Biomarkers Research Articles

The effect of assessor visibility on student stress and anxiety in emergency care simulation assessments

BackgroundSimulation assessment can result in anxiety for students. These assessments involve being observed by assessors, so there is a significant socio-evaluative stress component which may cause greater anxiety if assessors are visible to students during assessments. The aim of this study was to determine the effect of assessor visibility on biological and physiological markers of stress and levels of anxiety experienced by pre-hospital emergency care students in a simulation assessment environment.MethodsA paired comparison, pre-post test research design was used with two conditions; an assessor visible condition with simulation assessors visible to students in the room and an assessor not visible condition with assessors not in the room but connected via video link. With a sample of 29 emergency care students anxiety was measured with the State-Trait Anxiety Inventory and stress was measured with salivary cortisol and heart rate variability (HRV).ResultsDifferences in state anxiety scores, HRV variables and salivary cortisol suggested lower stress and anxiety in the assessor visible group. Only heart rate was significantly different between the groups (p = 0.016), with a higher heart rate in the assessor not visible group.ConclusionsGreater stress and anxiety may be experienced by students during emergency care simulation assessments when assessors are not visible to students.

Impact of soluble BCMA and non–T-cell factors on refractoriness to BCMA targeting T-cell engagers in multiple myeloma

AbstractAdoptive T-cell therapy is a promising therapy for multiple myeloma (MM), but its efficacy hinges on understanding the relevant biologic and predictive markers of response. B-cell maturation antigen (BCMA) is a key target antigen in MM with active development of multiple anti-BCMA T-cell engagers (TCEs) and chimeric antigen receptor T-cell therapies. The regulation of surface BCMA expression by MM cells, which leads to shedding of soluble BCMA (sBCMA), has triggered debate about the significance of sBCMA as a predictive marker and its potential impact on treatment outcomes. To address this, we leveraged whole-genome sequencing and in vitro assays to demonstrate that sBCMA may independently predict primary refractoriness to anti-BCMA therapies. In addition to sBCMA, tumor burden and surface BCMA antigen density collectively influenced the anti-BCMA TCE cytotoxic efficacy. Correlative analyses of 163 patients treated with the anti-BCMA TCE teclistamab validated and further underscored the association between elevated baseline sBCMA (>400 ng/mL) and refractoriness. Importantly, increasing the TCE dose, using TCE against alternative targets (eg, GPRC5D), and gamma secretase inhibitors were able to overcome the high sBCMA levels. These findings highlight the importance of taking into account the baseline sBCMA levels, disease burden, and TCE dose intensity when administering anti-BCMA TCEs, thereby offering critical insights for optimizing therapeutic strategies to overcome specific high-risk features and primary anti-BCMA TCE refractoriness.

Experience with HCV Detection and Molecular Genetic Characterization among Otherwise Healthy Pregnant Women and Their Partners in the Republic of Guinea.

According to recent data, there are currently 170 to 200 million people infected with HCV worldwide, and the number of new cases annually is approximately 40,000. Thus, the overall prevalence of the pathogen in the world is about 1.8-3%. The dynamic monitoring of circulating viral variants in specific groups that reflect the situation in the wider population, including potential pathogen spread, is of high importance for predicting the epidemiologic situation. Pregnant women are such a group. The Republic of Guinea is one of the poorest countries in the world, in which medicine receives little finance from the state. Among other conditions, HCV infection is not monitored in the country. This work used blood plasma from pregnant women living in the Republic of Guinea and their partners (1810 and 481). ELISA diagnostic kits were used to detect serologic markers, and PCR diagnostic kits were used to detect molecular biologic markers. Sanger sequencing, followed by phylogenetic analysis, was used for genotyping. The present study shows that HCV antibodies were detected in 3.2% of the pregnant women examined and in 3.33% of their male partners. HCV RNA was detected in 0.5% of cases in women and in all anti-HCV-positive male partners (3.33%). HCV RNA was more common in the men than in the pregnant women (χ2 = 25.6, df 1, p < 0.0001, RR = 6.69 with 95% CI: 2.97-15.04). The HCV viral load was determined for all the RNA-HCV-positive samples. The HCV viral load exceeded 1000 IU/mL in all nine women and only in two cases in men. The HCV genes NS5A and NS5B and the NS3 gene fragment were sequenced for 11 samples. Subtype 2q was determined for three isolates and 2j for another three isolates. Another five isolates could not be confidently assigned a subtype because different results were obtained with different methods of analyzing the three viral regions. It can be assumed that these isolates belong to new viral subtypes or to recombinant forms between genotype 2 subtypes. No drug resistance mutations were identified, but a large number of natural polymorphisms in the analyzed genomic regions of the HCV isolates were shown. These results may serve as baseline data for the future planning of a nationwide estimate of the prevalence of bloodborne infections among pregnant women.

Association between biological markers and somatic pain

Pain, as one of the major clinical and social problems, still lacks effective objective evaluation indicators. At present, nearly one in five adults suffer from different types and different parts of pain. An important feature of clinical pain is persistent pain, in addition to sensory discrimination processes, it involves a range of brain regions involved in top-down cognitive and emotional processing. However, clinical pain is often affected by multiple factors and is difficult to assess objectively. Recently, blood, urine, cerebrospinal fluid, and biopsy tissue have been identified using novel, sensitive, and specific protein analysis methods in an attempt to detect changes in biological markers associated with different pain types. This paper will summarize the biological markers related to different parts of pain in the latest relevant studies at home and abroad and focus on the application prospect of such biological markers in the diagnosis, treatment, and prognosis evaluation of the pain.

Research Progress on the Correlation between Gut Microorganisms and Gastrointestinal Diseases

The intestinal microbiota refers to the complex community of microorganisms present in the human digestive tract. With the development of high-throughput sequencing technologies such as 16SrRNA gene sequencing and metagenomic sequencing, the intestinal microbiota has been shown to be closely related to gastric cancer and colorectal cancer. At the same time, a series of studies have been conducted to explore the intestinal microbiota as a new type of non-invasive biological marker. This article summarizes the research on the intestinal microbiota of gastric cancer and colorectal cancer, and explains the changes in the intestinal microbiota when the disease occurs, so as to provide new ideas for finding potential molecular targets for the prevention, treatment, and intervention of tumors.

MecE, MecB, and MecC proteins orchestrate methyl group transfer during dichloromethane fermentation.

Dichloromethane (DCM), a common hazardous industrial chemical, is anaerobically metabolized by four bacterial genera: Dehalobacter, Dehalobacterium, Ca. Dichloromethanomonas, and Ca. Formimonas. However, the pivotal methyltransferases responsible for DCM transformation have remained elusive. In this study, we investigated the DCM catabolism of Dehalobacterium formicoaceticum strain EZ94, contained in an enriched culture, using a combination of biochemical approaches. Initially, enzymatic assays were conducted with cell-free protein extracts, after protein separation by blue native polyacrylamide gel electrophoresis. In the slices with the highest DCM transformation activity, a high absolute abundance of the methyltransferase MecC was revealed by mass spectrometry. Enzymatic activity assays with heterologously expressed MecB, MecC, and MecE from strain EZ94 showed complete DCM transformation only when all three enzymes were present. Our experimental results, coupled with the computational analysis of MecB, MecC, and MecE sequences, enabled us to assign specific roles in DCM transformation to each of the proteins. Our findings reveal that both MecE and MecC are zinc-dependent methyltransferases responsible for DCM demethylation and re-methylation of a product, respectively. MecB functions as a cobalamin-dependent shuttle protein transferring the methyl group between MecE and MecC. This study provides the first biochemical evidence of the enzymes involved in the anaerobic metabolism of DCM.IMPORTANCEDichloromethane (DCM) is a priority regulated pollutant frequently detected in groundwater. In this work, we identify the proteins responsible for the transformation of DCM fermentation in Dehalobacterium formicoaceticum strain EZ94 using a combination of biochemical approaches, heterologous expression of proteins, and computational analysis. These findings provide the basis to apply these proteins as biological markers to monitor bioremediation processes in the field.

Identifying biological markers and sociodemographic factors that influence the gap between phenotypic and chronological ages

ABSTRACT Introduction The world’s population is aging rapidly, leading to increased public health and economic burdens due to age-related cardiovascular and neurodegenerative diseases. Early risk detection is essential for prevention and to improve the quality of life in elderly individuals. Plus, health risks associated with aging are not directly tied to chronological age, but are also influenced by a combination of environmental exposures. Past research has introduced the concept of “Phenotypic Age,” which combines age with biomarkers to estimate an individual’s health risk. Methods This study explores which factors contribute most to the gap between chronological and phenotypic ages. We combined ten machine learning regression techniques applied to the NHANES dataset, containing demographic, laboratory and socioeconomic data from 41,474 patients, to identify the most important features. We then used clustering analysis and a mixed-effects model to stratify by sex, ethnicity, and education. Results We identified 28 demographic, biological and environmental factors related to a significant gap between phenotypic and chronological ages. Stratifying for sex, education and ethnicity, we found statistically significant differences in the outcome distributions. Conclusion By showing that health risk prevention should consider both biological and sociodemographic factors, we offer a new approach to predict aging rates and potentially improve targeted prevention strategies for age-related conditions.

Blood diagnostic and prognostic biomarkers in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis is a devastating neurodegenerative disease for which the current treatment approaches remain severely limited. The principal pathological alterations of the disease include the selective degeneration of motor neurons in the brain, brainstem, and spinal cord, as well as abnormal protein deposition in the cytoplasm of neurons and glial cells. The biological markers under extensive scrutiny are predominantly located in the cerebrospinal fluid, blood, and even urine. Among these biomarkers, neurofilament proteins and glial fibrillary acidic protein most accurately reflect the pathologic changes in the central nervous system, while creatinine and creatine kinase mainly indicate pathological alterations in the peripheral nerves and muscles. Neurofilament light chain levels serve as an indicator of neuronal axonal injury that remain stable throughout disease progression and are a promising diagnostic and prognostic biomarker with high specificity and sensitivity. However, there are challenges in using neurofilament light chain to differentiate amyotrophic lateral sclerosis from other central nervous system diseases with axonal injury. Glial fibrillary acidic protein predominantly reflects the degree of neuronal demyelination and is linked to non-motor symptoms of amyotrophic lateral sclerosis such as cognitive impairment, oxygen saturation, and the glomerular filtration rate. TAR DNA-binding protein 43, a pathological protein associated with amyotrophic lateral sclerosis, is emerging as a promising biomarker, particularly with advancements in exosome-related research. Evidence is currently lacking for the value of creatinine and creatine kinase as diagnostic markers; however, they show potential in predicting disease prognosis. Despite the vigorous progress made in the identification of amyotrophic lateral sclerosis biomarkers in recent years, the quest for definitive diagnostic and prognostic biomarkers remains a formidable challenge. This review summarizes the latest research achievements concerning blood biomarkers in amyotrophic lateral sclerosis that can provide a more direct basis for the differential diagnosis and prognostic assessment of the disease beyond a reliance on clinical manifestations and electromyography findings.

Prognostic value of CMR-derived extracellular volume in AL amyloidosis: a multicenter study

Background This study aimed to assess the prognostic value of cardiac magnetic resonance (CMR) variables and compare them with biological and echocardiographic markers in patients with AL cardiac amyloidosis (CA). Methods We conducted a prospective study across three tertiary centres, where patients underwent clinical examination, blood tests, echocardiography, and CMR. The primary endpoint was all-cause mortality. Results A total of 176 patients with AL CA were included, with a median age of 68 years (IQR 58-75). According to the 2004 Mayo Clinic staging, 121 patients (69%) were in stage 3. During a median follow-up of 22 months (IQR 8–48), 45 patients died, and 55 were hospitalized for heart failure. Patients who died had higher NT-proBNP and troponin levels, and lower LVEF, cardiac output, and longitudinal strain. Among CMR variables, extracellular volume (ECV) was most strongly associated with all-cause mortality. In multivariate Cox models, including Mayo Clinic staging, ECV ≥ 0.45 was independently associated with mortality (HR 2.36, CI 95% 1.47–5.60) and also with heart failure hospitalizations (HR 4.10, 95%CI 2.15–8.8). Conclusion ECV is a powerful predictor of outcomes in AL CA, providing additional prognostic value on top of Mayo Clinic staging.

High arsenic contamination in the breast milk of mothers inhabiting the Gangetic plains of Bihar: a major health risk to infants

Groundwater arsenic poisoning has posed serious health hazards in the exposed population. The objective of the study is to evaluate the arsenic ingestion from breastmilk among pediatric population in Bihar. In the present study, the total women selected were n = 513. Out of which n = 378 women after consent provided their breastmilk for the study, n = 58 subjects were non-lactating but had some type of disease in them and n = 77 subjects denied for the breastmilk sample. Hence, they were selected for the women health study. In addition, urine samples from n = 184 infants’ urine were collected for human arsenic exposure study. The study reveals that the arsenic content in the exposed women (in 55%) was significantly high in the breast milk against the WHO permissible limit 0.64 µg/L followed by their urine and blood samples as biological marker. Moreover, the child’s urine also had arsenic content greater than the permissible limit (< 50 µg/L) in 67% of the studied children from the arsenic exposed regions. Concerningly, the rate at which arsenic is eliminated from an infant’s body via urine in real time was only 50%. This arsenic exposure to young infants has caused potential risks and future health implications. Moreover, the arsenic content was also very high in the analyzed staple food samples such as rice, wheat and potato which is the major cause for arsenic contamination in breastmilk. The study advocates for prompt action to address the issue and implement stringent legislative measures in order to mitigate and eradicate this pressing problem that has implications for future generations.

Gold Nanowire Sponge Electrochemistry for Permeable Wearable Sweat Analysis Comfortably and Wirelessly.

Electrochemistry-based wearable and wireless sweat analysis is emerging as a promising noninvasive method for real-time health monitoring by tracking chemical and biological markers without the need for invasive blood sampling. It offers the potential to remotely monitor human sweat conditions in relation to metabolic health, stress, and electrolyte balance, which have implications for athletes, patients with chronic conditions, and individuals for the early detection and management of health issues. The state-of-the-art mainstream technology is dominated by the concept of a wearable microfluidic chip, typically based on elastomeric PDMS. While outstanding sensing performance can be realized, the design suffers from the poor permeability of PDMS, which could cause skin redness or irritation. Here, we introduce an omnidirectionally permeable, deformable, and wearable sweat analysis system based on gold nanowire sponges. We demonstrate the concept of all-in-one soft sponge electrochemistry, where the working, reference, and counter electrodes and electrolytes are all integrated within the sponge matrix. The intrinsic porosity of sponge in conjunction with vertically aligned gold nanowire electrodes gives rise to a high electrochemically active surface area of ∼67 cm2. Remarkably, this all-in-one sponge-based electrochemical system exhibited stable performance under a pressure of 10 kPa and 300% omnidirectional strain. The gold sponge biosensing electrodes could be sandwiched between two biocompatible sweat pads, which can serve as natural sweat collection and outflow layers. This naturally biocompatible and permeable platform can be integrated with wireless communication circuits, leading to a wireless sweat analysis system for the real-time monitoring of glucose, lactate, and pH during exercise.

Biomarkers and Prognostic Stratification of Squamous Cell Carcinoma of the Oral Cavity in Young Adults: how to personalize therapeutic management?

Abstract Squamous cell carcinomas (SCCs) of the oral cavity in young adults represent a heterogeneous entity. New prognostic biomarkers are described in the literature. The aim was to identify emerging biomarkers and prognostic stratification factors of young population. Clinical, biological, microbiological, histopathological, and molecular markers statistically associated with overall and disease-free survival (OS) and validated in literature. Young adults &amp;lt; 40 years who were non-smokers showed a marginally worse prognosis, while age &amp;lt; 30 years was unfavorable compared to &amp;gt; 30 years. High rate of Neutrophil-to-lymphocyte ratio (NLR) was associated with decreased 5-year disease-specific survival, PDL1 expression correlated with improved OS and recurrence-free survival, presence of Fusobacterium, Mutations in p53, Cyclin D1, and VEGF was associated with reduced OS. Combining these markers in young adult oral cavity SCCs should be used to adapt the intensification of therapy in addition to the TNM classification and minor histo-prognostic factors.

SARS-CoV2 pneumonia patients admitted to the ICU: Analysis according to clinical and biological parameters and the extent of lung parenchymal lesions on chest CT scan, a monocentric observational study

Background CT-scan and inflammatory and coagulation biomarkers could help in prognostication of COVID-19 in patients on ICU admission. Objective The objectives of this study were to measure the prognostic value of the extent of lung parenchymal lesions on computed tomography (CT) and of several coagulation and inflammatory biomarkers, and to explore the characteristics of the patients depending on the extent of lung parenchymal lesions. Design Retrospective monocentric observational study achieved on a dataset collected prospectively. Setting Medical ICU of the university hospital of Clermont-Ferrand, France. Patients All consecutive adult patients aged ≥18 years admitted between 20 March, 2020 and 31 August, 2021 for COVID-19 pneumonia. Interventions Characteristics at baseline and during ICU stay, and outcomes at day 60 were recorded. The extent of lung parenchyma lesions observed on the chest CT performed on admission was established by artificial intelligence software. Measurements Several clinical characteristics and laboratory features were collected on admission including plasma interleukin-6, HLA-DR monocytic–expression rate (mHLA-DR), and the extent of lung parenchymal lesions. Factors associated with day-60 mortality were investigated by uni- and multivariate survival analyses. Results 270 patients were included. Inflammation biomarkers including the levels of neutrophils, CRP, ferritin and Il10 were the indices the most associated with the severity of the extent of the lung lesions. Patients with more extensive lung parenchymal lesions (≥ 75%) on admission had higher CRP serum levels. The extent of lung parenchymal lesions was associated with a decrease in the PaO2/FiO2 ratio(p&lt;0.01), fewer ventilatory-free days (p = 0.03), and a higher death rate at day 60(p = 0.01). Extent of the lesion of more than 75% was independently associated with day-60 mortality (aHR = 1.72[1.06; 2.78], p = 0.03). The prediction of death at day 60 was improved when considering simultaneously biological and radiological markers obtained on ICU admission (AUC = 0.78). Conclusions The extent of lung parenchyma lesions on CT was associated with inflammation, and the combination of coagulation and inflammatory biomarkers and the extent of the lesions predicted the poorest outcomes.

Biological markers of brain network connectivity and pain sensitivity distinguish low coping from high coping Veterans with persistent post-traumatic headache.

Headache is the most common type of pain following mild traumatic brain injury. Roughly half of those with persistent post-traumatic headache (PPTH) also report neck pain which is associated with greater severity and functional impact of headache. This observational cohort study aimed to identify biological phenotypes to help inform mechanism-based approaches in the management of PPTH with and without concomitant neck pain. Thirty-three military Veterans (mean (SD) = 37±16 years, 29 males) with PPTH completed a clinical assessment, quantitative sensory testing, and magnetic resonance imaging of the brain and cervical spine. Multidimensional phenotyping was performed using a Random Forest analysis and Partitioning Around Medoids (PAM) clustering of input features from three biologic domains: 1) resting state functional connectivity (rsFC) of the periaqueductal gray (PAG), 2) quality and size of cervical muscles, and 3) mechanical pain sensitivity and central modulation of pain. Two subgroups were distinguished by biological features that included forehead pressure pain threshold and rsFC between the PAG and selected nodes within the default mode, salience, and sensorimotor networks. Compared to the High Pain Coping group, the Low Pain Coping group exhibited higher pain-related anxiety (p=0.009), higher pain catastrophizing (p=0.004), lower pain self-efficacy (p=0.010), and greater headache-related disability (p=0.012). Findings suggest that greater functional connectivity of pain modulation networks involving the PAG combined with impairments in craniofacial pain sensitivity, but not cervical muscle health, distinguish a clinically important subgroup of individuals with PPTH who are less able to cope with pain and more severely impacted by headache.

Neutrophil-to-Lymphocyte Ratio Any Association with Metabolic Syndrome in Schizophrenia

To date, hematologic inflammation coefficients (HICs) have been considered as biological markers linking the functions of the immune, endocrine, and autonomous nervous systems. HICs are markers of immune abnormalities that accompany various pathologic conditions and, to a large extent, determine disease prognosis, survival time, and function. According to the results of a meta-analysis covering the results of examination of more than 168 thousand patients, it was found that the ratio of neutrophils to lymphocytes (NLR) is associated with higher levels in patients with metabolic syndrome and can potentially be used for early detection of this pathology. Given these facts, it seems reasonable to test the assumption of the role of HICs in the pathogenesis of psychiatric disorders, their participation in the mechanisms of development of comorbid conditions, or predicting the outcome and effects of therapy. In 2024, the team of the Bekhterev Center began to perform work under the state assignment of the Ministry of Health of the Russian Federation, the purpose of which was to develop and validate a model for predicting individual risks of metabolic disorders in patients with psychiatric disorders, on the basis of which interpretive software will be presented. The team of authors of this article focused on conducting a systematic review of publications to test this hypothesis.

Comprehensive biomarker assessment for predicting severe acute kidney injury and need of kidney replacement therapy in liver transplantation patients

Background Renal dysfunction is a common complication following liver transplantation (LT). This study aimed to determine whether a comprehensive assessment of kidney function using nineteen serum and urinary biomarkers (BMs) within the first 48 h post-LT could enhance the prediction of severe acute kidney injury (AKI) and the need of kidney replacement therapy (KRT) during the first postoperative week. Methods Blood and urine (U) samples were collected during the pre- and postoperative periods. Nineteen BMs were evaluated to assess kidney health in the first 48 h after LT. Classification and regression tree (CART) cross-validation identified key predictors to determine the best BM combination for predicting outcomes. Results Among 100 LT patients, 36 developed severe AKI, and 34 required KRT within the first postoperative week. Preoperative assessment of U neutrophil gelatinase-associated lipocalin (NGAL) and liver-type fatty acid-binding protein (L-FABP) predicted the need for KRT with 75% accuracy. The combined assessment of U osmolality (OSM), U kidney injury molecule 1 (KIM-1), and tissue inhibitor of metalloproteinase (TIMP-1) within 48 h post-LT predicted severe AKI with 80% accuracy. U-OSM alone, measured within 48 h post-LT, had an accuracy of 83% for predicting KRT need, outperforming any BM combination. Conclusions Combined BM analysis can accurately predict severe AKI and KRT needs in the perioperative period of LT. U-OSM alone proved to be an effective tool for monitoring the risk of severe AKI, available in most centers. Further studies are needed to assess its impact on AKI progression postoperatively. Registered at Clinical Trials (clinicaltrials.gov) in March 24th, 2014 by title ‘Acute Kidney Injury Biomarkers: Diagnosis and Application in Pre-operative Period of Liver Transplantation (AKIB)’ and identifier NCT02095431.

Habitual Coffee, Tea, and Caffeine Consumption, Circulating Metabolites, and the Risk of Cardiometabolic Multimorbidity.

Cardiometabolic multimorbidity (CM) is an increasing public health concern. Previous observational studies have suggested inverse associations between coffee, tea, and caffeine intake and risks of individual cardiometabolic diseases; however, their associations with CM and related biological markers are unknown. This prospective study involved 172 315 (for caffeine analysis) and 188 091 (tea and coffee analysis) participants free of any cardiometabolic diseases at baseline from the UK Biobank; 168 metabolites were measured among 88 204 and 96 393 participants. CM was defined as the coexistence of at least 2 of the following conditions: type 2 diabetes, coronary heart disease, and stroke. Nonlinear inverse associations of coffee, tea, and caffeine intake with the risk of new-onset CM were observed. Compared with nonconsumers or consumers of less than 100 mg caffeine per day, consumers of moderate amount of coffee (3 drinks/d) or caffeine (200-300 mg/d) had the lowest risk for new-onset CM, with respective hazard ratios (95% CIs) of 0.519 (0.417-0.647) and 0.593 (0.499-0.704). Multistate models revealed that moderate coffee or caffeine intake was inversely associated with risks of almost all developmental stages of CM, including transitions from a disease-free state to single cardiometabolic diseases and subsequently to CM. A total of 80 to 97 metabolites, such as lipid components within very low-density lipoprotein, histidine, and glycoprotein acetyls, were identified to be associated with both coffee, tea, or caffeine intake and incident CM. Habitual coffee or caffeine intake, especially at a moderate level, was associated with a lower risk of new-onset CM and could play important roles in almost all transition phases of CM development. Future studies are warranted to validate the implicated metabolic biomarkers underlying the relation between coffee, tea, and caffeine intake and CM.

Thermography is a promising breast cancer detection complementary diagnostic tool

From the last Twenty years of complying with the strict standardized thermogram interpretation protocols by proper infrared-trained personnel as documented in the literature, breast thermography has achieved high sensitivity and specificity [1]. An abnormal thermogram is reported as the significant biological risk marker for the existence of or continued development of breast tumors. This paper further discusses the implementation, performance, and environmental requirements in characterizing thermography as being used for breast tumor screening under strict indoor controlled environmental conditions. The essential elements of performance requirements include display temperature color scale, display temperature resolution, emissivity setting, screening temperature range, workable target plane, response time, and selection of critical parameters such as uniformity, minimum detectable temperature difference, detector pixels and drift between auto-adjustment. The imaging procedure in this study was carried out at Warith International Oncology Institute

Assessing biological stress markers in the hair of individuals at ultra-high risk for psychosis using a novel method of extraction

Assessing biological stress markers in the hair of individuals at ultra-high risk for psychosis using a novel method of extraction

Acute COVID-19 severity markers predict post-COVID new-onset psychiatric disorders: A 2-year cohort study of 34,489 patients.

New-onset psychiatric disorders are frequent after COVID-19. We aim to determine whether acute COVID-19 severity markers can predict post-COVID new-onset psychiatric disorders. We conducted an electronic health records (EHR) cohort study of patients hospitalized for COVID-19 and without any known history of psychiatric disorders. Patients were included between January 2020 and September 2022 in one of the 36 university hospitals of the Assistance Publique - Hôpitaux de Paris. Acute COVID-19 clinical and biological severity markers were recorded during hospitalization for COVID-19. Psychiatric ICD-10 diagnoses were recorded up to 2 years and 9 months after hospitalization for COVID-19. Predictors of post-COVID new-onset psychiatric disorders were identified based on Cox regression models and sensitivity analyses. Predictive scores were built and tested in age- and sex-stratified populations. A total 34,489 patients hospitalized for COVID-19 were included; 3717 patients (10.8%) had at least one post-COVID new-onset psychiatric disorder. Hospital stay >7 days (HR = 1.72, 95%CI [1.59-1.86], p < 0.001), acute delirium (HR = 1.49, 95%CI [1.28-1.74], p < 0.001), elevated monocyte count (HR = 1.14, 95%CI [1.06-1.23], p < 0.001) and elevated plasma CRP (HR = 0.92, 95%CI [0.86-0.99], p = 0.04) independently predicted post-COVID new-onset psychiatric disorders. Sensitivity analyses confirmed hospital stay >7 days, acute delirium, and elevated monocyte count as predictors. Predictive scores based on these variables had good 12-month positive predictive values, up to 7.5 times more accurate than random in women < 65 years. In conclusion, hospital stay >7 days, acute delirium, and elevated monocyte count during acute COVID-19 predict post-COVID new-onset psychiatric disorders.