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Sepsis is defined as life-threatening organ dysfunction caused by dysregulated host systemic inflammatory and immune response to infection. Over decades, advanced understanding of host–microorganism interaction has gradually unmasked the genuine nature of sepsis, guiding toward new definition and novel therapeutic approaches. Diverse clinical manifestations and outcomes among infectious patients have suggested the heterogeneity of immunopathology, while systemic inflammatory responses and deteriorating organ function observed in critically ill patients imply the extensively hyperactivated cascades by the host defense system. From focusing on microorganism pathogenicity, research interests have turned toward the molecular basis of host responses. Though progress has been made regarding recognition and management of clinical sepsis, incidence and mortality rate remain high. Furthermore, clinical trials of therapeutics have failed to obtain promising results. As far as we know, there was no systematic review addressing sepsis-related molecular signaling pathways and intervention therapy in literature. Increasing studies have succeeded to confirm novel functions of involved signaling pathways and comment on efficacy of intervention therapies amid sepsis. However, few of these studies attempt to elucidate the underlining mechanism in progression of sepsis, while other failed to integrate preliminary findings and describe in a broader view. This review focuses on the important signaling pathways, potential molecular mechanism, and pathway-associated therapy in sepsis. Host-derived molecules interacting with activated cells possess pivotal role for sepsis pathogenesis by dynamic regulation of signaling pathways. Cross-talk and functions of these molecules are also discussed in detail. Lastly, potential novel therapeutic strategies precisely targeting on signaling pathways and molecules are mentioned.

Immune dysfunction and aberrant cytokine storms often lead to rapid exacerbation of the disease during late infection stages in SARS-CoV and MERS-CoV patients. However, the underlying immunopathology mechanisms are not fully understood, and there has been little progress in research regarding the development of vaccines, anti-viral drugs, and immunotherapy. The newly discovered SARS-CoV-2 (2019-nCoV) is responsible for the third coronavirus pandemic in the human population, and this virus exhibits enhanced pathogenicity and transmissibility. SARS-CoV-2 is highly genetically homologous to SARS-CoV, and infection may result in a similar clinical disease (COVID-19). In this review, we provide detailed knowledge of the pathogenesis and immunological characteristics of SARS and MERS, and we present recent findings regarding the clinical features and potential immunopathogenesis of COVID-19. Host immunological characteristics of these three infections are summarised and compared. We aim to provide insights and scientific evidence regarding the pathogenesis of COVID-19 and therapeutic strategies targeting this disease.

Artificial intelligence (AI) has been deeply applied in the medical field and has shown broad application prospects. Pre-consultation system is an important supplement to the traditional face-to-face consultation. The combination of the AI and the pre-consultation system can help to raise the efficiency of the clinical work. However, it is still challenging for the AI to analyze and process the complicated electronic health record (EHR) data. Our pre-consultation system uses an automated natural language processing (NLP) system to communicate with the patients through the mobile terminals, applying the deep learning (DL) techniques to extract the symptomatic information, and finally outputs the structured electronic medical records. From November 2019 to May 2020, a total of 2,648 pediatric patients used our model to provide their medical history and get the primary diagnosis before visiting the physicians in the outpatient department of the Shanghai Children's Medical Center. Our task is to evaluate the ability of the AI and doctors to obtain the primary diagnosis and to analyze the effect of the consistency between the medical history described by our model and the physicians on the diagnostic performance. The results showed that if we do not consider whether the medical history recorded by the AI and doctors was consistent or not, our model performed worse compared to the physicians and had a lower average F1 score (0.825 vs. 0.912). However, when the chief complaint or the history of present illness described by the AI and doctors was consistent, our model had a higher average F1 score and was closer to the doctors. Finally, when the AI had the same diagnostic conditions with doctors, our model achieved a higher average F1 score (0.931) compared to the physicians (0.92). This study demonstrated that our model could obtain a more structured medical history and had a good diagnostic logic, which would help to improve the diagnostic accuracy of the outpatient doctors and reduce the misdiagnosis and missed diagnosis. But, our model still needs a good deal of training to obtain more accurate symptomatic information.

Background Hemolytic uremic syndrome (HUS) is a main cause of acute renal failure in children. This study aimed to analyze the clinical characteristics of HUS. Methods A retrospective analysis was performed in 46 children with sporadic HUS. Results Of the 46 HUS patients, 20 (43.5%) were diarrhea-related HUS, and 26 (56.5%) were atypical HUS. Anemia, edema, oliguria, hemoglobinuria and hypertension were the most common manifestations. Thrombocytopenia, hyponatremia, hypocalcemia, hyperkalemia, metabolic acidosis, increased fibrinogen and hypocomplementemia were found in most patients. The age of onset (younger than 2 years or not, P =0.009), the duration of oliguria or anuria (more than one week or not, P =0.005), accompanied with extrarenal complications or not ( P =0.005), dialysis and plasma exchange ( P =0.04) were associated with the mortality rate. Conclusions The age of onset younger than 2 years, oliguria/anuria more than 1 week, and associated with extrarenal complications were predictive factors of poor prognosis.

Background Neuroblastoma currently has poor prognosis, therefore we proposed a new strategy by targeting neuroblastoma with genetically engineered anaerobic Salmonella (Sal-YB1). Methods Nude and nonobese diabetic-severe combined immunodeficiency (NOD-SCID) orthotopic mouse models were used, and Sal-YB1 was administered via tail vein. The therapeutic effectiveness, bio-safety, and mechanisms were studied. Results No mice died of therapy-related complications. Tumor size reduction was 70 and 30 % in nude and NOD-SCID mice, respectively. No Salmonella was detected in the urine; 75 % mice had positive stool culture if diaminopimelic acid was added, but all turned negative subsequently. Tumor tissues had more Sal-YB1 infiltration, necrosis, and shrinkage in Sal-YB1-treated mice. Significantly higher expression of TLR4, TNF-stimulated gene 6 protein (TSG6), and cleaved caspase 1, 3, 8, and 9 was found in the tumor masses of the Sal-YB1-treated group with a decrease of interleukin 1 receptor-associated kinase (IRAK) and nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha (IκBα). There was a high release of TNFα both in human macrophages and mouse tumor tissues with Sal-YB1 treatment. The antitumor effect of the supernatant derived from macrophages treated with Sal-YB1 could be reversed with TNFα and pan-caspase inhibitors. Conclusions This new approach in targeting neuroblastoma by bio-engineered Salmonella with the assistance of macrophages indirectly may have a clinical therapeutic impact in the future.

Background This study aimed to discribe the experience in supporting children with refractory cardiopulmonary failure with extracorporeal membrane oxygenation (ECMO). Methods We retrospectively reviewed 12 children with refractory cardiopulmonary failure supported with ECMO from February 2009 to August 2015 in the Pediatric Intensive Care Unit (PICU), Children’s Hospital, Zhejiang University School of Medicine. Results Seven of the 12 patients were weaned successfully from ECMO and dischaged from the hospital, with a survival rate of 58.3% (7/12). Among them, five patients had acute fulminant myocarditis (AFM). Complications during ECMO included hemorrhage, hemolysis, thrombosis, acute kidney injury, and secondary hematogenous infection. During 1-24 month follow-up, the seven surviving patients recovered with normal cardiopulmonary function. Conclusions ECMO is useful for supporting children with refractory cardiopulmonary failure, especially for treatment of AFM.

CD14 is the pivotal molecule in the diagnosis and therapy of CD14-associated diseases, and is important in bacteremia. The HeLa cell line is regarded as immortal due to its prolific character. The HeLa cell line is derived from human cervical cancer cells and has been widely used in cancer research and gene transfection. In the present study, we established the expression plasmid pcDNA3.1(+)-CD14, and transfected it into the human cervical cancer cell line HeLa to establish a stable cell line (HeLa-CD14) expressing human CD14 antigen on the membrane. After the human CD14 gene was cloned and sequenced through RT-PCR and T-A cloning techniques, the eukaryotic expression vector pcDNA3.1(+)-CD14 was constructed by cleaving with double restriction endonucleases and ligating with T4 ligase. HeLa cells were transfected with the pcDNA3.1(+)-CD14 recombinant plasmid using Superfect transfection reagent. The cells were selected using G418 and the expression of human CD14 on the transfectant was confirmed by RT-PCR and immunohistochemistry. The expression of CD14 mRNA was significantly different between the blank pcDNA3.1(+)-transfected cell group and the pcDNA3.1(+)-CD14-transfected cell group (p<0.01). The fluorescence was significantly stronger on the established stable cell line than on the transiently transfected HeLa cells, and no visible fluorescence was observed in blank pcDNA3.1(+)-transfected cells. In this study, the human CD14 transfectant, stable cell line HeLa-CD14, was successfully established, which may be used to study CD14 and cervical cancer in vitro and in vivo.

Ventilator-associated pneumonia (VAP) is a common and sometimes fatal complication in pediatric intensive care units (PICU). The aim of our study was to characterize the distribution and drug susceptibility of the pathogens isolated from the sputum of patients with VAP in the PICU of our hospital and to provide support to the administration of antibiotics early and reasonably in the clinic. Our study was conducted between January 2007 and December 2011 at the PICU of the Children's Hospital of Zhejiang University School of Medicine. The endotracheal aspirates were collected and transported to a microbiology laboratory within 15 min. The pathogens were routinely analyzed and identified with Vitek 60 and Kirby-Bauer disk diffusion methods. Among the 121 VAP patients, 127 pathogenic strains were isolated from sputum specimens. Gram-negative and gram-positive bacteria and fungi accounted for 64.57% (82/127), 29.92% (38/127) and 5.51% (7/127), respectively. Acinetobacter baumannii (25.61%), Escherichia coli (20.27%), Stenotrophomonas maltophilia (20.27%), Klebsiella pneumoniae (16.22%) and Pseudomonas aeruginosa (9.46%) were frequently identified isolates among gram-negative bacteria. Staphylococci were susceptible to vancomycin and linezolid. All fungi were sensitive to the antimicrobial agents. The gram-negative bacteria were more prevalent than gram-positive bacteria and fungi in VAP and demonstrated a higher drug resistance. It is important to administer antimicrobial agents early and reasonably for children with VAP. Knowledge of antibiotic resistance and the characteristics of drug resistance is important for VAP prophylaxis and treatment.

Temperature is a key variable in alpine regions such as the Tianshan Mountains, which affects the population and economic development in lowlands by regulating the melting of snow and glaciers. The climate change over the Tianshan Mountains may have a strong climate impact. This study develops a new downscaling scheme including global climate models and DEM to simulate a high‐resolution temperature data set (90 m) in the Tianshan Mountains from 2021 to 2050. First, at low resolution, we developed a batch gradient descent‐based nonlinear regression downscaling model to simulate the relationship between CMIP5 and CMIP6 temperature and explanatory variables. Then, we input high‐resolution explanatory variables into the model to obtain downscaled (90 m) grid temperature data sets. At 30 meteorological stations, the R2 of the observations and simulations is above 0.80 under RCP4.5 scenario and above 0.60 under SSP245 scenario. The RRMSE and MARE are below 0.53, and the slope of the linear functions of the two are close to 1. The simulation results show that Tianshan will accelerate warming in the next 30 years. Under the RCP4.5 scenario, the temperature will rise the fastest in autumn with 2°C/10a, and decrease in spring with 1.4°C/10a. Under the SSP245 scenario, the temperature will rise significantly in spring and winter, with 1°C/10a. Spatially, high mountains will warm faster than plains and basins. The insights gained in this research have the potential to inform climate forecasting efforts, providing a foundation for predicting runoff dynamics, assessing regional water resources, and estimating net primary productivity. Plain Language Summary Temperature is a critical variable in mountainous regions such as the Tianshan Mountains. A new method was established in this study to generate a high‐resolution temperature data set for this region. The approach leverages global climate models and topographic data to derive temperature estimates at a fine spatial scale (90 m grids) for the period 2021–2050. Validation against observations from 30 meteorological stations demonstrated robust model performance, with a strong agreement against historical data. The simulation results project rapid warming across the Tianshan Mountains over the next three decades, with heterogeneous rates across seasons and topography. The data set produced by this research provides a valuable basis for enhancing climate forecasts, thereby supporting improved predictions of runoff and sustainable management of regional water resources. Key Points Developed a temperature downscaling scheme based on batch gradient descent‐nonlinear regression Simulated the high‐resolution (90 m) temperature data set of Tianshan from January 2000 to December 2050 Tianshan will accelerate warming in the next 30 years, and high mountains will warm faster than plains and basins

[...]20 Chinese college students completed the preliminary version and were interviewed to determine whether they understood each question correctly. Some of the 20 students who were asked to evaluate the translation also felt uncertain about the exact meaning of the Chinese term, but when we added an explanation sentence to the questionnaire after the term they could get it. [...]in the final version of the translation, we added this sentence for explanation. [...]the IdFAI-C has high discriminative validity, high reliability, and good accuracy, making it suitable for Chinese physicians and foot-and-ankle surgeons to use in clinical practice.