Towards universal health coverage: achievements and challenges of 10 years of healthcare reform in China.

Universal health coverage (UHC) has been identified as a priority for the global health agenda. In 2009, the Chinese government launched a new round of healthcare reform towards UHC, aiming to provide universal coverage of basic healthcare by the end of 2020. We conducted a secondary data analysis and combined it with a literature review, analysing the overview of UHC in China with regard to financial protection, coverage of health services and the reported coverage of the WHO and the World Bank UHC indicators. The results include the following: out-of-pocket expenditures as a percentage of current health expenditures in China have dropped dramatically from 60.13% in 2000 to 35.91% in 2016; the health insurance coverage of the total population jumped from 22.1% in 2003 to 95.1% in 2013; the average life expectancy increased from 72.0 to 76.4, maternal mortality dropped from 59 to 29 per 100 000 live births, the under-5 mortality rate dropped from 36.8 to 9.3 per 1000 live births, and neonatal mortality dropped from 21.4 to 4.7 per 1000 live births between 2000 and 2017; and so on. Our findings show that while China appears to be well on the path to UHC, there are identifiable gaps in service quality and a requirement for ongoing strengthening of financial protections. Some of the key challenges remain to be faced, such as the fragmented and inequitable health delivery system, and the increasing demand for high-quality and value-based service delivery. Given that China has committed to achieving UHC and 'Healthy China 2030', the evidence from this study can be suggestive of furthering on in the UHC journey and taking the policy steps necessary to secure change

Rationale-Enhanced Language Models are Better Continual Relation Learners

Continual relation extraction (CRE) aims to solve the problem of catastrophic forgetting when learning a sequence of newly emerging relations. Recent CRE studies have found that catastrophic forgetting arises from the model's lack of robustness against future analogous relations. To address the issue, we introduce rationale, i.e., the explanations of relation classification results generated by large language models (LLM), into CRE task. Specifically, we design the multi-task rationale tuning strategy to help the model learn current relations robustly. We also conduct contrastive rationale replay to further distinguish analogous relations. Experimental results on two standard benchmarks demonstrate that our method outperforms the state-of-the-art CRE models.Comment: Accepted at EMNLP 202

Mutation of a TADR protein leads to rhodopsin and Gq-dependent retinal degeneration in Drosophila

The Drosophila photoreceptor is a model system for genetic study of retinal degeneration. Many gene mutations cause fly photoreceptor degeneration, either because of excessive stimulation of the visual transduction (phototransduction) cascade, or through apoptotic pathways that in many cases involve a visual arrestin Arr2. Here we report a gene named tadr (for torn and diminished rhabdomeres), which, when mutated, leads to photoreceptor degeneration through a different mechanism. Degeneration in the tadr mutant is characterized by shrunk and disrupted rhabdomeres, the light sensory organelles of photoreceptor. The TADR protein interacted in vitro with the major light receptor Rh1 rhodopsin, and genetic reduction of the Rh1 level suppressed the tadr mutation-caused degeneration, suggesting the degeneration is Rh1-dependent. Nonetheless, removal of phospholipase C (PLC), a key enzyme in phototransduction, and that of Arr2 failed to inhibit rhabdomeral degeneration in the tadr mutant background. Biochemical analyses revealed that, in the tadr mutant, the G(q) protein of Rh1 is defective in dissociation from the membrane during light stimulation. Importantly, reduction of G(q) level by introducing a hypomorphic allele of G(alphaq) gene greatly inhibited the tadr degeneration phenotype. These results may suggest that loss of a potential TADR-Rh1 interaction leads to an abnormality in the G(q) signaling, which in turn triggers rhabdomeral degeneration independent of the PLC phototransduction cascade. We propose that TADR-like proteins may also protect photoreceptors from degeneration in mammals including humans

Enhancing Virtual Distillation with Circuit Cutting for Quantum Error Mitigation

Virtual distillation is a technique that aims to mitigate errors in noisy quantum computers. It works by preparing multiple copies of a noisy quantum state, bridging them through a circuit, and conducting measurements. As the number of copies increases, this process allows for the estimation of the expectation value with respect to a state that approaches the ideal pure state rapidly. However, virtual distillation faces a challenge in realistic scenarios: preparing multiple copies of a quantum state and bridging them through a circuit in a noisy quantum computer will significantly increase the circuit size and introduce excessive noise, which will degrade the performance of virtual distillation. To overcome this challenge, we propose an error mitigation strategy that uses circuit-cutting technology to cut the entire circuit into fragments. With this approach, the fragments responsible for generating the noisy quantum state can be executed on a noisy quantum device, while the remaining fragments are efficiently simulated on a noiseless classical simulator. By running each fragment circuit separately on quantum and classical devices and recombining their results, we can reduce the noise accumulation and enhance the effectiveness of the virtual distillation technique. Our strategy has good scalability in terms of both runtime and computational resources. We demonstrate our strategy's effectiveness through noisy simulation and experiments on a real quantum device.Comment: 8 pages, 5 figure

Towards Usable Parental Control for Voice Assistants

Voice Personal Assistants (VPA) have become a common household appliance. As one of the leading platforms for VPA technology, Amazon created Alexa and designed Amazon Kids for children to safely enjoy the rich functionalities of VPA and for parents to monitor their kids' activities through the Parent Dashboard. Although this ecosystem is in place, the usage of Parent Dashboard is not yet popularized among parents. In this paper, we conduct a parent survey to find out what they like and dislike about the current parental control features. We find that parents need more visuals about their children's activity, easier access to security features for their children, and a better user interface. Based on the insights from our survey, we present a new design for the Parent Dashboard considering the parents' expectations

Development of a new stroke scale in an emergency setting

Background: Early identification of stroke is crucial to maximize early management benefits in emergency departments. This study aimed to develop and validate a new stroke recognition instrument for differentiating acute stroke from stroke mimics in an emergency setting. Methods: A prospective observational cohort study among suspected stroke patients presenting to Emergency Department in the Second Affiliated Hospital of Guangzhou Medical University was conducted from May 2012 to March 2013. The symptoms and signs of suspected stroke patients were collected. Logistic regression analysis was used to identify the factors associated with acute stroke. The symptoms and signs closely associated with acute stroke were selected to develop the new stroke scale, Guangzhou Stroke Scale (GZSS). The diagnostic value of GZSS was then compared with ROSIER, FAST and LAPSS. The primary outcome was confirmed stroke by CT within 24 h. Results: Four hundred and sixteen suspected stroke patients (247 ischemia, 107 hemorrhage, 4 transient ischemic attack, 58 non-stroke) were assessed. A new stroke scale, GZSS (total score from −1 to 8.5), was developed and consisted of nine parameters: vertigo (−1), GCS ≤ 8 (+2), facial paralysis (+1), asymmetric arm weakness (+1), asymmetric leg weakness (+1), speech disturbance (+0.5), visual field defect (+1), systolic blood pressure ≥145 mmHg (+1) and diastolic blood pressure ≥95 mmHg (+1). Among the four scales, the discriminatory value (C-statistic) of GZSS was the best (AUC: 0.871 (p < 0.001) when compared to ROSIER (0.772), LAPSS (0.722) and FAST (0.699). At an optimal cut-off score of >1.5 on a scale from −1 to 8.5, the sensitivity and specificity of GZSS were 83.2 and 74.1 %, whilst the sensitivities and specificities of ROSIER were 77.7 and 70.7 %, FAST were 76.0 and 63.8 %, LAPSS were 56.4 and 87.9 %. Conclusion: GZSS had better sensitivity than existing stroke scales in Chinese patients with suspected stroke. Further studies should be conducted to confirm its effectiveness in the initial differentiation of acute stroke from stroke mimics. Keywords: Diagnosis, Stroke, Stroke mimics, ROSIER scale, FAST scale, LAPSS scale, Emergency department, China Abbreviations: AUC, area under the ROC curve; CT, computed tomography; DWI, diffusion weighted imaging; FAST, the face arm speech test; GCS, Glasgow Coma Scale; IQR, inter quartile range; LAPSS, the Los Angeles Prehospital Stroke Screen; MRI, magnetic resonance imaging; NIHSS, National Institute of Health stroke scale; OR, odds ratio; ROC, receiver operating characteristic; ROSIER, the Recognition of Stroke in the Emergency Room scale; TIA, transient ischemic attac

Learning Robust Representations for Continual Relation Extraction via Adversarial Class Augmentation

Continual relation extraction (CRE) aims to continually learn new relations from a class-incremental data stream. CRE model usually suffers from catastrophic forgetting problem, i.e., the performance of old relations seriously degrades when the model learns new relations. Most previous work attributes catastrophic forgetting to the corruption of the learned representations as new relations come, with an implicit assumption that the CRE models have adequately learned the old relations. In this paper, through empirical studies we argue that this assumption may not hold, and an important reason for catastrophic forgetting is that the learned representations do not have good robustness against the appearance of analogous relations in the subsequent learning process. To address this issue, we encourage the model to learn more precise and robust representations through a simple yet effective adversarial class augmentation mechanism (ACA), which is easy to implement and model-agnostic. Experimental results show that ACA can consistently improve the performance of state-of-the-art CRE models on two popular benchmarks.Comment: Accepted by EMNLP 202

InfoCL: Alleviating Catastrophic Forgetting in Continual Text Classification from An Information Theoretic Perspective

Continual learning (CL) aims to constantly learn new knowledge over time while avoiding catastrophic forgetting on old tasks. We focus on continual text classification under the class-incremental setting. Recent CL studies have identified the severe performance decrease on analogous classes as a key factor for catastrophic forgetting. In this paper, through an in-depth exploration of the representation learning process in CL, we discover that the compression effect of the information bottleneck leads to confusion on analogous classes. To enable the model learn more sufficient representations, we propose a novel replay-based continual text classification method, InfoCL. Our approach utilizes fast-slow and current-past contrastive learning to perform mutual information maximization and better recover the previously learned representations. In addition, InfoCL incorporates an adversarial memory augmentation strategy to alleviate the overfitting problem of replay. Experimental results demonstrate that InfoCL effectively mitigates forgetting and achieves state-of-the-art performance on three text classification tasks. The code is publicly available at https://github.com/Yifan-Song793/InfoCL.Comment: Findings of EMNLP 2023. An improved version of arXiv:2305.0728

STEMI outcomes in Guangzhou and Hong Kong: two-centre retrospective interregional study

BACKGROUND AND OBJECTIVES:Healthcare systems are organized very differently in Hong Kong (HK) and Guangzhou (GZ). This study compared managements of the emergency departments (ED) and one-year mortalities of ST-segment elevation myocardial infarction (STEMI) patients in two teaching hospitals in Guangzhou and Hong Kong. METHODS:Retrospective observational study of STEMI mortalities and treatments in the Prince of Wales Hospital (PWH) and the Second Affiliated Hospital of Guangzhou Medical University (AHGZMU), was conducted between January and December 2010. The primary outcome was one-year all cause mortality. RESULTS:Univariate analysis of 76 cases from PWH and 111 cases from AHGZMU showed similar clinical characteristics, except for lower proportions of males (74% vs 92%, P = 0.002), hyperlipidemia (5% vs 25%, P67 years) and hyperglycemia (>10 mmol/L). Aged over 65 years, presence of anterior wall infarct, body weight ≤65 kg, SBP 10 mmol/L were the independent predictors of in-hospital MACE. CONCLUSION:There was no statistically significant difference between the standardized one-year all-cause mortalities of STEMI patients in the setting mainly using thrombolysis with shorter door-to-treatment time and the setting mainly using PCI with longer door-to-treatment time. Aged over 67 years and glucose level over 10 mmol/L were the independent predictors of one-year mortality. Older age, presence of anterior wall infarct, lower body weight, lower SBP at ED and hyperglycemia were the independent predictors of in-hospital MACE