Blood-based gene expression signatures could potentially be used as biomarkers for PD. However, it is unclear whether genetically-regulated transcriptomic signatures can provide novel gene candidates for use as PD biomarkers. We leveraged on the Genotype-Tissue Expression (GTEx) database to impute whole-blood transcriptomic expression using summary statistics of three large-scale PD GWAS. A random forest classifier was used with the consensus whole-blood imputed gene signature (IGS) to discriminate between cases and controls. Outcome measures included Area under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve. We demonstrated that the IGS (n = 37 genes) is conserved across PD GWAS studies and brain tissues. IGS discriminated between cases and controls in an independent whole-blood RNA-sequencing study (1176 PD, 254 prodromal, and 860 healthy controls) with mean AUC and accuracy of 64.8% and 69.4% for PD cohort, and 78.8% and 74% for prodromal cohort. PATL2 was the top-performing imputed gene in both PD and prodromal PD cohorts, whose classifier performance varied with biological sex (higher performance for males and females in the PD and prodromal PD, respectively). Single-cell RNA-sequencing studies (scRNA-seq) of healthy humans and PD patients found PATL2 to be enriched in terminal effector CD8+ and cytotoxic CD4+ cells, whose proportions are both increased in PD patients. We demonstrated the utility of GWAS transcriptomic imputation in identifying novel whole-blood transcriptomic signatures which could be leveraged upon for PD biomarker derivation. We identified PATL2 as a potential biomarker in both clinical and prodromic PD.
Background: Influenza is an acute respiratory infectious disease with a significant global disease burden. Additionally, the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions (NPIs) have introduced uncertainty to the spread of influenza. However, comparative studies on the performance of innovative models and approaches used for influenza prediction are limited. Therefore, this study aimed to predict the trend of influenza-like illness (ILI) in settings with diverse climate characteristics in China based on sentinel surveillance data using three approaches and evaluate and compare their predictive performance. Methods: The generalized additive model (GAM), deep learning hybrid model based on Gate Recurrent Unit (GRU), and autoregressive moving average-generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) model were established to predict the trends of ILI 1-, 2-, 3-, and 4-week-ahead in Beijing, Tianjin, Shanxi, Hubei, Chongqing, Guangdong, Hainan, and the Hong Kong Special Administrative Region in China, based on sentinel surveillance data from 2011 to 2019. Three relevant metrics, namely, Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and R squared, were calculated to evaluate and compare the goodness of fit and robustness of the three models. Results: Considering the MAPE, RMSE, and R squared values, the ARMA-GARCH model performed best, while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in China. Additionally, the models' predictive performance declined as the weeks ahead increased. Furthermore, blocked cross-validation indicated that all models were robust to changes in data and had low risks of overfitting. Conclusions: Our study suggested that the ARMA-GARCH model exhibited the best accuracy in predicting ILI trends in China compared to the GAM and GRU-based deep learning hybrid model. Therefore, in the future, the ARMA-GARCH model may be used to predict ILI trends in public health practice across diverse climatic zones, thereby contributing to influenza control and prevention efforts.
Addressing the need for modulated spin configurations is crucial, as they serve as the foundational building blocks for next-generation spintronics, particularly in atomically thin structures and at room temperature. In this work, we realize intrinsic ferromagnetism in monolayer flakes and tunable ferro-/antiferromagnetism in (Fe0.56Co0.44)5GeTe2 antiferromagnets. Remarkably, the ferromagnetic ordering (≥1 L) and antiferromagnetic ordering (≥4 L) remain discernible up to room temperature. The TC (â¼310 K) of the monolayer flakes sets a record high for known exfoliated monolayer van der Waals magnets. Within the framework of A-type antiferromagnetism, a notable odd-even layer-number effect at elevated temperatures (T = 150 K) is observed. Of particular interest is the strong ferromagnetic order in even-layer flakes at low temperatures. The intricate interplay among magnetic field strength, layer number, and temperature gives rise to a diverse array of phenomena, holding promise not only for new physics but also for practical applications.
Oncolytic viruses (OVs) represent an emerging immunotherapeutic strategy owing to their capacity for direct tumor lysis and induction of antitumor immunity. However, hurdles like transient persistence and moderate efficacy necessitate innovative approaches. Metabolic remodeling has recently gained prominence as a strategic intervention, wherein OVs or combination regimens could reprogram tumor and immune cell metabolism to enhance viral replication and oncolysis. In this review, we summarize recent advances in strategic reprogramming of tumor and immune cell metabolism to enhance OV-based immunotherapies. Specific tactics include engineering viruses to target glycolytic, glutaminolytic, and nucleotide synthesis pathways in cancer cells, boosting viral replication and tumor cell death. Additionally, rewiring T cell and NK cell metabolism of lipids, amino acids, and carbohydrates shows promise to enhance antitumor effects. Further insights are discussed to pave the way for the clinical implementation of metabolically enhanced oncolytic platforms, including balancing metabolic modulation to limit antiviral responses while promoting viral persistence and tumor clearance.
This research systematically assessed the changes in carbon, nitrogen and microbial profiling during pig and chicken manure transformation by black soldier fly larvae (BSFL) and subsequent composting process. BSFL had higher conversion efficiency for chicken manure. The pH, phosphorus and potassium contents in fresh BSFL frass increased than raw manure, but conductivity, total-/nitrate-/ammonium-nitrogen decreased. After BSFL conversion, pig manure had a larger nitrogen loss (25 %) while chicken manure had a larger carbon loss (32 %). During subsequent composting, the indicator changes (e.g. humus, ammonium nitrogen) in frass composts basically remained stable after 20-30 days. Compared to natural composts, frass composts had higher humification degree, cellulase activities, and more cellulose-degrading bacteria. Subsequent composting further reduced potential pathogens (reduced by 98.9 %-99.7 % than raw manure), and elevated the aromaticity and humification of frass. The findings gave an insight into the maturation management of manure-sourced insect frass.
High precision navigation and positioning technology, as a fundamental function, is gradually occupying an indispensable position in the various fields. However, a single sensor cannot meet the navigation requirements in different scenarios. This paper proposes a "plug and play" Vision/IMU/UWB multi-sensor tightly-coupled system based on factor graph. The difference from traditional UWB-based tightly-coupled models is that the Vision/IMU/UWB tightly-coupled model in this study uses UWB base station coordinates as parameters for real-time estimation without pre-calibrating UWB base stations. Aiming at the dynamic change of sensor availability in multi-sensor integrated navigation system and the serious problem of traditional factor graph in the weight distribution of observation information, this study proposes an adaptive robust factor graph model. Based on redundant measurement information, we propose a novel adaptive estimation model for UWB ranging covariance, which does not rely on prior information of the system and can adaptively estimate real-time covariance changes of UWB ranging. The algorithm proposed in this study was extensively tested in real-world scenarios, and the results show that the proposed system is superior to the most advanced combination method in all cases. Compared with the visual-inertial odometer based on the factor graph (FG-VIO), the RMSE is improved by 62.83 and 64.26% in scene 1 and 82.15, 70.32, and 75.29% in scene 2 (non-line-of-sight environment).
BACKGROUND: Rectal temperature (RT) is an important index of core temperature, which has guiding significance for the diagnosis and treatment of pet diseases. OBJECTIVES: Development and evaluation of an alternative method based on machine learning to determine the core temperatures of cats and dogs using surface temperatures. ANIMALS: 200 cats and 200 dogs treated between March 2022 and May 2022. METHODS: A group of cats and dogs were included in this study. The core temperatures and surface body temperatures were measured. Multiple machine learning methods were trained using a cross-validation approach and evaluated in one retrospective testing set and one prospective testing set. RESULTS: The machine learning models could achieve promising performance in predicting the core temperatures of cats and dogs using surface temperatures. The root mean square errors (RMSE) were 0.25 and 0.15 for cats and dogs in the retrospective testing set, and 0.15 and 0.14 in the prospective testing set. CONCLUSION: The machine learning model could accurately predict core temperatures for companion animals of cats and dogs using easily obtained body surface temperatures.
Body Temperature , Machine Learning , Animals , Cats/physiology , Dogs/physiology , Retrospective Studies , Male , Female , Prospective Studies
Kidney stones refer to abnormal crystal formation that occurs in the kidney. Among a variety of components of kidney stones, calcium oxalate (CaOx) is the most common type. Despite many efforts to investigate the pathogenesis of CaOx stones, the pathogenesis remains an issue of debate. With high occurrence and recurrence, individuals with stone formation are prone to frequently consult a doctor and to be hospitalized, and the treatment of kidney stones poses a heavy burden on the patients. Concerns should be focused not only on treatment but also on prevention. Herein, we reviewed the studies on prevention methods of CaOx stones through diet, lifestyle, and medication extending until the current time frame. As hyperoxaluria is the most common metabolic disorder among CaOx stone formations, we also included several studies on the treatment and prevention of hyperoxaluria. Our objective was to outline the effective methods to prevent renal CaOx stone formation.
Objectives: There has been a significant increase in subjective cognitive decline (SCD) studies in older adults over the years. A bibliometric analysis was conducted to demonstrate the current hotspots and emerging trends in SCD research in older adults and provide references for further research in this field. Methods: The study conducted a bibliometric analysis based on co-citation analysis. From the Web of Science Core Collection database, this study obtained 1,436 manuscripts regarding SCD in older adults published from 2003 to 2023. Software CiteSpace was used to analyse the results for countries, institutions, authors, journals, keywords, top-cited papers, and burst citations scientifically and intuitively. Results: Our result showed an overall upward trend in the volume of publications on SCD in the elderly population, suggesting that the study of SCD in older adults has attracted the attention of researchers. The United States dominates this research field, followed by China and France. The top three institutions were the University of California System, Institut National de la Sante et de la Recherche Medicale (Inserm), and UDICE-French Research Universities. Frank Jessen, Han Ying, and Kathryn Ellis were the top three researchers. The top three cited journals were Neurology, Alzheimers & Dementia, and Journal of Alzheimer's Disease. The keywords clustering were "depression", "functional connectivity", "cognitive reserve", "cognitive function", "physical activity", "recommendations", "dementia prevention", " behavioral disorders", "primary care", "early diagnosis", and "community-based study". Keywords with the highest citation bursts include "physical activity", "framework", "preclinical Alzheimer's disease", "future dementia", and "late life depression". Conclusions: Parallel to the growth trend, the range of research scopes and topics is expanding steadily, focusing on early screening and prevention, negative emotion, and symptom management, broadening researchers' perspectives, which can provide reference and guidance for nursing researchers to conduct research.
OBJECTIVE: To compare the detection rate and diagnostic accuracy of cardia polyps using endoscopy with blue laser imaging (BLI) and white-light imaging (WLI). METHODS: Patients were randomly divided into the BLI group and WLI group according to the endoscopic procedures. BLI followed by WLI was conducted in the BLI group, whereas WLI followed by BLI examination was conducted in the WLI group. The number, size, microstructure, and microvascular patterns of cardia polyps detected were recorded. Biopsy of the polyps was then performed. RESULTS: The detection rate of cardia polyps in the BLI group was higher than that in the WLI group (7.87% vs 4.22%, P = 0.018). The rate of overlooked lesions in the BLI group was lower than in the WLI group (0.64% vs 3.38%, P = 0.003). The diagnostic coincidence rate between magnifying BLI and histopathology was 88.16%. The sensitivity, specificity, positive predictive value and negative predictive value for the diagnosis of neoplastic lesions by magnifying endoscopy with BLI were 90.91%, 87.69%, 55.56%, and 98.28%, respectively. The most remarkable patterns for predicting inflammatory polyps were the prolonged and fine network patterns (sensitivity 71.43%, specificity 93.75%). Small round combined with honeycomb patterns were the most common among fundic gland polyps (sensitivity 80.00%, specificity 98.48%). Neoplastic lesions presented as villous or ridge-like combined with core vascular or unclear pattern for both microvascular and microstructure patterns. CONCLUSION: BLI is more effective than WLI in the detection and diagnosis of cardia polyps, and magnifying endoscopy with BLI may help diagnose such lesions.
Cardia , Feasibility Studies , Stomach Neoplasms , Humans , Female , Male , Middle Aged , Cardia/pathology , Cardia/diagnostic imaging , Adult , Stomach Neoplasms/diagnostic imaging , Stomach Neoplasms/diagnosis , Stomach Neoplasms/pathology , Aged , Polyps/diagnostic imaging , Polyps/diagnosis , Gastroscopy/methods , Sensitivity and Specificity , Predictive Value of Tests , Lasers
A concise and rapid detection method for Mycoplasma pneumoniae is urgently required due to its severe impact on human health. To meet such a need, this study proposed and constructed an innovative point-of-care testing (POCT) platform that consists of a hydrogen ion-selective loop-mediated isothermal amplification (H+-LAMP) sensor and an electrochemical detection device. The H+-LAMP sensor successfully integrated the working and reference electrodes and converted the H+ generated during the LAMP process into an electrochemical signal. High sensitivity and stability for pathogen detection were also achieved by treating the working electrode with an electrodeposited polyaniline solid contact layer and by using an ion-selective membrane. As a result, the sensor shows a sensitivity of 68.26 mV per pH, a response time of less than 2 s, and a potential drift of less than 5 mV within one hour, which well meets the urgent need. The results also demonstrated that the detection limit for Mycoplasma pneumoniae was lowered to 1 copy per µL, the nucleic acid extraction and detection process could be completed in 30 minutes, and the impact of interfering ions on the sensor was negligible. Validation with 20 clinical samples yielded satisfactory results. More importantly, the storage lifespan of such an electrochemical sensor is over seven days, which is a great advantage for on-site pathogen detection. Therefore, the hydrogen ion-selective sensor constructed in this investigation is particularly suitable as a core component for instant pathogen detection platforms.
A Lewis acid-promoted electrophilic thiocyanation/cyclization of ortho-alkynylanilines for the synthesis of indole derivatives has been developed. The reaction utilizes Me3SiBr as the Lewis acid and N-thiocyanatosuccinimide as the thiocyanation reagent. A series of 2-aryl-3-thiocyanato indoles were prepared in moderate to high yields under mild conditions without metals and oxidants. It provides an efficient protocol for the construction of the indole skeleton and C-SCN and C-N bonds in one step as well.
The vertebrate central nervous system (CNS) is the most complex system of the body. The CNS, especially the brain, is generally regarded as immune-privileged. However, the specialized immune strategies in the brain and how immune cells, specifically macrophages in the brain, respond to virus invasion remain poorly understood. Therefore, this study aimed to examine the potential immune response of macrophages in the brain of orange-spotted groupers (Epinephelus coioides) following red-spotted grouper nervous necrosis virus (RGNNV) infection. We observed that RGNNV induced macrophages to produce an inflammatory response in the brain of orange-spotted grouper, and the macrophages exhibited M1-type polarization after RGNNV infection. In addition, we found RGNNV-induced macrophage M1 polarization via the CXCR3.2- CXCL11 pathway. Furthermore, we observed that RGNNV triggered M1 polarization in macrophages, resulting in substantial proinflammatory cytokine production and subsequent damage to brain tissue. These findings reveal a unique mechanism for brain macrophage polarization, emphasizing their role in contributing to nervous tissue damage following viral infection in the CNS.
Small extracellular vesicles (sEV) derived from various cell sources have been demonstrated to enhance cardiac function in preclinical models of myocardial infarction (MI). The aim of this study was to compare different sources of sEV for cardiac repair and determine the most effective one, which nowadays remains limited. We comprehensively assessed the efficacy of sEV obtained from human primary bone marrow mesenchymal stromal cells (BM-MSC), human immortalized MSC (hTERT-MSC), human embryonic stem cells (ESC), ESC-derived cardiac progenitor cells (CPC), human ESC-derived cardiomyocytes (CM), and human primary ventricular cardiac fibroblasts (VCF), in in vitro models of cardiac repair. ESC-derived sEV (ESC-sEV) exhibited the best pro-angiogenic and anti-fibrotic effects in vitro. Then, we evaluated the functionality of the sEV with the most promising performances in vitro, in a murine model of MI-reperfusion injury (IRI) and analysed their RNA and protein compositions. In vivo, ESC-sEV provided the most favourable outcome after MI by reducing adverse cardiac remodelling through down-regulating fibrosis and increasing angiogenesis. Furthermore, transcriptomic, and proteomic characterizations of sEV derived from hTERT-MSC, ESC, and CPC revealed factors in ESC-sEV that potentially drove the observed functions. In conclusion, ESC-sEV holds great promise as a cell-free treatment for promoting cardiac repair following MI.
Extracellular Vesicles , Mesenchymal Stem Cells , Myocardial Infarction , Myocytes, Cardiac , Extracellular Vesicles/metabolism , Extracellular Vesicles/transplantation , Humans , Animals , Mice , Myocardial Infarction/therapy , Myocardial Infarction/metabolism , Myocytes, Cardiac/metabolism , Myocytes, Cardiac/cytology , Mesenchymal Stem Cells/metabolism , Mesenchymal Stem Cells/cytology , Embryonic Stem Cells/metabolism , Embryonic Stem Cells/cytology , Human Embryonic Stem Cells/cytology , Human Embryonic Stem Cells/metabolism , Fibroblasts/metabolism , Male , Myocardial Reperfusion Injury/therapy , Myocardial Reperfusion Injury/metabolism , Disease Models, Animal , Neovascularization, Physiologic , Cells, Cultured
Patients with pituitary neuroendocrine tumors (PitNETs) often experience neuropsychiatric disorders due to factors such as hormonal imbalances, and inadequate management of medications, surgeries, and radiation therapies. Commonly observed disorders include depression, anxiety, and cognitive dysfunction, which significantly impact patients' quality of life and prognosis. PitNETs have a significant presence of immune cells within the tumor microenvironment (TME), predominantly macrophages and T lymphocytes. These immune cells secrete a variety of cytokines, growth factors, and chemokines, which regulate the biological behaviors of PitNETs, including tumor initiation, proliferation, migration, invasion, and angiogenesis. In addition, this review provides a pioneering summary of the close relationships between the aberrant secretion of proinflammatory cytokines within the TME of PitNETs and the occurrence of neuropsychiatric disorders, along with their potential underlying mechanisms. The cytokines produced as a result of TME dysregulation may affect various aspects of the central nervous system, including neurotransmitter metabolism, neuroendocrine function, and neurovascular plasticity, thereby leading to a higher susceptibility to neurobehavioral disorders in PitNET patients.
Immobilization of imidazole molecules as proton carriers into MOFs to facilitate proton conduction is a general strategy for developing high proton conductive materials. Herein, we designed two imidazole substituted phthalic acid ligands and constructed two novel MOFs, {[Zr6(OH)16(H3L1)4]Cl8·20H2O}n [Zr-MOF; H3L1 = 2-(1H-imidazol-4-yl) methylaminoterephthalic acid] and {Gd(HCOO)(H2L2)2}n [Gd-MOF; H3L2 = 5-(1H-imidazol-4-yl)methylaminoisophthalic acid] and fully studied their porous nature, stability and water-assisted proton conduction. The resulting Zr-MOF exhibits a high proton conductivity of 1.82 × 10-2 S cm-1 at 98% RH and 80 °C, while Gd-MOF has a proton conductivity of 3.01 × 10-3 S cm-1 at 98% RH and 60 °C.
The underlying mechanism of the ongoing seismic swarm in the Noto Peninsula, Japan, which generates earthquakes at 10 times the average regional rate, remains elusive. We capture the evolution of the subsurface stress state by monitoring changes in seismic wave velocities over an 11-year period. A sustained long-term increase in seismic velocity that is seasonally modulated drops before the earthquake swarm. We use a three-dimensional hydromechanical model to quantify environmentally driven variations in excess pore pressure, revealing its crucial role in governing the seasonal modulation with a stress sensitivity of 6 × 10-9 per pascal. The decrease in seismic velocity aligns with vertical surface uplift, suggesting potential fluid migration from a high-pore pressure zone at depth. Stress changes induced by abnormally intense snow falls contribute to initiating the swarm through subsequent perturbations to crustal pore pressure.
In this issue, we established rapid, cost-effective, and simple detection methods including recombines polymerase amplification with lateral flow dipstick (RPA-LFD) and real-time RPA for cyprinid herpesvirus 3(CyHV-3), and evaluated their sensitivity, specificity, and applicability, the real-time RPA method could achieve sensitive diagnosis of CyHV-3 within 1.3 copies per reaction, respectively. The real-time RPA method is 10-fold more sensitive than RPA-LFD method. The exact number of CyHV-3 can be calculated in each sample by real-time RPA. The sera from koi also can be tested in these methods. In addition, no cross-reaction was observed with other related pathogens, including carp oedema virus (CEV), spring viraemia of carp virus (SVCV), cyprinid herpesvirus 1(CyHV-1), cyprinid herpesvirus 2(CyHV-2), type I grass carp reovirus (GCRV-I), type II GCRV (GCRV-II), type III GCRV (GCRV-III), and Aeromonas hydrophila.
BACKGROUND: Arachidonic acid (AA), one of the most ubiquitous polyunsaturated fatty acids (PUFAs), provides fluidity to mammalian cell membranes. It is derived from linoleic acid (LA) and can be transformed into various bioactive metabolites, including prostaglandins (PGs), thromboxanes (TXs), lipoxins (LXs), hydroxy-eicosatetraenoic acids (HETEs), leukotrienes (LTs), and epoxyeicosatrienoic acids (EETs), by different pathways. All these processes are involved in AA metabolism. Currently, in the context of an increasingly visible aging world population, several scholars have revealed the essential role of AA metabolism in osteoporosis, chronic obstructive pulmonary disease, and many other aging diseases. AIM OF REVIEW: Although there are some reviews describing the role of AA in some specific diseases, there seems to be no or little information on the role of AA metabolism in aging tissues or organs. This review scrutinizes and highlights the role of AA metabolism in aging and provides a new idea for strategies for treating aging-related diseases. KEY SCIENTIFIC CONCEPTS OF REVIEW: As a member of lipid metabolism, AA metabolism regulates the important lipids that interfere with the aging in several ways. We present a comprehensivereviewofthe role ofAA metabolism in aging, with the aim of relieving the extreme suffering of families and the heavy economic burden on society caused by age-related diseases. We also collected and summarized data on anti-aging therapies associated with AA metabolism, with the expectation of identifying a novel and efficient way to protect against aging.
Maturation defects are intrinsic features of osteoblast lineage cells in CKD patients. These defects persist ex vivo, suggesting that CKD induces epigenetic changes in bone cells. To gain insights into which signaling pathways contribute to CKD-mediated, epigenetically driven, impairments in osteoblast maturation, we characterized RNA expression and DNA methylation patterns by RNA-Seq and MethylationEpic in primary osteoblasts from nine adolescent and young adult dialysis patients with end-stage kidney disease and three healthy references. ATAC-Seq was also performed on a subset of osteoblasts. Bone matrix protein expression was extracted from the iliac crest and evaluated by proteomics. Gene set enrichment analysis was used to establish signaling pathways consistently altered in chromatin accessibility, DNA methylation, and RNA expression patterns. Single genes were suppressed in primary osteoblasts using shRNA and mineralization characterized in vitro. The effect of nuclear factor of activated T cells (NFAT) signaling suppression was also assessed using 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) incorporation. We found that signaling pathways critical for osteoblast differentiation were strongly downregulated in CKD osteoblasts. Gene set enrichment analysis identified highly significant methylation changes, differential chromatin accessibility, and altered RNA expression in NFAT signaling targets. NFAT inhibition reduced osteoblast proliferation. Combined analysis of osteoblast RNA expression and whole bone matrix composition identified 13 potential ligand-receptor pairs. In summary, epigenetic changes in CKD osteoblasts associate with altered expression of multiple osteoblast genes and signaling pathways. An increase in NFAT signaling may play a role in impaired CKD osteoblast maturation. Epigenetic changes also associate with an altered bone matrix, which may contribute to bone fragility. Further studies are necessary to elucidate the pathways affected by these genetic alterations since elucidating these pathways will be vital to correcting the underlying biology of bone disease in the CKD population.
