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The effects of the alkyl chain length of the mesoporogen on the physicochemical properties and 1-octene hydroisomerization of hierarchical SAPO-11 have been investigated.

AIM: To compare the oncological survival outcome between extended resections and segmental resection for non-metastatic splenic flexure tumors. METHODS: A total of 10063 splenic flexure colon cancers patients who underwent extended resection (n=5546) or segmental resection (n=4517) from 2010 to 2018 were included from the Surveillance, Epidemiology, and End Results (SEER)-registered database. Survival rates were compared between groups. To reduce the inherent bias of retrospective studies, propensity score matching (PSM) analysis was performed. RESULTS: Patients from the extended resection group had higher pT stage, pN stage, larger tumor size, and higher rates of elevated CEA level, perineural invasion, and tumor deposits than those from the segmental resection group (each PCONCLUSION: Extended procedures have no significant oncological benefits over segmental resection in the treatment of non-metastatic splenic flexure colon cancer, even for locally advanced cases. The larger number of harvested lymph nodes in the extended resection group did not confer any advantage relative to segmental resection with regard to CSS, since it was not associated with an increase in the number of invaded lymph nodes harvested.

Over the years, numerous evidences have demonstrated that microbes living in the human body are closely related to human life activities and human diseases. However, traditional biological experiments are time-consuming and expensive, so it has become a research topic in bioinformatics to predict potential microbe-disease associations by adopting computational methods. In this study, a novel calculative method called BPNNHMDA is proposed to identify potential microbe-disease associations. In BPNNHMDA, a novel neural network model is first designed to infer potential microbe-disease associations, its input signal is a matrix of known microbe-disease associations, and its output signal is matrix of potential microbe-disease associations probabilities. And moreover, in the novel neural network model, a new activation function is designed to activate the hidden layer and the output layer based on the hyperbolic tangent function, and its initial connection weights are optimized by adopting Gaussian Interaction Profile kernel (GIP) similarity for microbes, which can improve the training speed of BPNNHMDA efficiently. Finally, in order to verify the performance of our prediction model, different frameworks such as the Leave-One-Out Cross Validation (LOOCV) and k-Fold Cross Validation ( k-Fold CV) are implemented on BPNNHMDA respectively. Simulation results illustrate that BPNNHMDA can achieve reliable AUCs of 0.9242, 0.9127 ± 0.0009 and 0.8955 ± 0.0018 in LOOCV, 5-Fold CV and 2-Fold CV separately, which are superior to previous state-of-the-art methods. Furthermore, case studies of inflammatory bowel disease (IBD), asthma and obesity demonstrate that BPNNHMDA has excellent prediction ability in practical applications as well.

The reliable operation of flexible display devices poses a significant engineering challenge regarding the metrology of high barriers against water vapor. No reliable results have been reported in the range of 10–6 g∙(m2∙d)−1, and there is no standard ultra-barrier for calibration. To detect trace amount of water vapor permeation through an ultra-barrier with extremely high sensitivity and a greatly reduced test period, a predictive instrument was developed by integrating permeation models into high-sensitivity mass spectrometry measurement based on dynamic accumulation, detection, and evacuation of the permeant. Detection reliability was ensured by means of calibration using a standard polymer sample. After calibration, the lower detection limit for water vapor permeation is in the range of 10–7 g∙(m2∙d)−1, which satisfies the ultra-barrier requirement. Predictive permeation models were developed and evaluated using experimental data so that the steady-state permeation rate can be forecasted from non-steady-state results, thus enabling effective measurement of ultra-barrier permeation within a significantly shorter test period.

Background: Research has shown that essential proteins play important roles in the development and survival of organisms. Because of the high costs of traditional biological experiments, several computational prediction methods based on known protein-protein interactions (PPIs) have been recently proposed to detect essential proteins. Objective: Here, a novel prediction model called IoMCD is proposed to identify essential proteins by combining known PPIs with a variety of biological information about proteins, including gene expression data and homologous information of proteins. Methods: Compared to the traditional state-of-the-art prediction models, IoMCD involves two kinds of weights that are obtained, respectively, by extracting topological features of proteins from the original known protein–protein interaction (PPI) networks and calculating the Pearson correlation coefficients (PCCs) between the gene expression data of proteins. Based on these two kinds of weights and adopting a cross-entropy method, a unique weight is assigned to each protein. Subsequently, the homologous information of proteins is used to calculate an initial score for each protein. Finally, based on the unique weights and initial score of proteins, an iterative method is designed to measure the essentialities of proteins. Results: Intensive experiments were performed, and simulation results showed that the prediction accuracy of IoMCD, based on the dataset downloaded from the DIP and Gavin databases, was 92.16% and 89.71%, respectively, in the top 1% of the predicted essential proteins. Conclusion: Both simulation results demonstrated that IoMCD can achieve excellent prediction accuracy and could be an effective method for essential protein prediction.

Background Non-prescription antibiotic use at community is a main driver of antimicrobial resistance. Cough is a common condition and prevalent in all townships, including China. This study aims to investigate the non-prescription antibiotic use for cough in China and explore to which extent antibiotic use knowledge was correctly instructed in communities. Methods A probability-proportionate-to-size sampling method was adopted to survey from all 14 townships in Yiwu city, China. All participants were investigated by face-to-face interview on Portable Android Devices. The continuous variables were presented by mean and standard deviation or medium and inter-quartile range (IQR). The categorical variables were presented using percentage or constituent ratio. Chi-square test for univariate analysis and logistic regression for multivariate analysis were conducted to assess the odds ratios and 95% confidence intervals, respectively. Results A total of 3034 respondents across all the 14 townships and the 50 natural villages/streets completed all key items of the questionnaire. Of 2400 (79.10%) respondents stated that they experienced cough in the past 12 months with the medium age of 36.5 (IQR: 26–49) and 12.21% (293/2400) respondents had the non-prescription antibiotic use behavior. Among those 293 respondents, the proportion of non-prescription antibiotic use for cough peaked at around 16% among people aged 30–39 years old. The major sources of antibiotics were pharmacy (77.70%) and/or family storage (43.92%). Conclusions Non-prescription antibiotics use for cough is prevalent in the community, especially among people in their thirties. Strengthened drug purchase regulation and well-trained professional pharmacists would be promising alternatives to ameliorate AMR. Moreover, penetrating antibiotics knowledge to common citizens and is an urgent task to alleviate antimicrobial resistance. Therefore, proactive policies and regulations should be made to improve current situations.

It is still a great challenge to develop a new porous carbon adsorbent with excellent separation performance and to recover low-concentration CH4 in coal mine gas. This work provides a new idea for the study of CH4 adsorption on activated carbon (AC) composites. Composite materials with microporous structures were prepared from coconut-shell activated carbon (CAC) doped with graphene oxide (GO) by a chemical activation process in this paper. The expansion and dissociation of GO at high temperatures indirectly improve the specific surface area (SSA) of the composite. The interlayer aggregation is reduced, the activation effect is improved, and a new low-cost adsorption material is prepared. The SSA of CAC-50 is more than 3000 m2·g-1. A high SSA and a narrow pore size distribution lead to a higher total adsorption capacity of CH4. The breakthrough test also confirmed that AC/GOs had a better adsorption capacity for CH4. The separation performance of the CH4/N2 mixture is not good at room temperature, which is due to the influence of a high SSA and average pore size. As a low-cost and rich material, CAC has a wide range of application prospects. The composite is a potential material for recovering low-concentration CH4 from the coal mine, which is worthy of attention. In the future, the selectivity of AC/GOs to CH4 can be increased by loading functional groups or modification.

We propose a unified competition and cooperation framework for n insurers and investigate the resulting reinsurance game problem. Each insurer's surplus is assumed to be a diffusion process. Each i...

To establish a dynamic nomogram based on preoperative clinical data for prediction of lateral lymph node metastasis (LLNM) of papillary thyroid carcinoma.Retrospective study.The Sixth Affiliated Hospital of Sun Yat-Sen University.The data of 477 patients from 2 centers formed the training group and validation group and were retrospectively reviewed. Preoperative clinical factors influencing LLNM were identified by univariable and multivariable analysis and were to construct a predictive dynamic nomogram for LLNM. Receiver operating characteristic analysis and calibration curves were used to evaluate the predictive power of the nomogram.The following were identified as independent risk factors for LLNM: male sex (odds ratio [OR] = 4.6,The dynamic nomogram for preoperative prediction of LLNM in papillary thyroid carcinoma can help surgeons identify high-risk patients and develop individualized treatment plans.

A cluster of Chlamydia psittaci (C. psittaci) cases was reported in Zhejiang Province, China, 2019. This study evaluates the extent of the outbreak and determines the source of infection. Real-time PCR and sequencing of the ompA gene of C. psittaci were performed to identify the cases, the domesticated poultry and close contacts. The index patient was a 76-year-old woman with chronic vertigo, and Case 2 was a 64-year-old female farmer with herpes zoster. Both women bought psittaci-infected chickens or ducks from the same mobile street vendor and raised them for 10 days and 23 days before fever onset. There were no direct contact between the two women. C. psittaci test was positive for the two patients, one sick chicken, three healthy ducks and the vendor's chicken cage. Phylogenetic analysis showed that all seven C. psittaci positive samples carried identical ompA genotype A of C. psittaci. Of all of the patients' 148 close contacts, none tested positive for C. psittaci, or developed acute respiratory symptoms. Both patients were discharged after a 4-week hospital stay. In conclusion, the source of this cluster was the poultry infected with C. psittaci, which occasionally cause infections in farmers, but inter-human transmission seems unlikely.

The development of double encryption system enables information to switch reversibly between "False" and "True", which helps to ensure information security in the transmission process. Herein, a biomimetic cellulose nanofibre-based double information encryption sensor (CNF-DIES) with an excellent pH response and fluorescence colour-switching performance was prepared with fluorescein isothiocyanate and protoporphyrin IX modified acetylated cellulose nanofibres (ACNF) as the pH response switch and background, respectively. Interestingly, with the addition of cellulose, CNF-DIES can be regarded as both a dye and an ink binder, which can realize direct writing function. The fluorescein grafted to ACNF guaranteed the stability of writing and avoided the "coffee ring" phenomenon. The handwriting written by CNF-DIES processes excellent light/pH double encryption performance. Besides, the film prepared by CNF-DIES can realize high resolution fingerprint imaging. This work demonstrated a strategy for pH-responsive colour-tunable materials for sensors and double information encryption.

The present study aimed to explore the role of long non‑coding (lnc)RNA FTX and ubiquitin‑conjugating enzyme E2C (UBE2C) in promoting the progression of renal cell carcinoma (RCC) and the underlying regulatory mechanism. Relative levels of lncRNA FTX, UBE2C, AKT, CDK1 and CDK6 in RCC cell lines were detected by reverse transcription‑quantitative (RT‑q). Expression levels of UBE2C, phosphorylated (p)‑AKT/AKT, p‑CDK1/CDK1 and p‑CDK6/CDK6 in RCC and paracancerous specimens and RCC cells were measured by western blot or immunohistochemistry assay. In addition, the proliferative rate, cell viability, cell cycle progression, migratory rate and invasive rate of RCC cells overexpressing lncRNA FTX by lentivirus transfection were determined by a series of functional experiments, including the colony formation assay, MTT assay, flow cytometry, Transwell assay and wound healing assay. The targeted binding relationship in the lncRNA FTX/miR‑4429/UBE2C axis was validated by dual‑luciferase reporter assay. By intervening microRNA (miR)‑4492 and UBE2C by the transfection of miR‑4429‑mimics or short interfering UBE2C‑2, the regulatory effect of lncRNA FTX/miR‑4429/UBE2C axis on the progression of RCC was evaluated. Finally, a xenograft model of RCC in nude mice was established by subcutaneous implantation, thus evaluating the

Pelvic organ prolapse is seriously harmful to women's health and daily activities, and the incidence rate increases with age, which is more common among middle-aged and elderly women. Common treatment schemes are prone to relapse or complications. The purpose of this article was to study the clinical effect of laparoscopic pelvic floor reconstruction without mesh implantation in the treatment of pelvic organ prolapse and the influence of postoperative serum inflammatory factors, stress indicators, urination function and sexual function. The clinical curative effect of the operation plan was evaluated by the determination of POP-Q value and objective cure rate. The enzyme-linked immunosorbent assay determined the serum inflammatory factors and stress indexes before and after the operation. Urination function was detected by a urodynamics detector, and sexual function was investigated by a PISQ-12 questionnaire. The results show that laparoscopic pelvic floor reconstruction without mesh implantation has good clinical efficacy in the treatment of pelvic organ prolapse, with less stimulation to patients and less inflammation. After the operation, the patient's maximum urine flow rate exceeded 18mL/s, the sexual function score exceeded 45 points, and the urination function and sexual function were effectively improved.

Thin-walled cylindrical shell structures are widely used in various engineering fields due to their highly efficient load carrying capacity. This kind of structures is prone to buckling failure when subjected to axial compression loads. Machining the shell into corrugated shape is an effective method to prevent buckling. Rational design of corrugated shells can improve the load carrying efficiency of shell structures. However, there are few studies focused on the effects of various parameters on the longitudinal corrugated cylindrical shell buckling. In this paper, numerical studies are performed to analyze the factors affecting the buckling behaviors of thin-walled longitudinal corrugated cylindrical shells under axial compression loads. The cross section of the corrugated shell is obtained by superposing the sine curve on the reference circle. The critical buckling load, buckling mode and imperfection sensitivity of the longitudinal corrugated cylindrical shells are examined and compared with ordinary cylindrical shells. The effects of shell dimensions and material yield strength are taken into account. In addition, the influence of cross section shape parameters on the critical buckling load is considered, including the amplitude A and wave number k. Results show that the axial load carrying capacity of longitudinal corrugated cylindrical shells is better than ordinary cylindrical shells, and rational design of cross section shape can enhance the stability of corrugated shells. This work can provide some reference for relevant experimental studies. Furthermore, it can also give some guides for the application of thin-walled longitudinal corrugated cylindrical shells in actual engineering.

As a clean and efficient secondary energy, hydrogen energy is of great significance for building a clean, low-carbon, safe and efficient energy system. At present, high-pressure gaseous hydrogen storage systems for vehicles mostly use carbon fiber reinforced composite materials as the pressure-bearing materials of hydrogen storage vessel to obtain a lighter mass, so as to ensure the hydrogen storage system has a higher hydrogen storage density. However, unlike traditional steel hydrogen storage vessel, carbon fiber composite hydrogen storage vessel has low rigidity and is prone to bending and deformation during manufacture and use, which can cause safety accidents. Most of the previous studies on mechanical properties have focused on flat laminates, which are of limited help to the study of hydrogen storage vessel. In view of this situation, this work fabricated the curved carbon fiber laminates with the same manufacturing process as the hydrogen storage vessel and investigated their flexural performance using a combination of experimental and finite element methods. The bending experiments of curved carbon fiber laminates at different angles were carried out. And the finite element model for flexural performance prediction of curved carbon fiber laminates was established through validation against the experimental results. A parametric study was further performed to analyzed the influence of carbon fiber winding angle on the flexural performance. This work will provide reference and basis for the subsequent research on the flexural performance of carbon fiber composite hydrogen storage vessel.

As a kind of clean energy with good prospect, the demand of trans-regional transportation of hydrogen is increasing rapidly. However, due to the difficulty and high cost of pipeline transportation, tube bundle containers are more used to transport hydrogen. As the fixing device of tube bundle container, the frame structure should not only ensure that the gas cylinder can be fixed, but also meet the requirements of stiffness and strength. In order to improve the efficiency of hydrogen transportation, a new frame structure of 40-foot high pressure and large capacity tube bundle container for road transportation was designed. There are two groups of tube bundles at the front and rear of the tube bundle container, carrying 18 hydrogen storage bottles. The total hydrogen storage capacity is more than 1000kg and the pressure is 52MPa. The design process is as follows: firstly, the stress analysis of the original frame structure under four inertia force conditions was carried out, and it was found that the structure was difficult to meet the strength requirements for road transportation. Then, the beam distribution of tube bundle container frame structure was preliminarily determined by using the method of topology optimization and the geometric model of the optimized frame structure was remodeled according to the topology optimization results. Finally, the static analysis of the frame structure under various driving inertia force loads was carried out by ANSYS Workbench finite element analysis software. The results show that the designed tube bundle container frame structure meets the requirements of strength. This work provides a reference for the design and safety evaluation of similar tube bundle container frame structure products.

In situ hydrogels with rapid hemostasis and antibacterial activity have received considerable attention in the field of wound healing. Herein, a white light and NIR dual light-responsive cellulose nanofibril (CNF)-based in situ hydrogel wound dressing is tailored by using white light-responsive CNF and endogenous antibacterial CNF as the skeleton, Prussian blue nanoparticles, Pluronic® F127 and hydroxypropyl methyl cellulose as the NIR, temperature-responsive switch and binder, respectively. The dressing exhibits rapid hemostasis properties in rat liver injury model with low blood loss of 286.4 mg and short hemostasis time of 63 s. Meanwhile, the antibacterial activity of the dressing with white and NIR irradiation against Escherichia coli, Staphylococcus aureus and methicillin-resistant Staphylococcus aureus (MRSA) is higher than 99.9 %. Interestingly, the dressing with biocompatibility can promote MRSA infection wound healing and can be removed on demand without secondary injury to skin. Therefore, it has promising applications for first-aid hemostasis and wound healing.

Since the outbreak of COVID-19 in December 2019 in Wuhan, Zhejiang has become the province with the largest number of cases. The aim of this article is to present Zhejiang province’s experience of establishing an accurate and smart control mechanism for epidemic prevention and control and resumption of work and production using a ‘five-colour epidemic chart’. The number of confirmed cases, proportion of local cases, and occurrence of clustered outbreaks were used as evaluation indicators to calculate the county-level epidemic risk and were assigned different weight coefficients; the absence of cases for 3 and 7 consecutive days was used as the adjustment index. When the first chart was published on February 9, there were 1 very-high-risk, 12 high-risk, and 12 low-risk counties. Under the five-colour chart, Zhejiang began to adopt precise measures to prevent and control the epidemic and resume work and production. By February 24, the low-risk counties had expanded to 82, with no high-risk and very-high-risk counties. The epidemic situation in Zhejiang province has been effectively controlled. The experience of epidemic prevention and control in Zhejiang is worthy to be emulated and learned by other countries and regions.

Graphene oxide (GO) is widely used to improve the pore structure, dispersion capacity, adsorption selectivity, resistance to acids and bases, and thermal stability of metal-organic frameworks (MOFs). However, it remains a daunting challenge to enhance selectivity simply by modifying the pore surface polarity and producing a suitable pore structure for CO2 molecules through a combination of GO with MOFs. Herein, we demonstrate a novel porous hyper-cross-linked polyimide-UiO-graphene composite adsorbent for CO2 capture via in situ chemical knitting and condensation reactions. Specifically, a network of polyimides rich in carbonyl and nitrogen atoms with amino terminations was synthesized via the reaction of 4,4'-oxydiphthalic anhydride (ODPA) and 2,4,6-trimethyl-1,3-phenylenediamine (DAM). The product plays a crucial role in the separation of CO2 from N2. As expected, the resulting composite (PI-UiO/GO-1) exhibited a 3-fold higher CO2 capacity (8.24 vs 2.8 mmol·g-1 at 298 K and 30 bar), 4.2 times higher CO2/N2 selectivity (64.71 vs 15.43), and significantly improved acid-base resistance stability compared with those values of pristine UiO-66-NH2. Furthermore, breakthrough experiments verified that the porous composites can effectively separate CO2 from simulated fuel gas (CO2/N2 = 15/85 vol %) with great potential in industrial applications. More importantly, this strategy can be extended to prepare other MOF-based composites. This clearly advances the development of MOF-polymer materials for gas capture.

Binder jet 3D printing (BJ3DP) is one of the most promising 3D printing technologies, due to its ability of printing large-scale complex parts with high efficiency and low cost. The powder particle size is crucial for the sintering quality of BJ3DP. In this work, on the basis of the constitutive model of viscoplastic theory, the shape evolution (shrinkage and relative density) of cubes produced by BJ3DP using 316L stainless steel powders (normal distribution of powder sizes) with different mean particle sizes (i.e., 20, 30, 40, 50, 60, and 70 μm) was studied via finite element numerical simulation during sintering. It revealed that the volumetric shrinkage, relative density, and maximum sintering stress decreased with increasing the mean particle size. The maximum sintering stress of the sample with mean particle size of 70 μm was 0.0492 MPa, with the volumetric shrinkage of ~40% and the relative density of ~89%. In the meantime, the maximum sintering stress of the sample with mean particle size of 20 μm was 0.1789 MPa, with the volumetric shrinkage of ~48% and the relative density of ~97%. In addition, the simulated results of the relative density of assumed samples agreed well with the experimental results from the literature.

Damage mode identification and premature failure prevention for composite structures by acoustic emission have drawn a great deal of attention. Feature evaluation on streaming acoustic emission data is one of the significant issues in research of acoustic emission signal processing. This work conducts dynamic feature evaluation on 15 conventional acoustic emission features so as to seek a deeper insight into different features with damage accumulation. First, the procedure of dynamic feature evaluation is presented based on three basic algorithms. Second, the streaming acoustic emission data are collected from the adhesively bonded composite single-lap joint subjected to quasi-static tensile loads. Third, further efforts are made so as to explore the information contained as well as to interpret the effect of damage accumulation. It is found that different conventional acoustic emission features show distinctive functions, including damage mode identification, damage process indication, and both of them. Informative features for damage pattern recognition are independent on damage accumulation. Useful features for damage process description show sensitive dynamic characteristics with damage accumulation, especially before the complete failure of the specimen. Furthermore, dynamic feature evaluation can be used to detect singular signals.

BACKGROUND Abnormal microangiogenesis and microenvironmental disturbances within the Nasopharyngeal carcinoma (NPC) can exacerbate tumor hypoxia, which may increase radiotherapy resistance and thus lead to poor prognosis in NPC patients. A non-invasive imaging technique, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which can reflect the tumor blood perfusion and angiogenesis status, was used to investigate the relationships of DCE-MRI parameters with hypoxia-inducible factor 1 alpha (HIF-1α) expression and tumor grades in NPC patients. METHODS 42 treatment-naive patients with pathologically confirmed NPC were enrolled in this analysis. Plain magnetic resonance scans and DCE-MRI scans were performed before treatment, and post-processing was performed to calculate the relative enhancement (RE), maximum relative enhancement (MRE), maximum enhancement (ME), wash-in rate (WIR), wash-out rate (WOR), time to peak (TTP), and area under the curve (AUC). Immunohistochemistry was used to detect HIF-1α expression in electronasopharyngeal fiberoscopic specimens. The clinical grade/stage of NPC was jointly assessed by an experienced radiologist and a radiotherapist. The potential correlations of the DCE-MRI parameters with HIF-1α expression and clinical grades were analyzed. The statistical analysis was performed using SPSS 17.0 software package. RESULTS Among DCE-MRI parameters, RE, ME, and MRE were associated with the positive expression of HIF-lα in NPC and could reflect the hypoxic status in the local microenvironment of the cancer foci in vivo. RE, ME, and MRE were significantly higher in the positive HIF-1α expression group than in the negative HIF-1α expression group (F=5.281, P=0.027; F=11.923, P=0.001; F=6.228, P=0.017). RE, ME, and MRE were significantly correlated with clinical grade (F=3.646, P=0.021; F=3.204, P=0.034, F=3.050, P=0.040) and T stage (F=6.578, P=0.001; F=3.540, P=0.023; F=4.384, P=0.010). The values of RE, MRE, and ME gradually increased as the clinical grade and T stage increased. CONCLUSIONS DCE-MRI is a valuable imaging technique for the noninvasive evaluation of hypoxia in NPC, the development of individualized treatment protocols, and the prediction of efficacy.

Background: We aimed to evaluate the therapeutic effect of additional ursodeoxycholic acid (UDCA) with mesalazine, compared to mesalazine alone in patients with ulcerative colitis (UC). The mechanism was evaluated by monitoring the changes of IL-23-IL-17 axis and the intestinal microflora. Methods: In this prospective, single center study, patients with UC were randomly assigned to the Mesalazine group (n=20) or the UDCA + Mesalazine group (n=20). Mayo score and Inflammatory Bowel Disease Questionnaire (IBDQ), and fecal samples for 16S rRNA sequencing and blood samples for IL-23 and IL-17 ELISA were collected for analysis. Results: Mayo scores and IBDQ score of the UDCA + Mesalazine group were significantly better than those of the Mesalazine group (P = 0.015 and P < 0.001, respectively). At post-treatment week 4, IL-23 and IL-17 levels were significantly lower in the UDCA + Mesalazine group compared to those in the Mesalazine group (both P < 0.038). In patients with UC after treatment, Firmicutes in the UDCA + Mesalazine group was higher than those in the Mesalazine group (P < 0.001). The UDCA + Mesalazine group showed lower percentage of Proteobacteria compared to those in the Mesalazine group (P < 0.001). Conclusion: Additional UDCA could provide better therapeutic effects than mesalazine alone, possibly due to the change of IL-23 and IL-17 and the proportional distribution of intestinal microflora.

Highly efficient bifunctional electrocatalysts towards sluggish oxygen reduction and evolution reactions (ORR and OER) are of great significance for cathode catalysis of rechargeable metal–air batteries. Herein, we report a one-pot pyrolysis strategy to construct binary transition metal oxide (TMO) interfaces on a nitrogen doped porous carbon framework (CN) for bifunctional oxygen reaction catalysis. The constructed Fe3O4/Co3O4 interfaces not only help promote the stabilization of Fe2+ ions, but also generate abundant oxygen vacancies on the surface of composite catalysts (Fe3O4/Co3O4-CN), which boost the intrinsic oxygen reaction activity. The Fe3O4/Co3O4-CN catalyst exhibits a bifunctional electrocatalytic performance with a significantly lowered potential difference (ΔE) of 0.68 V between the half-wave potential of the ORR (E1/2) and the potential of the OER at a current density of 10 mA cm−2 (Ej=10), rivaling the best performance of previously reported bifunctional TMO catalysts to the best of our knowledge. The rechargeable Zn–air battery with Fe3O4/Co3O4-CN as the cathode catalyst exhibits superior performance with an energy density of 1045.82 W h kgZn−1 and a peak power density of 105.7 mW cm−2, as well as excellent cycling stability (over 80 h at a current density of 10 mA cm−2), demonstrating our new bifunctional oxygen electrocatalyst as a promising candidate for practical energy storage applications.

In reality, when facing a defined contribution (DC) pension fund investment problem, the fund manager may not have sufficient confidence in the reference model and rather considers some similar alternative models. In this paper, we investigate the robust equilibrium control-measure policy for an ambiguity-averse and risk-averse fund manger under the mean-variance (MV) criterion. The ambiguity aversion is introduced by adopting the model uncertainty robustness framework developed by Anderson. The risk aversion model is state-dependent, and takes a linear form of the current wealth level after contribution. Moreover, the fund manager faces stochastic labor income risk and allocates his wealth among a risk-free asset and a risky asset. We also propose two complicated ambiguity preference functions which are economically meaningful and facilitate analytical tractability. Due to the time-inconsistency of the resulting stochastic control problem, we attack it by using the game theoretical framework and the concept of subgame perfect Nash equilibrium. The extended Hamilton-Jacobi-Bellman-Isaacs (HJBI) equations and the verification theorem for our problem are established. The explicit expressions for the robust equilibrium policy and the corresponding robust equilibrium value function are derived by stochastic control technique. In addition, we discuss two special cases of our model, which shows that our results extend some existing works in the literature. Finally, some numerical experiments are conducted to demonstrate the effects of model parameters on our robust equilibrium policy.

Type 2 diabetes is one of the most common chronic diseases in modern society. However, there is still insufficient research on the pathogenesis, diagnosis and treatment of type 2 diabetes and its complications. Extracellular vesicles are small bilayer vesicles secreted by cells. In recent years, the effect of extracellular vesicles in type 2 diabetes and its complications has aroused extensive attention. The research on the influence of protein and nucleic acids carried by extracellular vesicles secreted by stem cells and inflammatory cells on the pathogenesis of type 2 diabetes and its complications provides new ideas for its diagnosis and treatment. This review focuses on the influence of extracellular vesicles on insulin resistance by regulating inflammation and glucose transporter 4 expression. The second part mainly discusses the research progress and limitations of extracellular vesicles use in treating and diagnosing type 2 diabetes and its complications. This review introduces the current research status of type 2 diabetes and its complications, illustrates the biogenesis of extracellular vesicles, their effect on type 2 diabetes pathogenesis and its complications and their potential as therapeutic tools and diagnostic markers in type 2 diabetes and its complications.

Globally, kidney disease has become a serious health challenge, with approximately 10% of adults suffering with the disease, and increasing incidence and mortality rates every year. Small extracellular vesicles (sEVs) are 30 nm-100 nm sized nanovesicles released by cells into the extracellular matrix (ECM), which serve as mediators of intercellular communication. Depending on the cell origin, sEVs have different roles which depend on internal cargoes including, nucleic acids, proteins, and lipids. Mesenchymal stem cell (MSCs) exert anti-inflammatory, anti-aging, and wound healing functions mainly via sEVs in a stable and safe manner. MSC-derived sEVs (MSC-sEVs) exert roles in several kidney diseases by transporting renoprotective cargoes to reduce oxidative stress, inhibit renal cell apoptosis, suppress inflammation, and mediate anti-fibrosis mechanisms. Additionally, because MSC-sEVs efficiently target damaged kidneys, they have the potential to become the next generation cell-free therapies for kidney disease. Herein, we review recent research data on how MSC-sEVs could be used to treat kidney disease.

Fortet-Mourier (FM) probability metrics are important probability metrics, which have been widely adopted in the quantitative stability analysis of stochastic programming problems. In this study, we contribute to different types of convergence assertions between a probability distribution and its empirical distribution when the deviation is measured by FM metrics and consider their applications in stochastic optimization. We first establish the quantitative relation between FM metrics and Wasserstein metrics. After that, we derive the non-asymptotic moment estimate, asymptotic convergence, and non-asymptotic concentration estimate for FM metrics, which supplement the existing results. Finally, we apply the derived results to four kinds of stochastic optimization problems, which either extend the present results to more general cases or provide alternative avenues. All these discussions demonstrate the motivation as well as the significance of our study.

We investigate the reinsurance contract and investment strategy problem between an insurer and a reinsurer under the continuous-time framework. For the reinsurance contract design, the joint interests of the insurer and the reinsurer are considered. That is, the insurer determines the claim risk sharing strategy, and the reinsurer determines the reinsurance price. The insurer and the reinsurer can invest in the common risk-free asset and different risky assets to increase their respective wealths. The competition between the insurer and the reinsurer is quantified through the relative performance. Both the insurer and the reinsurer aim at maximizing the expected value of the terminal pay-off while minimizing its variance. By using the stochastic optimal control technique, we derive analytically the optimal time-consistent investment strategy and obtain the optimal reinsurance contract. Finally, the influences of model parameters on the optimal reinsurance contract and time-consistent investment strategy are examined through numerical experiments.

IntroductionPertussis is one of the top 10 diseases of children under 10 years of age, and the few vaccine-preventable diseases who is on a rise in China in recent years; however, the true burden of pertussis, including age-stratified incidence and risk factors of severe sequelae, are under-recognised. We aim to estimate the health burden of laboratory-confirmed pertussis by age groups, considering the setting of illness onset (ie, in community, outpatient and inpatient), in a Chinese population (~2.23 million in total) at two sites.Methods and analysisThis paper describes the study design of a 1-year, prospective, age-stratified and population-based case–control study, including site selection, study population, case registry, ascertainment and enrolment, control recruitment, follow-up of case, microbiological methods, data collection, quality control activities and statistical methods used to generate incidence estimates. During June 2021 through May 2022, registry of suspected pertussis cases (namely chronic/persistent cough) will be conducted in several participating hospitals (SHs) at the two sites, which are selected based on Healthcare Utilisation and Attitudes Surveys (HUAS) carried out before study initiation. A case–control study will be conducted in the SHs and we aim to enrol a total of 1000 suspected pertussis cases (ie, all hospital admissions and the first 1–3 outpatient visits each week each hospital) and 2000 frequency matched healthy controls in community. Our primary study outcome, the laboratory-confirmed Bordetella pertussis infection, will be determined by a comprehensive laboratory methods and procedures (ie, culture, PCR and serological tests) in both cases and controls at enrolment and during 60-day’s follow-up visits. Finally, data from HUAS (ie, population size), case registry (ie, the total number of suspected pertussis cases) and case–control study (ie, the prevalence or population attributable fraction of Bordetella pertussis) will be combined to calculate incidence and its 95% CI through bootstrap method. Epidemiological analyses will be conducted to determine the risk factors associated with severe sequelae of pertussis.Ethics and disseminationThis study has been approved by Chinese Centre for Disease Control and Prevention’s Institutional Review Board (no. ICDC-202110). Results will be disseminated via academic presentations and publication in peer-reviewed journals, and will provide valuable scientific data and some new insights into the incidence, aetiology and risk factors for severe sequelae of pertussis to academic societies and the public health authorities who is currently struggling and fighting against this burdensome disease worldwide.

Functionalized graphene oxide (GO)/epoxy resin (EP) composite coating has attracted attention due to its advantages of epoxy resin in acid resistance, anticorrosion and having the characteristics of GO such as good chemical stability and strong electrolyte barrier properties. In this study, epoxypropyl functionalized graphene oxide (EFGO) was synthesized with a new strategy by grafting epichlorohydrin (ECH) onto the surface of GO. EFGO was then cross-linked with EP by diethylenetriamine (DETA) to fabricate EFGO/EP anticorrosive coating. The structure and property of EFGO and EFGO/EP were characterized and evaluated by various methods such as FTIR, Raman, XPS, SEM, and EIS. The results showed that the graft amount of epoxypropyl on GO surface could be effectively increased by using KI-KF catalysis system. The increase of the graft amount further improved the compatibility between EFGO and EP. EFGO/EP had a network structure with EFGO as the “central node”. The “central node” locked the movement of EP chain segment, as improving the thermal stability of EFGO/EP. The EFGO/EP coating fabricated by the EFGO, which grafted larger epoxypropyl, had good anticorrosion performance and adhesion with steel plates, showing a good barrier effect on electrolyte migration. The coating resistance reached up 4.88×108 Ω cm2.

View variation is one of the greatest challenges in the field of gait recognition. Subspace learning approaches are designed to solve this issue by projecting cross-view features into a common subspace before recognition. However, similarity measures are data-dependent, which results in low accuracy when cross-view gait samples are randomly arranged. Inspired by the recent developments of data-driven similarity learning and multi-nonlinear projection, we propose a new unsupervised projection approach, called multi-nonlinear multi-view locality-preserving projections with similarity learning (M2LPP-SL). The similarity information among cross-view samples can be learned adaptively in our M2LPP-SL. Besides, the complex nonlinear structure of original data can be well preserved through multiple explicit nonlinear projection functions. Nevertheless, its performance is largely affected by the choice of nonlinear projection functions. Considering the excellent ability of kernel trick for capturing nonlinear structure information, we further extend M2LPP-SL into kernel space, and propose its multiple kernel version MKMLPP-SL. As a result, our approaches can capture linear and nonlinear structure more precisely, and also learn similarity information hidden in the multi-view gait dataset. The proposed models can be solved efficiently by alternating direction optimization method. Extensive experimental results over various view combinations on the multi-view gait database CASIA-B have demonstrated the superiority of the proposed algorithms.

Semi-coke-based activated carbons (SACs) were prepared using semi-coke powders as raw materials. They were modified by organic reagents (benzene, methyl benzoate, and ethyl acetate), low-temperature plasma (CH4 and N2 atmosphere), and organic reagent-low temperature plasma synergistic methods. FT-IR analysis showed that the corresponding functional groups were introduced to the surface of the SACs and the absorption peak intensities of the corresponding functional groups were enhanced via low-temperature plasma treatment. Low-temperature N2 adsorption tests showed that the organic reagent played an important role for regulated mesopores of the SACs. The adsorption capacities of the SACs for CH4 and N2 were measured via static volumetric method, and their separation factors of the CH4/N2 were calculated, in which the biggest separation factor (5.08) of CH4/N2 was obtained from the SAC-ben-P-N2, which was synergistic modified by benzene and low-temperature plasma (N2 atmosphere) and its breakthrough time of methane was 93 s. The biggest breakthrough time of methane (112 s) was acquired from the SAC-ben, which was modified by benzene and its separation factor of CH4/N2 was 4.87.

Distributionally robust optimization is a dominant paradigm for decision-making problems where the distribution of random variables is unknown. We investigate a distributionally robust optimization problem with ambiguities in the objective function and countably infinite constraints. The ambiguity set is defined as a Wasserstein ball centered at the empirical distribution. Based on the concentration inequality of Wasserstein distance, we establish the asymptotic convergence property of the data-driven distributionally robust optimization problem when the sample size goes to infinity. We show that with probability 1, the optimal value and the optimal solution set of the data-driven distributionally robust problem converge to those of the stochastic optimization problem with true distribution. Finally, we provide numerical evidences for the established theoretical results.

Thick plate bending process (warm bending and tempering) has a profound impact on the material strength distribution (MSD) in hydrogenation reactor shells. To date, few studies have studied the thick plate bending process. In this work, an artificial neural network (ANN) combined with finite element analysis (FEA) was utilized to investigate the impact of thick plate bending on the MSD of reactor shells. First, tensile tests of 0-10% pre-strained 2.25Cr-1Mo-0.25 V specimens were subjected to 390 to 510 °C. The results obtained from this experiment were used to develop ANN with two inputs (temperature and plastic strain) to predict the strength of pre-deformed steel. Subsequently, the plastic strain distribution of reactor shells after warm bending was obtained via FEA. We then inputted the FEA results into well-established ANN to predict the MSD of un-tempered reactor shells. The MSD of an actual tempered reactor shell was measured to study the synergic effect of warm bending and tempering on MSD variation. Results showed that the average absolute relative errors between the proposed ANN and tensile test results were below 4%. The absolute relative errors of the proposed prediction method varied from 0.24 to 7.88%. The proposed method is therefore reliable in the lightweight design of the hydrogenation reactor.