BACKGROUND AND OBJECTIVE

Filipino farmers face unique occupational challenges that increase the risk of mental health issues, particularly anxiety. This study aims to determine the different personal, environmental, socioeconomic, occupational, and psychosocial factors associated with anxiety symptoms among Filipino farmers in Central Luzon.

Chain referral sampling method was used to recruit participants for the study, who underwent screening based on the eligibility criteria. Eligible participants were then asked about anxiety symptoms using the Generalized Anxiety Disorder-7 (GAD-7), while the validated, researcher-constructed Data Collection Tool for Factors Associated with Anxiety Symptoms (DCFAAS) was used to determine the farmers’ exposure to a variety of factors. Microsoft Excel was utilized in computing for frequency and percent distribution of participants, in each factor. Binary logistic regression was used to compute crude and adjusted odds ratio of each factor thru IBM SPSS Statistics®.

Among the 113 eligible farmers enrolled in the study, only 19 (16.8%) experienced anxiety symptoms, with excessive worrying, which was seen among 45 participants (39.8%). The mental health of Filipino farmers was significantly affected by the presence of physical illness (OR = 10.70 [95% CI 1.367, 83.773]) and having relatives affecting work completion (OR = 6.45 [95% CI 1.346, 30.896]). 

Despite the low prevalence of anxiety symptoms in this study, the findings suggest government policies to improve mental health service access to farmers, to integrate psychosocial support into agricultural programs, and to address family-related work pressures. By addressing these factors, it can improve farmer productivity and promote overall well-being, putting emphasis on the mental health of the Filipino farmers.

Objective: To investigate the knowledge of hepatitis C prevention and treatment and related factors among two groups of female sex workers (FSW) and men who have sex with men (MSM) in the Xizang Autonomous Region (Xizang) to provide a basis for the subsequent development of Hepatitis C publicity and education strategies. Methods: From August to September 2021, a special survey was conducted among 1 244 FSW and 234 MSM in 5 districts (counties) of 4 regions in Xizang. A one-on-one face-to-face questionnaire survey was adopted, and the χ² test and logistic regression were used to analyze the related factors of awareness of hepatitis C prevention and treatment among FSW and MSM. Results: The awareness rates of hepatitis C prevention and treatment knowledge among FSW and MSM were 35.0% (436/1 244) and 11.1% (26/234), respectively. Multivariate logistic regression analysis revealed that the positive related factors of FSW' awareness of hepatitis C prevention and treatment knowledge among those who had high school or technical secondary school education (aOR=4.72, 95%CI: 3.30-6.74) and college education or above (aOR=2.24, 95%CI: 1.58-3.18), those who experienced self-perceived risk of HCV infection (aOR=1.87, 95%CI: 1.43-2.45), negative related factors included married or cohabiting (aOR=0.58, 95%CI: 0.35-0.95), divorce or windowless (aOR=0.44, 95%CI: 0.27-0.72), no condom was used in the most recent commercial sexual activity (aOR=0.54, 95%CI: 0.43-0.69). The positive related factors of MSM's awareness of hepatitis C prevention and treatment knowledge were over 40 years old (aOR=8.65, 95%CI: 3.19-23.42) and having a self-perceived risk of HCV infection (aOR=6.25, 95%CI: 2.50-15.61). Conclusions: The awareness rate of hepatitis C prevention and treatment among FSW and MSM was relatively low in Xizang in 2021 and urgently needs to be improved. It is necessary to formulate targeted publicity strategies based on the characteristics of these two groups of people, increase publicity efforts, and expand the coverage of knowledge publicity to popularize key points about the clinical manifestations, treatment options, and transmission routes of hepatitis C, and carry out necessary warnings and education.
Humans ; Male ; Hepatitis C/therapy* ; Health Knowledge, Attitudes, Practice ; Surveys and Questionnaires ; Sex Workers/psychology* ; Homosexuality, Male ; Female ; Adult ; China ; Young Adult ; Middle Aged ; Logistic Models

Background/Aims: Multiple rapid swallows (MRS) is a provocative test during high-resolution esophageal manometry (HRM) to evaluate contraction reserve (CR). This study aims to determine the prevalence of CR in patients with ineffective esophageal motility (IEM) and MRS performed in the upright position, and to assess the ideal number of MRS sequences. Methods: We enrolled adult patients diagnosed with IEM according to the Chicago classification version 4.0 who underwent HRM with 3 MRS sequences. Presence of CR was identified as either: the distal contraction integral (DCI) of the post-MRS sequence exceeding the mean DCI of single swallows (ratio > 1) or the mean DCI of the 3 post-MRS sequences surpassing the mean DCI of single swallows. The occurrence of CR was compared following 1, 2, and 3 MRS sequences. Results: When assessing CR in 57 patients referenced to mean single supine swallow DCI, the pooled prevalence of CR following 1, 2, and 3 MRS sequences was 23/57 (40.4%), 31/57 (54.4%), and 33/57 (57.9%), respectively. More patients had CR after 2 MRS sequences compared to 1 (P < 0.001), but there was no significant difference in CR between 2 and 3 MRS sequences (P = 0.160). More patients had CR after 2 (P = 0.013) and 3 MRS sequences (P = 0.034) when CR was referenced to single upright compared to single supine swallows. Conclusion Among patients with IEM, 58.0% had CR after 3 upright MRS sequences and 2 were adequate to assess CR.

Randomized clinical trials are important in both clinical and academic stroke communities with increasing numbers of new design concepts emerging. One of the “less traditional” designs that have gained increasing interest in the last decade is non-inferiority trials. Whilst the concept might appear straightforward, the design and interpretation of non-inferiority trials can be challenging. In this review, we will use exemplars from clinical trials in the stroke field to provide an overview of the advantages and limitations of non-inferiority trials and how they should be interpreted in stroke research.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

BACKGROUND AND OBJECTIVE

Filipino farmers face unique occupational challenges that increase the risk of mental health issues, particularly anxiety. This study aims to determine the different personal, environmental, socioeconomic, occupational, and psychosocial factors associated with anxiety symptoms among Filipino farmers in Central Luzon.

Chain referral sampling method was used to recruit participants for the study, who underwent screening based on the eligibility criteria. Eligible participants were then asked about anxiety symptoms using the Generalized Anxiety Disorder-7 (GAD-7), while the validated, researcher-constructed Data Collection Tool for Factors Associated with Anxiety Symptoms (DCFAAS) was used to determine the farmers’ exposure to a variety of factors. Microsoft Excel was utilized in computing for frequency and percent distribution of participants, in each factor. Binary logistic regression was used to compute crude and adjusted odds ratio of each factor thru IBM SPSS Statistics®.

Among the 113 eligible farmers enrolled in the study, only 19 (16.8%) experienced anxiety symptoms, with excessive worrying, which was seen among 45 participants (39.8%). The mental health of Filipino farmers was significantly affected by the presence of physical illness (OR = 10.70 [95% CI 1.367, 83.773]) and having relatives affecting work completion (OR = 6.45 [95% CI 1.346, 30.896]). 

Despite the low prevalence of anxiety symptoms in this study, the findings suggest government policies to improve mental health service access to farmers, to integrate psychosocial support into agricultural programs, and to address family-related work pressures. By addressing these factors, it can improve farmer productivity and promote overall well-being, putting emphasis on the mental health of the Filipino farmers.

Cardiotoxicity is a critical issue in drug development that poses serious health risks, including potentially fatal arrhythmias. The human ether-à-go-go related gene (hERG) potassium channel, as one of the primary targets of cardiotoxicity, has garnered widespread attention. Traditional cardiotoxicity testing methods are expensive and time-consuming, making computational virtual screening a suitable alternative. In this study, we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds, with the aim of improving prediction accuracy and efficiency. We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. Our models demonstrated advanced predictive performance. The best machine learning model, XGBoost Morgan, achieved an accuracy (ACC) value of 0.84, and the deep learning model, Transformer_Morgan, achieved the best ACC value of 0.85, showing a high ability to distinguish between toxic and non-toxic compounds. On an external independent validation set, it achieved the best area under the curve (AUC) value of 0.93, surpassing ADMETlab3.0, Cardpred, and CardioDPi. In addition, we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods, such as voting and stacking, provided slight improvements in model stability. Furthermore, the SHapley Additive exPlanations (SHAP) explanations revealed the relationship between benzene rings, fluorine-containing groups, NH groups, oxygen in ether groups, and cardiotoxicity, highlighting the importance of these features. This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment. Using computational methods, this study facilitates a more efficient drug development process, reduces costs, and improves the safety of new drug candidates, ultimately benefiting medical and public health.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.