Advances in an In Vitro Tuberculosis Infection Model Using Human Lung Organoids for Host-Directed Therapies.

The emergence of drug-resistant Mycobacterium tuberculosis (M.tb) has led to the development of novel anti-tuberculosis (anti-TB) drugs. Common methods for testing the efficacy of new drugs, including two-dimensional cell culture models or animal models, have several limitations. Therefore, an appropriate model representative of the human organism is required. Here, we developed an M.tb infection model using human lung organoids (hLOs) and demonstrated that M.tb H37Rv can infect lung epithelial cells and human macrophages (hMφs) in hLOs. This novel M.tb infection model can be cultured long-term and split several times while maintaining a similar number of M.tb H37Rv inside the hLOs. Anti-TB drugs reduced the intracellular survival of M.tb in hLOs. Notably, M.tb growth in hLOs was effectively suppressed at each passage by rifampicin and bedaquiline. Furthermore, a reduction in inflammatory cytokine production and intracellular survival of M.tb were observed upon knockdown of MFN2 and HERPUD1 (host-directed therapeutic targets for TB) in our M.tb H37Rv-infected hLO model. Thus, the incorporation of hMφs and M.tb into hLOs provides a powerful strategy for generating an M.tb infection model. This model can effectively reflect host-pathogen interactions and be utilized to test the efficacy of anti-TB drugs and host-directed therapies.

Sodium-glucose cotransporter-2 inhibitors and their potential role in dementia onset and cognitive function in patients with diabetes mellitus: a systematic review and meta-analysis.

This systematic review and meta-analysis aimed to determine the association between the use of sodium-glucose cotransporter 2 (SGLT-2) inhibitors and dementia onset as well as cognitive function in patients with diabetes mellitus. We comprehensively searched the MEDLINE, Embase, and CENTRAL databases to select relevant studies published up to August 2023. The use of SGLT-2 inhibitors significantly lowers dementia risk compared to SGLT-2i non-users (Hazard ratio: 0.68, 95 % CI: 0.50-0.92). Furthermore, our findings indicated a positive effect of SGLT-2 inhibitor use on cognitive function score improvement, as demonstrated by the standardized mean difference of 0.88 (95 % CI: 0.32-1.44), particularly among populations with mild cognitive impairment or dementia. This systematic review and meta-analysis indicate a potential role of SGLT-2 inhibitors in reducing the risk of dementia in patients with diabetes mellitus. These findings underscore the need for well-controlled large clinical trials and future research in this field.

A novel G3BP1-GFP reporter human lung cell system enabling real-time monitoring of stress granule dynamics for in vitro lung toxicity assessment.

Under various cellular stress conditions, including exposure to toxic chemicals, RNA-binding proteins (RBPs), including Ras GTPase-activating protein-binding protein 1 (G3BP1), aggregate and form stress granule complexes, which serve as hallmarks of cellular stress. The existing methods for analyzing stress granule assembly have limitations in the rapid detection of dynamic cellular stress and ignore the effects of constitutively overexpressed RBP on cellular stress and stress-related processes. Therefore, to overcome these limitations, we established a G3BP1-GFP reporter in a human lung epithelial cell line using CRISPR/Cas9-based knock-in as an alternative system for stress granule analysis. We showed that the G3BP1-GFP reporter system responds to stress conditions and forms a stress granule complex similar to that of native G3BP1. Furthermore, we validated the stress granule response of an established cell line under exposure to various household chemicals. Overall, this novel G3BP1-GFP reporter human lung cell system is capable of monitoring stress granule dynamics in real time and can be used for assessing the lung toxicity of various substances in vitro.

Effects of defoliant exposure and medication use on the development of Parkinson's disease in veterans.

BACKGROUND: Vietnam-era veterans were exposed to Agent Orange (AO), which is associated with a high prevalence of Parkinson's disease (PD). However, little is known about the development of PD-like symptoms caused by drug-induced parkinsonism (DIP) in such populations. This study aimed to investigate PD incidence and PD risk following exposure to AO or DIP-risk drugs in veterans. METHODS: A retrospective cohort study was conducted using 12 years (2009-2020) of electronic medical records of the Veterans Health Service Medical Center, the largest Veterans Affairs hospital in South Korea (n = 37,246; 100% male; age, 65.57 ± 8.12 years). Exposure to AO or DIP-risk drugs, including antipsychotic, prokinetic, anti-epileptic, dopamine-depleting and anti-anginal agents, was assessed in veterans with PD, operationally defined as having a PD diagnosis and one or more prescriptions for PD treatment. The PD risk was calculated using multiple logistic regression analysis adjusted for age and comorbidities. RESULTS: The rates of DIP-risk drug use and AO exposure were 37.92% and 62.62%, respectively. The PD incidence from 2010 to 2020 was 3.08%; 1.30% with neither exposure, 1.63% with AO exposure, 4.38% with DIP-risk drug use, and 6.33% with both. Combined exposure to AO and DIP-risk drugs increased the PD risk (adjusted odds ratio = 1.68, 95% confidence interval, 1.36-2.08, P < 0.001). CONCLUSIONS: The PD incidence was 1.31 times higher with AO exposure alone and 1.68 times higher with AO exposure and DIP-risk drug use. The results suggest the necessity for careful monitoring and DIP-risk drug prescription in patients with AO exposure.

The Relation Between eHealth Literacy and Health-Related Behaviors: Systematic Review and Meta-analysis.

BACKGROUND: With widespread use of the internet and mobile devices, many people have gained improved access to health-related information online for health promotion and disease management. As the health information acquired online can affect health-related behaviors, health care providers need to take into account how each individual's online health literacy (eHealth literacy) can affect health-related behaviors. OBJECTIVE: To determine whether an individual's level of eHealth literacy affects actual health-related behaviors, the correlation between eHealth literacy and health-related behaviors was identified in an integrated manner through a systematic literature review and meta-analysis. METHODS: The MEDLINE, Embase, Cochrane, KoreaMed, and Research Information Sharing Service databases were systematically searched for studies published up to March 19, 2021, which suggested the relationship between eHealth literacy and health-related behaviors. Studies were eligible if they were conducted with the general population, presented eHealth literacy according to validated tools, used no specific control condition, and measured health-related behaviors as the outcomes. A meta-analysis was performed on the studies that could be quantitatively synthesized using a random effect model. A pooled correlation coefficient was generated by integrating the correlation coefficients, and the risk of bias was assessed using the modified Newcastle-Ottawa Scale. RESULTS: Among 1922 eHealth literacy-related papers, 29 studies suggesting an association between eHealth literacy and health-related behaviors were included. All retrieved studies were cross-sectional studies, and most of them used the eHealth Literacy Scale (eHEALS) as a measurement tool for eHealth literacy. Of the 29 studies, 22 presented positive associations between eHealth literacy and health-related behaviors. The meta-analysis was performed on 14 studies that presented the correlation coefficient for the relationship between eHealth literacy and health-related behaviors. When the meta-analysis was conducted by age, morbidity status, and type of health-related behavior, the pooled correlation coefficients were 0.37 (95% CI 0.29-0.44) for older adults (aged ≥65 years), 0.28 (95% CI 0.17-0.39) for individuals with diseases, and 0.36 (95% CI 0.27-0.41) for health-promoting behavior. The overall estimate of the correlation between eHealth literacy and health-related behaviors was 0.31 (95% CI 0.25-0.34), which indicated a moderate correlation between eHealth literacy and health-related behaviors. CONCLUSIONS: Our results of a positive correlation between eHealth literacy and health-related behaviors indicate that eHealth literacy can be a mediator in the process by which health-related information leads to changes in health-related behaviors. Larger-scale studies with stronger validity are needed to evaluate the detailed relationship between the proficiency level of eHealth literacy and health-related behaviors for health promotion in the future.

Risk Factors for the Prescription of Ineffective Antiviral Candidates for COVID-19 During the Early Pandemic Period in Korea.

BACKGROUND: Although the evidence of treatment for coronavirus disease 2019 (COVID-19) changed rapidly, little is known about the patterns of potential pharmacological treatment during the early period of the COVID-19 pandemic in Korea and the risk factors for ineffective prescription. METHODS: Using claims data from the Korean National Health Insurance System, this retrospective cohort study included admission episodes for COVID-19 from February to December 2020. Ineffective antiviral prescriptions for COVID-19 were defined as lopinavir/ritonavir (LPN/r) and hydroxychloroquine (HCQ) prescribed after July 2020, according to the revised National Institute of Health COVID-19 treatment guidelines. Factors associated with ineffective prescriptions, including patient and hospital factors, were identified by multivariate logistic regression analysis. RESULTS: Of the 15,723 COVID-19 admission episodes from February to June 2020, 4,183 (26.6%) included prescriptions of LPN/r, and 3,312 (21.1%) included prescriptions of HCQ. Of the 48,843 admission episodes from July to December 2020, after the guidelines were revised, 2,258 (4.6%) and 182 (0.4%) included prescriptions of ineffective LPN/r and HCQ, respectively. Patient factors independently associated with ineffective antiviral prescription were older age (adjusted odds ratio [aOR] per 10-year increase, 1.17; 95% confidence interval [CI], 1.14-1.20) and severe condition with an oxygen requirement (aOR, 2.49; 95% CI, 2.24-2.77). The prescription of ineffective antiviral drugs was highly prevalent in primary and nursing hospitals (aOR, 40.58; 95% CI, 31.97-51.50), public sector hospitals (aOR, 15.61; 95% CI, 12.76-19.09), and regions in which these drugs were highly prescribed before July 2020 (aOR, 10.65; 95% CI, 8.26-13.74). CONCLUSION: Ineffective antiviral agents were prescribed to a substantial number of patients during the first year of the COVID-19 pandemic in Korea. Treatment with these ineffective drugs tended to be prolonged in severely ill patients and in primary and public hospitals.

Evaluation of Robotic Systems on Cytotoxic Drug Preparation: A Systematic Review and Meta-Analysis.

Background and Objectives: With the increased prevalence of patients with cancer, the demand for preparing cytotoxic drugs was increased by health-system pharmacists. To reduce the workload and contamination of work areas in pharmacies, compounding robots preparing cytotoxic drugs have been introduced, and the use of the robots has been expanded in recent years. As reports on the comprehensive and quantitative evaluation of compounding robots remain lacking, a systematic review and meta-analysis were conducted to provide descriptive and quantitative evaluations of the accuracy of preparing injectable cytotoxic drugs. Materials and Methods: A systematic review and meta-analysis were conducted using published studies up to 2020. To identify eligible studies, PubMed, EMBASE, and Cochrane Library were used. All studies reporting the outcomes relevant to drug-compounding robots such as accuracy, safety, and drug contamination were included. Outcomes from included studies were descriptively summarized. Drug contamination by the robot was quantitatively analyzed using the odds ratio (OR) with a 95% confidence interval (CI). The risk of bias was assessed using the Risk of Bias Assessment tool for Non-randomized Studies (RoBANS). Results: A total of 14 compounding robot studies were eligible for review and 4 studies were included in the meta-analysis. Robotic compounding showed failure rates of 0.9-16.75%, while the accuracy range was set at 5%. Two studies reported that robotic compounding needed more time than manual compounding, two reported that robotic compounding needed less time, and one just reported preparation time without a control group. In a meta-analysis regarding the contamination of the compounding area, manual compounding was associated with lower contamination, although the result was not statistically significant (OR 4.251, 95% CI 0.439-51.772). For the contamination of infusion bags, the robot was associated with lower contamination (OR 0.176, 95% CI 0.084-0.365). Conclusions: Robotic compounding showed better accuracy than manual compounding and, without control groups, showed a high accuracy rate and also reduced the risk of drug contamination and compounding workload. The preparation time of the robot was not consistent because the type of robot and introduced system were different. In conclusion, robotic compounding showed mixed results compared to the manual compounding of drugs, so the system should be introduced considering the risks and benefits of robots.

Pulmonary fibrosis model using micro-CT analyzable human PSC-derived alveolar organoids containing alveolar macrophage-like cells.

Human lung organoids (hLOs) are useful for disease modelling and drug screening. However, a lack of immune cells in hLOs limits the recapitulation of in vivo cellular physiology. Here, we generated hLOs containing alveolar macrophage (AMφ)-like cells derived from pluripotent stem cells (PSC). To bridge hLOs with advanced human lung high-resolution X-ray computed tomography (CT), we acquired quantitative micro-CT images. Three hLO types were observed during differentiation. Among them, alveolar hLOs highly expressed not only lung epithelial cell markers but also AMφ-specific markers. Furthermore, CD68+ AMφ-like cells were spatially organized on the luminal epithelial surface of alveolar hLOs. Bleomycin-treated alveolar hLOs showed upregulated expression of fibrosis-related markers and extracellular matrix deposits in the alveolar sacs. Alveolar hLOs also showed structural alterations such as excessive tissue fraction under bleomycin treatment. Therefore, we suggest that micro-CT analyzable PSC-derived alveolar hLOs are a promising in vitro model to predict lung toxicity manifestations, including fibrosis.

Polyhexamethylene guanidine phosphate increases stress granule formation in human 3D lung organoids under respiratory syncytial virus infection.

Polyhexamethylene guanidine phosphate (PHMG-p), a humidifier disinfectant, is known to cause lung toxicity, including inflammation and pulmonary fibrosis. In this study, we aimed to investigate the effect of PHMG-p on human lung tissue models (2D epithelial cells and 3D organoids) under conditions of oxidative stress and viral infection. The effect of PHMG-p was studied by evaluating the formation of stress granules (SGs), which play a pivotal role in cellular adaptation to various stress conditions. Under oxidative stress and respiratory syncytial virus (RSV) infection, exposure to PHMG-p remarkably increased eIF2α phosphorylation, which is essential for SG-related signalling, and significantly increased SG formation. Furthermore, PHMG-p induced fibrotic gene expression and caused cell death due to severe DNA damage, which was further increased under oxidative stress and RSV infection, indicating that PHMG-p induces severe lung toxicity under stress conditions. Taken together, toxicity evaluation under various stressful conditions is necessary to accurately predict potential lung toxicity of chemicals affecting the respiratory tract.

Neighbor-Aware Non-Orthogonal Multiple Access Scheme for Energy Harvesting Internet of Things.

In a non-orthogonal multiple access (NOMA) environment, an Internet of Things (IoT) device achieves a high data rate by increasing its transmission power. However, excessively high transmission power can cause an energy outage of an IoT device and have a detrimental effect on the signal-to-interference-plus-noise ratio of neighbor IoT devices. In this paper, we propose a neighbor-aware NOMA scheme (NA-NOMA) where each IoT device determines whether to transmit data to the base station and the transmission power at each time epoch in a distributed manner with the consideration of its energy level and other devices' transmission powers. To maximize the aggregated data rate of IoT devices while keeping an acceptable average energy outage probability, a constrained stochastic game model is formulated, and the solution of the model is obtained using a best response dynamics-based algorithm. Evaluation results show that NA-NOMA can increase the average data rate up to 22% compared with a probability-based scheme while providing a sufficiently low energy outage probability (e.g., 0.05).

On the encoding capacity of human motor adaptation.

Primitive-based models of motor learning suggest that adaptation occurs by tuning the responses of motor primitives. Based on this idea, we consider motor learning as an information encoding procedure, that is, a procedure of encoding a motor skill into primitives. The capacity of encoding is determined by the number of recruited primitives, which depends on how many primitives are "visited" by the movement, and this leads to a rather counterintuitive prediction that faster movement, where a larger number of motor primitives are involved, allows learning more complicated motor skills. Here, we provide a set of experimental results that support this hypothesis. First, we show that learning occurs only with movement, that is, only with nonzero encoding capacity. When participants were asked to counteract a rotating force applied to a robotic handle, they were unable to do so when maintaining a static posture but were able to adapt when making small circular movements. Our second experiment further investigated how adaptation is affected by movement speed. When adapting to a simple (low-information-content) force field, fast (high-capacity) movement did not have an advantage over slow (low-capacity) movement. However, for a complex (high-information-content) force field, the fast movement showed a significant advantage over slow movement. Our final experiment confirmed that the observed benefit of high-speed movement is only weakly affected by mechanical factors. Taken together, our results suggest that the encoding capacity is a genuine limiting factor of human motor adaptation.NEW & NOTEWORTHY We propose a novel concept called "encoding capacity" of motor adaptation, which describes an inherent limiting-factor of our brain's ability to learn new motor skills, just like any other storage system. By reinterpreting the existing primitive-based models of motor learning, we hypothesize that the encoding capacity is determined by the size of the movement, and present a set of experimental evidence suggesting that such limiting effect of encoding capacity does exist in human motor adaptation.

An Energy Efficient UAV-Based Edge Computing System with Reliability Guarantee for Mobile Ground Nodes.

An edge computing system is a distributed computing framework that provides execution resources such as computation and storage for applications involving networking close to the end nodes. An unmanned aerial vehicle (UAV)-aided edge computing system can provide a flexible configuration for mobile ground nodes (MGN). However, edge computing systems still require higher guaranteed reliability for computational task completion and more efficient energy management before their widespread usage. To solve these problems, we propose an energy efficient UAV-based edge computing system with energy harvesting capability. In this system, the MGN makes requests for computing service from multiple UAVs, and geographically proximate UAVs determine whether or not to conduct the data processing in a distributed manner. To minimize the energy consumption of UAVs while maintaining a guaranteed level of reliability for task completion, we propose a stochastic game model with constraints for our proposed system. We apply a best response algorithm to obtain a multi-policy constrained Nash equilibrium. The results show that our system can achieve an improved life cycle compared to the individual computing scheme while maintaining a sufficient successful complete computation probability.

Deubiquitinases: Modulators of Different Types of Regulated Cell Death.

The mechanisms and physiological implications of regulated cell death (RCD) have been extensively studied. Among the regulatory mechanisms of RCD, ubiquitination and deubiquitination enable post-translational regulation of signaling by modulating substrate degradation and signal transduction. Deubiquitinases (DUBs) are involved in diverse molecular pathways of RCD. Some DUBs modulate multiple modalities of RCD by regulating various substrates and are powerful regulators of cell fate. However, the therapeutic targeting of DUB is limited, as the physiological consequences of modulating DUBs cannot be predicted. In this review, the mechanisms of DUBs that regulate multiple types of RCD are summarized. This comprehensive summary aims to improve our understanding of the complex DUB/RCD regulatory axis comprising various molecular mechanisms for diverse physiological processes. Additionally, this review will enable the understanding of the advantages of therapeutic targeting of DUBs and developing strategies to overcome the side effects associated with the therapeutic applications of DUB modulators.

A cross-sectional survey of knowledge, attitude, and willingness to engage in spontaneous reporting of adverse drug reactions by Korean consumers.

BACKGROUND: Spontaneous reporting (SR) of adverse drug reactions (ADRs) from patients can be considered as a valuable activity providing both objective and subjective data. However, improving the rate of under-reporting has been a major challenge to ensure successful operation of the SR system. This study aimed to assess knowledge, attitude, and intent to report ADRs and explore the factors contributing to consumers' reporting intent in South Korea. METHODS: Self-administered questionnaire was collected from a sex-, age-, and regionally stratified nationwide convenience sample of consumers using a commercial panel in December 2018. Univariate and multivariate logistic regression analyses were used to explore the factors contributing to the intent to report ADRs by consumers. RESULTS: A total of 1000 respondents were enrolled in the survey; 50.9% were males and the mean age was 44.4 (standard deviation, 13.3) years. While less than 15% of the respondents were aware of the SR system and even fewer (3.4%) had actual experience of SR, however, 59.2% expressed their intent to report ADRs. The positive attitude (adjusted odds ratio [aOR] 3.972, p < 0.001), awareness of the SR system (aOR 2.102, p < 0.01), self-efficacy for SR (aOR 1.956, p < 0.001), and experiences related to ADR counselling with healthcare professionals (OR 2.318, p < 0.001) are the significant factors contributing to reporting intent. CONCLUSIONS: Findings of this study highlight the need for increasing the awareness of the SR system among consumers and empowering them to report ADRs by themselves, which would ultimately improve the drug-safety environment.

Success Probability Characterization of Long-Range in Low-Power Wide Area Networks.

In low-power wide area networks (LPWAN), a considerable number of end devices (EDs) communicate with the gateway in a certain area, whereas for transmitted data, a low data rate and high latency are allowed. Long-range (LoRa), as one of the LPWAN technologies, considers pure ALOHA and chirp spread spectrum (CSS) in the media access control (MAC) and physical (PHY) layers such that it can improve the energy efficiency while mitigating inter-cell interference (ICI). This paper investigates the system throughput of LoRa networks under the assumption that the interferences between EDs for exclusive regions are ignored using CSS. In order to establish an analytical model for the performance of LoRa, we introduce the pure ALOHA capture model, which is the power threshold model. For this model, we assume that the interfering power is proportional to the length of the time overlapped. In addition, we discuss LoRa gain by comparing the total throughput of LoRa with that of non-CSS.

Association between Trimetazidine and Parkinsonism: A Population-Based Study.

BACKGROUND: The prevalence of drug-induced parkinsonism (DIP) has been reported with the use of trimetazidine (TMZ), an antianginal medication available in Asian and European countries. Very few studies have evaluated the association between DIP and TMZ use, and studies using population-based data from national databases are lacking. OBJECTIVES: To investigate the association between DIP and use of TMZ in patients with angina using data from a national healthcare claims database and to determine the predictive factors of DIP in TMZ use. METHODS: A cross-sectional study was conducted on patients aged 40 years or more diagnosed with angina, using the Korean National Healthcare claims 2014 database. The association between TMZ use and DIP was evaluated using multivariate logistic regression analysis, adjusting for confounders, including age; sex; insurance type; comorbidities; and concurrent medications known to be commonly associated with DIP, such as typical and atypical antipsychotics. RESULTS: Of the patients included in the study, 19% were prescribed TMZ. In addition, 2.5% of TMZ users had preexisting extrapyramidal and movement disorders. TMZ use was found to be a significant predictor of a new diagnosis of parkinsonism (adjusted OR [aOR] 1.39; 95% CI 1.06-1.81; p = 0.016). Age ≥65 years (aOR 2.07; 95% CI 1.13- 3.74; p = 0.017) and stroke as comorbid disease (aOR 3.23; 95% CI 1.87-5.61; p < 0.001) were also significantly associated with a new diagnosis of parkinsonism in TMZ users. CONCLUSIONS: Treatment with TMZ was a statistically significant predictor of a new diagnosis of parkinsonism. Efforts should focus on close monitoring of, and education on, TMZ use in relation to DIP in all patients who are prescribed TMZ, including those with preexisting extrapyramidal and movement disorders.

Transition pathway and its free-energy profile: a protocol for protein folding simulations.

We propose a protocol that provides a systematic definition of reaction coordinate and related free-energy profile as the function of temperature for the protein-folding simulation. First, using action-derived molecular dynamics (ADMD), we investigate the dynamic folding pathway model of a protein between a fixed extended conformation and a compact conformation. We choose the pathway model to be the reaction coordinate, and the folding and unfolding processes are characterized by the ADMD step index, in contrast to the common a priori reaction coordinate as used in conventional studies. Second, we calculate free-energy profile as the function of temperature, by employing the replica-exchange molecular dynamics (REMD) method. The current method provides efficient exploration of conformational space and proper characterization of protein folding/unfolding dynamics from/to an arbitrary extended conformation. We demonstrate that combination of the two simulation methods, ADMD and REMD, provides understanding on molecular conformational changes in proteins. The protocol is tested on a small protein, penta-peptide of met-enkephalin. For the neuropeptide met-enkephalin system, folded, extended, and intermediate sates are well-defined through the free-energy profile over the reaction coordinate. Results are consistent with those in the literature.

Neuroprotective effect of angiotensin II receptor blockers on the risk of incident Alzheimer's disease: A nationwide population-based cohort study.

Background: Recent studies on renin-angiotensin system (RAS) inhibitors have reported a reduced risk of Alzheimer's disease (AD). Nevertheless, the effect of RAS inhibitor type and blood-brain barrier (BBB) permeability on the risk of AD is still unknown. Objectives: To assess the effects of RAS inhibitors on the risk of AD based on the type and BBB permeability and investigate the cumulative duration-response relationship. Methods: This was a population-based retrospective cohort study using the Korean Health Insurance Review and Assessment database records from 2008 to 2019. The data of patients diagnosed with ischemic heart disease between January 2009 and June 2009 were identified for inclusion in the analyses. Propensity score matching was used to balance RAS inhibitor users with non-users. The association between the use of RAS inhibitors and incident AD was evaluated using a multivariate Cox proportional hazard regression model. The results are presented in adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs). Results: Among the 57,420 matched individuals, 7,303 developed AD within the follow-up period. While the use of angiotensin-converting enzyme inhibitors (ACEIs) was not significantly associated with AD risk, the use of angiotensin II receptor blockers (ARBs) showed a significant association with reduced risk of incident AD (aHR = 0.94; 95% CI = 0.90-0.99). Furthermore, the use of BBB-crossing ARBs was associated with a lower risk of AD (aHR = 0.83; 95% CI = 0.78-0.88) with a cumulative duration-response relationship. A higher cumulative dose or duration of BBB-crossing ARBs was associated with a gradual decrease in AD risk (P for trend < 0.001). No significant association between the use of ACEIs and the risk of AD was observed regardless of BBB permeability. Conclusion: Long-term use of BBB-crossing ARBs significantly reduced the risk of AD development. The finding may provide valuable insight into disease-modifying drug options for preventing AD in patients with cardiovascular diseases.

Machine learning reveals sex-specific associations between cardiovascular risk factors and incident atherosclerotic cardiovascular disease.

We aimed to investigate sex-specific associations between cardiovascular risk factors and atherosclerotic cardiovascular disease (ASCVD) risk using machine learning. We studied 258,279 individuals (132,505 [51.3%] men and 125,774 [48.7%] women) without documented ASCVD who underwent national health screening. A random forest model was developed using 16 variables to predict the 10-year ASCVD in each sex. The association between cardiovascular risk factors and 10-year ASCVD probabilities was examined using partial dependency plots. During the 10-year follow-up, 12,319 (4.8%) individuals developed ASCVD, with a higher incidence in men than in women (5.3% vs. 4.2%, P < 0.001). The performance of the random forest model was similar to that of the pooled cohort equations (area under the receiver operating characteristic curve, men: 0.733 vs. 0.727; women: 0.769 vs. 0.762). Age and body mass index were the two most important predictors in the random forest model for both sexes. In partial dependency plots, advanced age and increased waist circumference were more strongly associated with higher probabilities of ASCVD in women. In contrast, ASCVD probabilities increased more steeply with higher total cholesterol and low-density lipoprotein (LDL) cholesterol levels in men. These sex-specific associations were verified in the conventional Cox analyses. In conclusion, there were significant sex differences in the association between cardiovascular risk factors and ASCVD events. While higher total cholesterol or LDL cholesterol levels were more strongly associated with the risk of ASCVD in men, older age and increased waist circumference were more strongly associated with the risk of ASCVD in women.

A Bivalent Inactivated Vaccine Prevents Enterovirus 71 and Coxsackievirus A16 Infections in the Mongolian Gerbil.

Hand-foot-and-mouth disease (HFMD) is a viral infectious disease that occurs in children under 5 years of age. Its main causes are coxsackievirus (CV) and enterovirus (EV). Since there are no efficient therapeutics for HFMD, vaccines are effective in preventing the disease. To develop broad coverage against CV and EV, the development of a bivalent vaccine form is needed. The Mongolian gerbil is an efficient and suitable animal model of EV71 C4a and CVA16 infection used to investigate vaccine efficacy following direct immunization. In this study, Mongolian gerbils were immunized with a bivalent inactivated EV71 C4a and inactivated CVA16 vaccine to test their effectiveness against viral infection. Bivalent vaccine immunization resulted in increased Ag-specific IgG antibody production; specifically, EV71 C4a-specific IgG was increased with medium and high doses and CVA16-specific IgG was increased with all doses of immunization. When gene expression of T cell-biased cytokines was analysed, Th1, Th2, and Th17 responses were found to be highly activated in the high-dose immunization group. Moreover, bivalent vaccine immunization mitigated paralytic signs and increased the survival rate following lethal viral challenges. When the viral RNA content was determined from various organs, all three doses of bivalent vaccine immunization were found to significantly decrease viral amplification. Upon histologic examination, EV71 C4a and CVA16 induced tissue damage to the heart and muscle. However, bivalent vaccine immunization alleviated this in a dose-dependent manner. These results suggest that the bivalent inactivated EV71 C4a/CVA16 vaccine could be a safe and effective candidate HFMD vaccine.