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Objective·To develop a machine learning approach for early identification of metabolic syndromes associated with inflammatory metabolic state changes in breast cancer patients after neoadjuvant therapy, using common laboratory and transthoracic echocardiography indices.Methods·Female patients with primary invasive breast cancer diagnosed at the Department of Breast Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, between September 2020 and September 2022, were included. General patient information, laboratory test results, and transthoracic echocardiography data were collected. After feature extraction, five machine learning algorithms, including random forest (RF), gradient boosting (GB), support vector machine (SVM), K-nearest neighbor (KNN), and decision tree (DT), were applied to construct a prediction model for the changes of the patients′ metabolic state after neoadjuvant therapy, and the prediction performances of the five models were compared.Results·A total of 232 cases with valid clinical data were included, comprising 135 cases before neoadjuvant therapy and 97 cases after completing 4 cycles of neoadjuvant therapy. Feature extraction identified five key features: white blood cell count, hemoglobin, high-density lipoprotein (HDL), interleukin-2 receptor, and interleukin-8. In the multi-feature analysis, the area under the receiver operating characferistic curve (AUC) was higher in the combination of white blood cell count, hemoglobin and HDL compared to the combination of interleukin-2 receptor and interleukin-8 (RF: 0.928 vs 0.772, GB: 0.900 vs 0.792, SVM: 0.941 vs 0.764, KNN: 0.907 vs 0.762, DT: 0.799 vs 0.714). The RF, SVM, and GB models showed higher AUC (0.928, 0.941, 0.900) and accuracy (0.914, 0.897, 0.776). The SVM model exhibited superior accuracy in the training data compared to the RF and GB models (P=0.394, 0.122 and 0.097, respectively).Conclusion·The SVM model can be used to establish a prediction model for identifying breast cancer patients at high risk of developing inflammatory metabolic state-related metabolic syndrome after neoadjuvant therapy by incorporating five common clinical indicators, namely, white blood cell count, hemoglobin, high-density lipoprotein, interleukin-2 receptor, and interleukin-8. SVM modeling may be useful for clinicians to establish individualized screening protocols based on a patient′s inflammatory metabolic state.

Feline parvovirus (FPV) is highly infectious for cats and other Felidae and often causes severe damage to young kittens. In this study, we incorporated recombinase polymerase amplification (RPA) and Cas12a-mediated detection and developed an RPA-Cas12a-based real-time or end-point fluorescence detection method to identify the NS1 gene of FPV. The total time of RPA-Cas12a-based fluorescence assay is approximately 25 min. The assay presented a limit of detection (LOD) of 1 copies/μl (25 copies/per reaction), with no cross-reactivity with several feline pathogens. The clinical performance of the assay was examined using total genomic DNA purified from 60 clinical specimens and then compared to results obtained with qPCR detection of FPV with 93.3% positive predictive agreement and 100% negative predictive agreement. Together, the rapid reaction, cost-effectiveness, and high sensitivity make the RPA-Cas12a-based fluorescence assay a fascinating diagnostic tool that will help minimize infection spread through instant detection of FPV.

Objective·To analyze the differences and classify hypertrophic cardiomyopathy (HCM) patients and healthy controls (HC) using short-axis cine cardiac magnetic resonance (CMR) images-derived radiomics features.Methods·One hundred HCM subjects were included, and fifty HC were randomly selected at 2∶1 ratio during January 2018 to December 2021 in the Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine. The CMR examinations were performed by experienced radiologists on these subjects. CVI 42 post-processing software was used to obtain left ventricular morphology and function measurements, including left ventricular ejection fraction (LVEF), left ventricular end-diastolic volume (LVEDV) and left ventricular end-diastolic mass (LVEDM). The 3D radiomic features of the end-diastolic myocardial region were extracted from short-axis images CMR cine. The distribution of the radiomic features in the two groups was analysed and machine learning models were constructed to classify the two groups.Results·One hundred and seven 3D radiomic features were selected and extracted. After exclusion of highly correlated features, least absolute shrinkage and selection operator (LASSO) was used, and a 5-fold cross-validation was performed. There were still 11 characteristics with non-zero coefficients. The K-best method was used to decide the top 8 features for subsequent analysis. Among them, four features were significantly different between the two groups (all P

The unique experience of land reform in China holds significant implications for other nations in urgent need of liberating and developing their productivity, providing valuable insights and lessons. This study conducted a micro-level analysis of land reform in China, the United States, and India, focusing on the implications for other nations. Surveys were conducted on 459 households in 12 townships in Zhejiang and Sichuan provinces, China. A random sampling approach was employed, selecting 5 sample counties (cities, districts) across Jinhua, Shaoxing, and Chengdu. Within each county (city, district), 2–3 townships were randomly selected, and 2–3 villages were chosen from each township. Subsequently, 10–20 households were randomly surveyed in each village. Statistical analysis using descriptive statistics and the Logistic model revealed robust results with p values below 0.05 for key variables. China’s new urbanization strategy highlights the necessity of reforming the rural homestead system, particularly as higher urbanization rates prompt farmers to withdraw from and transfer their homesteads worldwide. Tailored homestead policies that consider regional disparities in urbanization levels are crucial. A micro-level survey underscores the impact of urbanization, household head identity, and age on farmers’ decisions regarding homestead exit and transfer. Addressing external pressures, efforts should prioritize the revitalization of rural areas and the promotion of sustainable development. This includes enhancing small and medium-sized cities, fostering on-site urbanization, and creating nearby employment opportunities for farmers. However, the effectiveness of these measures varies across regions and is influenced by local levels of marketization. Internally, there is a need to bolster skill training and vocational education for farmers. In summary, the policy recommendations stemming from the micro-level survey in this study offer valuable insights for land reform strategies and sustainable development initiatives, spanning from individual farmers to national policies. They also contribute to a deeper understanding for policymakers, providing a novel analytical perspective.

Objective·To assess the feasibility of using 3D imaging features extracted from cardiac magnetic resonance (CMR) short-axis cine images to predict left ventricular ejection fraction (LVEF).Methods·A total of 100 left ventricular hypertrophy (LVH) patients who visited the Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine from January 2018 to December 2021, as well as 100 healthy control (HC) subjects during the same period, were included. All subjects completed CMR examinations under the supervision of experienced cardiologists and radiologists. The endocardial and epicardial contours were then manually delineated by cardiologists. Measurements of cardiac function and morphology were completed and data was recorded, including LVEF, left ventricular end-diastolic volume (LVEDV), and left ventricular end-diastolic mass (LVEDM). Myocardial 3D radiomic features of CMR-cine sequences were extracted by the Pyradiomics package, and selected and sorted by using correlation coefficient and K-best method. The LVEF prediction was performed with linear regression (LR), random forest (RF) and gradient boost (GB) methods. Results were also compared with LVEF prediction based on clinical information and CMR parameters.Results·In terms of clinical indicators, there were significant differences between the LVH and HC groups, such as LVEDV and LVEDM (all P

Objective·To explore the association of somatizatic symptoms, anxiety and depression with clinical prognosis in the patients with chronic heart failure (CHF).Methods·The patients with CHF who visited the Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine from January 2018 to December 2021 were included. Demographic data and clinical features of the patients were collected. The Self-reported Somatic Symptom Scale of China (SSS-CN), the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7) were used to evaluate the patients′ conditions. Telephone follow-up was conducted at the 12th month after the first visit, and the specific information of the patients′ end-point events (including death, re-hospitalization, causes of death and re-hospitalization) was collected. Survival curve and Cox regression analysis were used to evaluate the clinical prognosis of the patients.Results·A total of 195 patients were included. The SSS-CN scores in CHF patients were different between the two genders, among the different heart rate groups and the different cardiac function grades of New York Heart Association (NYHA), also between the patients with anxiety/depression or not (all P

ObjectiveTo conduct the pathogenic bacteria detection， the carriage of virulence genes and the source tracing analysis in a foodborne disease outbreak event.MethodsThe samples collected from the event were rapid screened by FilmArray multiplex polymerase chain reacion（PCR） system， and were conducted to bacteria culture， isolation and identification simultaneously. Real-time PCR was performed for virulence genes of isolated strains. Homologous analysis of the strains was studied using 16S rRNA gene sequence analysis and pulsed field gel electrophoresis（PFGE） molecular genotyping.ResultsCampylobacter jejuni strains were detected from anal swabs of 2 patients and 4 canteen workers. All of the 6 Campylobacter jejuni strains carried flaA， cadF， imaA， cdtA， cdtB and cdtC virulence genes. All the strains were closely associated with Campylobacter jejuni via 16S rRNA gene sequence analysis， but the phylogenetic distance between one strain and the other 5 strains was slightly further. The results of PFGE showed that 6 strains of Campylobacter jejuni could be divided into 3 PFGE patterns， 3 strains and other 2 strains belonged to the same PFGE pattern respectively， with similarity of 52.2%. The rest belonged to a different PFGE pattern， with similarity of 26.7% compared to others.ConclusionLaboratory analysis indicated that different clones of Campylobacter jejuni infection was the cause of this foodborne disease outbreak.

With the acceleration of urbanization and the improvement of people’s pursuit of spiritual home construction, the standards required for the protection and renewal of historical and cultural sites are rising, and not only the tourist attractions and commercial blocks in ancient historical and cultural sites need to be protected, repaired and infused with the vitality and charm of the new era. The external natural landscape belt connecting the ancient city wall and supporting leisure facilities also need to complement the scenery in the city. The research background of this paper is Yantai City of Shandong Province tourist attractions as an example, the use of field research and literature research, to analyze the history of the city, using the method of local conditions to match planting, using the charm of ancient poetry to create scenery, to show the outside world the charm of Yantai, to show the world “ to show the world the ancient city called Suocheng, it covers half of the history of Yantai. Standing at the root of the ancient city wall to enjoy the scenery, as if to appreciate the charm of all kinds of beautiful historical city in the world” The charm of the historic old town.

Historical blocks play a very important role in the inheritance of a city’s context. The ancient city wall has always been a witness of the history and culture of various countries and nationalities, but it still stands despite the weather. For China, after the devastating destruction of the city demolition movement in the last century, there are not many relatively complete ancient city walls left. Ancient city walls played a military role in protecting towns in ancient times. In today’s world, ancient buildings bring people more spiritual culture and symbolic culture. It is more important to combine the development of historical blocks with modern cities. The significance of this combination to our contemporary social culture and social development is worth studying. Taking the design of “Suocheng” ancient town in Yantai City, Shandong Province as an example, this paper analyzes the existing situation, the structure of the ancient city wall and the surrounding environment of the ancient town by means of on-the-spot investigation and literature research. Without destroying its essential spirit, it gives the meaning of the new era, digs more possibilities and functions, forms a complete spatial combination with landscape design, makes full use of new materials, combines new forms with ancient building forms, and makes efforts to repair the old, protect and protect it.

Diabetic foot ulcers (DFU) are chronic, refractory wounds caused by diabetic neuropathy, vascular disease, and bacterial infection, and have become one of the most serious and persistent complications of diabetes mellitus because of their high incidence and difficulty in healing. Its malignancy results from a complex microenvironment that includes a series of unfriendly physiological states secondary to hyperglycemia, such as recurrent infections, excessive oxidative stress, persistent inflammation, and ischemia and hypoxia. However, current common clinical treatments, such as antibiotic therapy, insulin therapy, surgical debridement, and conventional wound dressings all have drawbacks, and suboptimal outcomes exacerbate the financial and physical burdens of diabetic patients. Therefore, development of new, effective and affordable treatments for DFU represents a top priority to improve the quality of life of diabetic patients. In recent years, nanozymes-based diabetic wound therapy systems have been attracting extensive interest by integrating the unique advantages of nanomaterials and natural enzymes. Compared with natural enzymes, nanozymes possess more stable catalytic activity, lower production cost and greater maneuverability. Remarkably, many nanozymes possess multienzyme activities that can cascade multiple enzyme-catalyzed reactions simultaneously throughout the recovery process of DFU. Additionally, their favorable photothermal-acoustic properties can be exploited for further enhancement of the therapeutic effects. In this review we first describe the characteristic pathological microenvironment of DFU, then discuss the therapeutic mechanisms and applications of nanozymes in DFU healing, and finally, highlight the challenges and perspectives of nanozyme development for DFU treatment.

Synergetic interactions between ruthenium and molybdenum oxide weaken H adsorption on ruthenium active sites and hence enhance the electrocatalytic activity towards hydrogen evolution reaction.

Urban runoff pollution has become one of the major sources of water pollution. Rapid urbanization process in China has led to a significant increase in the pollution loads, which has posed great threats on the regional water environmental safety. Thus, it is of great importance to systematically analyse the characteristics of runoff pollution in some typical highly urbanized regions. Taking the Dongguan City in South China as the study area, output and spatial characteristics of the pollution emissions were investigated through a GIS-based empirical model. The results showed that the annual pollution loads of chemical oxygen demand (COD), suspended solids (SS), total nitrogen (TN) and total phosphorus (TP) exported from the city were approximately 338489, 613175, 28292 and 2824 t/a, respectively. In particular, the Songshan Lake Area in the city had the largest pollution loads, while the Water Town New Area had the least. In terms of pollution export fluxes unit area, they were highest in the Central Downtown Area (i.e. 2124, 3450, 145 and 16 kg/hm2 a for COD, SS, TN and TP, respectively) and relatively lower in the Southeastern Bordering Shenzhen Area. Enhancing the environmental management and improving the public environmental protection awareness are necessary for mitigating runoff pollution.

Metal chalcogenide nanoparticles play a vital role in a wide range of applications and are typically stabilized by organic derivatives containing thiol, amine, or carboxyl moieties, where the nonconjugated particle-ligand interfaces limit the electronic interactions between the inorganic cores and organic ligands. Herein, a wet-chemistry method is developed for the facile preparation of stable platinum chalcogenide (S, Se) nanoparticles capped with acetylene derivatives (e.g., 4-ethylphenylacetylene, EPA). The formation of Pt-C≡ conjugated bonds at the nanoparticle interfaces, which is confirmed by optical and X-ray spectroscopic measurements, leads to markedly enhanced electronic interactions between the d electrons of the nanoparticle cores and π electrons of the acetylene moiety, in stark contrast to the mercapto-capped counterparts with only nonconjugated Pt-S- interfacial bonds, as manifested in spectroscopic measurements and density functional theory calculations. This study underscores the significance of conjugated anchoring linkages in the stabilization and functionalization of metal chalcogenides, a unique strategy for diverse applications.

Carbon-based functional nanocomposites have emerged as potent antimicrobial agents and can be exploited as a viable option to overcome antibiotic resistance of bacterial strains. In the present study, graphitic carbon nitride nanosheets are prepared by controlled calcination of urea. Spectroscopic measurements show that the nanosheets consist of abundant carbonyl groups and exhibit apparent photocatalytic activity under UV photoirradiation towards the selective production of singlet oxygen. Therefore, the nanosheets can effectively damage the bacterial cell membranes and inhibit the growth of bacterial cells, such as Gram-negative Escherichia coli, as confirmed in photodynamic, fluorescence microscopy, and scanning electron microscopy measurements. The results from this research highlight the unique potential of carbon nitride derivatives as potent antimicrobial agents.

Copper compounds have been extensively investigated for diverse applications. However, studies of cuprous hydroxide (CuOH) have been scarce due to structural metastability. Herein, a facile, wet-chemistry procedure is reported for the preparation of stable CuOH nanostructures via deliberate functionalization with select organic ligands, such as acetylene and mercapto derivatives. The resulting nanostructures are found to exhibit a nanoribbon morphology consisting of small nanocrystals embedded within a largely amorphous nanosheet-like scaffold. The acetylene derivatives are found to anchor onto the CuOH forming CuC linkages, whereas CuS interfacial bonds are formed with the mercapto ligands. Effective electronic coupling occurs at the ligand-core interface in the former, in contrast to mostly non-conjugated interfacial bonds in the latter, as manifested in spectroscopic measurements and confirmed in theoretical studies based on first principles calculations. Notably, the acetylene-capped CuOH nanostructures exhibit markedly enhanced photodynamic activity in the inhibition of bacteria growth, as compared to the mercapto-capped counterparts due to a reduced material bandgap and effective photocatalytic generation of reactive oxygen species. Results from this study demonstrate that deliberate structural engineering with select organic ligands is an effective strategy in the stabilization and functionalization of CuOH nanostructures, a critical first step in exploring their diverse applications.

Carbon-supported nanocomposites are attracting particular attention as high-performance, low-cost electrocatalysts for electrochemical water splitting. These are mostly prepared by pyrolysis and hydrothermal procedures that are time-consuming (from hours to days) and typically difficult to produce a nonequilibrium phase. Herein, for the first time ever, we exploit magnetic induction heating-quenching for ultrafast production of carbon-FeNi spinel oxide nanocomposites (within seconds), which exhibit an unprecedentedly high performance towards oxygen evolution reaction (OER), with an ultralow overpotential of only +260 mV to reach the high current density of 100 mA cm-2. Experimental and theoretical studies show that the rapid heating and quenching process (ca. 103 K s-1) impedes the Ni and Fe phase segregation and produces a Cl-rich surface, both contributing to the remarkable catalytic activity. Results from this study highlight the unique advantage of ultrafast heating/quenching in the structural engineering of functional nanocomposites to achieve high electrocatalytic performance towards important electrochemical reactions.