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Introduction Multimodal monitoring is the use of data from multiple physiological sensors combined in a way to provide individualized patient management. It is becoming commonplace in the civilian care of traumatic brain-injured patients. We hypothesized we could bring the technology to the battlefield using a noninvasive sensor suite and an artificial intelligence-based patient management guidance system. Methods Working with military medical personnel, we gathered requirements for a hand-held system that would adapt to the rapidly evolving field of neurocritical care. To select the optimal sensors, we developed a method to evaluate both the value of the sensor's measurement in managing brain injury and the burden to deploy that sensor in the battlefield. We called this the Value-Burden Analysis which resulted in a score weighted by the Role of Care. The Value was assessed using 7 criteria, 1 of which was the clinical value as assessed by a consensus of clinicians. The Burden was assessed using 16 factors such as size, weight, and ease of use. We evaluated and scored 17 sensors to test the assessment methodology. In addition, we developed a design for the guidance system, built a prototype, and tested the feasibility. Results The resulting architecture of the system was modular, requiring the development of an interoperable description of each component including sensors, guideline steps, medications, analytics, resources, and the context of care. A Knowledge Base was created to describe the interactions of the modules. A prototype test set-up demonstrated the feasibility of the system in that simulated physiological inputs would mimic the guidance provided by the current Clinical Practice Guidelines for Traumatic Brain Injury in Prolonged Care (CPG ID:63). The Value-Burden analysis yielded a ranking of sensors as well as sensor metadata useful in the Knowledge Base. Conclusion We developed a design and tested the feasibility of a system that would allow the use of physiological biomarkers as a management tool in forward care. A key feature is the modular design that allows the system to adapt to changes in sensors, resources, and context as well as to updates in guidelines as they are developed. Continued work consists of further validation of the concept with simulated scenarios. [ABSTRACT FROM AUTHOR]

Introduction Achieving simultaneous cerebral blood flow (CBF) and oxygenation measures, specifically for point-of-care injury monitoring in prolonged field care, requires the implementation of appropriate methodologies and advanced medical device design, development, and evaluation. The near-infrared spectroscopy (NIRS) method measures the absorbance of light whose attenuation is related to cerebral blood volume and oxygenation. By contrast, diffuse correlation spectroscopy (DCS) allows continuous noninvasive monitoring of microvascular blood flow by directly measuring the degree of light scattering because of red blood cell (RBC) movement in tissue capillaries. Hence, this study utilizes these two optical approaches (DCS–NIRS) to obtain a more complete hemodynamic monitoring by providing cerebral microvascular blood flow, hemoglobin oxygenation and deoxygenation in hemorrhage, and hypoxia-induced injuries. Materials and Methods Piglet models of hemorrhage and hypoxia-induced brain injury were used with DCS and NIRS sensors placed over the preorbital to temporal skull regions. To induce hemorrhagic shock, up to 70% of the animal's total blood volume was withdrawn through graded hemorrhage serially via a syringe from a femoral artery cannula in 10 mL/kg aliquots over 1 minute every 10 minutes. A second group of animals was subjected to hypoxia for ∼1 hour through graded hypoxia by serial titration from normoxic fraction inspired oxygen of 21% to hypoxic fraction inspired oxygen of 6%. A subset of animals served as sham-controls undergoing anesthesia, instrumentation, and ventilation as the injury groups, yet experiencing no blood loss or hypoxia. Results We first investigated the relationship between hemorrhagic shock and no shock by using measured biomarkers, including blood flow index from DCS associated with CBF and oxygenated (HbO) and de-oxygenated hemoglobin from NIRS. The statistical analysis revealed a significant difference between no shock and hemorrhagic shock (P  < .01). The HbO decreased with each blood loss as expected, yet the de-oxygenated hemoglobin was slightly changed. During hypoxia-induced global hypoxic–ischemic injury tests, the CBF results from graded hypoxia were consistent with the response previously measured during hemorrhagic shock. Moreover, HbO decreased when the animal was hypoxic, as expected. A statistical analysis was also conducted to compare the results with those of the sham controls. Conclusions There is a consistency in blood flow measures in both injury mechanisms (hemorrhagic shock and hypoxia), which is significant as the new prototype system provides similar measures and trends for each brain injury type, suggesting that the optical system can be used in response to different injury mechanisms. Notably, the results support the idea that this optical system can probe the hemodynamic status of local cerebral cortical tissue and provide insight into the underlying changes of cerebral tissue perfusion at the microvascular level. These measurement capabilities can improve shock identification and monitoring of medical management of injuries, particularly hemorrhagic shock, in prolonged field care. [ABSTRACT FROM AUTHOR]

Introduction Asthma is the most common diagnosis in military personnel who endorse chronic dyspnea. Service members have unique occupational risk factors, and there is concern that airborne exposures in the deployed environment as well as other occupational exposures may contribute to the development of asthma or exacerbate pre-existing disease. Asthma phenotyping with clinical biomarkers such as serum immunoglobulin E (IgE) levels and eosinophil (EOS) counts is useful in defining treatment strategies for the management of asthma. This study sought to characterize the phenotype of medically separated military personnel with career-limiting asthma to define potential management strategies and guide future research evaluating the unexplained prevalence of asthma in this population. Materials and Methods A retrospective chart review of active duty service members (ADSM) who underwent fitness for duty evaluation via medical evaluation board between 2005 and 2016 and were separated with a minimum 30% conditional disability rating for asthma was performed. Only ADSM who were diagnosed with asthma by a pulmonologist and had spirometry data available were included in the analysis. Demographics, spirometry data, and laboratory data to include IgE levels, radioallergosorbent panels, and EOS counts were analyzed from the DoD electronic medical record. Results A total of 141 service members were evaluated with a mean age of 42 ± 6.8 years, mean serum EOS count of 300 ± 358 cells/μL, and mean IgE level of 305 ± 363 IU/mL. The patients were further categorized into 4 subgroups based on serum EOS count and IgE level: group A with IgE < 100 IU/mL and EOS < 300 cells/μL (n  = 45; 33%), group B with IgE > 100 IU/mL and EOS < 300 cells/μL (n  = 44; 32%), group C with IgE < 100 IU/mL and EOS > 300 cells/μL (n  = 6; 1%), and group D with IgE > 100 IU/mL, EOS > 300 cells/μL (n  = 46; 34%). Among the cohorts, there were no statistically significant differences in demographics, body mass index, spirometry, smoking history, or disability rating. Conclusion The majority of ADSM with a defined asthma history do not have concordant elevations in serum IgE and blood EOS suggestive of a Th2-high phenotype. Asthma in this population is heterogeneous, and phenotyping using clinical biomarkers may be useful to define optimal treatment strategies. [ABSTRACT FROM AUTHOR]

Bipolar disorder (BD) is a severe psychiatric disease with high rates of misdiagnosis and underdiagnosis, resulting in a significant disease burden on both individuals and society. Abnormal neural oscillations have garnered significant attention as potential neurobiological markers of BD. However, untangling the mechanisms that subserve these baseline alternations requires measurement of their electrophysiological underpinnings. This systematic review investigates consistent abnormal resting-state EEG power of BD and conducted an initial exploration into how methodological approaches might impact the study outcomes. This review was conducted in Pubmed-Medline and Web-of-Science in March 2024 to summarize the oscillation changes in resting-state EEG (rsEEG) of BD. We focusing on rsEEG to report spectral power in different frequency bands. We identified 10 studies, in which neural oscillations was compared with healthy individuals (HCs). We found that BD patients had abnormal oscillations in delta, theta, beta, and gamma bands, predominantly characterized by increased power, indicating potential widespread neural dysfunction, involving multiple neural networks and cognitive processes. However, the outcomes regarding alpha oscillation in BD were more heterogeneous, which is thought to be potentially influenced by the disease severity and the diversity of samples. Furthermore, we conducted an initial exploration into how demographic and methodological elements might impact the study outcomes, underlining the importance of implementing standardized data collection methods. Key aspects we took into account included gender, age, medication usage, medical history, the method of frequency band segmentation, and situation of eye open/eye close during the recordings. Therefore, in the face of abnormal multiple oscillations in BD, we need to adopt a comprehensive research approach, consider the multidimensional attributes of the disease and the heterogeneity of samples, and pay attention to the standardized experimental design to improve the reliability and reproducibility of the research results. [ABSTRACT FROM AUTHOR]

Purpose We evaluated whether plasma Alzheimer disease (AD)–related biomarkers were associated with cancer-related cognitive decline among older breast cancer survivors. Methods We included survivors aged 60-90 years with primary stage 0-III breast cancers (n = 236) and frequency-matched noncancer control paricipant (n = 154) who passed a cognitive screen and had banked plasma specimens. Participants were assessed at baseline (presystemic therapy) and annually for up to 60 months. Cognition was measured using tests of attention, processing speed, and executive function and learning and memory; perceived cognition was measured by the Functional Assessment of Cancer Therapy-Cognitive Function v3 Perceived Cognitive Impairments. Baseline plasma neurofilament light, glial fibrillary acidic protein, β-amyloid 42 and 40 and phosphorylated tau 181 were assayed using single molecule arrays. Mixed models tested associations between cognition and baseline AD biomarkers, time, group (survivor vs control participant), and their 2- and 3-way interactions, controlling for age, race, Wide Range 4 Achievement Test Word Reading score, comorbidity, and body mass index; 2-sided P values of.05 were considered statistically significant. Results There were no group differences in baseline AD-related biomarkers except survivors had higher baseline neurofilament light levels than control participants (P  = .013). Survivors had lower adjusted longitudinal attention, processing speed, and executive function than control participants starting from baseline and continuing over time (P  ≤ .002). However, baseline AD-related biomarker levels were not independently associated with adjusted cognition over time, except control participants had lower attention, processing speed, and executive function scores with higher glial fibrillary acidic protein levels (P  = .008). Conclusion The results do not support a relationship between baseline AD-related biomarkers and cancer-related cognitive decline. Further investigation is warranted to confirm the findings, test effects of longitudinal changes in AD-related biomarkers, and examine other mechanisms and factors affecting cognition presystemic therapy. [ABSTRACT FROM AUTHOR]

Background Camonsertib is a selective oral inhibitor of ataxia telangiectasia and Rad3-related (ATR) kinase with demonstrated efficacy in tumors with DNA damage response gene deficiencies. On-target anemia is the main drug-related toxicity typically manifesting after the period of dose-limiting toxicity evaluation. Thus, dose and schedule optimization requires extended follow-up to assess prolonged treatment effects. Methods Long-term safety, tolerability, and antitumor efficacy of 3 camonsertib monotherapy dosing regimens were assessed in the TRESR study dose-optimization phase: 160 mg once daily (QD) 3 days on, 4 days off (160 3/4; the preliminary recommended Phase II dose [RP2D]) and two step-down groups of 120 mg QD 3/4 (120 3/4) and 160 mg QD 3/4, 2 weeks on, 1 week off (160 3/4, 2/1w). Safety endpoints included incidence of treatment-related adverse events (TRAEs), dose modifications, and transfusions. Efficacy endpoints included overall response rate, clinical benefit rate, progression-free survival, and circulating tumor DNA (ctDNA)-based molecular response rate. Results The analysis included 119 patients: 160 3/4 (n = 67), 120 3/4 (n = 25), and 160 3/4, 2/1w (n = 27) treated up to 117.1 weeks as of the data cutoff. The risk of developing grade 3 anemia was significantly lower in the 160 3/4, 2/1w group compared with the preliminary RP2D group (hazard ratio = 0.23, 2-sided P  = .02), translating to reduced transfusion and dose reduction requirements. The intermittent weekly schedule did not compromise antitumor activity. Conclusion The 160 3/4, 2/1w dose was established as an optimized regimen for future camonsertib monotherapy studies offering a substantial reduction in the incidence of anemia without any compromise to efficacy. Clinical Trial ID NCT04497116. [ABSTRACT FROM AUTHOR]

Background Serum level of microRNA-122 (miR-122) has been reported as a sensitive diagnostic biomarker for detecting liver injury, comparable to the aminotransferases. Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) activities are increased in other conditions, such as acute skeletal muscle injury (ASMI). We determined whether miR-122 is nonspecifically increased in patients suffering from ASMI. Methods We measured ALT, AST, creatine kinase (CK), and miR-122 in 3 groups: healthy controls (n = 24), patients with ASMI (total n = 29, 11 with recreational drug use and 18 without recreational drug use), and patients with acute liver injury (ALI; n = 14). Results Levels of ALT, AST, and CK increased 83%, 97%, and 100% for patients with ASMI and 100% for all 3 enzymes in ALI patients. In contrast, miR-122 increased in 34% of patients with ASMI (44.4% with recreational drug use and 18.2% without recreational drug use) and 100% of ALI patients. In 2 drug-induced liver injury cases, miR-122 increased about 12-24 hours before ALT and AST. Conclusion Recreational drug misuse is associated with both rhabdomyolysis and drug-induced liver injury (DILI). The traditional liver function markers AST and ALT were nonspecifically increased in the majority of patients with ASMI. miR-122 is only increased in patients at risk for DILI and demonstrates superior specificity for liver injury. [ABSTRACT FROM AUTHOR]

Non–small cell lung cancer (NSCLC) has been found to have recurrent genetic abnormalities, and novel therapies targeting these aberrations have improved patient survival. In this study, specimens from benign tissue, primary tumors, and brain metastases were obtained at autopsy from a 55-year-old White female patient diagnosed with NSCLC and were examined using next-generation sequencing (NGS) and chromosomal microarray assay (CMA). No genetic aberrations were noted in the benign tissue; however, NGS identified a mutation in the KRAS proto-oncogene, GTPase (KRAS): KRAS exon 2 p.G12D in primary and metastatic tumor specimens. We observed 7 DNA copy number aberrations (CNAs) in primary and metastatic tumor specimens; an additional 7 CNAs were exclusively detected in the metastatic tumor specimens. These DNA alterations may be genetic drivers in the pathogenesis of the tumor specimen from our patient and may serve as biomarkers for the classification and prognosis of NSCLC. [ABSTRACT FROM AUTHOR]

Lupus nephritis (LN) is one of the most severe clinical manifestations of systemic lupus erythematosus (SLE). Notably, the clinical manifestations of LN are not always consistent with the histopathological findings. Therefore, the diagnosis and activity monitoring of this disease are challenging and largely depend on invasive renal biopsy. Renal biopsy has side effects and is associated with the risk of bleeding and infection. There is a growing interest in the development of novel noninvasive biomarkers for LN. In this review, we summarize most of the LN biomarkers discovered so far by correlating current knowledge with future perspectives. These biomarkers fundamentally reflect the biological processes of kidney damage and repair during disease. Furthermore, this review highlights the role of urinary cell phenotype detection in the diagnosis, monitoring, and treatment of LN and summarizes the limitations and countermeasures of this test. [ABSTRACT FROM AUTHOR]

Background Cardiac injury caused by iron overload is the leading cause of mortality and morbidity in patients with beta-thalassemia, owing to frequent blood transfusion, increased iron overload, and blood hemolysis. Objective This research aimed to assess several novel cardiac biomarkers in the blood samples of children and adult patients with beta-thalassemia major (βTM), along with their respective control groups. These biomarkers included endothelin 1 (ET-1), N-terminal pro-brain natriuretic peptide (NT-proBNP), atrial natriuretic peptide (ANP), growth differentiation factor-15 (GDF-15), and renalase (RNLS). Methods This case-control study was done on 46 patients with βTM (23 children <18 years, and 23 adults ≥18 years) from the Genetic Hematology Center in Thi-Qar province, Iraq, and 42 comparable controls in 2 groups (21 for each group) in the period from February to April 2023. Results Levels of ET-1, NT-proBNP, ANP, GDF-15, RNLS, and ferritin were higher in the children and adults with βTM than in the control subjects. Conclusion Elevations of the novel cardiac biomarkers ET-1, NT-proBNP, ANP, GDF-15, and RNLS in the sera of children and adult patients with βTM when compared with comparable control subjects confirm that the majority of patients with βTM are at risk of cardiac and cardiovascular complications even when there are no obvious symptoms, especially in children, which gives suitable predictive biomarkers. [ABSTRACT FROM AUTHOR]

Apilimod dimesylate is a first-in-class phosphoinositide kinase, FYVE-type zinc finger-containing (PIKfyve) inhibitor with a favourable clinical safety profile and has demonstrated activity in preclinical C9orf72 and TDP-43 amyotrophic lateral sclerosis (ALS) models. In this ALS clinical trial, the safety, tolerability, CNS penetrance and modulation of pharmacodynamic target engagement biomarkers were evaluated. This phase 2a, randomized, double-blind, placebo-controlled, biomarker-end-point clinical trial was conducted in four US centres (ClinicalTrials.gov NCT05163886). Participants with C9orf72 repeat expansions were randomly assigned (2:1) to receive twice-daily oral treatment with 125 mg apilimod dimesylate capsules or matching placebo for 12 weeks, followed by a 12-week open-label extension. Safety was measured as the occurrence of treatment-emergent or serious adverse events attributable to the study drug and tolerability at trial completion or treatment over 12 weeks. Changes from baseline in plasma and CSF and concentrations of apilimod dimesylate and its active metabolites and of pharmacodynamic biomarkers of PIKfyve inhibition [soluble glycoprotein nonmetastatic melanoma protein B (sGPNMB) upregulation] and disease-specific CNS target engagement [poly(GP)] were measured. Between 16 December 2021 and 7 July 2022, 15 eligible participants were enrolled. There were no drug-related serious adverse events reported in the trial. Fourteen (93%) participants completed the double-blind period with 99% dose compliance [ n = 9 (90%) apilimod dimesylate; n = 5 (100%) placebo]. At Week 12, apilimod dimesylate was measurable in CSF at 1.63 ng/ml [standard deviation (SD): 0.937]. At Week 12, apilimod dimesylate increased plasma sGPNMB by >2.5-fold (P < 0.001), indicating PIKfyve inhibition, and lowered CSF poly(GP) protein levels by 73% (P < 0.001), indicating CNS tissue-level proof of mechanism. Apilimod dimesylate met prespecified key safety and biomarker end-points in this phase 2a trial and demonstrated CNS penetrance and pharmacodynamic target engagement. Apilimod dimesylate was observed to result in the greatest reduction in CSF poly(GP) levels observed to date in C9orf72 clinical trials. [ABSTRACT FROM AUTHOR]

Objectives To determine the role of keratin 17 (K17) as a predictive biomarker for response to chemotherapy by defining thresholds of K17 expression based on immunohistochemical tests that could be used to optimize therapeutic intervention for patients with pancreatic ductal adenocarcinoma (PDAC). Methods We profiled K17 expression, a hallmark of the basal molecular subtype of PDAC, by immunohistochemistry in 2 cohorts of formalin-fixed, paraffin-embedded PDACs (n = 305). We determined a K17 threshold of expression to optimize prognostic stratification according to the lowest Akaike information criterion and explored the potential relationship between K17 and chemoresistance by multivariate predictive analyses. Results Patients with advanced-stage, low K17 PDACs treated using 5-fluorouracil (5-FU)–based chemotherapeutic regimens had 3-fold longer survival than corresponding cases treated with gemcitabine-based chemotherapy. By contrast, PDACs with high K17 did not respond to either regimen. The predictive value of K17 was independent of tumor mutation status and other clinicopathologic variables. Conclusions The detection of K17 in 10% or greater of PDAC cells identified patients with shortest survival. Among patients with low K17 PDACs, 5-FU–based treatment was more likely than gemcitabine-based therapies to extend survival. [ABSTRACT FROM AUTHOR]

Purpose: Biomarkers are substances measured at the systemic level to evaluate organic responses in certain situations, establishing diagnoses, disease staging, and prognosis. Blood glucose is a biomarker recognized as a predictor of prognosis in children victims of traumatic brain injury (TBI). The scope of this study was to identify the accuracy of blood glucose as a biomarker of severe brain injury. Methods: A retrospective analytical study was conducted through the consecutive review of medical records of children and teenage victims of TBI who underwent neurological surgery between 2016 and 2023 in a level 1 trauma center. Two groups were compared: children with Glasgow Coma Scale (GCS) score ≤ 8 and children with GCS > 8. We calculated the predictive values to define the accuracy of blood glucose as a biomarker of brain injury. Results: Ninety-two medical records were included for analysis. Hyperglycemia predominated in cases with GCS ≤ 8 (48% vs 3%; p < 0.0001; OR, 30; 95% CI, 5.9902–150.2448). The glycemic measurement considering the cutoff point of 200 mg/dL or 11.1 mmol/L showed a specificity of 97%, a positive predictive value of 86%, an accuracy of 84%, and a likelihood ratio for a positive test of 16. Conclusion: Victims with GCS ≤ 8 are 16 times more likely to develop acute hyperglycemia after TBI when compared to those with GCS > 8. Blood glucose is a biomarker with an accuracy of 84% to predict severe brain injury, considering the cutoff point of 200 mg/dL or 11.1 mmol/L. [ABSTRACT FROM AUTHOR]

Background: Understanding the potential risk factors of heart diseases is key to effectively managing cardiac diseases. The present study quantifies the association of identified risk factors. In addition, the study has compared the association of mortality with hypertension, uncontrolled diabetes, and uncontrolled hyperlipidemia using Grey Relational Approach (GRA) for stroke, lung diseases, smoking, stress, obesity, and lack of exercise. Method: Data on risk factors of heart failure were collected from the Global Burden of Disease (GBD) study (2001–2017). From the GBD database, variables have selected the top leading risk factors responsible for mortality from cardiac diseases. Data on risk factors was analyzed using the GRA procedure (utilizing Grey [8.0] software). In the GRA method, the correlation was categorized into three components: GRA – Deng (assesses the effect of one variable specified by data on the other variables), GRA- absolute (assesses the association between variables measured), and GRA-SS (assessed the overall association between the variables measured). Stroke, lung diseases, smoking, stress, obesity, and lack of exercise were taken as dependent variables and their impact was assessed. Hypertension (high grade) uncontrolled diabetes, and uncontrolled hyperlipidemia were considered as independent variables. The relationship between dependent and independent variables was assessed. Results: Overall correlational analysis showed that type 2 diabetes (T2DM) is the risk factor that has a strong relationship with causing heart failure and thereby increases morbidity and mortality among Chinese patients. After T2DM, the second highest risk factor associated was severe dyslipidemia which is responsible for causing heart failure. High-grade hypertension is one-third most common risk factor in causing heart failure. GRA – Deng analysis showed that T2DM is the top risk factor associated with heart failure, followed by high-grade hypertension and severe dyslipidemia (uncontrolled). GRA-absolute analysis showed that severe dyslipidemia is the top risk factor associated with heart failure, followed by high-grade hypertension and T2DM (uncontrolled). GRA-SS analysis showed that high-grade hypertension is the top risk factor associated with heart failure, followed by severe dyslipidemia and T2DM (uncontrolled). Conclusions: The study reported that T2DM, severe dyslipidemia, and high-grade hypertension as strongly correlated with the development of heart failure after considering other several key risk factors (stroke, lung diseases, smoking, stress, obesity, and lack of exercise). Level of evidence: IV. Technical efficacy: Stage 5. [ABSTRACT FROM AUTHOR]

This editorial published in the journal Frontiers in Endocrinology discusses the advancements in thyroid cancer research, specifically focusing on molecular characterization and prediction models for recurrence. The article emphasizes the importance of accurate molecular and genetic characterization to differentiate between less aggressive and more aggressive thyroid tumors. It also explores the use of biomarkers and prediction models to improve the diagnosis and management of thyroid nodules. The document provides a summary of three studies related to thyroid cancer research, which identify genes associated with recurrence, analyze the genetic landscape of thyroid cancer in Chinese patients, and investigate the shared molecular mechanisms between thyroid cancer and Hashimoto's thyroiditis. These studies contribute to our understanding of thyroid cancer and may lead to personalized treatment options. [Extracted from the article]

Cognitive frailty (CF) is a heterogeneous syndrome that is becoming one of the most serious health problems as the world's population age is increasing. Elucidating its biological mechanisms as well as prevention and treatments is becoming increasingly significant, particularly in view of the associated health costs. We presented the study protocol of a research project funded by the Italian Ministry of Health (grant number RF-2016-02363298) aiming to investigate the cognitive and neuropsychological effects of a 5-week treatment with therapy based on the regenerative properties of ozone (O3) in a cohort of subjects stratified according to CF scores. We also studied the potential effects of O3 on blood-based biomarkers indicative of specific biological systems that may be altered in CF. Seventy-five older persons were recruited and randomly assigned to receive the active treatment (150 cc of oxygen-O2-O3 mixture at the concentration of 30 µg of O3 per cc of O2), O2, or the placebo (air) for 5 weeks. The main endpoints were the change in the scores of clinical scales from baseline (T0) to weeks 3 (T3), 9 (T9), and 15 (T15) after treatment and the change in biomarker levels resulting from transcriptomics, proteomics, and metabolomic patterns at the same times. The positive results from this study could have important clinical implications. [ABSTRACT FROM AUTHOR]

Objective: In this review, the authors update the 2018 position statement of the American Psychiatric Association Council of Research Workgroup on Biomarkers and Novel Treatments on pharmacogenomic (PGx) tools for treatment selection in depression. Methods: The literature was reviewed for new clinical trials and meta-analyses, published from 2017 to 2022, of studies using PGx tools for treatment selection in depression. The blinding and control conditions, as well as primary and secondary outcomes and post hoc analyses, were summarized. Results: Eleven new clinical trials and five meta-analyses were identified; all studies had primary outcome measures related to speed or efficacy of treatment response. Three trials (27%) demonstrated efficacy on the primary outcome measure with statistical significance; the three studies used different PGx tools; one study was open-label and the other two were small single-blind trials. Five trials (45%) did not detect efficacy with statistical significance on either primary or secondary outcome measures. Only one trial (9%) used adverse events as a primary outcome measure. All studies had significant limitations; for example, none adopted a fully blinded study design, only two studies attempted to blind the treating clinician, and none incorporated measures to estimate the effectiveness of the blinds or the influence of lack of blinding on the study results. Conclusions: The addition of these new data do not alter the recommendations of the 2018 report, or the advice of the U.S. Food and Drug Administration, that the evidence does not support the use of currently available combinatorial PGx tools for treatment selection in major depressive disorder. Priority efforts for future studies and the development and testing of effective tools include fully blinded study designs, inclusion of promising genetic variants not currently included in any commercially available tests, and investigation of other uses of pharmacogenomics, such as estimating the likelihood of rare adverse drug effects, rather than increasing the speed or magnitude of drug response. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. METHODS: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. RESULTS: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values

Abstract Background Understanding the potential risk factors of heart diseases is key to effectively managing cardiac diseases. The present study quantifies the association of identified risk factors. In addition, the study has compared the association of mortality with hypertension, uncontrolled diabetes, and uncontrolled hyperlipidemia using Grey Relational Approach (GRA) for stroke, lung diseases, smoking, stress, obesity, and lack of exercise. Method Data on risk factors of heart failure were collected from the Global Burden of Disease (GBD) study (2001–2017). From the GBD database, variables have selected the top leading risk factors responsible for mortality from cardiac diseases. Data on risk factors was analyzed using the GRA procedure (utilizing Grey [8.0] software). In the GRA method, the correlation was categorized into three components: GRA – Deng (assesses the effect of one variable specified by data on the other variables), GRA- absolute (assesses the association between variables measured), and GRA-SS (assessed the overall association between the variables measured). Stroke, lung diseases, smoking, stress, obesity, and lack of exercise were taken as dependent variables and their impact was assessed. Hypertension (high grade) uncontrolled diabetes, and uncontrolled hyperlipidemia were considered as independent variables. The relationship between dependent and independent variables was assessed. Results Overall correlational analysis showed that type 2 diabetes (T2DM) is the risk factor that has a strong relationship with causing heart failure and thereby increases morbidity and mortality among Chinese patients. After T2DM, the second highest risk factor associated was severe dyslipidemia which is responsible for causing heart failure. High-grade hypertension is one-third most common risk factor in causing heart failure. GRA – Deng analysis showed that T2DM is the top risk factor associated with heart failure, followed by high-grade hypertension and severe dyslipidemia (uncontrolled). GRA-absolute analysis showed that severe dyslipidemia is the top risk factor associated with heart failure, followed by high-grade hypertension and T2DM (uncontrolled). GRA-SS analysis showed that high-grade hypertension is the top risk factor associated with heart failure, followed by severe dyslipidemia and T2DM (uncontrolled). Conclusions The study reported that T2DM, severe dyslipidemia, and high-grade hypertension as strongly correlated with the development of heart failure after considering other several key risk factors (stroke, lung diseases, smoking, stress, obesity, and lack of exercise). Level of evidence IV. Technical efficacy Stage 5.

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Chronic heart failure (CHF) is a global medical, social, and economic problem. It is a syndrome caused by imbalanced neurohumoral regulation of the cardiovascular system, which is accompanied by impaired systolic and/or diastolic function of the heart. Currently, the search and study of new biological markers that can help in the early diagnosis of CHF, serve as a laboratory tool for assessing treatment effectiveness, or be used as prognostic markers and risk stratification criteria are ongoing. Researchers focused on studying the role of Klotho protein, fibroblast growth factor 23 (FGF23), and sclerostin in patients with CHF. Klotho expression decreases as the body ages, and impaired production has been reported in various aging-related diseases. The FGF23 / Klotho axis plays a key regulatory role in cardiovascular pathology. Laboratory, clinical, and genetic studies have suggested that sclerostin is associated with heart disease, although available data are not entirely consistent. Clinical work conducted on the study of the Klotho protein, FGF-23, and sclerostin indicates the potentially important diagnostic and prognostic significance of their analysis in patients with CHF. Thus, more studies of the issues related to serial testing of these biological markers, including in the aspect of the multibiomarker model, are needed.

The pathogenesis of multiple sclerosis (MS) is not completely understood, but genetic factors, autoimmunity, inflammation, demyelination, and neurodegeneration seem to play a significant role. Data from analyses of central nervous system autopsy material from patients diagnosed with multiple sclerosis, as well as from studies in the main experimental model of multiple sclerosis, experimental autoimmune encephalomyelitis (EAE), suggest the possibility of a role of oxidative stress as well. In this narrative review, we summarize the main data from studies reported on oxidative stress markers in patients diagnosed with MS and in experimental models of MS (mainly EAE), and case–control association studies on the possible association of candidate genes related to oxidative stress with risk for MS. Most studies have shown an increase in markers of oxidative stress, a decrease in antioxidant substances, or both, with cerebrospinal fluid and serum/plasma malonyl-dialdehyde being the most reliable markers. This topic requires further prospective, multicenter studies with a long-term follow-up period involving a large number of patients with MS and controls. [ABSTRACT FROM AUTHOR]

Background Lynch syndrome is a hereditary cancer predisposition syndrome caused by germline mutations in DNA mismatch repair genes, which lead to high microsatellite instability and frameshift mutations at coding mononucleotide repeats in the genome. Recurrent frameshift mutations in these regions are thought to play a central role in the increased risk of various cancers, but no biomarkers are currently available for the surveillance of high microsatellite instability-associated cancers. Methods A frameshift mutation-based biomarker panel was developed and validated by targeted next-generation sequencing of supernatant DNA from cultured high microsatellite instability colorectal cancer cells. This panel supported selection of 122 frameshift mutation targets as potential biomarkers. This biomarker panel was then tested using matched tumor, adjacent normal tissue, and buffy coat samples (53 samples) and blood-derived cell-free DNA (cfDNA) (38 samples) obtained from 45 high microsatellite instability and mismatch repair-deficient patients. We also sequenced cfDNA from 84 healthy participants to assess background noise. Results Recurrent frameshift mutations at coding mononucleotide repeats were detectable not only in tumors but also in cfDNA from high microsatellite instability and mismatch repair-deficient patients, including a Lynch syndrome carrier, with a varying range of target detection (up to 85.2%), whereas they were virtually undetectable in healthy participants. Receiver operating characteristic curve analysis showed high sensitivity and specificity (area under the curve = 0.94) of the investigated panel. Conclusions We demonstrated that frameshift mutations can be detected in cfDNA from high microsatellite instability and mismatch repair-deficient patients and asymptomatic carriers. The 122-target frameshift mutation panel described here has promise as a tool for improved surveillance of high microsatellite instability and mismatch repair-deficient patients, with the potential to reduce the frequency of invasive screening methods for this high-cancer-risk cohort. [ABSTRACT FROM AUTHOR]

Introduction The prevalence of waterpipe tobacco smoking is increasing globally. Biomarkers of waterpipe tobacco smoke (WTS) exposure are less studied. Aims and Methods To identify the types of biomarkers of WTS exposure and estimate changes in biomarker concentrations pre- to post-WTS exposure. PubMed, Embase, Web of Science, CINAHL Plus, PsycINFO, and Cochrane Library were searched for studies up to April 24, 2023. The types of biomarkers were identified. Random-effects models were used to estimate changes in biomarker concentrations pre- to post-WTS exposure. Results Seventy-three studies involving 3755 participants exposed to WTS (49% male, mean age: 24.8 years) and 11 types of biomarkers of WTS exposure were identified. The biomarkers included tobacco alkaloids, expired carbon monoxide (eCO), carboxyhemoglobin (COHb), tobacco-specific nitrosamines, volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), heavy metals, unmetabolized VOCs, unmetabolized PAHs, furan metabolites, and heterocyclic aromatic amines. Compared with pre-WTS exposure, eCO (breath; mean difference [MD] 27.00 ppm; 95% confidence interval [CI]: 20.91 to 33.08), COHb (blood; MD 4.30%; 95%CI: 2.57 to 6.03), COHb (breath; MD 7.14%; 95%CI: 4.96 to 9.31), nicotine (blood; MD 8.23 ng/mL; 95%CI: 6.27 to 10.19), and cotinine (urine; MD 110.40 ng/mL; 95%CI: 46.26 to 174.54) significantly increased post-WTS exposure. Conclusions Biomarkers of WTS exposure were systematically identified. The similarity between the biomarkers of WTS exposure and those of cigarette smoke and higher concentrations of some biomarkers post-WTS exposure underscore the need for further research on applying biomarkers in surveillance, interventions, and regulations to mitigate the harms of waterpipe tobacco smoking. Implications This study provides the first comprehensive overview of biomarkers investigated and available for assessing WTS exposure and their concentration changes in the human body. Researchers can use biomarkers such as eCO, COHb, nicotine, and cotinine to measure the health risks associated with WTS exposure and objectively evaluate the effectiveness of public health interventions aimed at reducing waterpipe tobacco smoking. Public health policymaking can also be informed through increased biomarker concentrations following WTS exposure, to implement regulations and public health education campaigns on limiting or preventing waterpipe tobacco smoking. [ABSTRACT FROM AUTHOR]

Introduction To improve the feasibility of remote biochemical verification of smoking status, our team developed "COast," a mobile app integrated with REDCap that allows a research participant to complete self-report research assessments and provide a breath sample via the iCOQuit Smokerlyzer for the purposes of carbon monoxide (CO) testing. The aims of the present study were to examine (1) the validity of remote CO data capture using COast as compared to gold-standard approaches (salivary cotinine, stand-alone CO monitor) and (2) the feasibility of remote CO data capture using COast as applied to both daily and weekly CO collection schedules. Methods Participants (N  = 143, 59% Female), including recently quit (n  = 36) and current (n  = 107) smokers, completed a baseline video session to capture validity data, and then were randomized to daily or weekly CO monitoring for a period of 1 month. Results Balancing both sensitivity and specificity, optimal cut-points for defining abstinence using the COast system were <4 parts per million (ppm) with salivary cotinine as the referent (Sensitivity = 100%, Specificity = 92.8%) and <8 ppm with the stand-alone CO monitor as the referent (Sensitivity = 100%, Specificity = 88.9%). Compliance across groups with CO monitoring was high with average compliance of 74% for the daily group and 84% for the weekly group. Self-reported feasibility and acceptability of using the system were strong. Conclusions Pairing the iCOQuit with REDCap via the COast app was both valid and feasible among a sample of adults who smoke cigarettes enrolled remotely. This integration may help to improve the rigor of decentralized smoking cessation trials. Implications With increasing prevalence of decentralized trial designs, innovative methods are needed to remotely capture biomarkers. Methods that leverage existing widely available research data capture platforms may be particularly useful for promoting adoption. The COast app, which integrates a Bluetooth-enabled CO monitor with REDCap, is a fitting, valid, and feasible solution to remotely biochemically verify smoking status. [ABSTRACT FROM AUTHOR]

Objective: Sepsis often prompts clinicians to start empirical antibiotics in suspected neonates while awaiting diagnosis. The next-generation testing with point-of-care (POC) techniques offers a lead-time advantage that could bridge the gap by providing a timely diagnosis. Materials and Methods: We conducted a prospective diagnostic study in 82 neonates enrolled between May and October 2022 in a level III neonatal intensive care unit. All neonates with a new episode of clinically suspected sepsis were included. Diagnostic accuracy of POC testing of C-reactive protein (CRP), interleukin-6 (IL-6), and procalcitonin (PCT) with standard laboratory methods was performed. Results: The mean gestation age and birth weight of the neonates were 33.17 ± 4.25 weeks and 1,695.4 ± 700.74 grams, respectively. Most neonates were preterm (75%) with nearly equal proportions of early (51.22%) and late-onset (48.78%) sepsis. The POC CRP correlated well with standard CRP (r = 0.8001, 95% CI: 0.706–0.867, p < 0.0001). Among the three biomarkers, CRP had the maximum diagnostic accuracy (area under the curve [AUC] – 0.73) followed by PCT (AUC – 0.65) and IL-6 (0.55). There was no significant difference in the diagnostic accuracy of CRP (p = 0.46), PCT (p = 0.29), and IL-6 (p = 0.60) in early- and late-onset sepsis. The mean time for POC estimation of IL-6, PCT, and CRP was 12 ± 3 min which was significantly less compared to 366 ± 61 min for standard techniques (p < 0.001). Conclusion: POC CRP correlates well with standard techniques of estimation, and CRP alone and in combination with PCT has good diagnostic accuracy in neonatal sepsis. Highlights of the Study: Point-of-care (POC) C-reactive protein (CRP) levels correlate well with standard laboratory estimation. CRP alone and in combination with procalcitonin (PCT) has maximum diagnostic accuracy in neonatal sepsis. POC testing can be used in both early- and late-onset sepsis with similar diagnostic accuracy. The mean time required for POC estimation of interleukin-6, PCT, and CRP is nearly 12 min which is significantly less than standard techniques. [ABSTRACT FROM AUTHOR]

Introduction Traumatic brain injury (TBI) is a leading cause of morbidity and mortality in both adult civilian and military populations. Currently, diagnostic and prognostic methods are limited to imaging and clinical findings. Biomarker measurements offer a potential method to assess head injuries and help predict outcomes, which has a potential benefit to the military, particularly in the deployed setting where imaging modalities are limited. We determine how biomarkers such as ubiquitin C-terminal hydrolase-L1 (UCH-L1), glial fibrillary acidic protein (GFAP), S100B, neurofilament light chain (NFL), and tau proteins can offer important information to guide the diagnosis, acute management, and prognosis of TBI, specifically in military personnel. Materials and Methods We performed a narrative review of peer-reviewed literature using online databases of Google Scholar and PubMed. We included articles published between 1988 and 2022. Results We screened a total of 73 sources finding a total of 39 original research studies that met inclusion for this review. We found five studies that focused on GFAP, four studies that focused on UCH-L1, eight studies that focused on tau proteins, six studies that focused on NFL, and eight studies that focused on S100B. The remainder of the studies included more than one of the biomarkers of interest. Conclusions TBI occurs frequently in the military and civilian settings with limited methods to diagnose and prognosticate outcomes. We highlighted several promising biomarkers for these purposes including S100B, UCH-L1, NFL, GFAP, and tau proteins. S100B and UCH-L1 appear to have the strongest data to date, but further research is necessary. The robust data that explain the optimal timing and, more importantly, trending of these biomarker measurements are necessary before widespread application. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors (ICIs) have become prominent therapies for gastrointestinal cancer (GC). However, it is urgent to screen patients who can benefit from ICIs. Protein patched homolog 1 (PTCH1) is a frequently altered gene in GC. We attempt to explore the association between PTCH1 mutation and immunotherapy efficacy. The Memorial Sloan Kettering Cancer Center (MSKCC) cohort (n  = 236) with GC (esophageal, gastric and colorectal cancers) patients receiving ICIs was used for discovery and the Peking University Cancer Hospital (PUCH) GC cohort (n  = 92) was used for validation. Overall survival (OS) and tumor mutational burden (TMB) of the PTCH1 mutant-type (PTCH1 -MUT) and PTCH1 wild-type (PTCH1 -WT) groups were compared. Furthermore, GC data were collected from The Cancer Genome Atlas to assess the potential mechanisms. In the MSKCC cohort, PTCH1 -MUT group showed significantly better OS (P  = 0.017) and higher TMB. Multivariate analysis showed that PTCH1 mutation was associated with better OS. In the PUCH cohort, PTCH1 -MUT group showed significantly longer OS (P  = 0.036) and progression-free survival, and higher durable clinical benefit and TMB. Immune cell infiltration analysis revealed that PTCH1 -MUT group had significantly higher distributions of CD8 T cells, CD4 T cells, NK cells, mast cells and M1 cells. The PTCH1- MUT group showed significantly higher expression of most immune-related genes. Gene set enrichment analysis showed that the PTCH1- MUT group had enriched INF-γ response, INF-α response, glycolysis and reactive oxygen species pathway gene sets. PTCH1 mutation may represent a potential biomarker for predicting ICIs response in GC. Nevertheless, prospective cohort studies should be performed to further validate our results. [ABSTRACT FROM AUTHOR]

Objectives Detecting occult cancer in patients with unprovoked venous thromboembolism (VTE) remains a significant challenge. Our objective was to investigate the potential predictive role of coagulation-related biomarkers in the diagnosis of occult malignancies. Methods We conducted a nested case-control study with a 1-year prospective cohort of 214 patients with unprovoked VTE, with a focus on identifying occult cancer. At the time of VTE diagnosis, we measured various biomarkers, including soluble P-selectin (sP-selectin), dimerized plasmin fragment D (D-dimer), platelets, leukocytes, hemoglobin, total extracellular vesicles (EVs), EVs expressing tissue factor on their surface (TF+EVs), and EVs expressing P-selectin on their surface (Psel+EVs) in all participants. Results We observed statistically significant increased levels of sP-selectin (P =.015) in patients with occult cancer. Despite an increase in Psel+EVs, TF+EVs, D-dimer, and platelets within this group, however, no significant differences were found. When sP-selectin exceeded 62 ng/mL and D-dimer surpassed 10,000 µg/L, the diagnosis of occult cancer demonstrated a specificity of up to 91% (95% CI, 79.9%-96.7%). Conclusions The combination of sP-selectin and D-dimer can be a valuable biomarker in detecting occult cancer in patients with unprovoked VTE. Further research is necessary to ascertain whether easily measurable biomarkers such as sP-selectin and D-dimer can effectively distinguish between patients who have VTE with and without hidden malignancies. [ABSTRACT FROM AUTHOR]

Glial fibrillary acidic protein (GFAP), a proxy of astrocyte reactivity, has been proposed as biomarker of Alzheimer's disease. However, there is limited information about the correlation between blood biomarkers and post-mortem neuropathology. In a single-centre prospective clinicopathological cohort of 139 dementia patients, for which the time-frame between GFAP level determination and neuropathological assessment was exceptionally short (on average 139 days), we analysed this biomarker, measured at three time points, in relation to proxies of disease progression such as cognitive decline and brain weight. Most importantly, we investigated the use of blood GFAP to detect the neuropathological hallmarks of Alzheimer's disease, while accounting for potential influences of the most frequent brain co-pathologies. The main findings demonstrated an association between serum GFAP level and post-mortem tau pathology (β = 12.85; P < 0.001) that was independent of amyloid deposits (β = 13.23; P = 0.02). A mediation analysis provided additional support for the role of astrocytic activation as a link between amyloid and tau pathology in Alzheimer's disease. Furthermore, a negative correlation was observed between pre-mortem serum GFAP and brain weight at post-mortem (r = −0.35; P < 0.001). This finding, together with evidence of a negative correlation with cognitive assessments (r = −0.27; P = 0.005), supports the role of GFAP as a biomarker for disease monitoring, even in the late phases of Alzheimer's disease. Moreover, the diagnostic performance of GFAP in advanced dementia patients was explored, and its discriminative power (area under the receiver operator characteristic curve at baseline = 0.91) in differentiating neuropathologically-confirmed Alzheimer's disease dementias from non-Alzheimer's disease dementias was determined, despite the challenging scenario of advanced age and frequent co-pathologies in these patients. Independently of Alzheimer's disease, serum GFAP levels were shown to be associated with two other pathologies targeting the temporal lobes—hippocampal sclerosis (β = 3.64; P = 0.03) and argyrophilic grain disease (β = −6.11; P = 0.02). Finally, serum GFAP levels were revealed to be correlated with astrocyte reactivity, using the brain GFAP-immunostained area as a proxy (ρ = 0.21; P = 0.02). Our results contribute to increasing evidence suggesting a role for blood GFAP as an Alzheimer's disease biomarker, and the findings offer mechanistic insights into the relationship between blood GFAP and Alzheimer's disease neuropathology, highlighting its ties with tau burden. Moreover, the data highlighting an independent association between serum GFAP levels and other neuropathological lesions provide information for clinicians to consider when interpreting test results. The longitudinal design and correlation with post-mortem data reinforce the robustness of our findings. However, studies correlating blood biomarkers and neuropathological assessments are still scant, and further research is needed to replicate and validate these results in diverse populations. [ABSTRACT FROM AUTHOR]

Background Emerging evidence suggests health-promoting properties of increased protein intake. There is increased interest in plant protein but a dearth of information in relation to its impact on muscle function. The objective of the present work was to examine the impact of intake of different types of proteins on muscle functional parameters including handgrip strength, biomarkers of metabolic health, sleep quality and quality of life in a group of older adults. Methods Healthy men and women aged 50 years and older entered a double-blinded, randomised, controlled nutritional intervention study with three parallel arms: high plant protein, high dairy protein and low protein. Participants consumed once daily a ready-to-mix shake (containing 20 g of protein in high protein groups) for 12 weeks. Changes in handgrip and leg strength, body composition, metabolic health, quality of life and sleep quality were analysed by linear mixed models in an intention-to-treat approach. Results Eligible participants (n  = 171) were randomly assigned to the groups (plant: n  = 60, dairy: n  = 56, low protein: n  = 55) and 141 completed the study. Handgrip strength increased after the intervention (P time = 0.038), with no significant difference between the groups. There was no significant difference between groups for any other health outcomes. Conclusions In a population of older adults, increasing protein intake by 20 g daily for 12 weeks (whether plant-based or dairy-based) did not result in significant differences in muscle function, body composition, metabolic health, sleep quality or quality of life, compared with the low protein group. [ABSTRACT FROM AUTHOR]

Background A number of biomarkers denoting various pathophysiological pathways have been implicated in the aetiology and risk of age-related diseases. Hence, the combined impact of multiple biomarkers in relation to ageing free of major chronic diseases, such as cancer, cardiovascular disease and type 2 diabetes, has not been sufficiently explored. Methods We measured concentrations of 13 biomarkers in a random subcohort of 2,500 participants in the European Prospective Investigation into Cancer and Nutrition Potsdam study. Chronic disease-free ageing was defined as reaching the age of 70 years within study follow-up without major chronic diseases, including cardiovascular disease, type 2 diabetes or cancer. Using a novel machine-learning technique, we aimed to identify biomarker clusters and explore their association with chronic disease-free ageing in multivariable-adjusted logistic regression analysis taking socio-demographic, lifestyle and anthropometric factors into account. Results Of the participants who reached the age of 70 years, 321 met our criteria for chronic-disease free ageing. Machine learning analysis identified three distinct biomarker clusters, among which a signature characterised by high concentrations of high-density lipoprotein cholesterol, adiponectin and insulin-like growth factor-binding protein 2 and low concentrations of triglycerides was associated with highest odds for ageing free of major chronic diseases. After multivariable adjustment, the association was attenuated by socio-demographic, lifestyle and adiposity indicators, pointing to the relative importance of these factors as determinants of healthy ageing. Conclusion These data underline the importance of exploring combinations of biomarkers rather than single molecules in understanding complex biological pathways underpinning healthy ageing. [ABSTRACT FROM AUTHOR]

Background Increasing mortality and morbidity of coronary artery disease (CAD) highlight the emerging need for novel noninvasive markers such as circulating microRNAs (miRNAs). Objective To evaluate the circulating levels of miR-126-3p, miR-210-3p, let-7g-5p, and miR-326, and their associations with known contributors to CAD, in CAD subgroups. Methods We divided the cohort into 4 groups: non-CAD controls (≤30% stenosis; n = 55), and patients with stable angina pectoris (SAP; n = 48), unstable AP (UAP; n = 46), and myocardial infarction (MI; n = 36). The circulating levels of miR-126-3p, miR-210-3p, let-7g-5p, and miR-326 were determined using TaqMan Advanced miRNA Assays in serum specimens. Results Circulating miR-126-3p levels were lower in the MI and UAP groups, compared with the non-CAD group, whereas miR-210-3p circulating levels were lower in the MI group than others. The levels of circulating let-7g-5p were shown to be useful for distinguishing UAP from MI, and there were substantial differences in circulating let-7g-5p levels between the UAP and MI groups. Moreover, lipid levels and ratios were lower in individuals with high circulating miR-126-3p and miR-210-3p levels. Conclusions The study results suggest that circulating miR-126-3p, miR-210-3p, and let-7g-5p are differentiated between different clinical presentations of CAD and associated with lipid levels, which are important risk factors and determinants of CAD. [ABSTRACT FROM AUTHOR]

Objective For over 60 years there has been conjecture about the identity of an Ehrlich's test positive pyrrole (Mauve Factor) reputed to be a biomarker for psychological disorders, including anxiety. We reviewed studies that attempt to identify Mauve Factor and subjected authentic standards of the 2 main candidates, kryptopyrrole and hydroxypyrrole, to the Ehrlich's reaction. Methods Modified Ehrlich's test for kryptopyrrole and hydroxypyrrole were applied to urine samples from 10 volunteers, anxious and nonanxious. Results Based on the mechanistic chemistry of Ehrlich's reaction and reactions of the 2 compounds, Mauve Factor cannot be hydroxypyrrole. Analyses of urine samples from volunteers, identified by the Generalized Anxiety Disorder - 7 item scale (GAD-7 ≥10; n = 5) and control urine samples (GAD-7 <10; n = 5) using a kryptopyrrole calibration graph, show that concentrations are similar in both groups. Conclusion Kryptopyrrole may be the elusive Mauve Factor. Its possible origin from stercobilin via gut microbiome–mediated metabolism, its link to gut-mediated neurological effects via γ-aminobutyric acid (GABA) receptors, and its predicted interaction with Zn2+ and consequent impact on zinc homeostasis are discussed. The GAD-7 scale does not differentiate between state and trait anxiety and as such, the minimal difference in pyrrole levels between volunteer groups requires further study. [ABSTRACT FROM AUTHOR]

Objective To evaluate the associations between analytical methods, such as microarray and enzyme-linked immunosorbent assay (ELISA); expedient cutoffs; and the lowest possible number of microarrays in analysis for target biomarker estimation in case-control studies. Methods This study included 321 serum specimens, gathered in different case-control studies to test for atherosclerosis and atrial fibrillation. Among them, 48 serum specimens were analyzed using microarray technology. We used ELISA and commercial kits for confirmation of the results. Results Three proteins—cadherin-P, neuronal nitric oxide synthase, and adenovirus fiber—were shown to have distinctly different values in the case group vs the control group. As a result, we used those proteins as the target for confirmation using our alternative analytical method. Also, these protein values represented the limiting range between the highest and lowest differences in case-control groups. The results of microarray assay were confirmed using ELISA and commercial kits in the same specimens, in which microarray profiling was performed, and also in separate large case-control groups. Conclusions A 1.5-fold difference in the protein content, as measured using microarray technology, was shown to be sufficient for further investigation of the candidate proteins. As few as 3 microarrays were considered sufficient for perspective evaluation of the target proteins. Microarray serum profiling, therefore, provides semiquantitative determination of protein in serum. [ABSTRACT FROM AUTHOR]

The advent of structural magnetic resonance imaging (sMRI) at the end of the 20th century opened the way toward a deeper understanding of the neurophysiology of psychiatric disorders, substantiating regional structural abnormalities underlying this group of clinical conditions. However, despite abundant and flourishing scientific research, sMRI methodologies are not currently integrated into daily diagnostic practice. One reason behind this failed translation may be the prevailing approach to logical reasoning in neuroimaging: The forward inference via frequentist-based statistics. This reasoning prevents clinicians from obtaining information about the selectivity of results, which are therefore of limited use regarding the definition of biomarkers and refinement of diagnostic processes. Recently, another type of inferential approach has started to emerge in the neuroimaging field: The reverse inference via Bayesian statistics. Here, we introduce the key concepts of this approach, with a particular emphasis on the clinical sMRI environment. We survey recent findings showing significant potential for clinical translation. Clinical opportunities and challenges for developing reverse inference-based neural markers for psychiatry are also discussed. We propose that a systematic sharing of imaging data across the human brain mapping community is an essential first step toward a paradigmatic clinical shift. We conclude that a defined synergy between forward-based and reverse-based sMRI research can illuminate current discussions on diagnostic brain markers, offering clarity on key issues and fostering new tailored diagnostic avenues. INSET: c. [ABSTRACT FROM AUTHOR]

Schizophrenia often occurs during youth, and psychosis risk syndrome occurs before the onset of psychosis. The aim of this study was to determine whether the visual event-related potential responses in youths with psychosis risk syndrome were defective in the presence of interference stimuli and associated with their clinical outcomes. A total of 223 participants, including 122 patients with psychosis risk syndrome, 50 patients with emotional disorders, and 51 healthy control subjects, were assessed. Baseline EEG was recorded during the three-stimulus visual oddball task. The event-related potentials induced by square pictures with different colors were measured. Almost all patients with psychosis risk syndrome were followed up for 12 months and were reclassified into three subgroups: conversion, symptomatic, and remission. The differences in baseline event-related potential responses were compared among the clinical outcome subgroups. The average N2 amplitude of the psychosis risk syndrome group was significantly less negative than that in the healthy control group (d=0.53). The baseline average N2 amplitude in the conversion subgroup was significantly less negative than that in the symptomatic (d=0.58) and remission (d=0.50) subgroups and in the healthy control group (d=0.97). The average N2 amplitude did not differ significantly between the symptomatic and remission subgroups (d=0.02). However, it was significantly less negative in the symptomatic and remission subgroups than in the healthy control group (d=0.46 and d=0.38). No statistically significant results were found in the P3 response. Youths with psychosis risk syndrome had significant N2 amplitude defects in attention processing with interference stimuli. N2 amplitude shows potential as a prognostic biomarker of clinical outcome in the psychosis risk syndrome. [ABSTRACT FROM AUTHOR]

Objectives Real-world evidence on exposure to harmful and potentially harmful constituents (HPHCs) and on biological effects in cigarette smokers who switch to electronic nicotine delivery systems (ENDS) can inform the health effects of switching. Aims and Methods This cross-sectional, observational study assessed adults who had smoked ≥10 cigarettes/day for ≥10 years, comparing 124 continuing cigarette smokers (Smokers) to 140 former smokers who switched to JUUL-brand ENDS exclusively for ≥6 months (Switchers). Assessments included biomarkers of exposure (BOEs) to select HPHCs, biomarkers of potential harm (BOPHs) related to smoking-related diseases, psychometric assessments of dependence on cigarettes and ENDS, respectively, and respiratory symptoms. Planned analyses compared geometric means, adjusted for demographic covariates; further analyses adjusted for additional lifestyle and smoking history covariates. Results Nicotine levels were significantly higher in Switchers (median time switched = 3 years), who were unusually heavy users of JUUL. All other BOEs, including NNAL and HPMA3 (primary endpoints), were significantly lower in Switchers than Smokers. Most BOPHs (sICAM-1 [primary], and eg, white blood cell count, MCP1, HbA1c) were significantly lower in Switchers than Smokers; HDL was significantly higher. Switchers reported significantly lower dependence on JUUL than Smokers did on cigarettes, and respiratory symptom scores were significantly lower among Switchers than Smokers. Conclusions Compared to continuing smokers, smokers who switched to JUUL had substantially lower exposures to multiple HPHCs, favorable differences in markers of inflammation, endothelial function, oxidative stress, and cardiovascular risk, and fewer respiratory symptoms. These findings suggest that switching from cigarettes to JUUL likely reduces smokers' health risks. Implications Short-term confinement studies and randomized clinical trials demonstrate that adult smokers who switch completely to ENDS experience substantial reductions in exposure to many smoking-related toxicants. This study extends those findings to longer periods of switching to JUUL-brand ENDS (almost 3 years on average) under naturalistic use conditions in real-world settings and also found that switching to JUUL resulted in favorable differences in BOPHs more proximally related to smoking-induced disease, as well as in respiratory symptoms. Smokers who switch to ENDS reduce their exposure to toxicants, likely reducing their disease risk. [ABSTRACT FROM AUTHOR]

Background The intricate interplay between work-related stress and its physiological impact has drawn extensive research attention. Dehydroepiandrosterone sulphate (DHEA-S) emerges as a potential biomarker reflecting stress-related endocrine changes. Aims This cross-sectional study aimed to examine the association between job demands and DHEA-S levels among healthcare workers. The study also explored potential correlations between DHEA-S levels and psychophysical symptoms commonly linked to work-related stress. Methods A sample of 488 healthcare workers from a local health authority participated. Job demands were measured using the Demands scale of the Health and Safety Management Standards Indicator Tool. DHEA-S levels and symptom prevalence were assessed through serum analysis and questionnaires, respectively. Results Workers exposed to high job demands exhibited significantly lower DHEA-S levels compared to those with low job demands. Psychophysical symptoms, including sleep disorders, depression, and headache, were more prevalent in the high-demands group. DHEA-S levels showed significant negative correlations with the prevalence of all considered symptoms. Conclusions The study shows the inverse relationship between job demands and DHEA-S levels among healthcare workers, indicating that high job demands correlate with reduced DHEA-S secretion and increased symptom prevalence. The findings suggest DHEA-S as a potential biomarker for assessing the physiological consequences of work-related stress. Proactive interventions in managing job demands are crucial for promoting employee well-being and productivity in demanding work environments. By recognizing DHEA-S as a stress biomarker, organizations can effectively address stress-related health risks and implement targeted interventions for enhancing employees' overall health and work performance. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the effect of TFF3 in the pathogenesis of Diabetic Kidney Disease (DKD), and explore the dynamic changes of TFF3 expression pattern in renal injury process. Methods: DKD animal model was established by streptozotocin (STZ) (40 mg/kg/d, ip, for 5 days, consecutively) combined with the high fat diet (HFD) for 12 weeks. While animals were sacrificed at different time stages in DKD process (4 weeks, 8 weeks and 12 weeks, respectively). Results: STZ combined with high-fat diet induced weight gain, increased blood glucose and decreased glucose tolerance in DKD mice. Compared to the control group, the DKD group exhibits extracellular matrix (ECM) accumulation and the renal injury was aggravated in a time-dependent manner. The TFF3 expression level was decreased in kidney, and increased in colon tissue. Conclusion: TFF3 is not only expressed in colon, but also expressed in renal medulla and cortex. TFF3 might be play a pivotal role in renal mucosal repair by gut-kidney crosstalk, and protect renal from high glucose microenvironment damage. [ABSTRACT FROM AUTHOR]

Background: Chronic limb-threatening ischemia (CLTI), the advanced stage of peripheral arterial disease, is diagnosed in the presence of ischemic rest pain, non-healing ulcers, or gangrene. Several studies have demonstrated that inflammation and endothelial dysfunction are some of the main substrates of CLTI. Methods: A narrative review was conducted and reported according to PRISMA guidelines. Three databases were searched—Web of Science, Medline, and EMBASE—for the studies assessing CLTI and the biological markers related to it. Results: We included 22 studies, and all the markers identified (C-reactive protein, D-dimers, fibrinogen, cytokines, IL-6, TNF-α, ICAM-1 (Intracellular Adhesion Molecule-1), VCAM-1 (Vascular Cell Adhesion Molecule-1), neutrophile-to-lymphocytes ratio (NLR), IL-8, Pentraxin-3, neutrophil gelatinase-associated lipocalin (NGAL), calprotectin, E-selectin, P-selectin, neopterin, High-Mobility Group Box-1 protein (HGMB-1), Osteoprotegerin (OPG) and Sortilin) were positively associated with advanced CLTI, with major limb or major cardiovascular events in these patients. Conclusions: All the studied markers had increased values in patients with CLTI, especially when associated with diabetes mellitus, proving a very important association between diabetes and major limb or cardiovascular events in these patients. There is a need for more studies to validate these markers in terms of diagnosis or prognosis in CLTI patients and in trying to find new medical strategies that target inflammation or endothelial dysfunction in these patients. [ABSTRACT FROM AUTHOR]

ObjectiveThe aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials.MethodsA systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included.ResultsA total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis."ConclusionsThere is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

Recently discovered specific markers open up new possibilities for the diagnosis of acute kidney injury (AKI) in burn disease in order to optimize the treatment of such patients. Early diagnosis with the involvement of biomarkers prevents the sudden death of burn patients and allows predicting the course of the pathological condition. There are several characteristics that an “ideal” AKI biomarker should conform to: being non-invasive, locally specific, highly sensitive, being a stable molecule at different temperatures and pH values, having the ability to rapidly increase in response to kidney injury (quantify it), remaining at high levels during the episode and decreasing during the recovery period. There is a difference between the biomarkers that can be freely filtered in the glomerulus, so any increase in their plasma concentration (due to damage to other renal tissues) can lead to a high concentration of indicators in the urine (loss of specificity), and high-molecular-weight markers that are not freely filtered and therefore are more specific when measured in urine. Renal function in burn patients is usually determined by blood and urine tests, as biopsy can cause iatrogenic damage and is not commonly used in this cohort. After the onset of AKI, the level of biomarkers remains elevated for a certain period. None of the described indicators is monospecific for AKI; this makes estimating the time of AKI quite difficult. It has been proven that the combination of three biomarkers at two different time points in adults and the combination of two indicators at two time intervals in children allows to increase the reliability of determining AKI up to 0.78

Background: Trees are one of the appropriate biological indicators in industrial areas and factories, and by monitoring them; it is possible to determine the state of heavy metal contamination of soil resources. This research was carried out with the aim of biological monitoring of heavy metals lead, cadmium, nickel and iron using plant biomarkers of Prosopis juliflora and Phoenix dactylifera in Shadgan Steel Factory. Methods: According to the geographical location of the factory, 4 stations were selected, where 24 soil samples and 72 leaf samples were collected randomly with 3 repetitions, from 4 different geographical directions. In order to investigate the bioaccumulation of metals in tree leaves, the bioaccumulation coefficient was used. Results: The results of analysis of variance (ANOVA) show that there was a significant difference between soil, palm tree and mesquite groups for the concentration of lead, cadmium, nickel and iron metals (P0.05) and this could be due to the accumulation in the lower parts of the plant, hence Phoenix dactylifera tree leaves and Prosopis juliflora is not a suitable biomarker for this metal. Considering that absorption through the soil is low, there is a possibility of pollutants entering through dry atmospheric precipitation. The accumulation potential of lead, cadmium, nickel and iron heavy metals was higher in Phoenix dactylifera tree than in Prosopis juliflora.