Despite curative-intent local therapy, approximately 27% to 53% of prostate cancer (PCa) patients experience prostate-specific antigen (PSA) recurrence, known as biochemical recurrence (BCR). BCR significantly raises the risk of PCa-related morbidity and mortality, yet there is not consensus on optimal management. Prostate-specific membrane antigen-positron emission tomography (PSMA PET) has emerged as highly sensitive imaging, distinguishing local recurrences from distant metastases, crucially influencing treatment decisions. Genomic biomarkers such as Decipher, Prolaris, and Oncotype DX contribute to refining recurrence risk profiles, guiding decisions on intensifying adjuvant therapies like radiotherapy and androgen deprivation therapy (ADT). This review assesses PSMA PET and biomarkers utility in post-radical prostatectomy BCR scenarios, highlighting their impact on clinical decision-making. Despite their promising roles, routine integration of biomarkers is limited by availability and cost, requiring further evidence. PSMA PET remains indispensable for restaging and treatment evaluation in these patients. Integrating biomarkers and PSMA PET promises to optimize personalized management strategies for BCR, though more comprehensive consensus-building studies are needed to define their standardized utility in clinical practice.

The human phospholipase B-II precursor (HPLBII-P) was originally purified from white blood cells but is also found in other cellular structures such as kidney glomeruli and tubuli. The objective of this report was to investigate the relationship of HPLBII-P in urine to acute kidney injury in patients with COVID-19 Methods Urine was collected at admission from 132 COVID-19 patients admitted to the intensive care units (ICU) because of respiratory failure. HPLBII-P was measured by a sensitive ELISA. For comparison, HNL was measured in urine, by the ELISA configured with mabs 763/8F, as a sign of tubular affection in addition to routine biomarkers of kidney disease Results Overall, the concentrations of urinary HPLBII-P were almost 3-fold higher in COVID-19 patients as compared to healthy controls (p

People with HIV (PWH) experience higher rates of cardiovascular events (CVEs) compared with the general population. A substantial body of evidence supports that select biomarkers of inflammation (soluble CD14 [sCD14], soluble CD163 [sCD163], highly sensitive C-reactive protein [hs-CRP], interleukin-6 [IL-6]), and coagulation (D-dimer) are elevated in PWH and related to increased rates of CVEs. Our previous work showed that smoking compared with nonsmoking was associated with significantly elevated sCD14, a biomarker of monocyte activation. We aimed to explore the effect of electronic cigarette (EC) provision on inflammatory biomarkers in PWH who smoked daily and then switched to an EC. Nineteen PWH were enrolled in a pilot study in which an EC and e-liquid were provided weekly or 8 weeks. Blood specimens for inflammatory biomarker analysis were obtained at baseline (BL) and at week 8. Biomarker levels were high at BL and did not differ significantly at week 8. There were small nonsignificant reductions in sCD163 and CRP levels. Non-significant increases in IL-6, D-dimer and sCD14 levels were also noted. Use of ECs for 8 weeks does not appear to significantly increase or decrease inflammatory biomarker levels in SWH. Further research with larger samples and a control group is needed.

Minerals might have played critical roles for the origin and evolution of possible life forms on Mars. The study of the interactions between “building blocks of life” and minerals relevant to Mars mineralogy under conditions mimicking the harsh Martian environment may provide key insight into possible prebiotic processes. Therefore, this contribution aims at reviewing the most important investigations carried out so far about the catalytic/protective properties of Martian minerals toward molecular biosignatures under Martian-like conditions. Overall, it turns out that the fate of molecular biosignatures on Mars depends on a delicate balance between multiple preservation and degradation mechanisms often regulated by minerals, which may take place simultaneously. Such a complexity requires more efforts in simulating realistically the Martian environment in order to better inspect plausible prebiotic pathways and shed light on the nature of the organic compounds detected both in meteorites and on the surface of Mars through in situ analysis.

Predictive biomarkers for immune checkpoint inhibitors (ICI), such as PD-L1 expression (TPS), remain limited in clinical applications. Improved novel ICI predictive biomarkers are urgently needed. We evaluated a live single-cell functional liquid biopsy cytokine profiling platform to track immunotherapy treatment response and outcomes. Peripheral blood mononuclear cell samples of healthy donors and NSCLC patients undergoing ICI-based therapies were collected longitudinally pre-/post-treatment under IRB-approved protocols. Samples were enriched for CD4+ and CD8+ T-lymphocytes and analyzed on the IsoLight platform. The single T-cells were captured in microchambers on IsoCode chips for cytokines profiling. Functional polyfunctionality data from 55,775 single cells were analyzed using the IsoSpeak software, kappa coefficient, and Kaplan-Meier survival plots. We found a significant difference between responders and non-responders in CD8+ T-cells’ changes in overall polyfunctionality and polyfunctional strength index (ΔPSI). ΔPSI score in CD8+ T-cells performed better than PD-L1 TPS and, when combined with PD-L1 TPS, strongly correlated with early ICI treatment response with a kappa coefficient of 1.0 (p=0.003). High CD4+ T-cells ΔPSI predicted a strong trend of improved PFS (3.9-fold) and OS (3-fold). In conclusion, single peripheral T-cell polyfunctionality dynamics analysis is a promising liquid biopsy profiling platform as NSCLC ICI predictive biomarker regardless of oncogene-addiction status.

Abstract Aim: The study aimed to evaluate the clinical laboratory features of moderate and severe COVID-19 patients among a cohort of the Egyptian population. The study also aimed to assess the accuracy—sensitivity, specificity, and area under the curve (AUC) of various detected parameters in predicting the severity of COVID-19 infection. Patients and methods: One hundred diagnosed COVID-19 patients and fifty healthy participants in total were involved in current study. COVID-19 patients were categorized based on how severe their symptoms into two groups. Estimates were made for serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), albumin, lactate dehydrogenase (LDH) and C-reactive protein (CRP) as well as white blood cells (WBCs) count, lymphocytes count, and hemoglobin content (Hb) content. Results: COVID-19 patients displayed increased serum levels of liver enzymes and CRP as well as WBCs count when compared to healthy individuals. On the other hand, Hb content, lymphocytes count, and albumin level fell in all COVID-19 patients. The severe group showed a statistically significant rise in liver enzymes, WBCs, and CRP levels, compared with moderate group. WBCs and lymphocytes counts were closely correlated with age, ALT, LDH, and CRP in all cases. WBCs and lymphocytes counts also had a negative correlation with albumin Level. Additionally, WBCs count, lymphocytes count, LDH activity and CRP level have higher AUC in severe than in moderate cases. WBCs count, LDH activity and CRP level have AUC above 0.80 in the severe group. Conclusion: The current investigation found a significant correlation between WBCs count, lymphocytes count, CRP level and liver injury in COVID-19 patients. WBCs count, lymphocytes count, LDH activity and CRP level were effective indicators for determining the severity of COVID-19.

The following narrative review embarks on a comprehensive exploration of the pivotal role played by the gut microbiome within the Diet-Microbiota-Immunity (DMI) tripartite, aiming to enhance anti-cancer immunotherapy efficacy. While revolutionizing cancer treatment, resistance to immunotherapy and immune-related adverse events (irAEs) remain challenges. The tumor microenvironment (TME), shaped by cancer cells, influences immunotherapy resistance. The gut microbiome, influenced by genetics, environment, diet, and interventions, emerges as a critical player in TME reshaping, thereby modulating immune responses and treatment outcomes. Dietary patterns like the Mediterranean diet, caloric restriction modifications, and specific nutritional components show promise in influencing the tumor microenvironment and gut microbiome for better treatment outcomes. Antibiotics, disrupting gut microbiota diversity, may compromise immunotherapy efficacy. This review emphasizes the need for tailored nutritional strategies to manipulate microbial communities, enhance immune regulation, and improve immunotherapy accessibility while minimizing side effects. Ongoing studies investigate the impact of dietary interventions on cancer immunotherapy, pointing towards promising developments in personalized cancer care. This narrative review synthesizes existing knowledge and charts a course for future investigations, presenting a holistic perspective on the dynamic interplay between dietary interventions, the gut microbiome, and cancer immunotherapy within the DMI tripartite.

Acute pancreatitis is a complex inflammatory disorder with significant morbidity and mortality. This review aims to integrate current knowledge of pancreatic morphology and immunology with the pathogenesis of acute pancreatitis, providing a comprehensive understanding of this critical condition. We conducted an extensive literature review, synthesizing data from recent studies and authoritative sources on pancreatic anatomy, histology, immunology, and the pathophysiology of acute pancreatitis. We also incorporated epidemiological data, clinical features, diagnostic criteria, and prognostic factors. The pancreas exhibits a complex morphology with intricate interactions between its exocrine and endocrine components. Its unique immunological landscape plays a crucial role in maintaining homeostasis and orchestrating responses to pathological conditions. In acute pancreatitis, disruption of intracellular calcium signaling leads to premature enzyme activation, triggering a cascade of events including mitochondrial dysfunction, ATP depletion, and release of pro-inflammatory mediators. This process can escalate from localized inflammation to systemic complications. The interplay between pancreatic morphology, immune responses, and pathophysiological mechanisms contributes to the varied clinical presentations and outcomes observed in acute pancreatitis. Understanding the intricate relationships between pancreatic morphology, immunology, and the pathogenesis of acute pancreatitis is crucial for developing more effective diagnostic and therapeutic strategies. This integrated approach provides new insights into the complex nature of acute pancreatitis and may guide future research directions in pancreatic disorders.

Novel sensing technologies for liquid biopsies offer a promising prospect for the early detection of metabolic conditions through -omics techniques. Indeed, high-field NMR facilities are routinely used for metabolomics investigations on a range of biofluids in order to rapidly recognize unusual metabolic patterns in patients suffering from a range of diseases. However, these techniques are restricted by the prohibitively large size and cost of such facilities, suggesting a possible role for smaller, low-field NMR instruments in biofluid analysis. Herein we describe selected biomolecule validation on a low-field benchtop NMR spectrometer (60 MHz), and present an associated protocol for the analysis of biofluids on compact NMR instruments. We successfully detect common markers of diabetic control at low-to-medium concentrations through optimized experiments, including glucose (≤ 2.6 mmol./L) and acetone (25 μmol./L), and additionally in readily-accessible biofluids. We present a combined protocol for the analysis of these biofluids with low-field NMR spectrometers for metabolomics, and offer a perspective on the future of this technique appealing to point-of-care applications.

Lymphangioleiomyomatosis (LAM) is a cystic pulmonary disorder that has been known to primarily affect women of childbearing age. The disorder can develop with mutations in the tuberous sclerosis (TSC) genes TSC1 & TSC2 but may arise by other irregular cases in the lack of these mutations. LAM can manifest in a wide variety of ways and generally compounded in symptoms of other lung disorders such as bronchitis, emphysema, & asthma. However, due to lack of effective diagnostic methods, biomarkers of LAM leading to a treatment for the disorder are currently unmet. Using integrative dating analytics and bioinformatics approaches; this study used publicly available microarray data to identify biomarkers in LAM. The results showed important differential expressed genes (DEGs) including: CDH2, CXCL6, ANXA10, MFAP5, RPS4Y1, DCBLD2, PAPPA, TFPI2, SERPINE1, LOX, MYH11, RGS1, SEPP1, TMOD1, ID1, SFTPB, CDH1, HTR2B, OGN, and IGLC1. Furthermore, gene – network and gene ontology (GO) analysis were conducted to show the importance of these genes from a molecular understanding. Taken together, the results revealed could serve as diagnostic and prognostic biomarkers with LAM patients.

Colon cancer (CC) is one of the leading causes of cancer-related death worldwide. Gene hypermethylation is a well-known alteration that contributes to tumour progression in CC. It is essential to analyse new molecular markers that can delineate more aggressive CC cases. The detection of new epigenetic alterations such as hypermethylation and hypomethylation of regulatory gene regions that participate in crucial mechanisms of cancer progression, such as epithelial mesenchymal transition (EMT), could be useful for identifying cases that might benefit from a closer follow-up by clinicians. In the present report we describe, for the first time, the hypermethylation of the ZEB1 gene, which is more frequent in cases without expression of hMLH1. More importantly, this epigenetic alteration is a good prognostic factor related to disease-free and overall survival in all cases and Consensus Molecular Subtypes (CMS2/3) independently of other clinical parameters such as patient age, stage, lymph node involvement, and blood vessel and perineural invasion.

Synucleins are a family of small, soluble proteins mainly expressed in neural tissue and in certain tumors. Since their discovery, tens of thousands of scientific reports have been published about this family of proteins as they are associated to severe human diseases. Although the physiological function of these proteins still elusive, their relation with neurodegeneration and cancer was clearly described over the years. In this review, we summarize data connecting synucleins and cancer, going from the structural description of these molecules, to their involvement in tumor-related processes, and discuss the putative use of this proteins as cancer molecular biomarkers.

Major depressive disorder (MDD) is a highly prevalent, debilitating disorder with a high rate of treatment resistance. One strategy to improve treatment outcomes is to identify patient-specific, pre-intervention factors that can predict treatment success. Neurophysiological measures such as electroencephalography (EEG), which measures the brain’s electrical activity from sensors on the scalp, offer one promising approach for predicting treatment response for psychiatric illnesses, including MDD. In this study, a secondary data analysis was conducted on the publicly available Two Decades-Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) database. Specifically, hierarchical regression modeling was used to predict treatment response from baseline demographics, symptom severity, and resting-state EEG features in 119 MDD patients receiving repetitive transcranial magnetic stimulation (rTMS). Across models, both age and baseline symptom severity, assessed by the Beck’s Depression Inventory, were significant predictors of rTMS treatment response, with older individuals and more severe depression scores associated with decreased odds of a positive treatment response. EEG measures contributed predictive power to these models; however, these improvements in outcome predictability only trended towards statistical significance (p~0.07 in multiple models). These findings provide confirmation of previous demographic and clinical predictors, while pointing to EEG metrics that may provide predictive information in future studies.

According to the literature, patients with chronic pain and mental disorders constitute a huge, heterogeneous group. However, it is known that social and psychological processes closely affect the level and expression of chronic pain. In this paper, we present a review of the literature, define methods of identifying pain biomarkers and consider the possibility of using them to assess pain in mental disorders. Group researchers searched PubMed, Scope, and Cochrane databases for "pain biomarkers in mental disorders" between 2011 and 2021. for available databases for full-text, peer-reviewed studies and review publications using the following keywords: pain biomarkers, neuroimaging pain, pain metabolomics, pain and psychiatric disorders, pain electroencephalography (EEG), serum pain biomarkers, saliva biomarkers, and diagnosis pain. The search included full-text articles, clinical trials, randomized controlled trials, and systematic reviews. Was used part of the PRISMA method to review the literature systematically. A literature search identified 283 studies based on the initially set inclusion and exclusion criteria. In the subsequent selection stages, 11 studies were selected for analysis. There are three main areas of the possible use of biomarkers for the clinical assessment of pain in psychiatric patients, neuroimaging, changes in metabolite levels in body fluids, and changes in gene expression. As a result of the review, individual pain mediators were distinguished that may be markers of pain in psychiatric patients. Some mediators indicate the specificity of pain and are of diagnostic importance. However, despite significant advances in research, most of the described biomarkers found in clinical trials assessing the severity and frequency of pain have no practical significance in psychiatric disorders. It is possible to diagnose pain based on neuroimaging using various methods, genetic methods, body fluids: blood and urine. Of the many, body fluid biomarkers are the most advanced. Discussion: Biomarker research is a dynamically developing field. The review has proposed new ways to diagnose pain by identifying pain biomarkers. Work presented pain diagnostics in psychiatric disorders based on biomarkers from various neuroimaging methods, blood and urine analysis. The possibility of new, effective techniques gives hope for the correct diagnosis of pain, especially in patients with mental disorders, which would allow for appropriate and adequate therapeutic therapies. In clinical practice is limited to a few methods. Assessment of pain biomarkers in body fluids (serum, saliva, and urine) seems to be the most practical and promising method of clinical application. Conclusions: There are new techniques that give hope for the correct diagnosis of pain, especially in patients with mental disorders, which will allow for their proper and adequate therapy. According to the literature, patients with chronic pain and mental disorders constitute a huge, heterogeneous group. However, it is known that social and psychological processes closely affect the level and expression of chronic pain.

The SARS coronavirus 2 (SARS-CoV-2) is the causative agent of the 2019 coronavirus disease (COVID-19) pandemic that has executed 6.9 million people and infected over 765 million. It’s become a major worldwide health alarm and is also known to cause abnormalities in various systems, including the hematologic system. COVID-19 infection primarily affects the lower res-piratory tract and can lead to a cascade of events, including a cytokine storm, intravascular thrombosis, and subsequent complications such as arterial and venous thromboses. COVID-19 can cause thrombocytopenia, lymphopenia, and neutrophilia, which are associated with worse out-comes. Prophylactic anticoagulation is essential to prevent complication and death rate associated with the virus's effect on the coagulation system. It is crucial to recognize these complications early and promptly start therapeutic anticoagulation to improve patient outcomes. While rare, COVID-19-induced disseminated intravascular coagulation exhibits some similarities to DIC induced by sepsis. LDH, D-dimer, ferritin, and CRP biomarker are often increase in serious COVID-19 cases and poor prognosis. Understanding the pathophysiology of the disease and identifying risk factors for adverse outcomes is critical for effective management of COVID-19.

The Aβ cascade and alternations of biomarkers in neuro-inflammation, synaptic dysfunction and neuronal injury followed by Aβ have progressed. But the question is how to use the biomarkers. Here, we examine the evidence and pathogenic implications of protein interactions and the time order of alternation. After the deposition of Aβ, the change of tau, NfL and NG is the main alternation and connection to others. The neuro-inflammation, synaptic dysfunction and neuronal injury function is exhibited prior the structural and metabolic changes in the brain following Aβ deposition. The time order of such biomarkers compared to the tau protein is not clear. Despite the close relationship between biomarkers and plaque Aβ deposition, several factors favor one or the other. There is an interaction between the proteins that CSF SNAP-25, VILIP-1 and YKL-40 can predict the brain amyloid burden. The Aβ cascade hypothesis could be the pathway, but not all subjects are converted to AD, even with very high elevated Aβ. The interaction of biomarkers and the time order of change require further research to identify the right subjects and right molecular target for precision medicine therapies.

For decades since the central dogma, cancer biology research has been focusing on the involvement of genes encoding proteins. It has been not until more recent times that a new molecular class has been discovered, named non-coding RNA (ncRNA), which has been shown to play crucial roles in shaping the activity of cells. An extraordinary number of studies into shown that ncRNAs represent an extensive and prevalent group of RNAs, including both oncogenic or tumor suppressive molecules. Henceforth, various clinical trials involving ncRNAs as extra ordinary biomarkers or therapies have started to emerge. In this review, we will focus on the prognostic and diagnostic role of ncRNAs for breast cancer.

This study investigated whether metabolomic fingerprints of bovine embryo growth media improve the prediction of successful embryo implantation. In this prospective cohort study, the metabolome from in vitro produced Day 7 blastocysts with successful implantation (n=11), blas-tocysts with failed implantation (n=10), and plain culture media without embryos (n=5) was in-cluded. Samples were analyzed using AbsoluteIDQ® p180 Targeted Metabolomics Kit with LC-MS/MS, and a total of 189 metabolites were analyzed from each sample. Blastocysts that re-sulted in successful embryo implantation had significantly higher levels of methionine sulfoxide (p<0.001), DOPA (p<0.05), spermidine (p<0.001), acetylcarnitine to free carnitine ratio (p<0.05), C2+C3 to free carnitine ratio (p<0.05), and lower levels of threonine (nep<0.001) and phosphati-dylcholine PC ae C30:0 (p<0.001) compared to control media. However, when compared to embryos that failed to implant, only DOPA, spermidine, C2/C0, (C2+C3)/C0 and PC ae C30:0 levels differentiated significantly. In summary, our study identifies a panel of differential metabolites in the culture media of bovine blastocysts that could act as potential biomarkers for the selection of viable blastocysts before embryo transfer.

Rapid and continuing advances in biomarker testing are not being matched by take-up in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. The potential that genomics has brought to biomarker testing in diagnosis, prediction and research is being realised, pre-eminently in many cancers, but also in an ever-wider range of conditions. One of the paradigmatic examples is BRCA1/2 testing in ovarian, breast, pancreatic and prostate cancers. Nevertheless, development is impeded by data deficiencies, and lack of policy alignment on standards, approval – and the role of real-world evidence in the process - and reimbursement. The acute nature of the problem is compellingly illustrated by the particular challenges facing the development and use of tumour agnostic therapies, where the gaps in preparedness for taking advantage of this innovative approach to cancer therapy are sharply exposed. Europe should already have in place a guarantee of universal access to a minimum suite of biomarker tests and should be planning for an optimum testing scenario with a wider range of biomarker tests integrated into a more sophisticated health system articulated around personalised medicine. Improving healthcare and winning advantages for Europe's industrial competitiveness and innovation require an appropriate policy framework – starting with an update to outdated recommendations.

Background: Post-operative delirium in elderly with hip fracture is associated with various adverse clinical outcomes. Nevertheless, the pathophysiological processes underpinning delirium have remained elusive. The aim of this study is to explore the associations between delirium and its features and immune-inflammatory and blood gas biomarkers.Methods: In this prospective study we examined 65 patients who underwent a hip fracture surgery and assessed the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), Richmond Agitation-Sedation Scale (RASS), and Delirium Rating Scale Revised-98 (DRS-R-98) before and during 4 days after the surgery. Complete Blood Count (CBC) and venous blood gas markers were obtained at the same time points.Results: Delirium was observed in 19 patients and was accompanied by significantly increased pO2, number of white blood cells, neutrophil percentage, and neutrophil/lymphocyte ratio, and lower mean platelet volume (MPV) (after adjusting for age, central nervous system (CNS) disease, blood loss during surgery, sleep disorders, and body mass index. The severity of delirium was associated with lowered number of platelets and MPV. Psychomotor disorders were associated with lower bicarbonate levels. The requirement of physical restraint of the patients was predicted by increased percentages of neutrophils and lymphocytes. Prior CNS disease was together with these biomarkers a significant predictor of delirium and severity of delirium. Conclusion: Delirium and psychomotor disorders following hip fracture and surgery may be caused by immune-inflammatory and oxidative stress pathways probably attributable to an aseptic inflammatory process. Oxygen administration may aggravate these pathways.

Hepatocellular carcinoma (HCC) is one of the most frequent cancers in humans, characterised by high resistance to conventional chemotherapy, late diagnosis, and high mortality rate. It is necessary to elucidate the molecular mechanisms involved in hepatocarcinogenesis to improve diagnosis and treatment outcomes. The Runt-related (RUNX) family of transcription factors (RUNX1, RUNX2, and RUNX3) participates in cardinal biological processes and play paramount roles in the pathogenesis of numerous human malignancies. Their role is often controversial as they can act as oncogenes or tumour suppressors, dependent on cellular context. Evidence shows that deregulated RUNX genes may be involved in hepatocarcinogenesis from the earliest to the latest stages. In this review, we summarise the topical evidence on the roles of RUNX gene family members in HCC. We discuss their possible application as non-invasive molecular markers for early diagnosis, prognosis, and development of novel treatment strategies in HCC patients.

Suicide is defined as the action of harming oneself with the intention of dying. It is estimated that worldwide one suicide occurs every 40 seconds, making it a major health problem. Studies in families have suggested that suicide has a genetic component, around the world studies have been carried out in search of genetic variants associated with suicidal behavior, these variants could be useful as potential biomarkers to identify people at risk of suicide. In this area in Mexico, some studies of variants in genes related to neurotransmission and other important pathways have been carried out and a possible association of variants located in genes has been suggested: SLC6A4, SAT-1, TPH-2, ANKK1, GSHR, SCARA50, RGS10, STK33, COMT, and FKBP5. This systematic review shows the genetic studies on the Mexican population. This article contributes by compiling the existing information on genetic variants and genes associated with suicidal behavior, said variants in the future could be used as potential biomarkers to identify people at risk of suicide.

This study was to investigate and assess salivary biomarkers as a means of diagnosing periodontitis. A total of 121 subjects were included: 28 periodontally healthy subjects, 24 with stage I, 24 with stage II, 23 with stage III, and 22 with stage IV periodontitis. Salivary proteins including active matrix metalloproteinase-8 (MMP-8), pro-MMP-8, total MMP-8, C-reactive protein, secretory immunoglobulin A and planktonic bacteria including Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, Porphyromonas nigrescens, Parvimonas micra, Campylobacter rectus, Eubacterium nodatum, Eikenella corrodens, Streptococcus mitis, Streptococcus mutans, Staphylococcus aureus, Enterococcus faecalis, and Actinomyces viscosus were measured from salivary samples. The performance of the diagnostic models was assessed by receiver operating characteristics (ROC) and area under the ROC curve (AUC) analysis. The diagnostic models were constructed based on the subjects’ proteins and/or microbial profiles, resulting in two potential diagnosis models, which achieved better diagnostic powers with an AUC value &gt; 0.750 for the diagnosis of stage II, III, and IV periodontitis (Model PC-I; AUC: 0.796, sensitivity: 0.754, specificity: 0.712) and for the diagnosis of stage III and IV periodontitis (Model PC-II; AUC: 0.796, sensitivity: 0.756, specificity: 0.868). This study can contribute to screening for periodontitis based on salivary biomarkers.

Ionizing radiation exposure is known to induce molecular and cellular injury, inflicting a cascade of potentially catastrophic events leading to tissue and organ damage. Metabolomic analysis allows for the identification and quantification of small molecules downstream of genomic changes induced by radiation exposure. We aimed to characterize metabolomic changes that underscore the prefinal stage of lethally irradiated rhesus nonhuman primates (NHPs). Peripheral blood was drawn at baseline, post-exposure as well as at the preterminal stage of NHPs (immediately prior to death in moribund NHPs), which did not survive exposure with 7.2 Gy total-body radiation (LD70/60). Herein, we analyzed global metabolomic changes using ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight mass spectrometry (QTOF-MS) in plasma samples of NHPs collected at various timepoints in relation to irradiation. The overall goal was to identify metabolic shifts present immediately prior to death. Our findings, for the first time, show that radiation induced significant time dependent metabolic perturbations when compared to pre-irradiation samples, particularly in the glycerophospholipid metabolism and steroid hormone biosynthesis and metabolism pathways. These findings provide valuable insights for identifying biomarkers for lethality, which may be helpful for triage during a mass casualty scenario.

The tumor microenvironment of colorectal cancer (CRC) is heterogenous; thus, it is likely that multiple immune-related and inflammatory markers are simultaneously expressed in the tumor. The aim of this study was to identify immune-related and inflammatory markers expressed in freshly frozen CRC tissues and to investigate whether they are related to the clinicopathological features and prognosis of CRC. Seventy patients with CRC who underwent curative surgical resection between December 2014 and January 2017 were included in this study. Tissue samples were obtained from tumor and non-tumor areas in the patients’ colons. The concentrations of immune-related markers (APRIL/TNFSF13, BAFF, LAG-3, PD-1, PD-L1, and CTLA-4) and inflammatory markers (CHIT, MMP-3, osteocalcin, pentraxin-3, sTNF-R1, and sTNF-R2) in the samples were measured using the Bio-plex Multiplex Immunoassay system. The concentrations of APRIL/TNFSF13, BAFF, and MMP-3 in the samples were significantly high; thus, we conducted analyses based on the cutoff values for these three markers. The high APRIL/TNFSH13 expression group showed a significantly higher rate of metastatic lesions than the low expression group, whereas the high MMP-3 expression group had higher CEA levels, more lymph node metastases, and more advanced disease stages than the low expression group. The five-year disease-free survival of the high MMP-3 expression group was significantly shorter than that of the low expression group (65.1% vs. 90.2%, p=0.033). This study provides evidence that the APRIL/TNFSF13, BAFF, and MMP-3 pathway is overexpressed CRC tissues and is associated with unfavorable clinicopathological features and poor prognosis in CRC patients. These markers could serve as diagnostic or prognostic biomarkers for CRC.

Astragalus membranaceus (AM) and Panax ginseng (PG) are two herbal products with a long history of clinical usage in traditional Chinese medicine (TCM), used in treating a variety of diseases especially in stimulating or inhibiting the immune system. To elucidate the immunity effect of these two traditional Chinese medicine on animal model, four pharmacodynamic indexes (spleen index, thymus index, splenic lymphocyte proliferation and cytotoxic activity of natural killer (NK) cells) were observed on mice. Furthermore, metabolic profiles of plasma were also analyzed by ultra-performance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-Q/TOF-MS, LC-MS) method. All mice were intragastric administrated at three doses (low dose, moderate dose and high dose) once daily for 30 days. Principal components analysis (PCA) and orthogonal projection to latent structure discriminant analysis (OPLS-DA) were performed on LC-MS spectra of plasma, showing that all administration groups developed the disturbance of internal milieu, compared to the blank control (BC) group. Besides, correlation analysis was conducted between pharmacodynamic index and metabolic index. It indicated that uracil, lysoPC(18:3(6Z,9Z,12Z)), sphinganine, LPA(0:0/16:0), UDP-glucuronate, PC(14:0/18:0) were five main endogenous substances, much closely related to four immunological indexes. Glycerophospholipid metabolism was found in both AM and PG groups. Pyrimidine metabolism and sphingolipid metabolism were closely regulated in AM groups. Energy metabolism (starch and sucrose metabolism, Pentose and glucuronate interconversions, together with glycerolipid metabolism) and glycerolipid metabolism were found in PG groups. These findings could contribute to the understanding of mice plasmatic metabolic profiling after long-term administration. Comparative immune-related metabolomic analysis of AM and PG was obtained on the base of pathway analysis of immune-related biomarkers. PG groups trended to have effect on cytotoxic activity of NK cells. AM groups trended to effect thymus index. Our work provides a detailed interpretation of immunological characteristics in different traditional Chinese medicine on metabonomic level.

This work aims to investigate the expression levels of four preselected miRNAs previously linked to Cancer and/or Obesity, with the purpose of finding potential biomarkers in the clinical management of Colorectal Cancer (CRC) developed by obese and non-obese patients. We analyzed samples from a total of 65 subjects, 43 affected by CRC and 22 without cancer. Serum and both subcutaneous and omental adipose tissues (SAT and OAT) were analyzed, as well as tumor and non-tumor colorectal tissues in the case of the CRC patients. The relative expression (2-∆∆Ct) levels of 4 miRNAs (miR-181a-5p, miR-143-3p, miR-132-3p and miR-23a-3p) were measured by RT-qPCR. Serum, SAT and OAT expression levels of these miRNAs showed significant differences between subjects with and without CRC, especially in the group of overweight/obese subjects. In CRC serum levels of miR-181a-5p, miR-143-3p and miR-23a-3p correlated with their levels in both SAT and OAT. Moreover, in the case of miR-181a-5p, these correlations were significantly influenced by the body mass index (BMI). From these data, we can conclude that both adiposity and CRC induce changes in the expression of the miRNAs investigated, demonstrating the potential utility of this panel of miRNAs in the diagnosis and prognosis of CRC patients.

Background: Diagnosis of acute kidney injury (AKI) relies on serum creatinine (SCr) changes. This study investigated if urinary aminopeptidases are early and predictive biomarkers of cardiac surgery associated-AKI (CSA-AKI). Methods: Glutamyl aminopeptidase (GluAp), alanyl aminopeptidase (AlaAp), dipeptidyl peptidase-4 (DPP4), proteinuria, albuminuria, N-acetyl-β-D-glucosaminidase (NAG) and neutrophile gelatinase-associated lipocalin (NGAL) were measured in urine samples from 44 patients at arrival in Intensity Care Unit (ICU) after cardiac surgery. Sensitivity, specificity, positive and negative predictive value for diagnosis of stages 1, 2 and 3 of AKI were analyzed for the highest quartile of each marker. We also studied the relationship with SCr after surgery, 6- and 12-months glomerular filtration rate (GFR) and other long-term events over the next 5 years. Results: GluAp diagnosed the maximal number of patients that developed stage 2 or 3 of AKI, increasing diagnostic sensitivity from 0 to 75 %. Besides, GluAp and DPP4 was related to the decrease in GFR at 6- or 12-months after surgery. Conclusions: Urinary aminopeptidases are a potential tool for the early diagnosis of CSA-AKI, being GluAp the most effective marker for diagnosing stages 2 or 3 of AKI at ICU admission. GluAp and DPP4 serve as predictive biomarkers for the decrease in GFR.

Cardiovascular disease (CVD) is one of the leading causes of death in Puerto Rico, where clopidogrel is commonly prescribed to prevent ischemic events. Genetic contributors to both a poor clopidogrel response and the severity of CVD have been identified mainly in Europeans. However, the non-random enrichment of single nucleotide polymorphisms (SNPs) associated with clopidogrel resistance within risk loci linked to underlying CVDs, and the role of admixture, has yet to be tested. This study aimed to assess possible interaction between genetic biomarkers linked to CVDs and those associated with clopidogrel resistance among admixed Caribbean Hispanics. We identified 50 SNPs significantly associated with CVDs in previous genome-wide association studies (GWAS). These SNPs were combined with another ten SNPs related to clopidogrel resistance in Caribbean Hispanics. We developed Python scripts to determine whether SNPs related to CVDs are in close proximity to those associated with clopidogrel response. Average and individual local ancestry (LAI) within each locus were inferred, and 60 random SNPs with their corresponding LAI were generated for enrichment estimation purposes. Our results showed no CVD-linked SNPs in close proximity to those associated with clopidogrel response among Caribbean Hispanics. Consequently, no genetic loci with a dual predictive role for risk of CVD severity and clopidogrel resistance were found in this population. Native American ancestry was the most enriched within risk loci linked to CVDs in this population. Non-random enrichment of disease susceptibility loci with drug response SNPs is a new frontier in Precision Medicine that needs further attention.

Rapid and continuing advances in biomarker testing are not being matched by uptake in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. The potential that genomics has brought to biomarker testing in diagnosis, prediction and research is being realised, pre-eminently in many cancers, but also in an ever-wider range of conditions – notably BRCA1/2 testing in ovarian, breast, pancreatic and prostate cancers. Nevertheless, the implementation of genetic testing in clinical routine setting is still challenging. Development is impeded by country-related heterogeneity, data deficiencies, and lack of policy alignment on standards, approval – and the role of real-world evidence in the process - and reimbursement. The acute nature of the problem is compellingly illustrated by the particular challenges facing the development and use of tumour agnostic therapies, where the gaps in preparedness for taking advantage of this innovative approach to cancer therapy are sharply exposed. Europe should already have in place a guarantee of universal access to a minimum suite of biomarker tests and should be planning for an optimum testing scenario with a wider range of biomarker tests integrated into a more sophisticated health system articulated around personalised medicine. Improving healthcare and winning advantages for Europe's industrial competitiveness and innovation require an appropriate policy framework – starting with an update to outdated recommendations.

The development of inexpensive, fast and reliable screening tests for COVID-19 is, as yet, an unmet need. The present study was aimed at evaluating the usefulness of serum arylesterase activity of paraoxonase-1 (PON1) measurement as a screening test in patients with different severity levels of COVID-19 infection. We included 615 COVID-19 positive patients who were classified as asymptomatic, mildly symptomatic, severely symptomatic, or fatally symptomatic. Results were compared with 50 healthy volunteers, 330 patients with cancer and 343 with morbid obesity. Results showed PON1 activity greatly decreased in COVID-19 compared to healthy vol-unteers; receiver operating characteristics plot showed a high diagnostic accuracy. The degree of COVID-19 severity did not influence PON1 levels. Our results indicated that PON1 determination was efficient for disease diagnosis but not for prognosis. Further, patients with obesity or cancer presented alterations similar to those of COVID-19 patients. As such, elevated levels of PON1 in-dicate the absence of COVID-19, but low levels may be present in various other chronic diseases. The assay is fast and inexpensive. We suggest that PON1 measurement could be used as an initial, high cut-off point screening method, while lower values should be confirmed with the more ex-pensive nucleic acid amplification test.

The Matāura River is the sixth largest river system in New Zealand and has long been subject to agricultural, industrial, and residential land use activities. The catchment has geographic and economic value and is of great cultural importance for local Māori, who have concerns over potential adverse impacts that anthropogenic stressors exert on the health of the river. There is a dearth of information on the impacts of these stressors towards the health of native species such as the longfin eel Anguilla dieffenbachii. This study assessed the environmental status of the Matāura River using biological and chemical methodologies incorporating A. dieffenbachii as a bioindicator species for exposure to combined anthroprogenic stressors. A range of biomarker endpoints were measured in caged and wild-caught eels (when available) to characterize site-specific responses to combined anthropogenic stressors. While there was no clear indication of cumulative impacts moving from pristine headwaters to the lower reaches of the Matāura River biomarkers of xenobiotic metabolization were induced in A. dieffenbachia and there was evidence of chemical contamination in sediments and tissues.

Novel treatment strategies are emerging for rare, genetic diseases, resulting in clinical trials that require adequate biomarkers for the assessment of the treatment effect. For enzyme defects, biomarkers that can be assessed from patient serum, such as enzyme activity, are highly useful, but the activity assays need to be properly validated to ensure a precise, quantitative measurement. Aspartylglucosaminuria (AGU) is a lysosomal storage disorder caused by the deficiency of the lysosomal hydrolase aspartylglucosaminidase (AGA). We have here established and validated a fluorometric AGA activity assay for human serum samples from healthy volunteers and AGU patients. We show that the validated AGA activity assay is suitable for the assessment of AGA activity in the serum of healthy controls and AGU patients, and it can be used for diagnostics of AGU and, potentially, for following a treatment effect.

Colorectal cancer prognosis get worse with advancement of disease into metastatic stage. There is a pertinent need to develop prognostic biomarkers that can be used for personalized and precision medicine. Alternative splicing provides an insight into understanding of changes at isoform expression level which may not be evident at gene level. In this direction, we utilized our prior knowledge about significant alternatively spliced genes and chose ADAM12 and MUC4 for further characterization in a metastatic cell line model. These genes were found to be good prognostic indicators in The Cancer Genome Atlas database. We studied the gene organization and designed primers to specifically amplify a group of isoforms. Differential expression of these group of isoforms was observed in normal, primary and metastatic colorectal cancer cell lines. We further validated the results using sanger sequencing. Isoform expression was found to respond to the 5-fluorouracil treatment. RNAseq analysis of the cell lines further validated the differential expression of gene isoforms. Successful detection of ADAM12 and MUC4 in cell lysates varied according to the antibody used which may reflect differential expression of isoforms. This comprehensive study underscores the importance of studying alternatively spliced isoforms and their probable used as prognostic or predictive biomarkers.

Background: Aberrations in endothelial cells, immune and oxidative pathways are associated with atherosclerosis (ATS) and unstable angina (UA). The role of trace elements, minerals, and the endogenous opioid system (EOS) in UA are less well established. Methods: We measured lipid, insulin resistance (IR), and immune, trace element (copper and zinc), mineral (magnesium, calcium), EOS (β-endorphin and mu-opioid receptor (MOR)) and antioxidant (vitamin D3) biomarkers in patients with ATS (n=60) and UA (n=60) and healthy controls (n=58). Results: ATS patients showed increased atherogenic and IR indices, IL-6, IL-10, β-endorphin, copper and magnesium, and lower zinc than healthy controls. Logistic regression showed that UA was significantly discriminated from ATS without UA with an accuracy of 85.5% using calcium, IL-10, β-endorphin, MOR, triglycerides, IR (all positively), and copper and vitamin D3 (inversely). Neural networks showed that UA was discriminated from ATS without UA with an area under the ROC curve of 0.942 using MOR, β-endorphin, calcium, insulin resistance, vitamin D3 and copper as input variables. We found that 50.0% of the variance in IR was explained by the regression on copper, IL-10, IL-6 (all positively), and zinc (inversely), while 32.9% of the variance in the atherogenic index of plasma was explained by copper, IL-10 (both positively), and magnesium (inversely). Conclusion: UA is not only mediated by insulin resistance, atherogenicity, and immune disorders, but also by aberrations in the endogenous opioid system and trace elements as well as lowered antioxidant levels. Copper appears to play a key role in IR and atherogenicity.

Zinc (Zn) is a trace element crucial for oxidative stress, apoptosis, the immune response, and more globally for various processes involved in cellular homeostasis. In some cancers, Zn homeostasis is dysregulated. In this review, the role of Zn in cancer and all the components associated to Zn, the use of Zn and Zn -related proteins as biomarkers and Zn-based strategies for the treatment of tumors will be described. ZIP and ZnT are proteins related to Zn metabolism in normal conditions. In cancer, the level of expression of Zn related proteins is abnormal. These Zn proteins may act as prognostic or diagnostic biomarkers, and may be helpful for detecting early-stage cancers or monitoring the course of the disease. Additionally, Zn and its pathways may also be targeted to treat cancers. Indeed, the use of metals for binding Zn cations allows to regulate the biodistribution of Zn within cells, and will control several downstream signaling pathways. Zinc may also be directly used as a therapeutic substance to improve the prognosis of cancer patients, especially with the supplementation of zinc or the use of Zn oxide nanoparticles.

Background: Type 2 diabetes mellitus (T2DM) is associated with increased atherogenicity and inflammatory responses, which may be related to increased levels of high mobility group box 1 (HMGB1) and Dickkopf-related protein 1 (DKK1). Objective: The role of HMGB1 and DKK1 in T2DM is examined in association with lipid and insulin profiles. Methods: Serum HMGB1 and DKK1 were measured in T2DM with and without hypertension and compared with controls. Results: HMGB1 and DKK1 are significantly higher in T2DM irrespective of hypertension. T2DM was also accompanied by increased atherogenicity indices. HMGB1 and DKK1 are significantly correlated with HbA1c, glucose, indices of insulin resistance, β-cell function, and glucose toxicity, and different atherogenic indices. A large part of the variance in the β-cell index (30.5%) and glucose toxicity (34.8%) was explained by the combined effects of HMGB1 and DKK1 and hypertension. We found that 18.3% of the variance of the atherogenic index of plasma was explained by HMGB1 and DKK1 levels and that 31.2% was explained by glucose toxicity, HMGB1 and body weight. Conclusion: The higher serum HMGB1 and DKK1 levels in T2DM patients and the associations with atherogenicity indicate that low grade inflammation and disorders in the Wnt pathways are associated with T2DM and that both HMGB1 and DKK1 may contribute to increased atherogenicity in T2DM. Moreover, both biomarkers may cause more deficits in β-cell function and increase glucose toxicity leading to the development of more inflammation and diabetic complications. HMGB1 and the Wnt pathways are new drug targets in the treatment of T2DM.

The human voice has the potential to serve as a valuable biomarker for the early detection, diagnosis, and monitoring of pediatric conditions. This scoping review synthesizes the current knowledge on the application of Artificial Intelligence (AI) in analyzing pediatric voice as a biomarker for health. The included studies featured voice recordings from pediatric populations aged 0-17 years, utilized feature extraction methods, and analyzed pathological biomarkers using AI models. Data from 62 studies were extracted, encompassing study and participant characteristics, recording sources, feature extraction methods, and AI models. The review showed a global representation of pediatric voice studies, with a focus on developmental, respiratory, speech, and language conditions. The most frequently studied conditions were Autism Spectrum Disorder, intellectual disabilities, asphyxia, and asthma. Mel-Frequency Cepstral Coefficients were the most utilized feature extraction method, while Support Vector Machines were the predominant AI model. The analysis of pediatric voice using AI demonstrates promise as a non-invasive, cost-effective biomarker for a broad spectrum of pediatric conditions. However, further research and development are crucial to enhance the accuracy and applicability of these tools in clinical settings.

Gastric Cancer (GC) is the fifth most frequently diagnosed malignant tumor and the third cause of cancer mortality worldwide. For advanced GC, a large number of novel drugs and combinations have been tested, but results are still disappointing and the disease incurable in the majority of cases. In this regard, it is critical to investigate the molecular mechanisms underlying GC development. Angiogenesis is one of the hallmarks of cancer with a fundamental role in GC growth and progression and ramucirumab, a monoclonal antibody binding to vascular endothelial growth factor-2 (VEGFR-2) is approved in the treatment of advanced and pretreated GC. However, no predictive biomarkers for ramucirumab have been identified so far. MicroRNAs (miRNAs) are a class of evolutionally conserved single-stranded noncoding RNAs playing an important role, via post-transcriptional regulation, in essentially all biologic processes such as cell proliferation, differentiation, apoptosis, survival, invasion, and migration. Notably, in our review, we focused on miRNAs involved in angiogenic pathways in GC. Moreover, we evaluated the possible prognostic and predictive role of angiogenesis-related miRNAs as novel biomarkers of GC.

In the era of nanotechnology, researchers are implementing point to care service to cancer patients to detect malignancy beforehand and to reduce the mortality rate of cancers. Cancer is known to be the most fatal disease among all other diseases and the survivability from cancer is quite impossible if the stage of the cancer is an advanced level. Though the early detection of cancer can increase the chances of survival with a double fold. Biosensor is a part of nanotechnology which is capable to provide point to care service in the field of medicine. With the rising number of cancer occurrences being identified around the world and the increasing number of deaths because of the identification of advanced cancer, biosensors can play a significant part in the early detection of cancer. New molecular methods, including as genomic and proteomic approaches, are increasingly being used to study patient molecular profiles. When such diagnosis method is paired with bioinformatics tools, they generate new data that can be used to discover new disease biomarkers. Finding precise and sensitive indicators that are corelated to a specific disease, as with many other diseases, can be challenging. Furthermore, the concentration of biomarkers in biological fluids varies according to illness states and phases. Peptides, proteins, up or down regulated expression of gene markers, and gene alternation are all examples of molecular markers that are commonly used to diagnose cancer. In this article, we have highlighted six different deadliest cancers such as Ovarian, Breast, Prostrate, Lung, Colorectal and Liver cancer. The article contains distinct types of biomarkers which are normally found in these kinds of cancer and generally used as a potential diagnostic target in the medicine field. The article mainly summarized the application of different types of biosensors devices in the detection of the mostly found biomarkers in the above cancer types.

Colorectal cancer (CRC) is the third most common neoplasm in the world and the second with the highest mortality rate. Single nucleotide polymorphisms (SNPs) in miRNA genes (mirSNPs) may be related to dysregulated miRNA expression in several neoplasms. This systematic review aims to investigate studies that investigate SNPs located in regions of miRNA genes that influence their expression and are associated with CRC, as well as their potential as biomarkers for the disease, based on the available literature. For this, searches were performed in public databases, including MEDLINE/PubMed, Embase, Web of Science and Scopus. The rigorous review of the PRISMA 2020 guidelines and the methodological quality of the studies were assessed sing the Newcastle-Ottawa scale and the Mixed Methods Assessment Tool. Of the 175 studies identified, 26 were considered eligible: 18 of them highlighted mirSNPs as potential biomarkers of risk and prognosis for CRC; 4 studies suggested a protective role; 1 study linked mirSNPs to treatment; and 3 studies found no relevant evidence. These results highlight the need for further research on this topic, since these variants have the potential to serve as biomarkers and may be useful in assessing risk, prognosis, and developing therapeutic strategies for patients with CRC.

The study explored the correlation between serum biomarkers and hepatocellular carcinoma detection in various fishing groups, utilizing a descriptive and experimental approach in Bangladesh. The study identified fishers often consume tobacco, polluted drinking water, and lack sufficient sunlight, all of which are extremely detrimental to their health. Fishermen who mostly fish at night and spend little time on the water during the daytime hours do not get enough sunlight, nor do they get enough vitamin D. An increased risk of liver cancer was found to be directly and strongly correlated with insufficient serum levels of vitamin D. In addition, a negligent lifestyle, a lack of awareness about hepatitis, and inadequate nutritional assistance have significantly increased their risk. Our results contribute to the information on HCC assessment and evaluation by clarifying the relevance of serum vitamin D, alpha-fetoprotein (AFP), creatinine (Cr), and hemoglobin A1C (HbA1c) in distinguishing between categories and sexes. According to the study, the combination of AFP, Vitamin-D, and Cr (AFP+Vit-D+Cr) has a high predictive value, which improves diagnosis and offers a reliable instrument for identifying liver cancer.

In tropical areas, simultaneous transmission of several vector-borne diseases is common due to ecological factors that are shared by arthropod vectors. Malaria and dengue virus, transmitted by Anopheles and Aedes mosquitoes, respectively, are among the top vector-borne diseases that cause significant morbidity and mortality in endemic areas. Notably, tropical areas often have suitable conditions for the co-existence of these mosquito species, highlighting the importance of identifying markers that accurately indicate the risk of acquiring each specific disease entity. Aedes are daytime-biting mosquitoes, while Anopheles preferentially bite during the night. These biting patterns raises the possibility of concurrent exposure to bites from both species. This pattern is important since mosquito saliva, deposited in the skin during blood feeding, induces immune responses that modulate pathogen establishment and infection. Previous studies have focused on characterizing such effects on the vector-pathogen interface for an individual pathogen and its mosquito vector. In this study, we evaluated associations between immune responses to salivary proteins from non-dengue and non-malaria vector mosquito species with clinical characteristics of malaria and dengue, respectively. Surprisingly, antibody responses against Anopheles antigens in dengue patients correlated with red blood cell count and hematocrit, while antibody responses against Aedes proteins were associated with platelet count in malaria patients. Our data indicate that concurrent exposure to multiple disease-carrying mosquito vectors and their salivary proteins with differing immunomodulatory properties could influence the transmission, pathogenesis, and clinical presentation of malaria, dengue fever, and other vector-borne illnesses.

The study of the human microbiome is a multidisciplinary area that affects from the field of technology to that of personalized medicine. The possibility of using microbiota biomarkers for the improvement in the diagnosis and monitoring of diseases (e.g. cancer), health conditions (e.g. obesity) or clinical parameters (e.g. ageing) has aroused great expectations, also in the scope of bio-electroanalytical chemistry. The well-known advantages of electrochemical transduction: high sensitivity, rapid response and possibility of miniaturization, together with the potential of new nanomaterials to improve both the design of electrode platforms and the performance of the resulting electrochemical biosensors make presumably a huge development in the next few years providing a better understanding of human microbiome entities. In this review article, the recent applications of electrochemical (bio)sensors for monitoring microbial metabolites and biomarkers of diseases related to different types of the human microbiome, with a special focus on the gastrointestinal microbiome, are reviewed. Examples of electrochemical devices applied to real samples are critically discussed as well as the challenges and prospects to be faced.

Heart failure (HF) has several etiologies including myocardial infarction (MI) and left ventricular remodeling (LVR), but its progression remains difficult to predict in clinical practice. Systems biology analyses of LVR after MI predict molecular insights of this event such as modulation of microRNA (miRNA) that could be used as a signature of HF progression. To define a miRNA signature of LVR after MI, we use 2 systems biology approaches integrating either proteomic data generated from LV of post-MI rat induced by left coronary artery ligation or multi-omics data (proteins and non-coding RNAs) generated from plasma of post-MI patients from the REVE-2 study. The first approach predicts 13 miRNAs and 3 of these miRNAs were validated to be associated with LVR in vivo: miR-21-5p, miR-23a-3p and miR-222-3p. The second approach predicts 24 miRNAs among 1310 molecules and 6 of these miRNAs were selected to be associated with LVR in silico: miR-17-5p, miR-21-5p, miR-26b-5p, miR-222-3p, miR-335-5p and miR-375. We identified a signature of 7 microRNAs associated with LVR after MI that support the interest of integrative systems biology analyses to define a miRNA signature of HF progression.

This study aimed to evaluate potential posttreatment changes in ADC values within the tissue surrounding the enhancing lesion, particularly in areas not exhibiting MRI characteristics of in-volvement. Additionally, the objective was to investigate the correlation between ADC values, treatment response, and survival outcomes in individuals diagnosed with gliomas. This retrospective study included a total of 49 patients that underwent either stereotactic biopsy or maximal surgical resection. Histologically confirmed as Grade III or IV gliomas, all cases adhered to the 2016 and 2021 WHO classifications, with subsequent radio-chemotherapy administered post-surgery. Patients were divided into two groups: short and long survival group. Baseline and follow-up MRI scans were obtained on a 1.5T MRI scanner. Two ROI circles were positioned near the enhancing area, one ROI in the NAWM ipsilateral to the neoplasm and another symmetrically in the contralateral hemisphere on ADC maps. At follow-up there was a significant difference in both ipsilateral and contralateral NAWM be-tween the two groups, -0.0857 (p=0.004) and -0.0607 (p=0.037), respectively. There was a weak negative correlation between survival and ADC values in ipsilateral and contralateral NAWM at the baseline with the correlation coefficient -0.328 (p=0.02) and -0.302 (p=0.04), respectively. The correlation was stronger at the follow-up. The findings indicate that ADC values in normal appearing white matter (NAWM) may function as a prognostic biomarker in patients with diffuse gliomas.

Human papillomavirus testing is increasingly central to screening programs for cervical cancer. Although HPV testing has excellent clinical sensitivity it suffers from modest clinical specificity. Cytology has taken an important role as a triage test, while more recently HPV16/18 genotyping has provided modest incremental benefits. Despite such progress issues remain to be addressed, some of which are how to: 1) improve access to the best methods, 2) decrease costs so more women can be screened, 3) simplify management algorithms, 4) Recognize the evolving diagnostic landscape created by widespread HPV vaccination. Part of the solution lies in improving the positive predictive value of the initial screen and reflex triage. An aspirational goal should be that most women attending colposcopy have true precancer; DNA methylation testing has a role to play here. Cervical cancers and CIN2/3 generally have high levels of methylation in target human and HPV genes. In contrast normal and healthy women with no intraepithelial lesions or malignancy usually have low methylation. Furthermore, there is an interesting and useful secular gradient of increasing cervical DNA methylation as women progress toward precancer and cancer. Recent results from clinical studies using commercially available routine qPCR-based DNA methylation tests have been encouraging, demonstrating the potential for higher sensitivity and specificity than current triage methods.

Through the ACE2, a main enzyme of the renin-angiotensin system (RAS), the SARS-CoV2 gains access into the cell, resulting in different complications which may extend beyond the RAS and impact the Arachidonic Acid (ArA) pathway. The contribution of the RAS through ArA pathways metabolites in the pathogenesis of COVID-19 is unknown. We investigated whether RAS components and ArA metabolites can be considered biomarkers of COVID-19. We measured the plasma levels of RAS and ArA metabolites using an LC-MS/MS. Results indicate that Ang1-7 levels were significantly lower, whereas Ang II levels were higher in the COVID-19 patients than healthy control individuals. The ratio of Ang1-7/Ang II as an indicator of the RAS classical and protective arms balance was dramatically lower in COVID-19 patients. There was no significant increase in inflammatory 19-HETE and 20-HETE lev-els. The concentration of EETs was significantly increased in COVID-19 patients, whereas the DHETs concentration was repressed. Their plasma levels were correlated with Ang II concentration in COVID-19 patients. In conclusion, evaluating the RAS and ArA pathway biomarkers could provide helpful information for the early detection of high-risk groups, avoid delayed medical attention, facilitate resource allocation and improve patient clinical outcomes to prevent long COVID incidence.

The neurologic effects of long-COVID are a therapeutic challenge. This article discusses the immunologic manifestations of long-COVID and proposes a non-androgenic, synthetic analog of dehydroepiandrosterone (DHEA), bromo-epi-androsterone (BEA), as a candidate for clinical trials for this exigent collection of neurologic conditions. Moreover, because there is an association between long-COVID and Alzheimer’s disease, the evaluation of BEA in long-COVID may serve as a proxy for its effect on neuroinflammatory biomarkers of Alzheimer’s disease that are shared with long-COVID.

Diabetic retinopathy (DR) is a progressive blinding disease that affects vision and quality of life of patients and severely impacts society. This complication, caused by abnormal glucose metabolism, leads to structural, functional, molecular, and biochemical abnormalities in the retina. Oxidative stress (OS) and inflammation also play pivotal roles in the pathogenic process of DR, leading to mitochondrial damage and decrease in the mitochondrial function. DR causes retinal degeneration in glial and neural cells, while the disappearance of pericytes in retinal blood vessels leads to modifications in vascular regulation and stability. Clinical changes include dilatation and blood flow alterations in response to the reduce in retinal perfusion in retinal blood vessels, leading to vascular leakage, neovascularization and neurodegeneration. Thus, DR is a highly complex disease with various biological factors that contribute to its pathogenesis. The interplay between biochemical pathways and non-coding RNAs (ncRNAs) is essential for understanding the development and progression of DR. Abnormal expression of ncRNAs has been confirmed to promote the development of DR, suggesting that ncRNAs such as miRNAs, lnc-RNAs and circ-RNAs have potential as diagnostic biomarkers and theranostic targets in DR. This review provides an overview of interactions between abnormal biochemical pathways and dysregulated expression of ncRNAs under the influence of hyperglycemic environment in DR.

Abstract: Background: COVID-19 is associated with various changes in immunity, including signaling through the pattern-recognition receptors (PRR). However, the role of these processes is poorly understood. The present study aimed to evaluate the relationships of the serum levels of the cyclic dinucleotide 2’3’-cyclic GMP-AMP (cGAMP) marker of PRR activation with immunoglobulin G antibodies against severe acute respiratory syndrome-linked coronavirus (IgG-SARS)-positive status and endothelial dysfunction in apparently healthy subjects and in patients with coronary heart disease (CHD). Methods: The present study investigated selected groups from two cohorts, including cohort 1 of 307 healthy volunteers and cohort 2 of 218 CHD patients. COVID-19 infection was confirmed by the detection of IgG-SARS against SARS-CoV-2 S1 protein receptor-binding domain. Cohort 1 (24–69 years of age; 44.8 ± 8.6 years; 80.4% men) was examined for systematic coronary risk evaluation by European Society of Cardiology (SCORE) starting from 2019 before the onset of the COVID-19 pandemic. Cohort 2 (63±10.9 years of age, 54% men) was processed starting from 2017 (three years prior to the COVID-19 pandemic) in a hospital setting to undergo coronary angiography to assess coronary lesions as Gensini score. The levels of cGAMP and endothelial markers (nitrate and nitrite combined as NOx and endothelin-1) were assessed in the serum to evaluate the associations with IgG-SARS status, SCORE, and extent of coronary lesions by correlation and receiver operating characteristic (ROC) analyses. Results: Serum cGAMP did not discriminate between SARS-positive and SARS-negative healthy subject of cohort 1. Moreover, the level of cGAMP was not associated with endothelial biomarkers in healthy subjects. However, serum cGAMP was associated with atherosclerosis in cohort 2 in patients with CHD (area under the curve (AUC) 0.69; 95% CI 0.587-0.806; P=0.001), indicating that serum cGAMP was lower in patients with coronary stenosis compared to that in patients without coronary lesions. Conclusions: Low levels of serum cGAMP were associated with atherosclerosis and markers of endothelial dysfunction in patients with CHD. However, cGAMP was not associated with endothelial biomarkers or IgG-SASR immune status in healthy subjects, suggesting that cGAMP may be a new biomarker of coronary lesions in the context of sterile inflammation.

Dermatophagoides pteronyssinus (Der p) subcutaneous immunotherapy (SCIT) has demonstrated efficacy in clinical trials of childhood allergic rhinitis (AR). Currently, there is a lack of some generally accepted biomarkers that may predict the clinical response to SCIT to eventually achieve personalized therapy. In this study, 28 children with AR received Der p SCIT for 26-30 months at baseline, and four efficacy endpoints, serum interleukin (IL)-5, periostin, Der p-specific IgE (sIgE), and Der p sIgG4, were measured by ELSIA. Clinical symptoms and characteristics were assessed by questionnaires, and the associations among periostin, Der p 2 sIgE and clinical efficacy were analyzed. The results showed that SCIT demonstrated a significant reduction in Der p 1 sIgE (P < 0.05) and Der p 2 sIgE (P < 0.01), an increase in Der p sIgG4 (P < 0.001) and an improvement in clinical efficacy at the fourth efficacy endpoint compared with that at baseline. A positive linear correlation was found in serum periostin and Der p sIgE (Pearson correlation=0.8868, P=0.045), Der p sIgG4 (Pearson correlation=-0.9025, P=0.036), and clinical efficacy. Importantly, the concentration of serum Der p 2 sIgE showed a positive linear correlation with clinical efficacy and serum periostin (Pearson correlation=0.9581, P=0.010). These results suggest that SCIT can result in reduced type 2 cytokines and Der p sIgE and has long-term efficacy in children with AR. Der p 2 sIgE has a positive linear correlation with clinical efficiency and serum periostin and may be a useful biomarker for the prediction of SCIT.

Chronic Traumatic Encephalopathy (CTE) is a neurodegenerative disease consistently associated with repetitive traumatic brain injuries (TBIs), which makes multiple professions, such as contact sports athletes, especially susceptible to its onset. There are currently no approved biomarkers to diagnose CTE, thus it can only be confirmed through a post-mortem brain autopsy. Several imaging and cerebrospinal fluid biomarkers have shown promise in the diagnosis. However, blood-based biomarkers can be more easily obtained and quantified, increasing their clinical feasibility and potential for prophylactic use. This article aimed to comprehensively review the studies into potential blood-based biomarkers of CTE, discussing common themes and limitations as well as suggesting future research directions. While the interest in blood-based biomarkers of CTE has recently increased, the research is still in its early stages. The main issue for many proposed biomarkers is their lack of selectivity for CTE. However, several molecules, such as tau phosphorylated on different epitopes, were able to discern CTE from different neurodegenerative diseases. Further, results from studies of exosomal biomarkers suggest that exosomes are a promising source of biomarkers reflective of the internal environment of the brain. Nonetheless, more longitudinal studies combining imaging, neurobehavioral and biochemical approaches are warranted to establish robust biomarkers of CTE.

Lung cancer remains the leading cause of cancer-related mortality worldwide. The main issue is the absence of a screening test available in clinical practice; the identification of non-invasive biomarkers is thus an urgent clinical necessity. Currently, low-dose computed tomography (LD-CT) demonstrates a 20% reduction of lung cancer mortality. However, it is not particularly suitable for clinical practice because of the costs, radiation, and the false positive rate. Several studies have therefore focused on research into biomarkers in body fluids. Despite the power of certain molecules to distinguish lung cancer patients from healthy subjects, no biomarker has yet been shown to significantly and reliably influence clinical decisions or to be translated from the laboratory to clinical practice. We performed an overview of the peer-reviewed biomedical literature published in the last 10 years on the research regarding biomarkers for the early diagnosis of lung cancer via a comprehensive analysis of the reviews published this past year. Our main aim was to bring to light the limitations and strengths of the research already conducted. Furthermore, future prospectives have been explored, bearing in mind the management of clinical trials and their integration into clinical practice.

No studies have examined the immune fingerprint of major neuro-cognitive psychosis (MNP) or deficit schizophrenia using M1 macrophage cytokines in combination with chemokines such as CCL-2 and CCL-11. The present study delineated the neuro-immune fingerprint of MNP/deficit schizophrenia by analyzing plasma levels of IL-1β, sIL-1RA, TNF-α, sTNFR1, sTNFR2, CCL-2 and CCL-11 in MNP (n=120) versus healthy controls (n=54) in association with neurocognitive deficits (as assessed with the Brief Assessment of Cognition in Schizophrenia) and PHEMN (psychotic, hostility, excitation, mannerism and negative) symptoms. All immune biomarkers were significantly higher in MNP than in normal controls. MNP was best predicted by a combination of CCL-11, TNF-α, IL-1β and sIL-1RA which yielded a bootstrapped (n=2000) area under the Receiver Operating Curve of 0.985. Composite scores reflecting M1 macrophage activity and neurotoxic potential including combined effects of CCL-11 plus CCL-2 were significantly increased in MNP. Nevertheless, the effects of increased IL-1β and TNF-α in MNP were attenuated (statistically) by increased sIL-1RA and sTNFR2, two negative immune-regulatory markers. A large part of the variance in PHEM (38.4%-52.6%) and negative (65.8-7439%) symptoms was explained by combinations of immune markers whereby CCL-11 was consistently the most important. The immune markers also explained a large part of the variance in the Mini Mental State examination, list learning, digit sequencing task, category instances, controlled word association, symbol coding and Tower of London. Soft Independent Modeling of Class Analogy performed on the biomarkers showed that the inter-class distance between the models constructed around MNP and controls was 19.3 indicating a good separation. Partial Least Squares analysis showed that 72.7% of the variance in overall phenomenology was explained by the regression on IL-1β, sIL-1RA, CCL-11, TNF-α (all positively) and education (inversely). It is concluded that the combination of the above-mentioned markers defines MNP as a distinct neuro-immune disorder and that those markers in combination explain a large part of the variance in memory and executivive impairments and PHEMN symptoms.

The incidence of hepatocellular carcinoma (HCC) is increasing and 40% of patients are diagnosed at advanced stages. Over the past 5 years, the number of clinical available treatments have dramatically increased for HCC, making patient management particularly complex. Immune checkpoint inhibitors (ICIs) have improved the overall survival of patients showing a durable treatment benefit over time, and a different response pattern with respect to tyrosine kinase inhibitors (TKIs). Although improved survival in responder cases, a sizeable group of patients are primary progressors or are ineligible for immunotherapy. Indeed, patients with non-viral etiologies, such non-alcoholic steatohepatitis (NASH), and alterations in specific driver genes might be less responsive to immunotherapy. Therefore, improving the comprehension of mechanisms of drug resistance and identifying biomarkers informative of the best treatment approach are required actions to improve patient survival. Numerous evidence indicated non-coding RNAs (ncRNAs) as pivotal players in cancer. Molecular mechanisms through which ncRNAs exert their effects in cancer progression and drug resistance have been widely investigated. Nevertheless, there are no studies summarizing the synergistic effect between ncRNA-based strategies and TKIs or ICIs in the preclinical setting. This review aims to provide up-to-date information regarding the possible use of ncRNAs as therapeutic targets in association with molecular targeted agents and immunotherapies and as predictive tools for the selection of optimized treatment options in advanced HCCs.

Objective: About a third of schizophrenia patients are treatment-resistant to antipsychotic therapy. No studies established the fingerprints or pathway-phenotypes of treatment-resistant schizophrenia. The present study aimed to delineate the pathway-phenotypes of non-responders (NRTT) and partial responders (PRTT) to treatment using machine learning. Methods: We recruited 115 schizophrenia patients and 43 healthy controls and measured schizophrenia symptom dimensions, neurocognitive tests, plasma CCL11, interleukin-(IL)-6, IL-10, Dickkopf protein 1 (DKK1), high mobility group box-1 protein (HMGB1), κ- and µ-opioid receptors (KOR and MOR, respectively), endomorphin-2 (EM-2), and β-endorphin. Results: Machine learning showed that the NRTT group is a qualitatively distinct class and is significantly discriminated from PRTT with an accuracy of 100% using a neuro-immune-opioid-cognitive (NIOC) pathway-phenotype with as main determinants list learning, controlled word association, and Tower of London test scores, CCL11, IL-6, and EM2. The top-5 symptom domains separating NRTT from PRTT were in descending order: psychomotor retardation, negative symptoms, psychosis, depression, and mannerism. Moreover, a NIOC pathway also discriminated PRTT from healthy controls with an accuracy of 100% while all PRTT and controls were authenticated as belonging to their respective classes. Conclusion: A non-response to treatment with antipsychotics is determined by increased severity of specific symptom profiles coupled with deficits in executive functions, and episodic and semantic memory, and aberrations in neuro-immune and opioid pathways. No patients showed complete remission after treatment indicating that non-remitting in PRTT is attributable to increased HMGB1 and residual deficits in attention, executive functions, and semantic memory.

Mucopolysaccharidosis type IVA (MPS IVA; Morquio A syndrome) is a rare autosomal recessive lysosomal storage disease (LSD) caused by deficiency of a hydrolase enzyme, N-acetylgalactosamine-6-sulfate sulfatase, and characterized clinically by mainly musculoskeletal manifestations. The mechanisms underlying bone involvement in humans are typically explored using invasive techniques such as bone biopsy, which complicates analysis in humans. We compared bone proteomes using DDA and SWATH-MS in wild-type and MPS IVA knockout mice to obtain mechanistic information about the disease. Our findings reveal over 1000 dysregulated proteins in knockout mice, including those implicated in oxidative phosphorylation, oxidative stress (reactive oxygen species), DNA damage, and iron transport, and suggest that lactate dehydrogenase may constitute a useful prognostic and follow-up biomarker. Identifying biomarkers that reflect MPS IVA clinical course, severity, and progression have important implications for disease management.

NSCLC is a very aggressive solid tumor, with a poor prognosis due to post-surgical recurrence. Analysis of the specific tumor and immune signatures of NSCLC samples is a critical step in prognostic evaluation and management decisions for patients after surgery. Routine histological assay has some limitations. Therefore, new diagnostic tools with the capability to quickly recognize NSCLC subtypes and correctly identify various markers are needed. We developed a technique for ex vivo expansion of cancer and immune cells from surgical tumor and lung tissue samples of patients with NSCLC (adenocarcinomas and squamous cell carcinomas) and their examination on ex vivo cell preparations and, parallelly, on histological sections after Romanovsky–Giemsa and immunofluorescent/immunochemical staining for cancer-specific and immune-related markers. As a result, PD-L1 expression was detected for some patients only by ex vivo analysis. Immune cell profiling in the tumor microenvironment revealed significant differences in the immunological landscapes between the patients’ tumors, with smokers’ macrophages with simultaneous expression of pro- and anti-inflammatory cytokines, neutrophils, and eosinophils being the dominant populations. The proposed ex vivo analysis may be used as an additional diagnostic tool for quick examining cancer and immune cells in whole tumor samples and avoiding false negatives in histological assays.

Ongoing beta cell death in type 1 diabetes (T1D) can be detected using biomarkers selectively discharged by dying beta cells into plasma. MicroRNA-375 (miR-375) ranks among top biomarkers based on studies in animal models and human islet transplantation. Our objective was to identify additional microRNAs that are co-released with miR-375 proportionate to the amount of beta cell destruction. RT-PCR profiling of 733 microRNAs in a discovery cohort of T1D patients 1 hour before/after islet transplantation indicated increased plasma levels of 22 microRNAs. Sub-selection for beta cell selectivity resulted in 15 microRNAs that were subjected to double-blinded multicenter analysis. This led to identification of 8 microRNAs that were consistently increased during early graft destruction: besides miR-375, these included miR-132/204/410/200a/429/125b, microRNAs with known function and enrichment in beta cells. Their potential clinical translation was investigated in a third independent cohort of 46 transplant patients, by correlating post-transplant microRNA levels to C-peptide levels 2 months later. Only miR-375 and miR-132 had prognostic potential for graft outcome and none of the newly identified microRNAs outperformed miR-375 in multiple regression. In conclusion, this study reveals multiple beta cell-enriched microRNAs that are co-released with miR-375 and can be used as complementary biomarkers of beta cell death.

Abstract: The aim of the study was to evaluate two widely studied biomarkers: MMP-9 and S100B in blood serum in healthy people after physical exercise mimicking physical activity during bi-lateral tonic-clonic seizures. Both biomarkers have been shown to increase after seizures, and their serum levels tend to be higher in epilepsy patients compared to individuals without epi-lepsy. To achieve this goal, we have developed two sets of exercises, each consisting of a tonic contrac-tion phase and a phase of alternating muscle work, lasting a total of approximately 5 minutes. Both sets of motor exercises were performed in the same group of healthy volunteers 6 months apart. Serum samples were collected before exercise, 3 hours after exercise, and the next day (time points 0, 3 hours, and 24 hours). Our results demonstrated that both sets of motor exercises led to a similar increase in MMP-9 levels, while neither while neither affected S100B levels. No significant differences in MMP-9 levels were observed due to muscle failure. We propose that the increase in MMP-9 is primarily induced by muscle contraction and additional mechanisms observed during exercise, such as neutrophil degranulation. S100B appears to be a promising biomarker in epilepsy, as it is not induced by physical activity but does increase following seizures.

Background: Physiosomatic symptoms are an important part of schizophrenia phenomenology. The aim of this study is to examine the biomarker, neurocognitive and symptomatic correlates of physiosomatic symptoms in schizophrenia. Methods: We recruited 115 schizophrenia patients and 43 healthy controls and measured the Fibromyalgia and Chronic Fatigue Syndrome Rating (FF) scale, schizophrenia symptom dimensions, and the Brief Assessment of Cognition in Schizophrenia. We measured neuro-immune markers including plasma CCL11 (eotaxin), interleukin-(IL)-6, IL-10, Dickkopf protein 1 (DKK1), high mobility group box 1 protein (HMGB1) and endogenous opioid system (EOS) markers including κ-opioid receptor (KOR), µ-opioid receptor (MOR), endomorphin-2 (EM2) and β-endorphin. Results: Patients with an increased FF score display increased ratings of psychosis, hostility, excitement, formal though disorders, psychomotor retardation and negative symptoms as compared with patients with lower FF scores. A large part of the variance in the FF score (55.1%) is explained by the regression on digit sequencing task, token motor task, list learning, IL-10, age (all inversely) and IL-6 (positively). Neural network analysis shows that the top-6 predictors of the FF score are (in descending order): IL-6, HMGB1, education, MOR, KOR and IL-10. We found that 45.1% of the variance in a latent vector extracted from cognitive test scores, schizophrenia symptoms and the FF score was explained by HMGB-1, MOR, EM2, DKK1, and CCL11. Conclusions: FF symptoms are an integral part of the phenome of schizophrenia. Neurotoxic immune and neurodegenerative pathways and to a lesser extent the EOS appear to drive FF symptoms in schizophrenia.

The progression of the recent COVID-19 pandemic surprised political authorities as well as scientists. The possibility to design powerful strategies for health care and preserving economic and social activities strongly relies on the capacity to monitor correctly the virus spreading and the immune response in the symptomatic and asymptomatic population. The available data relative to the first pandemic months indicate that the test reliability was progressively improved but also that the extremely variable methodologies used in the diagnostic studies generated data that are often not comparable. This condition prevents a simple metadata analysis for the identification of reliable diagnostics guidelines. Nevertheless, there are converging evidences that combinations of complementary approaches may enable more precise identification of virus infection. Furthermore, it appears that the similarities between SARS-CoV2 and the related types SARS-CoV1 and MERS that caused outbreaks in the last 20 years can be exploited to infer some information for which no direct evidence is still available

Prevalence estimates of Parkinson’s disease (PD) – the fastest growing neurodegenerative disease – are underestimated due to issues surrounding diagnostic accuracy, symptomatic undiagnosed cases, suboptimal prodromal monitoring, and limited screening access. Remotely monitored wearable devices and sensors provide precise, objective, and frequent measures of motor and non-motor symptoms. Here, we used consumer-grade wearable device and sensor data from the WATCH-PD study to develop a PD screening tool aimed at eliminating gaps between patient symptoms and diagnosis. Early-stage PD (n=82) and age-matched comparison (n=50) participants completed a multidomain assessment battery during a one-year longitudinal multicenter study. Using disease- and behavior-relevant feature engineering and multivariate machine learning modeling of early-stage PD status, we developed a highly accurate (92.3%), sensitive (90.0%), and specific (100%) Random Forest classification model (AUC=0.92) that performed well across environmental contexts. These findings provide robust support for further exploring consumer-grade wearable devices and sensors for global population-wide PD screening and surveillance.

The identification of biomarkers is crucial for cancer diagnosis, understanding the underlying biological mechanisms, and developing targeted therapies. In this study we propose a machine learning approach to predict the outcome and platinum resistance status of ovarian cancer patients using public available gene expression data. Six classical machine learning algorithms are compared on their predictive performance. Those with the highest score are analyzed by their feature importance using the SHAP algorithm. We were able to select multiple genes that were correlating with the outcome and platinum resistance status of the patients and validated those using Kaplan-Meier plots. In comparison to similar approaches the performance of the models were higher and different genes using feature importance analysis were identified. The most promising identified genes that could be used as biomarkers are: TMEFF2, ACSM3, SLC4A1 and ALDH4A1.

Ulcerative colitis (UC) is one of the two disorders known as inflammatory bowel diseases (IBD) along with Crohn’s disease (CD), with complex pathogenesis, requiring costly invasive investigations. Objective: to examine the most recent biomarkers proposed for UC diagnosis; to establish the strategy used to make the differential diagnosis between UC and CD relying on these biomarkers, also adding the benefit of finding new non-invasive tools in managing this condition. The search was performed in a single database (Web of Science) using the specific keywords „ulcerative colitis”, „biomarkers” and „diagnosis” for the last five years. Study eligibility criteria: clinical trials on adults and pediatric patients with ulcerative colitis compared with Crohn’s disease. Results: We selected 57 studies, randomized controlled trials (RCTs) and clinical case series (CCS), summarizing the latest most specific biomarkers in diagnosis of UC. Limitations: we considered RCTs and CCS from one database, limited to the search topics. Our findings indicate a important number of potential biomarkers with diagnostic value, which bring the advantage of a non-invasive method to approach this challenging disorder.

The present study was developed based on the data of The PDWAVES Consortium (www.pdwaves.eu) and the PharmaCog project. The Partners and institutional affiliations are reported on the cover page of this manuscript. In this study, the clinical, neuropsychological, and magnetic resonance imaging data collection and analysis in patients with ADMCI and healthy control participants were partially supported by the funds of “Ricerca Corrente 2022-2023” (Italian Ministry of Health) to the IRCCS Synlab SDN of Naples (Italy), IRCCS Ospedale San Martino of Genoa (Italy), Oasi Research Institute-IRCCS, Troina (Italy), IRCCS Fatebenefratelli of Brescia (Italy), and IRCCS San Raffaele Pisana of Rome (Italy). Prof. Claudio Del Percio’s and Dr. Roberta Biundo’s work for this study was supported by funds of the “PRIN-2022” project entitled "AmyEEG” (Italian Ministry of University and Research, Prot. 2022FJAXY8). At the same time, Prof. Claudio Babiloni’s work was supported by funds of the “Horizon Marie S. Curie Doctoral Network ” project entitled "CombiDiag” (European Committee, Proposal: 101071485).

A number of agents, including immune checkpoint inhibitors, have become available for the treatment of hepatocellular carcinoma (HCC). However, the objective response rate of these drugs is currently only 30% to 40%, with a high incidence of side effects. There are also no prac-tical biomarkers to predict their therapeutic effects. Most of the systemic therapies for HCC are performed in general hospitals without research facilities. Such hospitals can perform imaging tests, like CT and MRI, as well as pathological diagnosis using tumor tissue sampling and im-munohistochemical staining. However, analyzing tumor genomic or transcriptomic profiles is difficult because of limitations in facilities, personnel, and cost. Therefore, in this review, we provide an overview of the wide range of research that has been conducted on HCC biomarkers from blood, tissue, or imaging information that can be used practically in general hospitals for predicting the therapeutic effect of systemic therapies before treatment begins. For general hos-pitals that treat HCC patients, we recommend conducting treatment after assessing the state within the tumor tissue as much as possible by collecting blood and tissue samples and per-forming pre- treatment MRI image evaluations.

Cancer is a complex and heterogeneous disease, influenced by various factors that affect its progression and response to treatment. Although histopathological diagnosis is crucial for identifying and classifying cancer, it may not accurately predict the disease's development and evolution in all cases. To address this limitation, liquid biopsy has emerged as a valuable tool, enabling a more precise and non-invasive analysis of cancer. Liquid biopsy offers the ability to detect tumor DNA fragments, circulating tumor cells, and exosomes released by cancer cells into the bloodstream. Exosomes, in particular, have attracted significant attention in cancer research due to their specific protein composition, which can provide valuable insights into the disease. The protein profile of exosomes often differs from that of normal cells, reflecting the unique molecular characteristics of cancer. Analyzing these proteins can help identify cancer-associated markers that play critical roles in tumor progression, invasion, and metastasis. Ongoing research and clinical validation are essential to advance and effectively utilize protein biomarkers in cancer. Nevertheless, their potential to improve diagnosis and treatment is highly promising. This review discuss several exosome proteins of interest in breast cancer, particularly focusing on studies conducted in mammary tissue and cell lines in humans and experimental animals. Unfortunately, the studies conducted in the canine species are scarce. This emphasis sheds light on the limited research available in this field. Additionally, we present a curated selection of studies that have explored exosomal proteins as potential biomarkers, aiming to achieve the aforementioned benefits in breast cancer diagnosis, prognosis, monitoring, and treatment.

Clinical management in neuro-oncology has changed to an integrative approach that incorporates molecular profile alongside histopathology and imaging findings. While the WHO guideline recommends genotyping of informative alterations as a routine clinical practice for central nervous system (CNS) tumors, acquisition of tumor tissue in the CNS is invasive and not always possible. Liquid biopsy is a non-invasive approach that provides the opportunity to capture the complex molecular heterogeneity of the whole tumor through detection of circulating tumor biomarkers in body fluids, such as blood or cerebrospinal fluid. Despite all the advantages, the low abundance of tumor-derived biomarkers, particularly in CNS tumors, as well as their short half-life has limited the application of liquid biopsy in clinical practice. Thus, it is crucial to identify factors that are associated with the presence of these biomarkers and explore possible strategies that can increase the shedding of these tumoral components into biological fluids. In this review, we first describe the clinical applications of liquid biopsy in CNS tumors including its roles in early detection of recurrence and monitoring of treatment response. We then discuss the utilization of imaging in identifying factors that affect the detection of circulating biomarkers as well as how image-guided interventions such as focused ultrasound can help enhance the presence of tumor biomarkers through blood-brain barrier disruption.

The COVID-19 pandemic has brought marked changes worldwide to the management of airborne infectious diseases. It sparked the development of the SARS-CoV-2 vaccine and pharmacotherapeutics to prevent infection and increase the survival rate during the acute viral phase and the comorbidities associated with COVID-19. Periodontal disease may increase the morbidity and perhaps the mortality of a COVID-19 infection. However, the molecular interaction between periodontitis and COVID-19 infection remains undetermined. A potential pathogenic co-morbidity may involve periodontal pathogenic release of destructive cytokines in the highly inflamed connective tissue and risk for COVID-19. Additional biomarkers such as C-reactive proteins appear to play a role for risk and pathogenesis of COVID-19. The potential of herpesviruses, especially as it is related to aggressive periodontitis may also be a comorbidity for COVID-19. This paper reviews available evidence on the bidirectional association between periodontitis and COVID-19.

Extracellular vesicles (EVs) are secreted by almost every cell type and are considered as carriers of active biomolecules, such as nucleic acids, proteins and lipids. Their content can be up-taken and released into the cytoplasm of recipient cells, thereby inducing gene reprogramming and phenotypic changes in the acceptor cells. Whether the effects of EVs on the physiology of recipient cells are mediated by individual biomolecules or it is the collective outcome of the total transferred EV content, is still under debate. The EV RNA content consists of several types of RNA, such as messenger RNA (mRNA), microRNA (miRNA) and long non-coding RNA (lncRNA), the latter defined as transcripts longer than 200 nucleotides, that do not code for proteins, but with important established biological functions. This review aims to update our insights on the functional roles of EV and their cargo non-coding RNA during cancer progression, to highlight the utility of EV RNA as novel diagnostic or prognostic biomarkers in cancer, and to tackle the technological advances and limitations for EV RNA identification, integrity assessment and preservation of its functionality.

Bees have long been used as a bioindicator of environmental quality. They have the capacity to bio-accumulate various pollutants in cities such as PAHs and heavy metals, but they are also very sensitive to other pollutants in rural areas such as pesticides. The lethal and sub-lethal impacts of pesticides on bees have been extensively studied. However, studies often focus on a single molecule at a same time and rarely on a cocktail of pesticides. The oxidant stress in response to metals and NOx was also measure, but no studies were engaged on the impact of PAHs on honeybees. The aim of this study was to measure the oxidative stress in bees in response to the chronic ingestion of a mixture of pesticides (representative of pollutants in rural areas) on the first hand and a mixture of PAHs (representative of pollutants in urban areas) on the other hand, compared to a control group. We also wanted to determine whether this tool is effective in detecting environmental measures aimed at reducing pollution in urban and rural areas.

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Bisphenol A analogs (BPA analogs) are emerging contaminants with a rising production caused by the replacement of BPA with these compounds. The increased production of BPA analogs is leading to an increased release into various ecosystems, including sea. The aim of this study was to evaluate the biological effects of BPA analogs on a primary producer, the diatom Phaeodactylum tricornutum Bohlin. Three different BPA analogs (BPAF, BPF, and BPS) and their mixture were tested at the environmental relevant concentration of 300 ng/L. Growth curve, cell size and several biomarkers of oxidative stress and oxidative damage were measured. Our results indicated that the tested compounds caused alteration of the growth and induced oxidative stress altering many antioxidant enzymes. However, no oxidative damages were observed.

The noncoding RNAs (ncRNAs) are small transcript sequences that do not encode proteins but participate in the regulation of gene expression at the post-transcriptional level playing important biological roles such as proliferation and differentiation. In the tumor microenvironment, the dysregulated immunological response can participate in the progression and negative phenotype of cancer, the variability of switch cell differentiation and activation of the different immune cell lineages showed differential regulation by the type of cancer. Recent evidence showed that the upregulation of lncRNA can be used as a biomarker and predictive indicator for cancer progression. The use of lncRNA to turn off the tumor immune response and activate the anti-tumoral immune response is day by day a promising reality for the control of cancer. However, is imperatively elucidated the role of each ncRNA identified as well as its respective molecular pathways regulated, including the immune checkpoints, before its application at the clinical level. The correct delivery of lncRNA or mimics to inhibit its expression using the most efficient carriers to the cell or cellular organelle is a science that should continue to be developed.

Background: Biomarker development, improvement, and clinical implementation in the context of kidney disease has been a central focus of biomedical research for decades. To this point, only serum creatinine and urinary albumin excretion are well accepted biomarkers in kidney disease. With their known blind spot in early stages of kidney impairment and diagnostic limitations there is a need for better and more specific biomarkers. With the rise of large-scale analysis of thousands of peptides in serum or urine samples using mass spectrometry techniques hopes for biomarker development were high. Advances in proteomic research have led to the discovery of an increasing amount of potential proteomic biomarkers and identification of candidate biomarkers for clinical implementation in the context of kidney disease management. In this review we focus on urinary peptide and especially peptidomic biomarkers emerging from recent research and underline the role of those with the highest potential for clinical implementation. Methods: The Web of Science database (all databases) was searched on October 17th, 2020, using the search terms “marker*” OR biomarker* AND “renal disease” OR “kidney disease” AND “proteome*” OR “peptid*” AND “urin*”. English, full-text original articles on humans published within the last 5 years were included which were cited at least 5 times per year. Studies based on animal models, renal transplant studies, metabolite studies, studies on miRNA and studies on exosomal vesicles were excluded focusing on urinary peptide biomarkers. Results: The described search led to the identification of 3668 articles and application of inclusion and exclusion criteria as well as abstract and consecutive full-text analysis of 3 independent authors to a final number of 62 studies for this manuscript. The 62 manuscripts encompassed 8 established single peptide biomarkers and several proteomic classifiers including CKD273 and IgAN237. Discussion: This review provides a summary of recent evidence on single peptide urinary biomarkers in CKD while emphasizing the increasing role of proteomic biomarker research with new research on established and new proteomic biomarkers. Lessons learned from the last 5 years in this review might encourage future studies hopefully resulting in routine clinical applicability of new biomarkers.

Currently, large volumes of data are being collected on farms using multimodal sensor technol-ogies. These sensors measure the activity, housing conditions, feed intake, and health of farm animals. With traditional methods, the data from farm animals and their environment can be collected intermittently. However, with the advancement of wearable and non-invasive sensing tools, these measurements can be made in real-time for continuous quantitation relating to clinical biomarkers, resilience indicators, and behavioral predictors. The digital phenotyping of humans has drawn enormous attention recently due to its medical significance, but much research is still needed for the digital phenotyping of farm animals. Implications from human studies show great promise for the application of digital phenotyping technology in modern livestock farming, but these technologies must be directly applied to animals to understand their true capacities. Due to species-specific traits, certain technologies required to assess phenotypes need to be tailored ef-ficiently and accurately. Such devices allow for the collection of information that can better inform farmers on aspects of animal welfare and production that need improvement. By explicitly ad-dressing farm animals’ individual physiological and mental (affective states) needs, sensor-based digital phenotyping has the potential to serve as an effective intervention platform. Future re-search is warranted for the design and development of digital phenotyping technology platforms that create shared data standards, metrics, and repositories.

Metabolites are essential intermediate products in metabolism, and metabolism dysregulation indicates different types of diseases. Previous studies have shown that cigarette smoke dysregulated metabolites; however, limited information is available with electronic cigarette (E-cig) vaping. We hypothesized that E-cig vaping and cigarette smoking altered systemic metabolites, and we propose to understand the specific metabolic signature between E-cig users and cigarette smokers. Plasma from non-smoker controls, cigarette smokers, and e-cig users were collected, and metabolites were identified by UPLC–MS (Ultraperformance liquid chromatography-mass spectrometer). Nicotine degradation was activated by e-cig vaping and cigarette smoking with increased concentrations of cotinine, cotinine N-oxide, (S)-nicotine, and (R)-6-hydroxynicotine. Additionly, we found significant decreased concentrations in metabolites associated with tricarboxylic acid (TCA) cycle pathways in e-cig users verses cigarette smokers, such as: D-glucose, (2R,3S)-2,3-dimethylmalate, (R)-2-hydroxyglutarate, O-phosphoethanolamine, malathion, D-threo-isocitrate, malic acid, and 4-acetamidobutanoic acid. Cigarette smoking significant up-regulated sphingolipid metabolites, such as D-sphingosine, ceramide, N-(octadecanoyl)-sphing-4-enine, N-(9Z-octadecenoyl)-sphing-4-enine, and N-[(13Z)-docosenoyl]sphingosine, verses e-cig vaping. Overall, e-cig vaping dysregulated TCA cycle realted metabolites while cigarette smoking altered sphingolipid metabolites. Both e-cig and cigarette smoke increased nicotinic metabolites. Therefore, specific metabolic signature altered by e-cig vaping and cigarette smoking could serve as potential systemic biomarkers for early cardiopulmonary diseases.

Bronchopulmonary dysplasia (BPD) is a form of chronic lung disease that develops in neonates as a consequence of preterm birth and arrested fetal lung development. The incidence of BPD remains on the rise, as a result of increasing survival of extremely preterm infants. Severe BPD contributes to significant health care costs and is associated with prolonged hospitalizations, respiratory infections, and neurodevelopmental deficits. In this study, we aimed to detect novel biomarkers of severe BPD. We collected tracheal aspirates (TA) from preterm babies with mild/moderate (n = 8) and severe (n = 17) BPD, and we profiled the expression of 1048 miRNAs using a PCR array. Associations with biological pathways were determined with the Ingenuity Pathway Analysis (IPA) software. We found 31 miRNAs differentially expressed between the two disease groups (2-fold change, FDR &lt; 0.05). Of these, 4 miRNAs displayed significantly higher expression levels, and 27 miRNAs had significantly lower expression levels in the severe BPD vs. the mild/moderate BPD group. IPA identified cell signaling and inflammation pathways associated with miRNA signatures. We conclude that TAs of extreme premature infants contain miRNA signatures associated with severe BPD. These signatures may serve as biomarkers of disease severity in infants with BPD.

Metal exposure has been associated with a wide range of adverse birth outcomes and oxidative stress is a leading hypothesis of the mechanism of action of metal toxicity. We assessed the relationship between maternal exposure to essential and non-essential metals and metalloids in pregnancy and oxidative stress markers, and sought to identify windows of vulnerability and effect modification by fetal sex. In our analysis of 215 women from the PROTECT birth cohort study, we measured 14 essential and non-essential metals in urine samples at three time points during pregnancy. The oxidative stress marker 8-iso-prostaglandin F2α (8-iso-PGF2α) and its metabolite 2,3-dinor-5,6-dihydro-15-15-F2t-IsoP, as well as prostaglandin F2α (PGF2α), were also measured in the same urine samples. Using linear mixed models, we examined the main effects of metals on markers of oxidative stress as well as the visit-specific and fetal sex-specific effects. After adjustment for covariates, we found that a few urinary metal concentrations, most notably cesium (Cs) and copper (Cu), were associated with higher 8-iso-PGF2α with effect estimates ranging from 7.3 to 14.9 % for each interquartile range, increase in the metal concentration. The effect estimates were generally in the same direction at the three visits and a few were significant only among women carrying a male fetus. Our data show that higher urinary metal concentrations were associated with elevated biomarkers of oxidative stress. Our results also indicate a potential vulnerability of women carrying a male fetus.

In order to provide a new direction for the diagnosis and treatment of gastric cancer, the differentially expressed blood-based miRNAs in gastric carcinoma were obtained and analyzed from the datasets GSE113486, GSE112264 and GSE113740 by the SangerBox, the miRNA - target genes prediction, GO and KEGG functional enrichment analyses with DAVID 6.8, and the STRING database with Cytoscape, respectively. The correlation between the key miRNAs expression and the prognosis and diagnostic value of gastric cancer patients were detected by survival prognosis and ROC curve. QRT-PCR was used to detect the possible key miRNAs expression in human blood species. The dataset GSE108307 which shows the miRNAs affected by H. pylori infection was analyzed by GEO2R. The expression level of CagA and the clinically used gastric cancer markers were detected in human blood species for contrast. Five key blood-based miRNAs were determined, including hsa-miR-124-3p, hsa-miR-125a-3p, hsa-miR-29b-3p, hsa-miR-4276, and hsa-miR-575.The detection in human blood species as well as the cross analysis with H. pylori infection and clinically used markers expression suggested the importance and efficacy of the specific miRNAs in the early diagnosis and monitoring of gastric carcinoma. The study identified potential novel blood miRNA biomarkers of gastric cancer by bioinformatics and human blood species detection, which may give a new possibility of the important biomarkers for the diagnosis and prognosis of gastric cancer.

Cervical cancer (CC) is the most common cancer in women worldwide and is almost always associated with repeated infections by human papillomavirus (HPV). Screening by traditional tests combined with biomarker identification techniques for low- or high-grade injuries, are becoming increasingly important in diagnosis and prognosis, avoiding countless deaths. This article explores existing literature on the main serum biomarkers and the identification of biomarkers associated with the oncogenesis of HPV expression in the identification of pre-cancerous lesions and of CC for an effective treatment, with reduction of recurrence, as well as we explain strategies for the development of biomarkers based on DNA, proteins and other markers. We also describe how markers of chromosomal instability host DNA, promoting hypo- or hypermethylation of DNA, as well as polymorphisms and epigenetic events in the p53 gene. Finally, we discuss changes in gene expression using cDNA microarray techniques and changes in the expression of proteins and markers identified through mass spectrometry.

Background: Estrogen homeostasis is crucial for bladder function, and estrogen deprivation resulting from ovarian removal or ovarian dysfunction may lead to various bladder dysfunctions. However, the specific mechanisms are not fully understood. Methods: We simulated estrogen deprivation using a rat ovariectomy model and supplemented estrogen through subcutaneous injections. The metabolic characteristics of bladder tissue were analyzed using non-targeted metabolomics, followed by bioinformatics analysis to preliminarily reveal the association between estrogen deprivation and bladder function. Results: We successfully established a rat model with estrogen deprivation and, through multivariate analysis and validation, identified several promising biomarkers represented by 3, 5-tetradecadiencarnitine, lysoPC (15:0), and cortisol. Furthermore, we explored estrogen deprivation-related metabolic changes in the bladder primarily characterized by amino acid metabolism imbalance. Conclusions: This study, for the first time, depicted the metabolic profile of bladder resulting from estrogen deprivation, providing an important experimental basis for future research on bladder dysfunctions caused by estrogen deprivation.

Recent data has shown a continued rise in the worldwide annual incidence and mortality rates of head and neck cancers. The present standard for diagnosis and monitoring for disease recurrence or progression involves clinical examination, imaging, and invasive biopsy techniques of lesions suspected of being malignant. In addition to limitations relating to cost, time, and patient discomfort, these methodologies have inherent inaccuracies for detecting recurrence. In view of these limitations, the analysis of patient bodily fluid samples via liquid biopsy proposes a cost-effective and convenient alternative, which provides insight on the biogenetic and biomolecular underpinnings of oncologic disease processes. Liquid biopsy’s monitoring for biomarkers of head and neck cancer, including circulating tumor DNA, circulating tumor cells, and circulating cell-free RNA, has shown clinical utility in the screening, diagnosis, prognostication, and monitoring of patients with various forms of head and neck cancer. The present review will provide an update on the current literature examining the use of liquid biopsy in head and neck cancer care and the clinical applicability of potential biomarkers, with a focus on viral and non-viral circulating tumor DNA. Possible future avenues for research to address specific shortcomings of liquid biopsy will be discussed.

African swine fever (ASF) is a notifiable viral disease of domestic and wild suids. Despite intensive re-search efforts, the pathogenesis of the disease is still far from being understood. Analysis of biomarkers in different body fluids may supplement traditional pathogenesis studies. As reliable protocols are often es-tablished in laboratories with lower biosafety, reliable inactivation of samples is crucial. The objective of this study was to find a procedure that inactivates the virus while preserving the biomarkers for down-stream analyses. To this means, three different inactivation protocols were employed, namely Tergitol-type NP-40 (NP-40) and polyoxyethylene-p-t-octylphenol (Triton X-100), respectively, and one with 95 °C heating. It could be demonstrated that all samples treated with 0.5% (v/v) concentration of both deter-gents showed absence of virus infectivity. The same was true for heated samples. However, heated serum was not suitable for analyses. Next, the treatment impact on biomarker readouts was assessed. While all protocols had an impact on the detection of biomarkers, correlation was retained. Especially NP-40 could be the desired detergent for more accurate measurements while achieving efficient virus inactivation. Based on these studies, samples can be reliably inactivated for most biomarker analyses and thus broader interdisciplinary cooperation is possible.

Immune reconstitution inflammatory syndrome (IRIS) presents as an exaggerated immune reaction that occurs during dysregulated immune restoration in immunocompromised patients in late-stage HIV infection who commenced antiretroviral treatments. Virtually, any opportunistic pathogen can provoke this type of immune restoration disorders. In this review, we focus on recent development in the identification of risk factors for Cryptococcal IRIS and on advancements in our understanding of C-IRIS immunopathogenesis. We overview new findings in blood and cerebrospinal fluid which can potentially be useful in the diagnosis of cryptococcal meningitis IRIS. We assess the utility of these biomarkers to identify putative host-based targets, which may justify a clinical need for improvement in monitoring a patient’s laboratory results and adjusting treatment modalities in AIDS patients co-infected with Cryptococcus.

Purpose: To investigate the alterations in nitro-oxidative stress (OS) and antioxidant status in adolescents with metabolic syndrome (MetS) and whether these alterations occur independently from effects of overweight or obesity.Methods: Blood was collected in 47 adolescents with MetS and 94 adolescents without MetS as assessed with the International Diabetes Federation criteria. The International Obesity Task Force (IOTF) criteria were used to classify the subjects into those with overweight or obesity. We measured nitro-oxidative biomarkers including nitric oxide metabolites (NOx), lipid hydroperoxides (LOOH), and malondialdehyde (MDA), and antioxidant biomarkers, i.e. total radical-trapping antioxidant parameter (TRAP), paraoxonase (PON)-1 activity, thiol (SH-) groups, as well as tumor necrosis factor-α, glucose, insulin, triglycerides, uric acid and high-density lipoprotein cholesterol (HDL-C).Results: Logistic regression analysis showed that increased MDA and NOx and a lowered TRAP/uric acid ratio were associated with MetS. Machine learning including soft independent modeling of class analogy (SIMCA) showed that the top-3 most important features of MetS were increased glucose and MDA and lowered HDL-C. Support vector machine using MDA, glucose, insulin, HDL-C, triglycerides and body mass index as input variables yielded a 10-fold cross-validated accuracy of 89.8% when discriminating MetS from controls. The association between MetS and increased MDA was independent from the effects of overweight-obesity. glucose, insulin, triglycerides and HDL-C.Conclusion: In adolescents, increased MDA formation is a key component of MetS, indicating that increased production of reactive oxygen species with consequent lipid peroxidation and aldehyde formation participate in the development of MetS.

In the modern world, the problem of antibiotic therapy is acute. Despite the diversity of existing antibiotic drugs, their efficacy decreases as new, resistant forms of pathogenic microorganisms emerge. It is extremely difficult to control such processes and even more difficult to treat severe bacterial infections. In such situations, an individual approach to each patient is required and physicians need parameters to estimate the efficacy of antibiotic therapy. This review discusses the significance of monitoring the content of antibiotics in the blood for this purpose, in combination with the content of inflammatory markers, such as C-reactive protein and procalcitonin. The basic principles of antibiotic therapy, and factors in the resistance of microorganisms to antibiotics, are examined. Approaches to assess the efficacy of antibiotic therapy, as well as methods to detect antibiotics and inflammatory markers in the blood of patients, and comparative assessment of their capabilities and limitations, are described.

Surgeons are increasingly faced with a challenging, ageing and frail patient population. A significant absence of biomarkers to stratify outcomes of patients undergoing emergency laparotomy exists. Inflammageing describes a state of chronic inflammation associated with ageing and frailty and may predict worse outcomes. This retrospective observational study evaluated pre-morbid inflammatory markers in the prognostication of elderly patients undergoing emergency laparotomy. Patients aged ≥65 years undergoing surgery between 01/04/2017 – 01/04/2022 were identified. Pre-admission and acute C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), total white cell count (WCC), neutrophil count (NC) and lymphocyte count (LC) data points were captured. Pre-operative risk stratification scores and postoperative outcomes were recorded using the National Emergency Laparotomy Audit (NELA) database. A cohort of 196 patients was included: 57.7% were female, median age of 74.5 years. High-risk (NELA risk of mortality ≥5%) and frail (clinical frailty scale ≥4) patients experienced a significantly longer hospital and critical care stay (p<0.05). Pre-admission ESR ≥16 and LC ≥4.1 were significantly associated with a longer critical care stay (p<0.05), however, no statistical significance was observed with CRP, WCC and NC in predicting adverse outcomes. We found an elevated pre-morbid ESR and LC identifies a potential inflammageing cohort that demonstrate worse outcomes following emergency laparotomy. The prognostication of elderly surgical patients remains a challenge and represents an area of research deserving of future attention.

The early detection of cutaneous melanoma, a potentially lethal cancer with rising incidence, is key to increase survival and therapeutic adjustment. Especially in stages II-IV biomarkers are urgently needed for adjuvant therapy purposes after resection and for treatment of metastatic patients. We here investigated if fatty acid (FA) and protein composition of small extracellular vesicles (sEV) deriving from plasma of 0-I, II, and III-IV stage melanoma patients (n=38) could reflect disease stage and thus function as biomarker. The subpopulation of sEV expressing CD81 (CD81sEV) was isolated by an ad hoc immune affinity technique from microvesicle-depleted plasma. Biological macromolecules were investigated by gas chromatography and mass spectrometry in CD81sEV. A higher content of FA and a decrease in Saturation Index (C18:0/C18:1), already detectable in early stages, distinguished patients’ from healthy donor CD81sEV. Proteomics (identifier PXD024434) detected an exclusive and significant increase of CD14, PON1, PON3 and APOA5 in stage II and a significant decrease of Rap1b in stage III-IV CD81sEV. The FA and proteomic stage dependent CD81sEV signature strengthens the potential of circulating sEV studies in providing discriminatory information for early diagnosis, prediction of metastatic behavior and follow up of melanoma patients.

Glial fibrillary acidic protein (GFAP) is the major intermediate filament III protein of astroglia cells which is upregulated in traumatic brain injury (TBI). Here we reported that GFAP is truncated at both the C- and N-terminals by cytosolic protease calpain to GFAP breakdown products (GBDP) of 46-40K then 38K following pro-necrotic (A23187) and pro-apoptotic (staurosporine) challenges to primary cultured astroglia or neuron-glia mixed cells. In addition, with another pro-apoptotic challenge (EDTA) where caspases are activated but not calpain, GFAP was fragmented internally, generating a C-terminal GBDP of 20 kDa. Following controlled cortical impact in mice, GBDP of 46-40K and 38K were formed from day 3 to 28 post-injury. Purified GFAP protein treated with calpain-1 and -2 generates (i) major N-terminal cleavage sites between A-56 and A-75, and (ii) major C-terminal cleavage sites between T-383 and Q-388, producing a limit fragment of 38K. Caspase-6 treated GFAP was cleaved at D-78, R-79, D-266 and A-267, where GFAP was relatively resistant to caspase-3. We also derived a GBDP-38K N-terminal-specific antibody which only labels injured astroglia cell body in both cultured astroglia and mouse cortex and hippocampus after TBI. As a clinical translation, we observed that CSF samples collected from severe human TBI have elevated levels of GBDP-38K as well as two C-terminally released GFAP peptides (DGEVIKES and DGEVIKE). Thus, in addition to intact GFAP, both the GBDP-38K as well as unique GFAP released C-terminal proteolytic peptides species might have the potential in tracking brain injury progression.

The SARS-CoV-2 infection is a cause of hypoxemic acute respiratory failure, leading to frequent intensive care unit (ICU) admission. Due to invasive organ support and immunosuppressive therapies, these patients are prone to nosocomial infections. Our aim was to assess the value of daily measurements of C-reactive protein (CRP) and Procalcitonin (PCT) in the early identification of ICU-acquired infections in COVID-19 patients Methods: We undertook a prospective observational cohort study (12 months). All adult me-chanically-ventilated patients admitted for ≥ 72 hours to the ICU with COVID-19 pneumonia were divided into an infected group (n=35) and a non-infected group (n=83). Day 0 was considered as the day of the diagnosis of infection (infected group) and day 10 of ICU stay (non-infected group). The kinetics of CRP and PCT were assessed from day -10 to day 10 and evaluated using a general linear model, univariate, repeated-measures analysis. Results: 118 patients (mean age 63 years, 74% males) were eligible for the analysis. The groups did not differ in patients' age, gender, CRP, and PCT serum levels at ICU admission. However, the infected group encompassed patients with a higher severity (SOFA score at ICU admission, p=0.009) and a higher 28-day mortality (p<0.001). Before D0, CRP kinetics showed a significant increase in infected patients, whereas in noninfected it remained almost unchanged (p<0.001), while PCT kinetics did not appear to retain diagnostic value to predict superinfection in COVID-19 patients (p=0.593). Conclusion: COVID-19 patients who develop ICU-acquired infections exhibited different biomarker kinetics before the diagnosis of those infections. Daily CRP monitoring and the recognition of the CRP kinetics could be useful in the prediction of ICU-acquired infections.

Transfusion dependent thalassemia (TDT) patients are treated with continued blood transfusions and show a higher prevalence of depression. TDT with consequent iron overload and inflammation is associated with increased severity of depressive symptoms in TDT children.Aim of the study: To construct a pathway-phenotype which combines iron overload and neuro-immune biomarkers with depressive symptom subdomains in TDT children.Methods: We measured iron status parameters (iron, ferritin, transferrin saturation percentage) and inflammatory (interleukin-1β and tumour necrosis factor-α) biomarkers in TDT (n=111) and healthy (n=53) children and analyzed the results using machine learning.Results: Cluster analysis separated TDT children with depression from those without depression and revealed two depressive subgroups one with low self-esteem and another with increased social-irritability scores. Exploratory factor analysis validated four depressive symptom dimensions as reliable constructs, namely key depressive, physiosomatic, lowered self-esteem and social-irritability dimensions. Partial Least Squares showed that 73.0% of the variance in a latent vector extracted from those four clinical subdomains, immune-inflammatory and iron overload biomarkers was explained by exposure variables including the number of blood transfusions and hospitalizations and use of deferoxamine. The exposure data, iron and immune biomarkers, and symptom subdomains are reflective manifestations of a single latent trait, which shows internal consistency reliability and predictive relevance.Conclusions: The nomological network combining exposure, pathways and behavioral phenome manifestations provides an index of overall severity and disease risk and, therefore, constitutes a new drug target, indicating that iron overload and immune activation should be targeted to treat depression due to TDT.

Background: Over the past few years there has been immense evolution in various areas particularly in the areas of digital technologies wherein the pace of change is very high. Industrial areas such as operations and supply chain management together with advanced technologies such as machine learning, big data analytics, artificial intelligence, as well as the Internet of Things, create completely different forms of operational models for various industries. In the area of healthcare too, these emerging computational sophistication is introduced to revolutionise the approaches to prevent, diagnose and treat diverse diseases and illnesses. Objective: The objective of this study is to provide an extensive review of the contemporary approaches utilizing data to cope with significant mental disorders. From over 60 relevant scholarly articles published between 2011 and 2023, it discusses how tools such as predictive modelling, social media analysis, data from smartphones, and chatbots help with issues such as early detection, telemonitoring, provision of psychological support, and individualised prevention. Method: An initial literature review to analyse over 60 research articles, which include empirical studies that were conducted between 2011 and 2023. The research assessed implemented novel digital approaches to mental health interventions including big data analytics for predicting condition status, machine learning for examining social media content, behaviour monitoring through smartphone sensors, and using conversational agents or chatbots. The following is an overview of general conclusions from experimental and descriptive secondary research studies published in professional outlets concerning possible advantages and disadvantages of data science applied to important concerns in mental health. Results: Research reveals that integrating subtle e-health tools in tandem with typical treatment approaches holds the potential to expand mental health services to more or less integrate them into clients’ day-to-day lives, and practically individualize effective treatments accordingly. Technological solutions for instance allow remote risk assessment, symptom monitoring and determination of treatment compliance. New lines of virtualized paradigm solve social challenges that interfere with the conventional provision and consumption of care. However, questions of privacy and the long-term effects as well as clinical adoption are yet to be solved in a analytically distinct manner.

Introduction: Advanced glycation end-products (AGEs) may play a relevant role as inducers in the chronic inflammatory pathway present in immune-mediated diseases, such as systemic lupus erythematosus (SLE). AGEs concentrations have been associated, with discrepant results to date, with some parameters such as disease activity or accrual damage, suggesting their potential usefulness as biomarkers of the disease. Objectives: To confirm differences in AGEs levels measured by cutaneous autofluorescence between SLE patients and healthy controls (HC) and study their correlation with various disease parameters. Methods: Cross-sectional study, where AGEs levels were measured by skin autofluorescence, and SLE patients’ data were compared with those of sex- and age-matched HC in a 1:3 proportion through a multiple linear regression model. Correlations of AGEs levels with demographic and clinical data were analyzed through ANOVA tests. Both analyses were adjusted for confounders. Results: AGEs levels in SLE patients were significantly higher than in HC (p<0.001). We found statistically significant positive correlation with SLE disease activity index (SLEDAI) and damage index (SDI), physician and patient global assessment, C-reactive protein, leukocyturia, complement C4, IL6 and oral ulcers. We also found a negative statistically significant correlation with current positivity of anti-nuclear and anti-Ro60 antibodies. Conclusions: AGEs seem to have a role in LES pathophysiology, becoming a new management and prognosis biomarker in this disease. The association with specific antibodies and disease manifestations may indicate a specific clinical phenotype related to higher AGEs levels.

This narrative review aims to clarify the role of tertiary lymphoid structures in breast cancer. We examine their development, composition, prognostic value and current ways of recognising them. A comprehensive literature review was performed using PubMed/Medline, Scopus and EMBASE databases. A significant area of interest in breast cancer research involves targeting immune checkpoint molecules, particularly in the triple-negative subtype, where treatment options remain limited. However, existing biomarkers have limitations in accurately predicting treatment response.  In this context, tertiary lymphoid structures (TLS) emerge as a prognostic biomarker and also as a promising predictive marker for response. TLS are ectopic lymphoid formations or neo-organogenesis that can develop after prolonged exposure to inflammatory signals mediated by chemokines and cytokines. Their presence is inversely correlated with estrogen receptor (ER) and/or progesterone receptor (PR) expression, but positively associated with a higher pathologic complete response rate and improved overall  survival. In certain scenarios, TLS-positive tumors were associated with improved outcomes regardless of the presence of PDL-1 (programmed cell death ligand 1) expression or and TILs (tumor-infiltrating lymphocytes).

Abatacept (CTLA4-Ig) – a monoclonal antibody which restricts T cell activation – is an effective treatment for rheumatoid arthritis (RA). Herein, we aimed to investigate for biomarkers of response to abatacept. We performed a detailed immunological profiling of CTLA4-treated RA patients’ peripheral blood (PB) cells and sera using flow cytometry and proteomics analysis, respectively. At 6 months of treatment, 34.5% of patients attained clinical response. Notably, baseline levels of Th1 and myeloid cell populations were significantly elevated in PB of responders compared to non-responders (P-value<0.05). Additionally, proteomics analysis revealed 10 amongst 303 molecules which were associated with clinical responses. Should the present data be confirmed in a larger cohort could be of clinical value.

Early diagnosis and appropriate treatments are crucial to reducing mortality risk in septic patients. Low SOFA scores and current biomarkers may not discern adequately patients that could develop severe organ dysfunction or have an elevated mortality risk. The aim of this prospective observational study is to evaluate the predictive value of the biomarkers midregional proadrenomedullin (MR-proADM), procalcitonin (PCT), C-Reactive Protein (CRP), and lactate for 28-day mortality in patients with sepsis and a SOFA score ≤ 6. 284 patients were included, with a 28-day all-cause mortality of 8.45 % (N=24). Non-survivors were older (p=0.003), required mechanical ventilation (p=0.04) and were ventilated for longer (p=0.02), had a higher APACHE II (p=0.015) and SOFA (p=0.027) scores. Lactate showed the highest predictive ability for all-cause 28-day mortality with an area under the receiver-operating characteristic curve (AUROC) of 0.67 (0.55–0.79). The AUROC for all-cause 28-day mortality in patients with community-acquired infection was 0.69 (0.57–0.84) for SOFA, and 0.70 (0.58–0.82) for MR-proADM. A 2.1 nmol/L cut-off point for this biomarker in this subgroup of patients discerned with 100% sensibility survivors from non-survivors at 28 days. In patients with community acquired sepsis and initial SOFA score ≤ 6, MR-proADM could help identify patients at risk of 28-day mortality.

Prostate cancer (Pca) is a highly heterogeneous disease and the second more common tumor in males. Molecular and genetic profiles have been used to identify subtypes and guide therapeutic intervention. However, roughly 26% of primary Pca are driven by unknown molecular lesions. We use Principal Component Analysis (PCA) and custom RNAseq-data normalization to identify a gene expression signature which segregates primary PRAD from normal tissues. This Core-Expression Signature (PRAD-CES) includes 33 genes and accounts for 39% of data complexity along the PC1-cancer axis. The PRAD-CES is populated by protein-coding (AMACR, TP63, HPN) and RNA-genes (PCA3, ARLN1) sparsely found in previous studies, validated/predicted biomarkers (HOXC6, TDRD1, DLX1), and/or cancer drivers (PCA3, ARLN1, PCAT-14). Of note, the PRAD-CES also comprises six over-expressed LncRNAs without previous Pca association, four of them potentially modulating driver’s genes TMPRSS2, PRUNE2 and AMACR. Overall, our PCA capture 57% of data complexity within PC1-3. GO enrichment and correlation analysis involving major clinical features (i.e., Gleason Score, AR Score, TMPRSS2-ERG fusion and Tumor Cellularity) suggest that PC2 and PC3 gene signatures might describe more aggressive and inflammation-prone transitional forms of PRAD. Of note, surfaced genes may entail novel prognostic biomarkers and molecular alterations to intervene. Particularly, our work uncovered RNA genes with appealing implications on Pca biology and progression.