Strategic nucleic acid detection approaches for diagnosing African swine fever (ASF): navigating disease dynamics.

African swine fever (ASF) is a devastating disease caused by African swine fever virus (ASFV) and leads to significant economic losses in the pig farming industry. Given the absence of an effective vaccine or treatment, the mortality rate of ASF is alarmingly close to 100%. Consequently, the ability to rapidly and accurately detect ASFV on site and promptly identify infected pigs is critical for controlling the spread of this pandemic. The dynamics of the ASF virus load and antibody response necessitate the adoption of various detection strategies at different stages of infection, a topic that has received limited attention to date. This review offers detailed guidance for choosing appropriate ASF diagnostic techniques tailored to the clinical manifestations observed from the acute to chronic phases, including asymptomatic cases. We comprehensively summarize and evaluate the latest advancements in ASFV detection methods, such as CRISPR-based diagnostics, biosensors, and microfluidics. Additionally, we address the challenges of false negatives or positives due to ASF variants or the use of injected live attenuated vaccines. This review provides an exhaustive list of diagnostic tests suitable for detecting each stage of symptoms and potential target genes for developing new detection methods. In conclusion, we highlight the current challenges and future directions in ASFV detection, underscoring the need for continued research and innovation in this field.

Aronia melanocarpa extract extends the lifespan and health-span of Caenorhabditis elegans via mitogen-activated protein kinase 1.

Aging is a highly complex process and one of the largest risk factors for many chronic diseases. Aronia melanocarpa (AM) is rich in bioactive phytochemicals with antioxidant, anti-inflammatory, and anticancer properties. However, little is known about its effects on aging. The objective of this study was to evaluate the effects of AM extract on lifespan and health-span using Caenorhabditis elegans as a representative model. The mechanisms of its effects were explored using transcriptomics and untargeted metabolomics. Results showed that the lifespan of C. elegans was significantly extended by 22.2% after high-dose AM treatment. AM improved the behavior and physiological functions of C. elegans by increasing the pharyngeal pumping rate, decreasing lipofuscin accumulation and the reactive oxygen species level, enhancing resistance to oxidative stress, and increasing the activities of superoxide dismutase and catalase. Transcriptome analysis showed that the pmk-1 gene (mitogen-activated protein kinase 1), which is involved in the MAPK signaling pathway, was the gene with the largest fold change after AM intervention. However, in the C. elegans pmk-1(km25) mutant, the beneficial effect of AM in improving nematode senescence disappeared. An untargeted metabolomics study showed that the levels of 4-hydroxyproline, rhamnose, and cysteine were increased after AM supplementation, and their extending effect on the lifespan and health-span of C. elegans were partly dependent on the pmk-1 gene. In conclusion, our results revealed that AM can promote the lifespan and health-span of C. elegans via the PMK-1 pathway, highlighting the potential of AM as a dietary supplement to delay aging.

[Clinical Validation of a Prototype Smart Non-Invasive Pregnancy Glucose Monitor].

The aim of this study is to evaluate the effectiveness of a smart non-invasive blood glucose monitor prototype during pregnancy through clinical validation. The monitor utilizes near-infrared spectroscopy combined with AI big data analysis of photoelectric volumetric pulse wave data to achieve non-invasive monitoring of blood glucose in women during pregnancy. The research team developed a monitor that employs a sensing chip, effectively overcoming the problems of weak signals and individual differences in non-invasive blood glucose monitoring. The user experience is enhanced by visualizing the test results on the accompanying cell phone APP (application) of the smart non-invasive pregnancy blood glucose monitor. Clinical validation revealed that the non-invasive monitoring data for pregnant women aged 20~30 years significantly differed from those obtained via traditional blood glucose measurement methods, whereas no significant difference ( P<0.05) was observed for pregnant women aged 31~42 years. The study concluded that further calibration of the monitor and an expansion of the sample size are necessary to enhance consistency with invasive glucose monitoring results.

Interactions between Gut Microbiota and Natural Bioactive Polysaccharides in Metabolic Diseases: Review.

The gut microbiota constitutes a complex ecosystem, comprising trillions of microbes that have co-evolved with their host over hundreds of millions of years. Over the past decade, a growing body of knowledge has underscored the intricate connections among diet, gut microbiota, and human health. Bioactive polysaccharides (BPs) from natural sources like medicinal plants, seaweeds, and fungi have diverse biological functions including antioxidant, immunoregulatory, and metabolic activities. Their effects are closely tied to the gut microbiota, which metabolizes BPs into health-influencing compounds. Understanding how BPs and gut microbiota interact is critical for harnessing their potential health benefits. This review provides an overview of the human gut microbiota, focusing on its role in metabolic diseases like obesity, type II diabetes mellitus, non-alcoholic fatty liver disease, and cardiovascular diseases. It explores the basic characteristics of several BPs and their impact on gut microbiota. Given their significance for human health, we summarize the biological functions of these BPs, particularly in terms of immunoregulatory activities, blood sugar, and hypolipidemic effect, thus providing a valuable reference for understanding the potential benefits of natural BPs in treating metabolic diseases. These properties make BPs promising agents for preventing and treating metabolic diseases. The comprehensive understanding of the mechanisms by which BPs exert their effects through gut microbiota opens new avenues for developing targeted therapies to improve metabolic health.

Identification and validation of leukemia inhibitory factor as a protective factor in ischemic acute kidney injury.

BACKGROUND: Ischemia-reperfusion injury (IRI) is a common pathophysiological mechanism of acute kidney injury (AKI). There is an urgent need for a more comprehensive analysis of its underlying mechanisms. MATERIALS AND METHODS: The RNA-sequencing dataset GSE153625 was used to examine differentially expressed genes (DEGs) of kidney tissues in IRI-AKI mice compared with sham mice. We used 10 algorithms provided by cytohubba plugin and four external datasets (GSE192532, GSE52004, GSE98622, and GSE185383) to screen for hub genes. The IRI-AKI mouse model with different reperfusion times was established to validate the expression of hub gene in the kidneys. HK-2 cells were cultured in vitro under hypoxia/reoxygenation (H/R) conditions, via transfection with si-LIF or supplementation with the LIF protein to explore the function of the LIF gene. RESULTS: We screened a total of 1,540 DEGs in the IRI group compared with the sham group and identified that the LIF hub gene may play potential roles in IRI-AKI. LIF was markedly upregulated in the kidney tissues of IRI-AKI mice, as well as in HK-2 cells grown under H/R conditions. The knockdown of LIF aggravated apoptosis and oxidative stress (OS) injury under H/R conditions. Administration of the LIF protein rescued the effects of si-LIF, alleviating cellular apoptosis and OS. CONCLUSION: These findings indicate an important role of the LIF gene in term of regulating apoptosis and OS in the early phases of IRI-AKI. Targeting LIF may therefore represent a promising therapeutic strategy for IRI-AKI.

Enterococci independently increase the risk for initial antibiotic treatment failure and prolonged hospitalization in adult patients with complicated urinary tract infection: a retrospective cohort study.

OBJECTIVES: We aimed to investigate the impact of enterococci on initial antibiotic treatment (IAT) failure and prolonged hospitalization in complicated urinary tract infection (cUTI) cases, and to identify risk factors for enterococcal cUTI. METHODS: Adult cUTI patients were analyzed to compare the differences between the Enterococcus and non-Enterococcus groups. Univariate and multivariate analyses were employed to identify independent risk factors. RESULTS: This study included 419 patients, with the Enterococcus group showing significantly higher IAT failure rates and an extended average length of stay by 4.4 days compared to the non-Enterococcus group. Multivariate analysis identified enterococci, hospital-acquired UTIs (HA-UTI), indwelling catheters, and bed rest (bedridden) as independent risk factors for IAT failure. Enterococci were notably linked to prolonged hospitalization, other independent risk factors included IAT failure, prior antimicrobial use, age-adjusted Charlson comorbidity index (ACCI) ≥ 4, hypoalbuminemia, and bed rest. Urological cancer, HA-UTI, indwelling catheters, urinary retention, and urologic surgery were risk factors for enterococcal cUTI. CONCLUSION: We provide the first evidence that enterococci independently increase the risk for IAT failure and prolonged hospitalization in adults with cUTIs, highlighting the significance of timely identification to optimize measures including antibiotic regimens. Risk factors for enterococcal cUTI have also been identified to aid clinicians in managing this condition.

Differences in gray matter atrophy and functional connectivity between motor subtypes of Parkinson's disease.

Parkinson's disease (PD) patients with postural gait abnormalities exhibit poorer motor function scores, more severe non-motor symptoms, faster cognitive function deterioration, and a less favorable response to drugs and surgery compared to PD patients with tremor. This discrepancy is believed to be associated with more pronounced gray matter atrophy and abnormal functional connectivity. To investigate the distinctive pathological mechanisms between PD subtypes, we examined gray matter volume (GMV) and functional connectivity in patients with Parkinson's disease presenting with postural instability/gait difficulty (PD-PIGD), patients with tremor-dominant Parkinson's disease (PD-TD), and healthy controls. Voxel-based morphometry (VBM) of T1-weighted images was conducted to compare GMV among 64 PD-PIGD patients, 44 PD-TD patients, and 32 controls. Subsequently, functional connectivity within regions showing reduced GMV was compared across the groups. We analyzed whether differences among the groups were associated with clinical characteristics and neuroimaging biomarkers using partial correlation and binary logistic regression. Our comparison between PD-PIGD and PD-TD patients revealed a link between PD-PIGD and more extensive frontotemporal atrophy, potentially indicating increased basal ganglia activity accompanied by decreased cerebellum activity. Furthermore, in addition to the smaller GMV in the left middle temporal gyrus, the increased functional connectivity between this brain region and the right caudate was also the independent risk factor for PD-PIGD. In addition, we compared brain network connectivity between the PIGD and TD subtypes, using an independent component analysis (ICA). We found that Compared to PD-TD, PD-PIGD patients showed an enhanced sensorimotor network (SMN) around the left supplementary motor area. These findings suggest that severe gray matter atrophy and abnormal functional connectivity and brain networks may serve as pathophysiological mechanisms distinguishing PD-PIGD patients from other subtypes.

Integrating Mendelian Randomization with Single-cell Sequencing Data Reveals the Causal Effect and Related Mechanisms of Smoking on Parkinson's Disease.

INTRODUCTION: Smoking (nicotine) has been reported to possibly be neuroprotective and conducive to patients with early Parkinson's disease (PD). However, the causal effect of smoking on PD and the molecular mechanisms of smoking-related genes (SRGs) are vague. METHODS: First, genome-wide association study summary data on smoking (ukb-b-6244) and PD (ieu-b-7) were retrieved from the Integrative Epidemiology Unit OpenGWAS database for Mendelian randomization (MR) analysis. Sensitivity analyses were performed to validate the results of the MR analyses. Subsequently, a differential analysis of PD patients and controls was performed to identify differentially expressed SRGs (DE-SRGs). Finally, the expression of DE-SRGs was analyzed in annotated cell types. RESULTS: The MR analysis revealed that smoking was a protective factor causally related to PD (P=0.008, odds ratio=0.288). Furthermore, a total of five DE-SRGs enriched in Toll-like receptor signaling pathways were identified in GSE7621 dataset. Regarding single-cell analysis of GSE184950 dataset, a total of nine cell types were annotated. The expression of LRRN1 in oligodendrocyte progenitor cells and oligodendrocytes, respectively, differed significantly between PD patients and controls. CONCLUSIONS: Our study supported a causal relationship between smoking and PD and found that five SRGs (MAPK8IP1, LRRN1, LINC00324, HIST1H2BK, and YOD1) enriched in Toll-like receptor signaling pathways might be beneficial in PD. In addition, single-cell sequencing indicated that four SRGs were differentially expressed in different cell types. All four genes except MAPK8IP1 were significantly correlated with the 10 genes calculated by scPagwas. Thus, this evidence provides a theoretical basis for further research on the effect of nicotine (smoking) on PD. IMPLICATIONS: In order to explore the potential etiology and pathogenesis of Parkinson's disease, this study combined Mendelian randomization, transcriptomics and single-cell sequencing analysis to explore the association between exposure factors and Parkinson's disease, observe and confirm the relationship and mechanism between the two from the perspective of genetics, and provide more reliable evidence for causal inference.

Chrysanthemum morifolium Ramat extract and probiotics combination ameliorates metabolic disorders through regulating gut microbiota and PPARα subcellular localization.

BACKGROUND: Chrysanthemum morifolium Ramat, a traditional Chinese medicine, has the effects on liver clearing, vision improving, and anti-inflammation. C. morifolium and probiotics have been individually studied for their beneficial effects on metabolic diseases. However, the underlying molecular mechanisms were not completely elucidated. This study aims to elucidate the potential molecular mechanisms of C. morifolium and probiotics combination (CP) on alleviating nonalcoholic fatty liver disease (NAFLD) and the dysregulation of glucose metabolism in high-fat diet (HFD)-fed mice. METHODS: The therapeutic effect of CP on metabolism was evaluated by liver histology and serum biochemical analysis, as well as glucose tolerance test. The impact of CP on gut microbiota was analyzed by 16S rRNA sequencing and fecal microbiota transplantation. Hepatic transcriptomic analysis was performed with the key genes and proteins validated by RT-qPCR and western blotting. In addition, whole body Pparα knockout (Pparα-/-) mice were used to confirm the CP-mediated pathway. RESULTS: CP supplementation ameliorated metabolic disorders by reducing body weight and hepatic steatosis, and improving glucose intolerance and insulin resistance in HFD fed mice. CP intervention mitigated the HFD-induced gut microbiota dysbiosis, which contributed at least in part, to the beneficial effect of improving glucose metabolism. In addition, hepatic transcriptomic analysis showed that CP modulated the expression of genes associated with lipid metabolism. CP downregulated the mRNA level of lipid droplet-binding proteins, such as Cidea and Cidec in the liver, leading to more substrates for fatty acid oxidation (FAO). Meanwhile, the expression of CPT1α, the rate-limiting enzyme of FAO, was significantly increased upon CP treatment. Mechanistically, though CP didn't affect the total PPARα level, it promoted the nuclear localization of PPARα, which contributed to the reduced expression of Cidea and Cidec, and increased expression of CPT1α, leading to activated FAO. Moreover, whole body PPARα deficiency abolished the anti-NAFLD effect of CP, suggesting the importance of PPARα in CP-mediated beneficial effect. CONCLUSION: This study revealed the hypoglycemic and hepatoprotective effect of CP by regulating gut microbiota composition and PPARα subcellular localization, highlighting its potential for therapeutic candidate for metabolic disorders.

Integration of Hollow Microneedle Arrays with Jellyfish-Shaped Electrochemical Sensor for the Detection of Biomarkers in Interstitial Fluid.

This study integrates hollow microneedle arrays (HMNA) with a novel jellyfish-shaped electrochemical sensor for the detection of key biomarkers, including uric acid (UA), glucose, and pH, in artificial interstitial fluid. The jellyfish-shaped sensor displayed linear responses in detecting UA and glucose via differential pulse voltammetry (DPV) and chronoamperometry, respectively. Notably, the open circuit potential (OCP) of the system showed a linear variation with pH changes, validating its pH-sensing capability. The sensor system demonstrates exceptional electrochemical responsiveness within the physiological concentration ranges of these biomarkers in simulated epidermis sensing applications. The detection linear ranges of UA, glucose, and pH were 0~0.8 mM, 0~7 mM, and 4.0~8.0, respectively. These findings highlight the potential of the HMNA-integrated jellyfish-shaped sensors in real-world epidermal applications for comprehensive disease diagnosis and health monitoring.

The combined use of B vitamins and probiotics promotes B vitamin absorption and increases Akkermansia abundance.

B vitamins and probiotics are commonly used dietary supplements with well-documented health benefits. However, their potential interactions remain poorly understood. This study aims to explore the effects and underlying mechanisms of the combined use of B vitamins and probiotics by liquid chromatography-triple quadrupole mass spectrometry analysis, pharmacokinetic modeling, and 16S rRNA gene sequencing. By intragastric administration of seven B vitamins and three Lactobacillus strains to healthy rats (n = 8 per group), we found that probiotics significantly promoted the absorption (by approximately 14.5% to 71.2%) of vitamins B1, B3, B5, and B12. By conducting in vitro experiments (n = 3 per group) and a pseudo-germ-free rat model-based pharmacokinetic study (n = 6 per group), we confirmed that probiotics primarily enhanced the B vitamin absorption through gut microbiota-mediated mechanisms, rather than by directly producing B vitamins. Furthermore, we evaluated the effects of B vitamins and probiotics on the colon and gut microbiota by treating the pseudo-germ-free rats with blank solution, B vitamins, probiotics, and B vitamins + probiotics (n = 5 per group), respectively. Histopathological examination showed that the combination of B vitamins and probiotics synergistically alleviated the rat colon damage. High-throughput genetic sequencing also revealed the synergistic effect of B vitamins and probiotics in modulating the gut microbiota, particularly increasing the abundance of Verrucomicrobia and Akkermansia. In summary, the combined administration of B vitamins and probiotics may have a higher efficacy than using them alone.

Electrochemical biosensor based on RNA aptamer and ferrocenecarboxylic acid signal probe for C-reactive protein detection.

Monitoring health-related biomarkers using fast and facile detection techniques provides key physicochemical information for disease diagnosis or reflects body health status. Among them, electrochemical detection of various bio-macromolecules, e.g., the C-reactive protein (CRP), is of great interest in offering potential diagnosis for acute inflammation caused by infections, heart diseases, etc. Herein, a novel electrochemical aptamer biosensor was constructed from Ti3C2Tx MXene and in-situ reduced Au NPs for thiolated-RNA aptamer immobilization and CRP protein detection using Fc(COOH) as the signal probe. The sensory performances for CRP detection were optimized based on working conditions, including the incubation times and the pH. The large surface area offered by Ti3C2Tx MXene and high electrical conductivity originating from Au NPs endowed the as-fabricated aptamer biosensor with a decent sensitivity for CRP in a wide linear range of 0.05-80.0 ng/mL, good selectivity over interfering substances, and a low detection limit of 0.026 ng/mL. Such aptamer biosensors also detected CRP in serum samples using the spike & recovery method with reasonable recovery rates. The results demonstrated the potential of the as-fabricated electrochemical aptamer biosensor for fast and facile CRP detection in practical applications.

An innovative label-free electrochemical aptamer sensor: utilizing Ti3C2Tx/MoS2/Au NPs for accurate interleukin-6 detection.

In the medical field, changes in interleukin-6 (IL-6) concentration serve as essential biomarkers for monitoring and diagnosing various conditions, including acute inflammatory responses such as those seen in trauma and burns, and chronic illnesses like cancer. This paper detailed a label-free electrochemical aptamer sensor designed for IL-6 quantification. A composite material consisting of Ti3C2Tx and MoS2 was successfully synthesized to fabricate this sensor. The synergistic effect of MoS2's catalytic action on hydrogen peroxide (H2O2), used as a signalling marker, when combined with the exceptional conductivity and large specific surface area of Ti3C2Tx, not only enables an increased loading of MoS2 but also significantly boosts the electrochemical response. The in situ-reduced Au NPs provided stable immobilization sites for DNA aptamers (DNAapt) and facilitated electron transfer, ensuring accurate IL-6 recognition. Under optimal conditions, the aptamer sensor exhibited a wide linear range (5 pg/mL to 100 ng/mL) and a low limit of detection (LOD) of 2.9 pg/mL. Its sensing performance in human serum samples highlights its potential as a promising clinical analysis tool.

Identification of the CD8 + T-cell Related Signature for Predicting the Prognosis of Gastric Cancer Based on Integrated Analysis of Bulk and Single-cell RNA Sequencing Data.

The infiltration of CD8 + T cells in the tumor microenvironment is associated with better survival and immunotherapy response. However, their roles in gastric cancer have not been explored so far. In here, the profiles of GC gene expression were collected from The Cancer Genome Atlas database. Single-cell transcriptomic data originated from GSE134520. Cell clustering, annotation, and CD8 + T-cell differential genes were from the TISCH database. We determined 896 CD8 + T-cell differential genes by scRNA-seq analysis. After integrating immune-related genes, 174 overlapping genes were obtained and a novel risk model was subsequently built. The performance of CD8 + T-cell-associated gene signature was assessed in the training and external validation sets. The gene signature showed independent risk factors of overall survival for GC. A quantitative nomogram was built to enhance the clinical efficacy of this signature. Furthermore, low-risk individuals showed higher mutation status, higher immune checkpoint expression, low Tumour Immune Dysfunction and Exclusion (TIDE) scores, and higher IPS-PD-1 combined IPS-CTLA4 scores, indicating a greater response to immunotherapy. In addition, analysis of IMvigor210 immunotherapy cohort demonstrated that low-risk individuals had a favorable response to prognosis and immunotherapy. In conclusion, we generated a CD8 + T-cell-related signature that can serve as a promising tool for personalized prognosis prediction and guiding decisions regarding immunotherapy in GC patients.

Treatment of a Patient with Acute Promyelocytic Leukemia with Multiple Isolated Relapses in the Central Nervous System: A Case Report and Mini-Review of the Literature.

The efficacy of therapeutics for acute promyelocytic leukemia (APL) has exhibited an increase in recent years. Only a few patients experience relapse, including extramedullary relapse, and in patients with extramedullary relapse, the central nervous system (CNS) is the most common site. To date, there is no expert consensus or clinical guidelines available for CNS relapse, at least to the best of our knowledge. The optimal therapeutic strategy and management options for these patients remain unclear. The present study reports the treatment of a patient with APL with multiple isolated relapses in the CNS. In addition, through a mini-review of the literature, the present study provides a summary of various reports of this disease and discusses possible treatment options for these patients.

Matched Stochastic Resonance Enhanced Underwater Passive Sonar Detection under Non-Gaussian Impulsive Background Noise.

Remote passive sonar detection with low-frequency band spectral lines has attracted much attention, while complex low-frequency non-Gaussian impulsive noisy environments would strongly affect the detection performance. This is a challenging problem in weak signal detection, especially for the high false alarm rate caused by heavy-tailed impulsive noise. In this paper, a novel matched stochastic resonance (MSR)-based weak signal detection model is established, and two MSR-based detectors named MSR-PED and MSR-PSNR are proposed based on a theoretical analysis of the MSR output response. Comprehensive detection performance analyses in both Gasussian and non-Gaussian impulsive noise conditions are presented, which revealed the superior performance of our proposed detector under non-Gasussian impulsive noise. Numerical analysis and application verification have revealed the superior detection performance with the proposed MSR-PSNR detector compared with energy-based detection methods, which can break through the high false alarm rate problem caused by heavy-tailed impulsive noise. For a typical non-Gasussian impulsive noise assumption with α=1.5, the proposed MSR-PED and MSR-PSNR can achieve approximately 16 dB and 22 dB improvements, respectively, in the detection performance compared to the classical PED method. For stronger, non-Gaussian impulsive noise conditions corresponding to α=1, the improvement in detection performance can be more significant. Our proposed MSR-PSNR methods can overcome the challenging problem of a high false alarm rate caused by heavy-tailed impulsive noise. This work can lay a solid foundation for breaking through the challenges of underwater passive sonar detection under non-Gaussian impulsive background noise, and can provide important guidance for future research work.

Fabrication and mechanical modelling of dissolvable PVA/PVP composite microneedles with biocompatibility for efficient transdermal delivery of ibuprofen.

Microneedles offer minimally invasive, user-friendly, and subcutaneously accessible transdermal drug delivery and have been widely investigated as an effective transdermal delivery system. Ibuprofen is a common anti-inflammatory drug to treat chronic inflammation. It is crucial to develop microneedle patches capable of efficiently delivering ibuprofen through the skin for the effective treatment of arthritis patients requiring repeated medication. In this study, the mechanical properties of a new type of polymer microneedle were studied by finite element analysis, and the experimental results showed that the microneedle could effectively deliver drugs through the skin. In addition, a high ibuprofen-loaded microneedle patch was successfully prepared by micromolding and subjected to evaluation of its infrared spectrum morphology and dissolve degree. The morphology of microneedles was characterized by scanning electron microscopy, and the mechanical properties were assessed using a built linear stretching system. In the in-vitro diffusion cell drug release test, the microneedle released 85.2 ± 1.52% (210 ± 3.7 µg) ibuprofen in the modified Franz diffusion within 4 h, exhibiting a higher drug release compared to other drug delivery methods. This study provides a portable, safe and efficient treatment approach for arthritis patients requiring daily repeated medication.

MRI brain structural and functional networks changes in Parkinson disease with REM sleep behavior disorders.

Background: Rapid eye movement sleep behavior disorder (RBD) is common in individuals with Parkinson's disease (PD). In spite of that, the precise mechanism underlying the pathophysiology of RBD among PD remains unclear. Objective: The aim of the present study was to analyze gray matter volumes (GMVs) as well as the changes of functional connectivity (FC) among PD patients with RBD (PD-RBD) by employing a combination of voxel-based morphometry (VBM) and FC methods. Methods: A total of 65 PD patients and 21 healthy control (HC) subjects were included in this study. VBM analyses were performed on all subjects. Subsequently, regions with significant different GMVs between PD patients with and without RBD (PD-nRBD) were selected for further analysis of FC. Correlations between altered GMVs and FC values with RBD scores were also investigated. Additionally, receiver operating characteristic (ROC) curves were employed for the evaluation of the predictive value of GMVs and FC in identifying RBD in PD. Results: PD-RBD patients exhibited lower GMVs in the left middle temporal gyrus (MTG) and bilateral cuneus. Furthermore, we observed higher FC between the left MTG and the right postcentral gyrus (PoCG), as well as lower FC between the bilateral cuneus (CUN) and the right middle frontal gyrus (MFG) among PD-RBD patients in contrast with PD-nRBD patients. Moreover, the GMVs of MTG (extending to the right PoCG) was positively correlated with RBD severity [as measured by REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) score]. Conversely, the FC value between the bilateral CUN and the right MTG in PD-RBD patients was negatively correlated with RBDSQ score. Conclusion: This study revealed the presence replace with GMV and FC changes among PD-RBD patients, which were closely linked to the severity of RBD symptoms. Furthermore, the combination of basic clinical characteristics, GMVs and FC values effectively predicted RBD for individuals with PD.

Advances of Transition Metal-Based Electrochemical Non-enzymatic Glucose Sensors for Glucose Analysis: A Review.

Glucose concentration is a crucial parameter for assessing human health. Over recent years, non-enzymatic electrochemical glucose sensors have drawn considerable attention due to their substantial progress. This review explores the common mechanism behind the transition metal-based electrocatalytic oxidation of glucose molecules through classical electrocatalytic frameworks like the Pletcher model and the Hydrous Oxide-Adatom Mediator model (IHOAM), as well as the redox reactions at the transition metal centers. It further compiles the electrochemical characterization techniques, associated formulas, and their ensuing conclusions pertinent to transition metal-based non-enzymatic electrochemical glucose sensors. Subsequently, the review covers the latest advancements in the field of transition metal-based active materials and support materials used in non-enzymatic electrochemical glucose sensors in the last decade (2014-2023). Additionally, it presents a comprehensive classification of representative studies according to the active metal catalysts components involved.

Pedestrian-Accessible Infrastructure Inventory: Enabling and Assessing Zero-Shot Segmentation on Multi-Mode Geospatial Data for All Pedestrian Types.

In this paper, a Segment Anything Model (SAM)-based pedestrian infrastructure segmentation workflow is designed and optimized, which is capable of efficiently processing multi-sourced geospatial data, including LiDAR data and satellite imagery data. We used an expanded definition of pedestrian infrastructure inventory, which goes beyond the traditional transportation elements to include street furniture objects that are important for accessibility but are often omitted from the traditional definition. Our contributions lie in producing the necessary knowledge to answer the following three questions. First, how can mobile LiDAR technology be leveraged to produce comprehensive pedestrian-accessible infrastructure inventory? Second, which data representation can facilitate zero-shot segmentation of infrastructure objects with SAM? Third, how well does the SAM-based method perform on segmenting pedestrian infrastructure objects? Our proposed method is designed to efficiently create pedestrian-accessible infrastructure inventory through the zero-shot segmentation of multi-sourced geospatial datasets. Through addressing three research questions, we show how the multi-mode data should be prepared, what data representation works best for what asset features, and how SAM performs on these data presentations. Our findings indicate that street-view images generated from mobile LiDAR point-cloud data, when paired with satellite imagery data, can work efficiently with SAM to create a scalable pedestrian infrastructure inventory approach with immediate benefits to GIS professionals, city managers, transportation owners, and walkers, especially those with travel-limiting disabilities, such as individuals who are blind, have low vision, or experience mobility disabilities.