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Abstract Background Effective response and reducing the burden of family care for children with cancer is critical, and China currently lacks a specific assessment tool. Aims This study aimed to translate and validate the Caregiving Burden Scale for Family Caregivers of Children with Cancer (CBSFC-CC) and then test and implement the tool. Methods According to the Beaton cross-cultural debugging guide, preliminary Chinese version of CBSFC-CC scale was formed, which was suitable for Chinese language environment and clinical context. Exploratory factor analyses (EFA) and confirmatory factor analyses (CFA) were performed to verify structural validity. Convergent validity, discriminant validity and reliability were also conducted. Results A total of 529 family caregivers of children with cancer participated in the survey. EFA extracts and combines four factors and explained 65.80% of the total variation. CFA proved that all the goodness-of-fit indicators were acceptable. The Cronbach’s alpha of the Chinese version of CBSFC-CC was .96, and the test–retest reliability coefficient was .95. Four dimensions and 29 items were identified in the final Chinese version of CBSFC-CC. Conclusion The chinese version CBSFC-CC is scientifically reasonable and has good reliability and validity, which can be applied to the investigation of the nursing burden of family caregivers of children with cancer in China.

Abstract Background Schizophrenia (SZ), a psychiatric disorder for which there is no precise diagnosis, has had a serious impact on the quality of human life and social activities for many years. Therefore, an advanced approach for accurate treatment is required. New method In this study, we provide a classification approach for SZ patients based on a spatial–temporal residual graph convolutional neural network (STRGCN). The model primarily collects spatial frequency features and temporal frequency features by spatial graph convolution and single-channel temporal convolution, respectively, and blends them both for the classification learning, in contrast to traditional approaches that only evaluate temporal frequency information in EEG and disregard spatial frequency features across brain regions. Results We conducted extensive experiments on the publicly available dataset Zenodo and our own collected dataset. The classification accuracy of the two datasets on our proposed method reached 96.32% and 85.44%, respectively. In the experiment, the dataset using delta has the best classification performance in the sub-bands. Comparison with existing methods Other methods mainly rely on deep learning models dominated by convolutional neural networks and long and short time memory networks, lacking exploration of the functional connections between channels. In contrast, the present method can treat the EEG signal as a graph and integrate and analyze the temporal frequency and spatial frequency features in the EEG signal. Conclusion We provide an approach to not only performs better than other classic machine learning and deep learning algorithms on the dataset we used in diagnosing schizophrenia, but also understand the effects of schizophrenia on brain network features.

Abstract Objective This research aimed to identify the fundamental and geographic characteristics of the primary healthcare personnel mobility in Nanning from 2000 to 2021 and clarify the determinants that affect their transition to non-primary healthcare institutions. Methods Through utilizing the Primary Healthcare Personnel Database (PHPD) for 2000–2021, the study conducts descriptive statistical analysis on demographic, economic, and professional aspects of healthcare personnel mobility across healthcare reform phases. Geographic Information Systems (QGIS) were used to map mobility patterns, and R software was employed to calculate spatial autocorrelation (Moran’s I). Logistic regression identified factors that influenced the transition to non-primary institutions. Results Primary healthcare personnel mobility is divided into four phases: initial (2000–2008), turning point (2009–2011), rapid development (2012–2020), and decline (2021). The rapid development stage saw increased mobility with no spatial clustering in inflow and outflow. From 2016 to 2020, primary healthcare worker mobility reached its peak, in which the most significant movement occurred between township health centers and other institutions. Aside from their transition to primary medical institutions, the primary movement of grassroots health personnel predominantly directs towards secondary general hospitals, tertiary general hospitals, and secondary specialized hospitals. Since 2012, the number and mobility distance of primary healthcare workers have become noticeably larger and remained at a higher level from 2016 to 2020. The main migration of primary healthcare personnel occurred in their districts (counties). Key transition factors include gender, education, ethnicity, professional category, general practice registration, and administrative division. Conclusions This study provides evidence of the features of primary healthcare personnel mobility in the less developed western regions of China, in which Nanning was taken as a case study. It uncovers the factors that impact the flow of primary healthcare personnel to non-primary healthcare institutions. These findings are helpful to policy refinement and support the retention of primary healthcare workers.

Abstract Background Alzheimer’s disease (AD) and Parkinson’s disease (PD), two common irreversible neurodegenerative diseases, share similar early stage syndromes, such as olfaction dysfunction. Yet, the potential comorbidity mechanism of AD and PD was not fully elucidated. Methods The gene expression profiles of GSE5281 and GSE8397 were downloaded from the Gene Expression Omnibus (GEO) database. We utilized a series of bioinformatics analyses to screen the overlapped differentially expressed genes (DEGs). The hub genes were further identified by the plugin CytoHubba of Cytoscape and validated in the hippocampus (HIP) samples of APP/PS-1 transgenic mice and the substantial nigra (SN) samples of A53T transgenic mice by real-time quantitative polymerase chain reaction (RT-qPCR). Meanwhile, the expression of the target genes in the olfactory epithelium/bulb was detected by RT-qPCR. Finally, molecular docking was used to screen potential compounds for the target gene. Results One hundred seventy-four overlapped DEGs were identified in AD and PD. Five of the top ten enrichment pathways mainly focused on the synapse. Five hub genes were identified and further validated. As a common factor in AD and PD, the changes of synaptosomal-associated protein 25 (SNAP25) mRNA in olfactory epithelium/bulb were significantly decreased and had a strong association with those in the HIP and SN samples. Pazopanib was the optimal compound targeting SNAP25, with a binding energy of − 9.2 kcal/mol. Conclusions Our results provided a theoretical basis for understanding the comorbidity mechanism of AD and PD and highlighted that SNAP25 in the olfactory epithelium may serve as a potential target for early detection and intervention in both AD and PD.

Abstract Background Prevention, screening, and early treatment are the aims of postoperative delirium management. The scoring system is an objective and effective tool to stratify potential delirium risk for patients undergoing cardiac surgery. Methods Patients who underwent cardiac surgery between January 1, 2012, and January 1, 2019, were enrolled in our retrospective study. The patients were divided into a derivation cohort (n = 45,744) and a validation cohort (n = 11,436). The AD predictive systems were formulated using multivariate logistic regression analysis at three time points: preoperation, ICU admittance, and 24 h after ICU admittance. Results The prevalence of AD after cardiac surgery in the whole cohort was 3.6% (2,085/57,180). The dynamic scoring system included preoperative LVEF ≤ 45%, serum creatinine > 100 µmol/L, emergency surgery, coronary artery disease, hemorrhage volume > 600 mL, intraoperative platelet or plasma use, and postoperative LVEF ≤ 45%. The area under the receiver operating characteristic curve (AUC) values for AD prediction were 0.68 (preoperative), 0.74 (on the day of ICU admission), and 0.75 (postoperative). The Hosmer‒Lemeshow test indicated that the calibration of the preoperative prediction model was poor (P = 0.01), whereas that of the pre- and intraoperative prediction model (P = 0.49) and the pre, intra- and postoperative prediction model (P = 0.35) was good. Conclusions Using perioperative data, we developed a dynamic scoring system for predicting the risk of AD following cardiac surgery. The dynamic scoring system may improve the early recognition of and the interventions for AD.

Abstract Background Endoscopic screening is the widely accepted screening strategy for esophageal squmaous cell carcinoma (ESCC). However, massive endoscopic screening is expensive and not cost-efficient, and novel pre-endoscopy detection used as a preliminary screening method arouses new concerns. We are planning to launch an artificial intelligence (AI) assisted sponge cytology for detecting esophageal squmaous high-grade intraepithelial neoplasia (HGIN) and above lesions. The aim of this trail is to investigate the efficiency of AI-assisted sponge cytology in population-based screening of early esophageal squmaous epithelial lesions. Methods The study will be prospectively conducted in five regions with a high prevalence of ESCC. AI-assisted sponge cytology and endoscopic examination will be sequentially performed. Based on our previous data, at least 864 patients with esophageal HGIN and above lesions are needed to achieve enough statistical power. And, a calculated 112,500 individuals with high risks of ESCC will be recruited. In the first stage, each 24,000 participants who meet the inclusion criteria will be recruited on a voluntary basis. Setting pathological results as standard reference, diagnostic threshold and according performance of AI-assisted detection will be evaluated. A prediction model will be constructed by co-analyzing cytological results and relevant risk factors. Then, an external validation cohort will be used for validation of the model efficiency. Also, cost-efficiency analysis will be performed. This study protocol was registered on chineseclinicaltrial.gov (ChiCTR1900028524). Discussion Our study will determine whether this AI-assisted sponge cytology can be used as an effective pre-endoscopy detection tool for large-scale screening for ESCC in high-risk areas.

Abstract Background Genetic studies have implicated rare and common variations in liability for autism spectrum disorder (ASD). Of the discovered risk variants, those rare in the population invariably have large impact on liability, while common variants have small effects. Yet, collectively, common risk variants account for the majority of population-level variability. How these rare and common risk variants jointly affect liability for individuals requires further study. Methods To explore how common and rare variants jointly affect liability, we assessed two cohorts of ASD families characterized for rare and common genetic variations (Simons Simplex Collection and Population-Based Autism Genetics and Environment Study). We analyzed data from 3011 affected subjects, as well as two cohorts of unaffected individuals characterized for common genetic variation: 3011 subjects matched for ancestry to ASD subjects and 11,950 subjects for estimating allele frequencies. We used genetic scores, which assessed the relative burden of common genetic variation affecting risk of ASD (henceforth “burden”), and determined how this burden was distributed among three subpopulations: ASD subjects who carry a potentially damaging variant implicated in risk of ASD (“PDV carriers”); ASD subjects who do not (“non-carriers”); and unaffected subjects who are assumed to be non-carriers. Results Burden harbored by ASD subjects is stochastically greater than that harbored by control subjects. For PDV carriers, their average burden is intermediate between non-carrier ASD and control subjects. Both carrier and non-carrier ASD subjects have greater burden, on average, than control subjects. The effects of common and rare variants likely combine additively to determine individual-level liability. Limitations Only 305 ASD subjects were known PDV carriers. This relatively small subpopulation limits this study to characterizing general patterns of burden, as opposed to effects of specific PDVs or genes. Also, a small fraction of subjects that are categorized as non-carriers could be PDV carriers. Conclusions Liability arising from common and rare risk variations likely combines additively to determine risk of any individual diagnosed with ASD. On average, ASD subjects carry a substantial burden of common risk variation, even if they also carry a rare PDV affecting risk.

Abstract Background The Autism Sequencing Consortium identified 102 high-confidence autism spectrum disorder (ASD) genes, showing that individuals with ASD and with potentially damaging single nucleotide variation (pdSNV) in these genes had lower cognitive levels and delayed age at walking, when compared to ASD participants without pdSNV. Here, we made use of a Swedish sample of individuals with ASD (called PAGES, for Population-Based Autism Genetics & Environment Study) to evaluate the frequency of pdSNV and their impact on medical and psychiatric phenotypes, using an epidemiological frame and universal health reporting. We then combine findings with those for potentially damaging copy number variation (pdCNV). Methods SNV and CNV calls were generated from whole-exome sequencing and chromosome microarray data, respectively. Birth and medical register data were used to collect phenotypes. Results Of 808 individuals assessed by sequencing, 69 (9%) had pdSNV in the 102 ASC genes, and 144 (18%) had pdSNV in the 102 ASC genes or in a larger set of curated neurodevelopmental genes (from the Deciphering Developmental Disorders study, the gene2phenotype database, and the Radboud University gene lists). Three or more individuals had pdSNV in GRIN2B, POGZ, SATB1, DYNC1H1, SCN8A, or CREBBP. In comparison, out of the 996 individuals from whom CNV were called, 105 (11%) carried one or more pdCNV, including four or more individuals with CNV in the recurrent 15q11q13, 22q11.2, and 16p11.2 loci. Carriers of pdSNV were more likely to have intellectual disability (ID) and epilepsy, while carriers of pdCNV showed increased rates of congenital anomalies and scholastic skill disorders. Carriers of either pdSNV or pdCNV were more likely to have ID, scholastic skill disorders, and epilepsy. Limitations The cohort only included individuals with autistic disorder, the more severe form of ASD, and phenotypes are defined from medical registers. Not all genes studied are definitively ASD genes, and we did not have de novo information to aid in classification. Conclusions In this epidemiological sample, rare pdSNV were more common than pdCNV and the combined yield of potentially damaging variation was substantial at 27%. The results provide compelling rationale for the use of high-throughout sequencing as part of routine clinical workup for ASD and support the development of precision medicine in ASD.

Abstract Background The proportion of hospital deaths has declined in the past few decades, while the proportions of nursing home deaths have increased. This trend of increasing deaths in long-term care facilities underlines the importance of improving end-of-life care provisions in these settings to meet individual preferences and needs. Under these circumstances, a comprehensive understanding of end-of-life care preferences in local nursing home residents can help healthcare professionals and policymakers develop strategies to increase the advance directive completion rate and quality of care. This study aimed to explore and compare advance directive and end-of-life care preferences of nursing home residents in Hong Kong and Taiwan. Methods A structured questionnaire was developed by the research team to investigate advance directive and end-of-life care preferences in older Chinese nursing home residents. Nursing home residents with frail or pre-frail status and over the age of 64 were invited to participate in the study, and information on demographics, functional status, advance directive experiences, and end-of-life care expectations was collected through questionnaire interviews. Results A total of 325 eligible participants from 32 facilities completed the survey, including 238 older residents in Hong Kong and 87 in Taiwan. A significantly lower proportion of the Hong Kong residents had completed an advance directive compared with the Taiwanese (3 vs. 13%, p = 0.001). Among participants who did not have an advance directive, 46% of the Taiwanese participants said they would consider completing one in the future, compared with 20% of the Hong Kong participants (p

Abstract Background Endothelial injury is one of the predominant pathophysiological characteristics of sepsis and is the major cause of sepsis-induced multiple organ failure. Endothelial pyroptosis is a fatal mechanism of endothelial injury in sepsis, and specific, effective therapies are lacking. Although hepatocyte growth factor (HGF) has been shown to have anti-apoptotic and anti-necrotic effects, whether it prevents pyroptosis to improve endothelial injury in sepsis remains unclear. Methods Recombinant HGF was intravenously injected into mice with sepsis caused by caecal ligation puncture (CLP). Histopathological examination and transmission electron microscopy (TEM) were used to measure lung vascular endothelial injury. Lipopolysaccharide (LPS) was transfected into EA.hy926 cells to induce endothelial pyroptosis, and the cells were treated with HGF in the presence of inhibitors of c-Met and mTOR, namely, PHA-665752 and rapamycin, respectively. The mTOR signalling pathway and mitochondrial physiology were assessed using Western blot and flow cytometry. Results Intravenous HGF effectively alleviated pulmonary vascular endothelial injury and acute lung injury in the septic mice. The TEM results of lung tissue revealed that HGF attenuated pulmonary vascular endothelial pyroptosis, which was confirmed in vitro. Transfected LPS induced the pyroptosis of EA.hy926 cells and damaged their paracellular permeability, and these effects were ameliorated by treating the cells with recombinant HGF. The protective effect of HGF against pyroptosis was dependent on c-Met/mTOR signalling. mTOR activation effectively protected mitochondrial physiology and decreased reactive oxygen species (ROS) production in EA.hy926 cells in vitro. Conclusions These results demonstrated that HGF protected mitochondrial physiology by activating mTOR signalling to partially ameliorate endothelial pyroptosis and attenuate vascular endothelial injury and acute lung injury in sepsis animal model.

Abstract Background Proliferating cell nuclear antigen (PCNA), a ring-shaped homotrimer complex, promotes DNA replication via binding to DNA polymerase. Trimerized PCNA is critical for DNA replication. Enhancer of zeste homologue 2 (EZH2), which primarily acts as a histone methyltransferase, is essential for proliferation. However, how EZH2 promotes proliferation by controlling DNA replication through PCNA remains elusive. Results Here, we showed that low EZH2 levels repressed the proliferation of human dental pulp cells (hDPCs). The EZH2 protein level was dramatically upregulated in hDPCs at S phase in the absence of H3K27 trimethylation. Molecularly, EZH2 interacted with PCNA via the PIP box and dimethylated PCNA at lysine 110. Dimethylation of PCNA is essential for stabilization of the PCNA trimer and the binding of DNA polymerase δ to PCNA. Conclusions Our data reveal the direct interaction between PCNA and EZH2 and a novel mechanism by which EZH2 orchestrates genome duplication.

Abstract Background Integrating rare variation from trio family and case–control studies has successfully implicated specific genes contributing to risk of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASD), intellectual disability (ID), developmental disorders (DDs), and epilepsy (EPI). For schizophrenia (SCZ), however, while sets of genes have been implicated through the study of rare variation, only two risk genes have been identified. Methods We used hierarchical Bayesian modeling of rare-variant genetic architecture to estimate mean effect sizes and risk-gene proportions, analyzing the largest available collection of whole exome sequence data for SCZ (1,077 trios, 6,699 cases, and 13,028 controls), and data for four NDDs (ASD, ID, DD, and EPI; total 10,792 trios, and 4,058 cases and controls). Results For SCZ, we estimate there are 1,551 risk genes. There are more risk genes and they have weaker effects than for NDDs. We provide power analyses to predict the number of risk-gene discoveries as more data become available. We confirm and augment prior risk gene and gene set enrichment results for SCZ and NDDs. In particular, we detected 98 new DD risk genes at FDR < 0.05. Correlations of risk-gene posterior probabilities are high across four NDDs (ρ>0.55), but low between SCZ and the NDDs (ρ