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Missense mutations in ATM kinase, a master regulator of DNA damage responses, are found in many cancers, but their impact on ATM function and implications for cancer therapy are largely unknown. Here we report that 72% of cancer-associated ATM mutations are missense mutations that are enriched around the kinase domain. Expression of kinase-dead ATM (AtmKD/-) is more oncogenic than loss of ATM (Atm-/-) in mouse models, leading to earlier and more frequent lymphomas with Pten deletions. Kinase-dead ATM protein (Atm-KD), but not loss of ATM (Atm-null), prevents replication-dependent removal of Topo-isomerase I-DNA adducts at the step of strand cleavage, leading to severe genomic instability and hypersensitivity to Topo-isomerase I inhibitors. Correspondingly, Topo-isomerase I inhibitors effectively and preferentially eliminate AtmKD/-, but not Atm-proficientor Atm-/- leukemia in animal models. These findings identify ATM kinase-domain missense mutations as a potent oncogenic event and a biomarker for Topo-isomerase I inhibitor based therapy.

Abstract The current study was to explore the prevalence and risk factors elements of pre-frailty and frailty among patients undergoing hemodialysis (HD) in central China. A cross-sectional, multi-institutional investigation was conducted. From March to May 2024, using the convenience sampling method, a total of 408 HD patients from four hospitals in Xiangyang, China, were recruited for this study. The participants’ demographics, lifestyle factors, factors related to dialysis treatment, the FRAIL scale, psychological resilience, and medical coping modes were assessed using a questionnaire. Multi-categorical logistic regression was performed to examine factors associated with pre-frailty and frailty in this population. Furthermore, to evaluate the independent relationship between frailty and psychological resilience, multiple regression analysis was used to adjust potential confounders and obtain odds ratios (OR) and 95% confidence intervals (CI). Pearson correlation analysis was used for correlation analysis among various scales. Among the 408 participants, the prevalence of pre-frailty and frailty among participants for all ages was 26.2% and 38.5%. Multivariate logistic regression analysis showed that smoking status, falls, heart disease, and psychological resilience are all associated with pre-frailty and frailty. The Pearson correlation analysis showed that resignation was positively related to frailty and negatively related to psychological resilience in patients. Confrontation and avoidance were positively related to psychological resilience. Frailty was negatively related to psychological resilience. Psychological resilience was independently linearly associated with pre-frailty (OR 0.49, 95% CI 0.32–0.75, p

Abstract Low-light image enhancement aims to enhance the visibility and contrast of low-light images while eliminating complex degradation issues such as noise, artifacts, and color distortions. Most existing low-light image enhancement methods either focus on quality while neglecting computational efficiency or have limited learning and generalization capabilities. To address these issues, we propose a Bilateral Enhancement Network with signal-to-noise ratio fusion, called BiEnNet, for lightweight and generalizable low-light image enhancement. Specifically, we design a lightweight Bilateral enhancement module with SNR (Signal-to-Noise Ratio) Fusion (BSF), which serves the SNR map of the input low-light image as the interpolation weights to dynamically fuse global brightness features and local detail features extracted from a bilateral network and achieve differentiated enhancement across different regions. To improve the network’s generalization ability, we propose a Luminance Normalization (LNM) module for preprocessing and a Dual-Exposure Processing (DEP) module for post-processing. LNM divides the channels of input features into luminance-related channels and luminance independent channels, and reduces the inconsistency of the degradation distribution of input low-light images by only normalizing the luminance-related channels. DEP learns overexposure and underexposure corrections simultaneously by employing the ReLU activation function, inverting operation, and residual network, which can improve the robustness of enhancement effects under different exposure conditions while reducing network parameters. Experiments on the LOL-V1 dataset shows BiEnNet significantly increased PSNR by 8.6 $$\%$$ and SSIM by 3.6 $$\%$$ compared to FLW-Net, reduced parameters by 98.78 $$\%$$ , and improved computational speed by 52.64 $$\%$$ compared to the classical KIND.

Abstract Wazwaz Kaur Boussinesq (WKB) equation can effectively simulate the behavior of water waves in shallow water, including the nonlinear effect and dispersion phenomenon of waves, which is of great significance for understanding the dynamic process of ocean, river and other water bodies. To enrich the wave equation theory, the (3+1)-dimensional integer order derivative of WKB equation is changed to the fractional one with beta derivative. The current work deals with the fractional (3+1)-dimensional WKB equation for discussing its chaotic behavior and establishing some new analytic solutions. The chaotic properties of the equation are verified by the trend of evolution along with time, Lyapunov exponents and initial sensitivity analysis. And then complete discrimination system for polynomial method is applied to derive some trigonometric, hyperbolic, Jacobi elliptic and other solutions. The graphical demonstrations are provided for part of these solutions. From these visualized graphs, the solitary, periodic and quasi-periodic wave are shown and the effect of fractional derivatives on the equation can be seen intuitively.

Abstract Objective To investigate the value of 7E instructional model in the teaching of nursing students in nursing clinical probation. Methods One hundred and fifty-nine nursing undergraduates of the class of 2018 who were on probation in our hospital from November 2020 to June 2021 were selected as the control group by convenience sampling, and the traditional teaching model was adopted; an additional 171 nursing undergraduates of the class of 2019 who were on clinical probation in the same hospital from November 2021 to June 2022 were selected as the experimental group, and the 7E instructional model was adopted, including elicit, engagement, exploration, explain, elaborate, evaluate and extend. Results After the intervention, the experimental group was higher than the control group in theoretical knowledge scores (59.47 ± 4.51 VS 54.11 ± 8.46), practical skills scores (19.62 ± 1.36 VS 19.14 ± 1.24) and total course scores (90.13 ± 2.98 VS 84.67 ± 4.47); total scores of learning motivation (30.57 ± 5.24 VS 29.41 ± 4.77), learning cooperation ability (20.35 ± 4.41 VS 19.02 ± 4.25), information literacy (23.14 ± 4.36 VS 21.12 ± 3.95) and self-regulated learning ability (114.00 ± 19.72 VS 109.07 ± 18.61); total scores of viewpoint acquisition (43.58 ± 5.21 VS 42.16 ± 5.10), emotional care (33.41 ± 4.54 VS 32.09 ± 4.47), transposition thinking (13.04 ± 2.97 VS 11.56 ± 2.43) and empathy ability (89.03 ± 13.87 VS 85.81 ± 13.55); and total scores of positive attitudes toward communication skills (55.39 ± 7.03 VS 51.54 ± 6.54), with a statistically significant difference (P

Abstract This study aims to investigate the potential relationships between the systemic immune-inflammation index (SII) and body mass index (BMI), waist circumference, and the prevalence of obesity. A cross-sectional analysis was conducted on 7,645 individuals aged 20 and above from the NHANES 2017–2020. Multivariate linear regression analyses were conducted to evaluate the association of the logarithmically transformed SII (lgSII) with BMI and waist circumference. Additionally, multivariable logistic regression was utilized to explore the relationship between lgSII and the prevalence of obesity. Fitted smoothing curves and threshold-effect analysis were applied to elucidate nonlinear relationships. In the fully adjusted model, a positive relationship was observed between lgSII and BMI, waist circumference, and obesity prevalence (β = 3.13, 95% CI 2.10–4.16; β = 7.81, 95% CI 5.50–10.13; OR = 1.44, 95% CI 1.12–1.86). The variables of gender, age, race, education, marital status, poverty income ratio (PIR), energy intake, sleep disorder, smoking status, and alcohol use did not significantly modify the positive association between lgSII and obesity. However, physical activity appeared to influence the positive correlation between lgSII and obesity. Using a two-segment linear regression model, an inverted U-shaped relationship was observed between lgSII and both BMI and waist circumference. Furthermore, lgSII demonstrated a linear positive correlation with obesity prevalence. When stratified by physical activity, lgSII showed a non-significant negative correlation with obesity in the physically active group. Our findings underscore a robust association between the logarithmically transformed SII and BMI, waist circumference, and the prevalence of obesity.

Abstract Background This study investigates the molecular mechanisms of CC@AC&SF@PP NPs loaded with AC099850.3 siRNA and sorafenib (SF) for improving hepatitis B virus-related hepatocellular carcinoma (HBV-HCC). Methods A dataset of 44 HBV-HCC patients and their survival information was selected from the TCGA database. Immune genes related to survival status were identified using the ImmPort database and WGCNA analysis. A prognostic risk model was constructed and analyzed using Lasso regression. Differential analysis was performed to screen key genes, and their significance and predictive accuracy for HBV-HCC were validated using Kaplan–Meier survival curves, ROC analysis, CIBERSORT analysis, and correlation analysis. The correlation between AC099850.3 and the gene expression matrix was calculated, followed by GO and KEGG enrichment analysis using AC099850.3 and its co-expressed genes. HepG2.2.15 cells were selected for in vitro validation, and lentivirus interference, cell cycle determination, CCK-8 experiments, colony formation assays, Transwell experiments, scratch experiments, and flow cytometry were performed to investigate the effects of key genes on HepG2.2.15 cells. A subcutaneous transplanted tumor model in mice was constructed to verify the inhibitory effect of key genes on HBV-HCC tumors. Subsequently, pH-triggered drug release NPs (CC@AC&SF@PP) were prepared, and their therapeutic effects on HBV-HCC in situ tumor mice were studied. Results A prognostic risk model (AC012313.9, MIR210HG, AC099850.3, AL645933.2, C6orf223, GDF10) was constructed through bioinformatics analysis, showing good sensitivity and specificity in diagnostic prediction. AC099850.3 was identified as a key gene, and enrichment analysis revealed its impact on cell cycle pathways. In vitro cell experiments demonstrated that AC099850.3 promotes HepG2.2.15 cell proliferation and invasion by regulating immune checkpoint CD276 expression and cell cycle progression. In vivo, subcutaneously transplanted tumor experiments showed that AC099850.3 promotes the growth of HBV-HCC tumors in nude mice. Furthermore, pH-triggered drug release NPs (CC@AC&SF@PP) loaded with AC099850.3 siRNA and SF were successfully prepared and delivered to the in situ HBV-HCC, enhancing the effectiveness of combined therapy for HBV-HCC. Conclusions AC099850.3 accelerates the cell cycle progression and promotes the occurrence and development of HBV-HCC by upregulating immune checkpoint CD276 expression. CC@AC&SF@PP NPs loaded with AC099850.3 siRNA and SF improve the effectiveness of combined therapy for HBV-HCC.

Abstract Objective To explore the application effect of procedural pathways combined with information management in the construction of nursing staff skills training system. Methods This was a quasi-experimental study with a control group and an experimental group. A total of 300 newly admitted nurses or nurses who required training within three years of admission were selected as the experimental group, and 267 nurses who were trained in the same hospital during the same period in 2020 were selected as the control group. The experimental group received skills training using a system that combines procedural pathways with information management, while the control group received traditional teaching mode. The outcome measures included theoretical score, operation score, nurse competency, patient satisfaction, and nursing-related adverse events. The data were analyzed using t-test, chi-square test, and rank-sum test. Results The experimental group had higher scores in theoretical assessment, skills assessment, nurse competency, and patient satisfaction, and lower incidence of nursing-related adverse events than the control group (P

Background: Pigeon paramyxovirus type 1 (PPMV-1) is a significant pathogen affecting pigeon populations globally. The commonly used La Sota vaccine provides limited protection due to antigenic divergence from circulating PPMV-1 strains. An antigenically matched vaccine is needed to address this challenge. Methods: An attenuated aTJ strain was developed through reverse genetics by modifying the F protein cleavage site of the virulent TJ-WT strain. Pigeons were immunized twice with the aTJ strain via eyedrop and intranasal routes, followed by a challenge with a virulent PPMV-1 strain ten days after the booster immunization. Results: The attenuated aTJ strain induced robust serum antibody titers post-booster immunization, and vaccinated pigeons showed strong protection upon challenge, with significantly reduced morbidity, mortality, and viral shedding compared to controls. Conclusions: These findings suggest that the aTJ strain is a promising candidate for the promotion of PPMV-1 prevention and control, emphasizing the importance of antigenic matching in optimizing vaccine efficacy.

Abstract The tumour microenvironment is infiltrated by immunosuppressive cells, such as regulatory T cells (Tregs), which contribute to tumour escape and impede immunotherapy outcomes. Soluble fibrinogen-like protein 2 (sFGL2), a Treg effector protein, inhibits immune cell populations, via receptors FcγRIIB and FcγRIII, leading to downregulation of CD86 in antigen presenting cells and limiting T cell activation. Increased FGL2 expression is associated with tumour progression and poor survival in several different cancers, such as glioblastoma multiforme, lung, renal, liver, colorectal, and prostate cancer. Querying scRNA-seq human cancer data shows FGL2 is produced by cells in the tumour microenvironment (TME), particularly monocytes and macrophages as well as T cells and dendritic cells (DCs), while cancer cells have minimal expression of FGL2. We studied the role of FGL2 exclusively produced by cells in the TME, by leveraging Fgl2 knockout mice. We tested two murine models of cancer in which the role of FGL2 has not been previously studied: epithelial ovarian cancer and melanoma. We show that absence of FGL2 leads to a more activated TME, including activated DCs (CD86+, CD40+) and T cells (CD25+, TIGIT+), as well as demonstrating for the first time that the absence of FGL2 leads to more activated natural killer cells (DNAM-1+, NKG2D+) in the TME. Furthermore, the absence of FGL2 leads to prolonged survival in the B16F10 melanoma model, while the absence of FGL2 synergizes with oncolytic virus to prolong survival in the ID8-p53 −/− Brca2 −/− ovarian cancer model. In conclusion, targeting FGL2 is a promising cancer treatment strategy alone and in combination immunotherapies.

Abstract Background Tar is the main toxic of cigarettes, and its effect on atherosclerosis progression and the underlying mechanisms remain largely unknown. Vascular smooth muscle cells (VSMCs) play a key role in atherogenesis and plaque vulnerability. The present study sought to investigate the mechanism of atherosclerosis progression through tar-induced VSMC necroptosis, a recently described form of necrosis. Methods The effect of tar on atherosclerosis progression and VSMC necroptosis was examined in ApoE−/− mice and cultured VSMCs. The role of necroptosis in tar-induced plaque development was evaluated in RIPK3-deletion mice (ApoE−/−RIPK3−/−). The key proteins of necroptosis in carotid plaques of smokers and non-smokers were also examined. Quantitative proteomics of mice aortas was conducted to further investigate the underlying mechanism. Pharmacological approaches were then applied to modulate the expression of targets to verify the regulatory process of tar-induced necroptosis. Results Tar administration led to increased atherosclerotic plaque area and reduced collagen and VSMCs in ApoE−/− mice. The expression of RIPK1、RIPK3、and MLKL in VSMCs of plaques were all increased in tar-exposed mice and smokers. RIPK3 deletion protected against VSMC loss and plaque progression stimulated by tar. In mechanistic studies, quantitative proteomics analysis of ApoE−/− mice aortas suggested that tar triggered endoplasmic reticulum (ER) stress. PERK-eIF2α-CHOP axis was activated in tar-treated VSMCs and atherosclerotic plaque. Inhibition of ER stress using 4PBA significantly reduced plaque progression and VSMC necroptosis. Further study revealed that ER stress resulted in calcium (Ca2+) release into mitochondria and cytoplasm. Elevated Ca2+ levels lead to mitochondrial dysfunction and excessive reactive oxygen species (ROS) production, which consequently promote RIPK3-dependent necroptosis. In addition, Ca2+/calmodulin-dependent protein kinase II (CaMKII) activated by cytosolic Ca2+ overload binds to RIPK3, accounting for necroptosis. Conclusion The findings revealed that cigarette tar promoted atherosclerosis progression by inducing RIPK3-dependent VSMC necroptosis and identified novel avenues of ER stress and Ca2+ overload.

Abstract Giardia duodenalis is a gastrointestinal protozoan ubiquitous in nature. It is a confirmed zoonotic pathogen, and cattle are considered a source of giardiasis outbreaks in humans. This study aimed to evaluate the prevalence and multilocus genotype (MLG) of G. duodenalis in dairy cattle in Central Inner Mongolia. This study was based on the small subunit ribosomal RNA (SSU rRNA), glutamate dehydrogenase (gdh), triosephosphate isomerase (tpi), and beta-giardin (bg) genes of G. duodenalis. DNA extraction, polymerase chain reaction (PCR), and sequence analysis were performed on 505 dairy cattle fecal samples collected in 2021 from six sampling sites and four age groups in Central Inner Mongolia to determine the prevalence and MLG distribution of G. duodenalis. The PCR results of SSU rRNA revealed that the overall prevalence of G. duodenalis was 29.5% (149/505) and that the overall prevalence of the diarrhea and nondiarrhea samples was 31.5% (46/146) and 28.5% (103/359), respectively; the difference was not significant (p > 0.05). SSU rRNA sequence analysis revealed that G. duodenalis assemblage E (91.1%, 133/146) was primarily detected and that assemblage A (8.9%, 13/146) was detected in 13 samples. The G. duodenalis—positive samples were PCR amplified and sequenced for gdh, tpi, and bg, from which 38, 47, and 70 amplified sequences were obtained, respectively. A combination of G. duodenalis assemblages A and E were detected in seven samples. Multilocus genotyping yielded 25 different assemblage E MLGs, which formed six subgroups. To the best of our knowledge, this is the first report regarding G. duodenalis infection in dairy cattle in Inner Mongolia, China. This study revealed that Inner Mongolian cattle pose a risk of giardiasis transmission to humans and that the distribution of local cattle G. duodenalis assemblage E MLGs is diverse. The findings of this study can bridge the knowledge gap in the molecular epidemiological investigation of giardiasis in Central Inner Mongolia.

Abstract Background Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. Methods Using measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N = 437), we identified 413 higher plasma abundances of protein targets and 30 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p

Background: Perioperative neurocognitive disorders (PNDs) were the most common complication in elderly patients undergoing surgery. Early identification of risk factors for PNDs and implementation of preventive measures were critical to improve prognosis. We performed this systematic review and meta-analysis to explore the impact of preoperative frailty on PNDs in elderly surgical patients. Materials and Methods: Systematic searches were performed in PubMed, Embase, and Web of Science. A fixed-effect model in RevMan5.3 software was conducted due to the low heterogeneity. The potential risk bias was assessed through Funnel plot and Egger’s test. Sensitivity analysis was used to examine the robustness of the outcomes. Results: Sixteen cohort studies enrolling 4805 elderly patients were qualified for meta-analysis. Pooled results showed that preoperative frailty was linked to the development of PNDs (pooled odds ratio [OR]: 2.40, 95% confidence interval [CI]: 2.05–2.80, P < 0.001) without obvious heterogeneity (P = 0.19, I2 = 22%). Subgroup analyses revealed that the correlation between preoperative frailty and PNDs was more remarkable in prospective cohort studies (OR: 3.11, 95% CI: 2.47–3.91, P < 0.001) compared to retrospective cohort studies (OR: 1.94, 95% CI: 1.57–2.39, P < 0.001; test for subgroup difference, P = 0.003). In addition, the correlation in patients with cardiac surgery (OR: 3.38, 95% CI: 2.44–4.68, P < 0.001) was more noticeable than noncardiac surgery (OR: 2.17, 95% CI: 1.82–2.59, P < 0.001; test for subgroup difference P = 0.02). Conclusion: Our results demonstrated that preoperative frailty was independently associated with PNDs in geriatric patients undergoing elective surgery.

BackgroundIn recent years, remarkable progress has been made in the use of machine learning, especially in analyzing prognosis survival data. Traditional prediction models cannot identify interrelationships between factors, and the predictive accuracy is lower. This study aimed to construct Bayesian network models using the tree augmented naïve algorithm in comparison with the Cox proportional hazards model.MethodsA Bayesian network model and a Cox proportional hazards model were constructed to analyze the prognostic factors of endometrial cancer. In total, 618 original cases obtained from the Surveillance, Epidemiology, and End Results database were used to construct the Bayesian network model, which was compared with the traditional Cox proportional hazards model by analyzing prognostic factors. External validation was performed using a dataset from The First Affiliated Hospital of Shandong First Medical University.ResultsThe predictive accuracy, area under the receiver operating characteristic curve, and concordance index for the Bayesian network model were 74.68%, 0.787, and 0.72, respectively, compared to 68.83%, 0.723, and 0.71, respectively, for the Cox proportional hazards model. Tumor size was the most important factor for predicting survival, followed by lymph node metastasis, distant metastasis, chemotherapy, lymph node resection, tumor stage, depth of invasion, tumor grade, histological type, age, primary tumor site, radiotherapy and surgical sequence, and radiotherapy.ConclusionThe findings indicate that the Bayesian network model is preferable to the Cox proportional hazards model for predicting survival in patients with endometrial cancer.

BackgroundDelirium is a common complication among intensive care unit (ICU) patients that is linked to negative clinical outcomes. However, adherence to the Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU (PADIS guidelines), which recommend the use of the ABCDEF bundle, is sub-optimal in routine clinical care. To address this issue, AI-AntiDelirium, a nurse-led artificial intelligence-assisted prevention and management tool for delirium, was developed by our research team. Our pilot study yielded positive findings regarding the use of AI-AntiDelirium in preventing patient ICU delirium and improving activities of daily living and increasing intervention adherence by health care staff.MethodsThe proposed large-scale pragmatic, open-label, parallel-group, cluster randomized controlled study will assess the impact of AI-AntiDelirium on the incidence of ICU delirium and delirium-related outcomes. Six ICUs in two tertiary hospitals in China will be randomized in a 1:1 ratio to an AI-AntiDelirium or a PADIS guidelines group. A target sample size of 1,452 ICU patients aged 50 years and older treated in the ICU for at least 24 hours will be included. The primary outcome evaluated will be the incidence of ICU delirium and the secondary outcomes will be the duration of ICU delirium, length of ICU and hospital stay, ICU and in-hospital mortality rates, patient cognitive function, patient activities of daily living, and ICU nurse adherence to the ABCDEF bundle.DiscussionIf this large-scale trial provides evidence of the effectiveness of AI-AntiDelirium, an artificial intelligence-assisted system tool, in decreasing the incidence of ICU delirium, length of ICU and hospital stay, ICU and in-hospital mortality rates, patient cognitive function, and patient activities of daily living while increasing ICU nurse adherence to the ABCDEF bundle, it will have a profound impact on the management of ICU delirium in both research and clinical practice.Clinical trial registrationChiCTR1900023711 (Chinese Clinical Trial Registry).

Abstract Due to the huge toxicity of co-contaminated soil with PAHs and heavy metals and the complexity of their remediation, it is thus critical to take effective remediation actions to remove heavy metals and PAHs simultaneously from the co-contaminated soil. Biosurfactant-enhanced soil washing (BESW) were investigated in this study for remediation of soil co-contaminated with phenanthrene (PHE) and cadmium (Cd). The co-existence of PHE and Cd caused the change of the structure of soil and rhamnolipid micelle, which lead to different removal rate of PHE and Cd from co-contaminated soil compared with single contaminated soil. The results of FT-IR and NMR showed that PHE entered micelles of rhamnolipid and Cd formed the complexation with the external carboxyl groups of rhamnolipid micelle. We also found that pH, concentration of rhamnolipid solution, temperature and ionic strength had influence on co-contaminated soil remediation. The effects of above mentioned four factors on co-contaminated soil remediation in BESW processes were analyzed by using Taguchi design of experiment method. Taguchi based Grey Relational Analysis was conducted to identify the optimal remediation conditions, which included pH = 9, concentration of rhamnolipid = 5 g/L, temperature = 15 °C and ionic strength = 0.01 M. Under the optimal conditions for BESW, removal rates of cadmium and phenanthrene reached 72.4% and 87.8%, respectively in co-contaminated soil.

Objective The COVID-19 pandemic has had a major impact on healthcare utilisation. This study aimed to quantify how the online and face-to-face utilisation of healthcare services changed during this time and thus gain insights into the planning of future healthcare resources during the outbreak of infectious diseases.Design This work is an interrupted time-series study.Setting Monthly hospital-grade healthcare-service data from 22 tertiary first-class public hospitals managed by the Beijing Hospital Authority and online-consultation data from GoodDoctor were used in this study.Methods This is an interrupted time-series study about the change in face-to-face and online healthcare utilisation before and after the COVID-19 outbreak. We compared the impact of COVID-19 on the primary outcomes of both face-to-face healthcare utilisation (outpatient and emergency visits, discharge volume) and online healthcare utilisation (online consultation volume). And we also analysed the impact of COVID-19 on the healthcare utilisation of different types of diseases.Results The monthly average outpatient visits and discharges decreased by 36.33% and 35.75%, respectively, compared with those in 2019 in 22 public hospitals in Beijing. Moreover, the monthly average online consultations increased by 90.06%. A highly significant reduction occurred in the mean outpatients and inpatients, which dropped by 1 755 930 cases (p

Abstract Background The aberrant expression of E3 ubiquitin ligase Pellino-1 (PELI1) contributes to several human cancer development and progression. However, its expression patterns and functional importance in papillary thyroid cancer (PTC) remains unknown. Methods PELI1 expression profiles in PTC tissues were obtained and analyzed through the starBase v3.0 analysis. Real-time PCR, Immunohistochemical assays (IHC) and Western blot were used to investigate the mRNA and protein levels of PELI1 in PTC. The effects of PELI1 on PTC cell progression were evaluated through CCK-8, colony formation, Transwell, and Wound healing assay in vitro, and a PTC xenograft mouse model in vivo. The downstream target signal of PELI1 in PTC was analyzed by using Kyoto encyclopedia of genes and genomes (KEGG), and bioinformatics tools were used to identify potential miRNAs targeting PELI1. Human umbilical cord mesenchymal stem cells were modified by miR-30c-5p and the miR-30c-5p containing extracellular vesicles were collected (miR-30c-5p-EVs) by ultra-high-speed centrifugation method. Then, the effects of miR-30c-5p-EVs on PELI1 expression and PTC progression were evaluated both in vitro and in vivo. Results Both mRNA and protein expression of PELI1 were widely increased in PTC tissues, and overexpression of PELI1 was positively correlated with bigger tumor size and lymph node metastases. PELI1 promoted PTC cell proliferation and migration in vitro. While, PELI1 silencing significantly suppressed PTC growth in vivo accompanied with reduced expression of Ki-67 and matrix metallopeptidase 2 (MMP-2). Mechanistically, PI3K-AKT pathway was identified as the downstream target of PELI1, and mediated the functional influence of PELI1 in PTC cells. Moreover, we found that the expression of miR-30c-5p was inversely correlated with PELI1 in PTC samples and further confirmed that miR-30c-5p was a tumor-suppressive miRNA that directly targeted PELI1 to inhibit PTC cell proliferation and migration. Furthermore, we showed that miR-30c-5p-EVs could effectively downregulate PELI1 expression and suppress the PTC cell growth in vitro and in vivo. Conclusion This study not only supported the first evidence that miR-30c-5p loss-induced PELI1 accumulation facilitated cell proliferation and migration by activating the PI3K-AKT pathway in PTC but also provided novel insights into PTC therapy based on miR-carrying-hUCMSC-EVs.

BackgroundAdherence to the delirium bundle intervention is sub-optimal in routine practice, and inappropriate use of the instructional design of interventions may result in higher cognitive load among nurses. It remains unclear whether the Clinical Decision Support System (CDSS) Assisted Prevention and Management for Delirium (CDSS-AntiDelirium) results in the improvement of adherence to delirium intervention and the reduction of extraneous cognitive load, as well as improving adherence to delirium intervention, among nurses in the intensive care unit (ICU).MethodsThis study (named the CDSSD-ICU) is a multicentre, prospective, cluster randomized controlled clinical trial. A total of six ICUs in two hospitals will be randomized in a 1:1 ratio to receive either the CDSS-AntiDelirium group or the delirium guidelines group. The CDSS-AntiDelirium consists of four modules: delirium assessment tools, risk factor assessment, a nursing care plan, and a nursing checklist module. Each day, nurses will assess ICU patients with the assistance of the CDSS-AntiDelirium. A total of 78 ICU nurses are needed to ensure statistical power. Outcome assessments will be conducted by investigators who are blinded to group assignments. The primary endpoint will be adherence to delirium intervention, the secondary endpoint will be nurses' cognitive load measured using an instrument to assess different types of cognitive load. Repeated measures analysis of variance will be used to detect group differences. A structural equation model will be used to clarify the mechanism of improvement in adherence.DiscussionAlthough the CDSS has been widely used in hospitals for disease assessment, management, and recording, the applications thereof in the area of delirium are still in infancy. This study could provide scientific evidence regarding the impact of a CDSS on nurses' adherence and cognitive load and promote its further development in future studies.Clinical trial registrationChiCTR1900023711 (Chinese Clinical Trial Registry).

Abstract In aerial multi-view photogrammetry, whether there is a special positional distribution pattern among candidate homologous pixels of a matching pixel in the multi-view images? If so, can this positional pattern be used to precisely confirm the real homologous pixels? These problems have not been studied at present. Therefore, the study of the positional distribution pattern among candidate homologous pixels based on the adjustment theory in surveying is investigated in this paper. Firstly, the definition and computing method of pixel’s pseudo object-space coordinates are given, which can transform the problem of multi-view matching for confirming real homologous pixels into the problem of surveying adjustment for computing the pseudo object-space coordinates of the matching pixel. Secondly, according to the surveying adjustment theory, the standardized residual of each candidate homologous pixel of the matching pixel is figured out, and the positional distribution pattern among these candidate pixels is theoretically inferred utilizing the quantitative index of standardized residual. Lastly, actual aerial images acquired by different sensors are used to carry out experimental verification of the theoretical inference. Experimental results prove not only that there is a specific positional distribution pattern among candidate homologous pixels, but also that this positional distribution pattern can be used to develop a new object-side multi-view image matching method. The proposed study has an important reference value on resolving the defects of existing image-side multi-view matching methods at the mechanism level.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect many animal species, including minks, cats, and dogs. To gain insights into SARS-CoV-2 infections in cats and dogs, we developed and validated a set of serologic assays, including ELISA and virus neutralization. Evaluation of samples from animals before they acquired coronavirus disease and samples from cats roaming SARS-CoV-2–positive mink farms confirmed the suitability of these assays for specific antibody detection. Furthermore, our findings exclude SARS-CoV-2 nucleocapsid protein as an antigen for serologic screening of cat and dog samples. We analyzed 500 serum samples from domestic cats and dogs in the Netherlands during April–May 2020. We showed 0.4% of cats and 0.2% of dogs were seropositive. Although seroprevalence in cats and dogs that had unknown SARS-CoV-2 exposure was low during the first coronavirus disease wave, our data stress the need for development of continuous serosurveillance for SARS-CoV-2 in these 2 animal species.