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Abstract Background Older adults with hearing impairments are vulnerable to cognitive impairment. Although previous reports suggest a correlation between widowhood and cognitive impairment, further investigation is needed to elucidate the effect of widowhood on cognitive function and the moderating effects of social support and participation on widowhood-related cognitive impairment in this vulnerable demographic. Methods The study’s data were sourced from the nationally representative Chinese Longitudinal Healthy Longevity Survey (CLHLS) for the years 2011, 2014, and 2018. Multiple linear regression was used to analyze the association between widowhood and cognitive function among older adults. Multivariate logistic regression examined the effect of widowhood on the likelihood of experiencing various levels of cognitive impairment in older adults with hearing impairments. A moderating effect model explored the roles of social support and participation in mitigating widowhood-related cognitive impairment. Results The cognitive function of older adults with hearing impairment was found to be lower than that of those without hearing impairment. Widowhood was significantly negatively correlated with Mini-Mental State Examination (MMSE) scores in older adults, both with (Coef. = -0.898) and without (Coef.: = -0.680) hearing impairments. A stronger association was observed between widowhood and declining cognitive function among older adults with hearing impairment. Specifically, widowhood may be more likely to significantly increase the likelihood of moderate and severe cognitive impairment (RRR = 1.326, 1.538) among older adults with hearing impairments. Social support and social participation significantly moderated the cognitive impairment associated with widowhood among hearing-impaired older adults. These forms of support and engagement are buffers against the risk of widowhood-related cognitive impairment among this demographic. Conclusions Our findings indicate that widowhood is significantly associated with cognitive impairment in older adults with hearing impairment. Social support and participation help mitigate this risk. Strategies should prioritize early screening, specialized cognitive rehabilitation, comprehensive care, and enhancing social support and participation to maintain cognitive health in this vulnerable population following widowhood.

Introduction Elderly stable chronic obstructive pulmonary disease (COPD) patients frequently experience walking dysfunction. Research indicates that balance training holds promise for enhancing walking stability in these individuals, whereas respiratory therapy (RT) can enhance walking endurance effectively. However, existing balance training regimens tailored for COPD are intricate and lack specificity, and the impact of combined RT on patients’ walking function remains uncertain. This study aims to assess the influence of core training (CT) integrated with RT on walking function among elderly stable COPD patients.Methods and analysis This randomised, assessment-blinded, routine rehabilitation-controlled trial will be carried out at the Department of Respiratory and Critical Care Rehabilitation, the Second Rehabilitation Hospital of Shanghai. A total of 42 elderly patients diagnosed with stable COPD will be randomly allocated to either the study group (SG) or the control group in a 1:1 ratio. Both groups will undergo 6 weeks of standard rehabilitation training. Additionally, patients in the SG will receive CT based on RT. The primary outcome of the study is the 6 min walk test. Secondary outcomes encompass ultrasound indicators of the diaphragm and multifidus, pulmonary function tests, Berg balance scale test, trunk impairment scale test, COPD assessment test and St. George’s Respiratory Questionnaire.Ethics and dissemination Ethical approval was obtained from the Ethics Committee of the Second Rehabilitation Hospital of Shanghai (2023-01-01, see online supplemental file 1). All patients will provide written informed consent before participation. The results of the trial are intended for publication in a peer-reviewed journal.Trial registration number ChiCTR2400080276.

Numerous studies have explored the relationship between pharmacological treatment regimens and the quality of life (QoL) of type 2 diabetes (T2D) patients. However, there is a dearth of comparative studies focusing on the QoL among rural T2D patients in China across 3 distinct pharmacological treatments: oral antidiabetic drugs (OADs), insulin therapy, and a combination of OADs and insulin. Additionally, the specific correlation between these treatment regimens and distinct dimensions of QoL remains unclear, necessitating further investigation. Data from a survey of rural T2D patients in eastern China were analyzed to calculate QoL scores for different treatment groups. Multivariate linear regression was then used to assess variations in overall QoL and specific dimensions among patients on OADs, insulin, and combined therapy. OADs were most commonly used (70.36%), followed by combined (19.47%) and insulin therapy (10.17%). Patients on OADs reported the highest overall QoL, with reduced physical discomfort, improved psychological well-being, enhanced treatment satisfaction, and fewer medication side effects. Conversely, those on combined therapy had the lowest overall QoL, primarily due to increased physical discomfort. Insulin users had moderately positive overall QoL but lower psychological well-being and treatment satisfaction, along with more adverse reactions. Disparities in QoL and its dimensions exist among rural T2D patients based on treatment regimens. Healthcare providers should prioritize support systems and interventions to help patients manage side effects of insulin and combined therapy, thereby improving their QoL.

Abstract “National Civilized City” (NCC) is regarded as China’s highest honorary title and most valuable city brand. To win and maintain the “golden city” title, municipal governments must pay close attention to various key appraisal indicators, mainly environmental ones. In this study we verify whether cities with the title are more likely to mitigate SO2 pollution. We adopt the spatial Durbin difference-in-differences (DID) model and use panel data of 283 Chinese cities from 2003 to 2018 to analyze the local (direct) and spillover effects (indirect) of the NCC policy on SO2 pollution. We find that SO2 pollution in Chinese cities is not randomly distributed in geography, suggesting the existence of spatial spillovers and possible biased estimates. Our study treats the NCC policy as a quasi-experiment and incorporates spatial spillovers of NCC policy into a classical DID model to verify this assumption. Our findings show: (1) The spatial distribution of SO2 pollution represents strong spatial spillovers, with the most highly polluted regions mainly situated in the North China Plain. (2) The Moran’s I test results confirms significant spatial autocorrelation. (3) Results of the spatial Durbin DID models reveal that the civilized cities have indeed significantly mitigated SO2 pollution, indicating that cities with the honorary title are acutely aware of the environment in their bid to maintain the golden city brand. As importantly, we notice that the spatial DID term is also significant and negative, implying that neighboring civilized cities have also mitigated their own SO2 pollution. Due to demonstration and competition effects, neighboring cities that won the title ostensibly motivates local officials to adopt stringent policies and measures for lowering SO2 pollution and protecting the environment in competition for the golden title. The spatial autoregressive coefficient was significant and positive, indicating that SO2 pollution of local cities has been deeply affected by neighbors. A series of robustness check tests also confirms our conclusions. Policy recommendations based on the findings for protecting the environment and promoting sustainable development are proposed.

In the treatment of central nervous system disease, the blood–brain barrier (BBB) is a major obstruction to drug delivery that must be overcome. In this study, we propose a brain-targeted delivery strategy based on selective opening of the BBB. This strategy allows some simple bare nanoparticles to enter the brain when mixed with special opening material; however, the BBB still maintains the ability to completely block molecules from passing through. Based on the screening of BBB opening and matrix delivery materials, we determined that phospholipase A2-catalyzed 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoserine liposomes can efficiently carry drugs into the brain immediately. At an effective dose, this delivery system is safe, especially with its effect on the BBB being reversible. This mix & act delivery system has a simple structure and rapid preparation, making it a strong potential candidate for drug delivery across the BBB.

BackgroundPulmonary rehabilitation is considered beneficial for patients undergoing lung surgery, yet its specific impacts on exercise capacity, health-related quality of life (HRQL), and cardiopulmonary function require further elucidation. This study aimed to evaluate the effect of PR on these outcomes in patients undergoing lung surgery using a retrospective propensity score-matched analysis.MethodsWe retrospectively analyzed 420 patients with non-small cell lung cancer (NSCLC) who underwent lung surgery from January 2022 to May 2024. Among these, 84 patients received PR while 336 did not (control group). Propensity score matching (PSM) at a 1:1 ratio yielded 46 patients in each group. Baseline characteristics, spirometry, cardiopulmonary exercise testing, respiratory muscle strength, HRQL, and muscle measurements were assessed pre-and post-surgery.ResultsBefore PSM, significant differences existed between groups, with the PR group being older and having different pulmonary function baselines. After PSM, groups were well-balanced. Postoperatively, the PR group showed significant improvements in FEV1/FVC (64.17% vs. 50.87%, p

AbstractMessenger RNA (mRNA) has become one of the most potential drugs in recent years. However, efficient and safe delivery of fragile and easily degradable mRNA is a major challenge. Appropriate delivery system (DS) determines the final effect of mRNA. Cationic lipids play a crucial and decisive role in the entire DS, but also cause huge biosafety problems due to the high toxicity. In this study, a new DS for mRNA delivery that combines negatively charged phospholipids was developed in order to neutralize the positive charge and thus increase the safety. Further, the factors affecting mRNA transfection from cell to animal were investigated. The mRNA DS with optimum condition of lipid composition, proportions, structure, and transfection time was synthesized. Adding an appropriate amount of the anionic lipid to liposomes could increase the safety while maintaining the original transfection efficiency. For transporting mRNA in vivo, requirements regarding the mRNA encapsulation and releasing rate should be further considered to optimize DS design and preparation.

Abstract Background and Aims Distinguishing pancreatic cancer from nonneoplastic masses is critical and remains a clinical challenge. The study aims to construct a deep learning‐based artificial intelligence system to facilitate pancreatic mass diagnosis, and to guide EUS‐guided fine‐needle aspiration (EUS‐FNA) in real time. Methods This is a prospective study. The CH‐EUS MASTER system is composed of Model 1 (real‐time capture and segmentation) and Model 2 (benign and malignant identification). It was developed using deep convolutional neural networks and Random Forest algorithm. Patients with pancreatic masses undergoing CH‐EUS examinations followed by EUS‐FNA were recruited. All patients underwent CH‐EUS and were diagnosed both by endoscopists and CH‐EUS MASTER. After diagnosis, they were randomly assigned to undergo EUS‐FNA with or without CH‐EUS MASTER guidance. Results Compared with manual labeling by experts, the average overlap rate of Model 1 was 0.708. In the independent CH‐EUS video testing set, Model 2 generated an accuracy of 88.9% in identifying malignant tumors. In clinical trial, the accuracy, sensitivity, and specificity for diagnosing pancreatic masses by CH‐EUS MASTER were significantly better than that of endoscopists. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were respectively 93.8%, 90.9%, 100%, 100%, and 83.3% by CH‐EUS MASTER guided EUS‐FNA, and were not significantly different compared to the control group. CH‐EUS MASTER‐guided EUS‐FNA significantly improved the first‐pass diagnostic yield. Conclusion CH‐EUS MASTER is a promising artificial intelligence system diagnosing malignant and benign pancreatic masses and may guide FNA in real time. Trial registration number: NCT04607720.

Abstract Background and Purpose Early detection of non‐response to neoadjuvant chemoradiotherapy (nCRT) for locally advanced colorectal cancer (LARC) remains challenging. We aimed to assess whether pretreatment radiotherapy planning computed tomography (CT) radiomics could distinguish the patients with no response or no downstaging after nCRT from those with response and downstaging after nCRT. Materials and Methods Patients with LARC who were treated with nCRT were retrospectively enrolled between March 2009 and March 2019. Traditional radiological characteristics were analyzed by visual inspection and radiomic features were analyzed through computational methods from the pretreatment radiotherapy planning CT images. Differentiation models were constructed using radiomic methods and clinicopathological characteristics for predicting non‐response to nCRT. Model performance was assessed for classification efficiency, calibration, discrimination, and clinical application. Results This study enrolled a total of 215 patients, including 151 patients in the training cohort (50 non‐responders and 101 responders) and 64 patients in the validation cohort (21 non‐responders and 43 responders). For predicting non‐response, the model constructed with an ensemble machine learning method had higher performance with area under the curve (AUC) values of 0.92 and 0.89 as compared to the model constructed with the logistic regression method (AUC: 0.72 and 0.71 for the training and validation cohorts, respectively). Both decision curve and calibration curve analyses confirmed that the ensemble machine learning model had higher prediction performance. Conclusion Pretreatment CT radiomics achieved satisfying performance in predicting non‐response to nCRT and could be helpful to assist in treatment planning for patients with LARC.

Significant strides have been made in the field of WiFi-based human activity recognition, yet recent wireless sensing methodologies still grapple with the reliance on copious amounts of data. When assessed in unfamiliar domains, the majority of models experience a decline in accuracy. To address this challenge, this study introduces Wi-CHAR, a novel few-shot learning-based cross-domain activity recognition system. Wi-CHAR is meticulously designed to tackle both the intricacies of specific sensing environments and pertinent data-related issues. Initially, Wi-CHAR employs a dynamic selection methodology for sensing devices, tailored to mitigate the diminished sensing capabilities observed in specific regions within a multi-WiFi sensor device ecosystem, thereby augmenting the fidelity of sensing data. Subsequent refinement involves the utilization of the MF-DBSCAN clustering algorithm iteratively, enabling the rectification of anomalies and enhancing the quality of subsequent behavior recognition processes. Furthermore, the Re-PN module is consistently engaged, dynamically adjusting feature prototype weights to facilitate cross-domain activity sensing in scenarios with limited sample data, effectively distinguishing between accurate and noisy data samples, thus streamlining the identification of new users and environments. The experimental results show that the average accuracy is more than 93% (five-shot) in various scenarios. Even in cases where the target domain has fewer data samples, better cross-domain results can be achieved. Notably, evaluation on publicly available datasets, WiAR and Widar 3.0, corroborates Wi-CHAR’s robust performance, boasting accuracy rates of 89.7% and 92.5%, respectively. In summary, Wi-CHAR delivers recognition outcomes on par with state-of-the-art methodologies, meticulously tailored to accommodate specific sensing environments and data constraints.

Abstract Background and aims It is crucial to manage the recurrence of Crohn’s disease (CD). This study is aimed to explore whether visceral adipose tissue (VAT) and skeletal muscle (SM) are associated with the recurrence of CD upon different treatments. Methods All patients with a definite diagnosis of CD were retrospectively divided into three groups according to distinct treatment regimens: 5-amino salicylic acid group (Group A), steroids + azathioprine (Group B) and biologics (Group C). The pretreatment computerized tomography (CT) images and clinical data were collected. The VAT area, mesenteric fat index (MFI), the ratio of VAT area to fat mass (VAT area/FM) were assessed. The primary end point was the recurrence of CD within 1 year of follow-up. Results A total of 171 CD patients were enrolled, including 57 (33.33%) patients in Group A, 70 (40.94%) patients in Group B and 44 (25.73%) patients in Group C. Patients with 1-year recurrence had higher MFI (P = 0.011) and VAT area/FM (P = 0.000). ROC curve demonstrated that patients with the ratio of VAT area/FM and MFI higher than 0.578 and 1.394 tended to have recurrence with the AUC of 0.707 and 0.709. Similar results could be observed in Group A & B but not in Group C. Conclusions High VAT area/FM and MFI are related to recurrence within 1 year for newly diagnosed CD patients treated by 5-amino salicylic or azathioprine + steroids rather than biologics. We could not observe any radiological data associated with the recurrence of CD patients under biological treatment.

Xenobiotics can easily harm human lungs owing to the openness of the respiratory system. Identifying pulmonary toxicity remains challenging owing to several reasons: 1) no biomarkers for pulmonary toxicity are available that might help to detect lung injury; 2) traditional animal experiments are time-consuming; 3) traditional detection methods solely focus on poisoning accidents; 4) analytical chemistry methods hardly achieve universal detection. An in vitro testing system able to identify the pulmonary toxicity of contaminants from food, the environment, and drugs is urgently needed. Compounds are virtually infinite, whereas toxicological mechanisms are countable. Therefore, universal methods to identify and predict the risks of contaminants can be designed based on these well-known toxicity mechanisms. In this study, we established a dataset based on transcriptome sequencing of A549 cells upon treatment with different compounds. The representativeness of our dataset was analyzed using bioinformatics methods. Artificial intelligence methods, namely partial least squares discriminant analysis (PLS-DA) models, were employed for toxicity prediction and toxicant identification. The developed model predicted the pulmonary toxicity of compounds with a 92 % accuracy. These models were submitted to an external validation using highly heterogeneous compounds, which supported the accuracy and robustness of our developed methodology. This assay exhibits universal potential applications for water quality monitoring, crop pollution detection, food and drug safety evaluation, as well as chemical warfare agent detection.

Purpose: Vonoprazan (VPZ) produces a strong acid-inhibitory effect, which can potentially eradicate Helicobacter Pylori (H. pylori). We aimed to assess whether a 14-day VPZ-containing triple therapy was safe and effective in the Chinese population and the potential mechanism.Methods: Enrolled patients confirmed to be infected with H. pylori were randomly divided into four groups: VPZ + doxycycline + furazolidone, VPZ + doxycycline + amoxicillin, esomeprazole (EPZ) + bismuth + doxycycline + furazolidone, and EPZ + colloidal bismuth + doxycycline + amoxicillin for 14 days. The eradication rate, medication adherence, and incidence of adverse events (AEs) were evaluated. Inhibition of H. pylori by VPZ and EPZ in vitro was assessed. H. pylori treated with appropriate concentrations of VPZ and EPZ were sequenced by transcriptome analysis to explore the antibacterial mechanism.Results: A higher eradication rate were observed in VPZ-containing triple therapy. No obvious differences were observed in medication adherence or the incidence of AEs. VPZ had no direct inhibitory effect on H. pylori, whereas EPZ directly inhibited H. pylori may through downregulated genes related to the ribosome.Conclusion: In the Chinese population, 14-day VPZ-containing triple therapy was safe and more effective and can be used clinically as first-line H. pylori treatment.Clinical Trial Registration:ClinicalTrials.gov, identifier NCT05097846

Background: It remains unclear whether visceral adipose tissue (VAT) can predict the response of patients with Crohn’s disease (CD) to anti-tumour necrosis factor-α (anti-TNF-α) therapy. Objectives: This study aimed to investigate whether VAT predicts the efficacy of infliximab (IFX) for different sites of CD and its relationship with serum TNF-α levels and IFX serum trough concentration. Design: This is a multicentre retrospective study. Methods: Patients with CD treated with IFX from January 2014 to January 2021 were included. The perimeter of the visceral adipose area was obtained by a Computed Tomography (CT) scan. Participants were classified according to the lesion site (L 1 , L 2 , and L 3 ) and visceral fat area. The participants were divided into colon-uninvolved non-visceral obesity (L 1 -VAT L ), colon-uninvolved visceral obesity (L 1 -VAT H ), colon-involved non-visceral obesity (L 2 + L 3 -VAT L ), and colon involved visceral obesity (L 2 + L 3 -VAT H ) groups. The end points of this study were set as disease remission status at 6 and 12 months. Results: The final cohort included 140 patients. Regarding efficacy at 6 and 12 months, there was a significant difference between L 1 -VAT L (73.8% versus 36.8%, p = 0.006) and L 1 -VAT H (81.0% versus 47.4%, p = 0.008) groups. In the analysis of serum TNF-α levels and IFX serum trough concentrations, there was a significant difference between L 1 -VAT L and L 1 -VAT H (59.5 pg/mL versus 236.0 pg/mL, p TNF-α = 0.006), (10.0 μg/mL versus 0.4 μg/mL, p IFX = 0.000), and L 1 -VAT H and L 2 + L 3 -VAT H (78.7 pg/mL versus 118.6 pg/mL, p TNF-α = 0.031), (0.4 μg/mL versus 6.40 μg/mL, p IFX = 0.017). Conclusion: In L 1 patients, the VAT level predicted the efficacy of IFX, with high VAT values indicating poor efficacy. The VAT level may be a useful radiological marker to predict the efficacy of IFX in patients with various types of CD.

Inflammatory bowel disease (IBD) is an incurable digestive disease. Since patients have to live with it, improving patients’ quality of life is important. Caregiver’s positive feelings and closeness may have a positive effect on patients’ quality of life. We hypothesized that caregiver’s positive feeling affected patient’s quality of life through caregiver’s caring ability, and closeness might be the upstream of this chain. In this study, we conducted a single-center cross-sectional survey by questionnaire in China to tested the hypothesis. A total of 181 patient-caregiver pairs were included. The short version of the IBD questionnaire (SIBDQ), the twelve-item short-form health survey (SF-12), the positive aspects of caregiving (PAC) and Capacity Scale of caregivers were used to collect data. All the data were collected in one interview. Spearman correlation and Bootstrap method were used to analyze the data. Mediation analysis results indicated that caregiver’s caring ability mediated the association between caregiver’s positive feelings and patients’ quality of life (p < 0.01), which explained 34.1% of the total variation of patients’ quality of life. Mediation analysis results also revealed that patient-evaluated or caregiver-evaluated closeness had a positive effect on patients’ quality of life through caregiver’s positive feeling and caregiver’s caring ability (p < 0.05), which explained 2.1 and 2.3% of the variation of patients’ quality of life. Caregiver’s positive feelings were related to caregivers’ quality of life (p < 0.01), but there was no significant association between caregivers’ ability and caregivers’ quality of life. In summary, our model revealed that caregiver’s positive feeling affected patients’ quality of life through caregiver’s caring ability.

With the popularization of Wi-Fi router devices, the application of device-free sensing has garnered significant attention due to its potential to make our lives more convenient. Wi-Fi signal-based through-the-wall human detection offers practical applications, such as emergency rescue and elderly monitoring. However, the accuracy of through-the-wall human detection is hindered by signal attenuation caused by wall materials and multiple propagation paths of interference. Therefore, through-the-wall human detection presents a substantial challenge. In this paper, we proposed a highly robust through-the-wall human detection method based on a commercial Wi-Fi device (TwSense). To mitigate interference from wall materials and other environmental factors, we employed the robust principal component analysis (OR-PCA) method to extract the target signal of Channel State Information (CSI). Subsequently, we segmented the action-induced Doppler shift feature image using the K-means clustering method. The features of the images were extracted using the Histogram of Oriented Gradients (HOG) algorithm. Finally, these features were fed into an SVM classifier (G-SVM) optimized by a grid search algorithm for action classification and recognition, thereby enhancing human detection accuracy. We evaluated the robustness of the entire system. The experimental results demonstrated that TwSense achieved the highest accuracy of 96%.

BackgroundThe purpose of this paper is to develop and validate a standardized endoscopist acceptance scale for the implementation of artificial intelligence (AI) in gastrointestinal endoscopy.MethodsAfter investigating endoscopists who have previously used AI and consulting with AI experts, we developed a provisional scale to measure the acceptance of AI as used in gastrointestinal endoscopy that was then distributed to a sample of endoscopists who have used AI. After analyzing the feedback data collected on the provisional scale, we developed a new formal scale with four factors. Cronbach's alpha, confirmatory factor analysis (CFA), content validity, and related validity were conducted to test the reliability and validity of the formal scale. We also constructed a receiver operating characteristic (ROC) curve in order to determine the scale's ability to distinguish higher acceptance and satisfaction.ResultsA total of 210 valid formal scale data points were collected. The overall Cronbach's alpha was 0.904. All the factor loadings were >0.50, of which the highest factor loading was 0.86 and the lowest was 0.54 (AVE = 0.580, CR = 0.953). The correlation coefficient between the total score of the scale and the satisfaction score was 0.876, and the area under the ROC curve was 0.949 ± 0.031. Endoscopists with a score higher than 50 tend to be accepting and satisfied with AI.ConclusionThis study yielded a viable questionnaire to measure the acceptance among endoscopists of the implementation of AI in gastroenterology.

Objectives We aimed to construct a theoretical model and an observer-based measurement of shared decision making (SDM) in web-based pharmaceutical care consultation. Methods We first constructed a theoretical model through analysis of SDM models and interviews with 24 key informants. Then, the initial measurement was formulated, and the content was evaluated by 16 key informants alone. A cross-sectional study was executed, where 300 provider-patient encounters were collected at the online platform ‘Good Doctor Website’, for reliability and validity assessment. Content validity was evaluated by appropriateness score, that is the median of 7–9 and without disagreement. Interrater reliability was evaluated by Spearman correlation coefficient using 30 out of 300 samples. Single indicator validity was tested by Pearson correlation analysis, and convergent validity was evaluated by the Multiple Indicators Multiple Causes (MIMIC) model using 300 samples. Results Theoretical model constructed included four elements: ‘comprehensive understanding of the patient's condition’, ‘exchanging ideas on medication options’, ‘achieving a medication plan’, and ‘providing decision support’. Measurement constructed included four dimensions and 19 items, and four dimensions were in accordance with four elements of the theoretical model. We found median scores of these dimensions and items were 7–9 and without disagreement, indicating good content validity. Spearman correlation coefficients of 19 items were greater than 0.750, suggesting good interrater reliability. Pearson coefficients between 19 items and their external variables were significant ( p

Background Deliberate practice (DP) was proposed for effective clinical skill training, which highlights focused, repetitive practice and feedback as the key points for practice. Although previous studies have investigated the effect of feedback in DP, little is known about the proper repetitive cycles of clinical skills training especially in physical examination (PE) training. Methods We drew learning curves and designed a comparative study to find out the optimal number of hands-on practice cycles, an important aspect of DP, in abdominal PE training for medical students. A comparative study was conducted to validate the optimal number of hands-on practice by dividing students into two cohorts including Cohort A (high-frequency hand-on training) and B (low-frequency hand-on training). Results The learning curve study of 16 students exhibited a threshold of four repetitive practices when 81.25% students reached the competence score. A total of 74 students’ final exam scores were collected for analysis. Students in Cohort A (4–5 PEs) scored significantly higher than those in Cohort B (≤3 PEs) (84.41 ± 11.78 vs 76.83 ± 17.51] in the final exam (P = 0.030)). Conclusion High-frequency practice can improve students’ competence of abdominal PE skill. We recommend four cycles of hands-on practice for each student in a training course like PE training.

When implementing a pseudo-random number generator (PRNG) for neural network chaos-based systems on FPGAs, chaotic degradation caused by numerical accuracy constraints can have a dramatic impact on the performance of the PRNG. To suppress this degradation, a PRNG with a feedback controller based on a Hopfield neural network chaotic oscillator is proposed, in which a neuron is exposed to electromagnetic radiation. We choose the magnetic flux across the cell membrane of the neuron as a feedback condition of the feedback controller to disturb other neurons, thus avoiding periodicity. The proposed PRNG is modeled and simulated on Vivado 2018.3 software and implemented and synthesized by the FPGA device ZYNQ-XC7Z020 on Xilinx using Verilog HDL code. As the basic entropy source, the Hopfield neural network with one neuron exposed to electromagnetic radiation has been implemented on the FPGA using the high precision 32-bit Runge Kutta fourth-order method (RK4) algorithm from the IEEE 754-1985 floating point standard. The post-processing module consists of 32 registers and 15 XOR comparators. The binary data generated by the scheme was tested and analyzed using the NIST 800.22 statistical test suite. The results show that it has high security and randomness. Finally, an image encryption and decryption system based on PRNG is designed and implemented on FPGA. The feasibility of the system is proved by simulation and security analysis.

Abstract Background The overuse of antibiotics has been identified as a major challenge in regard to the rational prescription of medicines in low and middle income countries. Extensive studies on the effectiveness of persuasive interventions, such as guidelines have been undertaken. There is a dearth of research pertaining to the effects of restrictive interventions. This study aimed to evaluate the impacts of prescription restrictions in relation to types and administration routes of antibiotics on antibiotic procurement in primary care settings in China. Methods Data were drawn from the monthly procurement records of medicines for primary care institutions in Hubei province over a 31-month period from May 2011 to November 2013. We analyzed the monthly procurement volume and costs of antibiotics. Interrupted time series analyses with a difference-in-difference approach were performed to evaluate the effect of the restrictive intervention (started in August 2012) on antibiotic procurement in comparison with those for cardiovascular conditions. Sensitivity tests were performed by replacing outliers using a simple linear interpolation technique. Results Over the entire study period, antibiotics accounted for 33.65% of the total costs of medicines procured for primary care institutions: mostly non-restricted antibiotics (86.03%) and antibiotics administered through parenteral routes (79.59%). On average, 17.14 million defined daily doses (DDDs) of antibiotics were procured per month, with the majority (93.09%) for non-restricted antibiotics and over half (52.38%) for parenteral administered antibiotics. The restrictive intervention was associated with a decline in the secular trend of costs for non-restricted oral antibiotics (− 0.36 million Yuan per month, p = 0.029), and for parenteral administered restricted antibiotics (− 0.28 million Yuan per month, p = 0.019), as well as a decline in the secular trend of procurement volume for parenteral administered non-restricted antibiotics (− 0.038 million DDDs per month, p = 0.05). Conclusions Restrictive interventions are effective in reducing the procurement of antibiotics. However, the effect size is relatively small and antibiotic consumptions remain high, especially parenteral administered antibiotics.

Abstract Background Poor access to affordable insulin results in serious and needless complications and premature deaths for those with diabetes who need this essential medicine. To help address this issue, we assessed insulin availability, prices, affordability and price components in Hubei Province as China has the heaviest burden of diabetes globally. Methods In 2016, insulin availability and price data was collected in the capital and five other cities. A total of 30 public sector outlets (hospitals and primary care institutions) and 30 private pharmacies were sampled, using an adaptation of the World Health Organization/Health Action International methodology, Data was collected for all human and analogue insulins in stock, then analyzed by type (prandial, basal or pre-mixed) and duration of action. Prices were expressed as Median Price Ratios (MPRs) to Australian PBS prices. Price components were tracked for five insulin products in two cities.. Affordability was assessed as the number of days’ wages of the lowest paid unskilled government worker needed to purchase 10 ml 100 IU/ml (approximately 30 days’ supply). Results Mean availability was highest in public hospitals for prandial (70%), basal (80%) and pre-mixed insulin (90%). In primary care institutions and private pharmacies mean availability ranged from 10% to 33%. Median prices of all insulin types were higher that Australian PBS prices in all three sectors for human and analogue insulins (ranging from1.36–2.59 times). Patients have to pay 4 to 16 days’ wages to purchase a month’s treatment depending on the insulin type and sector. The largest component of the patient price was the manufacturers’ selling price (60%). Taxes in the form of import duties and VAT are applied in some sectors. Conclusions The availability of insulin in primary care institutions and private retail pharmacies was very low in Hubei. Only public hospitals had good insulin availability. Insulin prices were high in all sectors making this life-saving medicine unaffordable, especially for those on low incomes. Governments should consider using its bargaining power to reduce prices, abolish taxes on essential medicines such as insulin, and develop strategies for more equitable access to insulin.

In this paper, a multistable modified fourth-order autonomous Chua’s chaotic system is investigated. In addition to the dynamic characteristics of the third-order Chua’s chaotic system itself, what interests us is that this modified fourth-order autonomous Chua’s chaotic system has five different types of coexisting attractors: double-scroll, single band chaotic attractor, period-4 limit cycle, period-2 limit cycle, and period-1 limit cycle. Then, an inductorless modified fourth-order autonomous Chua’s chaotic circuit is proposed. The active elements as well as the synthetic inductor employed in this circuit are designed using second-generation current conveyors (CCIIs). The reason for using CCIIs is that they have high conversion rate and operation speed, which enable the circuit to work at a higher frequency range. The Multisim simulations confirm the theoretical estimates of the performance of the proposed circuit. Finally, using RK-4 numerical algorithm of VHDL 32-bit IQ-Math floating-point number format, the inductorless modified fourth-order autonomous Chua’s chaotic system is implemented on FPGA for the development of embedded engineering applications based on chaos. The system is simulated and synthesized on Virtex-6 FPGA chip. The maximum operating frequency of modified Chua’s chaotic oscillator based on FPGA is 180.180 MHz. This study demonstrates that the hardware-based multistable modified fourth-order autonomous Chua’s chaotic system is a very good source of entropy and can be applied to various embedded systems based on chaos, including secure communication, cryptography, and random number generator.

In this paper, we propose a method to design the pseudorandom number generator (PRNG) using three kinds of four-wing memristive hyperchaotic systems (FWMHSs) with different dimensions as multientropy sources. The principle of this method is to obtain pseudorandom numbers with good randomness by coupling XOR operation on the three kinds of FWMHSs with different dimensions. In order to prove its potential application in secure communication, the security of PRNG based on this scheme is analyzed from the perspective of cryptography. In addition, PRNG has passed the NIST 800.22 and ENT test, which shows that PRNG has good statistical characteristics. Finally, an image encryption algorithm based on PRNG is adopted. In the encryption algorithm, the optimized Arnold matrix scrambling method and the diffusion processing based on XOR are used to obtain the final encrypted image. Through the evaluation of encryption performance, it is concluded that there is no direct relationship between the pristine image and encrypted image. The results show that the proposed image encryption scheme has good statistical output characteristics and security performance in line with cryptography.

By introducing a flux-controlled memristor model with absolute value function, a 5D multistable four-wing memristive hyperchaotic system (FWMHS) with linear equilibrium points is proposed in this paper. The dynamic characteristics of the system are studied in terms of equilibrium point, perpetual point, bifurcation diagram, Lyapunov exponential spectrum, phase portraits, and spectral entropy. This system is of the group of systems that have coexisting attractors. In addition, the circuit implementation scheme is also proposed. Then, a secure communication scheme based on the proposed 5D multistable FWMHS with disturbance inputs is designed. Based on parametric modulation theory and Lyapunov stability theory, synchronization and secure communication between the transmitter and receiver are realized and two message signals are recovered by a convenient robust high-order sliding mode adaptive controller. Through the proposed adaptive controller, the unknown parameters can be identified accurately, the gain of the receiver system can be adjusted continuously, and the disturbance inputs of the transmitter and receiver can be suppressed effectively. Thereafter, the convergence of the proposed scheme is proven by means of an appropriate Lyapunov functional and the effectiveness of the theoretical results is testified via numerical simulations.

In this work, a novel 6D four-wing hyperchaotic system with a line equilibrium based on a flux-controlled memristor model is proposed. The novel system is inspired from an existing 5D four-wing hyperchaotic system introduced by Zarei (2015). Fundamental properties of the novel system are discussed, and its complex behaviors are characterized using phase portraits, Lyapunov exponential spectrum, bifurcation diagram, and spectral entropy. When a suitable set of parameters are chosen, the system exhibits a rich repertoire of dynamic behaviors including double-period bifurcation of the quasiperiod, a single two-wing, and four-wing chaotic attractors. Further analysis of the novel system shows that the multiple coexisting attractors can be observed with different system parameter values and initial values. Moreover, the feasibility of the proposed mathematical model is also presented by using Multisim simulations based on an electronic analog of the model. Finally, the active control method is used to design the appropriate controller to realize the synchronization between the proposed 6D memristive hyperchaotic system and the 6D hyperchaotic Yang system with different structures. The Routh–Hurwitz criterion is used to prove the rationality of the controller, and the feasibility and effectiveness of the proposed synchronization method are proved by numerical simulations.