FACS-based genome-wide CRISPR screens define key regulators of DNA damage signaling pathways.

DNA damage-activated signaling pathways are critical for coordinating multiple cellular processes, which must be tightly regulated to maintain genome stability. To provide a comprehensive and unbiased perspective of DNA damage response (DDR) signaling pathways, we performed 30 fluorescence-activated cell sorting (FACS)-based genome-wide CRISPR screens in human cell lines with antibodies recognizing distinct endogenous DNA damage signaling proteins to identify critical regulators involved in DDR. We discovered that proteasome-mediated processing is an early and prerequisite event for cells to trigger camptothecin- and etoposide-induced DDR signaling. Furthermore, we identified PRMT1 and PRMT5 as modulators that regulate ATM protein level. Moreover, we discovered that GNB1L is a key regulator of DDR signaling via its role as a co-chaperone specifically regulating PIKK proteins. Collectively, these screens offer a rich resource for further investigation of DDR, which may provide insight into strategies of targeting these DDR pathways to improve therapeutic outcomes.

In vivo CRISPR screens identify Mga as an immunotherapy target in triple-negative breast cancer.

Immune evasion is not only critical for tumor initiation and progression, but also determines the efficacy of immunotherapies. Through iterative in vivo CRISPR screens with seven syngeneic tumor models, we identified core and context-dependent immune evasion pathways across cancer types. This valuable high-confidence dataset is available for the further understanding of tumor intrinsic immunomodulators, which may lead to the discovery of effective anticancer therapeutic targets. With a focus on triple-negative breast cancer (TNBC), we found that Mga knock-out significantly enhances antitumor immunity and inhibits tumor growth. Transcriptomics and single-cell RNA sequencing analyses revealed that Mga influences various immune-related pathways in the tumor microenvironment. Our findings suggest that Mga may play a role in modulating the tumor immune landscape, though the precise mechanisms require further investigation. Interestingly, we observed that low MGA expression in breast cancer patients correlates with a favorable prognosis, particularly in those with active interferon-γ signaling. These observations provide insights into tumor immune escape mechanisms and suggest that further exploration of MGA's function could potentially lead to effective therapeutic strategies in TNBC.

Generating synthetic population for simulating the spatiotemporal dynamics of epidemics.

Agent-based models have gained traction in exploring the intricate processes governing the spread of infectious diseases, particularly due to their proficiency in capturing nonlinear interaction dynamics. The fidelity of agent-based models in replicating real-world epidemic scenarios hinges on the accurate portrayal of both population-wide and individual-level interactions. In situations where comprehensive population data are lacking, synthetic populations serve as a vital input to agent-based models, approximating real-world demographic structures. While some current population synthesizers consider the structural relationships among agents from the same household, there remains room for refinement in this domain, which could potentially introduce biases in subsequent disease transmission simulations. In response, this study unveils a novel methodology for generating synthetic populations tailored for infectious disease transmission simulations. By integrating insights from microsample-derived household structures, we employ a heuristic combinatorial optimizer to recalibrate these structures, subsequently yielding synthetic populations that faithfully represent agent structural relationships. Implementing this technique, we successfully generated a spatially-explicit synthetic population encompassing over 17 million agents for Shenzhen, China. The findings affirm the method's efficacy in delineating the inherent statistical structural relationship patterns, aligning well with demographic benchmarks at both city and subzone tiers. Moreover, when assessed against a stochastic agent-based Susceptible-Exposed-Infectious-Recovered model, our results pinpointed that variations in population synthesizers can notably alter epidemic projections, influencing both the peak incidence rate and its onset.

Integrated screens uncover a cell surface tumor suppressor gene KIRREL involved in Hippo pathway.

Cell surface proteins play essential roles in various biological processes and are highly related to cancer development. They also serve as important markers for cell identity and targets for pharmacological intervention. Despite their great potentials in biomedical research, comprehensive functional analysis of cell surface proteins remains scarce. Here, with a de novo designed library targeting cell surface proteins, we performed in vivo CRISPR screens to evaluate the effects of cell surface proteins on tumor survival and proliferation. We found that Kirrel1 loss markedly promoted tumor growth in vivo. Moreover, KIRREL was significantly enriched in a separate CRISPR screen based on a specific Hippo pathway reporter. Further studies revealed that KIRREL binds directly to SAV1 to activate the Hippo tumor suppressor pathway. Together, our integrated screens reveal a cell surface tumor suppressor involved in the Hippo pathway and highlight the potential of these approaches in biomedical research.

Artificial intelligence in myopia in children: current trends and future directions.

PURPOSE OF REVIEW: Myopia is one of the major causes of visual impairment globally, with myopia and its complications thus placing a heavy healthcare and economic burden. With most cases of myopia developing during childhood, interventions to slow myopia progression are most effective when implemented early. To address this public health challenge, artificial intelligence has emerged as a potential solution in childhood myopia management. RECENT FINDINGS: The bulk of artificial intelligence research in childhood myopia was previously focused on traditional machine learning models for the identification of children at high risk for myopia progression. Recently, there has been a surge of literature with larger datasets, more computational power, and more complex computation models, leveraging artificial intelligence for novel approaches including large-scale myopia screening using big data, multimodal data, and advancing imaging technology for myopia progression, and deep learning models for precision treatment. SUMMARY: Artificial intelligence holds significant promise in transforming the field of childhood myopia management. Novel artificial intelligence modalities including automated machine learning, large language models, and federated learning could play an important role in the future by delivering precision medicine, improving health literacy, and allowing the preservation of data privacy. However, along with these advancements in technology come practical challenges including regulation and clinical integration.

Corydecusines A-H, new phthalideisoquinoline hemicetal alkaloids from the bulbs of Corydalis decumbens inhibit Tau pathology by activating autophagy mediated by AMPK-ULK1 pathway.

Twelve phthalideisoquinoline hemiacetal alkaloids including eight new ones (1-8) and one natural alkaloid characterized by an aziridine moiety with unassigned NMR data (9), were isolated and identified from the bulbs of Corydalis decumbens. Their structures were established by comprehensive analyses of HRESIMS, NMR, X-ray crystallography, and ECD analyses. The unambiguously established structures of the phthalideisoquinoline hemiacetal alkaloids indicated that the absolute configurations of C-1, C-9, and C-7' were confusable only relied on coupling constants. A summary of their ECD spectra was concluded and provided an insight for C-1, C-9, and C-7' absolute configuration assignment. These new compounds were evaluated to induce autophagy flux through flow cytometry analysis. Moreover, compounds 2 and 6 could significantly induce autophagy and inhibit Tau pathology by AMPK-ULK1 pathway activation, which provided an avenue for anti-AD lead compounds discovery.

Enhancing equity in cervical screening - initiatives to increase screening participation.

PURPOSE OF REVIEW: Cervical cancer can be eliminated as a public health problem through a three-pillar approach including high coverage of human papillomavirus (HPV) vaccination and HPV-based cervical screening, and treatment of precancers and invasive cancers. However, access inequities prevent many women and people with a cervix benefitting from these life-saving advances. This review focuses on evidence-based interventions that can improve equity and scale-up of cervical screening. RECENT FINDINGS: The transition from conventional cytology to HPV screening provides multiple opportunities to address equity and a multipronged approach can be used to identify priority groups, understand barriers and develop tailored solutions. There are proven financing mechanisms, tools, technologies and screening delivery methods to overcome screening barriers in different settings. This includes self-sampling interventions, point-of-care testing, health service integration, consumer-led co-design processes and digital screening registries. SUMMARY: To achieve cervical cancer elimination globally, cervical screening must be delivered in an inclusive, culturally safe and context-appropriate manner. There are multiple tools and strategies that can be implemented to improve participation of never- and under-screened groups, and to enhance equity in cervical screening.

Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites.

BACKGROUND: Diabetic kidney disease (DKD) and diabetic retinopathy (DR) are major diabetic microvascular complications, contributing significantly to morbidity, disability, and mortality worldwide. The kidney and the eye, having similar microvascular structures and physiological and pathogenic features, may experience similar metabolic changes in diabetes. OBJECTIVE: This study aimed to use machine learning (ML) methods integrated with metabolic data to identify biomarkers associated with DKD and DR in a multiethnic Asian population with diabetes, as well as to improve the performance of DKD and DR detection models beyond traditional risk factors. METHODS: We used ML algorithms (logistic regression [LR] with Least Absolute Shrinkage and Selection Operator and gradient-boosting decision tree) to analyze 2772 adults with diabetes from the Singapore Epidemiology of Eye Diseases study, a population-based cross-sectional study conducted in Singapore (2004-2011). From 220 circulating metabolites and 19 risk factors, we selected the most important variables associated with DKD (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2) and DR (defined as an Early Treatment Diabetic Retinopathy Study severity level ≥20). DKD and DR detection models were developed based on the variable selection results and externally validated on a sample of 5843 participants with diabetes from the UK biobank (2007-2010). Machine-learned model performance (area under the receiver operating characteristic curve [AUC] with 95% CI, sensitivity, and specificity) was compared to that of traditional LR adjusted for age, sex, diabetes duration, hemoglobin A1c, systolic blood pressure, and BMI. RESULTS: Singapore Epidemiology of Eye Diseases participants had a median age of 61.7 (IQR 53.5-69.4) years, with 49.1% (1361/2772) being women, 20.2% (555/2753) having DKD, and 25.4% (685/2693) having DR. UK biobank participants had a median age of 61.0 (IQR 55.0-65.0) years, with 35.8% (2090/5843) being women, 6.7% (374/5570) having DKD, and 6.1% (355/5843) having DR. The ML algorithms identified diabetes duration, insulin usage, age, and tyrosine as the most important factors of both DKD and DR. DKD was additionally associated with cardiovascular disease history, antihypertensive medication use, and 3 metabolites (lactate, citrate, and cholesterol esters to total lipids ratio in intermediate-density lipoprotein), while DR was additionally associated with hemoglobin A1c, blood glucose, pulse pressure, and alanine. Machine-learned models for DKD and DR detection outperformed traditional LR models in both internal (AUC 0.838 vs 0.743 for DKD and 0.790 vs 0.764 for DR) and external validation (AUC 0.791 vs 0.691 for DKD and 0.778 vs 0.760 for DR). CONCLUSIONS: This study highlighted diabetes duration, insulin usage, age, and circulating tyrosine as important factors in detecting DKD and DR. The integration of ML with biomedical big data enables biomarker discovery and improves disease detection beyond traditional risk factors.

The AOFOG recommendations on human papillomavirus vaccination in the Asia-Pacific region.

Cervical cancer remains a disease burden in Asia. The Asia and Oceania Federation of Obstetrics and Gynecology envisages a need to produce a set of recommendations on the implementation of human papilloma virus vaccination program for both lower-middle-income countries (LMICs) and high-income countries (HICs), with an attempt to harmonize the practices yet allow flexibility to cater for different cultures, religions, needs and background of individual countries/cities. International guidelines and literature were sought, and recommendations were made in seven selected areas, including (i) the target groups for vaccination, (ii) the doses of vaccination including the use of single-dose vaccination, (iii) the types of vaccines, (iv) suggestions for special populations including those with previous HPV infection, human immunodeficiency virus carriers, and lesbian, gay, bisexual, transgender, questioning/queer group, (v) inter-changeability and the need of revaccination/booster, (vi) novel technologies and vaccines, and (vii) public education.

Improvement in Swallowing Function in Patients with Previous Irradiation for Nasopharyngeal Carcinoma by Expiratory Muscle Strength Training.

Dysphagia and chronic aspiration are common post-irradiation complications in nasopharyngeal carcinoma (NPC) survivors. Expiratory Muscle Strength Training (EMST) is a simple device-driven exercise therapy for swallowing training. This study investigates the effectiveness of EMST in a group of post-irradiated NPC patients. This prospective cohort, including twelve patients with previous irradiation for NPC and with swallowing disturbance, was performed between 2019 and 2021 in a single institution. Patients were trained with EMST for 8 weeks. Non-parametric analyses examined effects of EMST on primary outcome, maximum expiratory pressure. Secondary outcomes were measured with Penetration-aspiration scale, Yale pharyngeal residue severity rating scale (YPRSRS) by flexible endoscopic evaluation of swallowing, and Eating Assessment Tool (EAT-10) and M.D. Anderson Dysphagia Inventory questionnaire. Twelve patients, with a mean (SD) age of 64.3 (8.2) were recruited. There was no patient dropout with 88.9% overall compliance of training. Maximum expiratory pressure improved by 41% (median 94.5 to 133.5 cmH2O, p = 0.003). There was reduction in Penetration-aspiration scale with thin liquid (median 4 to 3, p = 0.026), and in YPRSRS at pyriform fossa with mildly thick liquid (p = 0.021) and at vallecula with thin liquid (p = 0.034), mildly thick liquid (p = 0.014) and pureed meat congee (p = 0.016). Questionnaire scores did not significantly change statistically. EMST is an easy-to-use and effective exercise therapy to improve airway safety and swallowing function in post-irradiated NPC survivors.

MOFs@POMs-derived bimetallic oxide Fe2(MoO4)3 nanoparticles for sensitive colorimetric detection of salicylic acid in aspirin.

A colorimetric sensing method for salicylic acid (SA) was developed by designing and fabricating bimetallic oxide nanozymes. Firstly, by calcinating MIL-100(Fe)@PMo12 (MOFs@POMs) at different temperature, Fe2(MoO4)3-Ts (T = 400℃, 500℃, 600℃, 700℃) nanoparticles (NPs) were successfully prepared. Secondly, by evaluating the peroxidase-like activities, Fe2(MoO4)3-600 NPs shows the best peroxidase-like activity attributed to the Fenton-like effect and the synergistic coupling interaction between Mo and Fe. Finally, based on the specific complexation between SA and Fe3+, a sensitive colorimetric sensor for SA was established, which exhibits superior selectivity and interference with a detection limit of 0.11 µM and a linear range of 10 to 100 µM, the lowest LOD for SA to date, to the best of our knowledge.

Effectiveness of group cognitive behavioral therapy for depression in adults: a systematic review and meta-analysis of delivery by different healthcare professionals.

This study addresses the gap in understanding the varied effectiveness of group cognitive behavioral therapy (gCBT) delivered by different professionals. This study aims to address this gap by conducting a systematic review of randomized controlled trials (RCTs) that evaluate gCBT and compare it to inactive controls in adults with a clinical diagnosis of depression. A total of 33 RCTs were included for analysis. In the overall analysis, 'profession of gCBT deliverer' was not a significant moderator in the meta-regression model (p = 0.57). For people without comorbidity, the overall effect size estimate was -0.69 (95% CI, -1.01. to -0.37, p = 0.03). Among gCBT deliverers, psychologists and nurses/psychiatric nurses demonstrated significant effectiveness, with psychologists showing a large effect size of -0.78 (95% CI, -1.25 to -0.30, p < 0.01) and nurses/psychiatric nurses showing a medium effect size of -0.45 (95% CI, -0.85 to -0.05, p = 0.03). The certainty of evidence for both professionals was moderate. These results have significant implications for the delivery of mental healthcare, as nurses/psychiatric nurses may be more accessible and cost-effective than psychologists in some settings. However, further research is necessary to determine the effectiveness of gCBT delivered by a broader range of healthcare professionals for patients with depression and other comorbidities.

Clinical and histological features of patients with chronic hepatitis B virus infection in the grey zone.

Chronic HBV infection patients who do not conform to any of the usual immune states are regarded as 'grey zone' patients. We aimed to investigate the proportion of chronic HBV infection patients in the grey zone, and evaluate the clinical characteristics and liver pathological changes in grey zone patients. Clinical data of 1391 treatment-naive chronic HBV infection patients with liver biopsy were collected. Natural history of HBV infection was determined based on European Association for the Study of the Liver (EASL) 2017, American Association for the Study of Liver Diseases (AASLD) 2018 and Chinese 2019 guidelines for the prevention and treatment of chronic HBV infection. Significant liver histological changes and associated risk factors of normal ALT grey zone patients were analysed. According to EASL, AASLD and Chinese criteria, there were 50.0%, 28% and 37.4% chronic HBV infection patients in the grey zone. Among the 353 grey zone patients with normal ALT, 72.4% had significant liver histological changes. ALT (optimal cut-off value 25 IU/L) and HBV DNA (optimal cut-off value 18,000 IU/mL) were independent risk factors of significant liver histological abnormalities. In conclusion, a substantial proportion of grey zone patients with normal ALT have significant liver histological changes that can be predicted by levels of serum ALT and HBV DNA. These results provide guidance of antiviral treatment in grey zone patients.

Effectiveness of enhancing contact model on reducing family caregiving burden and improving psychological wellbeing among caregivers of persons with schizophrenia in rural China.

BACKGROUND: It is unclear whether the enhancing contact model (ECM) intervention is effective in reducing family caregiving burden and improving hope and quality of life (QOL) among family caregivers of persons with schizophrenia (FCPWS). METHODS: We conducted a cluster randomized controlled trial in FCPWS in eight rural townships in Xinjin, Chengdu, China. In total, 253 FCPWS were randomly allocated to the ECM, psychoeducational family intervention (PFI), or treatment as usual (TAU) group. FCPWS in three groups were assessed caregiving burden, QOL and state of hope at baseline (T0), post-intervention (T1), 3-month (T2), and 9-month (T3) follow-up, respectively. RESULTS: Compared with participants in the TAU group, participants in the ECM group had statistically significantly lower caregiving burden scores both at T1 and T2 (p = 0.0059 and 0.0257, respectively). Compared with participants in the TAU group, participants in the PFI group had statistically significantly higher QOL scores in T1 (p = 0.0406), while participants in the ECM group had statistically significantly higher QOL scores in T3 (p = 0.0240). Participants in both ECM and PFI groups had statistically significantly higher hope scores than those in the TAU group at T1 (p = 0.0160 and 0.0486, respectively). CONCLUSIONS: This is the first study to explore the effectiveness of ECM on reducing family caregiving burden and improving hope and QOL in rural China. The results indicate the ECM intervention, a comprehensive and multifaceted intervention, is more effective than the PFI in various aspects of mental wellbeing among FCPWS. Future research needs to confirm ECM's effectiveness in various population.

Postoperative vasoplegia in lung transplantation: incidence and relation to outcome in a single-centre retrospective study.

BACKGROUND: The incidence and clinical importance of vasoplegia after lung transplantation remains poorly studied. We describe the incidence of vasoplegia and its association with complications after lung transplantation. METHODS: Perioperative data of 279 lung transplant recipients operated on from 2015 to 2020 in a UK hospital were analysed retrospectively. RESULTS: Vasoplegia occurred in 41.6% of patients after lung transplantation (mild, 31.0%; moderate, 55.2%; severe, 13.8%). Compared with non-vasoplegic patients, vasoplegic patients had a higher incidence of any acute kidney injury, defined by Kidney Disease Improving Global Outcomes (KDIGO) criteria (78.5% vs 65%, P=0.015), renal replacement therapy (47.4% vs 24.5%, P<0.001), and delayed chest closure (18.4% vs 9.2%, P=0.025); were ventilated longer (70 [32-368] vs 34 [19-105] h, P<0.001); and stayed longer in the ICU (12.9 [5-30] vs 6.8 [3-20] days, P<0.001). Mortality at 30 days and 1 yr was higher in patients with vasoplegia (11.2% vs 5.5% and 20.7% vs 11.7%, P=0.039, respectively). Severe vasoplegia represented a predictor of longer-term mortality (hazard ratio=1.65, P=0.008). Underlying infectious disease, increased BMI, higher preoperative pulmonary artery systolic pressure and bilirubin levels, lower glomerular filtration rate, and increased fresh frozen plasma transfusion were predictors of vasoplegia severity. Neutrophilia, leucocytosis, and increased C-reactive protein were associated with vasoplegia, but release of the neutrophil activation markers myeloperoxidase and heparin-binding protein was similar between groups. CONCLUSIONS: Influenced by preoperative status as well as procedural factors and inflammatory response, vasoplegia is a common and critical condition after lung transplantation with worse short-term outcomes and long-term survival.

Arachidonic acid impairs the function of the blood-testis barrier via triggering mitochondrial complex-ROS-P38 MAPK axis in hyperthermal Sertoli cells.

The death of Sertoli cells (SCs) under condition of heat stress (HS) affects spermatogenesis and is associated with impaired function of the blood-testis barrier (BTB). The fatty acid arachidonic acid (AA) is essential for the maintenance of cellular function. However, excessive release of AA during HS may adversely affect the reproductive function. The molecular mechanisms through which AA modulates the BTB in SCs are unclear. In this study, we found that 100 µM AA damaged testicular morphology and accelerated SC apoptosis during HS, reducing the stability of tight junction proteins (TJPs), shown by measurement of the levels of Claudin 11, 5, Occludin, and trans-epithelial electrical resistance (TEER). It was also found that AA adversely affected TJPs by increasing the accumulation of reactive oxygen species (ROS) and malondialdehyde (MDA), activating p38 mitogen-activated protein kinases (P38 MAPK) and reducing mitochondria DNA (mtDNA) and the expression of mitochondrial complexes I and III. In contrast, pretreatment with SB203508 (a P38 MAPK inhibitor), Rotenone (an inhibitor of complex I) and Antimycin A1 (an inhibitor of complex III) reversed TJPs degradation induced by AA. Interestingly, pretreatment of cells with 10 µM Baicalein, a 12/15 lipoxygenase (12/15-LOX) -dependent inhibitor of AA production, protected against AA-induced TJPs degradation, restored mitochondrial function, and reduced apoptosis. These results suggested an intriguing link between the induction of TJPs degradation induced by AA overload and mitochondrial antioxidant function during HS, which was found to be regulated by the mitochondrial complex-ROS-P38 MAPK axis.

UAV's Status Is Worth Considering: A Fusion Representations Matching Method for Geo-Localization.

Visual geo-localization plays a crucial role in positioning and navigation for unmanned aerial vehicles, whose goal is to match the same geographic target from different views. This is a challenging task due to the drastic variations in different viewpoints and appearances. Previous methods have been focused on mining features inside the images. However, they underestimated the influence of external elements and the interaction of various representations. Inspired by multimodal and bilinear pooling, we proposed a pioneering feature fusion network (MBF) to address these inherent differences between drone and satellite views. We observe that UAV's status, such as flight height, leads to changes in the size of image field of view. In addition, local parts of the target scene act a role of importance in extracting discriminative features. Therefore, we present two approaches to exploit those priors. The first module is to add status information to network by transforming them into word embeddings. Note that they concatenate with image embeddings in Transformer block to learn status-aware features. Then, global and local part feature maps from the same viewpoint are correlated and reinforced by hierarchical bilinear pooling (HBP) to improve the robustness of feature representation. By the above approaches, we achieve more discriminative deep representations facilitating the geo-localization more effectively. Our experiments on existing benchmark datasets show significant performance boosting, reaching the new state-of-the-art result. Remarkably, the recall@1 accuracy achieves 89.05% in drone localization task and 93.15% in drone navigation task in University-1652, and shows strong robustness at different flight heights in the SUES-200 dataset.

WiTransformer: A Novel Robust Gesture Recognition Sensing Model with WiFi.

The past decade has demonstrated the potential of human activity recognition (HAR) with WiFi signals owing to non-invasiveness and ubiquity. Previous research has largely concentrated on enhancing precision through sophisticated models. However, the complexity of recognition tasks has been largely neglected. Thus, the performance of the HAR system is markedly diminished when tasked with increasing complexities, such as a larger classification number, the confusion of similar actions, and signal distortion To address this issue, we eliminated conventional convolutional and recurrent backbones and proposed WiTransformer, a novel tactic based on pure Transformers. Nevertheless, Transformer-like models are typically suited to large-scale datasets as pretraining models, according to the experience of the Vision Transformer. Therefore, we adopted the Body-coordinate Velocity Profile, a cross-domain WiFi signal feature derived from the channel state information, to reduce the threshold of the Transformers. Based on this, we propose two modified transformer architectures, united spatiotemporal Transformer (UST) and separated spatiotemporal Transformer (SST) to realize WiFi-based human gesture recognition models with task robustness. SST intuitively extracts spatial and temporal data features using two encoders, respectively. By contrast, UST can extract the same three-dimensional features with only a one-dimensional encoder, owing to its well-designed structure. We evaluated SST and UST on four designed task datasets (TDSs) with varying task complexities. The experimental results demonstrate that UST has achieved recognition accuracy of 86.16% on the most complex task dataset TDSs-22, outperforming the other popular backbones. Simultaneously, the accuracy decreases by at most 3.18% when the task complexity increases from TDSs-6 to TDSs-22, which is 0.14-0.2 times that of others. However, as predicted and analyzed, SST fails because of excessive lack of inductive bias and the limited scale of the training data.

"Decoding MH"-A de-stigmatization campaign in the Hong Kong Police Force.

Police officers are under high level of stress given the intense and emergent work nature. If left untreated, their mental wellbeing would be at risk and work performance compromised. However, mental health stigma is common among police officers and is perpetuated by factors like police cultures emphasizing toughness and self-reliance. In view of this, since 2016, the Hong Kong Police Force had launched a holistic campaign for Force members which was the first among law enforcement organizations in Hong Kong, aiming to reduce stigma, by enhancing mental health knowledge and decreasing negative attitudes and behaviors towards mental health issues. The programme incorporated standardised trainings of the Mental Health First Aid course with examples modified to the local police context, and psychoeducation via the use of digital medium and sharing by public figures. Positive feedback was received. It was foreseen that the campaign effects would increase Force members' awareness of their mental health, encourage help-seeking and facilitate officers' decision making when encountering crises in the community.

Mild cognitive impairment among rural-dwelling older adults in China: A community-based study.

BACKGROUND: Epidemiological studies of mild cognitive impairment (MCI) and subtypes of MCI have rarely focused on rural residents in China. METHODS: This population-based study included 5068 participants (age ≥60 years) who were living in rural communities. We defined MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) following the Petersen's criteria that integrated neuropsychological assessments with in-person clinical evaluations. RESULTS: The overall prevalence of MCI, aMCI, and naMCI was 26.48%, 22.30%, and 4.18%, respectively. The prevalence of MCI increased with age. The adjusted odds ratio (OR) of MCI was 0.71 (95% confidence interval [CI] 0.61 to 0.82) for primary school (vs. illiteracy), 0.30 (0.24 to 0.39) for middle school or above, 1.35 (1.09 to 1.67) for being farmers, 0.65 (0.54 to 0.78) for alcohol consumption, 1.43 (1.20 to 1.70) for stroke history, and 1.14 (0.95 to 1.36) for any apolipoprotein E (APOE) ε4 allele (vs ε3/ε3). CONCLUSIONS: MCI affects over one-fourth of rural older adults in China. Overall MCI was associated with demographic factors, non-alcohol consumption, and stroke, but not with APOE genotype and cardiometabolic factors.