Common Biomarkers Research Articles

Novel insights into immunopathogenesis and crucial biomarkers between primary open‐angle glaucoma and systemic lupus erythematosus

AbstractGlaucoma is the primary factor underlying irreversible blindness. Recent studies suggest that the risk of glaucoma significantly increases in patients with systemic lupus erythematosus (SLE); however, the mechanism underlying this association remains unclear. Therefore, this study aimed to identify novel common biomarkers and potential therapeutic drugs for SLE and glaucoma. GSE27276, GSE50772, and GSE148371 datasets were sourced from the gene expression omnibus (GEO) database. An integrated analysis of the datasets for both diseases identified biomarkers and thoroughly examined their biological roles and molecular mechanisms using differential expression analysis (DEA), weighted gene co‐expression network analysis (WGCNA), gene enrichment analysis, machine learning, microRNA (miRNA) and transcription factor analyses, immune infiltration analyses, and single‐cell transcriptome analysis. Concurrently, molecular docking was used to forecast potential drugs targeting these biomarkers. Finally, reverse transcription quantitative real‐time polymerase chain reaction (RT‐qPCR) was performed in human trabecular meshwork stem cells to validate the five identified biomarkers. The 10 key genes identified through DEA and WGCNA were predominantly involved in immune, inflammatory, and autophagy pathways. Additionally, machine learning identified five biomarkers, and we established associated transcription factors and miRNA regulatory networks. Immune infiltration analysis indicated an elevated presence of immune cells, including macrophages, T cells, and B cells, in both conditions. Furthermore, the DSigDB database yielded 10 potential therapeutic agents, three of which showed strong binding potential to the biomarkers via molecular docking. The RT‐qPCR results confirmed the trend in gene expression. This study uncovered a new link between SLE and primary open‐angle glaucoma, identifying biomarkers and mechanisms of immunopathogenesis for future research and treatment strategies.

The distribution of biomarkers for Behcet syndrome and their clinical relevance in real-world studies

Objective: To explore the distribution of different biomarkers for Behcet's syndrome (BS) and their correlation with distinct clinical phenotypes of BS patients in real-world studies. Methods: This study was a retrospective cross-sectional study. A total of 483 patients diagnosed with BS in the Department of Rheumatology and Immunology, Peking University People's Hospital from 2019 to 2022 were enrolled. The baseline information and clinical features of the patients were recorded at their first diagnosis and tested the level of HLA-B51, several auto-antibodies, antistreptolysin-O(ASO), immune globulin, complement in blood serum and interleukin-6 (IL-6). Logistic regression was used to analyze the correlation of biomarkers and phenotypes. Results: Among BS patients, the number of positive cases for HLA-B51, anti-endothelial cell antibody (AECA), antinuclear antibodies (ANA) and ASO was 129, 115, 79 and 54, respectively. The positive rate of other biomarkers was less than 5.0%. About 12.6% of patients with BS had an increased level of IgA (n=61), and 10.8% of patients had an increased level of IgG (n=52). About 41.0% of patients had increased levels of IL-6 (n=198), and 6.4% of patients had decreased levels of IgM (n=31). About 11.2% of patients had decreased levels of C3 (n=54), and 6.0% of patients had decreased levels of C4 (n=29). Elevated IgA was a risk factor for the articular phenotype of BS (OR=2.652, P=0.011). Decreased complement C4 was a risk factor for the neurological phenotype of BS (OR=3.594, P=0.039). Positive ASO was a risk factor for the gastrointestinal phenotype of BS (OR=2.578, P=0.041). Elevated IL-6 was a risk factor for the ocular phenotype of BS (OR=7.560, P=0.016). Conclusion: HLA-B51 and AECA are common biomarkers in BS. Elevated IgA, decreased complement C4, positive ASO, and elevated IL-6 are risk factors for different phenotypes of BS.

An Electrochemical Nucleic Acid Biosensor for Triple-Negative Breast Cancer Biomarker Detection.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, affecting younger women and women of minorities. The nomenclature "triple negative" is derived from the absence of the three most common breast cancer biomarkers: progesterone receptor (PR), estrogen receptor (ER), and human epidermal growth factor receptor 2 (HER2). It derives its name from testing negative for these three most common breast cancer biomarkers. Currently, TNBC is diagnosed at advanced stages, necessitating the need for a diagnostic tool or method to identify this malignancy at an early stage prior to metastasis. In this study, a novel electrochemical biosensor was developed, optimized, and evaluated for the detection of microRNA-10b (miRNA-10b), marking the first use of this biomarker for the early diagnosis of TNBC. The biosensor demonstrated the ability to detect concentrations as low as 10 pM. Furthermore, the biosensor was specific toward the target biomarker, distinguishing non-target miRNAs of similar size. The efficacy of the biosensor for TNBC early diagnosis was further validated using human serum samples.

Rapid Fingerprinting of Urinary Volatile Metabolites and Point-of-Care Diagnosis of Phenylketonuria on a Patterned Nanorod Sensor Array with Multiplexed Surface-Enhanced Raman Scattering Readouts.

Phenylketonuria (PKU) is one of the most common genetic metabolic diseases, especially among newborns. Traditional clinical examination of newborn blood samples for PKU is invasive, laborious, and limited to hospitals and healthcare facilities. We reported herein a SERS-based sensor array with three thiophenolic nanoreceptors built on a patterned nanorod vertical array for rapid and inexpensive detection of characteristic volatile biomarkers indicative of PKU in the urine and accurate classification of newborn baby patients all performed on a hand-held SERS spectrophotometer. The well-ordered array was generated from the volatility-driven assembly of gold nanorods (AuNRs) into an upright and closely packed hexagonal configuration. The uniformly distributed nanowells between AuNRs offered an intense and aspect-ratio-dependent plasmonic field for the molecular enhancement of SERS outputs. The SERS-based detector was integrated into a test chip for regular monitoring of volatile phenylketone bodies in the spiked solution or patients' urine within 5 min, allowing the quantification of a wide variety of normal or abnormal metabolites at their physiologically relevant concentration range. The detection limits for common biomarkers of PKU, including phenylpyruvic acid, 4-hydroxyphenylacetic acid, and phenylacetic acid, were at a few μM and well below the diagnostic thresholds. Moreover, the volatile headspace mixtures from a given urine sample could be fingerprinted by the sensor array and discriminated using machine-learning algorithms. Ultimately, the discrimination of baby patients among 26 cases of mild and classic PKU phenotypes and 17 cases of healthy volunteers could be realized with an overall accuracy of 97%. This hand-held SERS platform plays a pivotal role in advancing healthcare applications in quick screening of neonatal PKU through a facile urinary vapor test.

Profile of immunological biomarkers in Behcet’s syndrome: a large-scale single-center real-world study

Behcet's syndrome (BS) is a vasculitis characterized by immune dysregulation. Biomarkers are valuable for assessing clinically atypical pathogenesis. We aimed to investigate the distribution of different biomarkers and their effects on the clinical features of patients with BS in a large-scale, real-world study. This is a retrospective, single-center study. In total, 502 patients diagnosed with BS were enrolled in this study. We analyzed the clinical features of this cohort and divided patients’ symptoms into six categories, including mucocutaneous, articular, neurological, gastrointestinal, vascular, and ocular involvements. HLA-B51 cells, autoantibodies, and subsets of immune cells from the patients were tested. Pearson’s correlation, Wilcoxon rank sum test and multivariate logistic regression were used for data analysis. Various autoantibodies were detected in the serum of 40.8% of patients with BS. The positivity rate of anti-endothelial cell antibodies (AECA) was the highest among autoantibodies and was found in 23.5% (118/502) of patients with BS. The positivity rate of HLA-B51 in patients with BS was 27.1%. Tumor necrosis factor (TNF)-α, IL-2, and IL-4 producing CD4+ T cells were positively correlated with the gastrointestinal BS. Increased IL-4+CD4+ T cell was a risk factor for gastrointestinal BS (P = 0.006, Overall rate [OR] = 2.491, 95% Confidence interval [CI]: [1.317, 5.100]). Various autoantibodies can be detected in patients with BS. HLA-B51 and AECA are the most common biomarkers. Increased IL-4+ CD4+ T cell was a risk factor for gastrointestinal involvement in BS.

Antimigratory Effect of Lipophilic Cations Derived from Gallic and Gentisic Acid and Synergistic Effect with 5-Fluorouracil on Metastatic Colorectal Cancer Cells: A New Synthesis Route.

Colorectal cancer (CRC) is the third leading cause of cancer deaths in the world. Standard drugs currently used for the treatment of advanced CRC-such as 5-fluorouracil (5FU)-remain unsatisfactory in their results due to their high toxicity, high resistance, and adverse effects. In recent years, mitochondria have become an attractive target for cancer therapy due to higher transmembrane mitochondrial potential. We synthesized gallic acid derivatives linked to a ten-carbon aliphatic chain associated with triphenylphosphonium (TPP+C10), a lipophilic cationic molecule that induces the uncoupling of the electron transport chain (ETC). Other derivatives, such as gentisic acid (GA-TPP+C10), have the same effects on colorectal cancer cells. Although part of our group had previously reported preparing these structures by a convergent synthesis route, including their application via flow chemistry, there was no precedent for a new methodology for preparing these compounds. In this scenario, this study aims to develop a new linear synthesis strategy involving an essential step of Steglich esterification under mild conditions (open flask) and a high degree of reproducibility. Moreover, the study seeks to associate GA-TPP+C10 with 5FU to evaluate synergistic antineoplastic effects. In addition, we assess the antimigratory effect of GA-TPP+C10 and TPP+C10 using human and mouse metastatic CRC cell lines. The results show a new and efficient synthesis route of these compounds, having synergistic effects in combination with 5FU, increasing apoptosis and enhancing cytotoxic properties. Additionally, the results show a robust antimigratory effect of GATPP+C10 and TPP+C10, reducing the activation pathways linked to tumor progression and reducing the expression of VEGF and MMP-2 and MMP-9, common biomarkers of advanced CRC. Moreover, TPP+C10 and GA-TPP+C10 increase the activity of metabolic signaling pathways through AMPK activation. The data allow us to conclude that these compounds can be used for in vivo evaluations and are a promising alternative associated with conventional therapies for advanced colorectal cancer. Additionally, the reported intermediates of the new synthesis route could give rise to analog compounds with improved therapeutic activity.

Identification of CD19 as a shared biomarker via PPARγ/β-catenin/Wnt3a pathway linking psoriasis and major depressive disorder

BackgroundPsoriasis, a chronic inflammatory skin disorder, is frequently linked with metabolic, cardiovascular, and psychological comorbidities. Recent research has highlighted the correlation between psoriasis and major depressive disorder (MDD); however, the underlying mechanism remains unclear. MethodsCommonly differentially expressed genes (DEGs) in psoriasis and MDD were identified and visualized using data from the GEO database. Subsequently, functional enrichment analysis was conducted using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Genemania. The hub gene was selected through LASSO and Random Forest algorithms, validated in clinical tissues using Student's t-test and Receiver Operating Characteristic curve. To investigate the hub gene's function in disease phenotype, we established imiquimod (IMQ)-induced psoriasiform dermatitis and chronic unpredictable mild stress (CUMS) mouse models. Lentiviral shRNA interference was topically applied in mice, and downstream pathways were validated at the mRNA and protein levels. ResultsA total of 395 overlapping DEGs were identified from GSE121212 and GSE54568 datasets, and twenty core genes were extracted. Functional enrichment analysis revealed that the core genes were significantly associated with the Wnt signaling pathway, neurodegeneration, and energy metabolism. CD19 was identified as the hub gene through algorithms, and external validation showed remarkable AUC values of 0.69 and 0.74, respectively. The level of CD19 increased significantly in IMQ-treated and CUMS-treated mice. Suppression of CD19 significantly alleviated the phenotypes of IMQ-induced psoriasiform dermatitis and CUMS-induced depressive-like behaviors by regulating the PPARγ/β-catenin/Wnt3a pathway. ConclusionCD19 may serve as a common biomarker or therapeutic target of psoriasis and MDD via PPARγ/β-catenin/Wnt3a pathway.

Tau PET positivity predicts clinically relevant cognitive decline driven by Alzheimer's disease compared to comorbid cases; proof of concept in the ADNI study.

β-amyloid (Aβ) pathology is not always coupled with Alzheimer's disease (AD) relevant cognitive decline. We assessed the accuracy of tau PET to identify Aβ(+) individuals who show prospective disease progression. 396 cognitively unimpaired and impaired individuals with baseline Aβ and tau PET and a follow-up of ≥ 2 years were selected from the Alzheimer's Disease Neuroimaging Initiative dataset. The participants were dichotomously grouped based on either clinical conversion (i.e., change of diagnosis) or cognitive deterioration (fast (FDs) vs. slow decliners (SDs)) using data-driven clustering of the individual annual rates of cognitive decline. To assess cognitive decline in individuals with isolated Aβ(+) or absence of both Aβ and tau (T) pathologies, we investigated the prevalence of non-AD comorbidities and FDG PET hypometabolism patterns suggestive of AD. Baseline tau PET uptake was higher in Aβ(+)FDs than in Aβ(-)FD/SDs and Aβ(+)SDs, independently of baseline cognitive status. Baseline tau PET uptake identified MCI Aβ(+) Converters and Aβ(+)FDs with an area under the curve of 0.85 and 0.87 (composite temporal region of interest) respectively, and was linearly related to the annual rate of cognitive decline in Aβ(+) individuals. The T(+) individuals constituted largely a subgroup of those being Aβ(+) and those clustered as FDs. The most common biomarker profiles in FDs (n = 70) were Aβ(+)T(+) (n = 34, 49%) and Aβ(+)T(-) (n = 19, 27%). Baseline Aβ load was higher in Aβ(+)T(+)FDs (M = 83.03 ± 31.42CL) than in Aβ(+)T(-)FDs (M = 63.67 ± 26.75CL) (p-value = 0.038). Depression diagnosis was more prevalent in Aβ(+)T(-)FDs compared to Aβ(+)T(+)FDs (47% vs. 15%, p-value = 0.021), as were FDG PET hypometabolism pattern not suggestive of AD (86% vs. 50%, p-value = 0.039). Our findings suggest that high tau PET uptake is coupled with both Aβ pathology and accelerated cognitive decline. In cases of isolated Aβ(+), cognitive decline may be associated with changes within the AD spectrum in a multi-morbidity context, i.e., mixed AD.

Markers for egg quality in European eel derived from offspring of females subjected to different gonadotropic treatments

Broodstock management techniques in general, and gonadotropic treatments for vitellogenesis induction in particular, can influence the maternal provisioning of different compounds to the eggs, thus affecting embryo and larval competence. Among these, the abundance of certain transcripts as well as lipid content and fatty acid composition have been used as egg quality markers alongside other egg morphological parameters, such as egg size and the occurrence of abnormal cleavages during the first stages of embryonic development. Here, we evaluated the use of different markers of egg quality from farmed-raised European eel, Anguilla anguilla, broodstock reared on the same formulated diet but subjected to different pituitary extract administration schemes: weekly injections of salmon pituitary extract (SPE) in a constant dose or weekly injections of carp pituitary extract (CPE) at a stepwise increasing dose. Egg batches were categorized in two quality groups (high and low) according to their survival to the first feeding larval stage. In agreement with previous studies, unfertilized eggs and 4-h post fertilization embryos (16-cell stage) from SPE treated females had higher epcam expression levels than CPE ones, which is a molecule involved in cell-cell adhesion. When comparing treatments, batches from the SPE treatment had a lower incidence of cleavage abnormalities which could originate from compromised cell adhesion. On the other hand, this difference was not observed when comparing high-quality batches (i.e. those surviving up to the first-feeding stage) and low-quality ones. From the five genes analysed: epcam, dcbld1, plec, cenpf, and cenpk, only the latter had a differential expression between high- and low-quality groups both in unfertilized eggs and 4 h-post-fertilization embryos. This gene, cenpk, is involved in kinetochore assemblage during cell division and appears to be promising as egg quality marker in European eel in combination with epcam and dcbld1. Common biomarkers, such as egg size, total protein and lipid content, were similar between groups. However, although fatty acid composition was similar between quality groups, DHA and EPA content in unfertilized eggs was affected by the gonadotropic treatment applied to the female broodstock, and higher for the CPE treated females than the SPE ones. This entails that the hormonal treatments applied for vitellogenesis induction can influence the amount of specific fatty acids being transferred to the eggs, even for female broodstock that were fed the same high-quality diet.

Point-based risk score for the risk stratification and prediction of hepatocellular carcinoma: a population-based random survival forest modeling study

The precise associations between common clinical biomarkers and hepatocellular carcinoma (HCC) risk remain unclear but hold valuable insights for HCC risk stratification and prediction. We examined the linear and nonlinear associations between the baseline levels of 32 circulating biomarkers and HCC risk in the England cohort of UK Biobank (UKBB) (n=397,702). The participants were enrolled between 2006 and 2010 and followed up to 31st October 2022. The primary outcome is incident HCC cases. We then employed random survival forests (RSF) to select the top ten most informative biomarkers, considering their association with HCC, and developed a point-based risk score to predict HCC. The performance of the risk score was evaluated in three validation sets including UKBB Scotland and Wales cohort (n=52,721), UKBB non-White-British cohort (n=29,315), and the Taizhou Longitudinal Study in China (n=17,269). Twenty-five biomarkers were significantly associated with HCC risk, either linearly or nonlinearly. Based on the RSF model selected biomarkers, our point-based risk score showed a concordance index of 0.866 in the England cohort and varied between 0.814 and 0.849 in the three validation sets. HCC incidence rates ranged from 0.95 to 30.82 per 100,000 from the lowest to the highest quintiles of the risk score in the England cohort. Individuals in the highest risk quintile had a 32-73 times greater risk of HCC compared to those in the lowest quintile. Moreover, over 70% of HCC cases were detected in individuals within the top risk score quintile across all cohorts. Our simple risk score enables the identification of high-risk individuals of HCC in the general population. However, including some biomarkers, such as insulin-like growth factor 1, not routinely measured in clinical practice may increase the model's complexity, highlighting the need for more accessible biomarkers that can maintain or improve the predictive accuracy of the risk score. This work was supported by the National Natural Science Foundation of China (grant numbers: 82204125) and the Science and Technology Support Program of Taizhou (TS202224).

Complex Assessment of the Functional State of the Urinary System in Preclinical Studies. Part 2. Markers of Nephrotoxicity (Review)

INTRODUCTION. The determination of nephrotoxicity markers is a useful and necessary step in the detection of renal injury in animal experiments; these markers help accurately localise organ damage. With multiple damaging agents, known nephrotoxicity mechanisms, and laboratory animal species, there is currently no widely accepted renal injury marker that meets all the prerequisites.AIM. This study aimed to collate literature data on nephrotoxicity markers, evaluate their prognostic significance, and formulate general recommendations for assessing urinary system function in preclinical studies.DISCUSSION. This article describes a comparative analysis of the nephrotoxicity markers recommended by regulatory authorities for monitoring drug-induced kidney injury. According to the results, the most commonly used and prognostically significant markers of acute kidney injury in preclinical studies are cystatin C, albumin, total protein, kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin-2 (NGAL), and clusterin. Chronic kidney injury markers include the above, plus the glomerular filtration rate, creatinine, urea, and osteopontin. An electrolyte panel can be used for the differential diagnosis of pre-renal azotaemia and acute kidney injury. Potential limitations for the routine use of kidney injury markers in preclinical research include the high cost of their quantitative determination and the lack of information on the applicability of data obtained from different species of laboratory animals.CONCLUSIONS. Having compared the prognostic significance of common biomarkers, the authors provided general recommendations for a comprehensive preclinical assessment of urinary system function, including laboratory investigations, instrument-based tests, and necropsy. A preclinical study design should be based on the study aims, the species and number of animals used, and special considerations for the test article.

Atherosclerosis and adverse pregnancy outcomes: Common biomarkers involved

Atherosclerosis and adverse pregnancy outcomes: Common biomarkers involved

Early detection of hepatobiliary involvement in cystic fibrosis: Biomarkers, radiologic methods, and genetic influences.

Cystic fibrosis-related hepatobiliary involvement (CFHBI) is a term used to describe a spectrum of hepatobiliary involvement ranging from a transient elevation of transaminase levels to advanced cystic fibrosis-associated liver disease (aCFLD). While CFHBI is common among people with cystic fibrosis (PwCF), aCFLD is rare impacting only approximately 5%-10% of the CF population. After respiratory/cardiorespiratory issues and transplant-related complications, aCFLD is now the 4th leading cause of mortality among PwCF. Additionally, aCFLD is an independent predictor of all-cause mortality and is associated with significant morbidity. Despite this recognition, our ability to predict those patients at greatest risk for aCFLD, identify early aCFLD, and monitor the incremental progression of CFHBI is lacking. Here, we review the strengths and weaknesses of the common biomarkers and imaging modalities used in the evaluation and monitoring of CFHBI, as well as the current understanding of genetic modifiers related to aCFLD.

Dual-Locked Enzyme-Activatable Bioorthogonal Fluorescence Turn-On Imaging of Senescent Cancer Cells.

Bioorthogonal pretargeting optical imaging shows the potential for enhanced diagnosis and prognosis. However, the bioorthogonal handles, known for being "always reactive", may engage in reactions at unintended sites with their counterparts, resulting in nonspecific fluorescence activation and diminishing detection specificity. Meanwhile, despite the importance of detecting senescent cancer cells in cancer therapy, current methods mainly rely on common single senescence-associated biomarkers, which lack specificity for differentiating between various types of senescent cells. Herein, we report a dual-locked enzyme-activatable bioorthogonal fluorescence (DEBOF) turn-on imaging approach for the specific detection of senescent cancer cells. A dual-locked bioorthogonal targeting agent (DBTA) and a bioorthogonally activatable fluorescent imaging probe (BAP) are synthesized as the biorthogonal pair. DBTA is a tetrazine derivative dually caged by two enzyme-cleavable moieties, respectively, associated with senescence and cancer, which ensures that its bioorthogonal reactivity ("clickability") is only triggered in the presence of senescent cancer cells. BAP is a fluorophore caged by trans-cyclooctane (TCO), whose fluorescence is only activated upon bioorthogonal reaction between its TCO and the decaged tetrazine of DBTA. As such, the DEBOF imaging approach differentiates senescent cancer cells from nonsenescent cancer cells or other senescent cells, allowing noninvasive tracking of the population fluctuation of senescent cancer cells in the tumor of living mice to guide cancer therapies. This study thus provides a general molecular strategy for biomarker-activatable in vivo bioorthogonal pretargeting imaging with the potential to be applied to other imaging modalities beyond optics.

Applications of Zebrafish Embryo Models to Predict Developmental Toxicity for Agrochemical Product Development.

The development of safe crop protection products is a complex process that traditionally relies on intensive animal use for hazard identification. Methods that capture toxicity in early stages of agrochemical discovery programs enable a more efficient and sustainable product development pipeline. Here, we explored whether the zebrafish model can be leveraged to identify mammalian-relevant toxicity. We used transgenic zebrafish to assess developmental toxicity following exposures to known mammalian teratogens and captured larval morphological malformations, including bone and vascular perturbations. We further applied toxicogenomics to identify common biomarker signatures of teratogen exposure. The results show that the larval malformation assay predicted teratogenicity with 82.35% accuracy, 87.50% specificity, and 77.78% sensitivity. Similar and slightly lower accuracies were obtained with the vascular and bone assays, respectively. A set of 20 biomarkers were identified that efficiently segregated teratogenic chemicals from nonteratogens. In conclusion, zebrafish are valuable, robust, and cost-effective models for toxicity testing in the early stages of product development.

Predicting the severity of mood and neuropsychiatric symptoms from digital biomarkers using wearable physiological data and deep learning

Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild cognitive impairment (MCI) and increase the risk of progression to dementia. Wearable devices collecting physiological and behavioral data can help in remote, passive, and continuous monitoring of moods and NPS, overcoming limitations and inconveniences of current assessment methods. In this longitudinal study, we examined the predictive ability of digital biomarkers based on sensor data from a wrist-worn wearable to determine the severity of NPS and mood disorders on a daily basis in older adults with predominant MCI. In addition to conventional physiological biomarkers, such as heart rate variability and skin conductance levels, we leveraged deep-learning features derived from physiological data using a self-supervised convolutional autoencoder. Models combining common digital biomarkers and deep features predicted depression severity scores with a correlation of r = 0.73 on average, total severity of mood disorder symptoms with r = 0.67, and mild behavioral impairment scores with r = 0.69 in the study population. Our findings demonstrated the potential of physiological biomarkers collected from wearables and deep learning methods to be used for the continuous and unobtrusive assessments of mental health symptoms in older adults, including those with MCI. Trial registrationThis trial was registered with ClinicalTrials.gov (NCT05059353) on September 28, 2021, titled “Effectiveness and Safety of a Digitally Based Multidomain Intervention for Mild Cognitive Impairment”.

Natural Protein Photon Upconversion Supramolecular Assemblies for Background-Free Biosensing.

The diagnosis of disease biomarkers is crucial for the identification, monitoring, and prognostic assessment of malignant disease. However, biological samples with autofluorescence, complex components, and heterogeneity pose major challenges to reliable biosensing. Here, we report the self-assembly of natural proteins and the triplet-triplet annihilation upconversion (TTA-UC) pair to form upconverted protein clusters (∼8.2 ± 1.1 nm), which were further assembled into photon upconversion supramolecular assemblies (PUSA). This PUSA exhibited unique features, including a small size (∼44.1 ± 4.1 nm), oxygen tolerance, superior biocompatibility, and easy storage via lyophilization, all of which are long sought after for photon upconversion materials. Further, we have revealed that the steric hindrance of the annihilator suppresses the stacking of the annihilator in PUSA, which is vital for maintaining the water dispersibility and enhancing the upconversion performance of PUSA. In conjunction with sarcosine oxidase, this near infrared (NIR)-excitable PUSA nanoprobe could perform background-free biosensing of urinary sarcosine, which is a common biomarker for prostatic carcinoma (PCa). More importantly, this nanoprobe not only allows for qualitative identification of urinary samples from PCa patients by the unaided eye under NIR-light-emitting diode (LED) illumination but also quantifies the concentration of urinary sarcosine. These remarkable findings have propelled photon upconversion materials to a new evolutionary stage and expedited the progress of upconversion biosensing in clinical diagnostics.

Research progress on humoral biomarkers of Alzheimer's disease: A review.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive memory loss. The main pathological features are neuronal fibrillary tangles caused by amyloid beta deposition and hyperphosphorylation of tau protein, accompanied by neuronal death and loss of synaptic structure. Early diagnosis is the key to the treatment of AD. It is known that some small molecular components are related to the pathogenesis of AD. This article will summarize the common AD biomarkers in cerebrospinal fluid and blood and analyze the current status of AD biomarkers and future research directions. This review summarizes the promising biomarkers for the diagnosis of AD in the last decade and describes their changes in AD body fluids. The diagnostic biomarkers related to AD were mainly distributed in cerebrospinal fluid and blood. Significant changes in these molecules can be detected in cerebrospinal fluid and blood, and they are correlated with AD severity. These humoral molecules have necessary relationship with AD and can be used as AD biomarkers to assist early diagnosis of AD.

Identification of common biomarkers affecting patient survival in cancers

Identification of common biomarkers affecting patient survival in cancers

Identifying Universal Fish Biomarker Genes in Response to PCB126 Exposure by Comparative Transcriptomic Analyses.

Water pollution remains a major environmental concern, with increased toxic by-products being released into water bodies. Many of these chemical contaminants persist in the environment and bio-accumulate in aquatic organisms. At present, toxicological tests are mostly based on laboratory tests, and effective methods for monitoring wild aquatic environments remain lacking. In the present study, we used a well-characterized toxic chemical, 3,3',4,4',5-polychlorinated biphenyl (PCB126), as an example to try to identify common biomarker genes to be used for predictive toxicity of this toxic substance. First, we used two laboratory fish models, the zebrafish (Danio rerio) and medaka (Oryzias latipes), to expose PCB126 to obtain liver transcriptomic data by RNA-seq. Comparative transcriptomic analyses indicated generally conserved and concerted changes from the two species, thus validating the transcriptomic data for biomarker gene selection. Based on the common up- and downregulated genes in the two species, we selected nine biomarker genes to further test in other fish species. The first validation experiment was carried out using the third fish species, Mozambique tilapia (Oreochromis mossambicus), and essentially, all these biomarker genes were validated for consistent responses with the two laboratory fish models. Finally, to develop universal PCR primers suitable for potentially all teleost fish species, we designed degenerate primers and tested them in the three fish species as well as in another fish species without a genomic sequence available: guppy (Poecilia reticulata). We found all the biomarker genes showed consistent response to PCB126 exposure in at least 50% of the species. Thus, our study provides a promising strategy to identify common biomarker genes to be used for teleost fish analyses. By using degenerate PCR primers and analyzing multiple biomarker genes, it is possible to develop diagnostic PCR arrays to predict water contamination from any wild fish species sampled in different water bodies.