Simple Biomarker Research Articles

Correlation between the C-reactive protein (CRP)-albumin-lymphocyte (CALLY) index and the prognosis of gastric cancer patients after gastrectomy: a systematic review and meta-analysis.

The C-Reactive Protein (CRP)-Albumin-Lymphocyte (CALLY) index is an established immuno-nutritional scoring system. We screened relevant literature from the major databases up until May, 2024, and extracted the data for analysis. A total of 2829 gastric cancer (GC) patients from six studies were included in this meta-analysis, the results of which revealed that the CALLY index was an independent prognostic factor for OS and RFS in both univariate analyses and multivariate analyses, and that a high CALLY index was a favorable prognostic factor. Moreover, GC patients in the high CALLY index group seemed to have better 5-year OS and 5-year RFS than those in the low CALLY index group. There was a higher proportion of patients with T1 status in the high CALLY index group than in the low CALLY index group. However, the opposite results were found in the analyses of lymph node metastasis positivity, lymph-vascular invasion positivity, postoperative complications, differentiated histological type, anastomotic leakage, and adjuvant chemotherapy. The present meta-analysis concluded that the CALLY index was a simple and useful independent prognostic biomarker for GC patients after gastrectomy.

Pan-Immune-Inflammatory Value is Superior to Other Inflammatory Indicators in Predicting Inpatient Major Adverse Cardiovascular Events and Severe Coronary Artery Stenosis after Percutaneous Coronary Intervention in STEMI Patients.

The inflammatory response to atherosclerosis is a process that leads to coronary artery disease. Pan-immune-inflammation value (PIV) has emerged as a new and simple biomarker of inflammation. However, studies on the predictive power of PIV for major adverse cardiovascular events (MACE) or the degree of coronary artery stenosis are scarce. We aimed to explore the predictive ability of PIV for MACE and the degree of coronary artery stenosis in patients with ST-segment elevation myocardial infarction (STEMI) after percutaneous coronary intervention (PCI) during hospitalization. This study included 542 patients who were diagnosed with STEMI and who underwent PCI between 2016 and 2023 and whose PIV and other inflammatory markers were measured. Using univariate and multivariate logistic regression analysis, risk variables for MACE following PCI and severe coronary stenosis during hospitalization were assessed to create receiver operating characteristic (ROC) curves and determine the best thresholds for inflammatory markers. Spearman correlation analysis was used to evaluate the correlation of PIV and other inflammatory markers with the Gensini score (GS). Compared with the systemic inflammatory index (SII), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR), the PIV may have greater predictive value in terms of the occurrence of MACE and the degree of coronary stenosis after PCI in hospitalized STEMI patients. The correlation between the PIV and GS was strong. PIV was superior to the SII, PLR, and NLR in predicting inpatient prognosis and severe coronary stenosis after PCI for STEMI patients.

Effectiveness of Femm Approach in Managing Women with Subfertility in Mwanza, Tanzania

Introduction: Infertility is a disease of the male or female reproductive system defined by the failure to achieve a pregnancy after 12 months or more of regular unprotected sexual intercourse. Approximately one in six people have experienced infertility at some stage in their lives. In Tanzania, the prevalence of infertility is 16%. Most couples suffer from this condition silently without knowing what to do. FEMM (Fertility Education and Medical Management) has come to bring back hope and happiness in these patients. Case series: Here we present four cases of women with subfertility who have suffered for more than five years without being able to conceive. Very interesting they all conceived within two to four months after using the FEMM approach. Currently, they are all pregnant at different gestation ages. Conclusion: Women who are not ovulating cannot conceive. Many times the answers to infertility are hiding in plain sight within the patterns of a woman's menstrual cycle. Failure to ovulate is the first sign of an underlying health condition in a woman followed by irregular cycles. Observing characteristics of cervical mucus is a simple and non-expensive biomarker any woman can tell you about. Fertility awareness together with medical management helped these women to conceive.

Unsupervised representation learning of chromatin images identifies changes in cell state and tissue organization in DCIS

Ductal carcinoma in situ (DCIS) is a pre-invasive tumor that can progress to invasive breast cancer, a leading cause of cancer death. We generate a large-scale tissue microarray dataset of chromatin images, from 560 samples from 122 female patients in 3 disease stages and 11 phenotypic categories. Using representation learning on chromatin images alone, without multiplexed staining or high-throughput sequencing, we identify eight morphological cell states and tissue features marking DCIS. All cell states are observed in all disease stages with different proportions, indicating that cell states enriched in invasive cancer exist in small fractions in normal breast tissue. Tissue-level analysis reveals significant changes in the spatial organization of cell states across disease stages, which is predictive of disease stage and phenotypic category. Taken together, we show that chromatin imaging represents a powerful measure of cell state and disease stage of DCIS, providing a simple and effective tumor biomarker.

Differentiated metabolomic profiling reveals plasma amino acid signatures for primary glomerular disease

Primary glomerular disease (PGD) is an idiopathic cause of renal glomerular lesions that is characterized by proteinuria or hematuria and is the leading cause of chronic kidney disease (CKD). The identification of circulating biomarkers for the diagnosis of PGD requires a thorough understanding of the metabolic defects involved. In this study, ultra-high performance liquid chromatography–tandem mass spectrometry was performed to characterize the amino acid (AA) profiles of patients with pathologically diagnosed PGD, including minimal change disease (MCD), focal segmental glomerular sclerosis (FSGS), membranous nephropathy, and immunoglobulin A nephropathy. The plasma concentrations of asparagine and ornithine were low, and that of aspartic acid was high, in patients with all the pathologic types of PGD, compared to healthy controls. Two distinct diagnostic models were generated using the differential plasma AA profiles using logistic regression and receiver operating characteristic analyses, with areas under the curves of 1.000 and accuracies up to 100.0% in patients with MCD and FSGS. In conclusion, the progression of PGD is associated with alterations in AA profiles, The present findings provide a theoretical basis for the use of AAs as a non-invasive, real-time, rapid, and simple biomarker for the diagnosis of various pathologic types of PGD.

Serum-free light chains as a dependable biomarker for stratifying patients with metabolic dysfunction-associated steatotic liver disease.

Adaptive immunity is gaining a significant role in progression of metabolic dysfunction-associated steatotic liver disease (MASLD). B-cell activity can be assessed by serum-free light chains (sFLCs) k and λ levels. The objective of the present investigation is to examine the utility of sFLCs as non-invasive biomarkers for the stratification of MASLD. We enrolled a consecutive cohort from an outpatient liver unit. Diagnosis of metabolic dysfunction-associated steatohepatitis (MASH) was made with liver biopsy according to current guidelines. Compensated advanced chronic liver disease (cACLD) and clinically significant portal hypertension (CSPH) were defined according to Baveno VII criteria. sFLCs were measured by turbidimetry using an immunoassay. We evaluated 254 patients, 162/254 (63.8%) were male. Median age was 54 years old, and the median body mass index was 28.4 kg/m2. A total of 157/254 (61.8%) subjects underwent liver biopsy: 88 had histological diagnosis of MASH, 89 were considered as simple metabolic dysfunction-associated steatotic liver (MASL) and 77/254 (30.3%) patients with compensated metabolic dysfunction-associated cirrhosis. By using Baveno VII criteria, 101/254 (39.7%) patients had cACLD; among them, 45/101 (44.5%) had CSPH. Patients with cACLD showed higher sFLC levels compared with patients without cACLD (p < .01), and patients with CSPH showed higher sFLC levels than patients without CSPH (p < .01). At multivariable analysis, sFLCs were associated with cACLD (p < .05) independently from γ-globulins and other known dysmetabolic risk factors. κFLC was associated with CSPH (p < .05) independently from γ-globulins and other known dysmetabolic risk factors. sFLCs could be a simple biomarker for stratification of cACLD in MASLD patients.

LIVERSTAT for risk stratification for patients with metabolic dysfunction-associated fatty liver disease.

LIVERSTAT is an artificial intelligence-based noninvasive test devised to screen for and provide risk stratification for metabolic dysfunction-associated fatty liver disease (MAFLD) by using simple blood biomarkers and anthropometric measurements. We aimed to study LIVERSTAT in patients with MAFLD and to explore its role for the diagnosis of advanced fibrosis. This is a retrospective study of data from MAFLD patients who underwent a liver biopsy. Patients with type 2 diabetes who underwent transient elastography and had liver stiffness measurement (LSM)<5kPa were included as patients with no fibrosis. Among these patients, controlled attenuation parameter <248dB/m was considered as no steatosis. The LIVERSTAT results were generated based on a proprietary algorithm, blinded to the histological and LSM data. The data for 350 patients were analyzed (mean age 53years, 45% male, advanced fibrosis 22%). The sensitivity, specificity, positive predictive value, negative predictive value, and misclassification rate of LIVERSTAT to diagnose advanced fibrosis were 90%, 50%, 30%, 95%, and 42%, respectively. The corresponding rates for Fibrosis-4 score (FIB4) were 56%, 83%, 44%, 89%, and 22%, respectively. When LSM was used as a second test, the corresponding rates for LIVERSTAT were 60%, 97%, 76%, 94%, and 8%, respectively, while the corresponding rates for FIB4 were 38%, 99%, 83%, 89%, and 11%, respectively. LIVERSTAT had a higher negative predictive value compared with FIB4 and a lower misclassification rate compared with FIB4 when used in a two-step approach in combination with LSM for the diagnosis of advanced fibrosis.

Serum cystatin C, monocyte/high-density lipoprotein-C ratio, and uric acid for the diagnosis of coronary heart disease and heart failure

BACKGROUND Coronary heart disease (CHD) and heart failure (HF) are the major causes of morbidity and mortality worldwide. Early and accurate diagnoses of CHD and HF are essential for optimal management and prognosis. However, conventional diagnostic methods such as electrocardiography, echocardiography, and cardiac biomarkers have certain limitations, such as low sensitivity, specificity, availability, and cost-effectiveness. Therefore, there is a need for simple, noninvasive, and reliable biomarkers to diagnose CHD and HF. AIM To investigate serum cystatin C (Cys-C), monocyte/high-density lipoprotein cholesterol ratio (MHR), and uric acid (UA) diagnostic values for CHD and HF. METHODS We enrolled 80 patients with suspected CHD or HF who were admitted to our hospital between July 2022 and July 2023. The patients were divided into CHD (n = 20), HF (n = 20), CHD + HF (n = 20), and control groups (n = 20). The serum levels of Cys-C, MHR, and UA were measured using immunonephelometry and an enzymatic method, respectively, and the diagnostic values for CHD and HF were evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS Serum levels of Cys-C, MHR, and UA were significantly higher in the CHD, HF, and CHD + HF groups than those in the control group. The serum levels of Cys-C, MHR, and UA were significantly higher in the CHD + HF group than those in the CHD or HF group. The ROC curve analysis showed that serum Cys-C, MHR, and UA had good diagnostic performance for CHD and HF, with areas under the curve ranging from 0.78 to 0.93. The optimal cutoff values of serum Cys-C, MHR, and UA for diagnosing CHD, HF, and CHD+HF were 1.2 mg/L, 0.9 × 109, and 389 µmol/L; 1.4 mg/L, 1.0 × 109, and 449 µmol/L; and 1.6 mg/L, 1.1 × 109, and 508 µmol/L, respectively. CONCLUSION Serum Cys-C, MHR, and UA are useful biomarkers for diagnosing CHD and HF, and CHD+HF. These can provide information for decision-making and risk stratification in patients with CHD and HF.

Evaluation of Oxidative Stress and Endothelial Dysfunction in COVID-19 Patients.

Background and Objectives: Heat shock proteins (HSPs) are stress proteins. The endogenous nitric oxide (NO) synthase inhibitor asymmetric dimethyl arginine (ADMA) is a mediator of endothelial dysfunction. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus causes endothelial dysfunction and coagulopathy through severe inflammation and oxidative stress. Using these markers, we analyzed the prognostic value of serum ADMA and HSP-90 levels for early prediction of severe coronavirus disease (COVID-19) patients. Materials and Methods: A total of 76 COVID-19 patients and 35 healthy control subjects were included in this case-control study. COVID-19 patients were divided into two groups: mild and severe. Results: Serum ADMA and HSP-90 levels were significantly higher in the COVID-19 patients compared to the control subjects (p < 0.001). Additionally, serum ADMA and HSP-90 levels were determined to be higher in a statistically significant way in severe COVID-19 compared to mild COVID-19 (p < 0.001). Univariable logistic regression analysis revealed that ADMA and HSP-90, respectively, were independent predictors of severe disease in COVID-19 patients (ADMA (OR = 1.099, 95% CI = 1.048-1.152, p < 0.001) and HSP-90 (OR = 5.296, 95% CI = 1.719-16.316, p = 0.004)). When the cut-off value for ADMA was determined as 208.94 for the prediction of the severity of COVID-19 patients, the sensitivity was 72.9% and the specificity was 100% (AUC = 0.938, 95%CI = 0.858-0.981, p < 0.001). When the cut-off value for HSP-90 was determined as 12.68 for the prediction of the severity of COVID-19 patients, the sensitivity was 88.1% and the specificity was 100% (AUC = 0.975, 95% CI= 0.910-0.997, p < 0.001). Conclusions: Increased levels of Heat shock proteins-90 (HSP-90) and ADMA were positively correlated with increased endothelial damage in COVID-19 patients, suggesting that treatments focused on preventing and improving endothelial dysfunction could significantly improve the outcomes and reduce the mortality rate of COVID-19. ADMA and HSP-90 might be simple, useful, and prognostic biomarkers that can be utilized to predict patients who are at high risk of severe disease due to COVID-19.

Serum albumin and white matter hyperintensities

People living with HIV and those diagnosed with alcohol use disorders (AUD) relative to healthy individuals commonly have low levels of serum albumin, substantiated as an independent predictor of cardiovascular events. White matter hyperintensities (WMH)—a neuroimaging feature of cerebral small vessel disease—are also related to cardiovascular disease. Despite consensus regarding associations between high levels of urine albumin and WMH prevalence, and low serum albumin levels and impaired cognitive functioning, relations between serum albumin and WMH burdens have rarely been evaluated. Here, a sample including 160 individuals with AUD, 142 living with HIV, and 102 healthy controls was used to test the hypothesis that serum albumin would be inversely related to WMH volumes and directly related to cognitive performance in the two diagnostic groups. Although serum albumin and periventricular WMH volumes showed an inverse relationship in both AUD and HIV groups, this relationship persisted only in the HIV group after consideration of traditional cardiovascular (i.e., age, sex, body mass index (BMI), nicotine use, hypertension, diabetes), study-relevant (i.e., race, socioeconomic status, hepatitis C virus status), and disease-specific (i.e., CD4 nadir, HIV viral load, HIV duration) factors. Further, serum albumin contributed more significantly than periventricular WMH volume to variance in performance on a verbal learning and memory composite score in the HIV group only. Relations in both HIV and AUD groups between albumin and hematological red blood cell markers (e.g., hemoglobin, hematocrit) suggest that in this sample, serum albumin reflects hematological abnormalities. Albumin, a simple serum biomarker available in most clinical settings, may therefore help identify periventricular WMH burden and performance levels in specific cognitive domains in people living with HIV. Whether serum albumin contributes mechanistically to periventricular WMH in HIV will require additional investigation.

Corticomotor pathway function and recovery after stroke: a look back and a way forward.

Stroke is a leading cause of adult disability that results in motor deficits and reduced independence. Regaining independence relies on motor recovery, particularly regaining function of the hand and arm. This review presents evidence from human studies that have used transcranial magnetic stimulation (TMS) to identify neurophysiological mechanisms underlying upper limb motor recovery early after stroke. TMS studies undertaken at the subacute stage after stroke have identified several neurophysiological factors that can drive motor impairment, including membrane excitability, the recruitment of corticomotor neurons, and glutamatergic and GABAergic neurotransmission. However, the inherent variability and subsequent poor reliability of measures derived from motor evoked potentials (MEPs) limit the use of TMS for prognosis at the individual patient level. Currently, prediction tools that provide the most accurate information about upper limb motor outcomes for individual patients early after stroke combine clinical measures with a simple neurophysiological biomarker based on MEP presence or absence, i.e. MEP status. Here, we propose a new compositional framework to examine MEPs across several upper limb muscles within a threshold matrix. The matrix can provide a more comprehensive view of corticomotor function and recovery after stroke by quantifying the evolution of subthreshold and suprathreshold MEPs through compositional analyses. Our contention is that subthreshold responses might be the most sensitive to reduced output of corticomotor neurons, desynchronized firing of the remaining neurons, and myelination processes that occur early after stroke. Quantifying subthreshold responses might provide new insights into post-stroke neurophysiology and improve the accuracy of prediction of upper limb motor outcomes.

Evaluating Cardiovascular Risks: The Platelet Lymphocyte Ratio and the Neutrophil Lymphocyte Ratio As High-Risk Heart Score Predictors in Non-ST Elevation Myocardial Infarction (NSTEMI) and Unstable Angina Patients.

Introduction Acute coronary syndromes (ACS), encompassing non-ST elevation myocardial infarction (NSTEMI) and unstable angina (UA), present significant challenges in risk assessment and management, particularly in resource-constrained environments like India. The burden of cardiovascular diseases in such regions necessitates cost-effective and readily accessible tools for risk stratification. Previous research has emphasized the role of inflammatory markers in coronary artery disease (CAD), prompting investigations into simple and affordable biomarkers for risk assessment. Platelet lymphocyte ratio (PLR) and neutrophil lymphocyte ratio (NLR) have emerged as potential biomarkers for thrombotic activity in cardiac illnesses, offering simplicity, accessibility, and cost-effectiveness in risk assessmentmaking them particularly valuable in resource-poor settings like India, where advanced diagnostic tools may be limited. Objective This study aims to evaluate the effectiveness of PLR and NLR as predictors of high-risk HEART(history, ECG, age, risk factors, and troponin) scores in patients with NSTEMI and UA. Methods A prospective cross-sectional study was conducted at the Saveetha Medical College and Hospitals in Chennai, India, from March 2021 to September 2022. The study included 288 adults diagnosed with NSTEMIor UA, aged 18 years and above. The inclusion criteria comprised patients with confirmed diagnoses of NSTEMI or UA based on clinical symptoms, electrocardiographic findings, and cardiac biomarker elevation. The exclusion criteria encompassed patients with active infections, acute traumatic injuries, end-stage renal disease, malignant neoplasms, and ST-elevation myocardial infarction (STEMI). In addition to the HEART score, PLR, and NLR were computed to assess the prognosis of patients admitted to the Saveetha Medical College and Hospitals. Results The statistical analysis revealed significant correlations between PLR, NLR, and HEART score risk categories. The Pearson's correlation coefficient indicated strong associations between PLR/NLR values and HEART score risk groups, suggesting their potential as predictive markers for adverse clinical outcomes. Additionally, analysis of variance (ANOVA) demonstrated significant differences in PLR/NLR values across different HEART score risk categories, further highlighting their relevance in risk stratification. The effect sizes for these correlations were moderate to large, indicating clinically meaningful associations between PLR/NLR and cardiovascular risk. Conclusion In cases of NSTEMI and UA, PLR and NLR show potential as simple and inexpensive indicators of high-risk patients. By leveraging these inexpensive biomarkers, healthcare providers can enhance risk assessment and prognostication in patients presenting with ACS, facilitating timely interventions and tailored management strategies.

Can the pan-immune-inflammation value predict gram negative bloodstream infection-related 30-day mortality in solid organ transplant patients?

BackgroundThe recently used pan-immune-inflammation value (PIV) has not been adequately studied as a predictive marker for mortality in immunosuppressed patients. The aim of this study was to evaluate the usefulness of baseline PIV level as a predictor of 30-day mortality in solid organ transplant (SOT) recipients with gram negative bloodstream infections (GN-BSI).MethodsThis retrospective, cross-sectional study was conducted between January 1, 2019, and December 31, 2022, in 1104 SOT recipients. During the study period, 118 GN-BSI were recorded in 113 patients. Clinical, epidemiological, and laboratory data were collected, and mortality rates (30-day and all-cause) were recorded.ResultsThe 113 recipients had a median age of 50 years [interquartile range (IQR) 37.5–61.5 years] with a male predominance (n = 72, 63.7%). The three most common microorganisms were as follows: 46 isolates (38.9%) of Escherichia coli, 41 (34.7%) of Klebsiella pneumoniae, and 12 (10.2%) of Acinetobacter baumannii. In 44.9% and 35.6% of the isolates, production of extended-spectrum beta-lactamases and carbapenem resistance were detected, respectively. The incidence of carbapenem-resistant GN-BSI was higher in liver recipients than in renal recipients (n = 27, 69.2% vs n = 13, 17.6%, p < 0.001). All-cause and 30-day mortality rates after GN-BSI were 26.5% (n = 30), and 16.8% (n = 19), respectively. In the group with GN-BSI-related 30-day mortality, the median PIV level was significantly lower (327.3, IQR 64.8–795.4 vs. 1049.6, IQR 338.6–2177.1; p = 0.002). The binary logistic regression analysis identified low PIV level [hazard ratio (HR) = 0.93, 95% confidence interval (CI) 0.86–0.99; p = 0.04], and increased age (HR = 1.05, 95% CI 1.01–1.09; p = 0.002) as factors associated with 30-day mortality. The receiver operating characteristic analysis revealed that PIV could determine the GN-BSI-related 30-day mortality with area under curve (AUC): 0.723, 95% CI 0.597–0.848, p = 0.0005.ConclusionsPIV is a simple and inexpensive biomarker that can be used to estimate mortality in immunosuppressed patients, but the results need to be interpreted carefully.

Potential clinical application of anti-Müllerian hormone testing in radioiodine treatment of thyroid carcinoma

Differentiated thyroid cancer is the most common endocrinological malignancy. Radioiodine treatment has a clear benefit in locally aggressive and metastatic cancers. There are discussions about long-term and acute adverse events.Anti-Müllerian hormone is regarded as the best endocrine marker for evaluating the physiological loss of oocytes in healthy women with regard to age. The impact of radioiodine treatment on anti-Müllerian hormone levels has been more significantly reported in patients over 35 years of age. About reproductive dysfunction, calculations of individual absorbed doses of radioiodine in ovaries after thyroid cancer therapy have not been performed yet. The aim of our ongoing prospective study is to determine serum anti-Müllerian hormone to estimate ovarian reserve for premenopausal women treated with radioiodine and to compare anti-Müllerian hormone levels before and after radioiodine treatment. Predicting radioiodine side effects by evaluating a simple serum biomarker may help to select an appropriate treatment strategy for young women planning pregnancy, specifically in the assessment of ovarian reserve and premature ovarian failure with early onset of menopause.

Evaluation of hematological inflammatory parameters in patients with palmoplantar pustulosis.

Palmoplantar pustulosis (PPP) is a chronic inflammatory disease of ill-defined etiopathology. Recent studies have proposed complete blood count-based hematological parameters, such as neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR), as biomarkers to monitor disease status in many inflammatory diseases. This study aimed to analyze for the first time the clinical significance of hematological parameters, including NLR, monocyte/lymphocyte ratio (MLR), PLR, mean platelet volume (MPV), plateletcrit (PCT), and pan-immune-inflammation value (PIV) in PPP patients. We retrospectively investigated the clinical and laboratory data of 237 patients with PPP and 250 sex-age-matched healthy controls (HCs). Hematological parameters were compared between patients with PPP and HCs. The correlations between these parameters and disease severity, as well as treatment response, were analyzed. NLR, MLR, MPV, PCT, and PIV values were significantly higher in PPP patients than in HCs. But in receiver-operating characteristic analyses, only monocyte count (Youden Index = 0.53), PCT (Youden Index = 0.65), and PIV (Youden Index = 0.52) performed relatively accurate distinguishment between moderate-to-severe cases and mild cases. PCT and PIV values were significantly correlated with disease severity. After treatment, both PIV and PCT values decreased significantly in the responder group but not in the non-responder group. Hematological parameters altered significantly in PPP patients. PCT and PIV can be used as simple and inexpensive biomarkers for systemic inflammation in PPP patients.

Coronary microvascular dysfunction and inflammation: Insights from the Coronary Microvascular Disease Registry

BackgroundCoronary microvascular dysfunction (CMD) is associated with various inflammatory conditions that worsen endothelial dysfunction. This study aimed to investigate the relationship between CMD and inflammation using common inflammatory markers derived from complete blood count (CBC) analysis. MethodsInformation was gathered from the Coronary Microvascular Disease Registry to examine the neutrophil-to-lymphocyte ratio (NLR), eosinophil-to-monocyte ratio (EMR), and monocyte-to-high-density lipoprotein ratio (MHR) in a cohort of patients with angina who showed non-obstructive coronary arteries and underwent invasive physiological assessments for CMD. ResultsOf the 171 patients studied, 126 were CMD-negative and 45 were CMD-positive, constituting two groups of interest. The average age of all patients was 61.7 ± 11.1 years, and 63.7 % were female. No significant differences were observed between the two groups in terms of baseline characteristics, cardiovascular risk factors, or potential anti-inflammatory medications. Furthermore, there were no statistically significant differences in NLR (2.54 ± 3.71 vs. 2.52 ± 2.28, p = 0.97), EMR (0.3 ± 0.21 vs. 0.34 ± 0.29, p = 0.31), or MHR (0.02 ± 0.01 vs. 0.01 ± 0.01, p = 0.54) between CMD-positive and CMD-negative patients. ConclusionOur findings did not show a noteworthy connection between CMD and inflammation, as suggested by various simple CBC-based biomarkers.

Furosemide stress test to predict acute kidney injury progression in critically ill children.

Furosemide stress test (FST) is a novel functional biomarker for predicting severe acute kidney injury (AKI); however, pediatric studies are limited. Children 3months to 18years of age admitted to the intensive care unit (ICU) of a tertiary care hospital from Nov 2019 to July 2021 were screened and those who developed AKI stage 1 or 2 within 7days of admission underwent FST (intravenous furosemide 1mg/kg). Urine output was measured hourly for the next 6h; a value > 2ml/kg within the first 2h was deemed furosemide responsive. Other biomarkers like plasma neutrophil gelatinase-associated lipocalin (NGAL) and proenkephalin (PENK) were also evaluated. Of the 480 admitted patients, 51 developed AKI stage 1 or 2 within 7days of admission and underwent FST. Nine of these patients were furosemide non-responsive. Thirteen (25.5%) patients (eight of nine from FST non-responsive group) developed stage 3 AKI within 7days of FST, nine (17.6%) of whom (seven from non-responsive group) required kidney support therapy (KST). FST emerged as a good biomarker for predicting stage 3 AKI and need for KST with area-under-the-curve (AUC) being 0.93 ± 0.05 (95% CI 0.84-1.0) and 0.96 ± 0.03 (95% CI 0.9-1.0), respectively. FST outperformed NGAL and PENK in predicting AKI stage 3 and KST; however, the combination did not improve the diagnostic accuracy. Furosemide stress test is a simple, inexpensive, and robust biomarker for predicting stage 3 AKI and KST need in critically ill children. Further research is required to identify the best FST cut-off in children.

Toxicity Detection of Pollutants in the Tallo River Using Simple Biomarkers of Oryzias celebensis Embryo

The current research demonstrated the use of simple biomarkers from Oryzias celebensis embryos to detect the effects of pollutants from the Tallo River. The biomarkers used in this research were somite number, egg biometrics, heart rate, survival rate, and hatching time. Pollutants were sampled from three hot spots in the Tallo River (Station 1 (S1), Station 2 (S2) and Station 3 (S3)). Two exposure models were used in this study: in situ and semi-in situ exposure. In situ exposure was carried out by placing ten embryos (stage 17) at each station for six days. Semi-in situ embryos (10 animals) were exposed to polluted water from each station and embryo rearing media (ERM) as a control at stage 17 until hatching in the laboratory. Biomarker data were analyzed using ANOVA (Analysis of variance) to determine the sensitivity of each biomarker used. Almost all the embryos used as model animals in the in situ experiment died, except for two embryos placed in stations 2 and 3. The embryos from station 2 hatched after 18 days. The embryos from station 3 died after 18 days. The semi in situ experiment showed that the number of somites and heart rate showed statistically significant differences between embryos exposed to water from S1 and control embryos (p &lt; 0.05). Other endpoints did not show potential as biomarkers. This study suggested that the number of somites and heart rate of O. celebensis embryos could potentially be used as biomarkers in effect-based monitoring.

Combined blood Neurofilament light chain and third ventricle width to differentiate Progressive Supranuclear Palsy from Parkinson's Disease: A machine learning study

IntroductionDifferentiating Progressive Supranuclear Palsy (PSP) from Parkinson's Disease (PD) may be clinically challenging. In this study, we explored the performance of machine learning models based on MR imaging and blood molecular biomarkers in distinguishing between these two neurodegenerative diseases. MethodsTwenty-eight PSP patients, 46 PD patients and 60 control subjects (HC) were consecutively enrolled in the study. Serum concentration of neurofilament light chain protein (Nf-L) was assessed by single molecule array (SIMOA), while an automatic segmentation algorithm was employed for T1-weighted measurements of third ventricle width/intracranial diameter ratio (3rdV/ID). Machine learning (ML) models with Logistic Regression (LR), Random Forest (RF), and XGBoost algorithms based on 3rdV/ID and serum Nf-L levels were tested in distinguishing among PSP, PD and HC. ResultsPSP patients showed higher serum Nf-L levels and larger 3rdV/ID ratio in comparison with both PD and HC groups (p < 0.005). All ML algorithms (LR, RF and XGBoost) showed that the combination of MRI and blood biomarkers had excellent classification performances in differentiating PSP from PD (AUC ≥0.92), outperforming each biomarker used alone (AUC: 0.85–0.90). Among the different algorithms, XGBoost was slightly more powerful than LR and RF in distinguishing PSP from PD patients, reaching AUC of 0.94 ± 0.04. ConclusionOur findings highlight the usefulness of combining blood and simple linear MRI biomarkers to accurately distinguish between PSP and PD patients. This multimodal approach may play a pivotal role in patient management and clinical decision-making, paving the way for more effective and timely interventions in these neurodegenerative diseases.

Predictive value of the systemic immune-inflammation index on one-year mortality in geriatric hip fractures.

Geriatric hip fractures are associated with a high incidence of mortality. This study examines the predictive value of the systemic immune-inflammation index (SII) on one-year mortality in elderly hip fracture patients. A single-center retrospective study was conducted between February 2017 and October 2020. Three hundred and eleven surgically treated consecutive hip fracture patients were included in the study. Admission, postoperative first day, and postoperative fifth-day SII values were calculated. The receiver operating characteristic (ROC) curve was used to calculate the cut-off values, and patients were divided into high and low groups according to these cut-off values. After univariate Cox regression analysis, significant factors were included in the multivariate Cox proportional hazards model to adjust the effect of covariates and explore independent predictive factors associated with mortality. Further subgroup analysis was performed to evaluate the accuracy of the results for different clinical and biological characteristics. The mean age was 80.7 ± 8.0 years, and women made up the majority (67.8%) of the patients. The one-year mortality rate was 28.0%. After univariate and multivariate analyses, high postoperative fifth-day SII remained an independent predictor of one-year mortality (adjusted HR 2.16, 95% CI 1.38-3.38, p = 0.001). Older age, male gender, Charlson comorbidity index (CCI) ≥ 2, and hypoalbuminemia were found to be other independent predictors. The optimal cut-off value of the postoperative fifth-day SII was calculated at 1751.9 units (p < 0.001). The postoperative fifth-day SII is a simple and useful inflammatory biomarker for predicting one-year mortality in patients with hip fracture.