased. The liver index was significantly decreased. Meanwhile, the serum levels of AST, ALT, TG, TC, MDA, TNF-α, IL-1ß and IL-6 were significantly decreased (P < 0.05, P < 0.01), but GSH level was inversely increased (P < 0.05). Metabolomic analysis revealed nine major pathways involved in the therapeutic effect of RDAE, including fructose and mannose metabolism. The levels of 7 amino acids including leucine, proline and alanine/sarcosine were significantly upregulated. Additionally, protein levels of p-NF-κB (p65)/NF-κB (p65), p-ERK1/2/ERK1/2, p-JNK/JNK, p-p38/p38, COX-2 and iNOS were significantly decreased (P < 0.01, P < 0.05). RDAE is used to treat acute ALD by improving lipid metabolism, inhibiting the expression of pro-inflammatory cytokines and regulating MAPKs/NF-κB/COX-2-iNOS signalling pathway. These findings provide valuable insights for acute ALD therapy based on traditional Chinese medicine (TCM).

Structural variations of a new fertility restorer gene, Rf20, underlie the restoration of wild abortive-type cytoplasmic male sterility in rice.

The discovery of a wild abortive-type cytoplasmic male sterile line and the breeding of its restorer line have led to the commercialization of three-line hybrid rice, which has contributed greatly to global food security. However, the molecular mechanisms underlying fertility abortion and the restoration of wild abortive-type cytoplasmic male sterile lines largely remain elusive. In this study, we cloned a restorer gene, Rf20, following a genome-wide association study analysis of the core parent lines of three-line hybrid rice. We found that Rf20 was present in all core parental lines, but different haplotypes and structural variants of its gene resulted in differences in Rf20 expression levels between sterile and restored lines. Rf20 could restore fertility in the wild abortive-type cytoplasmic male sterile line and was found to be responsible for fertility restoration in some cytoplasmic male sterile lines under high temperature. In addition, we found that Rf20 encodes a pentatricopeptide repeat protein that competes with WA352 for binding with COX11. This interaction enhances COX11's function as a scavenger of reactive oxygen species, which in turn restores pollen fertility. In this study, a new model of pentatricopeptide repeat proteins involved in the fertility recovery of cytoplasmic male sterile lines was proposed, which provides an important theoretical basis for the breeding of strong restorer lines and for overcoming high-temperature fertility recovery of some three-line sterile lines.

Supramolecular interactions in cocrystals of benzoic acid derivatives with selective COX-2 inhibitor etoricoxib.

The structures of three 1:1 cocrystal forms of etoricoxib {ETR; systematic name: 5-chloro-2-(6-methylpyridin-3-yl)-3-[4-(methylsulfonyl)phenyl]pyridine, C18H15ClN2O2S} have been synthesized and characterized by single-crystal X-ray diffraction; these are etoricoxib-benzoic acid (1/1), C18H15ClN2O2S·C7H6O2 (ETR-Bz), etoricoxib-4-fluorobenzoic acid (1/1), C18H15ClN2O2S·C7H5FO2 (ETR-PFB), and etoricoxib-4-nitrobenzoic acid (1/1), C18H15ClN2O2S·C7H5NO4 (ETR-PNB). Powder X-ray diffraction and thermal differential scanning calorimetry-thermogravimetry (DSC-TG) techniques were also used to characterize these multicomponent systems. Due to the influence of the corresponding acids, ETR shows different conformations. Furthermore, the energetic contributions of the supramolecular motifs have been established by energy framework studies of the stabilizing interaction forces and are consistent with the thermal stability of the cocrystals.

Investigating the effects of cytokine biomarkers on HIV incidence: a case study for individuals randomized to pre-exposure prophylaxis vs. control.

Introduction: Understanding and identifying the immunological markers and clinical information linked with HIV acquisition is crucial for effectively implementing Pre-Exposure Prophylaxis (PrEP) to prevent HIV acquisition. Prior analysis on HIV incidence outcomes have predominantly employed proportional hazards (PH) models, adjusting solely for baseline covariates. Therefore, models that integrate cytokine biomarkers, particularly as time-varying covariates, are sorely needed. Methods: We built a simple model using the Cox PH to investigate the impact of specific cytokine profiles in predicting the overall HIV incidence. Further, Kaplan-Meier curves were used to compare HIV incidence rates between the treatment and placebo groups while assessing the overall treatment effectiveness. Utilizing stepwise regression, we developed a series of Cox PH models to analyze 48 longitudinally measured cytokine profiles. We considered three kinds of effects in the cytokine profile measurements: average, difference, and time-dependent covariate. These effects were combined with baseline covariates to explore their influence on predictors of HIV incidence. Results: Comparing the predictive performance of the Cox PH models developed using the AIC metric, model 4 (Cox PH model with time-dependent cytokine) outperformed the others. The results indicated that the cytokines, interleukin (IL-2, IL-3, IL-5, IL-10, IL-16, IL-12P70, and IL-17 alpha), stem cell factor (SCF), beta nerve growth factor (B-NGF), tumor necrosis factor alpha (TNF-A), interferon (IFN) alpha-2, serum stem cell growth factor (SCG)-beta, platelet-derived growth factor (PDGF)-BB, granulocyte macrophage colony-stimulating factor (GM-CSF), tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), and cutaneous T-cell-attracting chemokine (CTACK) were significantly associated with HIV incidence. Baseline predictors significantly associated with HIV incidence when considering cytokine effects included: age of oldest sex partner, age at enrollment, salary, years with a stable partner, sex partner having any other sex partner, husband's income, other income source, age at debut, years lived in Durban, and sex in the last 30 days. Discussion: Overall, the inclusion of cytokine effects enhanced the predictive performance of the models, and the PrEP group exhibited reduced HIV incidences compared to the placebo group.

Canine ovarian epithelial tumours: histopathological and immunohistochemical evaluation with proposed histopathological classification system.

Canine ovarian epithelial tumours (OETs) are currently divided into ovarian adenomas and carcinomas, which are further inconsistently subclassified as papillary or cystic, whereas in human medicine, OETs are subdivided into several subtypes. This study aimed to establish clear morphological features enabling more consistent distinction between benign OETs and ovarian carcinomas (OvCas) as well as defining different histopathological patterns of canine OvCas. Analysis revealed a mitotic count threshold of >2 as a potential criterion for differentiating OvCas from benign OETs. Alongside ovarian adenomas, ovarian borderline tumours were introduced as a distinct category among benign OETs. OvCas exhibited five different histopathological patterns, namely papillary, solid with tubular differentiation, micropapillary, cystic and sarcomatous. Since some OvCas can morphologically overlap with other ovarian tumours, the expression of cytokeratin 7, a cytokeratin expressed in ovarian epithelium, was assessed and proved helpful, although it was not expressed in all cases. Furthermore, we investigated the expression of 14-3-3σ and cyclooxygenase 2 (COX-2). Based on the frequent expression of 14-3-3σ, this marker appears to have a role in canine OETs since it is not expressed in normal canine ovaries. The infrequent expression of COX-2 suggests that it is a poor candidate as a potential therapeutic target in canine OvCas.

Seagrass as a potential nutraceutical to decrease pro-inflammatory markers.

BACKGROUND: The Pro-inflammatory mediators such as prostaglandin E2, nitric oxide and TNF-α are the key players in the stimulation of the inflammatory responses. Thus, the pro-inflammatory mediators are considered to be potential targets for screening nutraceutical with anti-inflammatory activity. METHODS: In this context, we explored the anti-inflammatory potency of seagrass extract with western blot (Bio-Rad) analysis by using LPS induced RAW macrophages as in-vitro models, western blot analysis, In-silico methods using Mastero 13.0 software. RESULTS: The anti-inflammatory activity of Seagrass was demonstrated through down regulation of Pro-inflammatory markers such as Cyclooxygenase-2, induced Nitric oxide synthase and prostaglandin E synthase-1. The results were validated by docking the phytochemical constituents of seagrass namely Isocoumarin, Hexadecanoic acid, and Cis-9 Octadecenoic acid, 1,2 Benzene dicarboxylic acid and beta-sitosterol with TNF-alpha, COX-2, iNOS and PGES-1. CONCLUSION: The methanolic extract of seagrass Halophila beccarii is a potential nutraceutical agent for combating against inflammation with a significant anti-inflammatory activity.

Serum uric acid as a predictor of mortality in patients with stroke: results from National Health and Nutrition Examination Survey 2007-2016.

Objective: This research endeavors to explore the relationship between serum uric acid (SUA) concentration and all-cause mortality in stroke patients. Methods: We undertook a cross-sectional analysis utilizing data derived from the National Health and Nutrition Examination Survey (NHANES) spanning 2007 to 2016. The concentrations of SUA served as the independent variable, while the dependent variable was defined as all-cause mortality in stroke patients. The quartile method was utilized to classify uric acid levels into four distinct categories. Subsequently, three models were developed, and Cox proportional hazards regression was used to assess the effect of varying uric acid concentrations on the risk of all-cause mortality among stroke patients. Results: The study included a total of 10,805 participants, of whom 395 were stroke patients. Among all populations, the group with elevated levels of uric acid (Q4) exhibited a significant association with the overall mortality risk among stroke patients in all three models (model 1 p < 0.001, model 2 p < 0.001, model 3 p < 0.001). In the male population, there was no significant correlation observed between uric acid levels and the overall mortality risk among stroke patients in model 3 (Q2 p = 0.8, Q3 p = 0.2, Q4 p = 0.2). However, within the female population, individuals with high uric acid levels (Q4) demonstrated a noteworthy association with the overall mortality risk among stroke patients across all three models (model 1 p < 0.001, model 2 p < 0.001, model 3 p < 0.001). Conclusion: This cross-sectional investigation reveals a significant correlation between SUA levels and all-cause mortality in stroke patients, with a noticeable trend observed among females. Consequently, SUA may serve as a promising biomarker for assessing the prognosis of individuals affected by stroke.