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A nonparametric method proposed by DeLong et al in 1988 for comparing areas under correlated receiver operating characteristic curves is used widely in practice. However, the DeLong method as implemented in popular software quietly deletes individuals with any missing values, yielding potentially invalid and/or inefficient results. We simplify the DeLong algorithm using ranks and extend it to accommodate missing data by using a mixed model approach for multivariate data. Simulation results demonstrate the validity and efficiency of our procedure for data missing at random. We illustrate our proposed procedure in SAS, Stata, and R using the original DeLong data. [ABSTRACT FROM AUTHOR]

DNA methylation biomarkers have emerged as promising tools for cancer detection. Common methylation patterns across tumor types allow multi‐cancer detection. Droplet digital PCR (ddPCR) has gained considerable attention for methylation detection. However, multi‐cancer detection using multiple targets in ddPCR has never been performed before. Therefore, we developed a multiplex ddPCR assay for multi‐cancer detection. Based on previous data analyses using The Cancer Genome Atlas (TCGA), we selected differentially methylated targets for eight frequent tumor types (lung, breast, colorectal, prostate, pancreatic, head and neck, liver, and esophageal cancer). Three targets were validated using ddPCR in 103 tumor and 109 normal adjacent fresh frozen samples. Two distinct ddPCR assays were successfully developed. Output data from both assays is combined to obtain a read‐out from the three targets together. Our overall ddPCR assay has a cross‐validated area under the curve (cvAUC) of 0.948. Performance between distinct cancer types varies, with sensitivities ranging from 53.8% to 100% and specificities ranging from 80% to 100%. Compared to previously published single‐target parameters, we show that combining targets can drastically increase sensitivity and specificity, while lowering DNA input. In conclusion, we are the first to report a multi‐cancer methylation ddPCR assay, which allows for highly accurate tumor predictions. [ABSTRACT FROM AUTHOR]

Aim Materials and Methods Results Conclusions Diabetic cognitive impairment (DCI), considered one of the most severe and commonly overlooked complications of diabetes, has shown inconsistent findings regarding the metabolic profiles in DCI patients. This systematic review and meta‐analysis aimed to identify dysregulated metabolites as potential biomarkers for early DCI, providing valuable insights into the underlying pathophysiological mechanisms.A systematic search of four databases, namely PubMed, Embase, Web of Science and Cochrane, was conducted up to March 2024. Subsequently, a qualitative review of clinical studies was performed followed by a meta‐analysis of metabolite markers. Finally, the sources of heterogeneity were explored through subgroup and sensitivity analyses.A total of 774 unique publications involving 4357 participants and the identification of multiple metabolites were retrieved. Of these, 13 clinical studies reported metabolite differences between the DCI and control groups. Meta‐analysis was conducted for six brain metabolites and two metabolite ratios. The results revealed a significant increase in myo‐inositol (MI) concentration and decreases in glutamate (Glu), Glx (glutamate and glutamine) and N‐acetylaspartate/creatine (NAA/Cr) ratios in DCI, which have been identified as the most sensitive metabolic biomarkers for evaluating DCI progression. Notably, brain metabolic changes associated with cognitive impairment are more pronounced in type 2 diabetes mellitus than in type 1 diabetes mellitus, and the hippocampus emerged as the most sensitive brain region regarding metabolic changes associated with DCI.Our results suggest that MI, Glu, and Glx concentrations and NAA/Cr ratios within the hippocampus may serve as metabolic biomarkers for patients with early‐stage DCI. [ABSTRACT FROM AUTHOR]

Aim Materials and Methods Results Conclusions Non‐invasive diagnostics for metabolic dysfunction–associated fatty liver disease (MAFLD) remain challenging. We aimed to identify novel key genes as non‐invasive biomarkers for MAFLD, elucidate causal relationships between biomarkers and MAFLD and determine the role of immune cells as potential mediators.Utilizing published transcriptome data of patients with biopsy‐proven MAFLD, we applied linear models for microarray data, least absolute shrinkage and selector operation (LASSO) regressions and receiver operating characteristic (ROC) curve analyses to identify and validate biomarkers for MAFLD. Using the expression quantitative trait loci database and a cohort of 778 614 Europeans, we used Mendelian randomization to analyse the causal relationships between key biomarkers and MAFLD. Additionally, mediation analysis was performed to examine the involvement of 731 immunophenotypes in these relationships.We identified 31 differentially expressed genes, and LASSO regression showed three hub genes, IGFBP2, PEG10, and P4HA1, with area under the receiver operating characteristic (AUROC) curve of 0.807, 0.772 and 0.791, respectively, for identifying MAFLD. The model of these three genes had an AUROC of 0.959 and 0.800 in the development and validation data sets, respectively. This model was also validated using serum‐based enzyme‐linked immunosorbent assay data from MAFLD patients and control subjects (AUROC: 0.819, 95% confidence interval: 0.736–0.902). PEG10 was associated with an increased MAFLD risk (odds ratio = 1.106, p = 0.032) via inverse variance–weighted analysis, and about 30% of this risk was mediated by the percentage of CD11c + CD62L– monocytes.The MAFLD panels have good diagnostic accuracy, and the causal link between PEG10 and MAFLD was mediated by the percentage of CD11c + CD62L– monocytes. [ABSTRACT FROM AUTHOR]

Objectives Research Design and Methods Results Conclusion To present the Real‐World Progression In Diabetes (RAPIDS) 2.0 Risk Engine, the only simulation model to study the long‐term trajectories of outcomes arising from dynamic sequences of glucose‐lowering treatments in type 2 diabetes (T2DM).The RAPIDS model's risk equations were re‐estimated using a Least Absolute Shrinkage and Selection Operator (LASSO)‐based regularization of features that spanned baseline data from the last two quarters of current time and interactions with age. These equations were supplemented with estimates for the impact of dipeptidyl peptidase‐4 inhibitors, glucagon‐like peptide‐1 receptor agonists, and sodium‐glucose cotransporter‐2 inhibitor classes of drugs as monotherapies and their combinations with metformin based on newer trial data and comprehensive meta‐analyses. The probabilistic RAPIDS 2.0 model was calibrated (N = 25 000) and validated (N = 263 816) using electronic medical records (EMR) data between 2008 and 2021 from a national network of US healthcare organizations.The EMR‐based cohort had a mean age of 61 years at baseline, with 50% women, 70% non‐Hispanic White individuals and 20% non‐Hispanic Black individuals, and was followed for 17.5 quarters (range: 3–50). The final RAPIDS 2.0 risk engine accurately predicted the long‐term trajectories of all nine biomarkers and nine outcomes in the hold‐out validation sample. Similar accuracies in predictions were observed in each of the 14 subgroups studied.The RAPIDS 2.0 model demonstrated valid long‐term predictions of outcomes in individuals with T2DM in the United States as a function of dynamic sequences of treatment use patterns. This highlights its potential to project long‐term comparative effectiveness between alternative sequences of glucose‐lowering treatment uses in the United States. [ABSTRACT FROM AUTHOR]

Summary The autonomic nervous system regulates cardiovascular activity during sleep, likely impacting cardiovascular health. Aging, a primary cardiovascular risk factor, is associated with cardiac autonomic disbalance and diminished sleep slow waves. Therefore, slow waves may be linked to aging, autonomic activity and cardiovascular health. However, it is unclear how sleep and slow waves are linked to cardiac autonomic profiles across multiple nights in older adults. We conducted a randomized, crossover trial involving healthy adults aged 62–78 years. Across 2 weeks, we applied auditory stimulation to enhance slow waves and compared it with a SHAM period. We measured sleep parameters using polysomnography and derived heart rate, heart rate variability approximating parasympathetic activity, and blood pulse wave approximating sympathetic activity from a wearable. Here, we report the results of 14 out of 33 enrolled participants, and show that heart rate, heart rate variability and blood pulse wave within sleep stages differ between the first and second half of sleep. Furthermore, baseline slow‐wave activity was related to cardiac autonomic activity profiles during sleep. Moreover, we found auditory stimulation to reduce heart rate variability, while heart rate and blood pulse wave remained unchanged. Lastly, within subjects, higher heart rate coincided with increased slow‐wave activity, indicating enhanced autonomic activation when slow waves are pronounced. Our study shows the potential of cardiac autonomic markers to offer insights into participants' baseline slow‐wave activity when recorded over multiple nights. Furthermore, we highlight that averaging cardiac autonomic parameters across a night may potentially mask dynamic effects of auditory stimulation, potentially playing a role in maintaining a healthy cardiovascular system. [ABSTRACT FROM AUTHOR]

Background: Oral squamous cell carcinoma (OSCC) is a prevalent malignancy affecting the head and neck region. The prognosis for OSCC patients remains unfavorable due to the absence of precise and efficient early diagnostic techniques. Metabolomics offers a promising approach for identifying distinct metabolites, thereby facilitating early detection and treatment of OSCC. Objective: This review aims to provide a comprehensive overview of recent advancements in metabolic marker identification for early OSCC diagnosis. Additionally, the clinical significance and potential applications of metabolic markers for the management of OSCC are discussed. Results: This review summarizes metabolic changes during the occurrence and development of oral squamous cell carcinoma and reviews prospects for the clinical application of characteristic, differential metabolites in saliva, serum, and OSCC tissue. In this review, the application of metabolomic technology in OSCC research was summarized, and future research directions were proposed. Conclusion: Metabolomics, detection technology that is the closest to phenotype, can efficiently identify differential metabolites. Combined with statistical data analyses and artificial intelligence technology, it can rapidly screen characteristic biomarkers for early diagnosis, treatment, and prognosis evaluations. [ABSTRACT FROM AUTHOR]

Objective: The present study was performed to identify key biomarkers associated with immune cell infiltration in peri‐implantitis through bioinformatic analyses. Methods: Six peri‐implantitis soft tissue samples and six healthy gingiva samples were obtained from GSE106090, and were used to identify immune‐associated differentially expressed genes (DEGs) in peri‐implantitis. The candidate biomarkers associated with immune cell infiltration were examined by immunohistochemical staining. Results: We identified 2089 upregulated and 2173 downregulated genes. Upregulated DEGs were significantly associated with immune response. Ten key candidate biomarkers were identified in the PPI network, including IL1B, TLR2, TLR4, CCL4, CXCL8, IL10, IL6, CD4, CCL3, and PTPRC. The expression level of the 10 genes increased in peri‐implantitis soft tissue samples compared with healthy gingiva samples. The proportion of CD4+ T cells, iTreg, and Tfh in infiltration immune cells increased in peri‐implantitis soft tissue samples and were positively correlated with the expression level of candidate biomarkers TLR4, CCL3, CXCL8, and IL1B. Immunohistochemistry showed that there were more lymphocytes in peri‐implantitis soft tissue samples, with an increased expression level of TLR4, CCL3, CXCL8, and IL1B. Conclusion: Identification of four novel diagnostic biomarkers was helpful for revealing the molecular mechanisms and could serve as a risk predictor for the immune microenvironment in peri‐implantitis. [ABSTRACT FROM AUTHOR]

Background: Emerging research has identified the N6‐methyladenosine (m6A) modification and its regulatory enzymes, including methyltransferase 5 (METTL5), as critical players in cancer biology. However, the role of METTL5 in oral squamous cell carcinoma (OSCC) remains poorly understood. Materials and Methods: We conducted a comprehensive study to investigate the expression and implications of METTL5 in OSCC. We recruited 76 OSCC patients to analyze METTL5 mRNA and protein expression using RT‐qPCR and western blot. Additionally, we analyzed METTL5 expression and its correlation with clinical features, patient prognosis, immune cell infiltration, and biological pathways using the TCGA‐HNSCC dataset, which primarily consists of OSCC samples. Results: Our findings revealed significant overexpression of METTL5 in OSCC tissues compared to normal tissues. The high expression of METTL5 is associated with advanced cancer stages, higher tumor grades, nodal metastasis, and poorer patient outcomes, indicating its involvement in cancer progression. In silico functional analysis revealed that METTL5 plays a role in multiple biological pathways, highlighting its importance in cancer biology. Moreover, METTL5 has complex relationships with immune regulatory genes, suggesting its potential role in shaping the tumor immune microenvironment. Conclusion: METTL5 is a promising candidate for the prognosis and therapeutic intervention of OSCC. Its overexpression in cancer tissues, association with clinical features, and intricate links to immune regulatory networks underscore its significance in this malignancy. This study contributes to a deeper understanding of the complex factors influencing OSCC, and provides a foundation for future research and potential clinical applications. [ABSTRACT FROM AUTHOR]

Background and Aims: The goal of this study was to define basic constituents of the adult peripheral nervous system (PNS) using intact human nerve tissues. Methods: We combined fluorescent and chromogenic immunostaining methods, myelin‐selective fluorophores, and routine histological stains to identify common cellular and noncellular elements in aldehyde‐fixed nerve tissue sections. We employed Schwann cell (SC)‐specific markers, such as S100β, NGFR, Sox10, and myelin protein zero (MPZ), together with axonal, extracellular matrix (collagen IV, laminin, fibronectin), and fibroblast markers to assess the SC's relationship to myelin sheaths, axons, other cell types, and the acellular environment. Results: Whereas S100β and Sox10 revealed mature SCs in the absence of other stains, discrimination between myelinating and non‐myelinating (Remak) SCs required immunodetection of NGFR along with axonal and/or myelin markers. Surprisingly, our analysis of NGFR+ profiles uncovered the existence of at least 3 different novel populations of NGFR+/S100β− cells, herein referred to as nonglial cells, residing in the stroma and perivascular areas of all nerve compartments. An important proportion of the nerve's cellular content, including circa 30% of endoneurial cells, consisted of heterogenous S100β negative cells that were not associated with axons. Useful markers to identify the localization and diversity of nonglial cell types across different compartments were Thy1, CD34, SMA, and Glut1, a perineurial cell marker. Interpretation: Our optimized methods revealed additional detailed information to update our understanding of the complexity and spatial orientation of PNS‐resident cell types in humans. [ABSTRACT FROM AUTHOR]

Objective: Our objective was to evaluate the association of serum biomarkers with baseline psoriatic arthritis (PsA) disease activity, pharmacodynamic effects of deucravacitinib on biomarker levels, and the relationship between biomarkers and clinical responses to deucravacitinib. Methods: The phase 2 trial (ClinicalTrials.gov identifier: NCT03881059) randomly assigned 203 patients with PsA 1:1:1 to placebo, deucravacitinib at 6 mg once daily (QD), or deucravacitinib at 12 mg QD. Serum biomarkers associated with the interleukin 23 (IL‐23) pathway (IL‐17A, β‐defensin [BD‐2], and IL‐19), type I interferon pathway, inflammation, and collagen matrix turnover were measured by immunoassay. Clinical responses (≥75% improvement from baseline in the Psoriasis Area and Severity Index [PASI75] and ≥20% improvement from baseline in American College of Rheumatology criteria [ACR20] responses) were measured at week 16. Hematologic variables were also assessed. Results: IL‐17A, BD‐2, and IL‐19 had a modest association with PASI scores (r = 0.4, r = 0.56, and r = 0.5, respectively) at baseline. In deucravacitinib groups, IL‐17A, BD‐2, IL‐19, C‐X‐C motif ligand 9 (CXCL9), CXCL10, C‐reactive protein, matrix metalloproteinase 3, and collagen type 4 degradation marker levels were significantly reduced at week 16 versus baseline (P < 0.01); higher levels of IL‐23 pathway–associated biomarkers predicted higher PASI75 and ACR20 response rates in deucravacitinib‐treated patients. Significantly higher PASI75 response rates were seen in patients with high baseline IL‐17A (odds ratio 15.76) and BD‐2 levels (odds ratio 15.41) versus low baseline IL‐17A and BD‐2 levels. Changes in hematologic variables that are characteristic of JAK inhibition were not observed with deucravacitinib. Conclusion: Deucravacitinib significantly impacted biomarkers associated with Tyk2 signaling pathways of key inflammatory cytokines, including IL‐23 and type I interferon, and those related to collagen matrix turnover. These biomarkers may predict treatment responses to deucravacitinib. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is a prototypic autoimmune disease that primarily affects young women and causes a wide range of inflammatory manifestations. The hallmark of SLE is the production of antibodies to components of the cell nucleus (antinuclear antibodies [ANAs]). These antibodies can bind to DNA, RNA, and protein complexes with nucleic acids. Among ANAs, antibodies to DNA (anti‐DNA) are markers for classification and disease activity, waxing and waning disease activity in many patients. In the blood, anti‐DNA antibodies can bind to DNA to form immune complexes with two distinct roles in pathogenesis: (1) renal deposition to provoke nephritis and (2) stimulation of cytokine production following uptake into innate immune cells and interaction with internal nucleic acid sensors. These sensors are part of an internal host defense system in the cell cytoplasm that can respond to DNA from infecting organisms; during cell stress, DNA from nuclear and mitochondrial sources can also trigger these sensors. The formation of immune complexes requires a source of extracellular DNA in an immunologically accessible form. As shown in in vivo and in vitro systems, extracellular DNA can emerge from dead and dying cells in both a free and a particulate form. Neutrophils undergoing the process of NETosis can release DNA in mesh‐like structures called neutrophil extracellular traps. In SLE, therefore, the combination of ANAs and immunologically active DNA can create new structures that can promote inflammation throughout the body as well as drive organ inflammation and damage. [ABSTRACT FROM AUTHOR]

Aim: The success of vital pulp treatment (VPT) procedures is dependent on an accurate diagnosis of the pulpal inflammatory condition. Compared with current subjective pulpal diagnostic tests, inflammatory molecular biomarkers involved in the pathogenesis of pulpitis represent potential objective indicators of the degree of pulpal inflammation. Therefore, the aim of this study was to quantify level of inflammatory biomarkers – Interleukin 8 (IL‐8) and TNF‐α in patients diagnosed with reversible pulpitis (RP), irreversible pulpitis (IR) and normal pulp (NP) and investigate their diagnostic accuracy in differentiating between healthy and inflamed conditions. Methodology: This prospective, cross‐sectional study enrolled 72 patients aged 14–53 years with extremely deep carious lesions after establishing a clinical diagnosis of RP (n = 42), symptomatic IR (n = 22) and NP (n = 8). 50 μL of pulpal blood sample was collected from all the patients using a micropipette after pulpal exposure. The level of IL‐8 and TNF‐α was assessed in pg/mL using enzyme‐linked immunosorbent assays. Mann–Whitney U test was applied to establish the association between IL‐8/TNF‐α level and degree of pulp inflammation. Receiver operating curve (ROC) analysis was carried out to calculate area under the curve (AUC) for RP versus IR. Cut‐off values were established using Youden's index. Results: IL‐8 and TNF‐α levels differed significantly between RP and IR groups (p ≤.001). The median value of IL‐8 in RP and IP groups was 259.8 pg/mL [187.5–310.0] and 1357.8 pg/mL [1036.7–2177.6] respectively. The AUC‐ROC curve for RP versus IR was 0.997 with 95.5% sensitivity and 99.76% specificity. The median value of TNF‐α in RP and IR groups was 75.4 pg/mL [62.7–95.8] and 157.6 pg/mL [94.1–347.3]. The AUC‐ROC curve for TNF‐α was 0.812 with a sensitivity and specificity of 59.1% and 92.1%, respectively. IL‐8 and TNF‐α levels were below detection levels for all NP samples. Conclusion: This study showed that pulpal blood could provide an excellent medium for establishing pulpal diagnosis under extremely deep carious lesions. The selected cytokines, IL‐8 and TNF‐α, demonstrated excellent discriminatory performance for reversible and irreversible pulpitis. Future studies should correlate the IL‐8/TNF‐α levels with VPT treatment outcomes. [ABSTRACT FROM AUTHOR]

Aims: Human epidermal growth factor receptor 2 (HER2) expression is an important biomarker in breast cancer (BC). Most BC cases categorised as HER2‐negative (HER2−) express low levels of HER2 [immunohistochemistry (IHC) 1+ or IHC 2+/in‐situ hybridisation not amplified (ISH−)] and represent a clinically relevant therapeutic category that is amenable to targeted therapy using a recently approved HER2‐directed antibody–drug conjugate. A group of practising pathologists, with expertise in breast pathology and BC biomarker testing, outline best practices and guidance for achieving consensus in HER2 IHC scoring for BC. Methods and results: The authors describe current knowledge and challenges of IHC testing and scoring of HER2‐low expressing BC and provide best practices and guidance for accurate identification of BCs expressing low levels of HER2. These expert pathologists propose an algorithm for assessing HER2 expression with validated IHC assays and incorporate the 2023 American Society of Clinical Oncology and College of American Pathologist guideline update. The authors also provide guidance on when to seek consensus for HER2 IHC scoring, how to incorporate HER2‐low into IHC reporting and present examples of HER2 IHC staining, including challenging cases. Conclusions: Awareness of BC cases that are negative for HER protein overexpression/gene amplification and the related clinical relevance for targeted therapy highlight the importance of accurate HER2 IHC scoring for optimal treatment selection. [ABSTRACT FROM AUTHOR]

Aim: To investigate type III collagen (COL III) turnover in participants from the CANVAS Program biomarker substudy. Methods: Biomarkers of COL III formation (PRO‐C3) and COL III degradation fragments (C3M and CTX‐III) were assessed in baseline and year 3 plasma from patients enrolled in CANVAS, investigating the effect of canagliflozin in participants with type 2 diabetes. The clinical outcomes investigated in this study were hospitalization for heart failure, cardiovascular death and all‐cause mortality. Results: Higher levels of PRO‐C3 and C3M at baseline were associated with an increased incidence of all investigated outcomes, whereas levels of CTX‐III at baseline were not associated with any of the investigated outcomes. Levels of PRO‐C3 decreased and levels of CTX‐III increased following canagliflozin treatment. An increase from baseline to year 3 in PRO‐C3 in the placebo arm was associated with an increased incidence of cardiovascular outcomes, and in all participants was associated with an increased risk of all‐cause mortality. Conclusions: The changes in PRO‐C3 and CTX‐III reflect a shift in the dynamics of COL3 turnover following treatment with canagliflozin. These biomarkers are promising pharmacodynamic tools that can be used to monitor the impact of canagliflozin treatment and possibly other sodium‐glucose co‐transporter‐2 inhibitors on tissue remodelling in future interventional trials. [ABSTRACT FROM AUTHOR]

Aim: To investigate the associations of metabolic score for insulin resistance (METS‐IR) with all‐cause and cardiovascular disease (CVD)‐specific mortality and the potential mediating role of biological ageing. Methods: A cohort of 19 204 participants from the National Health and Nutrition Examination Survey (NHANES) 1999–2018 was recruited for this study. Cox regression models, restricted cubic splines, and Kaplan–Meier survival curves were used to determine the relationships of METS‐IR with all‐cause and CVD‐specific mortality. Mediation analyses were performed to explore the possible intermediary role of biological ageing markers, including phenotypic age (PhenoAge) and biological age (BioAge). Results: During a median follow‐up of 9.17 years, we observed 2818 deaths, of which 875 were CVD‐specific. Multivariable Cox regression showed that the highest METS‐IR level (Q4) was associated with increased all‐cause (hazard ratio [HR] 1.38, 95% confidence interval [CI] 1.14–1.67) and CVD mortality (HR 1.52, 95% CI 1.10–2.12) compared with the Q1 level. Restricted cubic splines showed a nonlinear relationship between METS‐IR and all‐cause mortality. Only METS‐IR above the threshold (41.02 μg/L) was positively correlated with all‐cause death. METS‐IR had a linear positive relationship with CVD mortality. In mediation analyses, we found that PhenoAge mediated 51.32% (p < 0.001) and 41.77% (p < 0.001) of the association between METS‐IR and all‐cause and CVD‐specific mortality, respectively. For BioAge, the mediating proportions of PhenoAge were 21.33% (p < 0.001) and 15.88% (p < 0.001), respectively. Conclusions: This study highlights the detrimental effects of insulin resistance, as measured by METS‐IR, on all‐cause and CVD mortality. Moreover, it underscores the role of biological ageing in mediating these associations, emphasizing the need for interventions targeting both insulin resistance and ageing processes to mitigate mortality risks in metabolic disorders. [ABSTRACT FROM AUTHOR]

Summary: Objective: Children with overweight/obesity (OW/OB) exhibit poor cardiometabolic health, yet mechanisms influencing brain health remain unclear. We examined the differences in neurological‐related circulating proteins in plasma among children with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) and the association with metabolic syndrome markers. Methods: In this cross‐sectional study, we included 84 Caucasian children (39% girls), aged 10.1 ± 1.1 years, from the ActiveBrains project (NCT02295072). A ninety‐two‐protein targeted approach using Olink's® technology was used. Results: We identified distinct concentrations of CD38, LAIR2, MANF and NRP2 proteins in MHO compared with MUO. Moreover, individual metabolic syndrome (MS) markers were linked to nine proteins (CD38, CPM, EDA2R, IL12, JAMB, KYNU, LAYN, MSR1 and SMOC2) in children with OW/OB. These proteins play crucial roles in diverse biological processes (e.g., angiogenesis, cholesterol transport, nicotinamide adenine dinucleotide (NAD+) catalysis and maintenance of blood–brain barrier) related to brain health. Conclusion: Our proteomics study suggests that cardiometabolic health (represented by MHO/MUO or individual MS markers) is associated with the concentration in plasma of several proteins involved in brain health. Larger‐scale studies are needed to contrast/confirm these findings, with CD38 standing out as a particularly noteworthy and robust discovery. [ABSTRACT FROM AUTHOR]

Summary: Objective: This study identified metabolite modules associated with adiposity and body fat distribution in childhood using gold‐standard measurements. Methods: We used cross‐sectional data from 329 children at mid‐childhood (age 5.3 ± 0.3 years; BMI 15.7 ± 1.5 kg/m2) from the Genetics of Glucose regulation in Gestation and Growth (Gen3G), a prospective pre‐birth cohort. We quantified 1038 plasma metabolites and measured body composition using the gold‐standard dual‐energy x‐ray absorptiometry (DXA), in addition to skinfold, waist circumference, and BMI. We applied weighted‐correlation network analysis to identify a network of highly correlated metabolite modules. Spearman's partial correlations were applied to determine the associations of adiposity with metabolite modules and individual metabolites with false discovery rate (FDR) correction. Results: We identified a 'green' module of 120 metabolites, primarily comprised of lipids (mostly sphingomyelins and phosphatidylcholine), that showed positive correlations (all FDR p < 0.05) with DXA estimates of total and truncal fat (ρadjusted = 0.11–0.19), skinfold measures (ρadjusted = 0.09–0.26), and BMI and waist circumference (ρadjusted = 0.15 and 0.18, respectively). These correlations were similar when stratified by sex. Within this module, sphingomyelin (d18:2/14:0, d18:1/14:1)*, a sphingomyelin sub‐specie that is an important component of cell membranes, showed the strongest associations. Conclusions: A module of metabolites was associated with adiposity measures in childhood. [ABSTRACT FROM AUTHOR]

Summary: Background: Filgotinib, an oral, once‐daily, Janus kinase 1 preferential inhibitor, is an approved treatment for moderately to severely active ulcerative colitis. Aims: The aim of this study is to assess the safety and efficacy of continued filgotinib therapy over ~4 years in the long‐term extension of the phase 2b/3 SELECTION trial (SELECTIONLTE; NCT02914535). Methods: In this interim analysis of SELECTIONLTE, SELECTION completers (week 10 responders to filgotinib who completed the maintenance study) continued their assigned treatment (double‐blind filgotinib 200 mg [FIL200] or filgotinib 100 mg) and SELECTION week 10 non‐responders received open‐label FIL200. We assessed safety by adverse events (AEs), and efficacy by partial Mayo Clinic Score (pMCS), inflammatory biomarkers and health‐related quality of life (HRQoL). We compared safety and efficacy between achievers and non‐achievers of a multi‐component endpoint, comprehensive disease control (CDC), comprising symptomatic, endoscopic, inflammatory biomarker and HRQoL improvements. Results: Data for completers (n = 250) and non‐responders (n = 372) were reported for ≤202 weeks. AE occurrences were low and consistent with previous analyses. The as‐observed proportion of FIL200‐treated patients in pMCS, biomarker and HRQoL remission during SELECTIONLTE remained high among completers (week 144: 80.0%, 86.4% and 86.0%, respectively) and increased among non‐responders (week 192: 62.1%, 76.7% and 59.3%, respectively). Significantly higher proportions of CDC achievers at SELECTION week 58 achieved pMCS, IBDQ and corticosteroid‐free pMCS remission than non‐achievers, up to LTE week 96. Conclusions: Filgotinib induced and maintained symptomatic remission and improved HRQoL over 4 years. Safety results showed a proven long‐term benefit–risk profile. FIL200‐treated CDC achievers had better long‐term outcomes than non‐achievers. [ABSTRACT FROM AUTHOR]

Summary: Background and Aims: For chronic hepatitis B (CHB) patients, there is still a need to improve hepatitis B surface antigen (HBsAg) clearance rates. This study aimed to assess the predictive effectiveness of soluble programmed cell death‐1 (sPD‐1) and soluble programmed cell death ligand‐1 (sPD‐L1) for HBsAg clearance in HBeAg‐negative CHB patients undergoing peginterferon (Peg‐IFN)‐based antiviral treatment. Methods: This study encompassed 280 patients undergoing treatment with Peg‐IFNα. Serum levels of sPD‐1 and sPD‐L1 were measured using ELISA kits at baseline, as well as at 12, 24 and 48 weeks. The primary endpoint of the study was the determination of HBsAg clearance at 48 weeks. Logistic regression analysis was employed to identify predictors of HBsAg clearance. Results: The clearance group demonstrated significantly lower serum sPD‐L1 levels compared to the non‐clearance group. While both groups exhibited an increase in sPD‐1 levels, only the clearance group showed a rise in sPD‐L1 levels. Multivariate analysis identified sPD‐L1 increase at 24 weeks, and HBsAg decline at 24 weeks as predictors for HBsAg clearance at 48 weeks. The combined use of these indicators showed a predictive performance for HBsAg clearance with an AUROC of 0.907 (95% CI: 0.861–0.953, p < 0.001). Conclusions: The study revealed an inverse relationship between the trends of sPD‐1/sPD‐L1 and HBsAg clearance during combined IFN and NAs treatment. Moreover, the magnitude of HBsAg reduction and sPD‐L1 increase emerged as significant predictors for HBsAg clearance. [ABSTRACT FROM AUTHOR]

Introduction: The successes in the field of pediatric kidney transplantation over the past 60 years have been extraordinary. Year over year, there have been significant improvements in short‐term graft survival. However, improvements in longer‐term outcomes have been much less apparent. One important contributor has been the phenomenon of low‐level rejection in the absence of clinical manifestations—so‐called subclinical rejection (SCR). Methods: Traditionally, rejection has been diagnosed by changes in clinical parameters, including but not limited to serum creatinine and proteinuria. This review examines the shortcomings of this approach, the effects of SCR on kidney allograft outcome, the benefits and drawbacks of surveillance biopsies to identify SCR, and new urine and blood biomarkers that define the presence or absence of SCR. Results: Serum creatinine is an unreliable index of SCR. Surveillance biopsies are the method most utilized to detect SCR. However, these have significant drawbacks. New biomarkers show promise. These biomarkers include blood gene expression profiles and donor derived‐cell free DNA; urine gene expression profiles; urinary cytokines, chemokines, and metabolomics; and other promising blood and urine tests. Conclusion: Specific emphasis is placed on studies carried out in pediatric kidney transplant recipients. Trial Registration: ClinicalTrials.gov: NCT03719339 [ABSTRACT FROM AUTHOR]

Background and purpose: Neurofilament light chain (NFL) has been shown to be increased in amyotrophic lateral sclerosis (ALS) and, to a lesser extent, in frontotemporal dementia (FTD). A meta‐analysis of NFL in ALS and FTD was performed. Methods: Available studies comparing cerebrospinal fluid and blood NFL levels in ALS versus neurologically healthy controls (NHCs), other neurological diseases (ONDs) and ALS mimics, as well as in FTD and related entities (behavioural variant of FTD and frontotemporal lobar degeneration syndromes) versus NHCs, ONDs and other dementias were evaluated. Results: In ALS, both cerebrospinal fluid and blood levels of NFL were higher compared to other categories. In FTD, behavioural variant of FTD and frontotemporal lobar degeneration syndromes, NFL levels were consistently higher compared to NHCs; however, several comparisons with ONDs and other dementias did not demonstrate significant differences. Discussion: Amyotrophic lateral sclerosis is characterized by higher NFL levels compared to most other conditions. In contrast, NFL is not as good at discriminating FTD from other dementias. [ABSTRACT FROM AUTHOR]

Background and purpose: A real‐time biomarker in chemotherapy‐induced peripheral neurotoxicity (CIPN) would be useful for clinical decision‐making during treatment. Neurofilament light chain (NfL) can be detected in blood in the case of neuroaxonal damage. The aim of the study was to compare the levels of plasma NfL (pNfL) according to the type of chemotherapeutic agent and the severity of CIPN. Methods: This single‐center prospective observational longitudinal study included patients treated with paclitaxel (TX; n = 34), brentuximab vedotin (BV; n = 29), or oxaliplatin (PT; n = 19). All patients were assessed using the Total Neuropathy Score–clinical version and Common Terminology Criteria for Adverse Events before, during, and up to 6–12 months after the end of treatment. Nerve conduction studies (NCS) were performed before and after chemotherapy discontinuation. Consecutive plasma samples were analyzed for NfL levels using a Simoa® analyzer. Changes in pNfL were compared between groups and were eventually correlated with clinical and NCS data. Clinically relevant (CR) CIPN was considered to be grade ≥ 2. Results: Eighty‐two patients, mostly women (59.8%), were included. One third of the patients who received TX (29.4%), BV (31%), or PT (36.8%) developed CR‐CIPN, respectively, without differences among them (p = 0.854). Although pNfL significantly increased during treatment and decreased throughout the recovery period in all three groups, patients receiving TX showed significantly greater and earlier changes in pNfL levels compared to the other agents (p < 0.001). Conclusions: A variable change in pNfL is observed depending on the type of agent and mechanism of neurotoxicity with comparable CIPN severity, strongly implying the need to identify different cutoff values for each agent. [ABSTRACT FROM AUTHOR]

Background/Objectives: At present, there are few biomarkers used to predict the prognosis of uterine serous carcinoma (USC). Netrin‐1 may be a promising biomarker candidate. We investigated netrin‐1 expression in USC tissues and healthy endometrial tissues to determine its relevance to disease prognosis. Materials and Methods: Netrin‐1 expression was examined in the tissues of 48 patients with USC and 30 patients with healthy benign endometrial tissues via immunohistochemistry. Results: None of the healthy tissues were stained with netrin‐1. In tumor tissues, the overall positivity rate of netrin‐1 was 75%, detected as high expression in 17 patients (35%) and low in 19 (40%). Patients who had tumors with no netrin‐1 expression (n = 12) had a median overall survival (OS) of 60.0 months (95% confidence interval [CI], 47–98), whereas patients who had tumors with low to strong netrin‐1 expression (n = 33) had a lower median OS of 50 months, but the difference was not statistically significant (95% CI, 58–108; P = 0.531). Disease‐free survival (DFS) was not statistically significant between the groups (95% CI, 67.7–115.9; P = 0.566). Patients with a tumor diameter ≥2 cm had higher netrin‐1 expression than those with a tumor diameter of 2 cm (P = 0.027). We did not find any difference in overall and DFS when age, tumor stage, histology, tumor diameter, p53 status, lymphovascular space invasion, myometrial invasion, and lymph node metastasis were compared according to netrin‐1 expression (P > 0.05). Conclusion: Netrin‐1 was expressed in USC but not in healthy tissues. Its expression was not associated with OS or DFS. Synopsis: Netrin‐1 is highly expressed in uterine serous carcinoma but not in healthy tissues; however, its association with survival remains unknown. [ABSTRACT FROM AUTHOR]

Background: Machine learning (ML) offers an opportunity in contact dermatitis (CD) research, where with full clinical picture, may support diagnosis and patch test accuracy. Objective: This review aims to summarise the existing literature on how ML can be applied to CD in its entirety. Methods: Embase, Medline, IEEE Xplore, and ACM Digital Library were searched from inception to February 7, 2024, for primary literature reporting on ML models in CD. Results: 7834 articles were identified in the search, with 110 moving to full‐text review, and six articles included. Two used ML to identify key biomarkers to help distinguish between allergic contact dermatitis (ACD) and irritant contact dermatitis (ICD), three used image data to distinguish between ACD and ICD, and one used clinical and demographical data to predict the risk of positive patch tests. All studies used supervision in their ML model training with a total of 49 704 patients across all data sets. There was sparse reporting of the accuracy of these models. Conclusions: Although the available research is still limited, there is evidence to suggest that ML has potential to support diagnostic outcomes in a clinical setting. Further research on the use of ML in clinical practice is recommended. [ABSTRACT FROM AUTHOR]

In a placebo‐controlled clinical study one may calculate the average treatment effect to convey the effect of the active treatment on some outcome. However, if it is speculated that the treatment only has an effect if the patient responds to the treatment defined by a certain biomarker response, then it is arguably more relevant to estimate the treatment effect among such responders. We present such a causal parameter that is based on principal stratification and is identified under the exclusion of a treatment effect among the nonresponders. We focus on time‐to‐event outcomes allowing for right censoring, and construct a doubly robust and efficient estimator based on the associated efficient influence function. The properties of the estimator are showcased in a simulation study and the methodology is applied to the Leader trial investigating the effect of liraglutide on the occurrence of cardiovascular events. [ABSTRACT FROM AUTHOR]

Objective: Our aim was to survey astrocyte and microglial activation across four brain regions in a mouse model of chronic migraine. Background: Chronic migraine is a leading cause of disability, with higher rates in females. The role of central nervous system neurons and glia in migraine pathophysiology is not fully elucidated. Preclinical studies have shown abnormal glial activation in the trigeminal nucleus caudalis of male rodents. No current reports have investigated glial activation in both sexes in other important brain regions involved with the nociceptive and emotional processing of pain. Methods: The mouse nitroglycerin model of migraine was used, and nitroglycerin (10 mg/kg) or vehicle was administered every other day for 9 days. Prior to injections on days 1, 5, and 9, cephalic allodynia was determined by periorbital von Frey hair testing. Immunofluorescent staining of astrocyte marker, glial fibrillary protein (GFAP), and microglial marker, ionized calcium binding adaptor molecule 1 (Iba1), in male and female trigeminal nucleus caudalis, periaqueductal gray, somatosensory cortex, and nucleus accumbens was completed. Results: Behavioral testing demonstrated increased cephalic allodynia in nitroglycerin‐ versus vehicle‐treated mice. An increase in the percent area covered by GFAP+ cells in the trigeminal nucleus caudalis and nucleus accumbens, but not the periaqueductal gray or somatosensory cortex, was observed in response to nitroglycerin. No significant differences were observed for Iba1 staining across brain regions. We did not detect significant sex differences in GFAP or Iba1 quantification. Conclusions: Immunohistochemical analysis suggests that, at the time point tested, immunoreactivity of GFAP+ astrocytes, but not Iba1+ microglia, changes in response to chronic migraine‐associated pain. Additionally, there do not appear to be significant differences between males and females in GFAP+ or Iba1+ cells across the four brain regions analyzed. Plain Language Summary: The aim of this study was to determine if supportive immune cells in the brains of males and females are altered in an animal model of chronic migraine. Mice in the chronic migraine group showed significant activation of astrocytes, but not microglia, in male and female mice in pain and emotion‐processing brain regions. These results suggest that some supportive cells in the brain may play a role in regulating chronic migraine. [ABSTRACT FROM AUTHOR]

Direct analysis in real time (DART) represents a new generation of ionization techniques that are used to rapidly ionize small molecules under ambient environments. The combination of DART with various mass spectrometry (MS) instruments allows analyzing multiple plant materials, including traditional Chinese herbal medicines (TCHMs), under simple or no sample treatment conditions. This review discussed the DART principles, including devices, ionization mechanisms, and operation parameters. Typical spectra detected by DART‐MS were exhibited and discussed. Numerous applications of DART‐MS in the fields of plant material and TCHM analysis were reviewed, including compound identification, biomarker discovery, fingerprinting analysis, and quantification analysis. Besides, modifications and improvements of DART‐MS, such as hyphenated application with other separation methods, laser‐based desorption techniques, and online sampling configuration, were summarized as well. [ABSTRACT FROM AUTHOR]

This article presents a case study of a patient with a rare vascular tumor called epithelioid hemangioendothelioma (EHE). The study describes the characteristics of EHE cells and discusses the challenges in diagnosing this tumor due to its variability and lack of specific markers. The article also compares EHE with other malignancies and emphasizes the importance of using vascular markers and molecular studies to confirm the diagnosis. The prognosis for EHE in the lungs or pleura is generally poor, and treatment usually involves surgery with or without chemoradiation. [Extracted from the article]

Purpose: Cancer patients' psycho‐physiological health is seriously affected by long‐term exposure to stress. Many studies have explored the impact of stress‐specific interventions on cancer patients' biomarker levels and cognitive functions. However, the current research findings are inconsistent, and their statistical power is limited by the small samples. Therefore, we conducted this meta‐analysis to verify the effect of stress‐specific interventions on cancer patients. Methods: The literature involved nine databases from the inception until January 13, 2024, extracted 19 randomized controlled trials (RCTs). Review Manager (RevMan) 5.4 software was used to perform a meta‐analysis, and the revised Cochrane risk of bias tool (RoB2) was utilized for quality evaluation. Results: Nine RCTs were assessed as having a low risk of bias, and others had a moderate risk. The results showed that stress‐specific interventions had beneficial effects on patients' subjective cognition but uncertain impacts on their executive function, tumour necrosis factor‐α level, morning cortisol level, and no effect on cortisol at other times, interleukin (IL)‐10, IL‐8, IL‐6, IL‐1, and C‐reactive protein. Conclusion: More rigorous studies are required to elucidate the influence of stress‐specific interventions on biomarker levels. The potential mechanism by which stress‐specific interventions affect the cancer patient's cognitive function remains unclear. [ABSTRACT FROM AUTHOR]

Aim: To investigate the effects of high‐intensity interval training (HIIT) on periodontitis (PD) progression and behavioural outcomes. Materials and Methods: Forty‐eight Wistar rats were divided into four groups: non‐trained (NT); non‐trained with PD; HIIT with PD; and HIIT. The HIIT protocol, involving daily treadmill sessions, spanned 8 weeks, with PD induced by ligature after the 6th week. Behavioural tests were conducted to assess anxiety and memory. Post euthanasia, we evaluated the systemic inflammatory profile and oxidative stress markers in the hippocampus and amygdala. A morphological evaluation and elemental composition analysis of the mandibular alveolar bone were performed. Results: PD exacerbated alveolar bone level, bone surface damage and alterations in calcium and phosphorus percentages on the bone surface (p <.05), while HIIT attenuated these changes (p <.05). HIIT improved systemic inflammatory markers altered by PD (tumour necrosis factor [TNF]‐α, interleukin [IL]‐10, TNF‐α/IL‐10 and IL‐1β/IL‐10 ratios, p <.05). PD animals exhibited lower total antioxidant capacity and levels of thiobarbituric acid reactive substances in the amygdala and hippocampus, respectively (p <.05). HIIT maintained these parameters at levels similar to those in NT animals. HIIT improved anxiety and memory outcomes altered by PD (p <.05). Conclusions: HIIT attenuates systemic inflammation, anxiety and memory outcomes promoted by PD. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by progressive loss of dopamine neurons and aberrant deposits of alpha‐synuclein (α‐syn) in the brain. The symptomatic treatment is started after the onset of motor manifestations in a late stage of the disease. Preclinical studies with neurotrophic factors (NTFs) show promising results of disease‐modifying neuroprotective or even neurorestorative effects. Four NTFs have entered phase I–II clinical trials with inconclusive outcomes. This is not surprising because the preclinical evidence is from acute early‐stage disease models, but the clinical trials included advanced PD patients. To conclude the value of NTF therapies, clinical studies should be performed in early‐stage patients with prodromal symptoms, that is, before motor manifestations. In this review, we summarize currently available diagnostic and prognostic biomarkers that could help identify at‐risk patients benefiting from NTF therapies. Focus is on biochemical and imaging biomarkers, but also other modalities are discussed. Neuroimaging is the most important diagnostic tool today, but α‐syn imaging is not yet viable. Modern techniques allow measuring various forms of α‐syn in cerebrospinal fluid, blood, saliva, and skin. Digital biomarkers and artificial intelligence offer new means for early diagnosis and longitudinal follow‐up of degenerative brain diseases. [ABSTRACT FROM AUTHOR]

Background: Chronic wounds have been associated with an elevated burden of cellular senescence, a state of essentially irreversible cell cycle arrest, resistance to apoptosis, and a secretory phenotype. However, whether senescent cells contribute to wound chronicity in humans remains unclear. The objective of this article is to assess the role of clinicopathological characteristics and cellular senescence in the time‐to‐healing of chronic wounds. Methods: A cohort of 79 patients with chronic wounds was evaluated in a single‐center academic practice from February 1, 2005, to February 28, 2015, and followed for up to 36 months. Clinical characteristics and wound biopsies were obtained at baseline, and time‐to‐healing was assessed. Wound biopsies were analyzed histologically for pathological characteristics and molecularly for markers of cellular senescence. In addition, biopsy slides were stained for p16INK4a expression. Results: No clinical or pathological characteristics were found to have significant associations with time‐to‐healing. A Cox proportional hazard ratio model revealed increased CDKN1A (p21CIP1/WAF1) expression to predict longer time‐to‐healing, and a model adjusted for gender and epidermal hyperplasia revealed increased CDKN1A expression and decreased PAPPA expression to predict longer time‐to‐healing. Increased p16INK4a staining was observed in diabetic wounds compared to non‐diabetic wounds, and the same association was observed in the context of high dermal fibrosis. Conclusions: The findings of this pilot study suggest that senescent cells contribute to wound chronicity in humans, especially in diabetic wounds. [ABSTRACT FROM AUTHOR]

Intravoxel incoherent motion (IVIM) MRI has emerged as a valuable technique for the assessment of tissue characteristics and perfusion. However, there is limited knowledge about the relationship between IVIM‐derived measures and changes at the level of the vascular network. In this study, we investigated the potential use of IVIM MRI as a noninvasive tool for measuring changes in cerebral vascular density. Variations in quantitative immunohistochemical measurements of the vascular density across different regions in the rat brain (cortex, corpus callosum, hippocampus, thalamus, and hypothalamus) were related to the pseudo‐diffusion coefficient D* and the flowing blood fraction f in healthy Wistar rats. We assessed whether region‐wise differences in the vascular density are reflected by variations in the IVIM measurements and found a significant positive relationship with the pseudo‐diffusion coefficient (p < 0.05, β = 0.24). The effect of cerebrovascular alterations, such as blood–brain barrier (BBB) disruption on the perfusion‐related IVIM parameters, is not well understood. Therefore, we investigated the effect of BBB disruption on the IVIM measures in a rat model of metabolic and vascular comorbidities (ZSF1 obese rat) and assessed whether this affects the relationship between the cerebral vascular density and the noninvasive IVIM measurements. We observed increased vascular permeability without detecting any differences in diffusivity, suggesting that BBB leakage is present before changes in the tissue integrity. We observed no significant difference in the relationship between cerebral vascular density and the IVIM measurements in our model of comorbidities compared with healthy normotensive rats. [ABSTRACT FROM AUTHOR]

The article discusses the importance of extending model-informed drug development (MIDD) by incorporating epidemiological and health economic considerations. It presents examples of extended MIDD in various therapeutic areas and emphasizes the need to go beyond safety and efficacy evaluation during regulatory approval. The article highlights the role of extended MIDD in assessing the public health impact of drugs, evaluating cost-effectiveness, and informing clinical trial design. It also discusses the application of extended MIDD in infectious diseases, cardiovascular diseases, and rare diseases. The authors emphasize the benefits of early adoption of modular approaches in drug development and suggest that continued progress in extended MIDD will enable better decision-making and optimization of drug use. [Extracted from the article]

The purpose of precision dosing is to increase the chances of therapeutic success in individual patients. This is achieved in practice by adjusting doses to reach precision dosing targets determined previously in relevant populations, ideally with robust supportive evidence showing improved clinical outcomes compared with standard dosing. But is this implicit assumption of translatable population‐level precision dosing targets correct and the best for all patients? In this review, the types of precision dosing targets and how they are determined are outlined, problems with the translatability of these targets to individual patients are identified, and ways forward to address these challengers are proposed. Achieving improved clinical outcomes to support precision dosing over standard dosing is currently hampered by applying population‐level targets to all patients. Just as "one‐dose‐fits‐all" may be an inappropriate philosophy for drug treatment overall, a "one‐target‐fits‐all" philosophy may limit the broad clinical benefits of precision dosing. Defining individual‐level precision dosing targets may be needed for greatest therapeutic success. Superior future precision dosing targets will integrate several biomarkers that together account for the multiple sources of drug response variability. [ABSTRACT FROM AUTHOR]

Biomarkers are often measured in bulk to diagnose patients, monitor patient conditions, and research novel drug pathways. The measurement of these biomarkers often suffers from detection limits that result in missing and untrustworthy measurements. Frequently, missing biomarkers are imputed so that down‐stream analysis can be conducted with modern statistical methods that cannot normally handle data subject to informative censoring. This work develops an empirical Bayes g$$ g $$‐modeling method for imputing and denoising biomarker measurements. We establish superior estimation properties compared to popular methods in simulations and with real data, providing the useful biomarker measurement estimations for down‐stream analysis. [ABSTRACT FROM AUTHOR]

The incorporation of novel therapeutic agents such as antibody‐drug conjugates, radio‐conjugates, T‐cell engagers, and chimeric antigen receptor cell therapies represents a paradigm shift in oncology. Cell‐surface target quantification, quantitative assessment of receptor internalization, and changes in the tumor microenvironment (TME) are essential variables in the development of biomarkers for patient selection and therapeutic response. Assessing these parameters requires capabilities that transcend those of traditional biomarker approaches based on immunohistochemistry, in situ hybridization and/or sequencing assays. Computational pathology is emerging as a transformative solution in this new therapeutic landscape, enabling detailed assessment of not only target presence, expression levels, and intra‐tumor distribution but also of additional phenotypic features of tumor cells and their surrounding TME. Here, we delineate the pivotal role of computational pathology in enhancing the efficacy and specificity of these advanced therapeutics, underscoring the integration of novel artificial intelligence models that promise to revolutionize biomarker discovery and drug development. [ABSTRACT FROM AUTHOR]

Aims Methods Conclusions There is a lack of therapies able to prevent anthracycline cardiotoxicity (AC). Remote ischaemic conditioning (RIC) has shown beneficial effects in preclinical models of AC.REmote iSchemic condItioning in Lymphoma PatIents REceiving ANthraCyclinEs (RESILIENCE) is a multinational, prospective, phase II, double‐blind, sham‐controlled, randomized clinical trial that evaluates the efficacy and safety of RIC in lymphoma patients receiving anthracyclines. Patients scheduled to undergo ≥5 chemotherapy cycles including anthracyclines and with ≥1 AC‐associated risk factors will be randomized to weekly RIC or sham throughout the chemotherapy period. Patients will undergo three multiparametric cardiac magnetic resonance (CMR) studies, at baseline, after the third cycle (intermediate CMR), and 2 months after the end of chemotherapy. Thereafter, patients will be followed up for clinical events over an anticipated median of ≥24 months. The primary endpoint is the absolute change from baseline in CMR‐based left ventricular ejection fraction (LVEF). The main secondary outcome is the incidence of AC events, defined as (1) a drop in CMR‐based LVEF of ≥10 absolute points, or (2) a drop in CMR‐based LVEF of ≥5 and <10 absolute points to a value <50%. Intermediate CMR will test the ability of T2 mapping to predict AC versus classical markers (left ventricular strain and cardiac injury biomarkers). A novel CMR sequence allowing ultrafast cine acquisition will be validated in this vulnerable population.The RESILIENCE trial will test RIC (a novel non‐invasive intervention to prevent AC) in a cohort of high‐risk patients. The trial will also test candidate markers for their capacity to predict AC and will validate a novel CMR sequence reducing acquisition time in a vulnerable population. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Patients with programmed cell death‐ligand 1 (PD‐L1) ≥50% metastatic non‐small cell lung cancer (NSCLC) treated with first‐line immunotherapy showed heterogeneous tumor responses. In this study, we investigated the clinical and immune‐inflammatory markers distinguishing patients with metastatic NSCLC achieving high depth of tumor response (HDPR) from those with non‐high depth of response (NHDPR). The impact of clinical features on the prognosis of patients with PD‐L1 ≥50% were further clarified.The clinical characteristics and immune‐inflammatory markers of 17 patients with PD‐L1 ≥50% metastatic NSCLC at Beijing Tiantan Hospital between July 2020 and December 2023 were retrospectively analyzed.Among the 17 patients, seven (41.2%) patients achieved HDPR (range: −50%, −72%) and 10 (58.8%) patients achieved NHDPR (range: −13%, −45%). Below normal CD4 + T lymphocytes/CD8 + T lymphocytes (CD4/CD8) ratio (p = 0.01) and oncogenes and/or tumor suppressor gene mutations (TP53/KRAS/EGFR) (p = 0.001) were found enriched for NHDPR compared with HDPR. With a median follow‐up of 26.0 months (range: 17.2–34.8 months), the median progression‐free survival (PFS) following first‐line immunotherapy and overall survival (OS) were 9.0 months (95% CI: 5.0–13.0) and not reached (NR), respectively. The neutrophil‐to‐lymphocyte ratio (NLR) was identified as an independent prognostic factor on first‐line PFS. Patients with an NLR ≥4 exhibited a shorter median PFS (7.0 months vs. NR; p = 0.033; 95% CI: 1.2–80.2) than those with an NLR <4 following first‐line immunotherapy.Among patients with PD‐L1 ≥50% metastatic NSCLC who received first‐line immunotherapy, a lower CD4/CD8 ratio and the presence of genes mutations showed a diminished tumor response and a higher NLR ratio exhibited a worse median PFS. [ABSTRACT FROM AUTHOR]

Background Methods Results Discussion Slower speaking rates and higher pause rates are found in individuals with migraine or post‐traumatic headache during headache compared to when headache‐free. We aimed to determine whether headache intensity influences the speaking rate and pause rate of participants with migraine or acute post‐traumatic headache (aPTH) following mild traumatic brain injury (mTBI).Using a speech elicitation tool, participants with migraine, aPTH, and healthy controls (HC) submitted speech samples over a period of 3 months. Speaking and pause rates were calculated when participants were headache‐free and when they had mild or moderate headache. In this observational study, speaking and pause rates in participants with migraine and aPTH were compared to HC, controlling for age, sex, and days since mTBI (participants with aPTH only).A total of 2902 longitudinal speech samples from 13 individuals with migraine (mean age = 33.5, SD = 6.6; 12 females/1 male), 43 individuals with aPTH (mean age = 44.4, SD = 13.5; 28 females/15 males), and 56 HC (mean age = 40.8, SD = 13.0; 36 females/20 males) were collected. There was no difference in speaking rate between HC and the combined headache cohort of participants (migraine and aPTH) when they had headache freedom or a mild headache. When participants had moderate intensity headache, their speaking rate was significantly slower compared to that of HC and compared to their speaking rate during mild headache intensity or headache freedom. For the combined headache cohort of participants, pause rates were significantly higher when they had headache freedom or had a headache of mild or moderate intensity relative to HC. Compared to participants' pause rate during headache freedom, their pause rate was significantly higher during mild and moderate headache intensity. Participants with aPTH had significantly slower speaking rates compared to participants with migraine during headache freedom, mild headache intensity, and moderate headache intensity. Participants with aPTH had significantly higher pause rates compared to participants with migraine when experiencing moderate headache intensity.For both aPTH and migraine, more severe headache pain was associated with higher pause rates and slower speaking rates, suggesting that speaking rate and pause rate could serve as objective biomarkers for headache‐related pain. Slower speaking rate in participants with aPTH could reflect additional consequences of TBI‐related effects on motor control and speech production. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Intraepithelial lymphocytes are the first line of defence of the human intestinal immune system. Besides, their composition is altered on patients with coeliac disease (CD), so they are considered as biomarkers with utility on their diagnose and/or monitoring. Our aim is to address their variability through the human gastrointestinal tract in health and characterized them in further depth in the coeliac duodenum.Intraepithelial lymphocytes were isolated from human gastric, duodenal, ileal and colonic biopsies, then stained with specific antibodies and acquired by flow cytometry.Our results confirmed that the profile of Intraepithelial lymphocytes change through the length of the human gastrointestinal tract. Besides and given the central role that Interleukin‐15 (IL‐15) elicits on CD pathogenesis; we also assessed the expression of its receptor revealing that there was virtually no functional IL‐15 receptor on duodenal Intraepithelial lymphocytes. Nevertheless and contrary to our expectations, the active IL‐15 receptor was not increased either on Intraepithelial lymphocytes from CD patients.IL‐15 might require additional stimulus to activate intraepithelial lymphocytes. These findings may provide novel tools to aid on a CD diagnosis and/or monitoring, at the time that provide the bases to perform functional studies in order of getting a deeper insight in the specific function that Intraepithelial lymphocytes elicit on CD pathogenesis. [ABSTRACT FROM AUTHOR]

Summary To use proteomic techniques to identify sensitive diagnostic biomarkers for paediatric immune thrombocytopenia (ITP). We selected children in ITP and control groups, using a four‐dimensional data‐independent acquisition approach (4D‐DIA) to analyse its protein expression. The significantly differentially expressed proteins were selected for enzyme‐linked immunosorbent assay (ELISA) validation in a cohort comprising 50 samples (13 healthy controls, 15 secondary thrombocytopenia controls and 22 children with ITP). Receiver operating characteristics (ROC) were generated to diagnose ITP and to assess the diagnostic effectiveness of this approach. Compared with the control group, 55 differentially expressed proteins (43 increased and 12 decreased) were determined in the ITP group. Matrix metalloproteinases‐9 (MMP‐9) and thrombospondin‐1 (THBS1) were significantly expressed and selected for ELISA. The verification outcomes aligned with the findings from the proteomic examinations. In contrast to the control cohort, the ITP subjects exhibited markedly elevated plasma MMP‐9 levels and reduced plasma THBS1 concentrations. Additionally, the ROC curves indicated the diagnostic value of these biomarkers. In conclusion, proteomics facilitates identifying the sensitive biomarkers for ITP diagnosis. We have preliminarily selected two differentially expressed proteins, MMP‐9 and THBS1, whose potential role as biomarkers for diagnosing ITP requires further research. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Patients with Parkinson's disease (PD) suffer from serious quality of life problems. Diabetes has been demonstrated as an independent risk element for PD, aggravating its severity and accelerating its progression. There are currently no suitable biomarkers to reveal the impact of diabetes on PD. The purpose of our research was to study the impact of diabetes on PD using corneal confocal microscopy (CCM), a non‐invasive and objective test.Fourteen PD patients with diabetes (PD‐DM), 60 PD patients without diabetes (PD‐NDM), and 30 healthy controls (HC) were included in the study. The clinical symptoms of patients with PD were assessed using the Unified Parkinson's Disease Rating Scale‐3 (UPDRS‐3) and the Parkinson's Disease Autonomic Symptom Prognosis Scale (SCOPA‐AUT). Participants underwent CCM to quantify the corneal nerve fibres.Corneal nerve fibre density (CNFD) and corneal nerve fibre length (CNFL) in patients with PD were lower than HC. Furthermore, CNFD in PD‐DM was lower than in PD‐NDM (P < 0.01). We also assessed the relationship between CCM parameters and clinical scores. CNFL and Hamilton anxiety (HAMA) have a negative correlation (r = −0.261, P = 0.032), but this study did not observe a significant correlation between CCM parameters and SCOPA‐AUT. Additionally, CNFD could distinguish PD‐DM from PD‐NDM, achieving an area under the curve of 75.06% (95% CI, 61.76%–88.36%).The CCM could be served as an objective and sensitive biomarker to investigate the impact of diabetes in PD. [ABSTRACT FROM AUTHOR]

At the 39th meeting of the International Society of Traumatic Stress Studies, four leading scientists and clinicians were invited to reflect on their careers, focusing on the biological mechanisms and markers of traumatic stress. Dr. Raul Andero has contributed to understanding how stress alters memory networks in the brain, influencing the development of novel treatments. Dr. Tanja Jovanovic has pioneered the measurement and mechanistic understanding of fear learning, bridging basic and clinical research. Dr. Murray B. Stein has scaled up clinical and lab observations to large populations, refining the field's understanding of traumatic stress. Dr. Arieh Y Shalev has shaped the definition of traumatic stress, pioneering the longitudinal investigation of stress and integrating advanced computational methods to identify individuals at risk. These panelists were asked to reflect on their initial problems, ambitions, concerns, and unexpected challenges, as well as the influence of their work, on new research trajectories. Their insights provide valuable lessons about the process and content of their work, and their pioneering efforts have significantly advanced our understanding of the biological mechanisms and markers of traumatic stress. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusions This study describes the pharmacokinetic (PK)/target engagement (TE) relationship of tozorakimab, an anti‐interleukin (IL)‐33 antibody, by building a mechanistic population PK/TE model using phase 1 biomarker data.The analysis included tozorakimab PK and TE in serum assessed in 60 tozorakimab‐treated participants, including healthy adults and patients with mild chronic obstructive pulmonary disease. Scenarios evaluated three dose frequencies (once every 2, 4 or 6 weeks) administered subcutaneously at seven doses of tozorakimab (30, 60, 90, 120, 150, 300 or 600 mg). For each dose, simulations were performed with 5000 virtual individuals to predict systemic TE. Inhibition of IL‐33/soluble ST2 (sST2) complex levels at trough PK at steady state was assessed in each dosing scenario. The PK/TE modelling analyses were performed using a nonlinear mixed‐effect modelling approach.The final two‐compartment PK model with tozorakimab binding IL‐33 in the central compartment adequately described the systemic PK and TE of tozorakimab at population and individual levels. The mean PK parameter estimates of absorption rate, central volume of distribution and clearance were 0.48 (90% confidence interval [CI]: 0.40–0.59, 1/day), 12.64 (90% CI: 8.60–18.62, L) and 0.87 (90% CI: 0.65–1.16, L/day), respectively. Consistent with the observed value, tozorakimab bioavailability was 45%. For all three dose frequencies, predicted inhibition of systemic IL‐33/sST2 levels was more than 95% at doses greater than 90 mg.The PK/TE model reliably quantified the relationship between PK and systemic TE of tozorakimab, with potential utility for predicting clinical dose–response relationships and supporting clinical dose selection. [ABSTRACT FROM AUTHOR]

Objective Methods Results Interpretation Neurofilament light chains (NfL) and phosphorylated neurofilament heavy chains (pNfH), established as diagnostic and prognostic biomarkers in hospital‐based amyotrophic lateral sclerosis (ALS) cohorts, are now surrogate markers in clinical trials. This study extends their evaluation to a population level, with the aim of advancing their full establishment and assessing the transferability of biomarker findings from controlled cohorts to real‐world ALS populations.We measured serum NfL and pNfH levels in all ALS patients (n = 790) and general population controls (n = 570) with available baseline samples participating in the epidemiological ALS Registry Swabia, providing platform‐specific (ELLA™) reference data and Z‐scores for controls, as well as reference data, disease‐specific Z‐scores and longitudinal data in ALS. We evaluated the diagnostic and prognostic utility of neurofilaments and quantified the impact of ALS‐related factors and non‐ALS confounders.Neurofilaments showed high diagnostic and prognostic utility at the population level, with NfL superior to pNfH. The novel concept of a population‐based ALS Z‐score significantly improved the prognostic utility compared to absolute raw values. Both biomarkers increased more strongly with age in controls than in ALS, and age adjustment improved diagnostic accuracy. Our data show that disease progression rates, ALS phenotype, body mass index (BMI), and renal function need to be considered when interpreting neurofilament levels; longitudinal neurofilament levels were generally stable in individual patients, especially when adjusted for age and baseline levels.Population‐based assessment enhances the utility of particularly serum NfL as a diagnostic and prognostic biomarker in ALS and improves the translation of findings from controlled cohorts to real‐world populations. ANN NEUROL 2024 [ABSTRACT FROM AUTHOR]

The dual‐stratified pathway of endometrial carcinomas (ECs) has long been dominant. However, in 2013, The Cancer Genome Atlas (TCGA) defined four EC subgroups with distinctive prognoses. Inspired by TCGA, in 2018, the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) provided four pragmatic molecular classifiers to apply surrogate immunohistochemical markers to TCGA subgroup categorization. These trends prompted the revision of 2020 WHO Classification of Female Genital Tumors, 5th edition (2020 WHO classification), in which four molecular subtypes are recognized: POLE‐ultramutated; mismatch repair‐deficient; p53‐mutant; and no specific molecular profile. In the 2020 WHO classification, the diagnostic algorithm is characterized by prioritizing POLEmut over other molecular abnormalities. Following the 2020 WHO classification, Federation of International Gynecology and Obstetrics (FIGO) proposed a new staging system in 2023. The updated system focuses on diagnostic parameters, such as histological type and grade, lymphovascular space invasion, and molecular alterations. These new histomolecular diagnostic concepts of ECs are being accordingly introduced into the routine pathology practice. For the first time, the 2020 WHO classification includes mesonephric‐like adenocarcinoma (MLA) as a novel histological entity, mimicking the conventional mesonephric adenocarcinoma, but is considered of Müllerian ductal origin. [ABSTRACT FROM AUTHOR]

ABSTRACT Background Method Result Conclusion Salivary biomarkers play an important role in the preventive strategy for oral cancer detection at an early stage. The aim of this study was to carry out a comparative quantitative analysis of the research material on the topic in one established database, Scopus and another emerging database, Dimensions.An electronic search was performed in Scopus and Dimensions in April 2024 with the search subjects “Saliva,” “Biomarkers,” “Diagnosis,” and “Oral Cancer.” The retrieved data were analyzed using Biblioshiny for RStudio and MS Excel.The search yielded 229 and 158 documents in Scopus and Dimensions, respectively. The data were studied to understand the coverage, concentration, and diversion of research articles. The analysis revealed high singularity index for Scopus and low overlap percentage between the two databases. Scopus was found to have higher citation count per article, however, the citation correlation between Scopus and Dimensions was found to be strong. Author productivity was found to be low in both the databases.Scopus and Dimensions vary in their scope, volume of data, and coverage policies. Both the databases have complimentary coverage on salivary biomarkers for oral cancer diagnosis. However, Scopus has a greater number of articles, sources, and citations resulting in better coverage of the topic. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance This study was undertaken to investigate the potential of interictal electroencephalographic (EEG) findings and electrically stimulated seizures during stereo‐EEG (SEEG) as surrogate markers for the spontaneous seizure onset zone (spSOZ). We hypothesized that combining the localizing information of these markers would allow clinically meaningful estimation of the spSOZ.We included all patients (n = 63) who underwent SEEG between January 2013 and March 2020 at Helsinki University Hospital and had spontaneous seizures during the recording. We scored spikes, gamma activity, and background abnormality on each channel visually during a 12‐h epoch containing waking state and sleep. Based on semiology, we classified stimulated seizures as typical or atypical/unclassifiable and estimated the stimulated SOZ (stimSOZ) for typical seizures. To assess which markers increased the odds of channel inclusion in the spSOZ, we fitted mixed effects logistic regression models.A combined regression model including the stimSOZ and interictal markers scored during sleep performed better in estimating which channels were part of the spSOZ than models based on stimSOZ (p < .001) or interictal markers (p < .001) alone. Of the individual markers, the effect sizes were greatest for inclusion of a channel in the stimSOZ (odds ratio [OR] = 60, 95% confidence interval [CI] = 37–97, p < .001) and for continuous (OR = 25, 95% CI = 12–55, p < .001) and subcontinuous (OR = 36, 95% CI = 21–64, p < .001) interictal spiking. At the individual level, the model's accuracy to predict spSOZ inclusion varied markedly (median accuracy = 85.7, range = 54.4–100), which was not explained by etiology (p > .05).Compared to either marker alone, combining visually rated interictal SEEG markers and stimulated seizures improved prediction of which SEEG channels belonged to the spSOZ. Inclusion in the stimSOZ and continuous or subcontinuous spikes increased the odds of spSOZ inclusion the most. Future studies should investigate whether suboptimal sampling of the true epileptogenic zone can explain the model's poor performance in certain patients. [ABSTRACT FROM AUTHOR]