Search

BackgroundNosocomial transmission of Clostridioides difficile infection (CDI) has been documented in Ningbo, China. However, data on molecular characteristics, clonal transmission, and risk factors of CDI in this region remain limited.MethodsA cross-sectional study enrolled hospitalized patients with diarrhea during September to November 2021. Stool samples from all patients were tested for C. difficile, and isolated strains underwent toxin gene identification, genotyping, and antibiotic susceptibility testing. Whole-genome sequencing and epidemiological variables were analyzed in patients infected with C. difficile strains of the same sequence types (STs) to identify nosocomial transmission and risk factors for CDI.ResultsOf the 907 investigated patients, 115 (12.7%) had microbiologically proven CDI, as their diarrhea was associated with toxigenic C. difficile strains, which comprised 106 A+B+CDT−, 3 A−B+CDT−, and 6 A+B+CDT+. Predominant genotypes (ST2, ST3, ST35, and ST54) exhibited distinct antibiotic resistance patterns. ST54 strains showed higher resistance to erythromycin (100%) but lower resistance to moxifloxacin (18.2%) and gatifloxacin (18.2%) (χ2 = 10.24–16.65, p 10 days) (odds ratio [95% confidence interval], 1.76 [1.05–2.93]) and penicillin-class antibiotics (1.69 [1.11–2.58]) were risk factors for CDI, with the latter being an independent risk factor (1.57 [1.02–2.42]). For C. difficile ST35 infection, intensive care unit (12.00 [2.77–52.05]) and neurology departments (8.08 [1.46–44.65]) admissions were risk factors, with the latter as an independent risk factor (1.56 [1.01–2.40]).ConclusionMultiple C. difficile genotypes with varied antibiotic resistance patterns circulated in Ningbo, with ST35 causing nosocomial clonal transmission among different floors and buildings within the hospital. These findings and the identified risk factors necessitate enhanced surveillance and infection control in the region.

Abstract STAM Binding Protein Like 1 (STAMBPL1), functions as a deubiquitinase (DUB) and plays a significant role in various types of cancers. However, its effect as a DUB participating in the HCC tumorigenesis and progression still unknown. In the study, the upregulation and strong prognosis value of STAMBPL1 were identified in HCC patients. Functionally, STAMBPL1 significantly promoted HCC cells proliferation and metastasis, and it interacts with TRAF2 and stabilize it via the deubiquitination at the K63 residue. The TRAF2 upregulation stabilized by STAMBPL1 overexpression transfers of P65 protein into the nucleus and activates the WNT/PI3K/ NF-kb signaling pathway. The 251–436 sites of STAMBPL1 particularly interact with the 294–496 sites of TRAF2, thereby exerting the function of DUB and removing the ubiquitin molecules attached to TRAF2. Our research unveiled a new function of STAMBPL1 in mediating TRAF2 deubiquitination and stabilization, thereby activating the WNT/PI3K/NF-kb signaling pathway, suggesting its potential as a novel biomarker and therapeutic target for HCC.

ObjectivesIt is important to accurately discriminate between clinical Clostridioides difficile infection (CDI) and colonization (CDC) for effective antimicrobial treatment.MethodsIn this study, 37 stool samples were collected from 17 CDC and 20 CDI cases, and each sample were tested in parallel through the real-time cell analysis (RTCA) system, real-time PCR assay (PCR), and enzyme-linked immunosorbent assay (ELISA).ResultsRTCA-measured functional and toxical C. difficile toxin B (TcdB) concentrations in the CDI group (302.58 ± 119.15 ng/mL) were significantly higher than those in the CDC group (18.15 ± 11.81 ng/mL) (p = 0.0008). Conversely, ELISA results revealed no significant disparities in TcdB concentrations between the CDC (26.21 ± 3.57 ng/mL) and the CDI group (17.07 ± 3.10 ng/mL) (p = 0.064). PCR results indicated no significant differences in tcdB gene copies between the CDC (774.54 ± 357.89 copies/μL) and the CDI group (4,667.69 ± 3,069.87 copies/μL) (p = 0.407). Additionally, the functional and toxical TcdB concentrations secreted from C. difficile isolates were measured by the RTCA. The results from the CDC (490.00 ± 133.29 ng/mL) and the CDI group (439.82 ± 114.66 ng/mL) showed no significant difference (p = 0.448). Notably, RTCA-measured functional and toxical TcdB concentration was significantly decreased when mixed with pooled CDC samples supernatant (p = 0.030).ConclusionThis study explored the novel application of the RTCA assay in effectively discerning clinical CDI from CDC cases.

In recent years, the rapid increase of CO2 emission has caused severe environmental issues. The environmental concern has made how to reduce the carbon emissions become a hot topic. Many scholars and research teams believe that the organic amine chemical absorption technology is the most favored and promising carbon capture technology due to its highly CO2 removal effectiveness. However, it is not applied wildly in industrial environment since the desorption process energy consumption is too much, over 4 GJ/t CO2. Many researchers report that catalysts can help to reduce the desorption energy. And it is generally assumed that four key properties of solid acid catalysts determined the performance of solid acid catalysts in the process of CO2 desorption: the total number of acid sites; specific surface area; the ratio of Brønsted acid sites to Lewis acid sites; the amount of Brønsted acid sites. Therefore, this paper reviews the recent research on the effect of different catalysts on the energy consumption of CO2 desorption and the progress of research on improving catalyst performance. Also, it provides views on the possible problems in practical industrial applications.

The net shell is a widely utilized large-span space structure known for its aesthetically pleasing design and uniform load distribution, as well as serving as a prominent architectural landmark. In recent years, the impact resistance research of mesh and shell structures has garnered increased attention due to the accumulation of local conflicts. In this study, a parametric model of the spherical mesh shell was developed with Rhino software, and a numerical analysis model for a K8 mesh shell was established through the application of the ABAQUS finite element analysis software. Subsequently, the proposed numerical analysis method for the impact test was applied to validate its accuracy. The research also explored various dynamic constitutive models, such as Cowper-Symonds, Johnson-Cook, modified temperature term Johnson-Cook, and modified strain term and temperature term Johnson-Cook, with the assessment of their impact on the numerical simulation of impact resistance. Based on the impact dynamic response of the spherical net shell of different materials, the selection of an appropriate dynamic constitutive model for the numerical simulation of impact resistance in the spherical net shell was the MJ-C model. The comparative analysis of different materials, including Q235B, Q355B, Q460D, and 6061-T6, indicated that when the impact material failed to penetrate the structure instantly, the improvement of the material strength would enhance the impact resistance of the structure. On the other hand, when the impact material managed to penetrate the structure instantly, the material strength would not significantly help mitigate the damage. Notably, brittle materials, such as aluminum alloy, exhibited a distinct absence of a pronounced yield stage compared with low-carbon steel, which ultimately led to a relatively abrupt deformation.

Abstract Background At present, the proportion of undiagnosed diabetes in Chinese adults is as high as 15.5%. People with diabetes who are not treated and controlled in time may have various complications, such as cardiovascular and cerebrovascular diseases and diabetic foot disorders, which not only seriously affect the quality of life of people with diabetes but also impose a heavy burden on families and society. Therefore, prevention and control of type 2 diabetes is of great significance. Methods We constructed a logistic regression model, a neural network model and a decision tree model to analyse the risk factors for type 2 diabetes and then compared the prediction accuracy of the different models by calculating the area under the relative operating characteristic (ROC) curve and back-inputting the data into the model. Results The prevalence of type 2 diabetes in 4177 subjects who were not diagnosed with type 2 diabetes was 9.31%. The most influential factors associated with type 2 diabetes were triglyceride (TG) ≥ 1.17 mmol/L (odds ratio (OR) =2.233), age ≥ 70 years (OR = 1.734), hypertension (OR = 1.703), alcohol consumption (OR = 1.674), and total cholesterol≥5.2 mmol/L (TC) (OR = 1.463). The prediction accuracies of the three prediction models were 90.8, 91.2, and 90.7%, respectively, and the areas under curve (AUCs) were 0.711, 0.780, and 0.698, respectively. The differences in the AUCs after back propagation (BP) of the neural network model, logistic regression model and decision tree model were statistically significant (P

Three-dimensional (3D) printing is an innovative manufacturing process based on 3D digital models that involves layer-by-layer addition of materials. In recent years, 3D printing has made good progress in the field of construction, thereby leading to more stringent requirements for materials. In this study, we first compare different equipment and materials used for 3D printing concrete. Subsequently, the mix ratio of extruded and cured 3D printed concrete is studied by using flow and slump as the main evaluation indexes. Through a universal test, the influence of different dosages of water reducer, retarder, and latex powder on the performance of 3D printed concrete (compression resistance strength) is studied. Furthermore, the optimum mix ratio for fiber reinforced concrete is determined, based on which axial pull-out, axial compression, and three-point bending tests are performed to elucidate the peak compressive strength, load–displacement curve, and mechanical properties of 3D printed concrete. By employing the ABAQUS finite element software, the shaft pulling force and axial compression of 3D printed concrete are simulated and analyzed to determine the parameters influencing the bonding performance of different 3D printed concrete layers. Moreover, the influence of water reducer and sand–glue ratio is observed to be greater than that of water gel ratio and sodium gluconate. The testing results showed that the mechanical strength of 3D printed concrete is lower than that of poured concrete. Meanwhile, bending and compressive strengths of 3D printed concrete and poured concrete are quite different.

By using straw to build an assembled flood wall, this study provided new ideas for useful applications of straw and for the development of assembly flood control facilities. A straw flexible space assembly flood control system is designed on the basis of Revit, and a hydraulic test of a scaled-down model of the system is conducted using a water-retaining test machine to prove the stability and impact resistance of the system. Finally, a numerical analysis model of the straw flexible space flood control system is established using ABAQUS software to perform finite element analysis of the system. A comparison of the test results and the numerical analysis results shows that they can be well fitted. Thus, this study lays a theoretical foundation for a large-scale engineering application of the proposed system.

Abstract Background To explore the risk factors of coexisting prediabetes and prehypertension, to provide theoretical basis for early intervention. Methods A multi-stage stratified random cluster sampling method was used to randomly select adult residents from Jilin Province in 2013 for questionnaire surveys, physical examinations, and laboratory tests. Results The prevalence of coexisting prediabetes and prehypertension in Jilin Province was 11.3%. The binary Logistic regression results showed that age, sex, education, triglyceride (TG), BMI, waist circumference and alcohol consumption were the effects of factor coexisting prediabetes and prehypertension. Conclusion It is important to pay attention to the early stage of hypertension and diabetes, control the transition from prehypertension and prediabetes to hypertension and diabetes, and improve the health of residents.

Based on available magnetic resonance imaging (MRI) studies, hippocampal alteration is one of the hallmarks during cognitive decline. However, the longitudinal hippocampal morphometric changes during the initial cognitive decline are unclear. Exploring a validated biomarker with high clinical relevance is urgent. This work proposed an automated MRI-driven longitudinal hippocampal alteration analysis system (LHAAS), which consists of hippocampal segmentation, reconstruction, registration, multivariate morphometric feature extraction, and longitudinal analysis of hippocampal morphometric and volumetric differences between groups. LHAAS was applied on two groups: cognitive unimpaired (CU) participants who maintained cognitive unimpaired (non-Progressors), and participants who converted to MCI during the following four years (Progressors). LHAAS can detect and visualize subtle deformations in the bilateral hippocampus of CU progressors four years before they show initial cognitive decline. For CU progressors, hippocampal atrophy initially occurs at the CA1 subregion and then along with disease progression, spreading to the CA2-3 and Subiculum subregion, exhibiting a left-greater-than-right trend. The volumetric analyses showed similar results. Besides, hippocampal subregions highly correlated with clinical measurement were identified by correlation analysis. LHAAS can accurately reflect the small hippocampal subregional atrophy at preclinical AD. This proposed system can track the longitudinal hippocampal alterations in the early stages of AD and provide insights for early intervention. Clinical and Translational Impact Statement: LHAAS offers early detection of subtle hippocampal alterations at preclinical AD. This advance enables pathological research and timely interventions to potentially improve patient outcomes in clinical implementation.

Metal halide perovskites have emerged as game-changing semiconductor materials in optoelectronics. As an efficient micro-/nano-manufacturing technology, direct laser writing (DLW) has been extensively used to fabricate patterns, micro/nanostructures, and pixel arrays on perovskites to promote their optoelectronic applications. Owing to the unique ionic properties and soft lattices of perovskites, DLW can introduce rich light–matter interactions, including laser ablation, crystallisation, ion migration, phase segregation, photoreaction, and other transitions, which enable diverse functionalities in addition to the intrinsic properties of perovskites. Based on their patterned structures, perovskites have numerous applications in displays, optical information encryption, solar cells, light-emitting diodes, lasers, photodetectors, and planar lenses, which are comprehensively discussed in this review. Finally, we discuss the challenges that must be addressed for the future development of this fascinating field.

Although federated learning (FL) represents a distributed machine learning paradigm that ensures privacy protection, the failure of stragglers to upload local models in a timely manner results in an overall degradation of the global model’s performance, and the difficulty of accurately predicting whether clients will succeed in uploading a local model makes client selection still a challenge. To address this issue, existing works mainly focus on increasing the number of clients who participate in training within a fixed time, however, the fact is that the performance of a global model depends on the data used for training. Therefore, increasing the clients’ data contribution to the global model can effectively enhance the global model’s performance. To this end, we propose a Bayesian estimation based FL framework, named FedBoost, to enhance the performance of the model when straggler problem exists. Specifically, we formulate a long-term problem aimed at maximizing clients’ cumulative effective data contributions, while satisfying a long-term fairness constraints, which ensure a minimum selection frequency for clients. By analyzing the stability of virtual queues, we transform the long-term problem into a stepwise one via Lyapunov optimization, reducing its computational complexity. Due to the inability of the server to predict whether clients successfully upload the local model before receiving the actual upload, we use Bayesian estimation based on the observed frequency of successful uploads to estimate this probability. Last, extensive experimental results indicate that the average test accuracy of our FedBoost is up to 5.59% higher than both FedAvg and FedCS on three real-world datasets, and achieves test loss that are at most 0.1646 below the two baselines. Furthermore, the value of Lapunov function remains lower than 1.4, and at least 85% of the estimation of probabilities are in a reasonable range.

Pain and inflammation are associated with the pathophysiology of different clinical conditions. The Lysimachia capillipes Hemsl. capilliposide (LCc) is the main bioactive component of this Chinese medicinal herb, which is widely used as a remedy for the treatment of colds and arthritis. This study investigated the analgesic and antiinflammatory activities of LCc in an animal model. LCc had no significant influence on the spleen, lung, liver and stomach coefficients in mice. Pharmacological studies showed that LCc at all doses (40, 60 and 90 mg/kg) increased the latency period of paw licking induced by thermal stimulation, and at the dose of 40 mg/kg it significantly suppressed abdominal writhing episodes of mice induced by intraperitoneal (i.p.) injection of acetic acid. LCc also had antiinflammatory effect on inflammation models. Doses of 60 and 90 mg/kg suppressed paw edema induced by subcutaneous (s.c.) injection of carrageenan. Mechanistic studies revealed that the antiinflammatory effect of LCc was associated with inhibition of the production of malondialdehyde (MDA), prostaglandin E2 (PGE2), tumor necrosis factor (TNF-α), cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2) in paw tissue of carrageenan-injected mice. These results show that LCc has analgesic and antiinflammatory effects in mice. [ABSTRACT FROM AUTHOR]

A social vulnerability evaluation of storm surges is important for any coastal city to commence in order to provide marine disaster preparedness and mitigation procedures and to formulate post-disaster emergency plans for coastal communities. This study establishes an integrated evaluation system of social vulnerability by blending a variety of single evaluation methods, applying the idea of combination weighting and calculating the social vulnerability index of storm surges. Shenzhen, with a current reputation of having the most economic development potential and a representative city in China, is chosen to evaluate its social vulnerability to storm surges via a historical social and economic statistical dataset spanning from 1986 to 2016. The research extends further by analyzing the city’s temporal variability. Results reveal that social vulnerability keeps almost constant from 1986–1991 and 1993–2004, while it decreased sharply in the remainder of times to show a ‘stair-type’ declining curve over the past 30 years. Resilience is progressively increasing by virtue of a continuous increase in medical institutions, fixed asset investments and salary levels of employees. These determinants contribute to the overall downward trend of social vulnerability for Shenzhen. Exposure and sensitivity increased slowly with some fluctuation, causing the changes of social responsibility to transpire. [ABSTRACT FROM AUTHOR]