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.

Systematic review of the complement components as potential biomarkers of pre-eclampsia: pitfalls and opportunities.

The complement system (C) is a crucial component of the innate immune system. An increasing body of research has progressively shed light on the pivotal role of C in immunological tolerance at the feto-maternal interface. Excessive C activation or impaired C regulation may determine the onset of pregnancy-related pathological conditions, including pre-eclampsia (PE). Thus, several studies have investigated the presence of C components or split products in blood matrixes (i.e., plasma, serum), urine, and amniotic fluid in PE. In the current study, we systematically reviewed the currently available scientific literature reporting measurements of C components as circulating biomarkers in PE, based on a literature search using Pubmed, Scopus, and Embase databases. A total of 41 out of 456 studies were selected after full-text analysis. Fourteen studies (34.1%) were identified as measuring the blood concentrations of the classical pathway, 5 (12.1%) for the lectin pathway, 28 (68.3%) for the alternative pathway, 17 (41.5%) for the terminal pathway components, and 16 (39%) for C regulators. Retrieved results consistently reported C4, C3, and factor H reduction, and increased circulating levels of C4d, Bb, factor D, C3a, C5a, and C5b-9 in PE compared to normal pregnancies, depicting an overall scenario of excessive C activation and aberrant C regulation. With evidence of C activation and dysregulation, C-targeted therapy is an intriguing perspective in PE management. Moreover, we also discussed emerging pitfalls in C analysis, mainly due to a lack of experimental uniformity and biased cohort selection among different studies and laboratories, aiming to raise a more comprehensive awareness for future standardization. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024503070.

Deciphering the molecular landscape of rheumatoid arthritis offers new insights into the stratified treatment for the condition.

Background: For Rheumatoid Arthritis (RA), a long-term chronic illness, it is essential to identify and describe patient subtypes with comparable goal status and molecular biomarkers. This study aims to develop and validate a new subtyping scheme that integrates genome-scale transcriptomic profiles of RA peripheral blood genes, providing a fresh perspective for stratified treatments. Methods: We utilized independent microarray datasets of RA peripheral blood mononuclear cells (PBMCs). Up-regulated differentially expressed genes (DEGs) were subjected to functional enrichment analysis. Unsupervised cluster analysis was then employed to identify RA peripheral blood gene expression-driven subtypes. We defined three distinct clustering subtypes based on the identified 404 up-regulated DEGs. Results: Subtype A, named NE-driving, was enriched in pathways related to neutrophil activation and responses to bacteria. Subtype B, termed interferon-driving (IFN-driving), exhibited abundant B cells and showed increased expression of transcripts involved in IFN signaling and defense responses to viruses. In Subtype C, an enrichment of CD8+ T-cells was found, ultimately defining it as CD8+ T-cells-driving. The RA subtyping scheme was validated using the XGBoost machine learning algorithm. We also evaluated the therapeutic outcomes of biological disease-modifying anti-rheumatic drugs. Conclusions: The findings provide valuable insights for deep stratification, enabling the design of molecular diagnosis and serving as a reference for stratified therapy in RA patients in the future.

Multiple sclerosis disease activity, a multi-biomarker score of disease activity and response to treatment in multiple sclerosis.

Regular assessment of disease activity in relapsing-remitting multiple sclerosis (RRMS) is required to optimize clinical outcomes. Biomarkers can be a valuable tool for measuring disease activity in multiple sclerosis (MS) if they reflect the pathological processes underlying MS pathogenicity. In this pilot study, we combined multiple biomarkers previously analyzed in RRMS patients into an MS disease activity (MSDA) score to evaluate their ability to predict relapses and treatment response to glatiramer acetate (GA). Response Gene to Complement 32 (RGC-32), FasL, IL-21, SIRT1, phosphorylated SIRT1 (p-SIRT1), and JNK1 p54 levels were used to generate cut-off values for each biomarker. Any value below the cutoff for RGC-32, FasL SIRT1, or p-SIRT1 or above the cutoff for IL-21 or JNK1 p54 was given a +1 value, indicating relapse or lack of response to GA. Any value above the cutoff value for RGC-32, FasL, SIRT1, p-SIRT1 or below that for IL-21 or JNK1 p54 was given a -1 value, indicating clinical stability or response to GA. An MSDA score above +1 indicated a relapse or lack of response to treatment. An MSDA score below -1 indicated clinical stability or response to treatment. Our results showed that the MSDA scores generated using either four or six biomarkers had a higher sensitivity and specificity and significantly correlated with the expanded disability status scale. Although these results suggest that the MSDA test can be useful for monitoring therapeutic response to biologic agents and assessing clinically challenging situations, the present findings need to be confirmed in larger studies.

Effects of vitamin D supplementation on oxidative stress biomarkers of Iranian women with polycystic ovary syndrome: a meta-analysis study.

Objective: To identify the impact of redox imbalance on the clinical evolution of patients with polycystic ovary syndrome and carry out a qualitative and quantitative projection of the benefits of vitamin D supplementation. Data sources: Combinations of the keywords polycystic ovary syndrome, vitamin D, oxidative stress, reactive oxygen species, antioxidant, and free radicals were used in PubMed, Cochrane Library, LILACS, EMBASE, and Web of Science databases. The last search was conducted on August 22, 2023.Selection of studies: Based on the inclusion and exclusion criteria, studies were selected considering a low risk of bias, published in the last 5 years in English, which investigated the effects of vitamin D supplementation in women with PCOS, focusing on oxidative stress markers. Of the 136 articles retrieved, 6 intervention studies (445 women) were included. Data collection: The risk of bias in included studies was assessed using the Jadad scale, and analysis and visualization of continuous data were performed using Review Manager 5.4.1, summarized as standardized mean differences (SMD) with confidence intervals (CI) of 95%. Data synthesis: Vitamin D effectively reduced malondialdehyde (P=0.002) and total testosterone (P=0.0004) levels and increased total antioxidant capacity levels (P=0.01). Although possible improvements in the modified Ferriman-Gallwey hirsutism score, levels of sex hormone-binding globulin, and free androgen index were identified and the results were not statistically significant. Conclusion: Vitamin D is a promising alternative for the treatment of PCOS with a positive influence on the oxidative, metabolic, and endocrine disorders of this syndrome.

Nonparametric receiver operating characteristic curve analysis with an imperfect gold standard.

This article addresses the challenge of estimating receiver operating characteristic (ROC) curves and the areas under these curves (AUC) in the context of an imperfect gold standard, a common issue in diagnostic accuracy studies. We delve into the nonparametric identification and estimation of ROC curves and AUCs when the reference standard for disease status is prone to error. Our approach hinges on the known or estimable accuracy of this imperfect reference standard and the conditional independent assumption, under which we demonstrate the identifiability of ROC curves and propose a nonparametric estimation method. In cases where the accuracy of the imperfect reference standard remains unknown, we establish that while ROC curves are unidentifiable, the sign of the difference between two AUCs is identifiable. This insight leads us to develop a hypothesis-testing method for assessing the relative superiority of AUCs. Compared to the existing methods, the proposed methods are nonparametric so that they do not rely on the parametric model assumptions. In addition, they are applicable to both the ROC/AUC analysis of continuous biomarkers and the AUC analysis of ordinal biomarkers. Our theoretical results and simulation studies validate the proposed methods, which we further illustrate through application in two real-world diagnostic studies.

Utilizing Raman spectroscopy for urinalysis to diagnose acute kidney injury stages in cardiac surgery patients.

BACKGROUND: The successful treatment and improvement of acute kidney injury (AKI) depend on early-stage diagnosis. However, no study has differentiated between the three stages of AKI and non-AKI patients following heart surgery. This study will fill this gap in the literature and help to improve kidney disease management in the future. METHODS: In this study, we applied Raman spectroscopy (RS) to uncover unique urine biomarkers distinguishing heart surgery patients with and without AKI. Given the amplified risk of renal complications post-cardiac surgery, this approach is of paramount importance. Further, we employed the partial least squares-support vector machine (PLS-SVM) model to distinguish between all three stages of AKI and non-AKI patients. RESULTS: We noted significant metabolic disparities among the groups. Each AKI stage presented a distinct metabolic profile: stage 1 had elevated uric acid and reduced creatinine levels; stage 2 demonstrated increased tryptophan and nitrogenous compounds with diminished uric acid; stage 3 displayed the highest neopterin and the lowest creatinine levels. We utilized the PLS-SVM model for discriminant analysis, achieving over 90% identification rate in distinguishing AKI patients, encompassing all stages, from non-AKI subjects. CONCLUSIONS: This study characterizes the incidence and risk factors for AKI after cardiac surgery. The unique spectral information garnered from this study can also pave the way for developing an in vivo RS method to detect and monitor AKI effectively.

The role of oxidative stress in the pathomechanism of major mood disorders: a narrative review with a special focus on uric acid.

Major mood disorder (i.e. major depressive disorder [MDD] and bipolar disorders [BPDs]) are among the most prevalent and disabling mental illnesses. Several, frequently intertwining theories (such as the monoamine, neuroinflammatory and neurotrophic theories) exist to explain the etiopathogenic background of mood disorders. A lesser-known hypothesis addresses the role of oxidative stress (OS; i.e. the overproduction and accumulation of free radicals) in the pathogenesis of these mental disorders. Free radicals are capable of damaging phospholipids, polyunsaturated fatty acids, proteins and nucleic acids. In the brain, OS impairs inter alia synaptic signalling and neuroplasticity. In the current paper, in addition to a brief description of the aforementioned pathophysiological processes involved in mood disorders (with a special focus on OS), we discuss in detail the results of studies on changes in non-enzymatic antioxidant uric acid (UA) levels in major mood disorders. Findings to date indicate that UA - a routinely measured laboratory parameter - may be a candidate biomarker to distinguish between MDD and BPD. Since the diagnostic criteria are identical for major depressive episodes regardless of whether the episode occurs in the context of MDD or BPD and also bearing in mind that the treatment for those two disorders is different, we may conclude that the identification of biomarkers to enable MDD to be distinguished from BPD would be of great clinical relevance. (Neuropsychopharmacol Hung 2024; 26(2): 105-124) Keywords: major depressive disorder, bipolar disorder, brain, oxidative stress, uric acid.

Plasma metabolites are altered before and after diagnosis of preeclampsia or fetal growth restriction.

Metabolomics is the study of small molecules (metabolites), within cells, tissues and biofluids. Maternal metabolites can provide important insight into the health and development of both mother and fetus throughout pregnancy. This study assessed metabolic profiles in the maternal circulation prior to and at the time of diagnosis of preeclampsia and fetal growth restriction. Maternal plasma samples were collected from two independent cohorts: (1) Established disease cohort: 50 participants diagnosed with early-onset preeclampsia (< 34 weeks' gestation), 14 with early-onset fetal growth restriction, and 25 gestation-matched controls. (2) Prospective cohort, collected at 36 weeks' gestation before diagnosis: 17 participants later developed preeclampsia, 49 delivered infants with fetal growth restriction (birthweight < 5th centile), and 72 randomly selected controls. Metabolic evaluation was performed by Metabolomics Australia on the Agilent 6545 QTOF Mass Spectrometer. In the established disease cohort, 77 metabolites were altered in circulation from participants with preeclampsia - increased L-cysteine (3.73-fold), L-cystine (3.28-fold), L-acetylcarnitine (2.57-fold), and carnitine (1.53-fold) (p < 0.05). There were 53 metabolites dysregulated in participants who delivered a fetal growth restriction infant-including increased levulinic acid, citric acid (1.93-fold), and creatine (1.14-fold) (p < 0.05). In the prospective cohort, 30 metabolites were altered in participants who later developed preeclampsia at term - reduced glutaric acid (0.85-fold), porphobilinogen (0.77-fold) and amininohippuric acid (0.82-fold) (p < 0.05) was observed. There were 5 metabolites altered in participants who later delivered a fetal growth restriction infant - including reduced 3-methoxybenzenepropanoic acid (p < 0.05). Downstream pathway analysis revealed aminoacyl-tRNA biosynthesis to be most significantly altered in the established cohort in preeclampsia (13/48 hits, p < 0.001) and fetal growth restriction (7/48 hits, p < 0.001). The predictive cohort showed no significant pathway alterations. This study observed altered metabolites in maternal plasma collected before and after diagnosis of a preeclampsia or fetal growth restriction. While a significant number of metabolites were altered with established disease, few changes were observed in the predictive cohort. Thus, metabolites measured in this study may not be useful as predictors of preeclampsia or fetal growth restriction.

Biliary atresia and cholestasis plasma non-targeted metabolomics unravels perturbed metabolic pathways and unveils a diagnostic model for biliary atresia.

The clinical diagnosis of biliary atresia (BA) poses challenges, particularly in distinguishing it from cholestasis (CS). Moreover, the prognosis for BA is unfavorable and there is a dearth of effective non-invasive diagnostic models for detection. Therefore, the aim of this study is to elucidate the metabolic disparities among children with BA, CS, and normal controls (NC) without any hepatic abnormalities through comprehensive metabolomics analysis. Additionally, our objective is to develop an advanced diagnostic model that enables identification of BA. The plasma samples from 90 children with BA, 48 children with CS, and 47 NC without any liver abnormalities children were subjected to metabolomics analysis, revealing significant differences in metabolite profiles among the 3 groups, particularly between BA and CS. A total of 238 differential metabolites were identified in the positive mode, while 89 differential metabolites were detected in the negative mode. Enrichment analysis revealed 10 distinct metabolic pathways that differed, such as lysine degradation, bile acid biosynthesis. A total of 18 biomarkers were identified through biomarker analysis, and in combination with the exploration of 3 additional biomarkers (LysoPC(18:2(9Z,12Z)), PC (22:5(7Z,10Z,13Z,16Z,19Z)/14:0), and Biliverdin-IX-α), a diagnostic model for BA was constructed using logistic regression analysis. The resulting ROC area under the curve was determined to be 0.968. This study presents an innovative and pioneering approach that utilizes metabolomics analysis to develop a diagnostic model for BA, thereby reducing the need for unnecessary invasive examinations and contributing to advancements in diagnosis and prognosis for patients with BA.

Quantitative urinary proteome analysis reveals potential biomarkers for disease activity of Behcet's disease uveitis.

PURPOSE: Behçet's disease-associated uveitis (BDU) is a severe, recurrent inflammatory condition affecting the eye and is part of a systemic vasculitis with unknown etiology, making biomarker discovery essential for disease management. In this study, we intend to investigate potential urinary biomarkers to monitor the disease activity of BDU. METHODS: Firstly, label-free data-dependent acquisition (DDA) and tandem mass tag (TMT)-labeled quantitative proteomics methods were used to profile the proteomes of urine from active and quiescent BDU patients, respectively. For further exploration, the remaining fifty urine samples were analyzed by a data-independent acquisition (DIA) quantitative proteomics method. RESULTS: Twenty-nine and 21 differential proteins were identified in the same urine from BDU patients by label-free DDA and TMT-labeled analyses, respectively. Seventy-nine differentially expressed proteins (DEPs) were significantly changed in other active BDU urine samples compared to those in quiescent BDU urine samples by IDA analysis. Gene Ontology (GO) and protein-protein interaction (PPI) analyses revealed that the DEPs were associated with multiple functions, including the immune and neutrophil activation responses. Finally, seven proteins were identified as candidate biomarkers for BDU monitoring and recurrence prediction, namely, CD38, KCRB, DPP4, FUCA2, MTPN, S100A8 and S100A9. CONCLUSIONS: Our results showed that urine can be a good source of biomarkers for BDU. These dysregulated proteins provide potential urinary biomarkers for BDU activity monitoring and provide valuable clues for the analysis of the pathogenic mechanisms of BDU.

Relationship between non-alcoholic fatty liver and progressive fibrosis and serum 25-hydroxy vitamin D in patients with type 2 diabetes mellitus.

OBJECTIVE: We aimed to analyze the relationship between non-alcoholic fatty liver and progressive fibrosis and serum 25-hydroxy vitamin D (25(OH)D) in patients with type 2 diabetes mellitus. METHODS: A total of 184 patients with T2DM who were hospitalized in the Department of Endocrinology of the ShiDong Clinical Hospital between January 2023 and June 2023 were selected. We compared review of anthropometric, biochemical, and inflammatory parameters and non-invasive scores between groups defined by ultrasound NAFLD severity grades.We determine the correlation between 25(OH)D and FLI and FIB-4 scores, respectively. RESULTS: Statistically significant differences were seen between BMI, WC, C-peptide levels, FPG, ALT, serum 25(OH)D, TC, HDL, lumbar spine bone density, FLI, and FIB-4 in different degrees of NAFLD. Multivariate logistic regression analysis showed that 25(OH)D (OR = 1.26, p = 0.001), age (OR = 0.93, P < 0.001) and BMI (OR = 1.04, p = 0.007) were independent predictors of NAFLD in patients with T2DM. CONCLUSIONS: This study revealed the correlation between serum 25(OH)D levels and NAFLD in patients with T2DM. We also demonstrated that serum 25(OH)D levels were negatively correlated with FLI/FIB-4 levels in patients with T2DM with NAFLD, suggesting that vitamin D deficiency may promote hepatic fibrosis progression in T2DM with NAFLD.

The association between the neutrophil-to-lymphocyte ratio and type 2 diabetes mellitus: a cross-sectional study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a prevalent chronic disease often accompanied by low-grade inflammation. Recently, the neutrophil-to-lymphocyte ratio (NLR) has garnered researchers' interest as an emerging inflammation biomarker. This study aimed to comprehensively explore the relationship between NLR and T2DM using the National Health and Nutrition Examination Survey (NHANES) database. METHOD: We employed a cross-sectional study design to analyze data from five NHANES cycles from 2007 to 2016, excluding individuals with incomplete data. This study utilized a weighted logistic regression model, subgroup analyses, and restricted cubic spline (RCS) analysis to assess the potential relationship between NLR and T2DM. RESULTS: A total of 9903 participants were eligible for the analysis, of which 1280 were diagnosed with T2DM. The T2DM group exhibited significantly higher NLR levels than the non-T2DM group. After adjusting for potential confounders, elevated NLR levels were associated with an increased risk of developing T2DM, indicated by an odds ratio (OR) of 1.14, 95% CI: (1.05,1.24), P = 0.003. The results of the subgroup analyses revealed a significant interaction effect between NLR and T2DM concerning race and hypertension (P for interaction < 0.05). In contrast, no significant interactions were found for age, sex, education level, body mass index (BMI), smoking status, recreational activities, and alcohol drinker (P for interaction > 0.05). RCS analysis showed a significant non-linear relationship between NLR and T2DM, with an inflection point at 2.27 (all P for non-linearity < 0.05). CONCLUSION: Our study indicates that an elevated neutrophil-to-lymphocyte ratio is associated with a higher risk of T2DM.

A new gatekeeper to control oligodendrogenesis.

The diversity of oligodendrocyte precursor cells (OPCs) is not well understood and is actively discussed in the field. A new study in PLOS Biology describes a novel marker for an OPC subpopulation that controls oligodendrogenesis and myelination.

Gene-vegetarianism interactions in calcium, estimated glomerular filtration rate, and testosterone identified in genome-wide analysis across 30 biomarkers.

We examined the associations of vegetarianism with metabolic biomarkers using traditional and genetic epidemiology. First, we addressed inconsistencies in self-reported vegetarianism among UK Biobank participants by utilizing data from two dietary surveys to find a cohort of strict European vegetarians (N = 2,312). Vegetarians were matched 1:4 with nonvegetarians for non-genetic association analyses, revealing significant effects of vegetarianism in 15 of 30 biomarkers. Cholesterol measures plus vitamin D were significantly lower in vegetarians, while triglycerides were higher. A genome-wide association study revealed no genome-wide significant (GWS; 5×10-8) associations with vegetarian behavior. We performed genome-wide gene-vegetarianism interaction analyses for the biomarkers, and detected a GWS interaction impacting calcium at rs72952628 (P = 4.47×10-8). rs72952628 is in MMAA, a B12 metabolic pathway gene; B12 has major deficiency potential in vegetarians. Gene-based interaction tests revealed two significant genes, RNF168 in testosterone (P = 1.45×10-6) and DOCK4 in estimated glomerular filtration rate (eGFR) (P = 6.76×10-7), which have previously been associated with testicular and renal traits, respectively. These nutrigenetic findings indicate genotype can modify the associations between vegetarianism and health outcomes.

Serum calgranulin C as a non-invasive predictor of activity among inflammatory bowel disease.

Inflammatory bowel disease is a chronic immune-mediated disorder with a relapsing and remitting course. It leads to disabling gastrointestinal symptoms, low quality of life, and a significant burden for healthcare utilization and associated costs. Therefore, non-invasive biomarkers are needed for early diagnosis and follow up to avoid the complications of invasive diagnostic procedures. Calgranulin C is a calcium binding protein with proinflammatory properties. The aim of this study was to evaluate the role of serum calgranulin C as a non-invasive biomarker for diagnosis and prediction of activity in comparison to different biomarkers and endoscopic activity scores in inflammatory bowel disease. The study included 80 inflammatory bowel disease patients (50 Ulcerative colitis and 30 Chron's patients) and 20 normal controls. Complete blood picture, C-reactive protein, erythrocyte sedimentation rate, fecal calprotectin and serum calgranulin C were measured. Colonoscopies with histopathological examination were done and different activity scoring systems assessed. Among ulcerative colitis group, serum calgranulin C was statistically significantly higher in comparison to control group [723.640±529.055 ng/ml versus 80.850±24.416 ng/ml]. Depending on the American college of gastroenterology ulcerative colitis activity index, fecal calprotectin and serum calgranulin C were statistically significantly higher among moderate to severe ulcerative colitis than those with mild activity and those in remission (p < 0.001, for both). Regarding Crohn's disease group, serum calgranulin C was statistically significantly higher in comparison to control group [759.233±797.963 ng/ml versus 80.850±24.416 ng/mL]. Depending on Crohn's disease activity index, both serum calgranulin C and fecal calprotectin were statistically significantly higher among active disease than those in remission (p < 0.001, for both). In conclusion, serum calgranulin C could be used as a non-invasive marker to predict activity and severity and to ensure remission among inflammatory bowel disease patients.

Investigate role of miRNA146a and IL-17 level in progressive rheumatoid arthritis disease.

Rheumatoid Arthritis (RA) is a chronic, progressive autoimmune disease, involves an intimate relationship between immune cells and cytokines and results in decreased lifespans and higher mortality rates. The goal of the current study was to investigate the impact of MicroRNA (miRNA)146a and interleukin-17 (IL-17) as prognosis markers in RA patients. This case-control study included 120 RA patients who visited the Rheumatology unit at Al-Saddar Medical City in the governorate of Najaf, and 30 normal controls. Venous blood samples were collected from both patients and controls. Blood samples were used for measuring IL-17 levels using an enzyme linked immunosorbent assay (ELISA) testing, and miRNA146a by the reverse transcription polymerase chain reaction (RT-PCR). The results showed higher frequency of RA in women than in men with elevate incidence in patients aged 40-59 years and 1-2 years RA disease duration of. The level of IL-17 was significantly higher in serum of RA patients compared with the control group (p < 0.0001). IL-17 level was significantly increased among the patients in RA stage 4 (p < 0.0001). IL-17 level was significantly increased in patients without treatment compared with treated patients. The expression of miRNA-146a was significantly higher in the patients' group than control group. In conclusion, IL-17 may play critical role in chronic inflammation and can be used as diagnostic biomarker for RA. miRNA-146a is overexpressed in RA patient relative to healthy individuals and it acts as a negative regulator for IL-17.

Profiles of miRNA expression and IFN-γ serum level as biomarker for the development of Multiple Sclerosis.

Multiple sclerosis (MS) is associated with a wide spectrum of sensory, motor, and psychological disorders. Cytokines level and microRNA (miRNA) expression have roles in the disease's progression and the start of a damaging immune response in the central nerve system. This research study aimed to determine the role of interferon-γ (IFN-γ) and microRNA-326 (MiR-326) as prognostic factors for the development of MS disease in relation to different treatments. This case-control study included 100 participants, classified as 80 MS patients and 20 apparently healthy subjects as a control group. IFN-γ level was determined by an enzyme linked immunosorbent assay. The expression level of micR326 was determined by the reverse transcription polymerase chain reaction technique. The mean level of serum IFN-γ in MS patients (102.83 ± 15.79 ng/ml) was significantly higher than in the control group (61.25 ± 12.51 ng/ml) (p=0.001). A higher concentration of IFN-γ was observed in the secondary progressive form of MS disease relative to relapsing-remitting multiple sclerosis (RRMS) and in comparison, with the controls group, this IFN-γ cytokine level was significantly higher in treatment-naive patients. There was an increase in the mean fold change of miRNA-326 expression in patients (3.1 ±1.65) compared to the control group (1.03 ±0.23). In conclusion, secondary progressive multiple sclerosis (SPMS) has higher IFN-γ serum level than RRMS. MiR-326 may participate in the development of MS and its expression can be a useful biomarker for the prediction of MS.

Correlation analysis between the early diagnosis and severity of neuropathic pain and the activation level of NLRP3 inflammasome: A retrospective study.

To investigate the correlation between neuropathic pain's early diagnosis, severity, and nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing-3 (NLRP3) inflammasome activation, we retrospectively evaluated 50 patients with neuropathic pain and 50 healthy individuals. Activation of the NLRP3 inflammasome was measured in blood samples, as well as pain levels and clinical markers. Neuropathic pain patients exhibited elevated NLRP3 inflammasome activation. Pain intensity positively correlated with activation. Correlation was also observed with inflammatory markers and pain-related biomarkers. NLRP3 inflammasome demonstrated high diagnostic sensitivity. In conclusion, NLRP3 inflammasome activation influences neuropathic pain initiation and progression. Measuring activation levels may serve as an early diagnostic indicator and severity gauge for neuropathic pain.

Relationship between admission blood urea nitrogen levels and postoperative length of stay in patients with hip fracture: A retrospective study.

To investigate the relationship between admission blood urea nitrogen (BUN) levels and postoperative length of stay (LOS) in hip fracture (HF) patients. This retrospective study retrieved related data from the MIMIC-IV database, of which the laboratory variables were taken preoperatively. The patients were divided into 4 groups according to the BUN quartile levels. After exploring the nonlinear relationship between BUN and LOS by generalized additive model, their connection was further analyzed using the generalized linear models, quantile regression models, and interaction analysis. Receiver operating characteristic curve analysis and decision curve analysis were performed to evaluate its value in predicting first intensive care unit admission and in-hospital mortality. Totally 1274 patients with HF were enrolled in the study. There was a nonlinear relationship between BUN and LOS (P < .05). Besides, BUN was an independent predictor for LOS after adjusting different covariates in 3 models (P < .05). Age served as a significant interactor in this relationship (P < .05). Moreover, receiver operating characteristic curve and decision curve analysis revealed the predictive value of BUN for intensive care unit admission and in-hospital mortality in HF. Admission BUN level as a cost-effective and easy-to-collect biomarker is significantly related to LOS in patients with HF. It helps clinicians to identify potential high-risk populations and take effective preventions before surgery to reduce postoperative LOS.