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.

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: Anxious depression is a prevalent characteristic observed in Asian psychiatric patients diagnosed with major depressive disorder (MDD). This study aims to investigate the prevalence and clinical presentation of anxious depression in Taiwanese individuals diagnosed with MDD. Methods: We recruited psychiatric outpatients aged over 18 who had been diagnosed with MDD through clinical interviews. This recruitment took place at five hospitals located in northern Taiwan. We gathered baseline clinical and demographic information from the participants. Anxious depression was identified using a threshold of an anxiety/somatization factor score ≥7 on the 21-item Hamilton Rating Scale for Depression (HAM-D). Results: In our study of 399 patients (84.21% female), 64.16% met the criteria for anxious depression. They tended to be older, married, less educated, with more children, and an older age of onset. Anxious depression patients had higher HAM-D and Clinical Global Impression–Severity scale score, more panic disorder (without agoraphobia), and exhibited symptoms like agitation, irritability, concentration difficulties, psychological and somatic anxiety, somatic complaints, hypochondriasis, weight loss, and increased insight. Surprisingly, their suicide rates did not significantly differ from non-anxious depression patients. This highlights the importance of recognizing and addressing these unique characteristics. Conclusion Our study findings unveiled that the prevalence of anxious depression among Taiwanese outpatients diagnosed with MDD was lower compared to inpatients but substantially higher than the reported rates in European countries and the United States. Furthermore, patients with anxious depression exhibited a greater occurrence of somatic symptoms.

Methamphetamine (Meth) abuse can cause serious mental disorders, including anxiety and depression. The gut microbiota is a crucial contributor to maintaining host mental health. Here, we aim to investigate if microbiota participate in Meth-induced mental disorders, and the potential mechanisms involved. Here, 15 mg/kg Meth resulted in anxiety- and depression-like behaviors of mice successfully and suppressed the Sigma-1 receptor (SIGMAR1)/BDNF/TRKB pathway in the hippocampus. Meanwhile, Meth impaired gut homeostasis by arousing the Toll-like receptor 4 (TLR4)-related colonic inflammation, disturbing the gut microbiome and reducing the microbiota-derived short-chain fatty acids (SCFAs). Moreover, fecal microbiota from Meth-administrated mice mediated the colonic inflammation and reproduced anxiety- and depression-like behaviors in recipients. Further, SCFAs supplementation optimized Meth-induced microbial dysbiosis, ameliorated colonic inflammation, and repressed anxiety- and depression-like behaviors. Finally, Sigmar1 knockout (Sigmar1^-/-) repressed the BDNF/TRKB pathway and produced similar behavioral phenotypes with Meth exposure, and eliminated the anti-anxiety and -depression effects of SCFAs. The activation of SIGMAR1 with fluvoxamine attenuated Meth-induced anxiety- and depression-like behaviors. Our findings indicated that gut microbiota-derived SCFAs could optimize gut homeostasis, and ameliorate Meth-induced mental disorders in a SIGMAR1-dependent manner. This study confirms the crucial role of microbiota in Meth-related mental disorders and provides a potential preemptive therapy.

Disease Outbreaks ; Humans ; Monkeypox/epidemiology*

Objective: To systematically examine the effectiveness and tolerability of psilocybin for treating end-of-life anxiety symptoms. Methods: The Medline, Embase, CENTRAL, and PsycINFO databases were searched up to November 25, 2020. We enrolled clinical trials investigating psilocybin for treating end-of-life anxiety symptoms. Meta-analysis was conducted using random-effects model. Results: Overall, five studies were included, revealing that psilocybin was superior to the placebo in treating state anxiety at 1 day (Hedges’ g, -0.70; 95% confidence interval, -1.01 to -0.39) and 2 weeks (-1.03; -1.47 to -0.60) after treatment. Psilocybin was more effective than placebo in treating trait anxiety at 1 day (-0.71; -1.15 to -0.26), 2 weeks (-1.08; -1.80 to -0.36), and 6 months (-0.84; -1.37 to -0.30) after treatment. Psilocybin was associated with transient elevation in systolic (19.00; 13.58–24.41 mm Hg) and diastolic (8.66; 5.18–12.15 mm Hg) blood pressure compared with placebo. The differences between psilocybin and placebo groups with regard to allcause discontinuation, serious adverse events, and heart rates were nonsignificant. Conclusion Psilocybin-assisted therapy could ameliorate end-of-life anxiety symptoms without serious adverse events. Because of the small sample sizes of the included studies and high heterogeneity on long-term outcomes, future randomized controlled trials with large sample sizes are needed.

INTRODUCTION: The COVID-19 pandemic has affected the world for more than a year, with multiple waves of infections resulting in morbidity, mortality and disruption to the economy and society. Response measures employed to control it have generally been effective but are unlikely to be sustainable over the long term. METHODS: We examined the evidence for a vaccine-driven COVID-19 exit strategy including academic papers, governmental reports and epidemiological data, and discuss the shift from the current pandemic footing to an endemic approach similar to influenza and other respiratory infectious diseases. RESULTS: A desired endemic state is characterised by a baseline prevalence of infections with a generally mild disease profile that can be sustainably managed by the healthcare system, together with the resumption of near normalcy in human activities. Such an endemic state is attainable for COVID-19 given the promising data around vaccine efficacy, although uncertainty remains around vaccine immunity escape in emergent variants of concern. Maintenance of non-pharmaceutical interventions remains crucial until high vaccination coverage is attained to avoid runaway outbreaks. It may also be worthwhile to de-escalate measures in phases, before standing down most measures for an endemic state. If a variant that substantially evades immunity emerges, it will need to be managed akin to a new disease threat, with pandemic preparedness and response plans. CONCLUSION An endemic state for COVID-19, characterised by sustainable disease control measures, is likely attainable through vaccination.
COVID-19 ; Disease Outbreaks/prevention & control* ; Humans ; Influenza, Human/prevention & control* ; Pandemics/prevention & control* ; SARS-CoV-2