The critical role of tumor microbiome in cancer immunotherapy

In recent years, the microbiome has shown an integral role in cancer immunotherapy and has become a prominent and widely studied topic. A full understanding of the interactions between the tumor microbiome and various immunotherapies offers opportunities for immunotherapy of cancer. This review scrutinizes the composition of the tumor microbiome, the mechanism of microbial immune regulation, the influence of tumor microorganisms on tumor metastasis, and the interaction between tumor microorganisms and immunotherapy. In addition, this review also summarizes the challenges and opportunities of immunotherapy through tumor microbes, as well as the prospects and directions for future related research. In conclusion, the potential of microbial immunotherapy to enhance treatment outcomes for cancer patients should not be underestimated. Through this review, it is hoped that more research on tumor microbial immunotherapy will be done to better solve the treatment problems of cancer patients.

Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

A novel deep learning method for large-scale analysis of bone marrow adiposity using UK Biobank Dixon MRI data

Background

Bone marrow adipose tissue (BMAT) represents > 10% fat mass in healthy humans and can be measured by magnetic resonance imaging (MRI) as the bone marrow fat fraction (BMFF). Human MRI studies have identified several diseases associated with BMFF but have been relatively small scale. Population-scale studies therefore have huge potential to reveal BMAT's true clinical relevance. The UK Biobank (UKBB) is undertaking MRI of 100,000 participants, providing the ideal opportunity for such advances.

Objective

To establish deep learning for high-throughput multi-site BMFF analysis from UKBB MRI data.

Materials and methods

We studied males and females aged 60-69. Bone marrow (BM) segmentation was automated using a new lightweight attention-based 3D U-Net convolutional neural network that improved segmentation of small structures from large volumetric data. Using manual segmentations from 61-64 subjects, the models were trained to segment four BM regions of interest: the spine (thoracic and lumbar vertebrae), femoral head, total hip and femoral diaphysis. Models were tested using a further 10-12 datasets per region and validated using datasets from 729 UKBB participants. BMFF was then quantified and pathophysiological characteristics assessed, including site- and sex-dependent differences and the relationships with age, BMI, bone mineral density, peripheral adiposity, and osteoporosis.

Results

Model accuracy matched or exceeded that for conventional U-Nets, yielding Dice scores of 91.2% (spine), 94.5% (femoral head), 91.2% (total hip) and 86.6% (femoral diaphysis). One case of severe scoliosis prevented segmentation of the spine, while one case of Non-Hodgkin Lymphoma prevented segmentation of the spine, femoral head and total hip because of T2 signal depletion; however, successful segmentation was not disrupted by any other pathophysiological variables. The resulting BMFF measurements confirmed expected relationships between BMFF and age, sex and bone density, and identified new site- and sex-specific characteristics.

Conclusions

We have established a new deep learning method for accurate segmentation of small structures from large volumetric data, allowing high-throughput multi-site BMFF measurement in the UKBB. Our findings reveal new pathophysiological insights, highlighting the potential of BMFF as a novel clinical biomarker. Applying our method across the full UKBB cohort will help to reveal the impact of BMAT on human health and disease.

Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese

Introduction

Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese.

Methods

Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD.

Results

A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters.

Conclusion

Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals.

MiRNAs as new potential biomarkers and therapeutic targets in brain metastasis

Brain metastases represent a formidable challenge in cancer management, impacting a significant number of patients and contributing significantly to cancer-related mortality. Conventional diagnostic methods frequently fall short, underscoring the imperative for non-invasive alternatives. Non-coding RNAs (ncRNAs), specifically microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), present promising avenues for exploration. These ncRNAs exert influence over the prognosis and treatment resistance of brain metastases, offering valuable insights into underlying mechanisms and potential therapeutic targets. Dysregulated ncRNAs have been identified in brain metastases originating from various primary cancers, unveiling opportunities for intervention and prevention. The analysis of ncRNA expression in bodily fluids, such as serum and cerebrospinal fluid, provides a noninvasive means to differentiate brain metastases from primary tumors. NcRNAs, particularly miRNAs, assume a pivotal role in orchestrating the immune response within the brain microenvironment. MiRNAs exhibit promise in diagnosing brain metastases, effectively distinguishing between normal and cancer cells, and pinpointing the tissue of origin for metastatic brain tumors. The manipulation of miRNAs holds substantial potential in cancer treatment, offering the prospect of reducing toxicity and enhancing efficacy. Given the limited treatment options and the formidable threat of brain metastases in cancer patients, non-coding RNAs, especially miRNAs, emerge as beacons of hope, serving as both diagnostic tools and therapeutic targets. Further clinical studies are imperative to validate the specificity and sensitivity of ncRNAs, potentially reshaping approaches to tackle this challenge and elevate treatment outcomes for affected patients.

miR-4716-3p and the target AKT2 Gene/rs2304186 SNP are associated with blood cancer pathogenesis in Pakistani population

AKT2 is crucial for cancer cells' invasion, metastasis, and survival. It is a possible downstream gene target of cancer glycolysis-related microRNAs. The study investigated the role of miRNA-4716-3p, rs2304186, and the AKT2 gene in blood cancer pathogenesis. RT-qPCR was used to analyze AKT2 gene mRNA and miRNA-4716-3p expression in 200 blood cancer samples and 200 healthy controls. Furthermore, Tetra-ARMS PCR was used to examine the rs2304186 AKT2 SNP in 300 patients and 290 control samples. miRNA-4716-3p was shown to be significantly downregulated (p = 0.0294), whereas mRNA expression of the AKT2 gene was found to be significantly upregulated (p = 0.0034) in blood cancer patients compared to healthy individuals. miRNA-4716-3p downregulation (p = 0.0466) was more pronounced, while AKT2 upregulation was non-significant (p = 0.1661) in untreated patients compared to chemotherapy-treated patients. Blood cancer risk was significantly associated with the rs2304186 GT genotype (p = 0.0432), TT genotype (p = 0.0502), and mutant allele (T) frequency (p = 0.0008). Polymorphism rs2304186 was associated with an increased risk of blood cancer in dominant (p = 0.0011), recessive (p = 0.0502), and additive (p = 0.0008) genetic models. The results suggested that the rs2304186 and the deregulated expression of miRNA-4716-3p and AKT2 gene at the mRNA level may significantly increase the incidence of blood cancer, particularly in the Pakistani population. Therefore, these may function as suitable biomarkers for blood cancer diagnosis and prognosis. Additional, larger-scale investigations may be required to affirm these results.

MicroRNAs in meningiomas: Potential biomarkers and therapeutic targets

Meningiomas, characterized primarily as benign intracranial or spinal tumors, present distinctive challenges due to their variable clinical behavior, with certain cases exhibiting aggressive features linked to elevated morbidity and mortality. Despite their prevalence, the underlying molecular mechanisms governing the initiation and progression of meningiomas remain insufficiently understood. MicroRNAs (miRNAs), small endogenous non-coding RNAs orchestrating post-transcriptional gene expression, have garnered substantial attention in this context. They emerge as pivotal biomarkers and potential therapeutic targets, offering innovative avenues for managing meningiomas. Recent research delves into the intricate mechanisms by which miRNAs contribute to meningioma pathogenesis, unraveling the molecular complexities of this enigmatic tumor. Meningiomas, originating from arachnoid meningothelial cells and known for their gradual growth, constitute a significant portion of intracranial tumors. The clinical challenge lies in comprehending their progression, particularly factors associated with brain invasion and heightened recurrence rates, which remain elusive. This comprehensive review underscores the pivotal role of miRNAs, accentuating their potential to advance our comprehension of meningioma biology. Furthermore, it suggests promising directions for developing diagnostic biomarkers and therapeutic interventions, holding the promise of markedly improved patient outcomes in the face of this intricate and variable disease.

Exosomal long non-coding RNAs in cancer: Interplay, modulation, and therapeutic avenues

In the intricate field of cancer biology, researchers are increasingly intrigued by the emerging role of exosomal long non-coding RNAs (lncRNAs) due to their multifaceted interactions, complex modulation mechanisms, and potential therapeutic applications. These exosomal lncRNAs, carried within extracellular vesicles, play a vital partin tumorigenesis and disease progression by facilitating communication networks between tumor cells and their local microenvironment, making them an ideal candidates for use in a liquid biopsy approach. However, exosomal lncRNAs remain an understudied area, especially in cancer biology. Therefore this review aims to comprehensively explore the dynamic interplay between exosomal lncRNAs and various cellular components, including interactions with tumor-stroma, immune modulation, and drug resistance mechanisms. Understanding the regulatory functions of exosomal lncRNAs in these processes can potentially unveil novel diagnostic markers and therapeutic targets for cancer. Additionally, the emergence of RNA-based therapeutics presents exciting opportunities for targeting exosomal lncRNAs, offering innovative strategies to combat cancer progression and improve treatment outcomes. Thus, this review provides insights into the current understanding of exosomal lncRNAs in cancer biology, highlighting their crucial roles, regulatory mechanisms, and the evolving landscape of therapeutic interventions. Furthermore, we have also discussed the advantage of exosomes as therapeutic carriers of lncRNAs for the development of personalized targeted therapy for cancer patients.

Proteomics and bioinformatics analyses based on two-dimensional electrophoresis and LC-MS/MS for the primary characterization of protein changes in chicken breast meat from divergent farming systems: Organic versus antibiotic-free

Proteomics is a key analytical method in meat research thanks to its potential in investigating the proteins at interplay in post-mortem muscles. This study aimed to characterize for the first time the differences in early post-mortem muscle proteomes of chickens raised under two farming systems: organic versus antibiotic-free. Forty post-mortem Pectoralis major muscle samples from two chicken strains (Ross 308 versus Ranger Classic) reared under organic versus antibiotic-free farming systems were characterized and compared using two-dimensional electrophoresis and LC-MS/MS mass spectrometry. Within antibiotic-free and organic farming systems, 14 and 16 proteins were differentially abundant between Ross 308 and Ranger Classic, respectively. Within Ross 308 and Ranger Classic chicken strains, 12 and 18 proteins were differentially abundant between organic and antibiotic-free, respectively. Bioinformatics was applied to investigate the molecular pathways at interplay, which highlighted the key role of muscle structure and energy metabolism. Antibiotic-free and organic farming systems were found to significantly impact the muscle proteome of chicken breast meat. This paper further proposes a primary list of putative protein biomarkers that can be used for chicken meat or farming system authenticity.

SH3GL2 and MMP17 as lung adenocarcinoma biomarkers: a machine-learning based approach

Objective

Using bioinformatics machine learning methods, our research aims to identify the potential key genes associated with Lung adenocarcinoma (LUAD).

Methods

We obtained two gene expression profiling microarrays (GSE68571 and GSE74706) from the public Gene Expression Omnibus (GEO) database at the National Centre for Biotechnology Information (NCBI). The purpose was to identify Differentially Expressed Genes (DEGs) between the lung adenocarcinoma group and the healthy control group. The limma R package in R was utilized for this analysis. For the differential gene diagnosis of lung adenocarcinoma, we employed the least absolute shrinkage and selection operator (LASSO) regression and SVM-RFE screening crossover. To evaluate the performance, ROC curves were plotted. We performed immuno-infiltration analysis using CIBERSORT. Finally, we validated the key genes through qRT-PCR and Western-blot verification, then downregulated MMP17 gene expression, upregulated SH3GL2 gene expression, and performed CCK8 experiments.

Results

A total of 32 Differentially Expressed Genes (DEGs) were identified. Two diagnostic marker genes, SH3GL2 and MMP17, were selected by employing LASSO and SVM-RFE machine learning methods. In Lung adenocarcinoma cells, the expression of MMP17 was observed to be elevated compared to normal lung epithelial cells in the control group (P < 0.05). In contrast, a down-regulation of SH3GL2 was found in Lung adenocarcinoma cells (P < 0.05). Finally, we downregulated MMP17 and upregulated SH3GL2 gene expression, then the CCK8 showed that the proliferation of both lung cancer cells was inhibited.

Conclusion

SH3GL2 and MMP17 are expected to be potential biomarkers for Lung adenocarcinoma.

Identification of pasteurized mare milk and powder adulteration with bovine milk using quantitative proteomics and metabolomics approaches

Adulteration in dairy products presents food safety challenges, driven by economic factors. Processing may change specific biomarkers, thus affecting their effectiveness in detection. In this study, proteomics and metabolomics approaches were to investigate the detection of bovine milk (BM) constituents adulteration in pasteurized mare milk (PMM) and mare milk powder (MMP). Several bovine proteins and metabolites were identified, with their abundances in PMM and MMP increasing upon addition of BM. Proteins like osteopontin (OPN) and serotransferrin (TF) detected adulteration down to 1 % in PMM, whereas these proteins in MMP were utilized to identify 10 % adulteration. Biotin and N6-Me-adenosine were effective in detecting adulteration in PMM as low as 10 % and 1 % respectively, while in MMP, their detection limits extend down to 0.1 %. These findings offer insights for authenticating mare milk products and underscore the influence of processing methods on biomarker levels, stressing the need to consider these effects in milk product authentication.

Meta-analysis of Circulatory mitomiRs in stress Response: Unveiling the significance of miR-34a and miR-146a

BACKGROUND

MicroRNAs (miRNAs) are short, noncoding RNAs with essential roles in cellular pathways and are often associated with various diseases and stress conditions. Recently, they have been discovered in mitochondria, termed "mitomiRs," with unique functions. Mitochondria, crucial organelles for energy production and stress responses, Dysregulated mitomiRs functions and expression has been evident in stress conditions such as cardiovascular and neurodegenerative. In this meta-analysis we have systematically identified miR-34a & miR-146a as possible potential biomarkers for affliction.

METHODS

A meta-analysis was conducted to assess the potential role of miR-34a and miR-146a, two specific mitomiRs, as biomarkers in stress-related conditions. The study followed PRISMA guidelines, involving comprehensive database searches in May and September 2023. Twelve studies meeting predefined inclusion criteria were selected, and data analysis included the evaluation of miR-34a and miR-146a expression levels in various stress conditions compared to control groups. We also performed Gene ontology (GO) and Pathway enrichment analysis to observe how mitomiRs affects our body.

RESULTS

The meta-analysis revealed a significant increase in overall mitomiRs (miR-34a and miR-146a) expression levels in experimental groups experiencing different stress conditions compared to control groups (Z = 3.54, p < 0.05 using RevMan software). miR-34a demonstrated more pronounced upregulation and exhibited potential as a specific biomarker in certain stress-related conditions (Z = 2.22, p < 0.05). However, miR-146a did not show a significant difference, requiring further investigation in various stress-related contexts. The Analysis indicated a high degree of heterogeneity among the studies.

CONCLUSION

This meta-analysis emphasises the importance of mitomiRs, especially miR-34a, as potential biomarkers in the intricate interplay between stress, mitochondrial function, and disease. The study opens new avenues for exploring miRNAs' diagnostic and therapeutic applications in stress-related diseases, highlighting their pivotal role at the crossroads of molecular biology, psychology, and medicine.

Development and functionalization of electrospun fiber coated thin film microextraction devices for rapid mass spectrometric determination of biologically important polar molecules

Rapid diagnosis of diseases is one of the challenging areas in clinical research. From the analytical chemist's perspective, the main challenges are isolating the compounds from the bio-specimen and lengthy analysis times. In this regard, solid phase microextraction offers a platform to address the abovementioned challenges. Moreover, its sharp tip-thin film geometry, known as coated blade spray (CBS), can enhance the extraction and act as an ionization source in direct mass spectrometric analysis. In this study, a new CBS device specifically designed for polar analytes was prepared and optimized to determine urinary metabolites. For this purpose, polyacrylonitrile (PAN) was selected as a base polymer as it can be electrospun to form a nanofibrous structure, and it can be modified with weak ion exchange moieties to interact with polar analytes. Following the electrospinning of PAN, hydrolysis was optimized, and conditions leading to sufficient extraction enhancement without dissolving the polymer were obtained when probes were treated with 5.0 M of NaOH for 2.5 h. Using the coated blades prepared as explained, the evaluation of various extraction conditions showed that 5 min is sufficient for equilibrium extraction. In addition, the solution's ionic strength and pH significantly affect the extraction. Optimum sorption was obtained at no salt added and pH 7.0 conditions. The CBS-MS optimization showed that 10.0 µL of ACN/MeOH/H2O (40:40:20, v/v/v) with formic acid kept for 15 seconds on the blade before voltage application leads to the highest signal. The limits of quantification of the analytes are between 50 and 100 ng/mL.

Tear metabolomics for the diagnosis of primary open-angle glaucoma

Primary Open-Angle Glaucoma (POAG) is the most prevalent glaucoma type, and the leading cause of irreversible visual impairment and blindness worldwide. Identification of early POAG biomarkers is of enormous value, as there is not an effective treatment for the glaucomatous optic nerve degeneration (OND). In this pilot study, a metabolomic analysis, by using proton (1H) nuclear magnetic resonance (NMR) spectroscopy was conducted in tears, in order to determine the changes of specific metabolites in the initial glaucoma eyes and to discover potential diagnostic biomarkers. A classification model, based on the metabolomic fingerprint in tears was generated as a non-invasive tool to support the preclinical and clinical POAG diagnosis. 1H NMR spectra were acquired from 30 tear samples corresponding to the POAG group (n = 11) and the control group (n = 19). Data were analysed by multivariate statistics (partial least squares-discriminant analysis: PLS-DA) to determine a model capable of differentiating between groups. The whole data set was split into calibration (65%)/validation (35%), to test the performance and the ability for glaucoma discrimination. The calculated PLS-DA model showed an area under the curve (AUC) of 1, as well as a sensitivity of 100% and a specificity of 83.3% to distinguish POAG group versus control group tear data. This model included 11 metabolites, potential biomarkers of the disease. When comparing the study groups, a decrease in the tear concentration of phenylalanine, phenylacetate, leucine, n-acetylated compounds, formic acid, and uridine, was found in the POAG group. Moreover, an increase in the tear concentration of taurine, glycine, urea, glucose, and unsaturated fatty acids was observed in the POAG group. These results highlight the potential of tear metabolomics by 1H NMR spectroscopy as a non-invasive approach to support early POAG diagnosis and in order to prevent visual loss.

Understanding long COVID myocarditis: A comprehensive review

Infectious diseases are a cause of major concern in this twenty-first century. There have been reports of various outbreaks like severe acute respiratory syndrome (SARS) in 2003, swine flu in 2009, Zika virus disease in 2015, and Middle East Respiratory Syndrome (MERS) in 2012, since the start of this millennium. In addition to these outbreaks, the latest infectious disease to result in an outbreak is the SARS-CoV-2 infection. A viral infection recognized as a respiratory illness at the time of emergence, SARS-CoV-2 has wreaked havoc worldwide because of its long-lasting implications like heart failure, sepsis, organ failure, etc., and its significant impact on the global economy. Besides the acute illness, it also leads to symptoms months later which is called long COVID or post-COVID-19 condition. Due to its ever-increasing prevalence, it has been a significant challenge to treat the affected individuals and manage the complications as well. Myocarditis, a long-term complication of coronavirus disease 2019 (COVID-19) is an inflammatory condition involving the myocardium of the heart, which could even be fatal in the long term in cases of progression to ventricular dysfunction and heart failure. Thus, it is imperative to diagnose early and treat this condition in the affected individuals. At present, there are numerous studies which are in progress, investigating patients with COVID-19-related myocarditis and the treatment strategies. This review focuses primarily on myocarditis, a life-threatening complication of COVID-19 illness, and endeavors to elucidate the pathogenesis, biomarkers, and management of long COVID myocarditis along with pipeline drugs in detail.

Current biomarkers and treatment strategies in Alzheimer disease: An overview and future perspectives

Alzheimer's disease (AD), a progressive degenerative disorder first identified by Alois Alzheimer in 1907, poses a significant public health challenge. Despite its prevalence and impact, there is currently no definitive ante mortem diagnosis for AD pathogenesis. By 2050, the United States may face a staggering 13.8 million AD patients. This review provides a concise summary of current AD biomarkers, available treatments, and potential future therapeutic approaches. The review begins by outlining existing drug targets and mechanisms in AD, along with a discussion of current treatment options. We explore various approaches targeting Amyloid β (Aβ), Tau Protein aggregation, Tau Kinases, Glycogen Synthase kinase-3β, CDK-5 inhibitors, Heat Shock Proteins (HSP), oxidative stress, inflammation, metals, Apolipoprotein E (ApoE) modulators, and Notch signaling. Additionally, we examine the historical use of Estradiol (E2) as an AD therapy, as well as the outcomes of Randomized Controlled Trials (RCTs) that evaluated antioxidants (e.g., vitamin E) and omega-3 polyunsaturated fatty acids as alternative treatment options. Notably, positive effects of docosahexaenoic acid nutriment in older adults with cognitive impairment or AD are highlighted. Furthermore, this review offers insights into ongoing clinical trials and potential therapies, shedding light on the dynamic research landscape in AD treatment.

Chemokine ligand 18 predicts all-cause mortality in patients hospitalized with chest pain of suspected coronary origin

Introduction

Chemokines mediate recruitment and activation of leucocytes. Chemokine ligand 18 (CCL18) is mainly expressed by monocytes/macrophages and dendritic cells. It is highly expressed in chronic inflammatory diseases, and locally in atherosclerotic plaques, particularly at sites of reduced stability, and systemically in acute coronary syndrome patients. Reports on its prognostic utility in the latter condition, including myocardial infarction (MI), are scarce.

Aim

To assess the utility of CCL18 as a prognostic marker of recurrent cardiovascular events in patients hospitalized with chest pain of suspected coronary origin.

Methods

The population consisted of 871 consecutive chest-pain patients, of whom 386 were diagnosed with acute myocardial infarction (AMI) based on Troponin-T (TnT) levels >50 ng/L. Stepwise Cox regression models, applying normalized continuous loge/SD values, were fitted for the biomarkers with cardiac mortality within 2 years and total mortality within 2 and 7 years as the dependent variables.

Results

Plasma samples from 849 patients were available. By 2 years follow-up, 138 (15.8%) patients had died, of which 86 were cardiac deaths. Univariate analysis showed a positive, significant association between CCL18 and total death [HR 1.55 (95% 1.30-1.83), p < 0.001], and for cardiac death [HR 1.32 (95% 1.06-1.64), p = 0.013]. Associations after adjustment were non-significant. By 7 years follow-up, 332 (38.1%) patients had died. CLL18 was independently associated with all-cause mortality [HR 1.14 (95% CI, 1.01-1.29), p = 0.030], but not with MI (n = 203) or stroke (n = 55).

Conclusion

CCL18 independently predicts long-term all-cause mortality but had no independent prognostic bearing on short-term cardiac death and CVD events.

Plasma miRNAs as potential biomarkers for schizophrenia in a Jordanian cohort

Background

Schizophrenia (SZ), a complex and chronic neuropsychiatric disorder affecting approximately 1 % of the general population, presents diagnostic challenges due to the absence of reliable biomarkers, and relying mainly on clinical observations. MicroRNAs (miRNAs) signatures in a wide range of diseases, including psychiatric disorders, hold immense potential for serving as biomarkers. This study aimed to analyze the expression levels of specific microRNAs (miRNAs) namely miR-29b-3p, miR-106b-5p, and miR-199a-3p and explore their diagnostic potential for SZ in Jordanian patients.

Methods

Small RNAs (miRNAs) were extracted from plasma samples of 30 SZ patients and 35 healthy controls. RNA was reverse transcribed and quantified by real-time polymerase chain reaction (qRT-PCR). The expression levels of three miRNAs (miR-29b-3p, miR-106b-5p and miR-199a-3p) were analyzed. Receiver operating characteristic (ROC) curves analysis was performed to evaluate diagnostic value of these miRNAs. Target genes prediction, functional enrichment and pathway analyses were done using miRWalk and Metascape. STRING database was used to construct protein-protein network and identify hub genes.

Results

Notably, miR-106b-5p and miR-199a-3p were significantly upregulated (p < 0.0001), while miRNA-29b-3p was downregulated (p < 0.0001) in SZ patients compared to controls. The diagnostic potential was assessed through ROC curves, revealing substantial diagnostic value for miR-199a-3p (AUC: 0.979) followed by miR-106b-5p (AUC: 0.774), with limited diagnostic efficacy for miR-29b-3p. Additionally, bioinformatic analyses for the predicted target genes of the diagnostically significant miRNAs uncovered Gene Ontology (GO) terms related to neurological development, including morphogenesis, which is involved in neuron differentiation, brain development, head development, and neuron projection morphogenesis. These findings highlight a potential connection between the identified miRNAs and SZ pathophysiology in the studied Jordanian population. Furthermore, a protein-protein interaction network from the target genes identified in association with neurological development in the Gene Ontology (GO) terms deepens our comprehension of the molecular landscape of the regulated target genes.

Conclusions

This comprehensive exploration highlights the promising role of miRNAs in unraveling intricate molecular pathways associated with SZ in the Jordanian cohort and suggests that plasma miRNAs could serve as reliable biomarkers for SZ diagnosis and disease progression. Remarkably, this study represents the first investigation into the role of circulating miRNA expression among Jordanian patients with SZ, providing valuable insights into the diagnostic landscape of this disorder.

Prognostic accuracy of 70 individual frailty biomarkers in predicting mortality in the Canadian Longitudinal Study on Aging

The frailty index (FI) uses a deficit accumulation approach to derive a single, comprehensive, and replicable indicator of age-related health status. Yet, many researchers continue to seek a single "frailty biomarker" to facilitate clinical screening. We investigated the prognostic accuracy of 70 individual biomarkers in predicting mortality, comparing each with a composite FI. A total of 29,341 individuals from the comprehensive cohort of the Canadian Longitudinal Study on Aging were included (mean, 59.4 ± 9.9 years; 50.3% female). Twenty-three blood-based biomarkers and 47 test-based biomarkers (e.g., physical, cardiac, cardiology) were examined. Two composite FIs were derived: FI-Blood and FI-Examination. Mortality status was ascertained using provincial vital statistics linkages and contact with next of kin. Areas under the curve were calculated to compare prognostic accuracy across models (i.e., age, sex, biomarker, FI) in predicting mortality. Compared to an age-sex only model, the addition of individual biomarkers demonstrated improved model fit for 24/70 biomarkers (11 blood, 13 test-based). Inclusion of FI-Blood or FI-Examination improved mortality prediction when compared to any of the 70 biomarker-age-sex models. Individual addition of seven biomarkers (walking speed, chair rise, time up and go, pulse, red blood cell distribution width, C-reactive protein, white blood cells) demonstrated an improved fit when added to the age-sex-FI model. FI scores had better mortality risk prediction than any biomarker. Although seven biomarkers demonstrated improved prognostic accuracy when considered alongside an FI score, all biomarkers had worse prognostic accuracy on their own. Rather than a single biomarker test, implementation of routine FI assessment in clinical settings may provide a more accurate and reliable screening tool to identify those at increased risk of adverse outcomes.

MIAT LncRNA: A multifunctional key player in non-oncological pathological conditions

The discovery of non-coding RNAs (ncRNAs) has unveiled a wide range of transcripts that do not encode proteins but play key roles in several cellular and molecular processes. Long noncoding RNAs (lncRNAs) are specific class of ncRNAs that are longer than 200 nucleotides and have gained significant attention due to their diverse mechanisms of action and potential involvement in various pathological conditions. In the current review, the authors focus on the role of lncRNAs, specifically highlighting the Myocardial Infarction Associated Transcript (MIAT), in non-oncological context. MIAT is a nuclear lncRNA that has been directly linked to myocardial infarction and is reported to control post-transcriptional processes as a competitive endogenous RNA (ceRNA) molecule. It interacts with microRNAs (miRNAs), thereby limiting the translation and expression of their respective target messenger RNA (mRNA) and regulating protein expression. Yet, MIAT has been implicated in other numerous pathological conditions such as other cardiovascular diseases, autoimmune disease, neurodegenerative diseases, metabolic diseases, and many others. In this review, the authors emphasize that MIAT exhibits distinct expression patterns and functions across different pathological conditions and is emerging as potential diagnostic, prognostic, and therapeutic agent. Additionally, the authors highlight the regulatory role of MIAT and shed light on the involvement of lncRNAs and specifically MIAT in various non-oncological pathological conditions.

Sweat as a source of non-invasive biomarkers for clinical diagnosis: An overview

Sweat has excellent potential as one of the sources of non-invasive biomarkers for clinical diagnosis. It is relatively easy to collect and process and may contain different disease-specific markers and drug metabolites, making it ideal for various clinical applications. This article discusses the anatomy of sweat glands and their role in sweat production, as well as the history and development of multiple sweat sample collection and analysis techniques. Another primary focus of this article is the application of sweat detection in clinical disease diagnosis and other life scenarios. Finally, the limitations and prospects of sweat analysis are discussed.

Association of postoperative delirium with serum and cerebrospinal fluid proteomic profiles: a prospective cohort study in older hip fracture patients

Postoperative delirium (POD) is a common neuropsychiatric complication in geriatric inpatients after hip fracture surgery and its occurrence is associated with poor outcomes. The purpose of this study was to investigate the relationship between preoperative biomarkers in serum and cerebrospinal fluid (CSF) and the development of POD in older hip fracture patients, exploring the possibility of integrating objective methods into future predictive models of delirium. Sixty hip fracture patients were recruited. Blood and CSF samples were collected at the time of spinal anesthesia when none of the subjects had delirium. Patients were assessed daily using the 4AT scale, and based on these results, they were divided into POD and non-POD groups. The Olink® platform was used to analyze 45 cytokines. Twenty-one patients (35%) developed POD. In the subsample of 30 patients on whom proteomic analyses were performed, a proteomic profile was associated with the incidence of POD. Chemokine (C-X-C motif) ligand 9 (CXCL9) had the strongest correlation between serum and CSF samples in patients with POD (rho = 0.663; p < 0.05). Although several cytokines in serum and CSF were associated with POD after hip fracture surgery in older adults, there was a significant association with lower preoperative levels of CXCL9 in CSF and serum. Despite the small sample size, this study provides preliminary evidence of the potential role of molecular biomarkers in POD, which may provide a basis for the development of new delirium predictive models.

Which neuroimaging and fluid biomarkers method is better in theranostic of Alzheimer's disease? An umbrella review

Biomarkers are measured to evaluate physiological and pathological processes as well as responses to a therapeutic intervention. Biomarkers can be classified as diagnostic, prognostic, predictor, clinical, and therapeutic. In Alzheimer's disease (AD), multiple biomarkers have been reported so far. Nevertheless, finding a specific biomarker in AD remains a major challenge. Three databases, including PubMed, Web of Science, and Scopus were selected with the keywords of Alzheimer's disease, neuroimaging, biomarker, and blood. The results were finalized with 49 potential CSF/blood and 35 neuroimaging biomarkers. To distinguish normal from AD patients, amyloid-beta42 (Aβ42), plasma glial fibrillary acidic protein (GFAP), and neurofilament light (NFL) as potential biomarkers in cerebrospinal fluid (CSF) as well as the serum could be detected. Nevertheless, most of the biomarkers fairly change in the CSF during AD, listed as kallikrein 6, virus-like particles (VLP-1), galectin-3 (Gal-3), and synaptotagmin-1 (Syt-1). From the neuroimaging aspect, atrophy is an accepted biomarker for the neuropathologic progression of AD. In addition, Magnetic resonance spectroscopy (MRS), diffusion weighted imaging (DWI), diffusion tensor imaging (DTI), tractography (DTT), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI), can be used to detect AD. Using neuroimaging and CSF/blood biomarkers, in combination with artificial intelligence, it is possible to obtain information on prognosis and follow-up on the different stages of AD. Hence physicians could select the suitable therapy to attenuate disease symptoms and follow up on the efficiency of the prescribed drug.

Double lateral flow immunosensing of undeclared pork and chicken components of meat products

Adulteration of meat products is a serious problem in the modern society. Consumption of falsified meat products can be hazardous to health and/or lead to violating religious dietary principles. To identify such products, rapid and simple test systems for point-of-need detection are in demand along with complex laboratory methods. This study presents the first double lateral flow (immunochromatographic) test system, which allows simultaneous revealing two prevalent types of falsifications-undeclared addition of pork and chicken components to meat products. In the proposed test system, porcine myoglobin (MG) and chicken immunoglobulin Y (IgY) were used as specific biomarkers recognizable by antibodies. Within the optimization of the analysis, the concentrations of the immune reagents and regimes of their application on the working membrane were selected, which provided minimal limits of detection (LODs) for both analytes. The developed test system enables the detection of MG and IgY with the LODs of 10 and 12 ng/mL, respectively, which accords to addition of 0.1% of the undeclared meat compounds. The applicability of the test system to control the composition of raw meat mixtures and cooked food products was confirmed. The developed approach can be considered as a promising tool for monitoring composition of meat products.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-024-05944-y.

Systematic review and meta-analysis of dysregulated microRNAs derived from liquid biopsies as biomarkers for amyotrophic lateral sclerosis

The discovery of disease-specific biomarkers, such as microRNAs (miRNAs), holds the potential to transform the landscape of Amyotrophic Lateral Sclerosis (ALS) by facilitating timely diagnosis, monitoring treatment response, and accelerating drug discovery. Such advancement could ultimately improve the quality of life and survival rates for ALS patients. Despite more than a decade of research, no miRNA biomarker candidate has been translated into clinical practice. We conducted a systematic review and meta-analysis to quantitatively synthesize data from original studies that analyzed miRNA expression from liquid biopsies via PCR and compared them to healthy controls. Our analysis encompasses 807 miRNA observations from 31 studies, stratified according to their source tissue. We identified consistently dysregulated miRNAs in serum (hsa-miR-3665, -4530, -4745-5p, -206); blood (hsa-miR-338-3p, -183-5p); cerebrospinal fluid (hsa-miR-34a-3p); plasma (hsa-miR-206); and neural-enriched extracellular vesicles from plasma (hsa-miR-146a-5p, -151a-5p, -10b-5p, -29b-3p, and -4454). The meta-analyses provided further support for the upregulation of hsa-miR-206, hsa-miR-338-3p, hsa-miR-146a-5p and hsa-miR-151a-5p, and downregulation of hsa-miR-183-5p, hsa-miR-10b-5p, hsa-miR-29b-3p, and hsa-miR-4454 as consistent indicators of ALS across independent studies. Our findings provide valuable insights into the current understanding of miRNAs' dysregulated expression in ALS patients and on the researchers' choices of methodology. This work contributes to the ongoing efforts towards discovering disease-specific biomarkers.

Measurements of I-FABP and citrulline in the postoperative period of non-cardiac surgeries with gastrointestinal complications: A prospective cohort observational study

BACKGROUND

Acute Gastrointestinal Injury (AGI) is associated with adverse clinical outcomes, including increased mortality. We aimed to investigate the potential of citrulline and intestinal fatty acid binding protein (I-FABP) as biomarkers for early AGI diagnosis and predicting outcomes in surgical patients.

METHODS

Prospective cohort study involving patients who underwent non-cardiac surgeries and were admitted to Intensive Care Units. AGI diagnosis was based on specific criteria, and severity was categorised following established guidelines. Statistical analyses were performed to assess the diagnostic accuracy of the biomarkers and their association with outcomes, P significant when <0.05.

RESULTS

AGI was identified in 40.3% of patients with varying severity. Mortality rates were significantly higher in the AGI group in the ICU (19.4% vs. 0%, p = 0.001) and hospital (22.6% vs. 2.17%, p = 0.003). Urinary I-FABP levels on days 3 and 7 showed reasonable and good accuracy for AGI diagnosis (AUC 0.732 and 0.813, respectively). Urinary I-FABP levels on days 2 and 3 accurately predict sepsis. Urinary citrulline levels on day one predicted mortality (AUC 0.87) furthermore urinary I-FABP levels on day 2 showed reasonable accuracy (sensitivity 83.3%, specificity 92.4%).

CONCLUSION

Urinary I-FABP and citrulline levels are promising diagnostic and prognostic markers in ICU patients following non-cardiac surgeries.

VEGF/VEGFR axis and its signaling in melanoma: Current knowledge toward therapeutic targeting agents and future perspectives

Melanoma is responsible for most skin cancer-associated deaths globally. The progression of melanoma is influenced by a number of pathogenic processes. Understanding the VEGF/VEGFR axis, which includes VEGF-A, PlGF, VEGF-B, VEGF-C, and VEGF-D and their receptors, VEGFR-1, VEGFR-2, and VEGFR-3, is of great importance in melanoma due to its crucial role in angiogenesis. This axis generates multifactorial and complex cellular signaling, engaging the MAPK/ERK, PI3K/AKT, PKC, PLC-γ, and FAK signaling pathways. Melanoma cell growth and proliferation, migration and metastasis, survival, and acquired resistance to therapy are influenced by this axis. The VEGF/VEGFR axis was extensively examined for their potential as diagnostic/prognostic biomarkers in melanoma patients and results showed that VEGF overexpression can be associated with unfavorable prognosis, higher level of tumor invasion and poor response to therapy. MicroRNAs linking to the VEGF/VEGFR axis were identified and, in this review, divided into two categories according to their functions, some of them promote melanoma angiogenesis (promotive group) and some restrict melanoma angiogenesis (protective group). In addition, the approach of treating melanoma by targeting the VEGF/VEGFR axis has garnered significant interest among researchers. These agents can be divided into two main groups: anti-VEGF and VEGFR inhibitors. These therapeutic options may be a prominent step along with the modern targeting and immune therapies for better coverage of pathological processes leading to melanoma progression and therapy resistance.

Short-term test for the toxicogenomic assessment of ecotoxic modes of action in Myriophyllum spicatum

In environmental risk assessment of substances, the 14-day growth inhibition test following OECD test guideline 239 is employed to assess toxicity in the macrophyte Myriophyllum spicatum. Currently, this test evaluates physiological parameters and does not allow the identification of the mode of action (MoA) by which adverse effects are induced. However, for an improved ecotoxicity assessment of substances, knowledge about their ecotoxic MoA in non-target organisms is required. It has previously been suggested that the identification of gene expression changes can contribute to MoA identification. Therefore, we developed a shortened three-day assay for M. spicatum including the transcriptomic assessment of global gene expression changes and applied this assay to two model substances, the herbicide and photosynthesis inhibitor bentazone and the pharmaceutical and HMG-CoA reductase inhibitor atorvastatin. Due to the lack of a reference genome for M. spicatum we performed a de novo transcriptome assembly followed by a functional annotation to use the toxicogenomic results for MoA discrimination. The gene expression changes induced by low effect concentrations of these substances were used to identify differentially expressed genes (DEGs) and impaired biological functions for the respective MoA. We observed both concentration-dependent numbers and differentiated patterns of DEGs for both substances. While bentazone impaired genes involved in the response to reactive oxygen species as well as light response, and also genes involved in developmental processes, atorvastatin exposure led to a differential regulation of genes related to brassinosteroid response as well as potential metabolic shifts between the mevalonate and methyl erythritol 4-phosphate pathway. Based on these responses, we identified biomarker candidates for the assessment of MoA in M. spicatum. Utilizing the shortened assay developed in this study, the investigation of the identified biomarker candidates may contribute to the development of future MoA-specific screening approaches in the ecotoxicological hazard prediction using aquatic non-standard model organisms.

A comprehensive guide to extract information from extracellular vesicles: a tutorial review towards novel analytical developments

In the medical field, extracellular vesicles (EVs) are gaining importance as they act as cells mediators. These are phospholipid bilayer vesicles and contain crucial biochemical information about their mother cells being carrier of different biomolecules such as small molecules, proteins, lipids, and nucleic acids. After release into the extracellular matrix, they enter the systemic circulation and can be found in all human biofluids. Since EVs reflect the state of the cell of origin, there is exponential attention as potential source of new circulating biomarkers for liquid biopsy. The use of EVs in clinical practice faces several challenges that need to be addressed: these include the standardization of lysis protocols, the availability of low-cost reagents and the development of analytical tools capable of detecting biomarkers. The process of lysis is a crucial step that can impact all subsequent analyses, towards the development of novel analytical strategies. To aid researchers to support the evolution of measurement science technology, this tutorial review evaluates and discuss the most commonly protocols used to characterize the contents of EVs, including their advantages and disadvantages in terms of experimental procedures, time and equipment. The purpose of this tutorial review is to offer practical guide to researchers which are intended to develop novel analytical approaches. Some of the most significant applications are considered, highlighting their main characteristics divided per mechanism of action. Finally, comprehensive tables which provide an overview at a glance are provided to readers.

Multilevel assessment of carbamazepine effects: An integrative approach using zebrafish early-life stages

Carbamazepine (CBZ) is the most commonly used drug in epilepsy treatment, and its metabolites are commonly detected among persistent pharmaceuticals in the aquatic environment. This study aimed to investigate CBZ effects on early-life-stage zebrafish (Danio rerio) (from 2 to 168 hpf) by employing of an integrative approach linking endpoints from molecular to individual level: (i) development; (ii) locomotor activity; (iii) biochemical markers (lactate dehydrogenase, glutathione-S-transferase, acetylcholinesterase and catalase) and (iv) transcriptome analysis using microarray. A 168 h - LC50 of 73.4 mg L-1 and a 72 h - EC50 of 66.8 mg L-1 for hatching were calculated while developmental effects (oedemas and tail deformities) were observed at CBZ concentrations above 37.3 mg L-1. At the biochemical level, AChE activity proved to be the most sensitive parameter, as evidenced by its decrease across all concentrations tested (∼25% maximum reduction, LOEC (lowest observed effect concentration) < 0.6 μg L-1). Locomotor behaviour seemed to be depressed by CBZ although this effect was only evident at the highest concentration tested (50 mg L-1). Molecular analysis revealed a dose-dependent effect of CBZ on gene expression. Although only 25 genes were deregulated in organisms exposed to CBZ when compared to controls, both 0.6 and 2812 μg L-1 treatments impaired gene expression related to development (e.g. crygmxl1, org, klf2a, otos, stx16 and tob2) and the nervous system (e.g. Rtn3, Gdf10, Rtn3), while activated genes were associated with behavioural response (e.g. prlbr and taar). Altogether, our results indicate that environmentally relevant CBZ concentrations might affect biochemical and genetic traits of fish. Thus, the environmental risk of CBZ cannot be neglected, especially in a realistic scenario of constant input of domestic effluents into aquatic systems.

Environmental fluoride exposure and implications on potential pediatric kidney health risks: an approach with urinary biomarkers

BACKGROUND

Environmental fluoride exposure at elevated levels is potentially linked to kidney injury, and may contribute to chronic kidney disease of uncertain etiology (CKDu) as a risk factor. However, this link remains unclear, and examining the risk of kidney damage from early life fluoride exposure may provide important insights. Hence, this study aimed to investigate associations of fluoride exposure with pediatric kidney health in CKDu impacted and unimpacted communities in Sri Lanka.

METHODS

Considering the geographical variations in environmental fluoride, climate, and prevalence of CKDu, four study groups were established within selected education zones in CKDu-endemic dry zone regions (D-En), and CKDu-nonendemic regions within the dry (D-NE), wet (W-NE), and intermediate (I-NE) climatic zones. The study population included 922 school students (11-18 years of age). Participants in each group were divided into four subgroups based on quartiles of respective urinary fluoride (UF) distribution for comparison of urinary kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), and albumin-creatinine ratio (ACR).

RESULTS

UF levels in participants particularly in CKDu endemic dry zone regions were significantly high compared to the other regions. Significantly high median urinary NGAL (in D-NE) and ACR (in D-EN, and W-NE) levels were observed in subgroups of higher UF quartiles. Albuminuria was not particularly identified in subjects with high UF excretion. Urinary KIM-1 showed no significant variation across the UF quartile subgroups. Linear regression identified weak associations of UF with kidney injury biomarkers.

CONCLUSIONS

Fluoride exposure is particularly high in CKDu-endemic dry zone communities. As implied by kidney injury biomarkers, a strong link between fluoride exposure and pediatric kidney health was not evident at the observed exposure levels in the study regions.

Develop and Validate a Prognostic Index With Laboratory Tests to Predict Mortality in Middle-Aged and Older Adults Using Machine Learning Models: A Prospective Cohort Study

BACKGROUND

Prognostic indices can enhance personalized predictions of health burdens. However, a simple, practical, and reproducible tool is lacking for clinical use. This study aimed to develop a machine learning-based prognostic index for predicting all-cause mortality in community-dwelling older individuals.

METHODS

We utilized the Healthy Aging Longitudinal Study in Taiwan (HALST) cohort, encompassing data from 5 663 participants. Over the 5-year follow-up, 447 deaths were confirmed. A machine learning-based routine blood examination prognostic index (MARBE-PI) was developed using common laboratory tests based on machine learning techniques. Participants were grouped into multiple risk categories by stratum-specific likelihood ratio analysis based on their MARBE-PI scores. The MARBE-PI was subsequently externally validated with an independent population-based cohort from Japan.

RESULTS

Beyond age, sex, education level, and BMI, 6 laboratory tests (low-density lipoprotein, albumin, aspartate aminotransferase, lymphocyte count, high-sensitivity C-reactive protein, and creatinine) emerged as pivotal predictors via stepwise logistic regression (LR) for 5-year mortality. The area under curves of MARBE-PI constructed by LR were 0.799 (95% confidence interval [95% CI]: 0.778-0.819) and 0.756 (95% CI: 0.694-0.814) for the internal and external validation data sets, and were 0.801 (95% CI: 0.790-0.811) and 0.809 (95% CI: 0.774-0.845) for the extended 10-year mortality in both data sets, respectively. Risk categories stratified by MARBE-PI showed a consistent dose-response association with mortality. The MARBE-PI also performed comparably with indices constructed with clinical health deficits and/or laboratory results.

CONCLUSIONS

The MARBE-PI is considered the most applicable measure for risk stratification in busy clinical settings. It holds potential to pinpoint older individuals at elevated mortality risk, thereby aiding clinical decision-making.

Using machine learning to identify proteomic and metabolomic signatures of stroke in atrial fibrillation

Atrial fibrillation (AF) is a common cardiac arrhythmia, with stroke being its most detrimental comorbidity. The exact mechanism of AF related stroke (AFS) still needs to be explored. In this study, we integrated proteomics and metabolomics platform to explore disordered plasma proteins and metabolites between AF patients and AFS patients. There were 22 up-regulated and 31 down-regulated differentially expressed proteins (DEPs) in AFS plasma samples. Moreover, 63 up-regulated and 51 down-regulated differentially expressed metabolites (DEMs) were discovered in AFS plasma samples. We integrated proteomics and metabolomics based on the topological interactions of DEPs and DEMs, which yielded revealed several related pathways such as arachidonic acid metabolism, serotonergic synapse, purine metabolism, tyrosine metabolism and steroid hormone biosynthesis. We then performed a machine learning model to identify potential biomarkers of stroke in AF. Finally, we selected 6 proteins and 6 metabolites as candidate biomarkers for predicting stroke in AF by random forest, the area under the curve being 0.976. In conclusion, this study provides new perspectives for understanding the progressive mechanisms of AF related stroke and discovering innovative biomarkers for determining the prognosis of stroke in AF.

Trimethylamine N-oxide, β-alanine, tryptophan index, and vitamin B6-related dietary patterns in association with stroke risk

BACKGROUND AND AIMS

The aim of this study was to examine the associations of dietary patterns derived by reduced-rank regression (RRR) model reflecting variation in novel biomarkers (trimethylamine N-oxide, β-alanine, tryptophan index, and vitamin B6) with stroke risk.

METHODS AND RESULTS

We performed analyses based on a community-based cohort study "the Prospective Follow-up Study on Cardiovascular Morbidity and Mortality in China (PFS-CMMC)". Factor loadings were calculated by RRR using 11 food groups collected via a validated food frequency questionnaire and the four response variables based on its nested case-control data (393 cases of stroke vs. 393 matched controls). Dietary pattern scores were derived by applying the factor loadings to the food groups in the entire cohort (n = 15,518). The associations of dietary pattern with the stroke risk were assessed using Cox proportional hazards models. The dietary pattern characterized with higher intakes of red meat and poultry but lower intakes of fresh vegetables, fresh fruits, and fish/seafoods were identified for further analyses. The hazard ratios (HR) for the highest vs. lowest quartile was 1.55 [95 % confidence interval (CI): 1.18-2.03, P trend = 0.001] for total stroke, 2.96 [95 % CI: 1.53-5.71, P trend <0.001] for non-ischemic stroke, after adjustment for sex, age, educational attainment, current smoking, current drinking, body mass index, total energy intake, family history of stroke, hypertension, diabetes, hyperlipidemia, and estimated glomerular filtration rate.

CONCLUSION

Our findings highlight the importance of limited meat intake and increased intakes of fresh vegetables, fruits, and fish/seafoods in the prevention of stroke among Chinese adults.

Can environmental factors increase oxidative responses in fish exposed to polycyclic aromatic hydrocarbons (PAHs)?

Relations among polycyclic aromatic hydrocarbons (PAHs), biomarkers of oxidative stress (lipid peroxidation, glutathione, and glutathione S-transferase activity), and the possible influence of environmental factors (temperature, pH, and salinity) were assessed in situ for specimens of Ramnogaster arcuata, a native estuarine fish. PAH levels found in the muscular tissue of R. arcuata ranged from 0.7 to 293.4 ng g-1 wet weight with petrogenic and pyrolytic inputs. Lipid peroxidation in the liver showed positive correlations (P < 0.05) with total PAHs (r = 0.66), 3-ring (r = 0.66) and 4-ring PAHs (r = 0.52) and glutathione in muscle (r = 0.58). Significant positive correlations (P < 0.05) were also evidenced between muscular glutathione with total (r = 0.62) and 3-ring PAHs (r = 0.75). Hepatic glutathione S-transferase negatively correlated with 4-ring PAHs (r = -0.58). These correlations suggest that lipid peroxidation and muscular glutathione could be good biomarkers for complex mixtures of PAHs, and hepatic glutathione S-transferase could be a suitable biomarker for 4-ring PAHs. Furthermore, significant correlations (P < 0.05) of environmental factors with PAH levels and biomarkers were observed, especially pH with 3-ring PAHs (r = -0.65), lipid peroxidation (r = -0.6), glutathione in the liver (r = -0.73) and muscle (r = -0.75); and temperature with 2-ring PAHs (r = -0.75) and glutathione in muscle (r = 0.51). The data suggest an influence of physicochemical parameters which could be driving a shift in PAH toxicity in R. arcuata. These results are essential for an integrated understanding of ecotoxicology and could help to predict environmental effects in present and future scenarios of ocean warming and acidification.

Detection of Naturally occurring abortive transcripts by Base-Stacking Hybridization Assisted Ligation and PCR amplification

Abortive transcripts (ATs) refer to nascent 2-10 nucleotides (nt) RNAs released by RNA polymerases before synthesizing productive RNAs. The quantitative detection of ATs is important for studying transcription initiation and the biological function of ATs; however, no method is available for the qualitative and quantitative assessment of such ultra-short oligonucleotides (typically shorter than 11 nt) in vivo at present, even with the LNA probes, the detection limit can only reach 11 nt. Here, we demonstrated the base stacking hybridization assisted ligation (BSHAL) technique, combined with TaqMan-MGB qPCR, can detect 4-10 nt ATs with a specificity of nucleotide resolution and a sensitivity of approximately 10 pM. By this technique, we detected endogenous ATs in cell lines, mice plasmas, and mice liver tissues, respectively, and proved that naturally occurring ATs do exist. We found that the 8 nt ATs of HMSB and Gapdh could be used as reference ATs for data normalization in Homo and mouse respectively, and 8 nt ATs of Afp and Gpc3 were suitable for use as plasma biomarkers of Hepatocellular carcinoma in mouse, indicate ATs are promising biomarkers. This study offers opportunities to study ATs and other ultra-short oligonucleotides in biological samples.

Comparative analysis of electrochemical and optical sensors for detection of chronic wounds biomarkers: A review

Chronic wounds (CW) present a significant healthcare challenge due to their prolonged healing time and associated complications. To effectively treat these wounds and prevent further deterioration, monitoring their healing progress is crucial. Traditional wound assessment methods relying on visual inspection and subjective evaluation are prone to inter-observer variability. Biomarkers play a critical role in objectively evaluating wound status and predicting healing outcomes, providing quantitative measures of wound healing progress, inflammation, infection, and tissue regeneration. Recent attention has been devoted to identifying and validating CW biomarkers. Various studies have investigated potential biomarkers, including growth factors, cytokines, proteases, and extracellular matrix components, shedding light on the complex molecular and cellular processes within CW. This knowledge enables a more targeted and personalized approach to wound management. Accurate and sensitive techniques are necessary for detecting CW biomarkers. Thus, this review compares and discusses the use of electrochemical and optical sensors for biomarker determination. The advantages and disadvantages of these sensors are highlighted. Differences in detection capabilities and characteristics such as non-invasiveness, portability, high sensitivity, specificity, simplicity, cost-effectiveness, compatibility with point-of-care applications, and real-time monitoring of wound biomarkers will be pointed out and compared. In summary, this work provides an overview of CW, explores the emerging field of CW biomarkers, and discusses methods for detecting these biomarkers, with a specific focus on optical and electrochemical sensors. The potential of further research and development in this field for advancing wound care and improving patient outcomes will also be noted.

miRNA expression in PCOS: unveiling a paradigm shift toward biomarker discovery

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder that affects a substantial percentage of women, estimated at around 9-21%. This condition can lead to anovulatory infertility in women of childbearing age and is often accompanied by various metabolic disturbances, including hyperandrogenism, insulin resistance, obesity, type-2 diabetes, and elevated cholesterol levels. The development of PCOS is influenced by a combination of epigenetic alterations, genetic mutations, and changes in the expression of non-coding RNAs, particularly microRNAs (miRNAs). MicroRNAs, commonly referred to as non-coding RNAs, are approximately 22 nucleotides in length and primarily function in post-transcriptional gene regulation, facilitating mRNA degradation and repressing translation. Their dynamic expression in different cells and tissues contributes to the regulation of various biological and cellular pathways. As a result, they have become pivotal biomarkers for various diseases, including PCOS, demonstrating intricate associations with diverse health conditions. The aberrant expression of miRNAs has been detected in the serum of women with PCOS, with overexpression and dysregulation of these miRNAs playing a central role in the atypical expression of endocrine hormones linked to PCOS. This review takes a comprehensive approach to explore the upregulation and downregulation of various miRNAs present in ovarian follicular cells, granulosa cells, and theca cells of women diagnosed with PCOS. Furthermore, it discusses the potential for a theragnostic approach using miRNAs to better understand and manage PCOS.

Systemic inflammation in relation to exceptional memory in the Long Life Family Study (LLFS)

Background and objectives

We previously found a substantial familial aggregation of healthy aging phenotypes, including exceptional memory (EM) in long-lived persons. In the current study, we aim to assess whether long-lived families with EM and without EM (non-EM) differ in systemic inflammation status and trajectory.

Methods

The current study included 4333 participants of the multi-center Long Life Family Study (LLFS). LLFS families were classified as EM (556 individuals from 28 families) or non-EM (3777 individuals from 416 families), with 2 or more offspring exhibiting exceptional memory performance (i.e. having baseline composite z-score representing immediate and delayed story memory being 1.5 SD above the mean in the nondemented offspring sample) considered as EM. Blood samples from baseline were used to measure inflammatory biomarkers including total white blood cell (WBC) and its subtypes (neutrophils, lymphocytes, monocytes) count, platelet count, high sensitivity C-reactive protein, and interleukin-6. Generalized linear models were used to examine cross-sectional differences in inflammatory biomarkers at baseline. In a sub-sample of 2227 participants (338 subjects from 24 EM families and 1889 from 328 non-EM families) with repeated measures of immune cell counts, we examined whether the rate of biomarker change differed between EM and non-EM families. All models were adjusted for family size, relatedness, age, sex, education, field center, APOE genotype, and body mass index.

Results

LLFS participants from EM families had a marginally higher monocyte count at baseline (b = 0.028, SE = 0.0110, p = 0.010) after adjusting for age, sex, education, and field site, particularly in men (p < 0.0001) but not in women (p = 0.493) (p-interaction = 0.003). Over time, monocyte counts increased (p < 0.0001) in both EM and non-EM families, while lymphocytes and platelet counts decreased over time in the non-EM families (p < 0.0001) but not in the EM families. After adjusting for multiple variables, there was no significant difference in biomarker change over time between the EM and non-EM families.

Discussion

Compared with non-EM families, EM families had significantly higher monocyte count at baseline but had similar change over time. Our study suggests that differences in monocyte counts may be a pathway through which EM emerges in some long-lived families, especially among men.

A New Approach to Staging Diabetic Eye Disease: Staging of Diabetic Retinal Neurodegeneration and Diabetic Macular Edema

Topic

The goal of this review was to summarize the current level of evidence on biomarkers to quantify diabetic retinal neurodegeneration (DRN) and diabetic macular edema (DME).

Clinical relevance

With advances in retinal diagnostics, we have more data on patients with diabetes than ever before. However, the staging system for diabetic retinal disease is still based only on color fundus photographs and we do not have clear guidelines on how to incorporate data from the relatively newer modalities into clinical practice.

Methods

In this review, we use a Delphi process with experts to identify the most promising modalities to identify DRN and DME. These included microperimetry, full-field flash electroretinogram, spectral-domain OCT, adaptive optics, and OCT angiography. We then used a previously published method of determining the evidence level to complete detailed evidence grids for each modality.

Results

Our results showed that among the modalities evaluated, the level of evidence to quantify DRN and DME was highest for OCT (level 1) and lowest for adaptive optics (level 4).

Conclusion

For most of the modalities evaluated, prospective studies are needed to elucidate their role in the management and outcomes of diabetic retinal diseases.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Vasohibin-1 Expression Can Predict Pathological Complete Remission of Advanced Bladder Cancer with Neoadjuvant Chemotherapy

BACKGROUND AND PURPOSE

Neoadjuvant chemotherapy (NAC) is a well-established standard practice in invasive bladder cancer (BCa), however patient selection remains challenging. High expression of vasohibin-1 (VASH1), an endogenous regulator of angiogenesis, has been reported in high-grade and advanced BCa; however, its prognostic value for chemotherapy outcomes remains unexplored. In this study, we sought to identify biomarkers of chemotherapy response focusing on the relationship between angiogenesis and tissue hypoxia.

METHODS

Forty Japanese patients with BCa who underwent NAC and radical cystectomy were included in the present analysis. We compared the immunohistochemical expression of CD34, VASH1, and carbonic anhydrase 9 (CA9) between patients who achieved tumor clearance at operation (ypT0) and those with residual disease after cystectomy.

RESULTS

There were 19 patients in the ypT0 group, while the remaining 21 patients had residual tumors at operation. Patients in the ypT0 group had high microvessel density (p = 0.031), high VASH1 density (p < 0.001), and stronger CA9 staining (p = 0.046) than their counterparts. Multivariate analysis identified microvessel and VASH1 density as independent predictive factors for pathological ypT0 disease (p = 0.043 and 0.002, respectively). The 5-year recurrence-free survival rate was higher in the high VASH1 density group than in the low VASH1 density group (66.3% vs. 33.3%, p = 0.036).

CONCLUSION

VASH1 density is a potential therapeutic biomarker for chemotherapy response in BCa.

High linoleic acid levels in red blood cells predict a poor response to neoadjuvant chemotherapy in human epidermal growth factor receptor type 2-positive breast cancer patients

OBJECTIVE

Polyunsaturated fatty acids are categorized as ω-3 or ⍵-6. Previous studies demonstrate that breast cancers display a high expression of fatty acid synthase and high fatty acid levels. Our study sought to determine if changes in plasma or red blood cell membrane fatty acid levels were associated with the response to preoperative (neoadjuvant) chemotherapy in non-metastatic breast cancer patients.

METHODS

Our prospective study assessed fatty acid levels in plasma and red blood cell membrane. Response to neoadjuvant chemotherapy was evaluated by the presence or absence of pathologic complete response and/or residual cancer burden.

RESULTS

A total of 28 patients were included. First, patients who achieved pathologic complete response had significantly higher neutrophil-to-lymphocyte ratio versus no pathologic complete response (P = 0.003). Second, total red blood cell membrane polyunsaturated fatty acids were higher in the absence of pathologic complete response (P = 0.0028). Third, total red blood cell membrane ⍵-6 polyunsaturated fatty acids were also higher in no pathologic complete response (P < 0.01). Among ⍵-6 polyunsaturated fatty acids, red blood cell membrane linoleic acid was higher in the absence of pathologic complete response (P < 0.01). Notably, plasma polyunsaturated fatty acid, ⍵-6, and linoleic acid levels did not have significant differences. A multivariate analysis confirmed red blood cell membrane linoleic acid was associated with no pathologic complete response; this was further confirmed by receiver operating characteristic analysis (specificity = 92.3%, sensitivity = 76.9%, and area under the curve = 0.855).

CONCLUSIONS

Pending further validation, red blood cell membrane linoleic acid might serve as a predictor biomarker of poorer response to neoadjuvant chemotherapy in non-metastatic human epidermal growth factor receptor type 2-positive breast cancer. Measuring fatty acids in red blood cell membrane could offer a convenient, minimally invasive strategy to identifying patients more likely to respond or those with chemoresistance.

Association of Intermediate-Stage Age-Related Macular Degeneration with Plasma Inflammatory Biomarkers in Persons with AIDS

Purpose

To evaluate associations of plasma levels of inflammatory biomarkers with age-related macular degeneration (AMD) and cataract in persons with AIDS.

Design

Nested case-control study (analysis 1) and nested cohort study (analysis 2).

Participants

Analysis 1: persons with AIDS and incident intermediate-stage AMD (n = 26) and controls without AMD matched for age, race/ethnicity, and gender (n = 49) from The Longitudinal Study of Ocular Complications of AIDS. Analysis 2: 475 persons from LSOCA with baseline plasma biomarker levels followed prospectively for cataract.

Methods

In both analyses, cryopreserved plasma specimens obtained at baseline were assayed for monocyte chemoattractant protein (MCP)-1 (CC motif chemokine ligand [CCL] 2), macrophage inflammatory protein (MIP)-1β (CCL4), soluble tumor necrosis factor receptor (sTNFR) 2, interleukin (IL)-18, and fractalkine (CX3 motif chemokine ligand 1 [CX3CL1]).

Main Outcome Measures

Analysis 1: mean difference (cases - controls) in plasma biomarker levels. Analysis 2: incident cataract.

Results

After adjusting for plasma human immunodeficiency virus RNA level, CD4+ T-cell count, and smoking, elevated baseline plasma levels of sTNFR2 and IL-18 (mean differences [cases - controls] 0.11 log10[pg/mL]; 95% confidence interval [CI], 0.01-0.20; P = 0.024 and 0.13 log10[pg/mL]; 95% CI, 0.01-0.24; P = 0.037, respectively) each were associated with incident AMD. In a competing risk (with mortality) analysis, elevated baseline standardized log10 plasma levels of MCP-1, sTNFR2, IL-18, and fractalkine each were associated with a decreased cataract risk.

Conclusions

When combined with previous data suggesting that AMD is associated with elevated plasma levels of C-reactive protein, soluble CD14, and possibly IL-6, the association of elevated plasma levels of sTNFR2 and IL-18 with incident AMD, but not with incident cataract, suggests that innate immune system activation, and possibly NLRP3 inflammasome activation, may play a role in the pathogenesis of AMD in this population.

Financial Disclosures

The authors have no proprietary or commercial interest in any materials discussed in this article.

A systematic review and meta-analysis of mortality and kidney function in uranium-exposed individuals

BACKGROUND

Humans are exposed to uranium (U) in a variety of applications. Both animal and observational human studies support an associated U nephrotoxicity. Few statistical syntheses of the human data have been performed and these analyses are limited in the types of exposures considered.

OBJECTIVES

This study aims to evaluate the state of current evidence and to expand on existing meta-analyses by systematically evaluating kidney-associated causes of mortality in multiple U-exposed populations. This study also aims to evaluate the effect of U exposure on kidney function and biomarkers of kidney injury.

METHODS

The published and grey literature were systematically reviewed for studies that reported Standardized Mortality Ratios (SMR) for kidney cancer, chronic nephritis/nephrosis, all-cause mortality, diabetes, all circulatory/heart disease, and/or ischemic heart disease in U-exposed humans. Studies that reported kidney biomarker measures for U-exposed versus control subjects were identified separately.

RESULTS

36 studies were included. The studies were parsed into subgroups based on setting of exposure. Analysis of kidney cancer and chronic nephritis/nephrosis mortality demonstrated an SMR of 0.93 (95CI: 0.82-1.05) and 0.82 (95CI: 0.70-0.96), respectively. The other clinical outcomes evaluated also demonstrated mortality deficits in exposed relative to unexposed individuals. Subgroup analyses demonstrated similar mortality deficits. Conversely, biomarker analyses suggested better kidney function in the controls, but none of these differences reached significance.

DISCUSSION

Given that most of the included mortality studies were conducted in occupational populations, the mortality deficits observed in our analyses were likely due to the healthy-worker effect. Additionally, our analyses of kidney biomarkers were severely limited by low precision due to a low number of available studies and small study-size. Future work needs to evaluate the progression of chronic and to end-stage kidney disease in community-based populations to better assess the full impact of prolonged chronic U exposure on kidney outcomes.

Comprehensive profiling of amino acids and derivatives in biological samples: A robust UHPLC-MS/MS method for investigating acute lung injury

The severe respiratory dysfunctions associated with acute lung injury (ALI) and its sequelae have a high morbidity and mortality rate, are multifactorial, and lack a viable treatment. Considering the critical function that amino acids and derivatives play in the genesis of illnesses and the regulation of metabolic processes, monitoring the levels of metabolites associated with amino acids in biological matrices is necessary and interesting to study their pathological mechanisms. Exploring the dynamics of amino acids and derivatives level and searching for biomarkers provides improved clinical ideas for the diagnosis and treatment of ALI. Therefore, we developed an ultra-high-performance liquid chromatography-electrospray tandem mass spectrometry (UHPLC-MS/MS) method that can simultaneously determine the amino acid and derivatives metabolic levels to study amino acid profiles in different biological samples to facilitate clinical research of ALI. In this study, 48 amino acids and derivatives, including neurotransmitters, polyamines, purines, and other types, were quantified simultaneously in a fast, high-throughput, sensitive, and reliable manner within a 15-minute run time without derivatization. No relevant studies have been reported to quantify these 48 amino acid metabolites in three biological samples simultaneously. Satisfactory linearity (R > 0.995), inter-day and intra-day accuracy (85.17-112.67 % and 85.29-111.60 %, respectively), inter-day and intra-day precision (RSD < 13.80 % and RSD < 12.01 %, respectively), matrix effects (81.00 %-118.00 %), recovery (85.09 %-114.65 %) and stability (RSD < 14.72 %) were all demonstrated by the optimized method's successful validation for all analytes. In addition, the suggested method was effectively implemented in plasma, urine, and lung tissue from normal mice and mice with ALI, with the aim of finding potential biomarkers associated with ALI. Potential biomarkers were screened through multivariate statistical analysis and volcanic map analysis, and the changes of markers in ALI were again identified through heat map analysis and correlation analysis with biochemical indicators, which provided ideas and references for subsequent mechanism studies. Here, the technique created in this work offers a quick and dependable way to perform an integrated analysis of amino acids in a variety of biological materials, which can provide research ideas for understanding the physiopathological state of various diseases.

Des-gamma-carboxy prothrombin and alpha-fetoprotein levels as biomarkers for hepatocellular carcinoma and their correlation with radiological characteristics

BACKGROUND

Alpha-fetoprotein (AFP), a commonly used biomarker for hepatocellular carcinoma (HCC), is normal in up to one-third of patients.

AIM

To evaluate the diagnostic performance of des-gamma-carboxy-prothrombin (DCP) alone and in combination with AFP.

METHODS

In this study, 202 patients with radiologically proven HCC were enrolled, and their DCP and AFP levels were evaluated for their diagnostic performance.

RESULTS

The mean age of the enrolled patients was 58.5 years; 72.0% were male. DCP was elevated in 86.6% (n = 175) of all patients, 100.0% (n = 74) of patients with portal vein thrombus, and 87.4% (n = 111) of patients with multicentric HCC. AFP was elevated in 64.3% (n = 130) of all the patients, 74% (n = 55) of the patients with portal vein thrombus, and 71.6% (n = 91) of the patients with multicentric HCC (P = 0.030, 0.001, and 0.015, respectively). In tumors less than 2 cm in size (n = 46), DCP was increased in 32 (69.5%) patients, and AFP was increased in 25 (54.3%) patients (P = 0.801). There was good pairing between DCP and AFP for HCCs of 2 cm size or larger (P < 0.001); however, the pairing among tumors < 2 cm size was not significant (P = 0.210). In 69 of the patients (34.1%), only one of the tumor markers was positive; DCP was elevated alone in 57/202 (28.2%) of all patients, and AFP alone was elevated in 12/202 (5.9%) of the patients. The areas under receiver operating characteristic curves (AUROC) for tumors > 2 cm was 0.74 for DCP and 0.59 for AFP; combining both markers resulted in an AUROC of 0.73. For tumors < 2 cm, the AUROC was 0.25 for DCP and 0.40 for AFP.

CONCLUSION

DCP, as an individual marker, had a better diagnostic performance in many cases of HCC. Hence, DCP may replace AFP as the primary HCC biomarker.

Dodecyl creatine ester therapy: from promise to reality

Pathogenic variants in SLC6A8, the gene which encodes creatine transporter SLC6A8, prevent creatine uptake in the brain and result in a variable degree of intellectual disability, behavioral disorders (e.g., autism spectrum disorder), epilepsy, and severe speech and language delay. There are no treatments to improve neurodevelopmental outcomes for creatine transporter deficiency (CTD). In this spotlight, we summarize recent advances in innovative molecules to treat CTD, with a focus on dodecyl creatine ester, the most promising drug candidate.

Chilled Pacu (Piaractus mesopotamicus) fillets: Modeling Pseudomonas spp. and psychrotrophic bacteria growth and monitoring spoilage indicators by 1H NMR and GC-MS during storage

This study aimed to assess the growth of Pseudomonas spp. and psychrotrophic bacteria in chilled Pacu (Piaractus mesopotamicus), a native South American fish, stored under chilling conditions (0 to 10 °C) through the use of predictive models under isothermal and non-isothermal conditions. Growth kinetic parameters, maximum growth rate (μmax, 1/h), lag time (tLag, h), and (Nmax, Log10 CFU/g) were estimated using the Baranyi and Roberts microbial growth model. Both kinetic parameters, growth rate and lag time, were significantly influenced by temperature (P < 0.05). The square root secondary model was used to describe the bacteria growth as a function of temperature. Secondary models, √μ = 0.016 (T + 10.13) and √μ =0.017 (T + 9.91) presented a linear correlation with R2 values >0.97 and were further validated under non-isothermal conditions. The model's performance was considered acceptable to predict the growth of Pseudomonas spp. and psychrotrophic bacteria in refrigerated Pacu fillets with bias and accuracy factors between 1.24 and 1.49 (fail-safe) and 1.45-1.49, respectively. Fish biomarkers and spoilage indicators were assessed during storage at 0, 4, and 10 °C. Volatile organic compounds, VOCs (1-hexanol, nonanal, octenol, and indicators 2-ethyl-1-hexanol) showed different behavior with storage time (P > 0.05). 1H NMR analysis confirmed increased enzymatic and microbial activity in Pacu fillets stored at 10 °C compared to 0 °C. The developed and validated models obtained in this study can be used as a tool for decision-making on the shelf-life and quality of refrigerated Pacu fillets stored under dynamic conditions from 0 to 10 °C.

Design, cohort profile and comparison of the KTD-Innov study: a prospective multidimensional biomarker validation study in kidney allograft rejection

There is an unmet need for robust and clinically validated biomarkers of kidney allograft rejection. Here we present the KTD-Innov study (ClinicalTrials.gov, NCT03582436), an unselected deeply phenotyped cohort of kidney transplant recipients with a holistic approach to validate the clinical utility of precision diagnostic biomarkers. In 2018-2019, we prospectively enrolled consecutive adult patients who received a kidney allograft at seven French centers and followed them for a year. We performed multimodal phenotyping at follow-up visits, by collecting clinical, biological, immunological, and histological parameters, and analyzing a panel of 147 blood, urinary and kidney tissue biomarkers. The primary outcome was allograft rejection, assessed at each visit according to the international Banff 2019 classification. We evaluated the representativeness of participants by comparing them with patients from French, European, and American transplant programs transplanted during the same period. A total of 733 kidney transplant recipients (64.1% male and 35.9% female) were included during the study. The median follow-up after transplantation was 12.3 months (interquartile range, 11.9-13.1 months). The cumulative incidence of rejection was 9.7% at one year post-transplant. We developed a distributed and secured data repository in compliance with the general data protection regulation. We established a multimodal biomarker biobank of 16,736 samples, including 9331 blood, 4425 urinary and 2980 kidney tissue samples, managed and secured in a collaborative network involving 7 clinical centers, 4 analytical platforms and 2 industrial partners. Patients' characteristics, immune profiles and treatments closely resembled those of 41,238 French, European and American kidney transplant recipients. The KTD-Innov study is a unique holistic and multidimensional biomarker validation cohort of kidney transplant recipients representative of the real-world transplant population. Future findings from this cohort are likely to be robust and generalizable.

Decreased serpin C1 in extracellular vesicles predicts response to methotrexate treatment in patients with pulmonary sarcoidosis

BACKGROUND

Sarcoidosis is a systemic granulomatous disease of unknown etiology primarily affecting the lungs. Treatment is needed when disease symptoms worsen and organ function deteriorates. In pulmonary sarcoidosis, prednisone and methotrexate (MTX) are the most common anti-inflammatory therapies. However, there is large inter-patient variability in response to treatment, and predictive response markers are currently lacking.

OBJECTIVE

In this study, we investigated the predictive potential of biomarkers in extracellular vesicles (EVs) isolated from biobanked serum of patients with pulmonary sarcoidosis stored prior to start of therapy.

METHODS

Protein concentrations of a four-protein test panel of inflammatory proteins were measured in a discovery (n = 16) and replication (n = 129) cohort of patients with sarcoidosis and 47 healthy controls. Response to therapy was defined as an improvement of the absolute score of > 5% forced vital capacity (FVC) and/or > 10% diffusion lung of carbon monoxide (DLCO) after 24 weeks compared to baseline (before treatment).

RESULTS

Serum protein levels differed between EV fractions and serum, and between sarcoidosis cases and controls. Serpin C1 concentrations in the low density lipid particle EV fraction were lower at baseline in the group of patients with a good response to MTX treatment in both the discovery cohort (p = 0.059) and in the replication cohort (p = 0.032). EV Serpin C1 showed to be a significant predictor for response to treatment with MTX (OR 0.4; p = 0.032).

CONCLUSION

This study shows that proteins isolated from EVs harbor a distinct signal and have potential as new predictive therapy response biomarkers in sarcoidosis.