Is there an association between serum 25-hydroxyvitamin D concentrations and obstructive sleep apnoea? A cross-sectional analysis of NHANES 2007-2008 data.

OBJECTIVES: The study aimed to investigate the relationship between serum 25-hydroxyvitamin D (25(OH)D) concentrations and obstructive sleep apnoea (OSA) and to assess the confounding effect of body mass index (BMI) on this relationship. DESIGN: This was a cross-sectional analysis using data from the 2007-08 National Health and Nutrition Examination Survey (NHANES). SETTING: Data were sourced from NHANES, a continuous survey sponsored by the Centres for Disease Control and Prevention, covering residents from 15 urban areas in the United States of America(USA). PARTICIPANTS: The study included 4901 participants aged 16 years and older who had completed 25(OH)D data and responses to the OSA questionnaire. MAIN EXPOSURE MEASURE: Serum 25(OH)D concentrations were measured using liquid chromatography-tandem mass spectrometry. MAIN OUTCOME MEASURE: The primary outcome was the self-reported diagnosis of OSA from questionnaires. RESULTS: After adjusting for age, sex and race (model 1), a significant negative association was observed between 25(OH)D and OSA (ß=-3.21, 95% CI: -6.17 to -0.26). However, this association was no longer significant after further adjustment for BMI (model 2) (ß=1.47, 95% CI: -1.48, 4.42). In the fully adjusted model (model 3), there was no significant association between 25(OH)D and OSA (ß=0.92, 95% CI: -1.93, 3.76). Subgroup analyses stratified by sex, age, race or BMI also revealed no significant associations between 25(OH)D and OSA. CONCLUSIONS: The study found no significant association between 25(OH)D and OSA. The observed correlation between lower levels of 25(OH)D and OSA may be due to confounding factors, such as higher BMI in the OSA group. Therefore, improving obesity management in OSA patients may be necessary to prevent 25(OH)D insufficiency. This underscores the importance of comprehensive management of both OSA and obesity to promote optimal health outcomes.

Characterization of water microbiota and their relationship with resident oysters during an oyster mortality event.

Microorganisms are vital for the health of marine invertebrates, and their assembly is driven by both deterministic and stochastic factors that regulate residents (innate to the host) and transients (from ambient water). However, the role of water microbiota and the significance of deterministic and stochastic processes in aquatic hosts facing mortality threats are largely unknown. This study examines the shifts in water microbiota during an oyster mortality event using amplicon sequencing and compared with those of resident oysters to disentangle the balance of the deterministic and stochastic factors involved. Water temperature and dissolved oxygen significantly shape the microbial community with a distinct monthly pattern, and Cyanobacteria blooms might exacerbate oyster mortality. The comparative analysis of microbial communities in oysters and water revealed that ≤ 21% of the genera were shared between oysters and water, implying that water microbiota cannot easily transfer into oysters. Furthermore, these shared genera had different functions, with oysters more involved in promoting host digestion and nutrient acquisition and water bacteria enriched more in functions promoting their own growth and survival. These findings illustrate that oysters may possess specific selection or barrier mechanisms that permit a small percentage of transients, controlled by stochastic factors and having a minimal effect on oyster mortality, to enter, whereas the majority of oyster microbiota are residents governed by deterministic factors. Consequently, oysters exhibit some plasticity in their symbiotic microbiota, enabling them to maintain microbial homeostasis and adapt to complex microbial surroundings. This may be a shared mechanism among marine invertebrates for survival in complex marine environments.IMPORTANCEPacific oysters are widely cultured and play vital ecological roles. However, the summer mortality hinders sustainable oyster farming. Untangling causative mechanisms of oyster mortality is a complex task due to the intricate "interactome" involving environmental factors, hosts, and pathogens. Interactions between hosts and microorganisms offer an ideal avenue for investigating the truth. We systematically investigated the microbial community in water and resident oysters during a summer mortality event and proposed that the assembly of oyster microbiota is primarily governed by deterministic processes independent of mortality. Pathogens mainly originate from resident members of the oyster microbiota, with a limited influence from the microbial community in the water. Additionally, environmental degraders, such as Cyanobacteria blooms, cannot be overlooked as a contributing factor of oyster mortality. This study evaluated the weight of deterministic and stochastic factors in microbial assembly during an oyster mortality event and greatly broadened our understanding of the "interactome" through the interaction between oysters and water in microbiota.

Oncolytic Virus Senecavirus A Inhibits Hepatocellular Carcinoma Proliferation and Growth by Inducing Cell Cycle Arrest and Apoptosis.

Background and Aims: Hepatocellular carcinoma (HCC) is a highly aggressive tumor with limited treatment options and high mortality. Senecavirus A (SVA) has shown potential in selectively targeting tumors while sparing healthy tissues. This study aimed to investigate the effects of SVA on HCC cells in vitro and in vivo and to elucidate its mechanisms of action. Methods: The cell counting kit-8 assay and colony formation assay were conducted to examine cell proliferation. Flow cytometry and nuclear staining were employed to analyze cell cycle distribution and apoptosis occurrence. A subcutaneous tumor xenograft HCC mouse model was created in vivo using HepG2 cells, and Ki67 expression in the tumor tissues was assessed. The terminal deoxynucleotidyl transferase dUTP nick end labeling assay and hematoxylin and eosin staining were employed to evaluate HCC apoptosis and the toxicity of SVA on mouse organs. Results: In vitro, SVA effectively suppressed the growth of tumor cells by inducing apoptosis and cell cycle arrest. However, it did not have a notable effect on normal hepatocytes (MIHA cells). In an in vivo setting, SVA effectively suppressed the growth of HCC in a mouse model. SVA treatment resulted in a significant decrease in Ki67 expression and an increase in apoptosis of tumor cells. No notable histopathological alterations were observed in the organs of mice during SVA administration. Conclusions: SVA inhibits the growth of HCC cells by inducing cell cycle arrest and apoptosis. It does not cause any noticeable toxicity to vital organs.

Application of a novel nested ensemble algorithm in predicting motor function recovery in patients with traumatic cervical spinal cord injury.

Traumatic cervical spinal cord injury (TCSCI) often causes varying degrees of motor dysfunction, common assessed by the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI), in association with the American Spinal Injury Association (ASIA) Impairment Scale. Accurate prediction of motor function recovery is extremely important for formulating effective diagnosis, therapeutic and rehabilitation programs. The aim of this study is to investigate the validity of a novel nested ensemble algorithm that uses the very early ASIA motor score (AMS) of ISNCSCI examination to predict motor function recovery 6 months after injury in TCSCI patients. This retrospective study included complete data of 315 TCSCI patients. The dataset consisting of the first AMS at ≤ 24 h post-injury and follow-up AMS at 6 months post-injury was divided into a training set (80%) and a test set (20%). The nested ensemble algorithm was established in a two-stage manner. Support Vector Classification (SVC), Adaboost, Weak-learner and Dummy were used in the first stage, and Adaboost was selected as second-stage model. The prediction results of the first stage models were uploaded into second-stage model to obtain the final prediction results. The model performance was evaluated using precision, recall, accuracy, F1 score, and confusion matrix. The nested ensemble algorithm was applied to predict motor function recovery of TCSCI, achieving an accuracy of 80.6%, a F1 score of 80.6%, and balancing sensitivity and specificity. The confusion matrix showed few false-negative rate, which has crucial practical implications for prognostic prediction of TCSCI. This novel nested ensemble algorithm, simply based on very early AMS, provides a useful tool for predicting motor function recovery 6 months after TCSCI, which is graded in gradients that progressively improve the accuracy and reliability of the prediction, demonstrating a strong potential of ensemble learning to personalize and optimize the rehabilitation and care of TCSCI patients.

Association between obstructive sleep apnea and risk of lung cancer: findings from a collection of cohort studies and Mendelian randomization analysis.

Background: Previous cohort studies conducted on large populations have suggested a potential association between obstructive sleep apnea (OSA) and an elevated risk of developing lung cancer. However, limited research has comprehensively investigated the correlation between the two conditions, and the causal effect remains unknown. Methods: A comprehensive and systematic search was conducted across various databases, including PubMed, Web of Science, Cochrane Library, and Embase, from their inception dates to November 1, 2023. To assess the relationship between OSA and lung cancer, a meta-analysis was performed. Additionally, a two-sample Mendelian randomization (MR) study was conducted using summary data. The datasets included 336,659 individuals from the FinnGen study for OSA and 27,209 individuals from the International Lung Cancer Consortium study, as well as 420,473 individuals from the UK Biobank study for lung cancer. The estimates from each study were aggregated using the inverse variance-weighted method. Results: Data from six population-based cohort studies, encompassing 6,589,725 individuals, indicated a significant increase in the risk of developing lung cancer among patients with OSA (HR 1.28, 95% CI 1.07-1.54). However, the MR analysis did not support a causal relationship between OSA and lung cancer (OR 1.001, 95% CI 0.929-1.100). This lack of association was consistent across specific subtypes of lung cancer, including non-small-cell lung cancer (OR 1.000, 95% CI 0.999-1.000, p = 0.974), lung adenocarcinoma (OR 0.996, 95% CI 0.906-1.094, p = 0.927), and squamous cell lung carcinoma (OR 1.034, 95% CI 0.937-1.140, p = 0.507). Conclusions: Our meta-analysis findings suggest an elevated risk of lung cancer among individuals with OSA. However, the MR analysis did not provide evidence supporting a causal relationship between OSA and lung cancer. Further investigation is required to uncover the underlying factors contributing to the observed association between OSA and lung cancer risk.

Synbiotic therapy with Clostridium sporogenes and xylan promotes gut-derived indole-3-propionic acid and improves cognitive impairments in an Alzheimer's disease mouse model.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized primarily by cognitive impairment. Recent investigations have highlighted the potential of nutritional interventions that target the gut-brain axis, such as probiotics and prebiotics, in forestalling the onset of AD. In this study, whole-genome sequencing was employed to identify xylan as the optimal carbon source for the tryptophan metabolism regulating probiotic Clostridium sporogenes (C. sporogenes). Subsequent in vivo studies demonstrated that administration of a synbiotic formulation comprising C. sporogenes (1 × 1010 CFU per day) and xylan (1%, w/w) over a duration of 30 days markedly enhanced cognitive performance and spatial memory faculties in the 5xFAD transgenic AD mouse model. The synbiotic treatment significantly reduced amyloid-ß (Aß) accumulation in the cortex and hippocampus of the brain. Importantly, synbiotic therapy substantially restored the synaptic ultrastructure in AD mice and suppressed neuroinflammatory responses. Moreover, the intervention escalated levels of the microbial metabolite indole-3-propionic acid (IPA) and augmented the relative prevalence of IPA-synthesizing bacteria, Lachnospira and Clostridium, while reducing the dominant bacteria in AD, such as Aquabacterium, Corynebacterium, and Romboutsia. Notably, synbiotic treatment also prevented the disruption of gut barrier integrity. Correlation analysis indicated a strong positive association between gut microbiota-generated IPA levels and behavioral changes. In conclusion, this study demonstrates that synbiotic supplementation significantly improves cognitive and intellectual deficits in 5xFAD mice, which could be partly attributed to enhanced IPA production by gut microbiota. These findings provide a theoretical basis for considering synbiotic therapy as a novel microbiota-targeted approach for the treatment of metabolic and neurodegenerative diseases.

Machine Learning for Predicting Stillbirth: A Systematic Review.

Stillbirth is a major global issue, with over 5 million cases each year. The multifactorial nature of stillbirth makes it difficult to predict. Artificial intelligence (AI) and machine learning (ML) have the potential to enhance clinical decision-making and enable precise assessments. This study reviewed the literature on predictive ML models for stillbirth highlighting input characteristics, performance metrics, and validation. The PubMed, Cochrane, and Web of Science databases were searched for studies using AI to develop predictive models for stillbirth. Findings were analyzed qualitatively using narrative synthesis and graphics. Risk of bias and the applicability of the studies were assessed using PROBAST. Model design and performance were discussed. Eight studies involving 14,840,654 women with gestational ages ranging from 20 weeks to full term were included in the qualitative analysis. Most studies used neural networks, random forests, and logistic regression algorithms. The number of predictive features varied from 14 to 53. Only 50% of studies validated the models. Cross-validation was commonly employed, and only 25% of studies performed external validation. All studies reported area under the curve as a performance metric (range 0.54-0.9), and five studies reported sensitivity (range, 60- 90%) and specificity (range, 64 - 93.3%). A stacked ensemble model that analyzed 53 features performed better than other models (AUC = 0.9; sensitivity and specificity > 85%). Available ML models can attain a considerable degree of accuracy for prediction of stillbirth; however, these models require further development before they can be applied in a clinical setting.

Predictive model for assessing malnutrition in elderly hospitalized cancer patients: A machine learning approach.

BACKGROUND: Malnutrition is prevalent among elderly cancer patients. This study aims to develop a predictive model for malnutrition in hospitalized elderly cancer patients. METHODS: Data from January 2022 to January 2023 on cancer patients aged 60+ were collected, involving 22 variables. Key variables were identified using the LASSO (Least Absolute Shrinkage and Selection Operator) method, and nine machine learning models were tested. SHAP was used to interpret the XGBoost model. Malnutrition prevalence was assessed. RESULTS: Among 450 participants, 46.4 % were malnourished. Key predictors identified were ADL (Activities of Daily Living), ALB (Albumin), BMI (Body Mass Index) and age. XGBoost had the highest AUC of 0.945, accuracy of 0.872, and sensitivity of 0.968. Higher ADL and age increased malnutrition risk, while lower ALB and BMI reduced it. CONCLUSIONS: The XGBoost model is highly effective in detecting malnutrition in elderly cancer patients, enabling early and rapid nutritional assessments.

Deficiency of SDHC promotes metastasis by reprogramming fatty acid metabolism in colorectal cancer.

BACKGROUND: Several studies have demonstrated a strong correlation between impaired Succinate dehydrogenase (SDH) function and the advancement of tumors. As a subunit of SDH, succinate dehydrogenase complex subunit C (SDHC) has been revealed to play tumor suppressive roles in several cancers, while its specific role in colorectal cancer (CRC) still needs further investigation. METHODS: Online database were utilized to investigate the expression of SDHC in colorectal cancer and to assess its correlation with patient prognosis. Cell metastasis was assessed using transwell and wound healing assays, while tumor metastasis was studied in a nude mice model in vivo. Drug screening and RNA sequencing were carried out to reveal the tumor suppressor mechanism of SDHC. Triglycerides, neutral lipids and fatty acid oxidation were measured using the Triglyceride Assay Kit, BODIPY 493/503 and Colorimetric Fatty Acid Oxidation Rate Assay Kit, respectively. The expression levels of enzymes involved in fatty acid metabolism and the PI3K/AKT signaling pathway were determined by quantitative real-time PCR and western blot. RESULTS: Downregulation of SDHC was found to be closely associated with a poor prognosis in CRC. SDHC knockdown promoted CRC metastasis both in vitro and in vivo. Through drug screening and Gene set enrichment analysis, it was discovered that SDHC downregulation was positively associated with the fatty acid metabolism pathways significantly. The effects of SDHC silencing on metastasis were reversed when fatty acid synthesis was blocked. Subsequent experiments revealed that SDHC silencing activated the PI3K/AKT signaling axis, leading to lipid accumulation by upregulating the expression of aldehyde dehydrogenase 3 family member A2 (ALDH3A2) and reduction of fatty acid oxidation rate by suppressing the expression of acyl-coenzyme A oxidase 1 (ACOX1) and carnitine palmitoyltransferase 1A (CPT1A). CONCLUSIONS: SDHC deficiency could potentially enhance CRC metastasis by modulating the PI3K/AKT pathways and reprogramming lipid metabolism.

Intervention effects of low-molecular-weight chondroitin sulfate from the nasal cartilage of yellow cattle on lipopolysaccharide-induced behavioral disorders: regulation of the microbiome-gut-brain axis.

Chondroitin sulfate (CS) is a sulfated linear polysaccharide with different functional activities, including antioxidant, anti-inflammatory, lipid-lowering, and immune regulation. As natural sulfated polysaccharides have high molecular weight, high apparent viscosity, low water solubility, complex structure, and high negative charge, they have difficulty binding to receptors within cells across tissue barriers, resulting in low bioavailability and unclear structure-activity relationships. In this study, an H2O2-Vc oxidative degradation system was employed to perform environmentally friendly and controllable degradation of CS extracted from the nasal cartilage of Shaanxi Yellow cattle. Two low-molecular-weight chondroitin sulfates (LMWCSs), CS-1 (14.8 kDa) and CS-2 (50.9 kDa), that exhibit strong in vitro free radical scavenging ability were obtained, and their structures were characterized. Mice intraperitoneally administered lipopolysaccharide (LPS) were used to explore the cognitive intervention effects of LMWCS. Supplementing CS-1 and CS-2 significantly downregulated the levels of the serum inflammatory factors, TNF-α and IL-1ß, promoted the expression of GSH in the brain, and inhibited the production of the lipid peroxidation product, malondialdehyde (MDA), ultimately inhibiting LPS-induced cognitive impairment in mice. Surprisingly, compared to the LPS model group, the abundances of Streptococcus, Eisenbergiella, Vampirovibrio, Coprococcus, Enterococcus and Lachnoanaerobaculum were significantly increased in the intestines of mice in the CS-1 and CS-2 group, whereas those of Parabacteroides and Mycoplasma were significantly decreased. Altogether, this study provides a theoretical basis for the comprehensive utilization of agricultural and animal resources and the application of brain nutrition, anti-inflammatory, and LMWCS health products.

Fut2 deficiency aggravates chronic colitis through 2-oxindole-AHR mediated cGAS-STING pathway.

OBJECTIVE: This study aims to disclose how loss of fucosyltransferase 2 (Fut2) impacts intestinal inflammation through cGAS-STING pathway that is closely associated with gut microbiota, and which microbial metabolite improves colitis in Fut2 deficiency. METHODS: Chronic colitis was induced in intestinal epithelial Fut2 knock out mice (Fut2△IEC), whose intestinal inflammation and activity of cGAS-STING pathway were evaluated. 16S rRNA sequencing and metabolomics were performed using intestinal samples. 2-oxindole was used to treat RAW264.7 cells and Fut2△IEC mice with colitis (Fut2△IEC-DSS) to investigate the effect of 2-oxindole on cGAS-STING response and intestinal inflammation. RESULTS: Fut2 loss exacerbated chronic colitis in mice, manifested by declined body weight, reduced colon length, increased disease activity index (DAI) and more colon injury in Fut2△IEC-DSS mice compared with WT-DSS (wild type mice with colitis). Lack of Fut2 promoted activation of cGAS-STING pathway. Fut2 deficiency had a primary impact on colonic microbiota, as shown by alteration of microbial diversity and structure, as well as decreased Lactobacillus. Metabolic structure and tryptophan metabolism in colonic luminal microbiota were also influenced by Fut2 loss. Fut2 deficiency also led to decreased levels of aryl hydrocarbon receptor (AHR) and its ligand 2-oxindole derived from tryptophan metabolism. 2-oxindole compromised cGAS-STING response through activating AHR in macrophages, and protected against intestinal inflammation and overactive cGAS-STING pathway in Fut2△IEC-DSS mice. CONCLUSION: Fut2 deficiency promotes cGAS-STING pathway through suppressing 2-oxindole-AHR axis, ultimately facilitating the susceptibility to chronic colitis.

Autophagy-related protein 5 (ATG5) interacts with bone marrow stromal cell antigen 2 (BST2) to stimulate HBV replication through antagonizing the antiviral activity of BST2.

Hepatitis B virus (HBV) infection is a major global health burden with 820 000 deaths per year. In our previous study, we found that the knockdown of autophagy-related protein 5 (ATG5) significantly upregulated the interferon-stimulated genes (ISGs) expression to exert the anti-HCV effect. However, the regulation of ATG5 on HBV replication and its underlying mechanism remains unclear. In this study, we screened the altered expression of type I interferon (IFN-I) pathway genes using RT² Profiler™ PCR array following ATG5 knock-down and we found the bone marrow stromal cell antigen 2 (BST2) expression was significantly increased. We then verified the upregulation of BST2 by ATG5 knockdown using RT-qPCR and found that the knockdown of ATG5 activated the Janus kinase/signal transducer and activator of transcription (JAK-STAT) signaling pathway. ATG5 knockdown or BST2 overexpression decreased Hepatitis B core Antigen (HBcAg) protein, HBV DNA levels in cells and supernatants of HepAD38 and HBV-infected NTCP-HepG2. Knockdown of BST2 abrogated the anti-HBV effect of ATG5 knockdown. Furthermore, we found that ATG5 interacted with BST2, and further formed a ternary complex together with HBV-X (HBx). In conclusion, our finding indicates that ATG5 promotes HBV replication through decreasing BST2 expression and interacting with it directly to antagonize its antiviral function.

Application of the convolution neural network in determining the depth of invasion of gastrointestinal cancer: a systematic review and meta-analysis.

BACKGROUND: With the development of endoscopic technology, endoscopic submucosal dissection (ESD) has been widely used in the treatment of gastrointestinal tumors. It is necessary to evaluate the depth of tumor invasion before the application of ESD. The convolution neural network (CNN) is a type of artificial intelligence that has the potential to assist in the classification of the depth of invasion in endoscopic images. This meta-analysis aimed to evaluate the performance of CNN in determining the depth of invasion of gastrointestinal tumors. METHODS: A search on PubMed, Web of Science, and SinoMed was performed to collect the original publications about the use of CNN in determining the depth of invasion of gastrointestinal neoplasms. Pooled sensitivity and specificity were calculated using an exact binominal rendition of the bivariate mixed-effects regression model. I2 was used for the evaluation of heterogeneity. RESULTS: A total of 17 articles were included; the pooled sensitivity was 84% (95% CI, 0.81-0.88), specificity was 91% (95% CI, 0.85-0.94), and the area under the curve (AUC) was 0.93 (95% CI, 0.90-0.95). The performance of CNN was significantly better than that of endoscopists (AUC: 0.93 vs 0.83, respectively; P = .0005). CONCLUSION: Our review revealed that CNN is one of the most effective methods of endoscopy to evaluate the depth of invasion of early gastrointestinal tumors, which has the potential to work as a remarkable tool for clinical endoscopists to make decisions on whether the lesion is feasible for endoscopic treatment.

Adipose-derived stem cells promote glycolysis and peritoneal metastasis via TGF-ß1/SMAD3/ANGPTL4 axis in colorectal cancer.

Peritoneal metastasis, the third most common metastasis in colorectal cancer (CRC), has a poor prognosis for the rapid progression and limited therapeutic strategy. However, the molecular characteristics and pathogenesis of CRC peritoneal metastasis are poorly understood. Here, we aimed to elucidate the action and mechanism of adipose-derived stem cells (ADSCs), a prominent component of the peritoneal microenvironment, in CRC peritoneal metastasis formation. Database analysis indicated that ADSCs infiltration was increased in CRC peritoneal metastases, and high expression levels of ADSCs marker genes predicted a poor prognosis. Then we investigated the effect of ADSCs on CRC cells in vitro and in vivo. The results revealed that CRC cells co-cultured with ADSCs exhibited stronger metastatic property and anoikis resistance, and ADSCs boosted the intraperitoneal seeding of CRC cells. Furthermore, RNA sequencing was carried out to identify the key target gene, angiopoietin like 4 (ANGPTL4), which was upregulated in CRC specimens, especially in peritoneal metastases. Mechanistically, TGF-ß1 secreted by ADSCs activated SMAD3 in CRC cells, and chromatin immunoprecipitation assay showed that SMAD3 facilitated ANGPTL4 transcription by directly binding to ANGPTL4 promoter. The ANGPTL4 upregulation was essential for ADSCs to promote glycolysis and anoikis resistance in CRC. Importantly, simultaneously targeting TGF-ß signaling and ANGPTL4 efficiently reduced intraperitoneal seeding in vivo. In conclusion, this study indicates that tumor-infiltrating ADSCs promote glycolysis and anoikis resistance in CRC cells and ultimately facilitate peritoneal metastasis via the TGF-ß1/SMAD3/ANGPTL4 axis. The dual-targeting of TGF-ß signaling and ANGPTL4 may be a feasible therapeutic strategy for CRC peritoneal metastasis.

Cascaded signal amplification strategy for ultra-specific, ultra-sensitive, and visual detection of Shigella flexneri.

Pathogen infections including Shigella flexneri have posed a significant threat to human health for numerous years. Although culturing and qPCR were the gold standards for pathogen detection, time-consuming and instrument-dependent restrict their application in rapid diagnosis and economically less-developed regions. Thus, it is urgently needed to develop rapid, simple, sensitive, accurate, and low-cost detection methods for pathogen detection. In this study, an immunomagnetic beads-recombinase polymerase amplification-CRISPR/Cas12a (IMB-RPA-CRISPR/Cas12a) method was built based on a cascaded signal amplification strategy for ultra-specific, ultra-sensitive, and visual detection of S. flexneri in the laboratory. Firstly, S. flexneri was specifically captured and enriched by IMB (Shigella antibody-coated magnetic beads), and the genomic DNA was released and used as the template in the RPA reaction. Then, the RPA products were mixed with the pre-loaded CRISPR/Cas12a for fluorescence visualization. The results were observed by naked eyes under LED blue light, with a sensitivity of 5 CFU/mL in a time of 70 min. With no specialized equipment or complicated technical requirements, the IMB-RPA-CRISPR/Cas12a diagnostic method can be used for visual, rapid, and simple detection of S. flexneri and can be easily adapted to monitoring other pathogens.

Simple, sensitive, and visual detection of 12 respiratory pathogens with one-pot-RPA-CRISPR/Cas12a assay.

Respiratory infections pose a serious threat to global public health, underscoring the urgent need for rapid, accurate, and large-scale diagnostic tools. In recent years, the CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated) system, combined with isothermal amplification methods, has seen widespread application in nucleic acid testing (NAT). However, achieving a single-tube reaction system containing all necessary components is challenging due to the competitive effects between recombinase polymerase amplification (RPA) and CRISPR/Cas reagents. Furthermore, to enable precision medicine, distinguishing between bacterial and viral infections is essential. Here, we have developed a novel NAT method, termed one-pot-RPA-CRISPR/Cas12a, which combines RPA with CRISPR molecular diagnostic technology, enabling simultaneous detection of 12 common respiratory pathogens, including six bacteria and six viruses. RPA and CRISPR/Cas12a reactions are separated by paraffin, providing an independent platform for RPA reactions to generate sufficient target products before being mixed with the CRISPR/Cas12a system. Results can be visually observed under LED blue light. The sensitivity of the one-pot-RPA-CRISPR/Cas12a method is 2.5 × 100 copies/µL plasmids, with no cross-reaction with other bacteria or viruses. Additionally, the clinical utility was evaluated by testing clinical isolates of bacteria and virus throat swab samples, demonstrating favorable performance. Thus, our one-pot-RPA-CRISPR/Cas12a method shows immense potential for accurate and large-scale detection of 12 common respiratory pathogens in point-of-care testing.

High-efficiency fiber-cladding power stripper based on all-dielectric optical thin films.

Although conventional fiber-cladding power strippers (CPSs) based on the techniques of high-index adhesive or corrosive liquids onto fiber inner cladding have been well developed, they are still facing challenges in special applications such as spaceborne or radiation-environment fiber lasers and amplifiers. In this paper, we propose and fabricate high-efficiency CPSs based on all-dielectric optical thin films. By numerically analyzing the propagation characteristics of cladding light at the thin film interface, we design a high-index T a 2 O 5 CPS and A l 2 O 3 CPS with single- and cascaded-layer films coated onto the fiber inner cladding, respectively. In our experiment, the CPSs are successfully fabricated onto the inner-cladding surface of 10/125 double-clad fiber based on ion-beam-assisted deposition technology. The stripping efficiency for the 976 nm residual cladding power was measured up to 99.38%, and the stripping power of the fiber CPS without active cooling can be 24 W at least. Such CPS could be advantageous for applications in spaceborne-based fiber lasers or amplifiers (e.g., gravitational wave detection, spaceborne lidar).

A Deep Learning Application of Capsule Endoscopic Gastric Structure Recognition Based on a Transformer Model.

BACKGROUND: Gastric structure recognition systems have become increasingly necessary for the accurate diagnosis of gastric lesions in capsule endoscopy. Deep learning, especially using transformer models, has shown great potential in the recognition of gastrointestinal (GI) images according to self-attention. This study aims to establish an identification model of capsule endoscopy gastric structures to improve the clinical applicability of deep learning to endoscopic image recognition. METHODS: A total of 3343 wireless capsule endoscopy videos collected at Nanfang Hospital between 2011 and 2021 were used for unsupervised pretraining, while 2433 were for training and 118 were for validation. Fifteen upper GI structures were selected for quantifying the examination quality. We also conducted a comparison of the classification performance between the artificial intelligence model and endoscopists by the accuracy, sensitivity, specificity, and positive and negative predictive values. RESULTS: The transformer-based AI model reached a relatively high level of diagnostic accuracy in gastric structure recognition. Regarding the performance of identifying 15 upper GI structures, the AI model achieved a macroaverage accuracy of 99.6% (95% CI: 99.5-99.7), a macroaverage sensitivity of 96.4% (95% CI: 95.3-97.5), and a macroaverage specificity of 99.8% (95% CI: 99.7-99.9) and achieved a high level of interobserver agreement with endoscopists. CONCLUSIONS: The transformer-based AI model can accurately evaluate the gastric structure information of capsule endoscopy with the same performance as that of endoscopists, which will provide tremendous help for doctors in making a diagnosis from a large number of images and improve the efficiency of examination.

UMP-CMP kinase 2 inhibits ZIKV replication through activation of type I IFN signaling pathway.

Cytidine/uridine monophosphate kinase 2 (UMP-CMP kinase 2, CMPK2) has been reported as an antiviral interferon-stimulated gene (ISG). We previously observed that the expression of CMPK2 was significantly upregulated after Zika Virus (ZIKV) infection in A549 cells. However, the association and the underlying mechanisms between CMPK2 induction and ZIKV replication remain to be determined. We investigated the induction of CMPK2 during ZIKV infection and the effect of CMPK2 on ZIKV replication in A549, U251, Vero, IFNAR-deficient U5A and its parental 2fTGH cells, Huh7 and its RIG-I-deficient derivatives Huh7.5.1 cells. The activation status of Jak-STAT signaling pathway was determined by detecting the phosphorylation level of STAT1, the activity of interferon stimulated response element (ISRE) and the expression of several interferon stimulated genes (ISGs). We found that ZIKV infection induced CMPK2 expression through an IFNAR and RIG-I dependent manner. Overexpression of CMPK2 inhibited while CMPK2 knockdown promoted ZIKV replication in A549 and U251 cells. Mechanically, we found that CMPK2 overexpression increased IFNß expression and activated Jak/STAT signaling pathway as shown by the increased level of p-STAT1, enhanced activity of ISRE, and the upregulated expression of downstream ISGs. These findings suggest that ZIKV infection induced CMPK2 expression, which inhibited ZIKV replication and serves as a positive feedback regulator for IFN-Jak/STAT pathway.

RUNX1 promotes angiogenesis in colorectal cancer by regulating the crosstalk between tumor cells and tumor associated macrophages.

Colorectal cancer (CRC) is a common malignancy worldwide. Angiogenesis and metastasis are the critical hallmarks of malignant tumor. Runt-related transcription factor 1 (RUNX1), an efficient transcription factor, facilitates CRC proliferation, metastasis and chemotherapy resistance. We aimed to investigate the RUNX1 mediated crosstalk between tumor cells and M2 polarized tumor associated macrophages (TAMs) in CRC, as well as its relationship with neoplastic angiogenesis. We found that RUNX1 recruited macrophages and induced M2 polarized TAMs in CRC by promoting the production of chemokine 2 (CCL2) and the activation of Hedgehog pathway. In addition, we found that the M2 macrophage-specific generated cytokine, platelet-derived growth factor (PDGF)-BB, promoted vessel formation both in vitro and vivo. PDGF-BB was also found to enhance the expression of RUNX1 in CRC cell lines, and promote its migration and invasion in vitro. A positive feedback loop of RUNX1 and PDGF-BB was thus formed. In conclusion, our data suggest that RUNX1 promotes CRC angiogenesis by regulating M2 macrophages during the complex crosstalk between tumor cells and TAMs. This observation provides a potential combined therapy strategy targeting RUNX1 and TAMs-related PDGF-BB in CRC.