Background: The projected expansion of an aging United States (US) workforce prompts further evaluation of the potential impact of work on cognitive health. This study aimed to investigate longitudinal associations of reward and effort at work with subjective memory among US older workers. Methods: Data were obtained from the population-based Health and Retirement Study. At the 2006 —2008 baseline, effort and reward were measured using hypotheses based on the effort-reward imbalance (ERI) model. A subjective memory summary score that was composed of two items, in which higher scores indicated better subjective memory, was assessed biennially between the baseline and 2018. Generalized estimating equations analyzed longitudinal associations of effort and reward categories with changes in subjective memory between the baseline and follow-ups. Demographic, socioeconomic, lifestyle, health, and work covariates were adjusted for in linear regression models.Supplementary analyses explored the associations of ERI components with each of the two items that formed the subjective memory summary score. Results: Among 3,497 workers aged 50 years and older, after covariate adjustments, high reward was significantly associated with better subjective memory (regression coefficient: 0.15 [95% confidence interval: 0.07, 0.23], p < 0.001). Compared to the combination of “low effort and low reward,” other effort-reward combinations were also associated with increased subjective memory (p < 0.05). Supplementary analyses demonstrated significant positive associations with independent high reward and ERI combinations. High effort was positively related to subjective memory, although the association was not significant after adjustments. Conclusion Work-related reward, independently and in combination with effort, may contribute to improved subjective memory among US older workers.

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.

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.

Systemic lupus erythematosus (SLE) is the most common form of lupus and a chronic autoimmune disorder that can affect multiple organ systems including the joints, skin, the cardiovascular system and even the central and peripheral nervous system. Although rare, these patients may present with neuropsychiatric symptoms. This patient presented initially with an SLE flare associated with sudden focal to generalized tonic-clonic seizures. Further rheumatologic workup was done which revealed that the patient also has scleroderma, an autoimmune connective tissue that causes inflammation of the skin and other key internal organs. Due to the seizure occurrence, cranial magnetic resonance imaging (MRI) was done which showed incidental mesial temporal sclerosis, which is the scarring of the medial part of the said lobe of the brain. Her overlap syndrome was managed with Hydrocortisone and she was given Valproic acid as her anti-epileptic drug with no recurrence of seizure afterwards.

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.

[摘 要] 目的：基于生物信息学分析和体内、体外实验研究长链非编码RNA00511（LINC00511）敲减对非小细胞肺癌细胞增殖、凋亡、侵袭等恶性生物学行为的影响，并初步探究其作用机制。方法：通过基因表达谱交互分析（GEPIA）数据库分析LINC00511在非小细胞肺癌的表达水平，及其与患者肿瘤分期、生存期等临床特征、肿瘤细胞恶性生物学行为有关基因的相关性；利用shRNA慢病毒载体构建LINC00511敲减的H1299肺癌细胞株，克隆形成实验、划痕愈合实验和流式细胞术分别检测对H1299细胞增殖、迁移、细胞周期和凋亡能力的影响，qRT-PCR检测相关调控基因表达，WB法检测肿瘤相关蛋白的表达；构建裸鼠皮下移植瘤模型，取瘤组织进行免疫组织化学实验检测Ki67表达情况。结果：GEPIA数据库分析表明LINC00511在非小细胞肺癌组织中表达水平升高，且与该病的临床分期情况相关（P < 0.05），LINC00511与肺癌中CASP3、CCNB1、CDK4等多种基因表达均有相关性（P < 0.01）；LINC00511敲减可抑制细胞的克隆形成和迁移能力、促进肺癌细胞凋亡并影响细胞周期进展（P < 0.05，P < 0.01）；LINC00511敲减可下调肺癌细胞CCNB、CDK4、TGF-β1基因的表达（P < 0.01），对CCND1、VEGFA基因表达无明显影响，LINC00511敲减可抑制细胞内MMP9、CTNNB1表达，上调CASP3的表达（P < 0.05，P < 0.01）；裸鼠体内实验证实，LINC00511敲减可抑制移植瘤体组织内Ki67的表达（P < 0.01）。结论：LINC00511在非小细胞肺癌组织中呈高表达，与肺癌临床分期和多种基因表达具有相关性，LINC00511敲减可能通过影响相关基因、蛋白的表达，抑制肺癌H1299细胞的恶性生物学行为。

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.