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This article introduces distance-based paper analytical devices (dPADs) integrated with molecularly imprinted polymers (MIPs) and carbon dots (CDs) for simultaneous quantification of cytokine biomarkers, namely C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-a), and interleukin-6 (IL-6) in human biological samples for diagnosis of cytokine syndrome. Using fluorescent CDs and MIP technology, the dPAD exhibits high selectivity and sensitivity. Detection is based on fluorescence quenching of CDs achieved through the interaction of the target analytes with the MIP layer on the paper substrate. Quantitative analysis is easily accomplished by measuring the distance length of quenched fluorescence with a traditional ruler and naked eye readout enabling rapid diagnosis of cytokine syndrome and the underlying infection. Our sensor demonstrated linear ranges of 2.50-24.0 pg mL-1 (R2 = 0.9974), 0.25-3.20 pg mL-1 (R2 = 0.9985), and 1.50-16.0 pg mL-1 (R2 = 0.9966) with detection limits (LODs) of 2.50, 0.25, and 1.50 pg mL-1 for CRP, TNF-a, and IL-6, respectively. This sensor also demonstrated remarkable selectivity compared to a sensor employing a non-imprinted polymer (NIP), and precision with the highest relative standard deviation (RSD) of 5.14%. The sensor is more accessible compared to prior methods relying on expensive reagents and instruments and complex fabrication methods. Furthermore, the assay provided notable accuracy for monitoring these biomarkers in various human samples with recovery percentages ranging between 99.22% and 103.58%. By integrating microfluidic systems, nanosensing, and MIPs technology, our developed dPADs hold significant potential as a cost-effective and user-friendly analytical method for point-of-care diagnostics (POC) of cytokine-related disorders. This concept can be further extended to developing diagnostic devices for other biomarkers. [ABSTRACT FROM AUTHOR]

Epidemiological studies have explored the relationship between allergic diseases and cancer risk or prognosis in AllergoOncology. Some studies suggest an inverse association, but uncertainties remain, including in IgE‐mediated diseases and glioma. Allergic disease stems from a Th2‐biased immune response to allergens in predisposed atopic individuals. Allergic disorders vary in phenotype, genotype and endotype, affecting their pathophysiology. Beyond clinical manifestation and commonly used clinical markers, there is ongoing research to identify novel biomarkers for allergy diagnosis, monitoring, severity assessment and treatment. Gliomas, the most common and diverse brain tumours, have in parallel undergone changes in classification over time, with specific molecular biomarkers defining glioma subtypes. Gliomas exhibit a complex tumour‐immune interphase and distinct immune microenvironment features. Immunotherapy and targeted therapy hold promise for primary brain tumour treatment, but require more specific and effective approaches. Animal studies indicate allergic airway inflammation may delay glioma progression. This collaborative European Academy of Allergy and Clinical Immunology (EAACI) and European Association of Neuro‐Oncology (EANO) Position Paper summarizes recent advances and emerging biomarkers for refined allergy and adult‐type diffuse glioma classification to inform future epidemiological and clinical studies. Future research is needed to enhance our understanding of immune–glioma interactions to ultimately improve patient prognosis and survival. [ABSTRACT FROM AUTHOR]

Immune-mediated cerebellar ataxias (IMCAs) have diverse etiologies. Patients with IMCAs develop cerebellar symptoms, characterized mainly by gait ataxia, showing an acute or subacute clinical course. We present a novel concept of latent autoimmune cerebellar ataxia (LACA), analogous to latent autoimmune diabetes in adults (LADA). LADA is a slowly progressive form of autoimmune diabetes where patients are often initially diagnosed with type 2 diabetes. The sole biomarker (serum anti-GAD antibody) is not always present or can fluctuate. However, the disease progresses to pancreatic beta-cell failure and insulin dependency within about 5 years. Due to the unclear autoimmune profile, clinicians often struggle to reach an early diagnosis during the period when insulin production is not severely compromised. LACA is also characterized by a slowly progressive course, lack of obvious autoimmune background, and difficulties in reaching a diagnosis in the absence of clear markers for IMCAs. The authors discuss two aspects of LACA: (1) the not manifestly evident autoimmunity and (2) the prodromal stage of IMCA's characterized by a period of partial neuronal dysfunction where non-specific symptoms may occur. In order to achieve an early intervention and prevent cell death in the cerebellum, identification of the time-window before irreversible neuronal loss is critical. LACA occurs during this time-window when possible preservation of neural plasticity exists. Efforts should be devoted to the early identification of biological, neurophysiological, neuropsychological, morphological (brain morphometry), and multimodal biomarkers allowing early diagnosis and therapeutic intervention and to avoid irreversible neuronal loss. [ABSTRACT FROM AUTHOR]

Background: Uterine fibroids are benign monoclonal tumors originating from the smooth muscle cells of the myometrium, constituting the most prevalent pathology within the female genital tract. Uterine sarcomas, although rare, still represent a diagnostic challenge and should be managed in centers with adequate expertise in gynecological oncology. Objectives: This article is aimed to summarize and discuss cutting-edge elements about the diagnosis and management of uterine fibroids and sarcomas. Methods: This paper is a report of the lectures presented in an expert meeting about uterine fibroids and sarcomas held in Palermo in February 2023. Outcome: Overall, the combination of novel molecular pathways may help combine biomarkers and expert ultrasound for the differential diagnosis of uterine fibroids and sarcomas. On the one hand, molecular and cellular maps of uterine fibroids and matched myometrium may enhance our understanding of tumor development compared to histologic analysis and whole tissue transcriptomics, and support the development of minimally invasive treatment strategies; on the other hand, ultrasound imaging allows in most of the cases a proper mapping the fibroids and to differentiate between benign and malignant lesions, which need appropriate management. Conclusions and Outlook: The choice of uterine fibroid management, including pharmacological approaches, surgical treatment, or other strategies, such as high-intensity focused ultrasound (HIFU), should be carefully considered, taking into account the characteristics of the patient and reproductive prognosis. [ABSTRACT FROM AUTHOR]

Background: The Taiwan Oncology Society (TOS) and the Taiwan Society of Pathology (TSP) have collaborated to present a joint position paper on the molecular tumor boards (MTBs) within the medical institutions of Taiwan. Materials and Methods: To raise awareness of MTBs among health-care professionals, policymakers, and the public, a total of 20 experts from TOS and TSP formulated a joint consensus statement through a voting process. Results: The joint statement proposes key recommendations: (1) MTB discussions encompass diverse molecular analyses including next-generation sequencing (NGS), RNA sequencing, whole-exon sequencing, and whole-genomic sequencing addressing relevant genomic changes, tumor mutation burden, microsatellite instability, and specific biomarkers for certain cancers. (2) MTB meetings should involve multidisciplinary participants who receive regular updates on NGS-related clinical trials. (3) Prioritize discussing cases with unique clinical needs, gene alterations lacking treatments, untreatable neoplasms, or oncogenes unresponsive to targeted therapies. (4) Base MTB discussions on comprehensive patient data, including genetics, pathology, timing of specimen collection, and NGS outcomes. (5) MTBs offer treatment recommendations: standard therapies, off-label use, clinical trials, genetic counseling, and multidisciplinary reviews. (6) MTB effectiveness can be gauged by member composition, case reviews, treatment suggestions, and patient outcomes. Encourage government incentives for MTB engagement. Conclusion: The primary aim of this initiative is to promote the advancement of precision oncology in Taiwan. [ABSTRACT FROM AUTHOR]

Simple Summary: Blood clots are formed when blood vessels are injured. They help stop bleeding and heal wounds, but can also cause serious problems if they block blood flow or break off and travel to other organs. This study investigates how blood clots differ in people with cancer compared to healthy or non-cancerous individuals. This study found that cancer patients have higher levels of histones in their blood, which make their clots stiffer and resistant to lysis. Further, clots formed in cancer patients have higher viscoelastic properties, and hence are harder to break down. These findings suggest that cancer patients have abnormal clotting properties that may increase their risk of developing thrombosis, and evaluating these properties can be helpful in detecting cancer. Background: Blood viscoelasticity and plasma protein levels can play an important role in the diagnosis and prognosis of cancer. However, the role of histones and DNA in modulating blood clot properties remains to be investigated. This study investigates the differences in blood viscoelasticity and plasma protein levels among cancer patients, individuals with other diseases, and healthy individuals. Methods: Blood samples were collected from 101 participants, including 45 cancer patients, 22 healthy individuals, and 34 individuals with other diseases. Rheological properties of clots formed in vitro by reconstituted elements of fibrinogen or plasma were analyzed with an Anton Paar Rheometer, USA. Plasma protein levels of D-dimer, TPA, EPCR, fibrinogen, and histone H3 were measured through ELISA. Blood clots were formed with or without DNA and histones (H3) by adding thrombin and calcium to plasma samples, and were evaluated for viscoelasticity, permeability, and degradation. Results: Cancer patients show higher blood viscoelasticity and plasma D-dimer levels compared to healthy individuals and individuals with other diseases. Our in vitro analysis showed that the addition of histone to the plasma results in a significant decrease in viscoelasticity and mean fiber thickness of the clot formed thereafter. In parallel studies, using plasma from patients, DNA and histones were detected in fibrin clots and were associated with less degradation by t-PA. Moreover, our results show that the presence of DNA and histones not only increases clots' permeability, but also makes them more prone to degradation. Conclusions: Plasma histones and DNA affect the structure of the clot formed and induce defective fibrinolysis. Moreover, the increased viscoelastic properties of plasma from cancer patients can be used as potential biomarkers in cancer prognosis. [ABSTRACT FROM AUTHOR]

Human sweat can be collected non-invasively with low infectivity; however, its application as a determination method has been challenged due to the presence of trace amounts of chiral metabolites. Moreover, its application as a biological fluid for disease diagnosis has not been previously reported. In this study, the human dried sweat spot paper (DSSP) method was proposed for the derivatization of a novel mass spectrometric chiral probe, N -[1-Oxo-5-(triphenylphosphonium) pentyl]-(S)-3-aminopyrrolidine (OTPA), determination and resolution of DL-lactic acid (DL-LA) enantiomers in human elbow sweat. The methodological validation revealed the resolution (Rs) as 1.78, the limit of detection (S/N = 3) as 20.83 fmol, good linearity (R2 ≥ 0.9996), and the intra-day and intra-day stability with RSD ranging from 0.53 to 10.85 %, while the average recovery rate of D-LA and L-LA were 104.00 % ± 4.68 % and 107.41 % ± 8.34 %, respectively, with high accuracy. In addition, the method was applied for the determination of DL-LA in the sweat on elbow of 10 healthy volunteers and 30 diabetic patients. The results demonstrated that the D/L ratio and L/D ratio were significantly different (p < 0.0001). In addition, a moderate positive linear correlation between the D/L-LA ratio in human sweat and fasting blood glucose level (r = 0.7744, p < 0.0001) was observed, thereby suggesting that the D/L ratio of lactate in human sweat correlate the glucose level in human fasting blood. The D/L lactate ratio in human sweat could be used as a potential biomarker for diabetes screening. The method can be used to screen for diabetes by providing a dry sweat paper to test equipment and has the potential to be a non-invasive early-warning diagnostic tool for diabetes. [Display omitted] • A dried sweat spot paper method for estimating DL-LA enantiomers in human sweat. • The D/L and L/D ratios of LA in diabetic patient sweat are significantly different. • The D/L-LA ratio in human sweat is positively correlated with fasting blood glucose levels. • DSSP combined with UHPLC-MS/MS accurately quantified D/L-LA ratio is a non-invasive preventive method for screening for diabetes. [ABSTRACT FROM AUTHOR]

Schematic diagram depicting the synthesis process of the intelligent paper-based biosensor and its colorimetric detection application for biomarkers in urine. (FP: filter paper; CPBA: Carboxyphenylboric acid; HRP: horseradish peroxidase; TMB: 3,3′,5,5′-tetramethylbenzidine; GLU: glusose; UA: uric acid; SAR: sarcosine; GOx: glucose oxidase; UOx: urate oxidase; SOx: urate oxidase.) [Display omitted] • A green, low-cost, portable and visual intelligent paper-based biosensor was created. • This sensor immobilized HRP in horseradish by a borate-modified filter paper. • This sensor can detect many substances simultaneously and improve detection efficiency. • This sensor boasts the advantages of superior sensitivity, stability and selectivity. In the increasing demand for real-time testing, the imperative for a straightforward, rapid, portable, and effective biosensor is evident. In this study, an intelligent paper-based biosensor was developed, employing cost-effective and readily available filter paper as a matrix to prepare boronate affinity paper-based materials. The immobilization of horseradish peroxidase (HRP) from crude horseradish extract onto the material surface was realized. Ultimately, a cold assembly technique was employed to construct this intelligent paper-based biosensor, which combined with a smartphone APP, facilitated the easy, accurate, and simultaneous detection of the content of glucose (GLU), uric acid (UA), and sarcosine (SAR) in urine, significantly enhancing the convenience and practicality of real-time monitoring. Additionally, UV spectroscopy served as an auxiliary method to affirm the reliability of the detection outcomes. For the detection of GLU, UA, and SAR, the biosensor exhibited linear ranges of 2–200, 2–500, and 2–500 µmol L–1, respectively, with detection limits (LODs) of 1 µmol L–1 for all analytes. In practical urine sample analysis, the recovery rates of GLU, UA, and SAR detected by the intelligent paper-based biosensors were within a reasonable range, with relative standard deviations below 3.5 %. This fully demonstrates the high accuracy and reliability of the intelligent paper-based biosensor. The development of this low-cost, portable biosensor provides a new method for the detection of biomarkers related to H 2 O 2. [ABSTRACT FROM AUTHOR]

A novel CuS grafted PEDOT:PSS conducting paper-based electrochemical immunosensor has been successfully fabricated for the detection of EpCAM antigen. Electrical conductivity is further improved by doping the CuS@PEDOT:PSS/WP electrode with different organic solvents such as N,N-dimethyl formamide (DMF), N,N-dimethyl acetamide (DMA), ethylene glycol (EG) and dimetyl sulfoxide (DMSO). It is observed that DMSO doped conducting paper shows the highest conductivity (6.1 × 10−2 S/cm) among all these solvents. This low cost, biodegradable electrochemical paper-based immunosensor (BSA/anti-EpCAM/EP) possesses a broad linear range from 0.01 pg/mL to 1000 ng/mL for EpCAM antigen detection. The immunosensor is found to have high sensitivity of 104.31 μA pg−1 mL. This conducting paper based immunosensor is further used to detect EpCAM antigen in human serum samples, thereby confirming a cost effective clinical tool over other costly conventional techniques. • An electrochemical paper-based immunosensor has been designed using CuS and PEDOT:PSS. • This low cost and flexible platform may be a promising candidate over other costly conventional electrodes. • It exhibits high sensitivity of 104.31 μA pg−1 mL in broad range of 0.01 pg/mL to 1000 ng/mL, for EpCAM detection. • The clinical applicability and validity has been checked with human serum sample. [ABSTRACT FROM AUTHOR]

Development of the portable device is significant for sensitive and rapid detection of an anthrax biomarker dipicolinic acid (DPA), existing in the B. anthracis. In this work, a novel HAp:Tb-EDTA paper-based ratiometric fluorescent sensor was obtained by a simple one-pot method for rapid and sensitive DPA detection. With the increased DPA concentration, the luminescence intensity of HAp (hydroxyapatite) remained constant, and thus applied as the stable reference signal, while the luminescence signal of Tb3+-EDTA was significantly enhanced due to the antenna effect. Therefore, the HAp:Tb-EDTA paper-based sensor was endowed with self-calibrated and ratiometric fluorescent detection performance for DPA. The proposed sensor showed excellent detection performance with a detection limit as low as 10.8 nM in the linear range of 0.5–30 μM. After combination with a smartphone, rapid visual and fluorescent detection of DPA was achieved. The proposed sensor was successfully applied to detect DPA from B. subtilis spore real samples, showing the application prospects of the paper-based sensors and opening a new horizon to develop novel paper-based point-of-care testing (POCT) devices. A sensing platform was constructed by a HAp:Tb-EDTA paper-based ratiometric fluorescent probe prepared by a one-pot method and combined with a smartphone. The sensing platform has good stability and can be used for sensitive detection of DPA released from Bacillus subtilis spores. [Display omitted] • A novel HAp:Tb-EDTA paper-based ratiometric fluorescent probe was facilely constructed. • The Tb3+-EDTA recognition unit uniformly distributed on HAp with a paper-like structure, making it superior to that based on commercial test papers. • A portable platform was constructed through combining with smartphones for real samples detection, showing widespread application prospects. • Opening a new horizon to develop novel paper-based point-of-care testing (POCT) devices. [ABSTRACT FROM AUTHOR]

Paper-based analytical devices (PADs), thanks to the versatility, cheapness, availability, biodegradability, and porosity of paper, have emerged as flexible sensing platforms for determining various analytes. However, lack of selectivity can be a problem in complex analysis conditions and samples. To improve the selectivity and specificity of PADs, they can be integrated with molecularly imprinted polymers (MIPs). The high selectivity of the sensor is the essential feature for biomarker analysis because the reliable and accurate determination of biomarkers provides valuable information about various diseases, especially cancer. Therefore, MIP-PAD systems offer a good option for biomarker analysis. This way, it is possible to achieve point-of-care tests, early diagnosis, and affordability. This review points out the significant processes of MIP-PAD fabrication and characterization (paper selection and fabrication, synthesis of MIP). The most recent applications of MIP-PADs for biological samples are explained and discussed in detail. Lastly, the commercialization of MIP-PADs is evaluated. This study is the first in the literature to assess MIP-PADs for biomarkers analysis. • The evaluation of MIP-PADs for biomarker detection. • Comprehensive research for fabrication and characterization of MIP-PADs. • The successful sensor applications of MIP-PADs for biological samples. • The place of MIP-PADs in commercial applications. [ABSTRACT FROM AUTHOR]

• IFCC position paper about CDT outlining caveats, key points, and recommendations. • Alcohol intake versus CDT is discussed as well as the cut-off and expected range. • Comparison studies using inadequate study populations will lead to wrong outcome. • Standardisation has led to test accuracy improvements in national EQAS. Carbohydrate deficient transferrin (CDT) is a biomarker for excessive alcohol consumption utilized in clinical and forensic medicine and workplace testing. Previously, many different analytical methods for CDT were used and the measurand varied considerably, making direct comparison of test results difficult. To end this confusion, the IFCC established a working group on CDT standardisation (WG-CDT) which completed its tasks in 2017. This IFCC position paper by the WG-CDT summarizes state of the art information about the measurand and the analytical methods and gives concise recommendations for its utilization. The results achieved by the CDT standardisation process led to accuracy improvements in national external quality assessment schemes over the years. A brief review of ROC based comparison studies with the traditional biomarkers (GGT, MCV, ALT and AST) discusses the bias resulting from inadequate study populations. In large groups of the general population the superior diagnostic performance of CDT is confirmed. The relationship between alcohol intake versus resulting CDT is discussed as well as the cutoff and measurement uncertainty. Concerning the application in practice, potential pitfalls are considered and recommendations handling both analytical and preanalytical caveats are given. Finally, some examples of serious misunderstandings in publications about CDT are addressed. [ABSTRACT FROM AUTHOR]

The use of microfluidic paper-based analytical devices (μPADs) for aiding medical diagnosis is a growing trend in the literature mainly due to their low cost, easy use, simple manufacturing, and great potential for application in low-resource settings. Many important biomarkers (proteins, ions, lipids, hormones, DNA, RNA, drugs, whole cells, and more) and biofluids are available for precise detection and diagnosis. We have reviewed the advances μPADs in medical diagnostics have achieved in the last few years, focusing on the most common human biofluids (whole blood/plasma, sweat, urine, tears, and saliva). The challenges of detecting specific biomarkers in each sample are discussed, along with innovative techniques that overcome such limitations. Finally, the difficulties of commercializing μPADs are considered, and future trends are presented, including wearable devices and integrating multiple steps in a single platform. • μPADs can be applied for simple and low-cost diagnosis in low-resource settings. • The challenges of applying μPADs to human biofluids are analyzed. • Recent advancements to overcome specific drawbacks for each fluid are discussed. • Difficulties in commercializing μPADs and future tendencies are presented. [ABSTRACT FROM AUTHOR]

The accurate detection of glucose and cholesterol plays a pivotal role in disease diagnosis and home care. To this end, biochemical analyzers have become extensively utilized tools for measuring disease biomarkers. Nonetheless, their poor portability and high cost have restricted their accessibility, limiting their use to laboratory settings and hindering the adoption of point-of-care testing (POCT). In contrast, the emergence of portable and affordable paper-based testing platform has revolutionized diagnostic testing by providing distance signals, enhancing intuitiveness and visual accessibility. Consequently, these platforms have become increasingly suitable for POCT. We have developed a POCT platform that integrated AuNS@Ag, stimulus-responsive hydrogel and test strips, enabling visual distance reading of glucose. The silver-coated AuNS and enzyme were encapsulated within a temperature-responsive N-isopropylacrylamide-acrylamide (NIPAM-AcAm) hydrogel to act as target recognition and reaction units respectively. Glucose can diffuse freely within the hydrogel porous matrix, thereby instigating enzyme-catalyzed reaction that induce alterations in the photothermal effect of the system. This dynamic process ensures efficient and responsive modulation of the system's photothermal properties. By ingeniously capturing distance signals induced by the photothermal effect-mediated water release the visualization and quantification of target substances are achieved, with a linear range spanning from 0 to 30 mM. The consistency between distance-based POCT platform and commercial blood glucose meter demonstrates that the platform provides a portable, affordable and reliable method for visual reading biomarkers. The proposed strategy enables direct, visual quantitative analysis of the target without the need for additional analytical instruments. Particularly, this method holds significant promise as an efficient platform for cholesterol and other disease markers measurement. [Display omitted] • A POCT platform was constructed for visible distance-readout of disease marker. • AuNS@Ag was employed as target recognition unit for photothermal signal output. • Temperature-responsive hydrogel as carrier and framework for the platform. [ABSTRACT FROM AUTHOR]

Glucose is the main source of energy for the human brain. This paper presents a non-invasive technique to study metabolic changes caused by glucose in human brain cell lines. In this paper we present the spectroscopic characterization of human normal brain (NHA; astrocytes) and human cancer brain (CRL-1718; astrocytoma and U-87 MG; glioblastoma) control cell lines and cell lines upon supplementation with glucose. Based on Raman techniques we have identified biomarkers that can monitor metabolic changes in lipid droplets, mitochondria and nucleus caused by glucose. We have studied the vibrations at 750 cm−1, 1444 cm−1, 1584 cm−1 and 1656 cm−1 as a function of malignancy grade. We have compared the concentration of cytochrome, lipids and proteins in the grade of cancer aggressiveness in normal and cancer human brain cell lines. Chemometric analysis has shown that control normal, control cancer brain cell lines and normal and cancer cell lines after supplementation with glucose can be distinguished based on their unique vibrational properties. PLSDA (Partial Least Squares Discriminant Analysis) and ANOVA tests have confirmed the main role of cytochromes, proteins and lipids in differentiation of control human brain cells and cells upon supplementation with glucose. We have shown that Raman techniques combined with chemometric analysis provide additional insight to monitor the biology of astrocytes, astrocytoma and glioblastoma after glucose supplementation. [ABSTRACT FROM AUTHOR]

Simple Summary: Achieving improved rates of overall survival remains a significant challenge in advanced-stage ovarian cancer; even if complete debulking is achieved, certain patients report poor results in terms of survival. Therefore, the aim of this paper is to investigate new prognostic markers that could point out which cases could benefit most from debulking surgery and which ones should be rather submitted to neoadjuvant therapies followed by debulking surgery. Background: Despite improving surgical techniques and achieving more often complete debulking procedures, certain patients with advanced-stage ovarian cancer still have a very poor prognosis. The aim of the current paper is to investigate whether inflammatory and nutritional status can predict the long-term outcomes of ovarian cancer patients. Methods: A retrospective analysis of 57 cases diagnosed with advanced-stage ovarian cancer submitted to surgery as first intent therapy was carried out. In all cases, the preoperative status was determined by calculating the CRP/albumin ratio, as well as the Glasgow score, the modified Glasgow score and the prognostic nutritional index. Results: Patients presenting higher values of the CRP/albumin ratio, with a higher Glasgow score, modified Glasgow score and prognostic nutritional index (PNI), were more frequently associated with incomplete debulking surgery, a higher peritoneal carcinomatosis index and poorer overall survival (20 months versus 9 months for the CRP/albumin ratio p = 0.011, 42 versus 27 versus 12 months for the Glasgow score p = 0.042, 50 versus 19 versus 12 months for the modified Glasgow score, p = 0.001, and 54 months versus 21 months, p = 0.011 for the prognostic nutritional index). Conclusions: A strong relationship between the nutritional and inflammatory status in advanced-stage ovarian cancer seems to exist. [ABSTRACT FROM AUTHOR]

General physicians misclassify depression in more than half of the cases. Researchers have explored the feasibility of leveraging passively collected data points, also called digital biomarkers, to provide more granular understanding of depression phenotypes as well as a more objective assessment of disease. This paper provides a systematic review following the PRISMA guidelines (Page et al., 2021) to understand which digital biomarkers might be relevant for passive screening of depression. Pubmed and PsycInfo were systematically searched for studies published from 2019 to early 2024, resulting in 161 records assessed for eligibility. Excluded were intervention studies, studies focusing on a different disease or those with a lack of passive data collection. 74 studies remained for a quality assessment, after which 27 studies were included. The review shows that depressed participants' real-life behavior such as reduced communication with others can be tracked by passive data. Machine learning models for the classification of depression have shown accuracies up to 0.98, surpassing the quality of many standardized assessment methods. Inconsistency of outcome reporting of current studies does not allow for drawing statistical conclusions regarding effectiveness of individual included features. The Covid-19 pandemic might have impacted the ongoing studies between 2020 and 2022. While digital biomarkers allow real-life tracking of participant's behavior and symptoms, further work is required to align the feature engineering of digital biomarkers. With shown high accuracies of assessments, connecting digital biomarkers with clinical practice can be a promising method of detecting symptoms of depression automatically. • This paper provides a PRISMA-guided systematic review of studies (2019-2024), showing model accuracy ranges of 0.52-0.98. • The review summarises constructs related to mood, location, smartphone use, communication, sleep quality and heart rate. • To be integrated into clinical practice, captured data needs to be reduced to the most relevant features. [ABSTRACT FROM AUTHOR]

2,6-pyridine dicarboxylic acid (DPA) is an exceptional biomarker of notorious anthrax spores. Therefore, the rapid, sensitive, and selective quantitative detection of DPA is extremely significant and urgent. This paper reports a Zn(II) metal–organic framework with the formula of {[Zn6(NDA)6(DPBT)3] 2H2O·3DMF}n (MOF-1), which consists of 2,6-naphthalenedicarboxylic acid (2,6-NDA), 4,7-di(4-pyridyl)-2,1,3-benzothiadiazole (DPBT), and Zn(II) ions. Structural analysis indicated that MOF-1 is a three-dimensional (3D) network which crystallized in the monoclinic system with the C2/c space group, revealing high pH, solvent, and thermal stability. Luminescence sensing studies demonstrated that MOF-1 had the potential to be a highly selective, sensitive, and recyclable fluorescence sensor for the identification of DPA. Furthermore, fluorescent test paper was made to detect DPA promptly with color changes. The enhancement mechanism was established by the hydrogen-bonding interaction and photoinduced electron transfer transition between MOF-1 and DPA molecules. [ABSTRACT FROM AUTHOR]

Introduction: Personalised prevention aims to delay or avoid disease occurrence, progression, and recurrence of disease through the adoption of targeted interventions that consider the individual biological, including genetic data, environmental and behavioural characteristics, as well as the socio-cultural context. This protocol summarises the main features of a rapid scoping review to show the research landscape on biomarkers or a combination of biomarkers that may help to better identify subgroups of individuals with different risks of developing specific diseases in which specific preventive strategies could have an impact on clinical outcomes. This review is part of the "Personalised Prevention Roadmap for the future HEalThcare" (PROPHET) project, which seeks to highlight the gaps in current personalised preventive approaches, in order to develop a Strategic Research and Innovation Agenda for the European Union. Objective: To systematically map and review the evidence of biomarkers that are available or under development in cancer, cardiovascular and neurodegenerative diseases that are or can be used for personalised prevention in the general population, in clinical or public health settings. Methods: Three rapid scoping reviews are being conducted in parallel (February–June 2023), based on a common framework with some adjustments to suit each specific condition (cancer, cardiovascular or neurodegenerative diseases). Medline and Embase will be searched to identify publications between 2020 and 2023. To shorten the time frames, 10% of the papers will undergo screening by two reviewers and only English-language papers will be considered. The following information will be extracted by two reviewers from all the publications selected for inclusion: source type, citation details, country, inclusion/exclusion criteria (population, concept, context, type of evidence source), study methods, and key findings relevant to the review question/s. The selection criteria and the extraction sheet will be pre-tested. Relevant biomarkers for risk prediction and stratification will be recorded. Results will be presented graphically using an evidence map. Inclusion criteria: Population: general adult populations or adults from specific pre-defined high-risk subgroups; concept: all studies focusing on molecular, cellular, physiological, or imaging biomarkers used for individualised primary or secondary prevention of the diseases of interest; context: clinical or public health settings. Systematic review registration: https://doi.org/10.17605/OSF.IO/7JRWD (OSF registration DOI). [ABSTRACT FROM AUTHOR]

Background: The identification of biomarkers for the early diagnosis of Alzheimer's disease (AD) is a crucial goal of the current research. Blood biomarkers are less invasive, easier to obtain and achievable by a cheaper means than those on cerebrospinal fluid (CSF) and significantly more economic than functional neuroimaging investigations; thus, a great interest is focused on blood isoforms of the phosphorylated Tau protein (pTau), indicators of ongoing tau pathology (i.e. neurofibrillary tangles, NFTs, an AD neuropathological hallmark) in the central nervous system (CNS). However, current data often highlight discordant results about the ability of blood pTau to predict CSF status. Objective: We aim to synthesise the studies that compared pTau levels on CSF and blood to assess their correlation in AD continuum. Methods: We performed a narrative literature review using, first, MEDLINE (via PubMed) by means of MeSH terms, and then, we expanded the reults by means of Scopus and Web of Sciences to be as inclusive as possible. Finally, we added work following an expert opinion. Only papers presenting original data on pTau values on both blood and CSF were included. Results: The 33 included studies show an extreme heterogeneity in terms of pTau isoform (pTau181, 217 and 231), laboratory methods, diagnostic criteria and choice of comparison groups. Most studies evaluated plasma pTau181, while data on other isoforms and serum are scarcer. Discussion: Most papers identify a correlation between CSF and blood measurements. Furthermore, even when not specified, it is often possible to show an increase in blood pTau values as AD-related damage progresses in the AD continuum and higher values in AD than in other neurodegenerative diseases. Notably, plasma pTau231 seems the first biomarker to look for in the earliest and pre-clinical stages, quickly followed by pTau217 and, finally, by pTau181. Conclusions: Our results encourage the use of blood pTau for the early identification of patients with AD continuum. [ABSTRACT FROM AUTHOR]

Intermediate filaments are one of three polymeric structures that form the cytoskeleton of epithelial cells. In the epithelium, these filaments are made up of a variety of keratin proteins. Intermediate filaments complete a wide range of functions in keratinocytes, including maintaining cell structure, cell growth, cell proliferation, cell migration, and more. Given that these functions are intimately associated with the carcinogenic process, and that hyperkeratinization is a quintessential feature of oral leukoplakias, the utility of keratins in oral leukoplakia is yet to be fully explored. This scoping review aims to outline the current knowledge founded on original studies on human tissues regarding the expression and utility of keratins as diagnostic, prognostic, and predictive biomarkers in oral leukoplakias. After using a search strategy developed for several scientific databases, namely, PubMed, Scopus, Web of Science, and OVID, 42 papers met the inclusion and exclusion criteria. One more article was added when it was identified through manually searching the list of references. The included papers were published between 1989 and 2024. Keratins 1–20 were investigated in the 43 included studies, and their expression was assessed in oral leukoplakia and dysplasia cases. Only five studies investigated the prognostic role of keratins in relation to malignant transformation. No studies evaluated keratins as a diagnostic adjunct or predictive tool. Evidence supports the idea that dysplasia disrupts the terminal differentiation pathway of primary keratins. Gain of keratin 17 expression and loss of keratin 13 were significantly observed in differentiated epithelial dysplasia. Also, the keratin 19 extension into suprabasal cells has been associated with the evolving features of dysplasia. The loss of keratin1/keratin 10 has been significantly associated with high-grade dysplasia. The prognostic value of cytokeratins has shown conflicting results, and further studies are required to ascertain their role in predicting the malignant transformation of oral leukoplakia. [ABSTRACT FROM AUTHOR]

Simple Summary: Immune checkpoint inhibitors have revolutionized cancer therapy and improved clinical outcomes. Immunotherapy is now increasingly combined with chemotherapy and other conventional treatments, such as radiation therapy, as part of the multimodal treatment of earlier-stage cancers. Although generally well tolerated and capable of inducing long-lasting responses, immunotherapy for thymic epithelial tumors can be challenging due to defects in immune self-tolerance, which increase the risk of immune-mediated toxicity. In order to improve the safety of immunotherapy and maximize clinical benefit in patients with thymic cancers, there is a pressing need to identify potential biomarkers of response and toxicity for this patient population. In this paper, we review the current role of immunotherapy for thymic cancers and discuss future applications across the spectrum of stage and histology of these diseases. Thymic epithelial tumors are a histologically diverse group of cancers arising from the epithelial compartment of the thymus. These tumors are characterized by a low tumor mutation burden, a lack of actionable genomic changes, and, especially with thymomas, defects in immune tolerance. Surgery is the mainstay of the management of resectable disease, whereas advanced, unresectable tumors are treated with platinum-based chemotherapy. Disease recurrence can occur months to years after frontline treatment. Although several options are available for conventional treatment of recurrent thymic tumors, response rates are generally low, and treatment-related toxicity can affect quality of life. A subset of patients benefit from biologic therapies, but there remains an unmet need for the development of new treatments. Immune checkpoint inhibitors are safe, clinically active, and have contributed to an improvement in survival for patients with a wide variety of cancers. However, the application of these revolutionary treatments for thymic cancers is limited to their use for the management of recurrent thymic carcinoma because of the risk of immune toxicity. In this paper, we review the current uses of immunotherapy for the management of thymic epithelial tumors and highlight potential strategies to improve safety and broaden the application of these treatments for patients with thymic cancers. [ABSTRACT FROM AUTHOR]

Purpose: This scoping review summarizes the applications of artificial intelligence (AI) and bioinformatics methodologies in analysis of ocular biofluid markers. The secondary objective was to explore supervised and unsupervised AI techniques and their predictive accuracies. We also evaluate the integration of bioinformatics with AI tools. Methods: This scoping review was conducted across five electronic databases including EMBASE, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics were included. Results: A total of 10,262 articles were retrieved from all databases and 177 studies met the inclusion criteria. The most commonly studied ocular diseases were diabetic eye diseases, with 50 papers (28%), while glaucoma was explored in 25 studies (14%), age-related macular degeneration in 20 (11%), dry eye disease in 10 (6%), and uveitis in 9 (5%). Supervised learning was used in 91 papers (51%), unsupervised AI in 83 (46%), and bioinformatics in 85 (48%). Ninety-eight papers (55%) used more than one class of AI (e.g. > 1 of supervised, unsupervised, bioinformatics, or statistical techniques), while 79 (45%) used only one. Supervised learning techniques were often used to predict disease status or prognosis, and demonstrated strong accuracy. Unsupervised AI algorithms were used to bolster the accuracy of other algorithms, identify molecularly distinct subgroups, or cluster cases into distinct subgroups that are useful for prediction of the disease course. Finally, bioinformatic tools were used to translate complex biomarker profiles or findings into interpretable data. Conclusion: AI analysis of biofluid markers displayed diagnostic accuracy, provided insight into mechanisms of molecular etiologies, and had the ability to provide individualized targeted therapeutic treatment for patients. Given the progression of AI towards use in both research and the clinic, ophthalmologists should be broadly aware of the commonly used algorithms and their applications. Future research may be aimed at validating algorithms and integrating them in clinical practice. [ABSTRACT FROM AUTHOR]

Metal–organic frameworks (MOFs) are actively explored as sensing materials owing to their high porosity, substantial surface area, and structural diversity, providing diverse chemical and physical properties. Their fluorescent characteristics are pivotal, enabling MOFs to function as probes for detecting specific target molecules. Unlike conventional disease diagnosis methods such as biopsies or blood collection, the detection of pathogenic biomarkers in human urine is conventional and less risky. While mass spectroscopy identifies proteins and metabolites in urine at high costs, MOF test papers offer a convenient solution. These papers confirm the existence of the target molecules through naked‐eye observation upon UV light irradiation at specific wavelengths. MOF‐based fluorescent probes facilitate disease diagnosis, including pheochromocytoma, toluene exposure, vitamin deficiencies, gout, hyperuricemia, cancers, body disorders, and teratogenicity, with low detection limits. This review delves into recent developments in MOF fluorescent probes, covering synthesis, emission spectra, and sensing mechanisms. [ABSTRACT FROM AUTHOR]

This report describes the knowledge mobilization and translation outcomes of the Canadian-funded portion of a large, international project called the Food Biomarker Alliance (FoodBAll), which ran from 2015 to 2019. This remarkably successful project led to a large number of important findings, outputs, and impacts. In particular, FoodBAll unequivocally demonstrated that metabolomics could be used to not only discover biomarkers of food intake (BFIs), but also to measure diet in a more objective manner. FoodBAll also created standards for assessing and validating BFIs, papers and databases describing BFIs, and kits for measuring BFIs and it laid the groundwork for many global studies exploring food composition and precision nutrition. [ABSTRACT FROM AUTHOR]

Articular cartilage damage and degeneration are among hallmark manifestations of joint injuries and arthritis, classically osteoarthritis. Cartilage compositional MRI (Cart-C MRI), a quantitative technique, which aims to detect early-stage cartilage matrix changes that precede macroscopic alterations, began development in the 1990s. However, despite the significant advancements over the past three decades, Cart-C MRI remains predominantly a research tool, hindered by various technical and clinical hurdles. This paper will review the technical evolution of Cart-C MRI, delve into its clinical applications, and conclude by identifying the existing gaps and challenges that need to be addressed to enable even broader clinical application of Cart-C MRI. [ABSTRACT FROM AUTHOR]

Translational research is key in advancing the diagnosis and therapy of systemic amyloidoses. This paper summarises our presentations at the ISA Workshop on Translation in Systemic Amyloidoses held in Athens on September 25-26, 2023. The critical advances made by the pioneers in the field are reviewed, with particular attention to the discoveries and developments of utmost importance to our understanding of what amyloid is and how the substance affects functions. Examples of translational research regarding the mechanisms of cardiac damage in light chain amyloidosis, the role of biomarkers in improving our understanding of the biology of the disease and patients' management, and the molecular mechanisms involved in the cytotoxicity are described. Advances in basic research continue to open new therapeutic avenues. [ABSTRACT FROM AUTHOR]

Since the completion of the Human Genome Project (HGP), biomedical sciences have moved away from a gene-centred view and towards a multi-factorial one in which environment, broadly speaking, plays a central role in the determination of human health and disease. Environmental exposures have been shown to be highly prevalent in disease causation. They are considered as complementary to genetic factors in the etiology of diseases, hence the introduction of the concept of the "exposome" as encompassing the totality of human environmental exposures, from conception onwards (Wild in Cancer Epidemiol Biomark Prev 14:1847–1850, 2005), and the launch of the Human Exposome Project (HEP) which aims to complement the HGP. At first sight, and seen as complementary to the genome, the exposome could thus appear as contributing to the rise of novel postgenomic deterministic narratives which place the environment at their core. Is this really the case? If so, what sort of determinism is at work in exposomics research? Is it a case of environmental determinism, and if so, in what sense? Or is it a new sort of deterministic view? In this paper, we first show that causal narratives in exposomics are still very similar to gene-centred deterministic narratives. They correspond to a form of Laplacian determinism and, above all, to what Claude Bernard called the "determinism of a phenomenon". Second, we introduce the notion of "reversed heuristic determinism" to characterize the specific deterministic narratives present in exposomics. Indeed, the accepted sorts of external environmental exposures conceived as being at the origins of diseases are determined, methodologically speaking, by their identifiable internal and biological markers. We conclude by highlighting the most relevant implications of the presence of this heuristic determinism in exposomics research. [ABSTRACT FROM AUTHOR]

Colorimetric sensing offers instant reporting via visible signals. Versus labor-intensive and instrument-dependent detection methods, colorimetric sensors present advantages including short acquisition time, high throughput screening, low cost, portability, and a user-friendly approach. These advantages have driven substantial growth in colorimetric sensors, particularly in point-of-care (POC) diagnostics. Rapid progress in nanotechnology, materials science, microfluidics technology, biomarker discovery, digital technology, and signal pattern analysis has led to a variety of colorimetric reagents and detection mechanisms, which are fundamental to advance colorimetric sensing applications. This review first summarizes the basic components (e.g., color reagents, recognition interactions, and sampling procedures) in the design of a colorimetric sensing system. It then presents the rationale design and typical examples of POC devices, e.g., lateral flow devices, microfluidic paper-based analytical devices, and wearable sensing devices. Two highlighted colorimetric formats are discussed: combinational and activatable systems based on the sensor-array and lock-and-key mechanisms, respectively. Case discussions in colorimetric assays are organized by the analyte identities. Finally, the review presents challenges and perspectives for the design and development of colorimetric detection schemes as well as applications. The goal of this review is to provide a foundational resource for developing colorimetric systems and underscoring the colorants and mechanisms that facilitate the continuing evolution of POC sensors. [ABSTRACT FROM AUTHOR]

Simple Summary: Proteomics can be very useful in identifying proteins, which helps find potential markers for diseases. Managing endometrial cancer can be difficult and finding reliable markers can contribute to an early diagnosis, to manage its evolution, and even predict the response to treatment. This paper reviews the current research on the proteins involved in endometrial cancer. Most studies used tissue, serum, and plasma samples and found potential diagnostic and prognostic markers. Eight studies were examined closely, with three showing strong similarities, sharing forty-five proteins. This review also identified the 10 most commonly reported proteins in these studies. While proteomics shows promise in finding diagnostic and prognostic markers for endometrial cancer, there is still a need for more research on new therapeutic targets. Proteomics can be a robust tool in protein identification and regulation, allowing the discovery of potential biomarkers. In clinical practice, the management of endometrial cancer can be challenging. Thus, identifying promising markers could be beneficial, helping both in diagnosis and prognostic stratification, even predicting the response to therapy. Therefore, this manuscript systematically reviews the existing evidence of the proteomic profile of human endometrial cancer. The literature search was conducted via Medline (through PubMed) and the Web of Science. The inclusion criteria were clinical, in vitro, and in vivo original studies reporting proteomic analysis using all types of samples to map the human endometrial cancer proteome. A total of 55 publications were included in this review. Most of the articles carried out a proteomic analysis on endometrial tissue, serum and plasma samples, which enabled the identification of several potential diagnostic and prognostic biomarkers. In addition, eight articles were analyzed regarding the identified proteins, where three studies showed a strong correlation, sharing forty-five proteins. This analysis also allowed the identification of the 10 most frequently reported proteins in these studies: EGFR, PGRMC1, CSE1L, MYDGF, STMN1, CASP3 ANXA2, YBX1, ANXA1, and MYH11. Proteomics-based approaches pointed out potential diagnostic and prognostic candidates for endometrial cancer. However, there is a lack of studies exploring novel therapeutic targets. [ABSTRACT FROM AUTHOR]

Various reviews and meta‐analyses have shown the positive effects of mindfulness‐based interventions (MBIs) on the mental health of cancer patients and survivors. Some studies have also investigated the impact of MBIs on physiological markers of health in oncology, but a systematic review has not been conducted in this field. The current paper aims to fill this gap in the literature. Following preferred reporting items for systematic reviews and meta‐analyses 2020 guidelines, data were obtained from the databases of Pubmed, Scopus, Web of Science in May 2022. Twenty‐five studies were included. Globally, 35 biomarkers were employed in these studies and were categorized 8 groups (cortisol; blood pressure (BP), heart rate, and respiratory rate; C‐reactive protein; telomere length and telomerase activity (TA); genetic signature; cytokines and hormones; leucocyte activation; leucocyte count and cell subpopulation analysis). In seven of these categories of biomarkers, positive effects of MBIs were observed. The most promising results were obtained for cortisol, BP, TA and pro‐inflammatory gene expression. However, the generally low number of studies per single biomarker limits the possibility to draw reliable conclusions. The present review presents a comprehensive state‐of‐the‐art for MBIs in oncology on biomarkers, confirming MBIs' potential for improving physiological health in cancer patients and survivors besides those already shown in literature on psychological well‐being. [ABSTRACT FROM AUTHOR]

The development of next-generation sequencing (NGS) opens opportunities for new applications such as liquid biopsy, in which tumor mutation genotypes can be determined by sequencing circulating tumor DNA after blood draws. However, with highly diluted samples like those obtained with liquid biopsy, NGS invariably introduces a certain level of misclassification, even with improved technology. Recently, there has been a high demand to use mutation genotypes as biomarkers for predicting prognosis and treatment selection. Many methods have also been proposed to build classifiers based on multiple loci with machine learning algorithms as biomarkers. How the higher misclassification rate introduced by liquid biopsy will affect the performance of these biomarkers has not been thoroughly investigated. In this paper, we report the results from a simulation study focused on the clinical utility of biomarkers when misclassification is present due to the current technological limit of NGS in the liquid biopsy setting. The simulation covers a range of performance profiles for current NGS platforms with different machine learning algorithms and uses actual patient genotypes. Our results show that, at the high end of the performance spectrum, the misclassification introduced by NGS had very little effect on the clinical utility of the biomarker. However, in more challenging applications with lower accuracy, misclassification could have a notable effect on clinical utility. The pattern of this effect can be complex, especially for machine learning-based classifiers. Our results show that simulation can be an effective tool for assessing different scenarios of misclassification. [ABSTRACT FROM AUTHOR]

Aims: To perform a systematic review of studies that sought to identify diagnostic biomarkers for the diagnosis of cardiovascular diseases (CVDs) and diabetes mellitus (DM), which could be used in low‐ and middle‐income countries (LMICs) where there is a lack of diagnostic equipment, treatments and training. Materials and Methods: Papers were sourced from six databases: the British Nursing Index, Google Scholar, PubMed, Sage, Science Direct and Scopus. Articles published between January 2002 and January 2023 were systematically reviewed by three reviewers and appropriate search terms and inclusion/exclusion criteria were applied. Results: A total of 18 studies were yielded, as well as 234 diagnostic biomarkers (74 for CVD and 160 for DM). Primary biomarkers for the diagnosis of CVDs included growth differentiation factor 15 and neurogenic locus notch homologue protein 1 (Notch1). For the diagnosis of DM, alpha‐2‐macroglobulin, C‐peptides, isoleucine, glucose, tyrosine, linoleic acid and valine were frequently reported across the included studies. Advanced analytical techniques, such as liquid chromatography mass spectrometry, enzyme‐linked immunosorbent assays and vibrational spectroscopy, were also repeatedly reported in the included studies and were utilized in combination with traditional and alternative matrices such as fingernails, hair and saliva. Conclusions: While advanced analytical techniques are expensive, laboratories in LMICs should carry out a cost–benefit analysis of their use. Alternatively, laboratories may want to explore emerging techniques such as infrared, Fourier transform‐infrared and near‐infrared spectroscopy, which allow sensitive noninvasive analysis. [ABSTRACT FROM AUTHOR]

Background: The multitude of metabolites generated by physiological processes in the body can serve as valuable biomarkers for many clinical purposes. They can provide a window into relevant metabolic pathways for health and disease, as well as be candidate therapeutic targets. A subset of these metabolites generated in the human body are volatile, known as volatile organic compounds (VOCs), which can be detected in exhaled breath. These can diffuse from their point of origin throughout the body into the bloodstream and exchange into the air in the lungs. For this reason, breath VOC analysis has become a focus of biomedical research hoping to translate new useful biomarkers by taking advantage of the non-invasive nature of breath sampling, as well as the rapid rate of collection over short periods of time that can occur. Despite the promise of breath analysis as an additional platform for metabolomic analysis, no VOC breath biomarkers have successfully been implemented into a clinical setting as of the time of this review. Aim of review: This review aims to summarize the progress made to address the major methodological challenges, including standardization, that have historically limited the translation of breath VOC biomarkers into the clinic. We highlight what steps can be taken to improve these issues within new and ongoing breath research to promote the successful development of the VOCs in breath as a robust source of candidate biomarkers. We also highlight key recent papers across select fields, critically reviewing the progress made in the past few years to advance breath research. Key scientific concepts of review: VOCs are a set of metabolites that can be sampled in exhaled breath to act as advantageous biomarkers in a variety of clinical contexts. [ABSTRACT FROM AUTHOR]

Simple Summary: This review outlines the use of metabolomics to detect biomarkers for bovine mastitis, offering insights into disease prediction and early diagnosis. It details the use of various biological samples for metabolomic analysis, including milk, blood, urine, rumen fluid, feces, and mammary tissue. Bovine mastitis is an inflammatory disease of the mammary glands, and its pathogenesis and diagnosis are complicated. Through qualitative and quantitative analysis of small-molecule metabolites, the metabolomics technique plays an important role in finding biomarkers and studying the metabolic mechanism of bovine mastitis. Therefore, this paper reviews the predictive and diagnostic biomarkers of bovine mastitis that have been identified using metabolomics techniques and that are present in samples such as milk, blood, urine, rumen fluid, feces, and mammary tissue. In addition, the metabolic pathways of mastitis-related biomarkers in milk and blood were analyzed; it was found that the tricarboxylic acid (TCA) cycle was the most significant (FDR = 0.0015767) pathway in milk fluid, and glyoxylate and dicarboxylate metabolism was the most significant (FDR = 0.0081994) pathway in blood. The purpose of this review is to provide useful information for the prediction and early diagnosis of bovine mastitis. [ABSTRACT FROM AUTHOR]

Type 2 diabetes mellitus (T2DM) is one of the most common metabolic diseases in the world and poses a significant public health challenge. Early detection and management of this metabolic disorder is crucial to prevent complications and improve outcomes. This paper aims to find core differences in male and female markers to detect T2DM by their clinic and anthropometric features, seeking out ranges in potential biomarkers identified to provide useful information as a pre-diagnostic tool whie excluding glucose-related biomarkers using machine learning (ML) models. We used a dataset containing clinical and anthropometric variables from patients diagnosed with T2DM and patients without TD2M as control. We applied feature selection with three different techniques to identify relevant biomarker models: an improved recursive feature elimination (RFE) evaluating each set from all the features to one feature with the Akaike information criterion (AIC) to find optimal outputs; Least Absolute Shrinkage and Selection Operator (LASSO) with glmnet; and Genetic Algorithms (GA) with GALGO and forward selection (FS) applied to GALGO output. We then used these for comparison with the AIC to measure the performance of each technique and collect the optimal set of global features. Then, an implementation and comparison of five different ML models was carried out to identify the most accurate and interpretable one, considering the following models: logistic regression (LR), artificial neural network (ANN), support vector machine (SVM), k-nearest neighbors (KNN), and nearest centroid (Nearcent). The models were then combined in an ensemble to provide a more robust approximation. The results showed that potential biomarkers such as systolic blood pressure (SBP) and triglycerides are together significantly associated with T2DM. This approach also identified triglycerides, cholesterol, and diastolic blood pressure as biomarkers with differences between male and female actors that have not been previously reported in the literature. The most accurate ML model was selection with RFE and random forest (RF) as the estimator improved with the AIC, which achieved an accuracy of 0.8820. In conclusion, this study demonstrates the potential of ML models in identifying potential biomarkers for early detection of T2DM, excluding glucose-related biomarkers as well as differences between male and female anthropometric and clinic profiles. These findings may help to improve early detection and management of the T2DM by accounting for differences between male and female subjects in terms of anthropometric and clinic profiles, potentially reducing healthcare costs and improving personalized patient attention. Further research is needed to validate these potential biomarkers ranges in other populations and clinical settings. [ABSTRACT FROM AUTHOR]

Objective: Identifying the biomarkers for uncontrolled chronic rhinosinusitis (CRS) is important for directing treatment decisions. Eosinophilia has been reported to be involved in the poor disease control of CRS and mucus eosinophil-derived neurotoxin (EDN) is potentially a biomarker of intense eosinophil activation. This study aimed to assess the relationship between mucus EDN levels, disease severity, and degree of CRS control. Methods: A total of 150 adult patients with CRS and 25 healthy controls were prospectively enrolled. The nasal mucus and tissue specimens were collected to analyze EDN levels. Disease severity was assessed by Lund-Mackay score and 22-item Sino-Nasal Outcome Test (SNOT-22) score. Five CRS symptom severities during the prior month (nasal blockage, rhinorrhoea/postnasal drip, facial pain/pressure, smell, sleep disturbance or fatigue), use of rescue medications in the last six months, and the presence of diseased mucosa on nasal endoscopy were obtained. Consistent with the European Position Paper on Rhinosinusitis and Nasal Polyps 2020 CRS control criteria, uncontrolled CRS was defined as meeting at least three items. Results: 40% of patients with CRS presented with uncontrolled status. Patients with uncontrolled CRS had significantly higher nasal mucus EDN levels (P = 0.010), percentage of blood eosinophil (P = 0.015), SNOT-22 score (P < 0.001), Lund-Mackay score (P = 0.008), and a more eosinophilic dominant phenotype of CRS (P < 0.001) than patients with controlled CRS. Furthermore, mucus EDN levels were positively correlated with blood eosinophils (r = 0.541, P = 0.005), SNOT-22 score (r = 0.460, P = 0.021), and Lund-Mackay score (r = 0.387, P = 0.039). Mucus EDN levels were the significant parameter related to uncontrolled CRS in multivariable analysis after adjusting for patient demographics and comorbidities (odds ratio = 1.323; P = 0.004). Conclusions: Mucus EDN levels may be a potential biomarker for identifying the CRS control status. [ABSTRACT FROM AUTHOR]

Inertinite‐rich coal is widely distributed in the Ordos Basin, represented by the No. 2 coal seam of the Middle Jurassic Yan'an Formation. This paper combined coal petrology and geochemistry to analyze the origin of inertinite, changes in the coal‐forming environment and control characteristics of wildfire. Research has shown that there are two forms of inertinite sources in the study area. Alongside typical fusinization, wildfire events also play a substantial role in inertinite formation. There are significant fluctuations in the coal‐forming environment of samples at different depths. Coal samples were formed in dry forest swamp with low water levels and strong oxidation, which have a high inertinite content, and the samples formed in wet forest swamp and limnic showed low inertinite content. Conversely, the inertinite content of different origins does not fully correspond to the depositional environment characterized by dryness and oxidation. Nonpyrogenic inertinites were significantly influenced by climatic conditions, while pyrofusinite was not entirely controlled by climatic conditions but rather directly impacted by wildfire events. The high oxygen level was the main factor causing widespread wildfire events. Overall, the combination of wildfire activity and oxidation generates a high content of inertinite in the Middle Jurassic coal of the Ordos Basin. [ABSTRACT FROM AUTHOR]

Determining whether a surrogate marker can be used to replace a primary outcome in a clinical study is complex. While many statistical methods have been developed to formally evaluate a surrogate marker, they generally do not provide a way to examine heterogeneity in the utility of a surrogate marker. Similar to treatment effect heterogeneity, where the effect of a treatment varies based on a patient characteristic, heterogeneity in surrogacy means that the strength or utility of the surrogate marker varies based on a patient characteristic. The few methods that have been recently developed to examine such heterogeneity cannot accommodate censored data. Studies with a censored outcome are typically the studies that could most benefit from a surrogate because the follow‐up time is often long. In this paper, we develop a robust nonparametric approach to assess heterogeneity in the utility of a surrogate marker with respect to a baseline variable in a censored time‐to‐event outcome setting. In addition, we propose and evaluate a testing procedure to formally test for heterogeneity at a single time point or across multiple time points simultaneously. Finite sample performance of our estimation and testing procedure are examined in a simulation study. We use our proposed method to investigate the complex relationship between change in fasting plasma glucose, diabetes, and sex hormones using data from the diabetes prevention program study. [ABSTRACT FROM AUTHOR]

Reproductive management significantly impacts dairy farm productivity, necessitating accurate timely pregnancy detection in cattle. This paper presents a novel handheld and portable fluorescence imaging system designed for quantitative assessment of pregnancy-specific biomarkers, addressing the limitations of current detection methods. The objective was to develop a cost-effective, at-farm solution for detecting pregnancy-specific protein B (PSPB) in bovine plasma samples. The system integrates an imaging module and a custom software application, enabling image capture, data processing, and PSPB concentration determination. Calibration utilizing known PSPB concentrations achieved a 0.6 ng/mL limit of detection. Validation encompassed a comparison with a standard ELISA method using 100 bovine plasma samples; minimal bias and good agreement were observed within the linear range of the calibration curve for both methods. The system offers portability, user-friendliness, and potential for multiplex detection, promising real-time, at-farm reproductive management. This study demonstrates the successful development and validation of a portable fluorescence imaging system, offering an efficient and accurate approach to detecting pregnancy-specific biomarkers in cattle. Its implications extend to improving dairy farm productivity by enabling timely and reliable reproductive management practices. [ABSTRACT FROM AUTHOR]

Non-invasive continuous health monitoring has become feasible with the advancement of biosensors. While monitoring certain biomarkers such as heart rate or skin temperature are now at a certain maturity, monitoring molecular biomarkers is still challenging. Progress has been shown in sampling, measurement, and interpretation of data toward non-invasive molecular sensors that can be integrated into daily wearable items. Toward this goal, this paper explores the potential of embroidered interdigitated transducer (IDT)-based sensors for non-invasive, continuous monitoring of human biomarkers, particularly glucose levels, in human sweat. The study employs innovative embroidery techniques to create flexible fabric-based sensors with gold-coated IDTs. In controlled experiments, we have shown the variation of glucose concentration in water can be wirelessly detected by tracking the resonant frequency of the embroidered sensors. The current sensors operate at 1.8 GHz to 2 GHz and respond to the change in glucose concentration with a sensitivity of 0.17 MHz/(mg/dL). The embroidered IDT-based sensors with wireless sensing will be a new measurement modality for molecular wearable sensors. The establishment of a wireless sensing mechanism for embroidered IDT-based sensors will be followed by an investigation of sweat for molecular detection. This will require adding functionalities for sampling and interpretation of acquired data. We envisage the embroidered IDT-based sensors offer a unique approach for seamless integration into clothing, paving the way for personalised, continuous health data capture. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate the diagnostic characteristics of biomarker for diabetic foot osteomyelitis (DFO). We searched PubMed, Scopus, Embase and Medline for studies who report serological markers and DFO before December 2022. Studies must include at least one of the following diagnostic parameters for biomarkers: area under the curve, sensitivities, specificities, positive predictive value, negative predictive value. Two authors evaluated quality using the Quality Assessment of Diagnostic Accuracy Studies tool. We included 19 papers. In this systematic review, there were 2854 subjects with 2134 (74.8%) of those patients being included in the meta‐analysis. The most common biomarkers were erythrocyte sedimentation rate (ESR), C‐reactive protein (CRP) and procalcitonin (PCT). A meta‐analysis was then performed where data were evaluated with Forrest plots and receiver operating characteristic curves. The pooled sensitivity and specificity were 0.72 and 0.75 for PCT, 0.72 and 0.76 for CRP and 0.70 and 0.77 for ESR. Pooled area under the curves for ESR, CRP and PCT were 0.83, 0.77 and 0.71, respectfully. Average diagnostic odds ratios were 16.1 (range 3.6–55.4), 14.3 (range 2.7–48.7) and 6.7 (range 3.6–10.4) for ESR, CRP and PCT, respectfully. None of the biomarkers we evaluated could be rated as 'outstanding' to diagnose osteomyelitis. Based on the areas under the curve, ESR is an 'excellent' biomarker to detect osteomyelitis, and CRP and PCT are 'acceptable' biomarkers to diagnose osteomyelitis. Diagnostic odds ratios indicate that ESR, CRP and PCT are 'good' or 'very good' tools to identify osteomyelitis. [ABSTRACT FROM AUTHOR]

Background: Small RNA molecules known as microRNAs (miRNAs) regulate gene expression during the post-translational steps. miRNAs are essential for many physiological processes, such as cell division, growth, and proliferation, as well as development and metabolism. Aims: To review the developments in investigations on miR-155 and miR-146a as possible biomarkers for multiple sclerosis (MS) disease diagnosis and prognosis. Methods: A comprehensive analysis of the available literature was carried out by searching databases including PubMed, Scopus, and Web of Science for papers published between 2011 and 2023 years. Only original articles written in the English language were considered for inclusion in this review. Results: A total of 29 studies were initially identified, with 14 meeting the inclusion criteria. Conclusion: The present study underscores the crucial role of microRNAs, particularly miR-155 and miR-146a, in the etiology and progression of multiple sclerosis (MS). Through an extensive analysis of the literature, we have found compelling evidence linking aberrations in the expression and function of these microRNAs to MS pathogenesis. Specifically, our synthesis suggests that miR-155 and miR-146a hold promise as valuable biomarkers for both the diagnosis and prognosis of MS. Despite the challenges posed by the heterogeneity of MS subtypes, the non-invasive accessibility of miRNAs in various bodily fluids, including serum, peripheral blood, cerebrospinal fluid, and extracellular vesicles, presents a promising avenue for the development of robust diagnostic and prognostic tools. By elucidating the intricate roles of miR-155 and miR-146a in MS, our findings contribute to advancing our understanding of the disease mechanisms and pave the way for the development of more effective diagnostic and therapeutic strategies. [ABSTRACT FROM AUTHOR]

Introduction: Osteoarthritis (OA) is a common degenerative disorder of the synovial joints and is usually an age-related disease that occurs due to continuous wear and tear of the cartilage in the joints. Presently, there is no proven medical management to halt the progression of the disease in the early stages. The purpose of our systematic review is to analyze the possible metabolites and metabolic pathways that are specifically involved in OA pathogenesis and early treatment of the disease. Materials and Methods: The articles were collected from PubMed, Cochrane, Google Scholar, Embase, and Scopus databases. "Knee", "Osteoarthritis", "Proteomics", "Lipidomics", "Metabolomics", "Metabolic Methods", and metabolic* were employed for finding the articles. Only original articles with human or animal OA models with healthy controls were included. Results: From the initial screening, a total of 458 articles were identified from the 5 research databases. From these, 297 articles were selected in the end for screening, of which 53 papers were selected for full-text screening. Finally, 50 articles were taken for the review based on body fluid: 6 urine studies, 15 plasma studies, 16 synovial fluid studies, 11 serum studies, 4 joint tissue studies, and 1 fecal study. Many metabolites were found to be elevated in OA. Some of these metabolites can be used to stage the OA Three pathways that were found to be commonly involved are the TCA cycle, the glycolytic pathway, and the lipid metabolism. Conclusion: All these studies showed a vast array of metabolites and metabolic pathways associated with OA. Metabolites like lysophospholipids, phospholipids, arginine, BCCA, and histidine were identified as potential biomarkers of OA but a definite association was not identified, Three pathways (glycolytic pathway, TCA cycle, and lipid metabolic pathways) have been found as highly significant in OA pathogenesis. These metabolic pathways could provide novel therapeutic targets for the prevention and progression of the disease. [ABSTRACT FROM AUTHOR]

Understanding the origins of potential source rocks and unraveling the intricate connections between reservoir oils and their source formations in the Siwa Basin (Western Desert, Egypt) necessitate a thorough oil-source correlation investigation. This objective is achieved through a meticulous analysis of well-log responses, Rock-Eval pyrolysis, and biomarker data. The analysis of Total Organic Carbon across 31 samples representing Paleozoic formations in the Siwa A-1X well reveals a spectrum of organic richness ranging from 0.17 wt% to 2.04 wt%, thereby highlighting diverse levels of organic content and the presence of both Type II and Type III kerogen. Examination of the fingerprint characteristics of eight samples from the well suggests that the Dhiffah Formation comprises a blend of terrestrial and marine organic matter. Notably, a significant contribution from more oxidized residual organic matter and gasprone Type III kerogen is observed. Contrarily, the Desouky and Zeitoun formations exhibit mixed organic matter indicative of a transitional environment, and thus featuring a pronounced marine influence within a more reducing setting, which is associated with Type II kerogen. Through analysis of five oil samples from different wellsdSIWA L-1X, SIWA R-3X, SIWA D-1X, PTAH 5X, and PTAH 6X, it is evident that terrestrial organic matter, augmented by considerable marine input, was deposited in an oxidizing environment, and contains Type III kerogen. Geochemical scrutiny confirms the coexistence of mixed terrestrial organic matter within varying redox environments. Noteworthy is the uniformity of identified kerogen Types II and III across all samples, known to have potential for hydrocarbon generation. The discovery presented in this paper unveils captivating prospects concerning the genesis of oil in the Jurassic Safa reservoir, suggesting potential links to Paleozoic sources or even originating from the Safa Member itself. These revelations mark a substantial advancement in understanding source rock dynamics and their intricate relationship with reservoir oils within the Siwa Basin. By illuminating the processes of hydrocarbon genesis in the region, this study significantly enriches our knowledge base. [ABSTRACT FROM AUTHOR]

BACKGROUND: The term 'dementia' covers a range of progressive brain diseases from which many elderly people suffer. Traditional cognitive and pathological tests are currently used to detect dementia, however, applications using Artificial Intelligence (AI) methods have recently shown improved results from improved detection accuracy and efficiency. OBJECTIVE: This research paper investigates the efficacy of one type of data analytics called supervised learning to detect Alzheimer's disease (AD) – a common dementia condition. METHODS: The aim is to evaluate cognitive tests and common biological markers (biomarkers) such as cerebrospinal fluid (CSF) to develop predictive classification systems for dementia detection. RESULTS: A data analytics process has been proposed, implemented, and tested against real data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) repository. CONCLUSION: The models showed good power in predicting AD levels, notably from specified cognitive tests' scores and tauopathy related features. [ABSTRACT FROM AUTHOR]

In clinical studies of chronic diseases, the effectiveness of an intervention is often assessed using "high cost" outcomes that require long-term patient follow-up and/or are invasive to obtain. While much progress has been made in the development of statistical methods to identify surrogate markers, that is, measurements that could replace such costly outcomes, they are generally not applicable to studies with a small sample size. These methods either rely on nonparametric smoothing which requires a relatively large sample size or rely on strict model assumptions that are unlikely to hold in practice and empirically difficult to verify with a small sample size. In this paper, we develop a novel rank-based nonparametric approach to evaluate a surrogate marker in a small sample size setting. The method developed in this paper is motivated by a small study of children with nonalcoholic fatty liver disease (NAFLD), a diagnosis for a range of liver conditions in individuals without significant history of alcohol intake. Specifically, we examine whether change in alanine aminotransferase (ALT; measured in blood) is a surrogate marker for change in NAFLD activity score (obtained by biopsy) in a trial, which compared Vitamin E (⁠|$n=50$|⁠) versus placebo (⁠|$n=46$|⁠) among children with NAFLD. [ABSTRACT FROM AUTHOR]

In medical diagnostic research, it is customary to collect multiple continuous biomarker measures to improve the accuracy of diagnostic tests. A prevalent practice is to combine the measurements of these biomarkers into one single composite score. However, incorporating those biomarker measurements into a single score depends on the combination of methods and may lose vital information needed to make an effective and accurate decision. Furthermore, a diagnostic cut-off is required for such a combined score, and it is difficult to interpret in actual clinical practice. The paper extends the classical biomarkers' accuracy and predictive values from univariate to bivariate markers. Also, we will develop a novel pseudo-measures system to maximize the vital information from multiple biomarkers. We specified these pseudo-and-or classifiers for the true positive rate, true negative rate, false-positive rate, and false-negative rate. We used them to redefine classical measures such as the Youden index, diagnostics odds ratio, likelihood ratios, and predictive values. We provide optimal cut-off point selection based on the modified Youden index with numerical illustrations and real data analysis for this paper's newly developed pseudo measures. [ABSTRACT FROM AUTHOR]