Search

Process-induced porosity significantly affects the fatigue resistance of additive-manufactured components under cyclic loads. In this study, the influence of process-induced porosity defect characteristics on the fatigue properties of wire arc additive manufacturing (WAAM) Al–Si–Mg parts was quantitatively analyzed using the Kitagawa-Takahashi diagram and machine learning methods. Two specimens with different porosity and distributions were fabricated using two welding wires with different surface states. The cross-section porosity of the two groups was 0.42% and 2.06%, respectively. According to the test results, the static strength of the two groups was equivalent, but the elongation of the porosity group specimen was reduced by 58.7%, and the fatigue strength (139.8 MPa) was lower than that of the control group (160.2 MPa). Combining high-cycle fatigue post-mortem inspection and scanning electron microscopy analysis, the geometric features of the critical defects were obtained. The fatigue performance was assessed by combining extreme value statistics and the Kitagawa-Takahashi diagram according to critical defects, which showed good consistency but was still not conservative as some failure data were within the safe-life range. Therefore, four parameters of applied stress and the projected area, location, and morphology of the critical defects were trained using an extreme gradient boosting model (XGBoost) and random forest (RF). The XGBoost model is 95.7 % more accurate than the RF model in predicting fatigue life. The importance of four parameters in limiting fatigue life is ranked in the above order.

Abstract Background Bile acids are essential for energy metabolism. Deoxycholic acid (DCA) in particular is associated with metabolic disorders such as type 2 diabetes mellitus (T2DM) and obesity. However, the direct effects of DCA on metabolism and body composition have yet to be studied in depth. Methods Targeted metabolomics analysis of human feces was performed. C57BL/6J mice fed a high-fat diet (HFD) were gavaged with DCA, and the effects were measured by metabolic tolerance tests and metabolic cages. Body composition was evaluated by echoMRI. To evaluate the beneficial function of DCA on thermogenesis and lipolysis, histological staining and qPCR were carried out. Results There was negative correlation between fecal DCA levels and serum glucose levels, as well as the Homeostatic Model Assessment for Insulin Resistance (HOMA) index in humans. Our findings confirmed that DCA could ameliorate glucose metabolism and insulin sensitivity in mice fed with HFD. DCA supplementation alleviated HFD-induced obesity and decreased the fat mass significantly by promoting lipolysis. Moreover, DCA significantly enhanced energy expenditure and thermogenesis in brown adipose tissue in mice with obesity induced by HFD. Conclusions Based on the results of our mouse model, DCA may have applications in alleviating obesity and its related metabolic disorders in humans.

Abstract Osteoarthritis (OA), a ubiquitous degenerative joint disorder, is marked by pain and disability, profoundly impacting patients' quality of life. As the population ages, the global prevalence of OA is escalating. Omics technologies have become instrumental in investigating complex diseases like OA, offering comprehensive insights into its pathogenesis and progression by uncovering disease-specific alterations across genomics, transcriptomics, proteomics, and metabolomics levels. In this review, we systematically analyzed and summarized the application and recent achievements of omics technologies in OA research by scouring relevant literature in databases such as PubMed. These studies have shed light on new potential therapeutic targets and biomarkers, charting fresh avenues for OA diagnosis and treatment. Furthermore, in our discussion, we highlighted the immense potential of spatial omics technologies in unraveling the molecular mechanisms of OA and in the development of novel therapeutic strategies, proposing future research directions and challenges. Collectively, this study encapsulates the pivotal advances in current OA research and prospects for future investigation, providing invaluable references for a deeper understanding and treatment of OA. This review aims to synthesize the recent progress of omics technologies in the realm of OA, aspiring to furnish theoretical foundations and research orientations for more profound studies of OA in the future.

Legume proteins have recently gained significant interest in the food industry for their eco-friendliness and nutritional qualities. Research shows that the replacement of specific animal protein sources with legume proteins presents sustainability and economic benefit. Nonetheless, legume proteins frequently exhibit inferior functional properties and palatability compared to animal proteins. Various non-thermal technologies, including high hydrostatic pressure, ultrasound, cold plasma, pulsed electric field, and dynamic high-pressure microjet, had been investigated to enhance the functional properties of legume proteins without loss of nutritional and sensory properties. Although these technologies show potential, no systematic study has been conducted to summarize and compare their effects on different legume proteins. This review aims to fill this gap by addressing the most promising approaches of non-thermal technologies for the modification of functional properties of legume proteins. New insights are discussed, elaborating the effect of non-thermal technologies on the structural and functional behavior of proteins.

Ulcerative colitis (UC) is a common infl ammatory disease of the gastrointestinal tract. Traditional Chinese medicine (TCM) has long been used in Asia as a treatment for UC and Puerariae Radix (PR) is a reliable anti-diarrheal therapy. The aims of this study were to investigate the protective effect of PR using the dextran sulfate sodium salt (DSS)-induced UC model in mice and identify molecular mechanisms of PR action. The chemical constituents of PR via ultra-performance liquid chromatography/tandem mass spectrometry and identifi ed potential PR and UC targets using a network pharmacology (NP) approach were obtained to guide mouse experiments. A total of 180 peaks were identifi ed from PR including 48 flavonoids, 46 organic acids, 14 amino acids, 8 phenols, 8 carbohydrates, 7 alkaloids, 6 coumarins and 43 other constituents. NP results showed that caspase-1 was the most dysregulated of the core genes associated with UC. A PR dose of 0.136 mg/g administered to DSS treated mice reversed weight loss and decreased colon lengths found in UC mice. PR also alleviated intestinal mucosal shedding, infl ammatory cell infi ltration and mucin loss. PR treatment suppressed upregulation of NOD-like receptor protein 3 (NLRP3), cysteinyl aspartate-specific proteases-1 (caspase-1), apoptosis-associated speck-like (ASC) and gasdermin D (GSDMD) at both the protein and mRNA expression levels. The addition of a small molecule dual-specifi city phosphatase inhibitor NSC 95397 inhibited the positive effects of PR. These results indicated that PR exerts a protective effect on DSS-induced colitis by inhibiting NLRP3 infl ammasome activation in mice.

Post-stroke depression (PSD) is a psychological disease that can occur following a stroke and is associated with serious consequences. Research on the pathogenesis and treatment of PSD is still in the infancy stage. Patients with PSD often exhibit gastrointestinal symptoms; therefore the role of gut microbiota in the pathophysiology and potential treatment effects of PSD has become a hot topic of research. In this review, describe the research on the pathogenesis and therapy of PSD. We also describe how the gut microbiota influences neurotransmitters, the endocrine system, energy metabolism, and the immune system. It was proposed that the gut microbiota is involved in the pathogenesis and treatment of PSD through the regulation of neurotransmitter levels, vagal signaling, hypothalamic–pituitary–adrenal axis activation and inhibition, hormone secretion and release, in addition to immunity and inflammation.

Aims: Heart failure (HF) is associated with profound changes in cardiac metabolism. At present, there is still a lack of relevant research to explore the key microbiome and their metabolites affecting the progression of HF. Herein, the interaction of gut microbiota and circulating free fatty acid (FFA) in HF patients and mice is investigated. Methods and Results: In HF patients, by applying metagenomics analysis and targeted FFA metabolomics, enriched abundance of Clostridium sporogenes (C.sp) in early and late stage of HF patients, which negatively correlated to saturated free fatty acid (SFA) levels, is identified. KEGG analysis further indicates microbiota gene enrichment in FFA degradation in early HF, and decreased gene expression in FFA synthesis in late HF. In HF mice (C57BL/6J) induced by isoproterenol (ISO), impaired intestinal permeability is observed, and decreased fecal C.sp and increased SFA are further validated. At last, by supplementing C.sp to ISO‐induced HF mice, the cardiac function, fibrosis, and myocardial size are partially rescued, together with decreased circulating SFA levels. Conclusions: Clostridium abundance is increased in HF, compensating cardiac function deterioration via downregulation of circulating SFA levels. The results demonstrate that the gut microbiota–SFA axis plays an important role in HF protection, which may provide a strategic advantage for the probiotic therapy development in HF.

Gouty arthritis (GA), a metabolic and immunologic disease, primarily affects joints. Dysbiosis of intestinal flora is an important cause of GA. The metabolic disorders of intestinal flora leading to GA and immune disorders might play an important role in patients with hyperuricemia and established GA. However, the exact mechanisms, through which the dysbiosis of intestinal flora causes the development of GA, are not fully understood yet. Moreover, several therapies commonly used to treat GA might alter the intestinal flora, suggesting that modulation of the intestinal flora might help prevent or treat GA. Therefore, a better understanding of the changes in the intestinal flora of GA patients might facilitate the discovery of new diagnostic and therapeutic approaches. The current review article discusses the effects of intestinal flora dysbiosis on the pathogenesis of GA and the cross-regulatory effects between gut flora and drugs for treating GA. This article also highlights the modulatory effects of gut flora by traditional Chinese medicine (TCM) to lower uric acid levels and relieve joint pain as well as provides a summary and outlook, which might help guide future research efforts.

As a representative of the fourth-generation light sources, the High Energy Photon Source (HEPS) in Beijing, China, utilizes a multi-bend achromat lattice to obtain an approximately 100 times emittance reduction compared with third-generation light sources. New technologies bring new challenges to operate the storage ring. In order to meet the beam commissioning requirements of HEPS, a new framework for the development of high-level applications (HLAs) has been created. The key part of the new framework is a dual-layer physical module to facilitate the seamless fusion of physical simulation models with the real machine, allowing for fast switching between different simulation models to accommodate the various simulation scenarios. As a framework designed for development of physical applications, all variables are based on physical quantities. This allows physicists to analytically assess measurement parameters and optimize machine parameters in a more intuitive manner. To enhance both extensibility and adaptability, a modular design strategy is utilized, partitioning the entire framework into discrete modules in alignment with the requirements of HLA development. This strategy not only facilitates the independent development of each module but also minimizes inter-module coupling, thereby simplifying the maintenance and expansion of the entire framework. To simplify the development complexity, the design of the new framework is implemented using Python and is called Python-based Accelerator Physics Application Set (Pyapas). Taking advantage of Python's flexibility and robust library support, we are able to develop and iterate quickly, while also allowing for seamless integration with other scientific computing applications. HLAs for both the HEPS linac and booster have been successfully developed. During the beam commissioning process at the linac, Pyapas's ease of use and reliability have significantly reduced the time required for the beam commissioning operators. As a development framework for HLA designed for the new-generation light sources, Pyapas has the versatility to be employed with HEPS, as well as with other comparable light sources, due to its adaptability.

Abstract Introduction With regard to the esthetics and comfort of orthodontic treatment, the requirement for removable clear aligners (CAs) is increasing. Unlike conventional fixed orthodontic appliances, CAs were made of thermoplastic film by thermoforming on the personalized dental models. The construction of orthodontic thermoplastic is a critical factor for orthodontic tooth movement (OTM). Polyethylene terephthalate glycol-modified (PETG) and thermoplastic polyurethane (TPU) are the most commonly orthodontic thermoplastics; however, the evidence of the differences between different orthodontic thermoplastic are limited to vitro environment and the evidence in vivo environment is not available. Therefore, this trial aims to provide reliable evidence for orthodontists’ personalized treatment plans whether the two most commonly used orthodontic thermoplastics of PETG and TPU have differences in the efficiency of OTM. Methods and analysis This randomized controlled clinical study will recruit 44 orthodontic patients for orthodontic treatment. All the subjects will be randomized into two groups (PETG and TPU, n = 22 for each group). In the first stage (M0 to M1), clear aligners will be made of two orthodontic thermoplastics and move the maxillary first or second premolars 2 mm. In the second stage, patients will take the standard orthodontic treatments. The primary outcome will be the efficiency of clear aligners made of different materials on the digital models. The secondary outcome will be the efficiency of clear aligners made of different materials on the cone-beam computed tomography (CBCT). The efficiency will be calculated through the superimposition of the digital models and CBCT. Discussion The results from this trial will serve as evidence for orthodontists and manufacturers and clarify whether the difference in orthodontic thermoplastics significantly impacts the efficiency of OTM. Trial registration number ChiCTR2300070980. Registered on 27 April 2023. https://www.chictr.org.cn/showproj.html?proj=186253

The panoramic stereo video has brought a new visual experience for the audience with its immersion and stereo effect. In panoramic stereo video, the face is an important element. However, the face image in panoramic stereo video has varying degrees of deformation. This brings new challenges to face recognition. Therefore, this paper proposes a face recognition model DCM2Net (Deformable Convolution MobileFaceNet) for panoramic stereo video. The model mainly integrates the feature information between channels during feature fusion, redistributes the information between channels in the deeper part of the network, and fully uses the information between different channels for feature extraction. This paper also built a panoramic stereo video live system, using the DCM2Net model to recognize the face in panoramic stereo video, and the recognition results are displayed in the video. After experiments on different datasets, the results show that our model has better results on popular datasets and panoramic datasets.

In recent years, negative Poisson's ratio structures have attracted many scholars' attention as a result of their distinctive mechanical properties and exceptional energy absorption ability. However, the geometry of structures with negative Poisson's ratio is generally complex, and the preparation of the model has become problematic. Therefore, the increasingly mature additive manufacturing industry can be used to prepare three-dimensional models. In this paper, five negative Poisson's ratio structures were fabricated by 3D printing, and cementitious materials were poured onto them. The purpose of this study is to investigate the mechanical properties of different structural reinforced concrete specimens under in-plane quasi-static uniaxial compression and obtain the deformation and failure modes of different structural reinforced concrete specimens. In the experiment, two-dimensional digital image correlation (2D-DIC) and acoustic emission (AE) techniques were used to obtain plane displacement and internal damage evolution, and the plane strain field was calculated using Vic-2D software. The experimental results show that the ductility and energy absorption capacity of structural reinforced concrete specimens have been significantly improved, and there are significant differences in the performance of different structural reinforced concrete due to different deformation modes.

Gouty nephropathy (GN) is a metabolic disease with persistently elevated blood uric acid levels. The main manifestations of GN are crystalline kidney stones, chronic interstitial nephritis, and renal fibrosis. Understanding the mechanism of the occurrence and development of GN is crucial to the development of new drugs for prevention and treatment of GN. Currently, most studies exploring the pathogenesis of GN are primarily based on animal and cell models. Numerous studies have shown that inflammation, oxidative stress, and programmed cell death mediated by uric acid and sodium urate are involved in the pathogenesis of GN. In this article, we first review the mechanisms underlying the abnormal intrinsic immune activation and programmed cell death in GN and then describe the characteristics and methods used to develop animal and cell models of GN caused by elevated uric acid and deposited sodium urate crystals. Finally, we propose potential animal models for GN caused by abnormally high uric acid levels, thereby provide a reference for further investigating the methods and mechanisms of GN and developing better prevention and treatment strategies.

Abstract Background Liver fibrosis and hepatocellular carcinogenesis secondary to liver fibrosis are serious liver diseases with no effective treatments. Mori fructus aqueous extracts (MFAEs) have served as successful treatments for many types of liver injury including fibrosis although the molecular mechanisms are unknown at present. Purpose To investigate the effect of MFAEs in alleviating acute and chronic liver injury and tried to decipher the underlying mechanism. Methods and results Mice were divided into 5 groups (n = 8) for acute (groups: control, 0.3% CCl4, bifendate (BD), 100 and 200 mg/kg MFAEs, 7 d) and chronic (groups: control, 10% CCl4, BD, 100 and 200 mg/kg MFAEs, 4 weeks) liver injury study. Each mouse was injected intraperitoneally with 10 µL/g corn oil containing CCl4 expect the control group. HepG2 cells were used in vitro study. Eighteen communal components were identified by UPLC-LTQ-Orbitrap-MS. We utilized a mouse model for acute and chronic liver injury using CCl4 and MFAEs administration effectively blocked fibrosis and significantly inhibited inflammation in the liver. MFAEs activated the nuclear factor erythroid derived 2 like 2/heme oxygenase 1 (Nrf2/HO-1) pathway and promoted the synthesis of the antioxidants glutathione (GSH), superoxidedismutase (SOD) and glutathione peroxidase (GSH-Px) that resulted in reduced levels of CCl4-induced oxidative stress molecules including reactive oxygen species. These extracts administered to mice also inhibited ferroptosis in the liver by regulating the expression of Acyl-CoA synthetase long chain family member 4 (ACSL4), solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4), thus reducing the occurrence of liver fibrosis. Both in vivo and in vitro tests indicated that the mechanism of MFAEs protection against liver fibrosis was linked to activation of Nrf2 signaling. These effects were blocked in vitro by the addition of a specific Nrf2 inhibitor. Conclusion MFAEs inhibited oxidative stress, ferroptosis and inflammation of the liver by activating Nrf2 signal pathway and provided a significant protective effect against CCl4-induced liver fibrosis. Graphical Abstract

Abstract Though diel variations are geographically widespread phenomena among phytoplankton and zooplankton, knowledge is limited regarding diel variations in planktonic ciliate (microzooplankton) community structure. In this study, we analyzed diel variations in community structure of planktonic ciliates in the northern South China Sea (nSCS) and tropical Western Pacific (tWP). Hydrological characteristics during day and night were slightly different over both the nSCS and tWP, while ciliate average abundance at night was clearly higher than in the day in the upper 200 m. In both the nSCS and tWP, abundance proportions of large size-fraction (> 30 μm) aloricate ciliates at night were higher than in the day. While for tintinnids, abundance proportion of large lorica oral diameter at night were lower than in the day. The relationship between environmental factors and ciliate abundance pointed out that depth and temperature were main factors influencing aloricate ciliate and tintinnid in both day and night. For some dominant tintinnid species, chlorophyll a was another important factor influencing their diel vertical distribution. Our results provide fundamental data for better understanding the mechanisms of planktonic ciliate community diel variation in the tropical Western Pacific Ocean.

Abstract Backgroud With the reform of medical system in China, Beijing municipal hospitals explored a new pharmaceutical care model and set up medication therapy management services (MTMs) in ambulatory care since 2019. We were one of the first hospitals to set up this service in China. At the present, there were relatively few reports about the effect of MTMs in China. In this study, we summarized the implementation of MTMs in our hospital, explore the feasibility of pharmacist-led MTMs in ambulatory care and the impact of MTMs on patients’ medical costs. Methods A retrospective study was conducted in a university-affiliated, tertiary comprehensive hospital in Beijing, China. The patients who received at least one MTMs and with complete medical records and pharmaceutical documents from May 2019 to February 2020 were included. Pharmacists provided pharmaceutical care for patients according to the MTMs standards issued by the American Pharmacists Association, identified the numbers and classification of the patients’ perceived medication-related demands, identified medication-related problems (MRPs), and developed the medication-related action plans (MAPs). All MRPs found by pharmacists, pharmaceutical interventions, and resolving recommendations were documented, and calculate the cost of treatment drugs that patients can reduce. Results A total of 112 patients received MTMs in ambulatory care, among them 81 cases with the completed record were included in this study. 67.9% of patients had five or more diseases, 83% of them co-took over 5 drugs. While performing MTMs, 128 patients’ perceived medication-related demands were recorded in all, monitoring and judgment of adverse drug reaction (ADR) (17.19%) was the most common demand. 181 MRPs were found, with an average of 2.55 MPRs per patient. Nonadherence (38%), excessive drug treatment (20%), and adverse drug events (17.12%) were the top three MRPs. Pharmaceutical care (29.77%), adjustment of drug treatment plan (29.10%) and referral to the clinical department (23.41%) were the top three MAPs. Whereby the MTMs provided by pharmacists, the cost-saving of each patient was about $ 43.2 monthly. Conclusion By participating in the MTMs of outpatients, the pharmacists could identify more MRPs and develop personalized MAPs timely for patients, thereby promoting rational drug use and reducing medical expenses.

Macrophages have been shown to have an important function in atherosclerosis. Here the authors show that, in human atherosclerotic plaques and mouse models, GSDME and pyroptosis promote atherosclerosis and inhibition of these pathways could reduce pathology associated with atherosclerotic disease.

Dampness-heat syndrome diarrhea (DHSD) is a common clinical disease with a high prevalence but still has no satisfactory therapeutic medicine, so the search for a safe and effective drug candidate is ongoing. This study aims to explore the efficacy and mechanisms of Lianweng granules (LWG) in the treatment of DHSD and to identify the blood transport components of LWG. We assessed the efficacy of LWG in DHSD by various in vivo metrics such as body weight, disease activity index (DAI), histopathologic examination, intestinal barrier function, levels of inflammatory, apoptotic biomarkers, and oxidative stress. We identified the blood components of LWG using ultra-high performance liquid chromatography-mass spectrometry/mass spectrometry (UHPLC-MS/MS), and the resolved key components were used to explore the relevant targets. We next predicted the potential mechanisms of LWG in treating DHSD using network pharmacology and molecular docking based on the relevant targets. Finally, the mechanisms were validated in vivo using RT-qPCR, Western blotting, ELISA, and immunofluorescence and evaluated in vitro using Cell Counting Kit-8 (CCK-8), small interfering RNA, cellular enthusiasm transfer assay (CETSA), and drug affinity response target stability (DARTS). Ninety-one pharmacodynamic components of LWG enter the bloodstream and exert possible therapeutic effects. In vivo, LWG treatment improved body weight, reduced colonic injury and DAI scores, lowered inflammation, oxidative stress, and apoptosis markers, and partially restored intestinal barrier function in DHSD mice. Guided by network pharmacology and molecular docking, it is suggested that LWG may exert therapeutic effects by inhibiting IL-6/STAT3/PI3K/AKT signaling. LWG significantly decreased the expression of IL-6, p-STAT3, p-PI3K, p-AKT, and other proteins. These findings were supported by in vitro experiments, where CETSA, DARTS, and siRNA evidenced LWG’s targeting of STAT3. LWG targeted STAT3 to inhibit inflammation, oxidative stress, and apoptosis in the colon, thereby restoring the intestinal barrier function to some extent and exerting a therapeutic effect on DHSD.

MYBs constitute the second largest transcription factor (TF) superfamily in flowering plants with substantial structural and functional diversity, which have been brought into focus because they affect flower colors by regulating anthocyanin biosynthesis. Up to now, the genomic data of several Chrysanthemum species have been released, which provides us with abundant genomic resources for revealing the evolution of the MYB gene family in Chrysanthemum species. In the present study, comparative analyses of the MYB gene family in six representative species, including C. lavandulifolium, C. seticuspe, C. ×morifolium, Helianthus annuus, Lactuca sativa, and Arabidopsis thaliana, were performed. A total of 1104 MYBs, which were classified into four subfamilies and 35 lineages, were identified in the three Chrysanthemum species (C. lavandulifolium, C. seticuspe, and C. ×morifolium). We found that whole-genome duplication and tandem duplication are the main duplication mechanisms that drove the occurrence of duplicates in CmMYBs (particularly in the R2R3-MYB subfamily) during the evolution of the cultivated chrysanthemums. Sequence structure and selective pressure analyses of the MYB gene family revealed that some of R2R3-MYBs were subjected to positive selection, which are mostly located on the distal telomere segments of the chromosomes and contain motifs 7 and 8. In addition, the gene expression analysis of CmMYBs in different organs and at various capitulum developmental stages of C. ×morifolium indicated that CmMYBS2, CmMYB96, and CmMYB109 might be the negative regulators for anthocyanin biosynthesis. Our results provide the phylogenetic context for research on the genetic and functional evolution of the MYB gene family in Chrysanthemum species and deepen our understanding of the regulatory mechanism of MYB TFs on the flower color of C. ×morifolium.

This study was conducted to investigate the effects of solid-state fermented wheat bran on immune performance and inflammatory response in laying hens. A total of 225 18-week-old Hy-Line brown-egg laying hens were randomly divided into 3 groups with 5 replicates per group and 15 hens per replicate. Laying hens were fed a basal diet (corn-soybean meal diet) supplemented with 0 (control group), 10% wheat bran and 10% fermented wheat bran, respectively. The results showed: (1) Compared to wheat bran group, the contents of crude protein, trichloroacetic acid-soluble protein, dietary fibre (DF), mannan and total polyphenols in wheat bran were increased by solid state fermentation. (2) Compared to the control group, fermented wheat bran increased the levels of serum biochemical parameters, reproductive hormones, immunoglobulins and anti-inflammatory factors. Therefore, long-term dietary supplementation of 10% fermented wheat bran plays an important role in improving the immune performance of laying hens.

We investigated the effects of carbon tetrachloride (CCl4) exposure on liver detoxification. We confirmed that 0.2%-0.8% CCl4 decreased the liver carboxylesterase (CarE), lactate dehydrogenase (LDH) activity and total protein (TP) levels, while 0.2% and 0.8% CCl4 increased the liver acetylcholine esterase (AChE) activity (P< 0.05). It was observed0.4%-0.8% CCl4 increased serum glutathione S-transferase (GST) and catalase (CAT) activity, 0.1%-0.8% CCl4 increased the level of malondialdehyde (MDA), and 0.2% CCl4 increased the level of total superoxide dismutase (T-SOD). The expression of nod-like receptor protein 3 (NLRP3), interleukin-1β (IL-1β), and tumour necrosis factor-α (TNF-α) were significantly elevated in 0.2%-0.8% CCl4 exposure (P< 0.05). The expression of p38MAPK, gasdermin D (GSDMD), and nuclear factor kappa-B kinase (IKK) was decreased in 0.1%-0.8% CCl4 exposure, while the apoptosis was not statistically different in all groups. This indicates that 0.1% CCl4 exposure could damage the liver structure and detoxification function via p38MAPK/NF-κB/NLRP3 pathway.

Vegetation plays an important role in global or regional environmental change. In this study, the spatial–temporal variations of NDVI and its response to climate in China and its seven sub-regions were investigated based on MODIS NDVI data, ERA5-land precipitation (PRE) and temperature (TEM) data from 2001 to 2020. The inter-annual growth rate of NDVI in China was 0.0021/yr in the past 20 years. The inter-annual growth rates of NDVI in seven sub-regions had significant differences at regional or seasonal scales. The ratio of improved vegetation area to the total studied area reached about 70%. In summer, vegetation degradation was concentrated in East China and Southwest China. The vegetation in Central China and South China improved more obviously in autumn than in the other seasons. The vegetation of Northeast China had a remarkable degradation in autumn and winter, especially in winter. The influence degree of PRE (q = 0.54, P

Objectives This study explored the miR-101 clinical significance in hypertensive disorder complicating pregnancy (HDCP). Methods Pregnant women with gestational hypertension (GH)/mild preeclampsia (mPE)/severe preeclampsia (sPE) were included. The miR-101 levels were measured. Correlation between miR-101 and soluble fmslike tyrosine kinase-1 (sFlt-1), miR-101 predictive value, and factors influencing HDCP grade were evaluated. Results Serum miR-101 was down-regulated and negatively correlated with sFlt-1. miR-101 was an independent risk factor for HDCP and decreased with HDCP severity. The area under the curve of miR-101 in differentiating GH from mPE and mPE from sPE was 0.7764 and 0.8529. Conclusion Serum miR-101 level may be a biomarker for grading HDCP.

BackgroundStem cell transplantation is one of the treatment methods for acute myocardial infarction (AMI). MicroRNA-1 contributes to the study of the essential mechanisms of stem cell transplantation for treating AMI by targeted regulating the myocardial microenvironment after stem cell transplantation at the post-transcriptional level. Thus, microRNA-1 participates in regulating the myocardial microenvironment after stem cell transplantation, a promising strategy for the Stem cell transplantation treatment of AMI. However, the naked microRNA-1 synthesized is extremely unstable and non-targeting, which can be rapidly degraded by circulating RNase. Herein, to safely and effectively targeted transport the naked microRNA-1 synthesized into myocardial tissue, we will construct pseudo-endogenous microRNA-targeted myocardial ultrasound nanobubble pAd-AAV-9/miRNA-1 NB and evaluate its characteristics, targeting, and function.MethodsThe pAd-AAV-9/miRNA-1 gene complex was linked to nanobubble NBs by the “avidin-biotin bridging” method to prepare cardiomyocyte-targeted nanobubble pAd-AAV-9/miRNA-1 NB. The shape, particle size, dispersion, and stability of nanobubbles and the connection of pAd-AAV-9/miRNA-1 gene complex to nanobubble NB were observed. The virus loading efficiency was determined, and the myocardium-targeting imaging ability was evaluated using contrast-enhanced ultrasound imaging in vivo. The miRNA-1 expression level in myocardial tissue and other vital organs ex vivo of SD rats was considered by Q-PCR. Also, the cytotoxic effects were assessed.ResultsThe particle size of NBs was 504.02 ± 36.94 nm, and that of pAd-AAV-9/miRNA-1 NB was 568.00 ± 37.39 nm. The particle size and concentration of pAd-AAV-9/miRNA-1 NBs did not change significantly within 1 h at room temperature (p > 0.05). pAd-AAV-9/miRNA-1 NB had the highest viral load rate of 86.3 ± 2.2% (p 0.05).ConclusionThe pAd-AAV-9/miRNA-1 NB constructed in this study could carry naked miRNA-1 synthesized in vitro for targeted transport into myocardial tissue successfully and had sound contrast-enhanced imaging effects in vivo.

Abstract Due to the difficulty in sampling of metastatic tumors, patient selection is commonly based on results of primary tumor samples when metastatic samples are not available. However, due to tumor heterogeneity, metastatic tumors may be different from primary tumors in their phenotypes. The aim of this study was to investigate the expression of EGFR, HER2, and HER3 between primary and lymph node metastatic lesions of colorectal cancer. Paired primary tumors and lymph node metastases from 79 patients with colorectal cancer were retrospectively collected and analyzed for EGFR, HER2, and HER3 expression. High EGFR, HER2, and HER3 expression (2+ and 3+) was found in 64.2%, 66.0%, and 85.0% of primary tumors, and 56.8%, 46.0%, and 76.0% of lymph node metastases, respectively. Correlation rates between primary and metastatic lesions were 67.1%, 63.3%, and 74.7% for EGFR, HER2, and HER3, respectively. Stage IV tumors (with distant metastasis) had higher correlation rates of HER2 expression compared to stage III tumors (without distant metastasis) (P = 0.050). Moderate correlation rates in EGFR, HER2, and HER3 expression were observed between primary and metastatic lesions of colorectal cancer. Tumor stage or existence of distant metastasis could serve as potential predictive markers for the correlation of HER2 expression between primary tumors and lymph node metastases of colorectal cancer.

Using plane wave pesudopotential method based on density functional theory, we studied the structural transition of intermetallic compounds Ni3Ti1-xNbx (0≤x≤1). By constructing and relaxing various Ni3Ti1-xNbx structures, the most stable configurations were obtained. The variations of the Ni3Ti1-xNbx structures with x were fitted based on the calculated results. It can be seen that the Nb concentration will be in the range of 29.5%∼71.2% in ternary D019 phases if they participate from the system. The structural transitions can induce the change of mechanical and electronic properties of the compounds. It is shown that the elastic constants such as C44 and C66, decrease with the increase of x although the elastic constants such as C11 and C13 as well as the B/G ratio increase evidently. It indicates that the possibility of shear deformation of the system increases with the increase of the Nb concentration. The formation of different stacking-faults becomes favorable with the substitution of Nb for Ti, which results in the structural transition of Ni3Ti1-xNbx. The conclusions are further supported by density of states and charge density differences.

Objective: To observe the clinical efficacy and safety of Yiqi Yangxue formula (YQYXF) on knee osteoarthritis (KOA), and to explore the underlying therapeutic mechanism of YQYXF through endogenous differential metabolites and their related metabolic pathways.Methods: A total of 61 KOA patients were recruited and divided into the treatment group (YQYXF, 30 cases) and the control group (celecoxib, Cxb, 31 cases). Effects of these two drugs on joint pain, swelling, erythrocyte sedimentation rate (ESR) and c-reactive protein (CRP) were observed, and their safety and adverse reactions were investigated. In animal experiments, 63 SD rats were randomly divided into normal control (NC) group, sham operation (sham) group, model (KOA) group, Cxb group, as well as low-dose (YL), medium-dose (YM), and high-dose groups of YQYXF (YH). The KOA rat model was established using a modified Hulth method. Ultra-high-performance liquid chromatography/Q Exactive HF-X Hybrid Quadrupole-Orbitrap Mass (UHPLC-QE-MS)-based metabolomics technology was used to analyze the changes of metabolites in plasma samples of rats. Comprehensive (VIP) >1 and t-test p < 0.05 conditions were used to screen the disease biomarkers of KOA, and the underlying mechanisms of YQYXF were explored through metabolic pathway enrichment analysis. The related markers of YQYXF were further verified by ELISA (enzyme-linked immunosorbent assay).Results: YQYXF can improve joint pain, swelling, range of motion, joint function, Michel Lequesen index of severity for osteoarthritis (ISOA) score, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, ESR, and CRP. No apparent adverse reactions were reported. In addition, YQYXF can improve cartilage damage in KOA rats, reverse the abnormal changes of 16 different metabolites, and exert an anti-KOA effect mainly through five metabolic pathways. The levels of reactive oxygen species (ROS) and glutathione (GSH) were significantly decreased after the treatment of YQYXF.Conclusion: YQYXF can significantly improve the clinical symptoms of KOA patients without obvious adverse reactions. It mainly improved KOA through modulating lipid metabolism-related biomarkers, reducing lipid peroxidation and oxidative stress.

Background: Cang-Ai Volatile Oil (CAVO) is a traditional Chinese medicine prescription that can be used for improving depressive symptoms through the regulation of dopamine (DA) and 5-hydroxytryptamine (5-HT) and inhibition of the inflammation. The purpose of this study is to verify whether CAVO has effects on depressed mood and cortical excitability in human. Methods: Forty-six healthy individuals were enrolled and instructed to inhale the CAVO for a month (five times per day). Each inhalation lasted for at least one minute. Depressed mood was assessed using Hamilton Rating Scale for Depression (24-items) (HAM-D24), and cortical excitability was tested using functional near-infrared spectroscopy (fNIRS). During fNIRS assessment, two types of verbal fluency tests (VFT) were adopted. Results: One month of CAVO inhalation led to significant decreases in HAM-D24 score, and the mean concentration of oxygenated hemoglobin (HbO2) was significantly increased in the right frontal pole. Conclusion: Inhaling the CAVO can significantly improve depressed mood and cortical excitability in human. The improvement of cortical excitability is mainly focused on the right frontal pole, which is closely associated with emotional processing and executive functioning.

Three-dimensional (3D) printed polymer-reinforced cementitious composites are expected to be used to improve the ductility of cement-based materials. However, research on the maximum flexural capacity and failure mode of lattice-reinforced cementitious composites remains insufficient. In this study, six types of cells with different volume fractions are designed, and mainly undergo bending and tensile deformation. According to the load characteristics during a three-point bending test, five kinds of graded lattice structures are designed. Moreover, a skin-lattice structure and uniform lattice structure are designed, and plain cement mortar is set to comprehensively evaluate the bending mechanical properties of graded lattice-reinforced cementitious composites. The crack evolution and failure mode of these composites under three-point bending load are studied using digital image correlation (DIC). The results show that compared with the uniform lattice, the graded lattice can improve the maximum bending capacity of cement-based materials, improve their cracking characteristics and failure modes during the bending process, and enhance their toughness while reducing the amount of required material. Compared with the plain cement mortar specimen, the graded lattice-reinforced specimen with the largest bending peak load is found to have a 175% increase in the bending peak load and a significant increase in the bending bearing capacity.

Falls are the main contributor to both fatal and nonfatal injuries in elderly individuals as well as significant sources of morbidity and mortality, which are mostly induced by impaired balance control. The ability to keep balance is a remarkably complex process that allows for rapid and precise changes to prevent falls with multiple systems involved, such as musculoskeletal system, the central nervous system and sensory system. However, the exact pathogenesis of falls caused by balance disorders in the elderly has eluded researchers to date. In consideration of aging phenomenon aggravation and fall risks in the elderly, there is an urgent need to explore the pathogenesis and treatments of falls caused by balance disorders in the elderly. The present review discusses the epidemiology of falls in the elderly, potential pathogenic mechanisms underlying multiple systems involved in falls caused by balance disorders, including musculoskeletal system, the central nervous system and sensory system. Meanwhile, some common treatment strategies, such as physical exercise, new equipment based on artificial intelligence, pharmacologic treatments and fall prevention education are also reviewed. To fully understand the pathogenesis and treatment of falls caused by balance disorders, a need remains for future large-scale multi-center randomized controlled trials and in-depth mechanism studies.

As natural functional bioactive ingredients found in foods and plants, polyphenols play various antioxidant and anti-inflammatory roles to prevent the development of disease and restore human health. The multi-target modulation of polyphenols provides a novel practical therapeutic strategy for neurodegenerative diseases that are difficult to treat with traditional drugs like glutathione and cholinesterase inhibitors. This review mainly focuses on the efficacy of polyphenols on ischemic stroke, Parkinson's disease and Alzheimer's disease, including in vivo and in vitro experimental studies. It is further emphasized that polyphenols exert neuroprotective effects primarily through inhibiting production of oxidative stress and inflammatory cytokines, which may be the underlying mechanism. However, polyphenols are still rarely used as medicines to treat neurodegenerative diseases. Due to the lack of clinical trials, the mechanism of polyphenols is still in the stage of insufficient exploration. Future large-scale multi-center randomized controlled trials and in-depth mechanism studies are still needed to fully assess the safety, efficacy and side effects of polyphenols.

Digital droplet PCR (ddPCR) is a powerful amplification technique for absolute quantification of viral nucleic acids. Although commercial ddPCR devices are effective in the lab bench tests, they cannot meet current urgent requirements for on-site and rapid screening for patients. Here, we have developed a portable and fully integrated lab-on-a-disc (LOAD) device for quantitively screening infectious disease agents. Our designed LOAD device has integrated (i) microfluidics chips, (ii) a transparent circulating oil-based heat exchanger, and (iii) an on-disc transmitted-light fluorescent imaging system into one compact and portable box. Thus, droplet generation, PCR thermocycling, and analysis can be achieved in a single LOAD device. This feature is a significant attribute for the current clinical application of disease screening. For this custom-built ddPCR setup, we have first demonstrated the loading and ddPCR amplification ability by using influenza A virus-specific DNA fragments with different concentrations (diluted from the original concentration to 107 times), followed by analyzing the droplets with an external fluorescence microscope as a standard calibration test. The measured DNA concentration is linearly related to the gradient–dilution factor, which validated the precise quantification for the samples. In addition to the calibration tests using DNA fragments, we also employed this ddPCR-LOAD device for clinical samples with different viruses. Infectious samples containing five different viruses, including influenza A virus (IAV), respiratory syncytial virus (RSV), varicella zoster virus (VZV), Zika virus (ZIKV), and adenovirus (ADV), were injected into the device, followed by analyzing the droplets with an external fluorescence microscope with the lowest detected concentration of 20.24 copies/µL. Finally, we demonstrated the proof-of-concept detection of clinical samples of IAV using the on-disc fluorescence imaging system in our fully integrated device, which proves the capability of this device in clinical sample detection. We anticipate that this integrated ddPCR-LOAD device will become a flexible tool for on-site disease detection.

A number of studies have investigated phrasal verbs from various aspects (Liu, 2006; Yu, 2011; Liao & Fukuya, 2004). However, those studies lack generality, because only a couple of phrasal verbs were chosen as examples, or too much content prompt was offered in task response of L2 learners. The current study applies a corpus-based approach to investigate English phrasal verbs in free conversations from a Chinese learner corpus, SWECCL (Wen & Wang, 2008), which demonstrates Chinese students’ actual use of phrasal verbs. This study focuses on analysis of two phenomena: development of phrasal verb uses and avoidance of phrasal verbs across different proficiency levels in Chinese students’ oral English conversations. Results showed that students at higher proficiency level used more phrasal verbs in oral communication, and the progress of phrasal verb use was evident from middle proficiency level to advanced proficiency level. The study also found that phrasal verbs occurred less frequently overall in L2 learners’ oral conversations compared with frequency of their single-word synonyms.

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disease, and its diagnosis is dependent on behavioral manifestation, such as impaired reciprocal social interactions, stereotyped repetitive behaviors, as well as restricted interests. However, ASD etiology has eluded researchers to date. In the past decades, based on strong genetic evidence including mutations in a single gene, gene editing technology has become an essential tool for exploring the pathogenetic mechanisms of ASD via constructing genetically modified animal models which validates the casual relationship between genetic risk factors and the development of ASD, thus contributing to developing ideal candidates for gene therapies. The present review discusses the progress in gene editing techniques and genetic research, animal models established by gene editing, as well as gene therapies in ASD. Future research should focus on improving the validity of animal models, and reliable DNA diagnostics and accurate prediction of the functional effects of the mutation will likely be equally crucial for the safe application of gene therapies.

Autophagy is an intracellular degradation system that maintains the stable state of cell energy metabolism. Some recent findings have indicated that autophagy dysfunction is an important driving factor for the occurrence and development of osteoarthritis (OA). The decrease of autophagy leads to the accumulation of damaged organelles and macromolecules in chondrocytes, which affects the survival of chondrocytes and ultimately leads to OA. An appropriate level of autophagic activation may be a new method to prevent articular cartilage degeneration in OA. This minireview discussed the mechanism of autophagy and OA, key autophagy targets regulating OA progression, and evaluated therapeutic applications of drugs targeting autophagy in preclinical and clinical research. Some critical issues worth paying attention to were also raised to guide future research efforts.

BackgroundGlobally, Alzheimer’s Disease (AD) accounts for the majority of dementia, making it a public health concern. AD treatment is limited due to the limited understanding of its pathogenesis. Recently, more and more evidence shows that ferroptosis lead to cell death in the brain, especially in the regions of the brain related to dementia.Materials and methodsThree microarray datasets (GSE5281, GSE9770, GSE28146) related to AD were downloaded from Gene Expression Omnibus (GEO) datasets. Ferroptosis-related genes were extracted from FerrDb database. Data sets were separated into two groups. GSE5281 and GSE9770 were used to identify ferroptosis-related genes, and GSE28146 was used to verify results. During these processes, protein–protein interaction (PPI), the Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. Finally, the differentiated values of ferroptosis-related genes were determined by receiver operator characteristic (ROC) monofactor analysis to judge their potential quality as biomarkers.ResultsTwenty-four ferroptosis-related genes were obtained. Using STRING (https://cn.string-db.org/) and Cytoscape with CytoHubba, the top 10 genes (RB1, AGPAT3, SESN2, KLHL24, ALOX15B, CA9, GDF15, DPP4, PRDX1, UBC, FTH1, ASNS, GOT1, PGD, ATG16L1, SLC3A2, DDIT3, RPL8, VDAC2, GLS2, MTOR, HSF1, AKR1C3, NCF2) were identified as target genes. GO analysis revealed that response to carboxylic acid catabolic process, organic acid catabolic process, alpha-amino acid biosynthetic process and cellular amino acid biosynthetic process were the most highly enriched terms. KEGG analysis showed that these overlapped genes were enriched in p53 signaling pathways, longevity regulating pathway, mTOR signaling pathway, type 2 diabetes mellitus and ferroptosis. Box plots and violine plots were created and verified to confirm the significance of identified target genes. Moreover, ROC monofactor analysis was performed to determine the diagnostic value of identified genes. Two genes (ASNS, SESN2) were subsequently obtained. For the tow genes, STRING was used to obtain the five related genes and determined enriched GO terms and KEGG pathways for those genes.ConclusionOur results suggest that ASNS and SENS2 may serve as potential diagnostic biomarkers for AD and provide additional evidence regarding the essential role of ferroptosis in AD.

Following the accelerated development of urbanization and industrialization, atmospheric particulate matter has become a significant threat to public health globally. Environmental health studies usually use the mass concentration of fine particles (PM2.5) as a base data to predict the health risks of particulate exposure. However, PM2.5 data from ground monitoring stations in China has not been provided until January 2013 by the Ministry of Environmental Protection of China. Hence, an alternative dataset of PM2.5 spatiotemporal distributions extending to years earlier than 2013 is urgently needed, which is of great significance to atmospheric environment assessment and pollution prevention and control. Atmospheric aerosol products by the moderate-resolution imaging spectroradiometer (MODIS) have been released since 2000, which provides the possibility to reconstruct historical PM2.5. However, most current methods do not have the ability to estimate PM2.5 mass concentration independently of ground observations. The PM2.5 mass concentration data set produced by PM2.5 remote sensing (PMRS) model based on physical processes does not depend on the ground observations, and also is not affected by the uncertainty of model emission sources or the completeness of chemical reaction mechanism. These ensure that the point-by-point validation for PM2.5 mass concentration data is more convincing, and the dataset can also be further used for model assimilation and artificial intelligence training to improve their predictions. In this study, we calculate the monthly PM2.5 mass concentration near the ground over land of China using aerosol inversion products (aerosol optical depth and fine-mode fraction) of MODIS and meteorological data (boundary layer height & relative humidity) provided by the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) data set. The results show that, in China, 6 pollution centers mainly concentrated in the central and eastern regions. The highest PM2.5 mass concentration occurred in winter, whereas the pollution range was larger in summer. There are 63.4% of validation sites with biases within ±20 μg m−3, and the expected error is as ±(15 μg m−3 + 30%) enveloped by the monthly mean PM2.5 mass concentrations. The monthly PM2.5 is stored as NETCDF format, with a spatial resolution of 1°×1°. The published data is available in http://www.dx.doi.org/10.11922/sciencedb.j00076.00061.

The compilation of technology lists addressing climate change has a guiding effect on promoting technological research and development, demonstration, and popularization. It is also crucial for China to strengthen ecological civilization construction, achieve the carbon emission peak and carbon neutrality target, and enhance global climate governance capabilities. This study first proposes the existing classification outline of the technology promotion lists, technology demand lists, and future technology lists. Then, different methodologies are integrated on the basis of the existing outline of four technology lists: China’s existing technological promotion list for addressing climate change, China’s demand list for climate change mitigation technology, China’s key technology list for addressing climate change, and China’s future technology list for addressing climate change. What’s more, core technologies are analyzed in the aspects of technology maturity, carbon reduction cost, carbon reduction potential, economic benefits, social influence, uncertainty, etc. The results show that: key industries and sectors in China already have relatively mature mitigation/adaptation technologies to support the achievement of climate change targets. The multi-sectoral system of promoting climate-friendly technologies has been established, which has played an active role in tackling climate change. Currently, climate technology needs are concentrated in the traditional technology and equipment upgrading, renewable energy technology, and management decision-making support technology. The key technologies are concentrated in 3 major areas and 12 technological directions that urgently need a breakthrough. For carbon emmission peak and nentrality, carbon depth reduction and zero carbon emissions and geoengineering technology (CDR and SRM) have played an important role in forming the structure of global emissions and achieving carbon neutrality in the future. Thus, the uncertainty assessment for the comprehensive technology cost-effectiveness, technology integration direction, technical maturity, ethics and ecological impacts is supportive to the national technology strategy. Finally, the presented study proposes several policy implications for medium- and long-term technology deployment, improving technology conversion rate, promoting the research and development of core technologies, and forming a technology list collaborative update and release mechanism.

Mapping the mass concentration of near-surface atmospheric particulate matter (PM) using satellite observations has become a popular research niche, leading to the development of a variety of instruments, algorithms, and datasets over the past two decades. In this study, we conducted a holistic review of the major advances and challenges in quantifying PM, with a specific focus on instruments, algorithms, datasets, and modeling methods that have been developed over the past 20 years. The aim of this study is to provide a general guide for future satellite-based PM concentration mapping practices and to better support air quality monitoring and management of environmental health. Specifically, we review the evolution of satellite platforms, sensors, inversion algorithms, and datasets that can be used for monitoring aerosol properties. We then compare various practical methods and techniques that have been used to estimate PM mass concentrations and group them into four primary categories: (1) univariate regression, (2) chemical transport models (CTM), (3) multivariate regression, and (4) empirical physical approaches. Considering the main challenges encountered in PM mapping practices, for example, data gaps and discontinuity, a hybrid method is proposed with the aim of generating PM concentration maps that are both spatially continuous and have high precision.

Objective(s): Oxymatrine can regulate glucose metabolism. But the underlying mechanisms remain unclear. We investigated the relationship of oxymatrine and voltage-gated potassium (Kv) channel in rat islet β cells and INS-1 cells.Materials and Methods: Insulin secretion and Kv channel currents were tested by radioimmunoassay and patch-clamp technique, respectively. The INS-1 cell viability was detected using cell counting kit-8 experiments. Flowcytometry analysis and western blot were employed for cell apoptosis and protein levels, respectively. INS-1 cell proliferation was assessed by the 5-Ethynyl-2’- deoxyuridine method. Results: Oxymatrine potentiated insulin secretion at high glucose (p Conclusion: The results indicate that oxymatrine can stimulate insulin secretion and decrease kv channel currents in islet β cells. Besides, oxymatrine also increases cell viability, proliferation, and reduces cell apoptosis in INS-1 cells. The effects of oxymatrine are related to kv channels. This finding provides new insight into the mechanisms of oxymatrine-regulated islet function.

Rheumatoid arthritis (RA) is a chronic autoimmune disease that primarily affects the joints. Microbial infection is considered a crucial inducer of RA. Alterations in the composition of intestinal bacteria in individuals with preclinical and established RA suggest a vital role of the gut microbiota in immune dysfunction characteristic of RA. However, the mechanisms by which gut dysbiosis contributes to RA are not fully understood. Furthermore, multiple therapies commonly used to treat RA may alter gut microbiota diversity, suggesting that modulating the gut microbiota may help prevent or treat RA. Hence, a better understanding of the changes in the gut microbiota that accompany RA should aid the development of novel therapeutic approaches. This mini-review discusses the impact of gut dysbiosis in the pathogenesis of RA, the selection of gut microbiota-related biomarkers for diagnosing RA, and provides examples of cross-modulation between the gut microbiota and some drugs commonly used to treat RA. Some suggestions and outlooks are also raised, which may help guide future research efforts.

Automatic detection and alarm of abnormal electrocardiogram (ECG) events play an important role in an ECG monitor system; however, popular classification models based on supervised learning fail to detect abnormal ECG effectively. Thus, we propose an ECG anomaly detection framework (ECG-AAE) based on an adversarial autoencoder and temporal convolutional network (TCN) which consists of three modules (autoencoder, discriminator, and outlier detector). The ECG-AAE framework is trained only with normal ECG data. Normal ECG signals could be mapped into latent feature space and then reconstructed as the original ECG signal back in our model, while abnormal ECG signals could not. Here, the TCN is employed to extract features of normal ECG data. Then, our model is evaluated on an MIT-BIH arrhythmia dataset and CMUH dataset, with an accuracy, precision, recall, F1-score, and AUC of 0.9673, 0.9854, 0.9486, 0.9666, and 0.9672 and of 0.9358, 0.9816, 0.8882, 0.9325, and 0.9358, respectively. The result indicates that the ECG-AAE can detect abnormal ECG efficiently, with its performance better than other popular outlier detection methods.

Background: Previous studies have shown that Leukocyte cell-derived chemotaxin2 (LECT2) is associated with the development of HCC. However, there are still no studies with a comprehensive analysis of the role of LECT2 in hepatocellular carcinoma (HCC).Methods: TCGA data sets were used to analyze the expression of LECT2 in HCC. In addition, the prognostic value of LECT2 in HCC was also investigated. DriverDBv3 was used to analyze the Mutation, CNV, and methylation profiles of LECT2. And, validated by immunohistochemistry in 72 HCC samples. The prognostic value of LECT2 and the correlation with clinicopathological features were analyzed. The GO/KEGG enrichment analysis of LECT2 co-expression and gene set enrichment analysis (GSEA) was performed using the R software package. The PPI interaction network was constructed by Search Tool for the Retrieval of Interacting Genes (STRING) database. Immune infiltration was estimated by the XCELL, TIMER, QUANTISEQ, MCPCOUNTER, EPIC, CIBERSORT abs and CIBERSORT algorithms, and Spearman was used to analyzing their correlation with LECT2. Moreover, we analyzed the correlation of LECT2 expression with immune checkpoint molecules and HLA genes. Finally, we analyzed the IC50 values of six chemotherapeutic drugs by the pRRophetic package.Results: Reduced LECT2 expression levels found in HCC patients. Moreover, decreased levels of LECT2 were associated with poor overall survival, disease-free survival, disease-specific survival, and progression-free survival. Besides, methylation was significantly associated with LECT2 expression. The functional enrichment analysis revealed that LECT2 may affect HCC progression through various pathways such as JAK/STAT signaling pathway, cell cycle, and pathways in cancer. Additionally, the results showed that LECT2 expression was negatively correlated with immune infiltration of B cells, Neutrophil, Monocyte, Cancer-associated fibroblast, and Myeloid dendritic cell, and positively correlated with T cell CD8+ naive, Endothelial cell, and Hematopoietic stem cell. LECT2 expression was negatively correlated with multiple immune checkpoint molecules and HLA genes. Chemosensitivity analysis showed that chemosensitivity was lower in the LECT2 high expression group. We validated the prognostic value of LECT2 and analysis of clinicopathological features showed a lower TNM stage in the group with high expression of LECT2.Conclusion: Low expression of LECT2 in HCC is closely associated with poor prognosis, LECT2 may have potential clinical applications due to its unique immunological effects.

Polycystic ovary syndrome (PCOS) is one of the most prevalent gynecological endocrine conditions affecting reproductive women. It can feature a variety of symptoms, such as obesity, insulin resistance, skin conditions, and infertility. Women with PCOS are susceptible to illnesses including mood disorders, diabetes, hypertension, and dyslipidemia. Among them, depression is the most common in PCOS and has a detrimental effect on quality of life. Depression may occasionally develop due to the pathological traits of PCOS, but its exact pathogenesis in PCOS have eluded researchers to date. Therefore, there is an urgent need to explore the pathogenesis and treatments of depression in PCOS. The present review discusses the epidemiology of depression in PCOS, potential pathogenic mechanisms underlying PCOS and depression, as well as some potential factors causing depression in PCOS, including obesity, insulin resistance, hyperandrogenism, inflammation, and infertility. Meanwhile, some common treatment strategies for depression in PCOS, such as lifestyle intervention, acupuncture, oral contraceptive pills, psychological intervention, and insulin-sensitizer, are also reviewed. To fully understand the pathogenesis and treatment of depression in PCOS, a need remains for future large-scale multi-center randomized controlled trials and in-depth mechanism studies.

ObjectivesTo evaluate the immunogenicity of the third dose of inactivated SARS-CoV-2 vaccine in rheumatoid arthritis (RA) patients and explore the effect of RA drugs on vaccine immunogenicity.MethodsWe recruited RA patients (n = 222) and healthy controls (HC, n = 177) who had been injected with a third dose of inactivated SARS-CoV-2 vaccine, and their neutralizing antibody (NAb) titer levels were assessed.ResultsRA patients and HC were age- and gender-matched, and the mean interval between 3rd vaccination and sampling was comparable. The NAb titers were significantly lower in RA patients after the third immunization compared with HC. The positive rate of NAb in HC group was 90.4%, while that in RA patients was 80.18%, and the difference was significant. Furthermore, comparison of NAb titers between RA treatment subgroups and HC showed that the patients in the conventional synthetic (cs) disease-modifying anti-rheumatic drugs (DMARDs) group exhibited no significant change in NAb titers, while in those receiving the treatment of biological DMARDs (bDMARDs), Janus Kinase (JAK) inhibitors, and prednisone, the NAb titers were significantly lower. Spearman correlation analysis revealed that NAb responses to SARS-CoV-2 in HC did differ significantly according to the interval between 3rd vaccination and sampling, but this finding was not observed in RA patients. In addition, NAb titers were not significantly correlated with RA-related laboratory indicators, including RF-IgA, RF-IgG, RF-IgM, anti-CCP antibody; C-RP; ESR; NEUT% and LYMPH%.ConclusionSerum antibody responses to the third dose of vaccine in RA patients were weaker than HC. Our study will help to evaluate the efficacy and safety of booster vaccination in RA patients and provide further guidance for adjusting vaccination strategies.

Highlights A zero-reflection-induced phase singularity is achieved through precisely controlling the resonance characteristics using two-dimensional nanomaterials. An atomically thin nano-layer having a high absorption coefficient is exploited to enhance the zero-reflection dip, which has led to the subsequent phase singularity and thus a giant lateral position shift. We have improved the detection limit of low molecular weight molecules by more than three orders of magnitude compared to current state-of-art nanomaterial-enhanced plasmonic sensors. Abstract Detection of small cancer biomarkers with low molecular weight and a low concentration range has always been challenging yet urgent in many clinical applications such as diagnosing early-stage cancer, monitoring treatment and detecting relapse. Here, a highly enhanced plasmonic biosensor that can overcome this challenge is developed using atomically thin two-dimensional phase change nanomaterial. By precisely engineering the configuration with atomically thin materials, the phase singularity has been successfully achieved with a significantly enhanced lateral position shift effect. Based on our knowledge, it is the first experimental demonstration of a lateral position signal change > 340 μm at a sensing interface from all optical techniques. With this enhanced plasmonic effect, the detection limit has been experimentally demonstrated to be 10–15 mol L−1 for TNF-α cancer marker, which has been found in various human diseases including inflammatory diseases and different kinds of cancer. The as-reported novel integration of atomically thin Ge2Sb2Te5 with plasmonic substrate, which results in a phase singularity and thus a giant lateral position shift, enables the detection of cancer markers with low molecular weight at femtomolar level. These results will definitely hold promising potential in biomedical application and clinical diagnostics.

Network anomaly detection plays a crucial role as it provides an effective mechanism to block or stop cyberattacks. With the recent advancement of Artificial Intelligence (AI), there has been a number of Autoencoder (AE) based deep learning approaches for network anomaly detection to improve our posture towards network security. The performance of existing state-of-the-art AE models used for network anomaly detection varies without offering a holistic approach to understand the critical impacts of the core set of important performance indicators of AE models and the detection accuracy. In this study, we propose a novel 5-layer autoencoder (AE)-based model better suited for network anomaly detection tasks. Our proposal is based on the results we obtained through an extensive and rigorous investigation of several performance indicators involved in an AE model. In our proposed model, we use a new data pre-processing methodology that transforms and removes the most affected outliers from the input samples to reduce model bias caused by data imbalance across different data types in the feature set. Our proposed model utilizes the most effective reconstruction error function which plays an essential role for the model to decide whether a network traffic sample is normal or anomalous. These sets of innovative approaches and the optimal model architecture allow our model to be better equipped for feature learning and dimension reduction thus producing better detection accuracy as well as f1-score. We evaluated our proposed model on the NSL-KDD dataset which outperformed other similar methods by achieving the highest accuracy and f1-score at 90.61% and 92.26% respectively in detection.