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In recent years, the issue of PM2.5-O3 compound pollution has become a significant global environmental concern. This study examines the spatial and temporal patterns of global PM2.5-O3 compound pollution and exposure risks, firstly at the global and urban scale, using spatial statistical regression, exposure risk assessment, and trend analyses based on the datasets of daily PM2.5 and surface O3 concentrations monitored in 120 cities around the world from 2019 to 2022. Additionally, on the basis of the common emission sources, spatial heterogeneity, interacting chemical mechanisms, and synergistic exposure risk levels between PM2.5 and O3 pollution, we proposed a synergistic PM2.5-O3 control framework for the joint control of PM2.5 and O3. The results indicated that: (1) Nearly 50% of cities worldwide were affected by PM2.5-O3 compound pollution, with China, South Korea, Japan, and India being the global hotspots for PM2.5-O3 compound pollution; (2) Cities with PM2.5-O3 compound pollution have exposure risk levels dominated by ST + ST (Stabilization) and ST + HR (High Risk). Exposure risk levels of compound pollution in developing countries are significantly higher than those in developed countries, with unequal exposure characteristics; (3) The selected cities showed significant positive spatial correlations between PM2.5 and O3 concentrations, which were consistent with the spatial distribution of the precursors NOx and VOCs; (4) During the study period, 52.5% of cities worldwide achieved synergistic reductions in annual average PM2.5 and O3 concentrations. The average PM2.5 concentration in these cities decreased by 13.97%, while the average O3 concentration decreased by 19.18%. This new solution offers the opportunity to construct intelligent and healthy cities in the upcoming low–carbon transition.

Abstract Chitinase-3-like protein 1 (CHI3L1) is a secreted glycoprotein that is induced and regulated by multiple factors during inflammation in enteritis, pneumonia, asthma, arthritis, and other diseases. It is associated with the deterioration of the inflammatory environment in tissues with chronic inflammation caused by microbial infection or autoimmune diseases. The expression of CHI3L1 expression is upregulated in several malignant tumors, underscoring the crucial role of chronic inflammation in the initiation and progression of cancer. While the precise mechanism connecting inflammation and cancer is unclear, the involvement of CHI3L1 is involved in chronic inflammation, suggesting its role as a contributing factor to in the link between inflammation and cancer. CHI3L1 can aggravate DNA oxidative damage, induce the cancerous phenotype, promote the development of a tumor inflammatory environment and angiogenesis, inhibit immune cells, and promote cancer cell growth, invasion, and migration. Furthermore, it participates in the initiation of cancer progression and metastasis by binding with transmembrane receptors to mediate intracellular signal transduction. Based on the current research on CHI3L1, we explore introduce the receptors that interact with CHI3L1 along with the signaling pathways that may be triggered during chronic inflammation to enhance tumorigenesis and progression. In the last section of the article, we provide a brief overview of anti-inflammatory therapies that target CHI3L1.

Abstract This study presented a comprehensive computational fluid dynamics-based model for fused filament fabrication (FFF) three-dimensional (3D) printing multiphase and multiphysics coupling. A model based on the framework of computational fluid dynamics was built, utilizing the front-tracking method for high precision of multiphase material interfaces, a fully resolved simulation at the mesoscale explores the underlying physical mechanism of the self-supported horizontal printing. The study investigated the influence of printing temperature and velocity on the FFF process, exhibiting a certain self-supporting forming ability over a specific range. The results indicated that during the printing of large-span horizontal extension structures, the bridge deck material transitions from initial straight extension to sagging deformation, ultimately adopting a curved shape. The straight extension distance is inversely proportional to the depth of the sagging deformation. Additionally, the study revealed that printing temperature primarily affected the curing time of the molten material, while printing velocity fundamentally affected the relaxation time of both thermal and dynamic characteristics of the material.

Abstract. Background:. This systematic review aimed to examine whether dual-task (DT) training was superior to single-task (ST) training in improving DT walking, balance and cognitive functions for individuals with Parkinson’s disease (PD). Methods:. Literature search was performed in the following electronic databases: PubMed, the Cochrane Library, Web of Science, and Metstr covering inception to May 10, 2023. And in order to facilitate comparison across trials, we calculated the effect size (Hedges’ g) of gait, balance, cognitive, and other parameters under both ST and DT conditions, using the mean change score and standard deviation (SD) of change score of the experimental and control groups. Randomized controlled trials that examined the effects of DT motor and cognitive training in individuals with Parkinson’s disease were included for this systematic review. Results:. A total of 214 participants recruited from six articles (actually five trials) were involved in this review. In terms of walking ability, only double support time and stride time variability showed significant between-group difference (Hedges’ g = 0.34, 0.18, respectively). Compared to ST training group, DT training group had a more improvement effect in laboratory balance measurement (Hedges’ g = 0.18, 1.25), but no significant improvement in clinical balance measurement. No significant between-group differences were observed, thus its training effect on cognitive function was inconclusive. Conclusions:. The DT training failed to achieve promising results better than ST training in improving DT walking and balance functions for individuals with PD. Any firm conclusion cannot be drawn at present, due to the limited number of eligible publications. Larger sample size and high-quality studies are needed to investigate the effectiveness of DT training in individuals with PD.

Background: Epidemiological reports indicate a potential association between androgenic alopecia (AGA) and increased prostate cancer (PC) prevalence, but conflicting reports also exist. This study aims to elucidate the causality of AGA on PC risk using Mendelian randomization (MR) analysis. Materials and methods: Two-sample MR analyses utilized public genome-wide association studies summary data for single-nucleotide polymorphisms associated with AGA. Four statistical methods were used: inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode, with IVW as the preliminary estimation method. Additionally, sensitivity analyses were conducted to address pleiotropic bias. Results: Genetically proxied AGA did not demonstrate a causal effect on PC risk (IVW P > 0.05). Consistently, complementary methods yielded results aligned with IVW. Conclusions: Our MR analysis indicates no causal relationship between genetically predicted AGA and PC risk, suggesting that observed associations in epidemiological studies may not be causal.

In order to study the influence of air pressure and water pressure on the particle size parameters of ultrasonic atomization spray, an experimental platform was designed in this paper. Anionic surfactant rapid infiltration T was selected to configure a solution with a concentration of 0.07 % for experiment. The changes of particle size parameters of ultrasonic atomization spray under different combinations of air pressure and water pressure were analyzed. The experimental results show that the particle size parameters D10, D50, D90, VAD, SMD and NAD decrease with the increase of air pressure, and the decrease is affected by water pressure. At the same time, the above particle size parameters also increase with the increase of water pressure, and the increase will also be affected by air pressure. The influence of air pressure on the change of droplet size is greater than that of water pressure. When the pressure changes, the change trend of particle size parameters D10 and NAD is highly consistent, and the increase of particle size of D50, VAD and SMD is highly consistent.

Abstract Machine tools, often referred to as the “mother machines” of the manufacturing industry, are crucial in developing smart manufacturing and are increasingly becoming more intelligent. Digital twin technology can promote machine tool intelligence and has attracted considerable research interest. However, there is a lack of clear and systematic analyses on how the digital twin technology enables machine tool intelligence. Herein, digital twin modeling was identified as an enabling technology for machine tool intelligence based on a comparative study of the characteristics of machine tool intelligence and digital twin. The review then delves into state-of-the-art digital twin modeling-enabled machine tool intelligence, examining it from the aspects of data-based modeling and mechanism-data dual-driven modeling. Additionally, it highlights three bottleneck issues facing the field. Considering these problems, the architecture of a digital twin machine tool (DTMT) is proposed, and three key technologies are expounded in detail: Data perception and fusion technology, mechanism-data-knowledge hybrid-driven digital twin modeling and virtual-real synchronization technology, and dynamic optimization and collaborative control technology for multilevel parameters. Finally, future research directions for the DTMT are discussed. This work can provide a foundation basis for the research and implementation of digital-twin modeling-enabled machine tool intelligence, making it significant for developing intelligent machine tools.

Abstract Marine resources are rich. In recent years, more and more people have paid attention to the development of blue food. Fish protein is one of the essential biomolecules in blue food. It is a natural emulsifier because of its natural, nontoxic, easily obtained, degradable, and good surface activity. The research and application of fish protein as an emulsifier were reviewed in this paper. The emulsifying mechanism of fish protein was discussed. The emulsifying property of fish protein was affected by natural factors (source and protein concentration) and processing environment (ion strength, temperature, and pH). The emulsifying property of fish protein was improved by ultrasound, high pressure, microgel, complexation, glycosylation, and enzyme cross‐linking. It was pointed out that future research of fish protein applications should focus on the problems of shortening the gap between laboratory and commercial; stable emulsion of fish protein is difficult to preserve and single loading. It provides a reference for the development of fish protein emulsifiers.

Abstract Objectives The increasing prevalence of severe Mycoplasma pneumoniae pneumonia (SMPP) poses a significant threat to the health of children. This study aimed to characterise and assess the outcomes in children with SMPP. Methods We retrospectively analysed children hospitalised for M. pneumoniae pneumonia (MPP) between January and December 2022. Retrospectively, demographic, clinical, underlying diseases, laboratory and radiological findings, and treatment outcomes were collected and analysed. Disease severity was defined as severe or general according to the Guideline for diagnosis and treatment of community-acquired pneumonia in children (2019 version). Results Over a 12-month observation period, 417 children with MPP were enrolled, 50.6% (211/417) of whom had SMPP, with the peak incidence observed in winter. Of the 211 children with SMPP, 210 were treated and discharged with improvement, while one child with congenital heart disease died of cardioembolic stroke. A significantly higher proportion of patients with SMPP had underlying diseases, extrapulmonary complications (myocardial and digestive system involvement), and bacterial co-infection. A total of 25 (12%) children with SMPP received mechanical ventilation. The median duration of mechanical ventilation was 3 days. All children were treated with macrolide antibiotic. A significantly higher proportion of patients with SMPP received antibiotic other than macrolides, methylprednisolone sodium succinate, intravenous immunoglobulin and anticoagulation, compared with patients with general MPP (GMPP). Children with SMPP had significantly higher levels of white blood cells, neutrophil percentage, C-reactive protein, procalcitonin, interferon-γ, interleukin (IL)-2, IL-5, IL-6, IL-8, IL-10 and significantly lower percentages of lymphocytes, monocytes, and natural killer cells, compared with GMPP group. Conclusion Our findings suggest that severely ill children have more pronounced inflammatory reaction and extrapulmonary complications. For effective management of children with SMPP, hormonal, prophylactic, anticoagulant therapy, as well as the use of antibiotics other than macrolides for bacterial co-infections, could be incorporated into treatment regimens.

With the great development of the construction industry, prefabricated building components have been greatly developed. To study the compressive performance of the new wallboard, the axial compression performance test of six full-scale new lattice wallboards was carried out in this paper. The failure mode, axial pressure-displacement relationship curve, axial compression bearing capacity, and axial pressure-strain relationship of the wallboard were obtained through the experiments. This reveals the influence of the thickness of the concrete surface and the number of ribs on the performance of the wallboard. The test results show that the ultimate bearing capacity of the specimen increases with the increase of the thickness of the concrete surface layer with the same number of ribs. Specimen DW -30 increased by 4% over DW -20 and DW -50 increased by 41.6% over DW -30. The ultimate bearing capacity of the three-ribbed specimens was higher than that of the two-ribbed specimens for the same concrete face thickness, about 1.11 times that of the two-ribbed specimens. The concrete facing thickness and the number of ribs have a restraining effect on the deformation of the wallboard. Additionally, the calculation formula of axial bearing capacity of type latticed wallboard considering the influence of eccentric compression was proposed, which can provide a reference for engineering calculation.

Abstracts: Objectives: To assess the dynamics of the anti-SARS-CoV-2 IgG antibody levels and their efficacy against COVID-19. Methods: We conducted a longitudinal serological analysis of 852 breakthrough COVID-19 infections among the community-based population in Yichang, China. Anti-SARS-CoV-2 IgG levels were measured by chemiluminescence at approximately 3, 4, and 9 months after infection. A linear mixed model predicted IgG antibody decline over 18 months. The effectiveness of antibodies in preventing symptomatic and severe infections was determined using an existing meta-regression model. Results: IgG antibodies slowly declined after breakthrough infections. Initially high at around 3 months (339.44 AU/mL, IQR: 262.78-382.95 AU/mL), levels remained significant at 9 months (297.74 AU/mL, IQR: 213.22-360.62 AU/mL). The elderly (≥60 years) had lower antibody levels compared to the young (

The tumor microenvironment is increasingly acknowledged as a critical contributor to cancer progression, mediating genetic and epigenetic alterations. Beyond diverse cellular interactions from the microenvironment, physicochemical factors such as tumor acidosis also significantly affect cancer dynamics. Recent research has highlighted that tumor acidosis facilitates invasion, immune escape, metastasis, and resistance to therapies. Thus, noninvasive measurement of tumor acidity and the development of targeted interventions represent promising strategies in oncology. Techniques like contrast-enhanced ultrasound (CEUS) can effectively assess blood perfusion, while ultrasound-stimulated microbubble cavitation (USMC) has proven to enhance tumor blood perfusion. We therefore aimed to determine whether CEUS assesses tumor acidity and whether USMC treatment can modulate tumor acidity. Firstly, we tracked CEUS perfusion parameters in MCF7 tumor models and compared them with in vivo tumor pH recorded by pH microsensors. We found that the peak intensity and area under curve of tumor contrast-enhanced ultrasound correlated well with tumor pH. We further conducted USMC treatment on MCF7 tumor-bearing mice, tracked changes of tumor blood perfusion and tumor pH in different perfusion regions before and after the USMC treatment to assess its impact on tumor acidity and optimize therapeutic ultrasound pressure. We discovered that USMC with 1.0 Mpa significantly improved tumor blood perfusion and tumor pH. Furthermore, tumor vascular pathology and PGI2 assays indicated that improved tumor perfusion was mainly due to vasodilation rather than angiogenesis. More importantly, analysis of glycolysis-related metabolites and enzymes demonstrated USMC treatment can reduce tumor acidity by reducing tumor glycolysis. These findings support that CEUS may serve as a potential biomarker to assess tumor acidity and USMC is a promising therapeutic modality for reducing tumor acidosis.

Equid alphaherpesvirus 1 (EqAHV1) is a viral pathogen known to cause respiratory disease, neurologic syndromes, and abortion storms in horses. Currently, there are no vaccines that provide complete protection against EqAHV1. Marker vaccines and the differentiation of infected and vaccinated animals (DIVA) strategy are effective for preventing and controlling outbreaks but have not been used for the prevention of EqAHV1 infection. Glycoprotein 2 (gp2), located on the envelope of viruses (EqAHV1), exhibits high antigenicity and functions as a molecular marker for DIVA. In this study, a series of EqAHV1 mutants with deletion of gp2 along with other virulence genes (TK, UL24/TK, gI/gE) were engineered. The mutant viruses were studied in vitro and then in an in vivo experiment using Golden Syrian hamsters to assess the extent of viral attenuation and the immune response elicited by the mutant viruses in comparison to the wild-type (WT) virus. Compared with the WT strain, the YM2019 Δgp2, ΔTK/gp2, and ΔUL24/TK/gp2 strains exhibited reduced growth in RK-13 cells, while the ΔgI/gE/gp2 strain exhibited significantly impaired proliferation. The YM2019 Δgp2 strain induced clinical signs and mortality in hamsters. In contrast, the YM2019 ΔTK/gp2 and ΔUL24/TK/gp2 variants displayed diminished pathogenicity, causing no observable clinical signs or fatalities. Immunization with nasal vaccines containing YM2019 ΔTK/gp2 and ΔUL24/TK/gp2 elicited a robust immune response in hamsters. In particular, compared with the vaccine containing the ΔTK/gp2 strain, the vaccine containing the ΔUL24/TK/gp2 strain demonstrated enhanced immune protection upon challenge with the WT virus. Furthermore, an ELISA for gp2 was established and refined to accurately differentiate between infected and vaccinated animals. These results confirm that the ΔUL24/TK/gp2 strain is a safe and effective live attenuated vaccine candidate for controlling EqAHV1 infection.

This study proposes a hybrid prediction model using sparrow search algorithm (SSA) to optimize the convolutional neural network (CNN) and support vector machine (SVM), in order to perform accurate prediction of secondary supply temperature (Ts2). The historical operation data of Weifang residential building thermal station was adopted and reasonable data preprocessing was performed to suppress the interference of abnormal data. The input variables of the prediction model were screened using the correlation analysis method, taking the influence of the hysteresis effect into consideration. The SSA–CNN–SVM model was then developed for prediction. The performance of the model was evaluated by the root mean square error, mean absolute error, mean absolute percentage error (MAPE), and absolute value of relative error of each time step. The results obtained demonstrated that the SSA–CNN–SVM model has high prediction accuracy. The MAPE values of the two heat exchange stations were between 2.28 % and 2.4 %. The indoor temperature significantly affected the prediction accuracy of Ts2. After the introduction of the indoor temperature, the MAPE of the predicted values of the hybrid model was reduced by 0.35 %. The maximum reduction in MAPE of the SSA–CNN–SVM model was 1.5 % compared with other prediction models.

A new type of Ni-free cryogenic steel has been developed by replacing the more expensive Ni with low-cost Mn， which has become a new hot spot in the current research of steel for liquefied natural gas （LNG） storage tanks. The concept and characteristics of cryogenic steel are introduced in the beginning and then the research of high manganese austenitic cryogenic steel at home and abroad are introduced in this paper. In addition， the requirements on composition and properties of high manganese austenitic cryogenic steel in national and group standards are listed in detail. By comprehensive analysing the effects of different elements on the mechanical properties of high manganese austenitic cryogenic steel， it is concluded that Fe-24Mn-0.45C-3Cr-0.5Cu series high manganese austenitic cryogenic steel has excellent comprehensive properties， and can be used as a reference for the optimization of composition of high manganese austenitic cryogenic steel design. For the welding process， heat treatment can effectively improve the low temperature toughness of high manganese steel. And the research shows that considering the low temperature toughness， shielded metal are welding has better effect than that of submerged arc welding， although there is no big difference between yield strength and tensile strength

Abstract Background Despite the existence of proposed prognostic features on computed tomography (CT) for patients with advanced‐stage non‐small cell lung cancer (NSCLC), including radiologists' handcrafted (RaH) features, radiomics features, and deep learning features, comprehensive studies that examine their reproducibility, stability, and biological interpretability remain limited. Methods The Image Biomarker Standardization Initiative‐reported tolerance, Kappa, interclass correlation coefficient, and coefficient of variance were employed to identify reproducible features among RaH, radiomics, and deep learning features derived from NSCLC phantoms. The reproducible features were then input into six artificial intelligence algorithms to develop prognostic models for targeted therapy and immunotherapy using real‐world patients with advanced‐stage NSCLC to assess their capability and stability. Pathway enrichment was also conducted to explore the underlying biological pathways associated with these reproducible features. Results Reproducible features in advanced NSCLC included RaH features (9/9, 100%), radiomics features (572/1835, 31.17%), and deep learning features (3442/4096, 84.03%). Among the six artificial intelligence‐based prognostic methods, the RaH features exhibited least variability. We also observed that the optimal CT‐based prognostic approach differed depending on treatment regimens for advanced NSCLC. In analysis using the Cancer Genome Atlas Program lung adenocarcinoma dataset, the identified reproducible prognostic features, specifically tumor size‐derived radiomics and RaH features, showed significant associations with five key signaling pathways involved in NSCLC survival outcomes (false‐discovery rate p

Abstract We examined the remains of an individual who was unearthed from the Tuchengzi site and was believed to be from the Warring States period in China. The remains exhibited segmental femoral fracture. We aimed to deduce the cause of fracture, medical interventions, healing process, and motion behavior after fracture healing using several techniques, including macroscopic observation, computed tomography (CT), and finite element analysis. Based on the morphology of the long bones, it appeared that the individual was male. The fractures resulted in an adduction angle of 5.47° and an anterior flexion angle of 21.34° in the proximal femur, while the femoral neck anteversion angle had been replaced by a retroversion angle of 10.74°. Additionally, the distal femur formed an abnormal anterior convex angle of 144.60°. CT revealed mature callus formation and visible trabecular bundles. The finite element analysis indicated that the maximum von Mises stress in the femur was 17.44 MPa during standing and 96.46 MPa during walking. We suggest that medical practitioners in the Warring States period possessed a good knowledge of thigh anatomy, enabling them to perform fracture reduction and fixation. Reasonable medical intervention facilitated fracture healing and load recovery. Satisfactory fracture healing ensured that the individual could engage in normal standing and walking activities after rehabilitation.

Abstract Background Breast cancer is the second leading cause of cancer-related death in women, and drug resistance during treatment is a major challenge. However, the mechanisms underlying drug resistance are not fully understood. Here we applied whole-exome sequencing (WES) to clarify resistant rules to Herceptin and tyrosine kinase inhibitors (TKIs). Methods There are 12 HER2+ breast cancer patients who were done WES. Samples from tumor and surrounding tissues underwent DNA sequencing and analysis. Various experimental and bioinformatics techniques were employed, including genomic capture, mutation analysis (Genome Analysis Toolkit (GATK), etc.), bioinformatics assessments, and drug-gene interaction investigations. Ultimately, the study explored the association of APOB gene expression with breast cancer recurrence rates, immune cell infiltration, and drug response. Results The C > T mutation frequency was highest in the Herceptin-insensitive (HI) and verification groups, codenamed YI, contrasting with the Herceptin-sensitive (HE) group. No microsatellite instability (MSI)-H patients were in the HE group, but both HI and YI groups had 1 each. Significant differences in transition-transversion (TiTv) were observed in the HI and YI groups rather than the HE group. In the TKI- insensitive (TI) group, C > T mutations were highest, differing from the TKI-sensitive (TE) group. TE group included 2 MSI-H patients. Significant differences in TiTv were found in the TI group rather than the TE group. Mutated APOB may resist Herceptin and TKI, increasing immune infiltration. We identified potential drugs targeting it. Conclusions Our study suggested that a higher percentage of C > T mutations, significant differences in TiTv, and MSI-H status may indicate Herceptin resistance, while a higher percentage of C > T mutations, significant differences in TiTv, and the absence of MSI-H may indicate TKI resistance in breast cancer patients. For patients resistant to both Herceptin and TKI, mutated APOB may play a crucial role in resistance.

Streptococcus pneumoniae is a common pathogen associated with community-acquired bacterial meningitis, characterized by high morbidity and mortality rates. While vaccination reduces the incidence of meningitis, many survivors experience severe brain damage and corresponding sequelae. The pathogenesis of pneumococcal meningitis has not been fully elucidated. Currently, meningitis requires bacterial disruption of the blood – brain barrier, a process that involves the interaction of bacterial surface components with host cells and various inflammatory responses. This review delineates the global prevalence, pathogenesis, and treatment strategies of pneumococcal meningitis. The objective is to enhance the thorough comprehension of the clinical manifestations and biological mechanisms of the disease, thereby enabling more efficient prevention, diagnosis, and therapeutic interventions.

Two different low molecular cryoprotectants were analyzed in silver carp surimi proteins during different frozen storage conditions (FTC), and a comparison was performed with a conventional cryoprotectant mixture of sucrose (4%) and sorbitol (4%) as positive control (PC). The results showed that a significant decline was noted in sulfhydryl contents (SH), an increase in carbonyl groups, and a surface hydrophobicity due to myosin and protein oxidation. Meanwhile, FTC also altered the stability of secondary and tertiary structures due to the denaturative changes in myofibrillar proteins (MP). Meanwhile, samples that incorporated KC (3%), KOG (3%), and PC showed significant stability in MP against FTC induced changes. This is due to their strong hydrophilic and hydrogen interactions. MP samples containing KOG (3%) demonstrated improved cryoprotective abilities against oxidative and structural changes. Thus, we can recommend KOG as a potential cryoprotectant for maintaining the shelf-life of fish and related products on an industrial scale.

While liver fibrosis remains a serious, progressive, chronic liver disease, and factors causing damage persist, liver fibrosis may develop into cirrhosis and liver cancer. However, short-term liver fibrosis is reversible. Therefore, an early diagnosis of liver fibrosis in the reversible transition phase is important for effective treatment of liver diseases. Chitinase-3-like protein 1 (CHI3L1), an inflammatory response factor that participates in various biological processes and is abundant in liver tissue, holds promise as a potential biomarker for liver diseases. Here, we aimed to review research developments regarding serum CHI3L1 in relation to the pathophysiology and diagnosis of liver fibrosis of various etiologies, providing a reference for the diagnosis, treatment, and prognosis of liver diseases.

IntroductionThe increasing incidence of Klebsiella pneumoniae and carbapenem-resistant Klebsiella pneumoniae (CRKP) has posed great challenges for the clinical anti-infective treatment. Here, we describe the molecular epidemiology and antimicrobial resistance profiles of K. pneumoniae and CRKP isolates from hospitalized patients in different regions of China.MethodsA total of 219 K. pneumoniae isolates from 26 hospitals in 19 provinces of China were collected during 2019–2020. Antimicrobial susceptibility tests, multilocus sequence typing were performed, antimicrobial resistance genes were detected by polymerase chain reaction (PCR). Antimicrobial resistance profiles were compared between different groups.ResultsThe resistance rates of K. pneumoniae isolates to imipenem, meropenem, and ertapenem were 20.1%, 20.1%, and 22.4%, respectively. A total of 45 CRKP isolates were identified. There was a significant difference in antimicrobial resistance between 45 CRKP and 174 carbapenem-sensitive Klebsiella pneumoniae (CSKP) strains, and the CRKP isolates were characterized by the multiple-drug resistance phenotype.There were regional differences among antimicrobial resistance rates of K. pneumoniae to cefazolin, chloramphenicol, and sulfamethoxazole,which were lower in the northwest than those in north and south of China.The mostcommon sequence type (ST) was ST11 (66.7% of the strains). In addition, we detected 13 other STs. There were differences between ST11 and non-ST11 isolates in the resistance rate to amikacin, gentamicin, latamoxef, ciprofloxacin, levofloxacin, aztreonam, nitrofurantoin, fosfomycin, and ceftazidime/avibactam. In terms of molecular resistance mechanisms, the majority of the CRKP strains (71.1%, 32/45) harbored blaKPC-2, followed by blaNDM (22.2%, 10/45). Strains harboring blaKPC or blaNDM genes showed different sensitivities to some antibiotics.ConclusionOur analysis emphasizes the importance of surveilling carbapenem-resistant determinants and analyzing their molecular characteristics for better management of antimicrobial agents in clinical use.

The emergence of carbapenem-resistant Klebsiella pneumoniae (CRKP) has significant challenges to human health and clinical treatment, with KPC-2-producing CRKP being the predominant epidemic strain. Therefore, there is an urgent need to identify new therapeutic targets and strategies. Non-coding small RNA (sRNA) is a post-transcriptional regulator of genes involved in important biological processes in bacteria and represents an emerging therapeutic strategy for antibiotic-resistant bacteria. In this study, we analyzed the transcription profile of KPC-2-producing CRKP using RNA-seq. Of the 4693 known genes detected, the expression of 307 genes was significantly different from that of carbapenem-sensitive Klebsiella pneumoniae (CSKP), including 133 up-regulated and 174 down-regulated genes. Both the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) analysis showed that these differentially expressed genes (DEGs) were mainly related to metabolism. In addition, we identified the sRNA expression profile of KPC-2-producing CRKP for the first time and detected 115 sRNAs, including 112 newly discovered sRNAs. Compared to CSKP, 43 sRNAs were differentially expressed in KPC-2-producing CRKP, including 39 up-regulated and 4 down-regulated sRNAs. We chose sRNA51, the most significantly differentially expressed sRNA in KPC-2-producing CRKP, as our research subject. By constructing sRNA51-overexpressing KPC-2-producing CRKP strains, we found that sRNA51 overexpression down-regulated the expression of acrA and alleviated resistance to meropenem and ertapenem in KPC-2-producing CRKP, while overexpression of acrA in sRNA51-overexpressing strains restored the reduction of resistance. Therefore, we speculated that sRNA51 could affect the resistance of KPC-2-producing CRKP by inhibiting acrA expression and affecting the formation of efflux pumps. This provides a new approach for developing antibiotic adjuvants to restore the sensitivity of CRKP.

Abstract To reduce the high burden of disease caused by air pollution, the World Health Organization (WHO) released new Air Quality Guidelines (AQG) on September 22, 2021. In this study, the daily fine particulate matter (PM2.5) and surface ozone (O3) data of 618 cities around the world is collected from 2019 to 2022. Based on the new AQG, the number of attainment days for daily average concentrations of PM2.5 (≤ 15 µg m−3) and O3 (≤ 100 µg m−3) is approximately 10% and 90%, respectively. China and India exhibit a decreasing trend in the number of highly polluted days (> 75 µg m−3) for PM. Every year over 68% and 27% of cities in the world are exposed to harmful PM2.5 (> 35 µg m−3) and O3 (> 100 µg m−3) pollution, respectively. Combined with the United Nations Sustainable Development Goals (SDGs), it is found that more than 35% of the world's cities face PM2.5‐O3 compound pollution. Furthermore, the exposure risks in these cities (China, India, etc.) are mainly categorized as “High Risk”, “Risk”, and “Stabilization”. In contrast, economically developed cities are mainly categorized as “High Safety”, “Safety”, and “Deep Stabilization.” These findings indicate that global implementation of the WHO's new AQG will minimize the inequitable exposure risk from air pollution.

Abstract Cesium lead triiodide (CsPbI3) perovskite receives tremendous attention for photovoltaic applications, owing to its remarkable thermal stability and optoelectronic properties. However, realizing the CsPbI3 perovskite with high black‐phase stability and optoelectronic properties remains a significant challenge, which largely affects the photovoltaic performance of perovskite solar cells (PSCs). Herein, aromatic ammonium agents are used to modulate the crystallization of the CsPbI3 perovskite to improve its black‐phase stability and optoelectronic properties for efficient PSCs. Systemically experimental studies and comprehensively theoretical calculations are performed, which reveal that histammonium dihydrochloride (HACl2) could strongly couple with the perovskite during its crystallization, leading to faster nucleation and slower perovskite growth, and thus modulating the crystallization dynamics of the perovskites. Moreover, the residual diammonium cations (HA2+) distributed at the grain boundaries and on the surface of the perovskites can effectively passivate defects through electrostatic interactions, substantially suppressing trap‐assisted nonradiative recombination, and prompting more matched perovskite surface energetics. Consequently, the photovoltaic performance of CsPbI3 PSCs is largely improved because of a combination of enhanced crystallinity and optoelectronic properties of the perovskites. This work offers a new avenue to prepare inorganic perovskites with high optoelectronic properties for photovoltaics.

The functions of tumour protein, translationally controlled 1 (TPT1), have been extensively researched in various cell types. Although TPT1 was reported to have accelerating effects on the lipid deposition of mouse hepatocytes, and the activation roles in phosphatidylinositol 3 kinase (PI3K/AKT) pathway, its role in the differentiation of ovine stromal vascular fractions (SVFs) and their underlying mechanisms have not been addressed. Therefore, the objective of this study was to explore whether TPT1 participates in the adipogenic differentiation regulation of ovine SVFs and the underlying mechanisms. The results from this study revealed that TPT1 was abundant in the tail fat of sheep and the protein was located in the nucleus of C3H10T1/2 cell line and ovine SVFs. Moreover, TPT1 expression was up-regulated during the adipogenic differentiation of SVFs. The overexpression of TPT1 dramatically accelerated the adipogenic differentiation of SVFs, accompanied by the up-regulation of adipogenic marker genes, while TPT1 inhibition had opposite effects. TPT1 also had a negative effect on forkhead box O1 (FOXO1). The PI3K/AKT pathway was involved in the promotion of adipogenesis induced by overexpressing TPT1. We concluded that TPT1 promotes the adipogenic differentiation of ovine SVFs through PI3K/AKT-dependent pathway and attenuates the expression of FOXO1 in ovine SVFs.

Abstract Background Acute respiratory infections (ARI) are a threat to human health and survival, resulting in many paediatric hospitalisations. However, the epidemiological and clinical severity characteristics of the human parainfluenza virus (PIV), one of the most prevalent respiratory viruses, are not well understood in children. Methods To identify the epidemiological features of PIV infection, in 2019, hospitalised children with ARI were screened using multiplex polymerase chain reaction (PCR) for PIV and 10 other common respiratory pathogens. Subtyping of randomly selected PIV-positive samples was performed using reverse transcription-PCR. Demographics, epidemiology, clinical manifestations, diagnosis, and outcomes were compared between PIV subtypes. Results The annual detection rate for PIV was 14.9%, with a peak from April to September. Children under one year of age had the highest rate of PIV infection (45.5%) compared to other age groups. Of the 121 sequenced samples, 58.7%, 36.4% and 4.9% were positive for PIV-3, PIV-1 and PIV-2, respectively, and no PIV-4 was detected. Severe infections were associated with pre-existing underlying diseases and co-infections, but not with PIV serotype. After excluding cases of co-infection, we found that PIV-2 infection was associated with upper respiratory tract infections, whereas PIV-1 and PIV-3 mainly caused lower respiratory tract infections. Apart from the proportion of patients with fever, there were no significant differences among the three subtypes in terms of clinical symptoms, severity, and outcome. Conclusion Here, PIV was the main pathogen causing ARI in hospitalised children. Appropriate attention should be paid to children with underlying diseases and co-infections to prevent the worsening of severe PIV infection.

旨在为炸制鱼饼中晚期糖基化终末产物（AGEs）含量的控制提供理论依据和参考，以冷冻鲢鱼糜为原料制作鱼饼，通过分析连续炸制过程中（每3 h炸制1次）鱼饼中AGEs的生成与其理化指标和油脂氧化程度之间的相关性，探讨炸制过程中油脂氧化对鱼饼中AGEs生成的影响。结果表明：鱼饼外层AGEs含量显著高于内层，炸制9~18 h，鱼饼AGEs含量显著高于其他阶段（p

Drought stress has serious effects on the growth and yield of wheat in both productivity and quality and is an abiotic factor. Traditional methods of crop drought stress monitoring have some deficits. This work has been conducted in order to enhance these conventional methods by proposing a new deep learning approach. This paper has presented a deep learning-based model customized for monitoring drought stress in winter wheat during the critical growth stages. Drought-afflicted winter wheat images were captured at three crucial phases: rising–jointing, heading–flowering, and flowering–maturity. These images are correlated against soil moisture data to construct a comprehensive dataset. DenseNet121 was chosen as the network model since it extracts features from images relating to phenotypes. Several factors, like training methods, learning rate adjustment, and addition of the attention mechanism, are optimized in eight sets of experiments. This provided the final DenseNet-121 model with an average recognition accuracy of 94.67% on the test set, which means that monitoring drought stress during wheat growth’s key periods is feasible and effective.

Graphene has been considered an ideal reinforcement in aluminum alloys with its high Young’s modulus and fracture strength, which greatly expands the application range of aluminum alloys. However, the dispersion of graphene and the interfacial reaction between graphene and the aluminum matrix limit its application due to elevated temperature. Friction stirring processing (FSP) is regarded as a promising technique to prepare metal matrix composites at lower temperatures. In this paper, FSP was used to prepare graphene-nanoplates-reinforced aluminum composites (GNPs/Al). The corresponding effects of the process parameters and graphene content on GNPs/Al were thoroughly studied. The results showed that plastic strain, heat input, and graphene content were the key influencing factors. Large degrees of plastic strain can enhance the dispersion of graphene by increasing the number of stirring passes and the ratio of stirring to welding velocity, thereby improving the strength of GNPs/Al. Low heat input restricts the plastic flow of graphene in the matrix, whereas excessive heat input can promote interfacial reactions and lead to the formation of a more brittle phase, Al4C3. This is primarily associated with the stirring velocity and welding velocity. High graphene content levels can improve the material strength by refining the grain size, improving the load transfer ability, and acting as a precipitate to prevent dislocation movement. These findings make a contribution to the development of advanced aluminum alloys with graphene reinforcement, offering broader application potential in industries.

Surfactants are amphiphilic molecules that are capable of mixing water and oil. Biosurfactants are eco-friendly, low-toxicity, and stable to a variety of environmental factors. Optimizing conditions for microorganisms to produce biosurfactants can lead to improved production suitable for scaling up. In this study, we compared heterologous expression levels of the luminescence system luxCDABE operon controlled by regulatable promoters araC-PBAD and its strong version araC-PBAD-SD in Escherichia coli K12, Pseudomonas aeruginosa PAO1, and P. putida KT2440. Real-time monitoring of luminescence levels in the three strains indicated that luxCDABE controlled by araC-PBAD-SD promoter with 0.2% arabinose supplementation in P. putida produced the highest level of luminescence. By using the araC-PBAD-SD promoter-controlled rhlAB expression in P. putida, we were able to produce mono-rhamnolipid at a level of 1.5 g L−1 when 0.02% arabinose was supplemented. With the same system to express olsB, lyso-ornithine lipid was produced at a level of 10 mg L−1 when 0.2% arabinose was supplemented. To our knowledge, this is the first report about optimizing conditions for lyso-ornithine lipid production at a level up to 10 mg L−1. Taken together, our results demonstrate that regulatable araC-PBAD-SD promoter in P. putida KT2440 is a useful system for heterologous production of biosurfactants.

This paper proposed a two-dimensional steady-state field prediction approach that combines B-spline functions and a fully connected neural network. In this approach, field data, which are determined by corresponding control vectors, are fitted by a selected B-spline function set, yielding the corresponding best-fitting weight vectors, and then a fully connected neural network is trained using those weight vectors and control vectors. The trained neural network first predicts a weight vector using a given control vector, and then the corresponding field can be restored via the selected B-spline set. This method was applied to learn and predict two-dimensional steady advection–diffusion physical fields with absorption and source terms, and its accuracy and performance were tested and verified by a series of numerical experiments with different B-spline sets, boundary conditions, field gradients, and field states. The proposed method was finally compared with a generative adversarial network (GAN) and a physics-informed neural network (PINN). The results indicated that the B-spline neural network could predict the tested physical fields well; the overall error can be reduced by expanding the selected B-spline set. Compared with GAN and PINN, the proposed method also presented the advantages of a high prediction accuracy, less demand for training data, and high training efficiency.

Accurate monitoring and estimation of heavy metal concentrations is an important process in the prevention and treatment of soil pollution. However, the weak correlation between spectra and heavy metals in soil makes it difficult to use spectroscopy in predicting areas with a risk of heavy metal pollution. In this paper, a method for detection of Ni in soil in eastern China using the fractional-order derivative (FOD) and spectral indices was proposed. The visible-near-infrared (Vis-NIR) spectra were preprocessed using the FOD (range: 0 to 2, interval: 0.1) to solve the problems of baseline drift and overlapping peaks in the original spectra. The product index (PI), ratio index (RI), sum index (SI), difference index (DI), normalized difference index (NDI), and brightness index (BI) were applied and compared. The results showed that the spectral detail increased as the FOD increased, and the interference of the baseline drift and overlapping peaks was eliminated as the spectral reflectance decreased. Furthermore, the FOD extracted the spectral sensitivity information more effectively and improved the correlation between the Vis-NIR spectra and the Ni concentration, and the NDI had a maximum correlation coefficient (r) of 0.803 for order 1.9. The estimation model based on the NDI dataset constructed after FOD processing had the best performance, with a validation accuracy [Formula: see text] of 0.735, RMSE of 3.848, and RPD of 2.423. In addition, this method is easy to carry out and suitable for estimating other heavy metal elements in soil.

The underwater laser polarization detection technology integrates the polarization characteristics of light into the detection and identification of underwater targets. Addressing the challenge of poor accuracy in identifying targets in strong underwater scattering environments, this article proposes an overall scheme for a laser polarization underwater detection device that suppresses scatter using polarized pulse signals. By overcoming key technological barriers in the design of polarization-preserving optical detection systems and utilizing the method of differential amplitude to measure polarization, a laser polarization underwater detection device was developed and underwater polarization detection experiments were conducted, achieving precise detection of underwater targets. The results indicate that the underwater detection device we designed has a root mean square error of less than 5.7% to detect the polarization of the target, demonstrating the accuracy and precision of the underwater detection device.

ObjectiveTo evaluate the clinical application of the CT-based radiomics prediction model for discriminating SCC and SCH.MethodsA total of 254 clinical samples were selected from 291 patients with larynx-occupying lesions who underwent primary surgery. All lesions were validated via histopathological examination at The Second Hospital of Jilin University between June 2004 and December 2019. All patients were randomly allocated to the training (n = 177) and validation (n = 77) cohorts. After the acquisition of CT images, manual 3D tumor segmentation was performed using the CT images of the arterial, venous, and non-contrast phases via ITK-SNAP software. Subsequently, radiomics features were extracted using A.K. software. Based on the above features, three different diagnostic models (CTN, CTA+CTV, and CTN+CTA+CTV) were constructed to classify squamous cell carcinoma (SCC) and squamous cell hyperplasia (SCH). Additionally, receiver operating characteristic (ROC) and decision curve analysis (DCA) curves were measured to evaluate the diagnostic characteristics and clinical safety of the proposed three prognostic models.ResultsIn the radiomic prediction Model 1 (CTN), the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the training cohorts in differentiating SCC and SCH were 0.883, 0.785, 0.645, 1.000, 1.000, and 0.648, while in the testing cohorts, these values were 0.852, 0.792, 0.66, 1.000, 1.000, and 0.652, respectively. In the radiomic prediction Model 2 (CTA+CTV), the AUC, accuracy, sensitivity, specificity, PPV, and NPV values of the training cohorts were 0.965, 0.91, 0.916, 0.9, 0.933, and 0.875, respectively, while in the testing cohorts, the corresponding values were 0.902, 0.805, 0.851, 0.733, 0.833, and 0.759, respectively. In the radiomic prediction Model 3(CTN+CTA+CTV), the AUC, accuracy, sensitivity, specificity, PPV, and NPV values of the training cohorts were 0.985, 0.944, 0.953, 0.929, 0.953, and 0.929, while in the testing cohorts, the corresponding values were 0.965, 0.857, 0.894, 0.8, 0.875, and 0.828, respectively.ConclusionThe radiomic prediction Model 3, based on the arterial-venous-plain combined scan phase of CT, achieved promising diagnostic performance, expected to be regarded as a preoperative imaging tool in classifying SCC and SCH to guide clinicians to develop individualized treatment programs.

Wheat is a major grain crop in China, accounting for one-fifth of the national grain production. Drought stress severely affects the normal growth and development of wheat, leading to total crop failure, reduced yields, and quality. To address the lag and limitations inherent in traditional drought monitoring methods, this paper proposes a multimodal deep learning-based drought stress monitoring S-DNet model for winter wheat during its critical growth periods. Drought stress images of winter wheat during the Rise-Jointing, Heading-Flowering and Flowering-Maturity stages were acquired to establish a dataset corresponding to soil moisture monitoring data. The DenseNet-121 model was selected as the base network to extract drought features. Combining the drought phenotypic characteristics of wheat in the field with meteorological factors and IoT technology, the study integrated the meteorological drought index SPEI, based on WSN sensors, and deep image learning data to build a multimodal deep learning-based S-DNet model for monitoring drought stress in winter wheat. The results show that, compared to the single-modal DenseNet-121 model, the multimodal S-DNet model has higher robustness and generalization capability, with an average drought recognition accuracy reaching 96.4%. This effectively achieves non-destructive, accurate, and rapid monitoring of drought stress in winter wheat.