Hyaluronidase inhibits TGF-ß-mediated rat periodontal ligament fibroblast expression of collagen and myofibroblast markers: An in vitro exploration of periodontal tissue remodeling.

OBJECTIVE: To determine the effect of hyaluronic acid (HA) degradation by hyaluronidase (HYAL) in inhibiting collagen fiber production by rat periodontal ligament cells (rPDLCs). DESIGN: Primary rPDLCs were isolated from the euthanized rats and used for in vitro experiments. The appropriate HYAL concentration was determined through CCK-8 testing for cytotoxicity detection and Alizarin red staining for mineralization detection. RT-qPCR and western blot assays were conducted to assess the effect of HYAL, with or without TGF-ß, on generation of collagen fiber constituents and expression of actin alpha 2, smooth muscle (ACTA2) of rPDLCs. RESULTS: Neither cell proliferation nor mineralization were significantly affected by treatment with 4 U/mL HYAL. HYAL (4 U/mL) alone downregulated type I collagen fiber (Col1a1 and Col1a2) and Acta2 mRNA expression; however, ACTA2 and COL1 protein levels were only downregulated by HYAL treatment after TGF-ß induction. CONCLUSIONS: Treatment of rPDLCs with HYAL can inhibit TGF-ß-induced collagen matrix formation and myofibroblast transformation.

The Predictive Value of the Inflammatory Prognostic Index for Detecting No-Reflow in ST-Elevation Myocardial Infarction Patients. / O Valor Preditivo do Índice Prognóstico Inflamatório para Detecção de No-Reflow em Pacientes com Infarto do Miocárdio com Supradesnivelamento do Segmento ST.

BACKGROUND: No-reflow (NR) is characterized by an acute reduction in coronary flow that is not accompanied by coronary spasm, thrombosis, or dissection. Inflammatory prognostic index (IPI) is a novel marker that was reported to have a prognostic role in cancer patients and is calculated by neutrophil/lymphocyte ratio (NLR) multiplied by C-reactive protein/albumin ratio. OBJECTIVE: We aimed to investigate the relationship between IPI and NR in ST-segment elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention (pPCI). METHODS: A total of 1541 patients were enrolled in this study (178 with NR and 1363 with reflow). Lasso panelized shrinkage was used for variable selection. A nomogram was created based on IPI for detecting the risk of NR development. Internal validation with Bootstrap resampling was used for model reproducibility. A two-sided p-value <0.05 was accepted as a significance level for statistical analyses. RESULTS: IPI was higher in patients with NR than in patients with reflow. IPI was non-linearly associated with NR. IPI had a higher discriminative ability than the systemic immune-inflammation index, NLR, and CRP/albumin ratio. Adding IPI to the baseline multivariable logistic regression model improved the discrimination and net-clinical benefit effect of the model for detecting NR patients, and IPI was the most prominent variable in the full model. A nomogram was created based on IPI to predict the risk of NR. Bootstrap internal validation of nomogram showed a good calibration and discrimination ability. CONCLUSION: This is the first study that shows the association of IPI with NR in STEMI patients who undergo pPCI.

FUNDAMENTO: O no-reflow (NR) é caracterizado por uma redução aguda no fluxo coronário que não é acompanhada por espasmo coronário, trombose ou dissecção. O índice prognóstico inflamatório (IPI) é um novo marcador que foi relatado como tendo um papel prognóstico em pacientes com câncer e é calculado pela razão neutrófilos/linfócitos (NLR) multiplicada pela razão proteína C reativa/albumina. OBJETIVO: Nosso objetivo foi investigar a relação entre IPI e NR em pacientes com infarto do miocárdio com supradesnivelamento do segmento ST (IAMCSST) submetidos a intervenção coronária percutânea primária (ICPp). MÉTODOS: Um total de 1.541 pacientes foram incluídos neste estudo (178 com NR e 1.363 com refluxo). A regressão penalizada LASSO (Least Absolute Shrinkage and Select Operator) foi usada para seleção de variáveis. Foi criado um nomograma baseado no IPI para detecção do risco de desenvolvimento de NR. A validação interna com reamostragem Bootstrap foi utilizada para reprodutibilidade do modelo. Um valor de p bilateral <0,05 foi aceito como nível de significância para análises estatísticas. RESULTADOS: O IPI foi maior em pacientes com NR do que em pacientes com refluxo. O IPI esteve associado de forma não linear com a NR. O IPI apresentou maior capacidade discriminativa do que o índice de imunoinflamação sistêmica, NLR e relação PCR/albumina. A adição do IPI ao modelo de regressão logística multivariável de base melhorou a discriminação e o efeito do benefício clínico líquido do modelo para detecção de pacientes com NR, e o IPI foi a variável mais proeminente no modelo completo. Foi criado um nomograma baseado no IPI para prever o risco de NR. A validação interna do nomograma Bootstrap mostrou uma boa capacidade de calibração e discriminação. CONCLUSÃO: Este é o primeiro estudo que mostra a associação de IPI com NR em pacientes com IAMCSST submetidos a ICPp.

Can Pre-Ablation Biomarkers Be Used to Predict Arrhythmia Recurrence after Ablation Index-Guided Atrial Fibrillation Ablation? / Os Biomarcadores podem ser Utilizados para Prever Recorrência de Arritmia após a Ablação de Fibrilação Atrial Guiada pelo Ablation-Index?

BACKGROUND: Ablation Index (AI) software has allowed better atrial fibrillation (AF) ablation results, but recurrence rates remain significant. Specific serum biomarkers have been associated with this recurrence. OBJECTIVES: To evaluate whether certain biomarkers could be used (either individually or combined) to predict arrhythmia recurrence after AI-guided AF ablation. METHODS: Prospective multicenter observational study of consecutive patients referred for AF ablation from January 2018 to March 2021. Hemoglobin, brain natriuretic peptide (BNP), C-reactive protein, high sensitivity cardiac troponin I, creatinine clearance, thyroid-stimulating hormone (TSH) and free thyroxine (FT4) were assessed for their ability to predict arrhythmia recurrence during follow-up. Statistical significance was accepted for p values of<0.05. RESULTS: A total of 593 patients were included - 412 patients with paroxysmal AF and 181 with persistent AF. After a mean follow-up of 24±6 months, overall single-procedure freedom from atrial arrhythmia was 76.4%. Individually, all biomarkers had no or only modest predictive power for recurrence. However, a TSH value >1.8 µUI/mL (HR=1.82 [95% CI, 1.89-2.80], p=0.006) was an independent predictor of arrhythmia recurrence. When assessing TSH, FT4 and BNP values in combination, each additional "abnormal" biomarker value was associated with a lower freedom from arrhythmia recurrence (87.1 % for no biomarker vs. 83.5% for one vs. 75.1% for two vs. 43.3% for three biomarkers, p<0.001). Patients with three "abnormal" biomarkers had a threefold higher risk of AF recurrence compared with no "abnormal" biomarker (HR=2.88 [95% CI, 1.39-5.17], p=0.003). CONCLUSIONS: When used in combination, abnormal TSH, FT4 and BNP values can be a useful tool for predicting arrhythmia recurrence after AI-guided AF ablation.

FUNDAMENTO: O software ablation index (AI) permitiu melhorar os resultados da ablação de fibrilação atrial (FA), mas as taxas de recorrência permanecem significativas. Biomarcadores séricos específicos têm sido associados a essa recorrência. OBJETIVOS: Avaliar se certos biomarcadores podem ser utilizados (individualmente ou combinados) para predizer a recorrência de FA pós ablação guiada pelo AI. MÉTODOS: Estudo multicêntrico, observacional, prospectivo de pacientes consecutivos, encaminhados para ablação de FA de janeiro de 2018 a março de 2021. Hemoglobina, peptídeo natriurético cerebral (BNP), proteína C reativa, troponina I ultrassensível, clearance de creatinina, Hormônio Tireoestimulante (TSH), e Tiroxina livre (T4) foram avaliados quanto à capacidade de prever a recorrência de arritmias durante o acompanhamento. Valores de p <0,05 foram aceitos como estatisticamente significativos. RESULTADOS: Um total de 593 pacientes foram incluídos ­ 412 com FA paroxística e 181 com FA persistente. Durante o seguimento médio de 24±6 meses, 76,4% não apresentaram recidiva após ablação. Individualmente, os biomarcadores demonstraram um valor preditivo baixo ou nulo para recorrência. No entanto, TSH >1,8 µUI/mL [HR=1,82 (IC95%, 1,89-2,80), p=0,006] foi um preditor independente de recorrência. Avaliando-se a combinação de TSH, FT4 e BNP, a adição de cada valor "anormal" foi associada a uma menor sobrevida livre de recorrência (87,1% se nenhum vs. 83,5% se um vs. 75,1% se dois vs. 43,3% se três biomarcadores, p<0,001). Doentes com três biomarcadores "anormais" apresentaram três vezes maior probabilidade de recorrência de FA, comparativamente aos que não apresentaram nenhum biomarcador "anormal" (HR=2,88 [IC95%, 1,39-5,17], p=0,003). CONCLUSÕES: Quando combinados, valores anormais de TSH, FT4 e BNP podem ser uma ferramenta útil para prever a recorrência de FA pós ablação guiada pelo AI.

Serum Tau-A and Tau-C Levels and Their Association with Cognitive Impairment and Dementia Progression in a Memory Clinic Derived Cohort.

BACKGROUND: Serum-measured fragments of Tau cleaved by ADAM-10 (Tau-A) and Caspase-3 (Tau-C) have been found linked to change in cognitive function and risk of dementia. OBJECTIVES: 1) To determine the discriminatory abilities of Tau-A, and Tau-C in subjects with either mild cognitive impairment (MCI) due to Alzheimer's disease (AD) or AD dementia compared to a control group. 2) To determine if there is a relation between Tau-A, and Tau-C and established cerebrospinal fluid (CSF) markers of AD- ß-Amyloid1-42 (AB42), Phosphorylated-tau-181 (p-tau), and total-tau. 3) To determine if Tau-A and Tau-C are associated with progression rate from MCI due to AD to AD dementia. DESIGN: Cross-sectional and a substudy using a retrospective cohort design. SETTING: Memory clinic derived subjects contributing to the Danish Dementia Biobank. PARTICIPANTS: Cognitively unimpaired subjects (n=49), patients with mild cognitive impairment (MCI) due to AD (n=45), and Alzheimer's dementia (n=52). MEASUREMENTS: Competitive enzyme-linked immunosorbent assay (ELISA)-measured serum levels of Tau-A, and Tau-C. RESULTS: The ratio between Tau-A and Tau-C differed between the three groups (p=0.015). Age- and sex-adjusted Tau-A differed between groups with lower ratios being associated with more severe disease (p=0.023). Tau-C was trending towards significant correlation to CSF-levels of AB42 (Pearson correlation coefficient 0.164, p=0.051). Those with Tau-C-levels in the 2nd quartile had a hazard ratio (HR) of 2.91 (95% CI 1.01 - 8.44, p=0.04) of progression compared to those in the 1st quartile. Those in the 3rd quartile was found to have a borderline significant (p=0.055) HR of 2.63 (95% CI 0.98 - 7.05) when compared to those in the lowest quartile. CONCLUSIONS: Tau-A and the ratio between Tau-A and Tau-C showed significant differences between groups and were correlated to CSF-AB42. Tau-C values in the middle range were associated with faster progression from MCI to dementia. This pilot study adds to the mounting data suggesting serum-measured Tau-A and Tau-C as biomarkers useful in relation to diagnosis and progression rate in AD but need further validation.

Is having a moderate or low history, electrocardiogram, age, risk factors, troponin risk score a handicap for long-term mortality?

OBJECTIVE: History, electrocardiogram, age, risk factors, troponin risk score and troponin level follow-up are used to safely discharge low-risk patients with suspected non-ST elevation acute coronary syndrome from the emergency department for a 1-month period. We aimed to comprehensively investigate the 6-month mortality of patients with the history, electrocardiogram, age, risk factors, troponin risk score. METHODS: A total of 949 non-ST elevation acute coronary syndrome patients admitted to the emergency department from 01.01.2019 to 01.10.2019 were included in this retrospective study. History, electrocardiogram, age, risk factors, troponin scores of all patients were calculated by two emergency clinicians and a cardiologist. We compared the 6-month mortality of the groups. RESULTS: The mean age of the patients was 67.9 (56.4-79) years; 57.3% were male and 42.7% were female. Six-month mortality was significantly lower in the high-risk history, electrocardiogram, age, risk factors, troponin score group than in the low- and moderate-risk groups: 11/80 (12.1%), 58/206 (22%), and 150/444 (25.3%), respectively (p=0.019). CONCLUSION: Patients with high history, electrocardiogram, age, risk factors, troponin risk scores are generally treated with coronary angioplasty as soon as possible. We found that the mortality rate of this group of patients was lower in the long term compared with others. Efforts are also needed to reduce the mortality of moderate and low-risk patients. Further studies are needed on the factors affecting the 6-month mortality of moderate and low-risk acute coronary syndrome patients.

Reduced expression of miRNAs as potential biomarkers in axial spondyloarthritis.

OBJECTIVE: This study aimed to investigate the value of miR-29a-3p, miR-27a, miR126-3p, miR-146a-5p, miR-625-3p, miR-130a, miR-32, miR-218, miR-131, and miR5196 in the diagnosis of axial spondyloarthritis and to determine whether there is a difference in miRNA expression levels between radiographic axial spondyloarthritis and non-radiographic axial spondyloarthritis, as well as the relationship between miRNA expression levels, disease activity, and uveitis history. METHODS: This study included 50 patients with axial spondyloarthritis (25 with radiographic axial spondyloarthritis and 25 with non-radiographic axial spondyloarthritis) and 25 healthy individuals. The fold change of miRNA expression for each miRNA was calculated using the 2-ΔΔCt method. RESULTS: The expression of all miRNAs except miR-130a was downregulated in axial spondyloarthritis patients (miR-27a: fold regulation: -11.21, p<0.001; miR-29a-3p: fold regulation: -2.63, p<0.001; miR-32: fold regulation: -2.94, p=0.002; miR-126-3p: fold regulation -10.94, p<0.001; miR-132: fold regulation: -2.18, p<0.001; miR-146-5p: fold regulation: -9.78, p<0.001; miR-218: fold regulation: -2.65, p<0.001; miR-625-3p: fold regulation: -2.01, p=0.001; miR-5196-3p: fold regulation: -7.04, p<0.001). The expression levels of these miRNAs did not differ significantly between non-radiographic axial spondyloarthritis and radiographic axial spondyloarthritis patients (p>0.05 for all). CONCLUSION: Particularly, miR-27a, miR-126-3p, miR-146-5p, and miR-5196-3p were found to be substantially downregulated in both non-radiographic axial spondyloarthritis and radiographic axial spondyloarthritis patients, suggesting their potential as diagnostic biomarkers for axial spondyloarthritis.

Plasma proteome profiling reveals dynamic of cholesterol marker after dual blocker therapy.

Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT.

Specific plasma microRNA profiles could be potential non-invasive biomarkers for biochemical pregnancy loss following embryo transfer.

BACKGROUND: Plasma microRNAs act as biomarkers for predicting and diagnosing diseases. Reliable non-invasive biomarkers for biochemical pregnancy loss have not been established. We aim to analyze the dynamic microRNA profiles during the peri-implantation period and investigate if plasma microRNAs could be non-invasive biomarkers predicting BPL. METHODS: In this study, we collected plasma samples from patients undergoing embryo transfer (ET) on ET day (ET0), 11 days after ET (ET11), and 14 days after ET (ET14). Patients were divided into the NP (negative pregnancy), BPL (biochemical pregnancy loss), and CP (clinical pregnancy) groups according to serum hCG levels at day11~14 and ultrasound at day28~35 following ET. MicroRNA profiles at different time-points were detected by miRNA-sequencing. We analyzed plasma microRNA signatures for BPL at the peri-implantation stage, we characterized the dynamic microRNA changes during the implantation period, constructed a microRNA co-expression network, and established predictive models for BPL. Finally, the sequencing results were confirmed by Taqman RT-qPCR. RESULTS: BPL patients have distinct plasma microRNA profiles compared to CP patients at multiple time-points during the peri-implantation period. Machine learning models revealed that plasma microRNAs could predict BPL. RT-qPCR confirmed that miR-181a-2-3p, miR-9-5p, miR-150-3p, miR-150-5p, and miR-98-5p, miR-363-3p were significantly differentially expressed between patients with different reproductive outcomes. CONCLUSION: Our study highlights the non-invasive value of plasma microRNAs in predicting BPL.

Preoperative peripheral inflammatory markers are predictors of postoperative central diabetes insipidus in craniopharyngioma patients: a retrospective study.

BACKGROUND: Postoperative central diabetes insipidus (CDI) is commonly observed in craniopharyngioma (CP) patients, and the inflammatory response plays an important role in CPs. We aimed to evaluate the predictive value of preoperative peripheral inflammatory markers and their combinations regarding CDI occurrence in CPs. METHODS: The clinical data including preoperative peripheral inflammatory markers of 208 CP patients who underwent surgical treatment were retrospectively collected and analyzed. The preoperative peripheral white blood cells (WBC), neutrophils, lymphocytes, monocytes, platelet (PLT), neutrophil-to-lymphocyte ratio (NLR), derived-NLR (dNLR), monocyte-to-lymphocyte ratio (MLR) and PLT-to-lymphocyte ratio (PLR) were assessed in total 208 CP patients and different age and surgical approach CP patient subgroups. Their predictive values were evaluated by the receiver operator characteristic curve analysis. RESULTS: Preoperative peripheral WBC, neutrophils, NLR, dNLR, MLR, and PLR were positively correlated and lymphocyte was negatively associated with postoperative CDI occurrence in CP patients, especially when WBC ≥ 6.66 × 109/L or lymphocyte ≤ 1.86 × 109/L. Meanwhile, multiple logistic regression analysis showed that WBC > 6.39 × 109/L in the > 18 yrs age patients, WBC > 6.88 × 109/L or lymphocytes ≤ 1.85 × 109/L in the transcranial approach patients were closely associated with the elevated incidence of postoperative CDI. Furthermore, the area under the curve obtained from the receiver operator characteristic curve analysis showed that the best predictors of inflammatory markers were the NLR in total CP patients, the MLR in the ≤ 18 yrs age group and the transsphenoidal group, the NLR in the > 18 yrs age group and the dNLR in the transcranial group. Notably, the combination index NLR + dNLR demonstrated the most valuable predictor in all groups. CONCLUSIONS: Preoperative peripheral inflammatory markers, especially WBC, lymphocytes and NLR + dNLR, are promising predictors of postoperative CDI in CPs.

Exploring disease-specific metabolite signatures in hereditary angioedema patients.

Introduction: Hereditary angioedema (HAE) is a rare, life-threatening autosomal dominant genetic disorder caused by a deficient and/or dysfunctional C1 esterase inhibitor (C1-INH) (type 1 and type 2) leading to recurrent episodes of edema. This study aims to explore HAE patients' metabolomic profiles and identify novel potential diagnostic biomarkers for HAE. The study also examined distinguishing HAE from idiopathic angioedema (AE). Methods: Blood plasma samples from 10 HAE (types 1/2) patients, 15 patients with idiopathic AE, and 20 healthy controls were collected in Latvia and analyzed using LC-MS based targeted metabolomics workflow. T-test and fold change calculation were used to identify metabolites with significant differences between diseases and control groups. ROC analysis was performed to evaluate metabolite based classification model. Results: A total of 33 metabolites were detected and quantified. The results showed that isovalerylcarnitine, cystine, and hydroxyproline were the most significantly altered metabolites between the disease and control groups. Aspartic acid was identified as a significant metabolite that could differentiate between HAE and idiopathic AE. The mathematical combination of metabolites (hydroxyproline * cystine)/(creatinine * isovalerylcarnitine) was identified as the diagnosis signature for HAE. Furthermore, glycine/asparagine ratio could differentiate between HAE and idiopathic AE. Conclusion: Our study identified isovalerylcarnitine, cystine, and hydroxyproline as potential biomarkers for HAE diagnosis. Identifying new biomarkers may offer enhanced prospects for accurate, timely, and economical diagnosis of HAE, as well as tailored treatment selection for optimal patient care.

Comparative single-cell multiplex immunophenotyping of therapy-naive patients with rheumatoid arthritis, systemic sclerosis, and systemic lupus erythematosus shed light on disease-specific composition of the peripheral immune system.

Introduction: Systemic autoimmune diseases (SADs) are a significant burden on the healthcare system. Understanding the complexity of the peripheral immunophenotype in SADs may facilitate the differential diagnosis and identification of potential therapeutic targets. Methods: Single-cell mass cytometric immunophenotyping was performed on peripheral blood mononuclear cells (PBMCs) from healthy controls (HCs) and therapy-naive patients with rheumatoid arthritis (RA), progressive systemic sclerosis (SSc), and systemic lupus erythematosus (SLE). Immunophenotyping was performed on 15,387,165 CD45+ live single cells from 52 participants (13 cases/group), using an antibody panel to detect 34 markers. Results: Using the t-SNE (t-distributed stochastic neighbor embedding) algorithm, the following 17 main immune cell types were determined: CD4+/CD57- T cells, CD4+/CD57+ T cells, CD8+/CD161- T cells, CD8+/CD161+/CD28+ T cells, CD8dim T cells, CD3+/CD4-/CD8- T cells, TCRγ/δ T cells, CD4+ NKT cells, CD8+ NKT cells, classic NK cells, CD56dim/CD98dim cells, B cells, plasmablasts, monocytes, CD11cdim/CD172dim cells, myeloid dendritic cells (mDCs), and plasmacytoid dendritic cells (pDCs). Seven of the 17 main cell types exhibited statistically significant frequencies in the investigated groups. The expression levels of the 34 markers in the main populations were compared between HCs and SADs. In summary, 59 scatter plots showed significant differences in the expression intensities between at least two groups. Next, each immune cell population was divided into subpopulations (metaclusters) using the FlowSOM (self-organizing map) algorithm. Finally, 121 metaclusters (MCs) of the 10 main immune cell populations were found to have significant differences to classify diseases. The single-cell T-cell heterogeneity represented 64MCs based on the expression of 34 markers, and the frequency of 23 MCs differed significantly between at least twoconditions. The CD3- non-T-cell compartment contained 57 MCs with 17 MCs differentiating at least two investigated groups. In summary, we are the first to demonstrate the complexity of the immunophenotype of 34 markers over 15 million single cells in HCs vs. therapy-naive patients with RA, SSc, and SLE. Disease specific population frequencies or expression patterns of peripheral immune cells provide a single-cell data resource to the scientific community.

The unique association between the level of plateletcrit and the prevalence of diabetic kidney disease: a cross-sectional study.

Objective: The activation of platelets in individuals with type 2 diabetes mellitus (T2DM) triggers inflammation and hemodynamic abnormalities, contributing to the development of diabetic kidney disease (DKD). Despite this, research into the relationship between plateletcrit (PCT) levels and DKD is sparse, with inconsistent conclusions drawn regarding the connection between various platelet parameters and DKD. This highlights the necessity for comprehensive, large-scale population studies. Therefore, our objective is to explore the association between PCT levels and various platelet parameters in relation to DKD. Methods: In this cross-sectional study, hematological parameter data were collected from a cohort of 4,302 hospitalized Chinese patients. We analyzed the relationships between PCT, platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), platelet large cell ratio (P-LCR), and DKD, along with the urinary albumin-to-creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR). Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic potential of these parameters. Results: DKD patients exhibited significantly higher PCT levels compared to those without DKD. Multivariate regression analysis identified elevated PCT and PLT levels as potential independent risk factors for both DKD and UACR, while lower MPV levels might serve as independent protective factors for eGFR. The areas under the ROC curve for PCT in relation to DKD and UACR (≥30 mg/g) were 0.523 and 0.526, respectively. The area under the ROC curve for PLT in relation to UACR (≥30 mg/g) was 0.523. Conclusion: PCT demonstrates a weak diagnostic value for T2DM patients at risk of developing DKD and experiencing proteinuria, and PLT shows a similarly modest diagnostic utility for detecting proteinuria. These insights contribute to a deeper understanding of the complex dynamics involved in DKD. Additionally, incorporating these markers into routine clinical assessments could enhance risk stratification, facilitating early interventions and personalized management strategies.

Association between monocyte to lymphocyte ratio and diabetic foot ulcer in the population of the US with diabetes based on the 1999-2004 National Health and Nutrition Examination Survey data: a retrospective cross-sectional study.

Background: Diabetic foot ulcer (DFU) is a severe complication that occurs in patients with diabetes and is a primary factor that necessitates amputation. Therefore, the occurrence and progression of DFU must be predicted at an early stage to improve patient prognosis and outcomes. In this regard, emerging evidence suggests that inflammation-related markers play a significant role in DFU. One such potential marker, the monocyte-lymphocyte ratio (MLR), has not been extensively studied in relation to DFU. This study aimed to define a connection between MLR and DFU. Methods: A cross-sectional study was conducted using National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2004. DFU was defined based on survey questionnaires assessing the presence of nonhealing ulcers in the lower extremities for more than 4 weeks in diabetes patients. The MLR was calculated as the ratio of the monocyte count to the lymphocyte count, which was directly obtained from laboratory data files. Logistic regression analysis was performed to assess the relationship between the MLR and DFU. Stratified analysis according to age, sex, body mass index, blood glucose, hemoglobin, and glycated hemoglobin categories was conducted, and multiple imputations were applied to missing data. Results: In total, 1246 participants were included; the prevalence of DFU was 9.4% (117/1246). A multivariable regression model revealed a significant association between DFU and a 0.1 unit increase in MLR after adjusting for all covariates (adjusted odds ratio=1.16, 95% confidence interval: 1.02-1.33). Subgroup analyses revealed consistent findings regarding the impact of MLR on the presence of DFU (p > 0.05). Conclusion: MLR is significantly associated with DFU in diabetes patients, and can be used as one of the indicators for predicting the occurrence of DFU. MLR assessment may be a valuable component in the follow-up of patients with diabetes.

Serum bta-miRNA-375 as a potential biomarker for the early diagnosis of enzootic bovine leukosis.

To identify a biomarker for the early diagnosis of enzootic bovine leukosis (EBL) caused by bovine leukemia virus (BLV), we investigated the expression of a microRNA, bta-miR-375, in cattle serum. Using quantitative reverse-transcriptase PCR analysis, we measured bta-miR-375 levels in 27 samples from cattle with EBL (EBL cattle), 45 samples from animals infected with BLV but showing no clinical signs (NS cattle), and 30 samples from cattle uninfected with BLV (BLV negative cattle). In this study, we also compared the kinetics of bta-miR-375 with those of the conventional biomarkers of proviral load (PVL), lactate dehydrogenase (LDH), and thymidine kinase (TK) from the no-clinical-sign phase until EBL onset in three BLV-infected Japanese black (JB) cattle. Bta-miR-375 expression was higher in NS cattle than in BLV negative cattle (P < 0.05) and greater in EBL cattle than in BLV negative and NS cattle (P < 0.0001 for both comparisons). Receiver operating characteristic curves demonstrated that bta-miR-375 levels distinguished EBL cattle from NS cattle with high sensitivity and specificity. In NS cattle, bta-miR-375 expression was increased as early as at 2 months before EBL onset-earlier than the expression of PVL, TK, or LDH isoenzymes 2 and 3. These results suggest that serum miR-375 is a promising biomarker for the early diagnosis of EBL.

Long-term clinical outcomes of certolizumab pegol treatment in non-radiographic axial spondyloarthritis stratified by baseline MRI and CRP status.

OBJECTIVE: There is a paucity of data on long-term clinical responses in patients with non-radiographic axial spondyloarthritis (nr-axSpA) based on their baseline objective signs of inflammation such as MRI or C-reactive protein (CRP) levels. This study reports clinical outcomes up to 3 years of the C-axSpAnd trial, including safety follow-up extension (SFE) from Weeks 52 to 156, stratified by patients' baseline MRI and CRP status. METHODS: C-axSpAnd (NCT02552212) was a phase 3, multicentre study that evaluated certolizumab pegol (CZP) in patients with active nr-axSpA who had active sacroiliitis on MRI and/or elevated CRP. In this post hoc analysis, efficacy outcomes are reported to Week 156 of C-axSpAnd for patients stratified according to their MRI and CRP status at Week 0 (MRI+/CRP-, MRI-/CRP+ and MRI+/CRP+). RESULTS: Across all outcome measures, including major improvement in Ankylosing Spondylitis Disease Activity Score (ASDAS-MI) and Assessment of SpondyloArthritis international Society criteria ≥40% response (ASAS40), outcomes were generally sustained in SFE patients from Week 52 to Week 156. MRI+/CRP+ patients showed numerically higher or comparable responses relative to MRI-/CRP+ and MRI+/CRP- patients at Weeks 52 and 156; however, all three subgroups demonstrated substantial improvements from Week 0 (in CZP-randomised patients, ASDAS-MI at Week 156 [observed case]: MRI+/CRP+: 73.1%, MRI-/CRP+: 52.2%, MRI+/CRP-: 30.4%; ASAS40: MRI+/CRP+: 76.9%, MRI-/CRP+: 62.5%, MRI+/CRP-: 65.2%). CONCLUSIONS: In patients with nr-axSpA and objective signs of inflammation, long-term clinical outcomes achieved after 1 year were generally sustained at 3 years across MRI+/CRP+, MRI-/CRP+ and MRI+/CRP- subgroups.

Anti-fatigue activity of methyl dihydrojasmonate and linalool in a rat model evaluated by a novel index for neuro-immune and oxidative stress interactions.

Avoiding fatigue is a long-standing challenge in both healthy and diseased individuals. Establishing objective standard markers of fatigue is essential to evaluate conditions in spatiotemporally different locations and individuals and identify agents to fight against fatigue. Herein, we introduced a novel method for evaluating fatigue using nervous system markers (including dopamine, adrenaline, and noradrenaline), various cytokine levels (such as interleukin [IL]-1ß, tumor necrosis factor [TNF]-α, IL-10, IL-2, IL-5 and IL-17A), and oxidative stress markers (such as diacron-reactive oxygen metabolites [d-ROMs] and biological antioxidant potential [BAP]) in a rat fatigue model. Using this method, the anti-fatigue effects of methyl dihydrojasmonate (MDJ) and linalool, the fragrance/flavor compounds used in various products, were assessed. Our method evaluated the anti-fatigue effects of the aforementioned compounds based on the changes in levels of the nerves system markers, cytokines, and oxidative stress markers. MDJ exerted more potent anti-fatigue effects than linalool. In conclusion, the reported method could serve as a useful tool for fatigue studies and these compounds may act as effective therapeutic agents for abrogating fatigue symptoms.

Diagnostic biomarker discovery from brain EEG data using LSTM, reservoir-SNN, and NeuCube methods in a pilot study comparing epilepsy and migraine.

The study introduces a new online spike encoding algorithm for spiking neural networks (SNN) and suggests new methods for learning and identifying diagnostic biomarkers using three prominent deep learning neural network models: deep BiLSTM, reservoir SNN, and NeuCube. EEG data from datasets related to epilepsy, migraine, and healthy subjects are employed. Results reveal that BiLSTM hidden neurons capture biological significance, while reservoir SNN activities and NeuCube spiking dynamics identify EEG channels as diagnostic biomarkers. BiLSTM and reservoir SNN achieve 90 and 85% classification accuracy, while NeuCube achieves 97%, all methods pinpointing potential biomarkers like T6, F7, C4, and F8. The research bears implications for refining online EEG classification, analysis, and early brain state diagnosis, enhancing AI models with interpretability and discovery. The proposed techniques hold promise for streamlined brain-computer interfaces and clinical applications, representing a significant advancement in pattern discovery across the three most popular neural network methods for addressing a crucial problem. Further research is planned to study how early can these diagnostic biomarkers predict an onset of brain states.

Insulin-like growth factor 1 and sex hormones for assessment of anthropometric and pubertal growth of Egyptian children and adolescents with type 1 diabetes mellitus (single center study).

BACKGROUND: This study aimed to assess the anthropometric measures and pubertal growth of children and adolescents with Type 1 diabetes mellitus (T1DM) and to detect risk determinants affecting these measures and their link to glycemic control. PATIENTS AND METHODS: Two hundred children and adolescents were assessed using anthropometric measurements. Those with short stature were further evaluated using insulin-like growth factor 1 (IGF-1), bone age, and thyroid profile, while those with delayed puberty were evaluated using sex hormones and pituitary gonadotropins assay. RESULTS: We found that 12.5% of our patients were short (height SDS < -2) and IGF-1 was less than -2 SD in 72% of them. Patients with short stature had earlier age of onset of diabetes, longer duration of diabetes, higher HbA1C and urinary albumin/creatinine ratio compared to those with normal stature (p < 0.05). Additionally, patients with delayed puberty had higher HbA1c and dyslipidemia compared to those with normal puberty (p < 0.05). The regression analysis revealed that factors associated with short stature were; age at diagnosis, HbA1C > 8.2, and albumin/creatinine ratio > 8 (p < 0.05). CONCLUSION: Children with uncontrolled T1DM are at risk of short stature and delayed puberty. Diabetes duration and control seem to be independent risk factors for short stature.