Prevalence of Perceived Voice Disorders and Associated Risk Factors in Teachers and General Population in Croatia.

OBJECTIVES: There is no available data on the prevalence of voice disorders in Croatia. The objective of this research was to determine the prevalence of perceived voice disorders (PVD) in teachers and general population in Croatia using the Croatian Voice Handicap Index (VHI-HR) questionnaire. METHODS: This research was divided into two phases. In phase I, the potential of the VHI-HR questionnaire to distinguish individuals with and without voice disorders was assessed. A total of 113 participants completed the VHI-HR. Receiver operating characteristic analysis was performed. In phase II, a cross-sectional study was conducted. A total of 1898 participants, including 1088 teachers from 434 Croatian schools, and 810 nonteachers were included in the study. The questionnaire on sociodemographic factors, potential risk factors associated with voice disorders, and the VHI-HR was administered. The differences in the PVD prevalence in teachers and nonteacher adults and adverse effects of PVD were investigated. The multiple logistic regression model was used to examine the factors associated with PVD occurrence. RESULTS: In phase I, the cut-off point of 18.32 with 93.44% sensitivity and 98.08% specificity for VHI-HR was determined. In phase II, higher lifetime PVD prevalence was found among teachers. The point prevalence of PVD was 45.68% for teachers, and 21.11% for nonteachers. This study demonstrated that being a teacher, a woman, having a family history of voice disorders, reflux, working in environment with elevated noise levels, and having more than 30years of employment are associated with PVD occurrence. CONCLUSIONS: VHI-HR score of 19 and higher proves effective in distinguishing individuals with voice disorders from those without. The odds of having PVD for teachers are 2.83 times higher than for nonteachers. Risk factors for voice disorders, among others, include occupational use of voice and working in environments with elevated noise levels.

Gender differences in risk factors for ischemic stroke: a longitudinal cohort study in East China.

OBJECTIVES: Epidemiological studies of stroke and its risk factors can help develop strategies to prevent stroke. We aimed to explore the current gender-specific prevalence of stroke and associated risk factors. METHODS: Data were collected using a structured precoded questionnaire designed by the Stroke Screening and Prevention Programme of the National Health and Wellness Commission Stroke Prevention and Control Project Committee, between June 2020 and November 2021. A total of 7394 residents took part in the study, 187 of whom had a stroke. The baseline information of each participant was obtained and included in this study. The chi-square test and Kruskal-Wallis tests were used to examine the relationship between these indicators and stroke, and then multivariate logistic regression was used to construct the prediction scale between different genders. RESULTS: of 7394 participants,4571 (61.82%) were female. The overall prevalence of stroke patients in the study population was 2.53%, Multivariate analysis found that residence status (OR = 0.43, p = 0.002) 、HCY (OR = 0.962, p = 0.000)、Previous TIA (OR = 0.200, p = 0.002) 、Hypertension (OR = 0.33, p = 0.000) and Dyslipidemia (OR = 0.668, p = 0.028) were significant predictors of stroke. there are gender differences in the traditional risk factors for stroke, and women have more risk factors. ROC analysis confirmed the accuracy of the stroke risk model, and the AUC of the stroke risk model for the general population was 0.79 with p < 0.05. In the gender model, the female AUC was 0.796 (p < 0.05). and the male AUC was 0.786 with p < 0.05. CONCLUSION: The prevalence of stroke in adults aged 40 years and above is high in eastern China were high. management of risk factors can effectively prevent the occurrence of most strokes. more attention should be paid to gender differences associated with stroke.

Comparison of triglyceride glucose index and modified triglyceride glucose indices in prediction of cardiovascular diseases in middle aged and older Chinese adults.

BACKGROUND: Triglyceride and glucose (TyG) index, a surrogate marker of insulin resistance, has been validated as a predictor of cardiovascular disease. However, effects of TyG-related indices combined with obesity markers on cardiovascular diseases remained unknown. We aimed to investigate the associations between TyG index and modified TyG indices with new-onset cardiovascular disease and the time-dependent predictive capacity using a national representative cohort. METHODS: This study is a retrospective observational cohort study using data from China Health and Retirement Longitudinal Study (CHARLS) of 7 115 participants. The TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. The modified TyG indices were developed combining TyG with body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR). We used adjusted Cox proportional hazards regression to analyze the association and predictive capacity based on hazard ratio (HR) and Harrell's C-index. RESULTS: Over a 7-year follow-up period, 2136 participants developed cardiovascular disease, including 1633 cases of coronary heart disease and 719 cases of stroke. Compared with the lowest tertile group, the adjusted HR (95% CI) for new-onset cardiovascular disease in the highest tertile for TyG, TyG-BMI, TyG-WC, and TyG-WHtR were 1.215 (1.088-1.356), 1.073 (0.967-1.191), 1.078 (0.970-1.198), and 1.112 (1.002-1.235), respectively. The C-indices of TyG index for cardiovascular disease onset were higher than other modified TyG indices. Similar results were observed for coronary heart disease and stroke. CONCLUSION: TyG and TyG-WhtR were significantly associated with new-onset cardiovascular diseases, and TyG outperformed the modified TyG indices to identify individuals at risk of incident cardiovascular event.

Predicting operative outcomes of total shoulder arthroplasty using the model for end-stage liver disease score.

Background: The aim of this study was to assess the efficacy of the Model for End-Stage Liver Disease (MELD) score in predicting postoperative complications following total shoulder arthroplasty (TSA). Methods: The American College of Surgeons National Surgical Quality Improvement database was queried for all patients who underwent TSA between 2015 and 2019. The study population was subsequently classified into two categories: those with a MELD score ≥ 10 and those with a MELD score < 10. A total of 5265 patients undergoing TSA between 2015 and 2019 were included in this study. Among these, 4690 (89.1%) patients had a MELD score ≥ 10, while 575 (10.9%) patients had a MELD score < 10. Postoperative complications within 30 days of the TSA were collected. Multivariate logistic regression analysis was conducted to explore the correlation between a MELD score ≥ 10 and postoperative complications. The anchor based optimal cutoff was calculated by receiver operating characteristic analysis to determine the MELD score cutoff that most accurately predicts a specific complication. Youden's index (J) determined the optimal cutoff point calculation for the maximum sensitivity and specificity; these were deemed to be "acceptable" if the area under curve (AUC) was greater than 0.7 and "excellent" if greater than 0.8. Results: Multivariate regression analysis found a MELD score ≥ 10 to be independently associated with higher rates of reoperation (OR, 2.08; P = .013), cardiac complications (OR, 3.37; P = .030), renal complications (OR, 7.72; P = .020), bleeding transfusions (OR, 3.23; P < .001), and nonhome discharge (OR, 1.75; P < .001). The receiver operating characteristic analysis showed that AUC for a MELD score cutoff of 7.61 as a predictor of renal complications was 0.87 (excellent) with sensitivity of 100.0% and specificity of 70.0%. AUC for a MELD score cutoff of 7.76 as a predictor of mortality was 0.76 (acceptable) with sensitivity of 81.8% and specificity of 71.0%. Conclusion: A MELD score ≥ 10 was correlated with high rates of reoperation, cardiac complications, renal complications, bleeding transfusions, and nonhome discharge following TSA. MELD score cutoffs of 7.61 and 7.76 were effective in predicting renal complications and mortality, respectively.

Multiomics Analysis Revealed Colorectal Cancer Pathogenesis.

Gut microbiota-derived microbial compounds may link to the pathogenesis of colorectal cancer (CRC). However, the role of the host-microbiome in the incidence and progression of CRC remains elusive. We performed 16S rRNA sequencing, metabolomics, and proteomic studies on samples from 85 CRC patients who underwent colonoscopy examination and found two distinct changed patterns of microbiome in CRC patients. The relative abundances of Catabacter and Mogibacterium continuously increased from intramucosal carcinoma to advanced stages, whereas Clostridium, Anaerostipes, Vibrio, Flavonifractor, Holdemanella, and Hungatella were significantly altered only in intermediate lesions. Fecal metabolomics analysis exhibited consistent increases in bile acids, indoles, and urobilin as well as a decrease in heme. Serum metabolomics uncovered the highest levels of bilin, glycerides, and nucleosides together with the lowest levels of bile acids and amino acids in the stage of intermediate lesions. Three fecal and one serum dipeptides were elevated in the intermediate lesions. Proteomics analysis of colorectal tissues showed that oxidation and autophagy through the PI3K/Akt-mTOR signaling pathway contribute to the development of CRC. Diagnostic analysis showed multiomics features have good predictive capability, with AUC greater than 0.85. Our overall findings revealed new candidate biomarkers for CRC, with potentially significant diagnostic and prognostic capabilities.

Correlation of Hemoglobin Level With New Inflammatory Markers in the Emergency Department: A Retrospective Study Exploring Neutrophil-to-Lymphocyte, Monocyte-to-Lymphocyte, Platelet-to-Lymphocyte, and Mean Platelet Volume-to-Platelet Count Ratios.

Background Anemia of chronic disease is known to be associated with inflammation. However, the relationship between hemoglobin (Hb) levels and potential inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume-to-platelet count ratio (MPV/PC) has not been extensively studied. The primary objective of this retrospective analytical study conducted at Al Zahraa Hospital University Medical Center (ZHUMC), Beirut, was to investigate the correlation between Hb levels and potential inflammatory markers (NLR, MLR, PLR, MPV/PC) in patients visiting the emergency department (ED), across different genders and age groups. The secondary objectives were to compare Hb levels and inflammatory markers values between the referred medical ward group (the hospitalized patients who were admitted to the medical ward), and the non-referred to medical ward group (the patients who were discharged home from the ED), and to evaluate the predictability of inflammatory markers and Hb levels for referral to the medical ward, including the determination of optimal cutoff values for hospital admission to the medical ward. Methods We analyzed the blood parameters of 379 adult patients who presented to the ED with various medical complaints between September 1, 2022, and November 30, 2022 (three months). These patients were included in the study after we checked their eligibility regarding the verification of all our inclusion and exclusion criteria. Results Our findings revealed a significant negative correlation between Hb levels and PLR (r = -0.24) in both genders and across different age groups. The group referred to the medical ward exhibited lower Hb levels and higher NLR, MLR, and PLR values (P < 0.001). NLR/Hb ratio emerged as a predictive factor for admission in genitourinary (R² = 0.158; OR = 5.62) and respiratory groups (R² = 0.206; OR = 5.89), with specific cutoff values of 0.533 (Sensitivity = 57.1% & Specificity = 84.2%) and 0.276 (Sensitivity = 85% & Specificity = 51.1%), respectively. Conclusions Our study demonstrates that hemoglobin level negatively correlates with PLR. NLR, MLR, and PLR stand as important inflammatory markers. Moreover, we present the first study in the literature to show that NLR/Hb ratio can serve as a predictor for referral to the medical ward, particularly in the genitourinary and respiratory patient groups, underscoring its value in risk assessment as a prognostic marker reflecting the need for admission when the case is more serious.

Application of roc-analysis to assess the quality of predicting the risk of chronic rhinosinusitis recurrence.

OBJECTIVE: Aim: To propose a new, original approach to assessing the quality of a multivariate regression model for predicting the risk of recurrence in patients with chronic rhinosinusitis based on ROC analysis with the construction of appropriate curves, estimating the area under them, as well as calculating the sensitivity, accuracy, specificity, and predictive value of a positive and negative classification results, the likelihood ratio of positive and negative patient detection results. PATIENTS AND METHODS: Materials and Methods: 204 patients aged with a diagnosis of chronic rhinosinusitis were examined. RESULTS: Results: To build a multivariate regression model 14 probable factors of chronic rhinosinusitis occurrence were selected to determine the diagnostic value of the proposed model we calculate the sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), the likelihood ratio of a positive test (LR+), the likelihood ratio of a negative test (LR-) and prediction accuracy % of the proposed mathematical model. In order to determine the prognostic value of the risk ratio of CRS recurrence model, ROC- analysis was performed, ROC curves were obtained. CONCLUSION: Conclusions: The multivariate regression model makes it possible to predict potential complications and the possibility of disease recurrence. The construction of ROC-curves allows us to assert the excellent classification quality of chronic rhinosinusitis recurrence.

Methods of determining optimal cut-point of diagnostic biomarkers with application of clinical data in ROC analysis: an update review.

INTRODUCTION: An important application of ROC analysis is the determination of the optimal cut-point for biomarkers in diagnostic studies. This comprehensive review provides a framework of cut-point election for biomarkers in diagnostic medicine. METHODS: Several methods were proposed for the selection of optional cut-points. The validity and precision of the proposed methods were discussed and the clinical application of the methods was illustrated with a practical example of clinical diagnostic data of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and malondialdehyde (MDA) for prediction of inflammatory bowel disease (IBD) patients using the NCSS software. RESULTS: Our results in the clinical data suggested that for CRP and MDA, the calculated cut-points of the Youden index, Euclidean index, Product and Union index methods were consistent in predicting IBD patients, while for ESR, only the Euclidean and Product methods yielded similar estimates. However, the diagnostic odds ratio (DOR) method provided more extreme values for the optimal cut-point for all biomarkers analyzed. CONCLUSION: Overall, the four methods including the Youden index, Euclidean index, Product, and IU can produce quite similar optimal cut-points for binormal pairs with the same variance. The cut-point determined with the Youden index may not agree with the other three methods in the case of skewed distributions while DOR does not produce valid informative cut-points. Therefore, more extensive Monte Carlo simulation studies are needed to investigate the conditions of test result distributions that may lead to inconsistent findings in clinical diagnostics.

Classification performance of sEMG and kinematic parameters for distinguishing between non-lame and induced lameness conditions in horses.

Despite its proven research applications, it remains unknown whether surface electromyography (sEMG) can be used clinically to discriminate non-lame from lame conditions in horses. This study compared the classification performance of sEMG absolute value (sEMGabs) and asymmetry (sEMGasym) parameters, alongside validated kinematic upper-body asymmetry parameters, for distinguishing non-lame from induced fore- (iFL) and hindlimb (iHL) lameness. Bilateral sEMG and 3D-kinematic data were collected from clinically non-lame horses (n = 8) during in-hand trot. iFL and iHL (2-3/5 AAEP) were induced on separate days using a modified horseshoe, with baseline data initially collected each day. sEMG signals were DC-offset removed, high-pass filtered (40 Hz), and full-wave rectified. Normalized, average rectified value (ARV) was calculated for each muscle and stride (sEMGabs), with the difference between right and left-side ARV representing sEMGasym. Asymmetry parameters (MinDiff, MaxDiff, Hip Hike) were calculated from poll, withers, and pelvis vertical displacement. Receiver-operating-characteristic (ROC) and area under the curve (AUC) analysis determined the accuracy of each parameter for distinguishing baseline from iFL or iHL. Both sEMG parameters performed better for detecting iHL (0.97 ≥ AUC ≥ 0.48) compared to iFL (0.77 ≥ AUC ≥ 0.49). sEMGabs performed better (0.97 ≥ AUC ≥ 0.49) than sEMGasym (0.76 ≥ AUC ≥ 0.48) for detecting both iFL and iHL. Like previous studies, MinDiff Poll and Pelvis asymmetry parameters (MinDiff, MaxDiff, Hip Hike) demonstrated excellent discrimination for iFL and iHL, respectively (AUC > 0.95). Findings support future development of multivariate lameness-detection approaches that combine kinematics and sEMG. This may provide a more comprehensive approach to diagnosis, treatment, and monitoring of equine lameness, by measuring the underlying functional cause(s) at a neuromuscular level.

The clinical utility of cystatin C based eGFR in assessing renal function among HIV/AIDs patients on ART at Mildmay Uganda.

BACKGROUND: In clinical practice, Measurement of estimated glomerular filtration rates (eGFR) is the gold standard assessing renal function the glomerular filtration rate often estimated from plasma creatinine. Several studies have shown Cystatin C based eGFR (Cys C) to be a better parameter for the diagnosis of impaired renal function. Cystatin C based eGFR has been proposed as a potential renal function marker but its use in HIV&AIDS patients has not been well evaluated. METHODS: A cross sectional study was carried out on 914 HIV&AIDS patients on antiretroviral therapy (ART) attending Mildmay Uganda for care and treatment between January to March 2015. Serum Cystatin C based eGFR was measured using the particle enhanced immunoturbidimetric assay. Creatinine was analyzed using enzymatic Creatinine PAP method and creatinine clearance was calculated according to C&G. RESULTS: The sensitivity of Cystatin C based eGFR was 15.1% (95% CI = 8.4, 24) with specificity 99.3% (95% CI = 98- 99.7). The positive and negative predictive values were 70.0% (95% CI 45.7-88.1) and 91.2% (95% CI 98.11-92.94) respectively. The positive likelihood ratio was 18.81 and negative likelihood ratio was 0.85. Cystatin C based eGFR had diagnostic accuracy of 90.7 and area under curve was 0.768. CONCLUSION: Cystatin C based eGFR exhibited a high specificity and a high positive likelihood ratio in diagnosis of kidney disease among HIV&AIDS patients. Cystatin C based eGFR can be used as a confirmatory test.

Benchmarking different docking protocols for predicting the binding poses of ligands complexed with cyclooxygenase enzymes and screening chemical libraries.

Introduction: Non-steroidal anti-inflammatory drugs (NSAIDs) constitute an important class of pharmaceuticals acting on cyclooxygenase COX-1 and COX-2 enzymes. Due to their numerous severe side effects, it is necessary to search for new selective, safe, and effective anti-inflammatory drugs. In silico design of novel therapeutics plays an important role in nowadays drug discovery pipelines. In most cases, the design strategies require the use of molecular docking calculations. The docking procedure may require case-specific condition for a successful result. Additionally, many different docking programs are available, which highlights the importance of identifying the most proper docking method and condition for a given problem. Methods: In the current work, the performances of five popular molecular docking programs, namely, GOLD, AutoDock, FlexX, Molegro Virtual Docker (MVD) and Glide to predict the binding mode of co- crystallized inhibitors in the structures of known complexes available for cyclooxygenases were evaluated. Furthermore, the best performers, Glide, AutoDock, GOLD and FlexX, were further evaluated in docking-based virtual screening of libraries consisted of active ligands and decoy molecules for cyclooxygenase enzymes and the obtained docking scores were assessed by receiver operating characteristics (ROC) analysis. Results: The results of docking experiments indicated that Glide program outperformed other docking programs by correctly predicting the binding poses (RMSD less than 2 Å) of all studied co-crystallized ligands of COX-1 and COX-2 enzymes (i.e., the performance was 100%). However, the performances of the other studied docking methods for correctly predicting the binding poses of the ligands were between 59% to 82%. Virtual screening results treated by ROC analysis revealed that all tested methods are useful tools for classification and enrichment of molecules targeting COX enzymes. The obtained AUCs range between 0.61-0.92 with enrichment factors of 8 - 40 folds. Conclusion: The obtained results support the importance of choosing appropriate docking method for predicting ligand-receptor binding modes, and provide specific information about docking calculations on COXs ligands.

Development of recombinant capsid protein-based single serum dilution ELISA for sero-detection of porcine circovirus type 2 infection in pigs.

Porcine Circovirus 2 (PCV2) is the major causative agent of postweaning multisystemic wasting syndrome (PMWS) of swine and is one of the reasons for severe economic loss in swine industry. In India, there is a considerable prevalence rate of PCV2 infection in pig population, PCV2d being the most prominent genotype. Proper sero-diagnosis and sero-surveillance of the disease is formulated as an effective control measure. In this study, a recombinant capsid protein-based single serum dilution indirect ELISA was developed for determination of antibody titre of the infected pigs. The capsid protein (Cap) of PCV2d was produced in Saccharomyces cerevisiae cells and the capsid protein was purified by affinity chromatography. This recombinant protein was used as a coating antigen to develop a cost effective, highly sensitive and specific single serum dilution ELISA. The in-house developed ELISA was optimized to be used in a 1:200 single serum dilution. The developed ELISA along with a commercial ELISA kit were compared with a sensitive immuno-peroxidase assay (IPMA) by receiver-operating characteristics (ROC) test. Our results showed that the developed single serum dilution ELISA had a higher sensitivity and specificity in comparison to the commercial ELISA. The area under the ROC curve (AUC) also confirmed that the developed ELISA had a better overall diagnostic performance in comparison to the commercial ELISA kit.

Semi-supervised ROC analysis for reliable and streamlined evaluation of phenotyping algorithms.

OBJECTIVE: High-throughput phenotyping will accelerate the use of electronic health records (EHRs) for translational research. A critical roadblock is the extensive medical supervision required for phenotyping algorithm (PA) estimation and evaluation. To address this challenge, numerous weakly-supervised learning methods have been proposed. However, there is a paucity of methods for reliably evaluating the predictive performance of PAs when a very small proportion of the data is labeled. To fill this gap, we introduce a semi-supervised approach (ssROC) for estimation of the receiver operating characteristic (ROC) parameters of PAs (eg, sensitivity, specificity). MATERIALS AND METHODS: ssROC uses a small labeled dataset to nonparametrically impute missing labels. The imputations are then used for ROC parameter estimation to yield more precise estimates of PA performance relative to classical supervised ROC analysis (supROC) using only labeled data. We evaluated ssROC with synthetic, semi-synthetic, and EHR data from Mass General Brigham (MGB). RESULTS: ssROC produced ROC parameter estimates with minimal bias and significantly lower variance than supROC in the simulated and semi-synthetic data. For the 5 PAs from MGB, the estimates from ssROC are 30% to 60% less variable than supROC on average. DISCUSSION: ssROC enables precise evaluation of PA performance without demanding large volumes of labeled data. ssROC is also easily implementable in open-source R software. CONCLUSION: When used in conjunction with weakly-supervised PAs, ssROC facilitates the reliable and streamlined phenotyping necessary for EHR-based research.

Predicting the outcome of death by CALL Score in COVID-19 patients

SUMMARY OBJECTIVE: The aim of this study was to assess the performance of the CALL Score tool in predicting the death outcome in COVID-19 patients. METHODS: A total of 897 patients were analyzed. Univariate and multivariate logistic regression analyses were conducted to determine the association between characteristics of the CALL Score and the occurrence of death. The relationship between CALL Score risk classification and the occurrence of death was also examined. Receiver operating characteristic curve analysis was performed to identify optimal cutoff points for the CALL Score and the outcome. RESULTS: The study revealed that age>60 years, DHL>500, and lymphocyte count ≤1000 emerged as independent predictors of death. Higher risk classifications of the CALL Score were associated with an increased likelihood of death. The optimal CALL Score cutoff point for predicting the death outcome was 9.5 (≥9.5), with a sensitivity of 70.4%, specificity of 80.3%, and accuracy of 80%. CONCLUSION: The CALL Score showed promising discriminatory ability for death outcomes in COVID-19 patients. Age, DHL level, and lymphocyte count were identified as independent predictors. Further validation and external evaluation are necessary to establish the robustness and generalizability of the CALL Score in diverse clinical settings.

Evaluating joint confidence region of hypervolume under ROC manifold and generalized Youden index.

In biomarker evaluation/diagnostic studies, the hypervolume under the receiver operating characteristic manifold ( HUM K $$ {\mathrm{HUM}}_K $$ ) and the generalized Youden index ( J K $$ {J}_K $$ ) are the most popular measures for assessing classification accuracy under multiple classes. While HUM K $$ {\mathrm{HUM}}_K $$ is frequently used to evaluate the overall accuracy, J K $$ {J}_K $$ provides direct measure of accuracy at the optimal cut-points. Simultaneous evaluation of HUM K $$ {\mathrm{HUM}}_K $$ and J K $$ {J}_K $$ provides a comprehensive picture about the classification accuracy of the biomarker/diagnostic test under consideration. This article studies both parametric and non-parametric approaches for estimating the confidence region of HUM K $$ {\mathrm{HUM}}_K $$ and J K $$ {J}_K $$ for a single biomarker. The performances of the proposed methods are investigated by an extensive simulation study and are applied to a real data set from the Alzheimer's Disease Neuroimaging Initiative.

Elevated Troponin I as a Marker for Unfavorable Outcomes in Acute Ischemic Stroke.

OBJECTIVE: To assess if elevated cardiac troponin I (cTnI) serves as a sign of unfavorable functional outcomes in ischemic stroke. METHODS: In this single-center prospective cohort study, 100 consecutive patients admitted with acute ischemic stroke (normal troponin I group n = 52, raised troponin I group n = 48) were included. Hospital mortality was documented in both groups; the remaining patients were followed up to 90 days. Then two groups were compared in terms of unfavorable short-term outcomes (Modified Rankin Scale > 3) and mortality. Multivariate logistic regression was conducted to determine the predictive value of elevated cTnI. The Kaplan-Meier curve was drawn and compared to determine the difference in survival between the two groups. To find out the most probable cut-off level for an unfavorable outcome, a receiver operating characteristic (ROC) analysis was conducted. RESULT:  A higher frequency of coronary artery disease (p=0.030), higher National Institutes of Health Stroke Scale (NIHSS) (p=0.008) score, and lower Glasgow Coma Scale (GCS) (p=0.002) was observed in raised troponin I group. Even after the exclusion of confounding elevated troponin I was found to be an independent predictor of unfavorable outcomes (adjusted odds ratio, OR 8.25 {95% confidence interval, CI: 2.65-25.75}; p<0.001). The patients with raised troponin I had a significantly lower rate of survival after 90 days (p=0.022). The elevated troponin I was observed to have a significantly high accuracy (p<0.001; area under curve, AUC: 0.768 {moderate accuracy}, 95% CI: 0 .676 to 0.861) in predicting unfavorable outcomes. CONCLUSION: Elevated cTnI is independently associated with unfavorable short-term outcomes. It is also associated with a lower rate of survival.

Discriminant Analysis of Aroma Differences between Cow Milk Powder and Special Milk Powder (Donkey, Camel, and Horse Milk Powder) in Xinjiang Based on GC-IMS and Multivariate Statistical Methods.

In order to explore the aromatic differences between Xinjiang cow milk powder and specialty milk powder (donkey, camel, and horse milk powder), Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) analysis was employed to investigate the volatile compounds in these four types of milk powders. A total of 61 volatile substances were detected, with ketones, aldehydes, and alcohols being the primary flavor components in the milk powders. While the aromatic components of the different milk powders showed similarities in terms of types, there were significant differences in their concentrations, exhibiting distinct characteristics for each type. The Partial Least Squares Discriminant Analysis (PLS-DA) showed that there were 15, 14, and 23 volatile compounds that could be used for discrimination of cow milk powder against specialty milk powders, respectively. And it was validated by Receiver Operating Characteristic (ROC) analysis, and finally, 8, 6, and 19 volatile compounds were identified as valid differential marker substances. To facilitate visual discrimination between the different milk powders, we established GC-IMS fingerprint spectra based on the final discriminant markers. These studies provide theoretical guidance for the application of volatile compounds to discriminate adulteration of milk powder marketed in Xinjiang.

[Assessment of environmental and genetic risk factors for the development of primary open-angle glaucoma]. / Sredovye i geneticheskie faktory riska razvitiya pervichnoi otkrytougol'noi glaukomy.

Primary open-angle glaucoma (POAG) is a multifactorial disease with both environmental and genetic factors involved in its pathogenesis. PURPOSE: The study evaluates the role of a number of environmental and genetic risk factors in the risk of POAG development and builds a prognostic model. MATERIAL AND METHODS: The study group included 197 patients aged 44 to 90 years (98 - patients with POAG, 99 - the control group), who were treated in the Republican Clinical Ophthalmological Hospital of the Ministry of Health of the Republic of Tatarstan named after Prof. E.V. Adamyuk. RESULTS: Age, family history of the disease, presence of type 2 diabetes mellitus, arterial hypertension were revealed to be associated with an increased risk of POAG development. The polymorphisms of matrix metalloproteinase MMP9 and vitamin D receptor (VDR) genes were shown to influence the development of POAG. The prognostic model considering these factors had high sensitivity and specificity (72.0% and 82.6% respectively). CONCLUSION: The prognostic model based on environmental and genetic factors is important for assessing the risk of POAG and early detection of the disease.

Characterization of a miRNA Signature with Enhanced Diagnostic and Prognostic Power for Patients with Bladder Carcinoma.

Bladder carcinoma is globally among the most prevalent cancers and is associated with a high mortality rate at advanced stages. Its detection relies on invasive diagnostic methods that are unpleasant for the patient. Non-invasive molecular biomarkers, such as miRNAs, could serve as alternatives for early detection and prognosis of this malignancy. We designed a computational approach that combines transcriptome profiling, survival analyses, and calculation of diagnostic power in order to isolate miRNA signatures with high diagnostic and prognostic utility. Our analysis of TCGA-BLCA data from 429 patients yielded one miRNA signature, consisting of five upregulated and three downregulated miRNAs with cumulative diagnostic power that outperforms current diagnostic methods. The same miRNAs have a strong prognostic significance since their expression is associated with the overall survival of bladder cancer patients. We evaluated the expression of this signature in 19 solid cancer types, supporting its unique diagnostic utility for bladder carcinoma. We provide computational evidence regarding the functional implications of this miRNA signature in cell cycle regulation, demonstrating its abundance in body fluids, including peripheral blood and urine. Our study characterized a novel miRNA signature with the potential to serve as a non-invasive method for bladder cancer diagnosis and prognosis.

Elevated concentrations of Neu5Ac and Neu5,9Ac2 in human plasma: potential biomarkers of cardiovascular disease.

Cardiovascular disease (CVD) is a group of health conditions affecting the heart and vascular system with very high prevalence and mortality rates. The presence of CVD is characterised by high levels of inflammation which have previously been associated with increased plasma concentrations of N-acetyl neuraminic acid (Neu5Ac). While Neu5Ac has been studied in the context of CVD, Neu5,9Ac2 has not, despite being the second most abundant sialic acid in human plasma. A small-scale pilot study of thirty plasma samples from patients with diagnosed CVD, and thirty age and sex-matched healthy controls, was designed to gain insight into sialic acids as biomarkers for CVD and potential future areas of study. Each sample was assayed for Neu5Ac and Neu5,9Ac2 concentrations. Mean Neu5Ac and Neu5,9Ac2 concentrations were significantly elevated in patients with CVD compared to healthy controls (Neu5Ac: P < 0.001; Neu5,9Ac2: P < 0.04). Receiver operator curve (ROC) analysis indicated that both Neu5Ac and Neu5,9Ac2 have reasonable predictive power for the presence of CVD (Neu5Ac AUC: 0.86; Neu5,9Ac2 AUC: 0.71). However, while Neu5Ac had both good sensitivity (0.82) and specificity (0.81), Neu5,9Ac2 had equivalent specificity (0.81) but very poor sensitivity (0.44). A combination marker of Neu5Ac + Neu5,9Ac2 showed improvement over Neu5Ac alone in terms of predictive power (AUC: 0.93), sensitivity (0.87), and specificity (0.90). Comparison to a known inflammatory marker, high sensitivity c-reactive protein (hs-CRP: P-value: NS, ROC:0.50) was carried out, showing that both Neu5Ac and Neu5,9Ac2 outperformed this marker. Further to this, hs-CRP values were combined with the three different sialic acid markers to determine any effect on the AUC values. A slight improvement in AUC was noted for each of the combinations, with Neu5Ac + Neu5,9Ac2 + hs-CRP giving the best AUC of 0.97 overall. Thus, Neu5Ac would appear to offer good potential as a predictive marker for the presence of CVD, which the addition of Neu5,9Ac2 predictive power improves, with further improvement seen by the addition of hs-CRP.