BACKGROUND: Striatal hyperdopaminergia is implicated in the pathoetiology of schizophrenia, but how this relates to dopaminergic midbrain activity is unclear. Neuromelanin-sensitive MRI (NM-MRI) provides a marker of long-term dopamine function. We examined if midbrain NM-MRI contrast-to-noise ratio (NM-CNR) was higher in people with schizophrenia relative to controls and if this correlated with dopamine synthesis capacity.
METHODS: N=154 participants (n=74 individuals with schizophrenia and n=80 healthy controls) underwent NM-MRI of the substantia nigra and ventral tegmental area (SN-VTA). A subset of the schizophrenia group (n=38) also received [18F]-DOPA PET to measure dopamine synthesis capacity (Kicer) in the SN-VTA and striatum.
RESULTS: SN-VTA NM-CNR was significantly higher in patients with schizophrenia relative to controls (effect size=0.38, p=0.019). This effect was greatest for voxels in the medial and ventral SN-VTA. In patients, SN-VTA Kicer positively correlated with SN-VTA NM-CNR (r=0.44, p=0.005) and striatal Kicer (r=0.71, p<0.001). Voxelwise analysis demonstrated that SN-VTA NM-CNR was positively associated with striatal Kicer (r=0.53, p=0.005) and that this relationship appeared strongest between the ventral SN-VTA and associative striatum in schizophrenia.
CONCLUSIONS: Our results suggest that neuromelanin levels are higher in patients with schizophrenia relative to controls, particularly in midbrain regions that project to parts of the striatum which receive innervation from the limbic and association cortices. The direct relationship between measures of neuromelanin and dopamine synthesis suggests that these aspects of schizophrenia pathophysiology are linked. Our findings highlight specific mesostriatal circuits as the loci of dopamine dysfunction in schizophrenia and, thus, potential therapeutic targets.

Transfer RNA-derived small RNAs (tsRNAs) are a class of small non-coding RNA (sncRNA) molecules derived from tRNA, including tRNA derived fragments (tRFs) and tRNA halfs (tiRNAs). tsRNAs can affect cell functions by participating in gene expression regulation, translation regulation, intercellular signal transduction, and immune response. They have been shown to play an important role in various human diseases, including cardiovascular diseases (CVDs). Targeted regulation of tsRNAs expression can affect the progression of CVDs. The tsRNAs induced by pathological conditions can be detected when released into the extracellular, giving them enormous potential as disease biomarkers. Here, we review the biogenesis, degradation process and related functional mechanisms of tsRNAs, and discuss the research progress and application prospects of tsRNAs in different CVDs, to provide a new perspective on the treatment of CVDs.

OBJECTIVE: To examine the associaiton between environmental measures and brain volumes and its potential mediators.
METHODS: This was a prospective study.
METHODS: Our analysis included 34,454 participants (53.4% females) aged 40-73 years at baseline (between 2006 and 2010) from the UK Biobank. Brain volumes were measured using magnetic resonance imaging between 2014 and 2019.
RESULTS: Greater proximity to greenspace buffered at 1000 m at baseline was associated with larger volumes of total brain measured 8.8 years after baseline assessment (standardized β (95% CI) for each 10% increment in coverage: 0.013(0.005,0.020)), grey matter (0.013(0.006,0.020)), and white matter (0.011(0.004,0.017)) after adjustment for covariates and air pollution. The corresponding numbers for natural environment buffered at 1000 m were 0.010 (0.004,0.017), 0.009 (0.004,0.015), and 0.010 (0.004,0.016), respectively. Similar results were observed for greenspace and natural environment buffered at 300 m. The strongest mediator for the association between greenspace buffered at 1000 m and total brain volume was smoking (percentage (95% CI) of total variance explained: 7.9% (5.5-11.4%)) followed by mean sphered cell volume (3.3% (1.8-5.8%)), vitamin D (2.9% (1.6-5.1%)), and creatinine in blood (2.7% (1.6-4.7%)). Significant mediators combined explained 18.5% (13.2-25.3%) of the association with total brain volume and 32.9% (95% CI: 22.3-45.7%) of the association with grey matter volume. The percentage (95% CI) of the association between natural environment and total brain volume explained by significant mediators combined was 20.6% (14.7-28.1%)).
CONCLUSIONS: Higher coverage percentage of greenspace and environment may benefit brain health by promoting healthy lifestyle and improving biomarkers including vitamin D and red blood cell indices.

Over the past decades, accumulating evidence suggests that the gut microbiome exerts a key role in Alzheimer\'s disease (AD). The Alzheimer\'s Association Workgroup is updating the diagnostic criteria for AD, which changed the profiles and categorization of biomarkers from \"AT(N)\" to \"ATNIVS.\" Previously, most of studies focus on the correlation between the gut microbiome and amyloid beta deposition (\"A\"), the initial AD pathological feature triggering the \"downstream\" tauopathy and neurodegeneration. However, limited research investigated the interactions between the gut microbiome and other AD pathogenesis (\"TNIVS\"). In this review, we summarize current findings of the gut microbial characteristics in the whole spectrum of AD. Then, we describe the association of the gut microbiome with updated biomarker categories of AD pathogenesis. In addition, we outline the gut microbiome-related therapeutic strategies for AD. Finally, we discuss current key issues of the gut microbiome research in the AD field and future research directions. HIGHLIGHTS: The new revised criteria for Alzheimer\'s disease (AD) proposed by the Alzheimer\'s Association Workgroup have updated the profiles and categorization of biomarkers from \"AT(N)\" to \"ATNIVS.\" The associations of the gut microbiome with updated biomarker categories of AD pathogenesis are described. Current findings of the gut microbial characteristics in the whole spectrum of AD are summarized. Therapeutic strategies for AD based on the gut microbiome are proposed.

The incidence of tumors in the human digestive system is relatively high, including esophageal cancer, liver cancer, pancreatic cancer, gastric cancer and colorectal cancer. These malignancies arise from a complex interplay of environmental and genetic factors. Among them, long non‑coding RNAs (lncRNAs), which cannot be translated into proteins, serve an important role in the development, progression, migration and prognosis of tumors. Small nucleolar RNA host gene 16 (SNHG16) is a typical lncRNA, and its relationship with digestive system tumors has been widely explored. The prevailing hypothesis suggests that the principal molecular mechanism of SNHG16 in digestive system tumors involves it functioning as a competitive endogenous RNA that interacts with other proteins, regulates various genes and influences a downstream target molecule. The present review summarizes recent research on the relationship between SNHG16 and numerous types of digestive system cancer, encompassing its biological functions, underlying mechanisms and potential clinical implications. Furthermore, it outlines the association between SNHG16 expression and pertinent risk factors, such as smoking, infection and diet. The present review indicated the promise of SNHG16 as a potential biomarker and therapeutic target in human digestive system cancer.

BACKGROUND: Blood-based biomarkers are a cost-effective and minimally invasive method for diagnosing the early and preclinical stages of amyloid positivity (AP). Our study aims to investigate our novel immunoprecipitation-immunoassay (IP-IA) as a test for predicting cognitive decline.
METHODS: We measured levels of amyloid beta (Aβ)X-40 and AβX-42 in immunoprecipitated eluates from the DELCODE cohort. Receiver-operating characteristic (ROC) curves, regression analyses, and Cox proportional hazard regression models were constructed to predict AP by Aβ42/40 classification in cerebrospinal fluid (CSF) and conversion to mild cognitive impairment (MCI) or dementia.
RESULTS: We detected a significant correlation between AßX-42/X-40 in plasma and CSF (r = 0.473). Mixed-modeling analysis revealed a substantial prediction of AßX-42/X-40 with an area under the curve (AUC) of 0.81 for AP (sensitivity: 0.79, specificity: 0.74, positive predictive value [PPV]: 0.71, negative predictive value [NPV]: 0.81). In addition, lower AβX-42/X-40 ratios were associated with negative PACC5 slopes, suggesting cognitive decline.
CONCLUSIONS: Our results suggest that assessing the plasma AβX-42/X-40 ratio via our semiautomated IP-IA is a promising biomarker when examining patients with early or preclinical AD.
CONCLUSIONS: New plasma Aβ42/Aβ40 measurement using immunoprecipitation-immunoassay Plasma Aβ42/Aβ40 associated with longitudinal cognitive decline Promising biomarker to detect subjective cognitive decline at-risk for brain amyloid positivity.

BACKGROUND: The understanding of neuropathic pain remains incomplete, highlighting the need for research on biomarkers for improved diagnosis and treatment. This review focuses on identifying potential biomarkers in blood and cerebrospinal fluid for neuropathic pain in different neuropathies.
METHODS: Searches were performed in six databases: PubMed, Web of Science, Scopus, Cochrane Library, EMBASE, and CINAHL. Included were observational studies, namely cross-sectional, cohort, and case-control, that evaluated quantitative biomarkers in blood or cerebrospinal fluid. Data were qualitatively synthesized, and meta-analyses were conducted using R. The study is registered with PROSPERO under the ID CRD42022323769.
RESULTS: The literature search resulted in 16 studies for qualitative and 12 for quantitative analysis, covering patients over 18 years of age with painful neuropathies. A total of 1403 subjects were analyzed, identifying no significant differences in levels of C-Reactive Protein (CRP), Interleukin-6 (IL-6), and Tumor Necrosis Factor-alpha (TNF-alpha) between patients with and without pain. Despite the high inter-rater reliability and adequate bias assessment, the results suggest negligible differences in inflammatory biomarkers, with noted publication bias and heterogeneity among studies, indicating the need for further research.
CONCLUSIONS: Our review underscores the complex nature of neuropathic pain and the challenges in identifying biomarkers, with no significant differences found in CRP, IL-6, and TNF-alpha levels between patients with and without pain. Despite methodological robustness, the results are limited by publication bias and heterogeneity. This emphasizes the need for further research to discover definitive biomarkers for improved diagnosis and personalized treatment of neuropathic pain.

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

Parkinsonian disorders, including Parkinson\'s disease (PD), multiple system atrophy (MSA), dementia with Lewy body (DLB), corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP) are often misdiagnosed due to overlapping symptoms and the absence of precise biomarkers. Furthermore, there are no current methods to ascertain the progression and conversion of prodromal conditions such as REM behaviour disorder (RBD). Extracellular vesicles (EVs), containing a mixture of biomolecules, have emerged as potential sources for parkinsonian diagnostics. However, inconsistencies in previous studies have left their diagnostic potential unclear. We conducted a meta-analysis, following PRISMA guidelines, to assess the diagnostic accuracy of general EVs isolated from various bodily fluids, including cerebrospinal fluid (CSF), plasma, serum, urine or saliva, in differentiating patients with parkinsonian disorders from healthy controls (HCs). The meta-analysis included 21 studies encompassing 1285 patients with PD, 24 with MSA, 105 with DLB, 99 with PSP, 101 with RBD and 783 HCs. Further analyses were conducted only for patients with PD versus HCs, given the limited number for other comparisons. Using bivariate and hierarchal receiver operating characteristics (HSROC) models, the meta-analysis revealed moderate diagnostic accuracy in distinguishing patients with PD from HCs, with substantial heterogeneity and publication bias. The trim-and-fill method revealed at least two missing studies with null or low diagnostic accuracy. CSF-EVs showed better overall diagnostic accuracy, while plasma-EVs had the lowest performance. General EVs demonstrated higher diagnostic accuracy compared to CNS-originating EVs, which are more time-consuming, labour- and cost-intensive to isolate. In conclusion, while holding promise, utilizing biomarkers in general EVs for PD diagnosis remains unfeasible due to existing challenges. The focus should shift toward harmonizing the field through standardization, collaboration, and rigorous validation. Current efforts by the International Society For Extracellular Vesicles (ISEV) aim to enhance the accuracy and reproducibility of EV-related research through rigor and standardization, aiming to bridge the gap between theory and practical clinical application.

High-resolution computed tomography (HRCT) imaging is critical for diagnostic evaluation of Idiopathic Pulmonary Fibrosis (IPF). However, several other interstitial lung diseases (ILDs) often exhibit radiologic pattern similar to IPF on HRCT making the diagnosis of the disease difficult. Therefore, biomarkers that distinguish IPF from other ILDs can be a valuable aid in diagnosis. Using mass spectrometry, we performed proteomic analysis of plasma extracellular vesicles (EVs) in patients diagnosed with IPF, chronic hypersensitivity pneumonitis, nonspecific interstitial pneumonitis, and healthy subjects. A five-protein signature was identified by lasso regression and was validated in an independent cohort using ELISA. The five-protein signature derived from mass spectrometry data showed an area under the receiver operating characteristic curve of 0.915 (95%CI: 0.819-1.011) and 0.958 (95%CI: 0.882-1.034) for differentiating IPF from other ILDs and from healthy subjects, respectively. Stepwise backwards elimination yielded a model with 3 and 2 proteins for discriminating IPF from other ILDs and healthy subjects, respectively, without compromising diagnostic accuracy. In summary, we discovered and validated EV protein biomarkers for differential diagnosis of IPF in independent cohorts. Interestingly, the biomarker panel could also distinguish IPF and healthy subjects with high accuracy. The biomarkers need to be evaluated in large prospective cohorts to establish their clinical utility.