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Two researchers independently assessed studies published up to February 5, 2023, across PubMed, Web of Science, Embase, and Cochrane Library, to investigate the associations of sleep traits with cardiometabolic risk factors, as well as with cardiovascular diseases. Fourteen systematic reviews consisting of 23 meta-analyses, and 11 Mendelian randomization (MR) studies were included in this study. Short sleep duration was associated with a higher risk of obesity, type 2 diabetes (T2D), hypertension, stroke, and coronary heart disease (CHD) in observational studies, while a causal role was only demonstrated in obesity, hypertension, and CHD by MR. Similarly, long sleep duration showed connections with a higher risk of obesity, T2D, hypertension, stroke, and CHD in observational studies, none was supported by MR analysis. Both observational and MR studies indicated heightened risks of hypertension, stroke, and CHD in relation to insomnia. Napping was linked to elevated risks of T2D and CHD in observational studies, with MR analysis confirming a causal role in T2D. Additionally, snoring was correlated with increased risks of stroke and CHD in both observational and MR studies. This work consolidates existing evidence on a causal relationship between sleep characteristics and cardiometabolic risk factors, as well as cardiovascular diseases.

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Objective: To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2 (T2DM) in the middle-aged and elderly populations based on the results of a Meta-analysis, and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service. Methods: Cohort studies evaluating T2DM risks were identified in Chinese and English databases. The logistic model utilized Meta-combined effect values such as the odds ratio (OR) to derive ß, the partial regression coefficient, of the logistic model. The Meta-combined incidence rate of T2DM was used to obtain the parameter α of the logistic model. Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service. The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7602 individuals who did not have T2DM at their baseline medical checkups done at the community health center. This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people. Results: A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM, including age, central obesity, smoking, physical inactivity, impaired fasting glucose, a reduced level of high-density lipoprotein cholesterol (HDL-C), hypertension, body mass index (BMI), triglyceride glucose (TYG) index, and a family history of diabetes, with the OR values and 95% confidence interval (CI) being 1.04 (1.03, 1.05), 1.55 (1.29, 1.88), 1.36 (1.11, 1.66), 1.26 (1.07, 1.49), 3.93 (2.94, 5.24), 1.14 (1.06, 1.23), 1.47 (1.34, 1.61), 1.11 (1.05, 1.18), 2.15 (1.75, 2.62), and 1.66 (1.55, 1.78), respectively, and the combined ß values being 0.039, 0.438, 0.307, 0.231, 1.369, 0.131, 0.385, 0.104, 0.765, and 0.507, respectively. A total of 37 studies reported the incidence rate, with the combined incidence being 0.08 (0.07, 0.09) and the parameter α being -2.442 for the logistic model. The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7602 individuals who had medical checkups and were followed up for at least once. External validation results showed that the predictive model had an area under curve (AUC) of 0.794 (0.771, 0.816), accuracy of 74.5%, sensitivity of 71.0%, and specificity of 74.7% in the 7602 individuals. Conclusion: The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.

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Although the negative association of tobacco smoking with osteoporosis is well-documented, little is known regarding the shared genetic basis underlying these conditions. In this study, we aim to investigate a shared genetic architecture between smoking and heel estimated bone mineral density (eBMD), a reliable proxy for osteoporosis. We conducted a comprehensive genome-wide cross-trait analysis to identify genetic correlation, pleiotropic loci and causal relationship of smoking with eBMD, leveraging summary statistics of the hitherto largest genome-wide association studies conducted in European ancestry for smoking initiation (Nsmoker = 1 175 108, Nnonsmoker = 1 493 921), heaviness (cigarettes per day, N = 618 489), cessation (Ncurrent smoker = 304 244, Nformer smoker = 843 028), and eBMD (N = 426 824). A significant negative global genetic correlation was found for smoking cessation and eBMD (${r}_g$ = -0.051, P = 0.01), while we failed to identify a significant global genetic correlation of smoking initiation or heaviness with eBMD. Partitioning the whole genome into independent blocks, we observed 6 significant shared local signals for smoking and eBMD, with 22q13.1 showing the strongest regional genetic correlation. Such a genetic overlap was further supported by 71 pleiotropic loci identified in the cross-trait meta-analysis. Mendelian randomization identified no causal effect of smoking initiation (beta = -0.003 g/cm2, 95% CI = -0.033 to 0.027) or heaviness (beta = -0.017 g/cm2, 95% CI = -0.072 to 0.038) on eBMD, but a putative causal effect of genetic predisposition to being a current smoker was associated with a lower eBMD compared to former smokers (beta = -0.100 g/cm2, 95% CI = -0.181 to -0.018). Our study demonstrates a pronounced biological pleiotropy as well as a putative causal link between current smoking status and eBMD, providing novel insights into the primary prevention and modifiable intervention of osteoporosis by advocating individuals to avoid, reduce or quit smoking as early as possible.

We conducted a comprehensive genome-wide cross-trait analysis to investigate the shared genetic basis and causal relationship underlying smoking and osteoporosis. Our findings revealed that smoking and eBMD are inherently linked through biological pleiotropy. Importantly, our study discovered that quitting smoking significantly reduced the risk of lower eBMD. We recommend individuals to avoid, reduce, or quit smoking as early as possible to protect bone health.

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This study investigates the influence of N-methyl-D-aspartate receptor (NMDAR) antagonists on the mismatch negativity (MMN) components of event-related potentials (ERPs) in healthy subjects and explores whether NMDAR antagonists have different effects on MMN components under different types of antagonists, drug dosages, and deviant stimuli. We conducted a comprehensive literature search of PubMed, EMBASE, and the Cochrane Library from inception to August 1, 2023 for studies comparing the MMN components between the NMDAR antagonist intervention group and the control group (or baseline). All statistical analyses were performed using Stata version 12.0 software. Sixteen articles were included in the systematic review: 13 articles were included in the meta-analysis of MMN amplitudes, and seven articles were included in the meta-analysis of MMN latencies. The pooled analysis showed that NMDAR antagonists reduced MMN amplitudes [SMD (95% CI) = 0.32 (0.16, 0.47), P < 0.01, I2 = 47.3%, p < 0.01] and prolonged MMN latencies [SMD (95% CI) = 0.31 (0.13, 0.49), P = 0.16, I2 = 28.3%, p < 0.01]. The type of antagonist drug regulates the effect of NMDAR antagonists on MMN amplitudes. Different antagonists, doses of antagonists, and types of deviant stimuli can also have different effects on MMN. These findings indicate a correlation between NMDAR and MMN, which may provide a foundation for the application of ERP-MMN in the early identification of NMDAR encephalitis.

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Little is known regarding the long-term adverse effects of COVID-19 on female-specific cancers, nor the shared genetic influences underlying these conditions. We performed a comprehensive genome-wide cross-trait analysis to investigate the shared genetic architecture between COVID-19 (infection, hospitalization, and critical illness) with three female-specific cancers (breast cancer (BC), epithelial ovarian cancer (EOC), and endometrial cancer (EC)). We identified significant genome-wide genetic correlations with EC for both hospitalization (rg = 0.19, p = 0.01) and critical illness (rg = 0.29, p = 3.00 × 10-4). Mendelian randomization demonstrated no valid association of COVID-19 with any cancer of interest, except for suggestive associations of genetically predicted hospitalization (ORIVW = 1.09, p = 0.04) and critical illness (ORIVW = 1.06, p = 0.04) with EC risk, none withstanding multiple correction. Cross-trait meta-analysis identified 20 SNPs shared between COVID-19 with BC, 15 with EOC, and 5 with EC; and transcriptome-wide association studies revealed multiple shared genes. Findings support intrinsic links underlying these complex traits, highlighting shared mechanisms rather than causal associations.

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While a higher level of physical activity (PA) is inversely associated with a higher breast cancer (BC) risk, the health benefits of daily steps on obesity-related BC biomarkers remain unclear. We aimed to understand the associations of changes in step counts with levels of five obesity-related BC biomarkers during a two-year follow-up. In total, 144 non-cancer women (47.96 ± 5.72) were observed on both 2019 and 2021. A structured questionnaire, daily steps and fasting blood samples were collected before (t0, 2019) and after (t1, 2021). Levels of biomarkers (IGF-binding proteins 3, adiponectin, soluble leptin receptor, C-reactive protein, and resistin) were assayed by ELISA. Participants were divided into persistent low steps, decreasing steps, increasing steps, and persistent high steps. Associations of categories on proposed biomarkers were estimated using linear regression models, with persistent low steps as reference. Associations between time-varying step counts with biomarkers were quantified using mixed linear models. Compared with persistent low steps, increasing steps is associated with a reduction in C-reactive protein level (ß=-0.74, 95%CI=-1.23--0.26, P-value = 2.98 × 10-3). An inverse association between time-varying step counts with C-reactive protein level was identified, consistent across different obesity types and baseline step level categories. No association with daily step counts was observed for other proteins.

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BACKGROUND: Inflammatory adipokines and cytokines play a pivotal role in linking obesity and breast cancer (BC) risk in women. We investigated the longitudinal associations between BMI change and trajectories of inflammatory biomarkers related to BC risk. METHODS: A longitudinal study was conducted among 442 Chinese women with 3-year repeated measures from 2019 to 2021. Plasma circulating inflammatory biomarkers related to BC risk, including adiponectin (ADP), resistin (RETN), soluble leptin receptor (sOB-R), insulin-like growth factor-binding protein-3 (IGFBP-3), and C-reactive protein (CRP), were examined annually. Linear mixed-effect models (LMM) were applied to investigate associations of time-varying BMI with trajectories of biomarkers. We additionally examined the modification effect of baseline BMI groups, menopausal status, and metabolic syndrome. RESULTS: BMI was associated with increased levels of RETN, CRP, sOB-R, and decreased levels of ADP at baseline. An increasing BMI rate was significantly associated with an average 3-year increase in RETN (ß = 0.019, 95% CI 0.004 to 0.034) and sOB-R (ß = 0.022, 95% CI 0.009 to 0.035), as well as a decrease in ADP (ß = - 0.006, 95% CI - 0.012 to 0.001). These associations persisted across different baseline BMI groups. An increasing BMI rate was significantly associated with an average 3-year increase in CRP levels among normal weight (ß = 0.045, 95% CI 0.001 to 0.088) and overweight (ß = 0.060, 95% CI 0.014 to 0.107) women. As BMI increased over time, a more remarkable decrease in ADP was observed among women with metabolic syndrome (ß = - 0.016, 95% CI - 0.029 to - 0.004) than those without metabolic syndrome at baseline. CONCLUSIONS: A higher increase rate of BMI was associated with poorer trajectories of inflammatory biomarkers related to BC risk. Recommendations for BMI reduction may benefit BC prevention in women, particularly for those with metabolic syndrome.

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Little is known regarding the shared genetic influences underlying the observed phenotypic association between chronotype and breast cancer in women. Leveraging summary statistics from the hitherto largest genome-wide association study conducted in each trait, we investigated the genetic correlation, pleiotropic loci, and causal relationship of chronotype with overall breast cancer, and with its subtypes defined by the status of oestrogen receptor. We identified a negative genomic correlation between chronotype and overall breast cancer ( r g $$ {r}_g $$ = -0.06, p = 3.00 × 10-4 ), consistent across oestrogen receptor-positive ( r g $$ {r}_g $$ = -0.05, p = 3.30 × 10-3 ) and oestrogen receptor-negative subtypes ( r g $$ {r}_g $$ = -0.05, p = 1.11 × 10-2 ). Five specific genomic regions were further identified as contributing a significant local genetic correlation. Cross-trait meta-analysis identified 78 loci shared between chronotype and breast cancer, of which 23 were novel. Transcriptome-wide association study revealed 13 shared genes, targeting tissues of the nervous, cardiovascular, digestive, and exocrine/endocrine systems. Mendelian randomisation demonstrated a significantly reduced risk of overall breast cancer (odds ratio 0.89, 95% confidence interval 0.83-0.94; p = 1.30 × 10-4 ) for genetically predicted morning chronotype. No reverse causality was found. Our work demonstrates an intrinsic link underlying chronotype and breast cancer, which may provide clues to inform management of sleep habits to improve female health.

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BACKGROUND: Both depression and breast cancer (BC) contribute to a substantial global burden of morbidity and mortality among women, and previous studies have observed a potential depression-BC link. We aimed to comprehensively characterize the phenotypic and genetic relationships between depression and BC. METHODS: We first evaluated phenotypic association using longitudinal follow-up data from the UK Biobank (N = 250,294). We then investigated genetic relationships leveraging summary statistics from the hitherto largest genome-wide association study of European individuals conducted for depression (N = 500,199), BC (N = 247,173), and its subtypes based on the status of estrogen receptor (ER + : N = 175,475; ER - : N = 127,442). RESULTS: Observational analysis suggested an increased hazard of BC in depression patients (HR = 1.10, 95%CIs = 0.95-1.26). A positive genetic correlation between depression and overall BC was observed ([Formula: see text] = 0.08, P = 3.00 × 10-4), consistent across ER + ([Formula: see text] = 0.06, P = 6.30 × 10-3) and ER - subtypes ([Formula: see text] = 0.08, P = 7.20 × 10-3). Several specific genomic regions showed evidence of local genetic correlation, including one locus at 9q31.2, and four loci at, or close, to 6p22.1. Cross-trait meta-analysis identified 17 pleiotropic loci shared between depression and BC. TWAS analysis revealed five shared genes. Bi-directional Mendelian randomization suggested risk of depression was causally associated with risk of overall BC (OR = 1.12, 95%Cis = 1.04-1.19), but risk of BC was not causally associated with risk of depression. CONCLUSIONS: Our work demonstrates a shared genetic basis, pleiotropic loci, and a putative causal relationship between depression and BC, highlighting a biological link underlying the observed phenotypic relationship; these findings may provide important implications for future studies aimed reducing BC risk.

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PURPOSE: While crudely quantified lipoproteins have been reported to affect the risk of breast cancer, the effects of subclass lipoproteins characterized by particle size, particle number, and lipidomes remain unknown. METHODS: Utilizing nuclear magnetic resonance-based GWAS of 85 lipoprotein traits, we performed two-sample univariable Mendelian randomization (MR) to evaluate the causal relationship between each trait with breast cancer (Ncase/control = 133,384/113,789) and with its estrogen receptor (ER) subtypes. Then, we applied multivariable MR to investigate the independent effects considering both general and central obesity. RESULTS: In univariable MR, a heterogeneous effect of subclass high-density lipoproteins (HDL) was observed, in which small HDL traits (ORs ranged from 0.89 to 0.94) were associated with a decreased risk of breast cancer while non-small HDLs traits (OR ranged from 1.04 to 1.08) were associated with an increased risk of breast cancer. Very-low-density lipoproteins (VLDL) traits and serum total triglycerides (TG) were associated with a decreased risk of breast cancer (ORs ranged from 0.88 to 0.94). Similar association patterns were found for ER + subtype. In multivariable MR, only the protective effects of small HDL, VLDL and TG on ER + subtype remained significant. CONCLUSION: We identified a heterogeneous effect of subclass HDLs and a consistent protective effect of VLDL on breast cancer. Only the effects of small HDL and VLDL on ER + subtype remained robust after controlling for obesity. These findings provide new insight into the causal pathway underlying lipoproteins and breast cancer.

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BACKGROUND: Previous Mendelian randomization (MR) studies on obesity and risk of breast cancer adopted a small number of instrumental variables and focused mainly on the crude total effect. We aim to investigate the independent causal effect of obesity on breast cancer susceptibility, considering the distribution of fat, covering both early and late life. METHODS: Using an enlarged set of female-specific genetic variants associated with adult general [body mass index (BMI)] and abdominal obesity [waist-to-hip ratio (WHR) with and without adjustment for BMI, WHR and WHRadjBMI] as well as using sex-combined genetic variants of childhood obesity (childhood BMI), we performed a two-sample univariable MR to re-evaluate the total effect of each obesity-related exposure on overall breast cancer (Ncase = 133 384, Ncontrol = 113 789). We further looked into its oestrogen receptor (ER)-defined subtypes (NER+ = 69 501, NER- = 21 468, Ncontrol = 105 974). Multivariable MR was applied to estimate the independent causal effect of each obesity-related exposure on breast cancer taking into account confounders as well as to investigate the independent effect of adult and childhood obesity considering their inter-correlation. RESULTS: In univariable MR, the protective effects of both adult BMI [odds ratio (OR) = 0.89, 95% CI = 0.83-0.96, P = 2.06 × 10-3] and childhood BMI (OR = 0.78, 95% CI = 0.70-0.87, P = 4.58 × 10-6) were observed for breast cancer overall. Comparable effects were found in ER+ and ER- subtypes. Similarly, genetically predicted adult WHR was also associated with a decreased risk of breast cancer overall (OR = 0.87, 95% CI = 0.80-0.96, P = 3.77 × 10-3), restricting to ER+ subtype (OR = 0.88, 95% CI = 0.80-0.98, P = 1.84 × 10-2). Conditional on childhood BMI, the effect of adult general obesity on breast cancer overall attenuated to null (BMI: OR = 1.00, 95% CI = 0.90-1.10, P = 0.96), whereas the effect of adult abdominal obesity attenuated to some extent (WHR: OR = 0.90, 95% CI = 0.82-0.98, P = 1.49 × 10-2; WHRadjBMI: OR = 0.92, 95% CI = 0.86-0.99, P = 1.98 × 10-2). On the contrary, an independent protective effect of childhood BMI was observed in breast cancer overall, irrespective of adult measures (adjusted for adult BMI: OR = 0.84, 95% CI = 0.77-0.93, P = 3.93 × 10-4; adjusted for adult WHR: OR = 0.84, 95% CI = 0.76-0.91, P = 6.57 × 10-5; adjusted for adult WHRadjBMI: OR = 0.80, 95% CI = 0.74-0.87, P = 1.24 × 10-7). CONCLUSION: Although successfully replicating the inverse causal relationship between adult obesity-related exposures and risk of breast cancer, our study demonstrated such effects to be largely (adult BMI) or partly (adult WHR or WHRadjBMI) attributed to childhood obesity. Our findings highlighted an independent role of childhood obesity in affecting the risk of breast cancer as well as the importance of taking into account the complex interplay underlying correlated exposures.

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Background: The relationship between type 2 diabetes mellitus (T2DM) and gallstone disease (GSD) have been incompletely understood. We aimed to investigate their phenotypic and genetic associations and evaluate the biological mechanisms underlying these associations. Methods: We first evaluated the phenotypic association between T2DM and GSD using data from the UK Biobank (n>450,000) using a prospective observational design. We then conducted genetic analyses using summary statistics from a meta-analysis of genome-wide association studies of T2DM, with and without adjusting for body mass index (BMI) (Ncase=74,124, Ncontrol=824,006; T2DMadjBMI: Ncase=50,409, Ncontrol=523,897) and GSD (Ncase=43,639, Ncontrol=506,798). Results: A unidirectional phenotypic association was observed, where individuals with T2DM exhibited a higher GSD risk (hazard ratio (HR)=1.39, P<0.001), but not in the reverse direction (GSD→T2DM: HR=1.00, P=0.912). The positive T2DM-GSD genetic correlation (rg=0.35, P=7.71×10-23) remained even after adjusting for BMI (T2DMadjBMI: rg=0.22, P=4.48×10-10). Mendelian randomization analyses provided evidence of a unidirectional causal relationship (T2DM→GSD: odds ratio (OR)=1.08, P=4.6×10-8; GSD→T2DM: OR=1.02, P=0.48), even after adjusting for important metabolic confounders (OR=1.02, P=0.02). This association was further corroborated through a comprehensive functional analysis reflected by 23 pleiotropic single nucleotide polymorphisms, as well as multiple neural and motor-enriched tissues. Conclusion: Through comprehensive observational and genetic analyses, our study clarified the causal relationship between T2DM and GSD, but not in the reverse direction. These findings might provide new insights into prevention and treatment strategies for T2DM and GSD.

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Little is known regarding the shared genetic architecture or causality underlying the phenotypic association observed for uterine leiomyoma (UL) and breast cancer (BC). Leveraging summary statistics from the hitherto largest genome-wide association study (GWAS) conducted in each trait, we investigated the genetic overlap and causal associations of UL with BC overall, as well as with its subtypes defined by the status of estrogen receptor (ER). We observed a positive genetic correlation between UL and BC overall (rg = 0.09, p = 6.00 × 10-3), which was consistent in ER+ subtype (rg = 0.06, p = 0.01) but not in ER- subtype (rg = 0.06, p = 0.08). Partitioning the whole genome into 1,703 independent regions, local genetic correlation was identified at 22q13.1 for UL with BC overall and with ER+ subtype. Significant genetic correlation was further discovered in 9 out of 14 functional categories, with the highest estimates observed in coding, H3K9ac, and repressed regions. Cross-trait meta-analysis identified 9 novel loci shared between UL and BC. Mendelian randomization demonstrated a significantly increased risk of BC overall (OR = 1.09, 95% CI = 1.01-1.18) and ER+ subtype (OR = 1.09, 95% CI = 1.01-1.17) for genetic liability to UL. No reverse causality was found. Our comprehensive genome-wide cross-trait analysis demonstrates a shared genetic basis, pleiotropic loci, as well as a putative causal relationship between UL and BC, highlighting an intrinsic link underlying these two complex female diseases.

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The Chinese government has set long-term carbon neutrality and renewable energy (RE) development goals for the power sector. Despite a precipitous decline in the costs of RE technologies, the external costs of renewable intermittency and the massive investments in new RE capacities would increase electricity costs. Here, we develop a power system expansion model to comprehensively evaluate changes in the electricity supply costs over a 30-year transition to carbon neutrality. RE supply curves, operating security constraints, and the characteristics of various generation units are modelled in detail to assess the cost variations accurately. According to our results, approximately 5.8 TW of wind and solar photovoltaic capacity would be required to achieve carbon neutrality in the power system by 2050. The electricity supply costs would increase by 9.6 CNY¢/kWh. The major cost shift would result from the substantial investments in RE capacities, flexible generation resources, and network expansion.

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PURPOSE: Previous studies have confirmed that patients with obstructive sleep apnea (OSA) have higher systemic inflammatory markers, including intercellular adhesion molecule-1(ICAM-1), vascular cell adhesion molecule-1(VCAM-1), and E-selectin compared to control subjects. However, the effects of continuous positive airway pressure (CPAP) therapy on circulating levels of ICAM-1, VCAM-1, and E-selectin in OSA patients remain inconsistent. Therefore, the primary purpose of the present meta-analysis is to estimate the effect of CPAP therapy on these cell adhesion molecules (CAMs) in patients with OSA. METHODS: The PubMed, Scopus, Embase, and Cochrane Library databases were searched. The overall effects were measured by the standardized mean difference (SMD) with a 95% confidence interval (CI). A random effects model or a fixed-effects model was used, depending on the heterogeneity of the studies. RESULTS: A total of 11 studies were included, comprising 650 OSA patients. The pooled results showed that CPAP therapy significantly decreased ICAM-1 (SMD = - 0.283, 95% CI - 0.464 to - 0.101, p = 0.002) and E-selectin levels (SMD = - 0.349, 95% CI - 0.566 to - 0.133, p = 0.002). In contrast, there was no significant improvement of VCAM-1 levels after CPAP treatment (SMD = - 0.160, 95% CI - 0.641 to 0.320, p = 0.513). CONCLUSIONS: Our meta-analysis demonstrated that CPAP treatment significantly decreased the circulating levels of ICAM-1 and E-selectin in OSA patients. Thus, ICAM-1 and E-selectin may be effective markers to evaluate CPAP therapy for reducing OSA cardiovascular risk in clinical practice.

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Epilepsy is a common neurological disease that affects more than 50 million people worldwide. Neuro-inflammation plays an important role in epilepsy. Activation of the immune system and an excessive inflammatory response can increase the frequency of seizures and increase the susceptibility to epilepsy. Therefore, anti-inflammatory therapies may have antiepileptic effects. Connexin 43 (Cx43) is a major component of astroglial hemichannels and gap junctions. Gap junctions are important for the direct exchange of substances and information between cells, as well as regulating the neuroinflammatory response, changing neuronal excitability, neuronal apoptosis, and synaptic remodeling. Cx43-mediated gap junction pathway can be crucial in epilepsy-induced neuroinflammatory cascades. Further, pro-inflammatory cytokines may in turn directly affect the expression of the Cx43 protein in astrocytes. Therefore, examining the association between neuroinflammation and epilepsy can be instrumental in uncovering the pathogenesis of epilepsy, which can lead to the development of novel and more effective antiepileptic drugs.

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Salt-leaching is considered to be a major method for soil desalting in agriculture. Therefore, conservation of soil nutrition is significant to soil fertility and environment protection during the salt-leaching process. The effect of poly-γ-glutamic acid bioproduct (PGAB), which was manufactured by solid-state fermentation with the bacteria producing glutamic acid (GA) and poly-γ-glutamic acid (γ-PGA) and organic waste, on keeping nitrogen (N) during salt-leaching was investigated in this study. The isolated bacteria producing GA and γ-PGA were identified as Brevibacterium flavum and Bacillus amyloliquefaciens, respectively. After the saline soil was leached for 90 days, compared to the control, soil salinity (0-30 cm) in the PGAB treatment was decreased by 39.9%, while soil total N was significantly (P < 0.05) higher than other treatments. Furthermore, the microbial biomass N (0-30 cm) in PGAB treatment was increased by 119.5%; populations of soil total bacteria, fungi, actinomyces, nitrogen-fixing bacteria, ammonifying bacteria, nitrifying bacteria, and denitrifying bacteria and soil algae biomass were also significantly (P < 0.05) increased. In terms of physical properties, the percentage of soil aggregates with diameter > 0.25 mm was increased by 293.5%, and the soil erosion-resistance coefficient was increased by 50.0%. In conclusion, the PGAB can effectively conserve soil N during the process of salt-leaching and therefore offer a sustainable way to improve coastal saline soil.

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The dorsal raphe nucleus (DRN) is a key site for 5-hydroxytryptamine (5-HT) synthesis and release. DRN dysfunction has been implicated in several stress-related disorders, including depression and anxiety. The lateral habenular nucleus (LHb) has been shown to inhibit the activity of DRN 5-HT neurons, and thus the LHb-DRN pathway plays an important role in the pathogenesis of depression. Although it is known that the LHb also receives the projection from the 5-HT neuron in the DRN, whether 5-HT neurons in the DRN can influence activity of the LHb in vivo and whether this effect is related to the induced behavioral changes have not been investigated. In the current study, we determined how injecting γ-aminobutyric acid (GABA) into the DRN to inhibit 5-HT neurons affected behavior and the changes in the activity of LHb neurons in mice. We found that GABA injection into the DRN induced depression-like behavior in mice, as indicated by increased immobility time, and decreased climbing time in the forced swimming test and the tail suspension test, decreased time spent in the center and total distance moved in the open field test. Using extracellular single unit recording, we showed that the firing rate of LHb neurons decreased after GABA microinjection into the DRN. Further, c-Fos expression in LHb neurons was inhibited. Together our results indicate that inhibition of DRN 5-HT neurons can cause decreased LHb activity and depression-like behavior in mice, however this depression-like behavior could be independent of the LHb activity. The observed decrease in LHb activity is probably due to the presence of a negative feedback loop between the DRN and the LHb, which may play a role in maintaining emotional homeostasis.

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The suprachiasmatic nucleus plays an important role in generating circadian rhythms in mammals. The lateral habenular nucleus (LHb) is closely linked to this structure. Interestingly, the LHb shows a rhythmic firing rate in vivo and in vitro, and sustained oscillation of rhythmic genes in vitro. However, under the in vivo condition, whether rhythmic gene expression in the LHb has circadian rhythms remains unknown. In this study, we examined LHb tissue in rats to determine Period2 (Per2) gene and protein expression at six zeitgeber time points (ZT2, ZT6, ZT10, ZT14, ZT18, and ZT22) in a 12-h light and 12-h dark (LD) environment. We found that in the LD environment, Per2 gene expression and PER2 protein levels in the LHb were higher in the day and lower in the night, showing periodic oscillation, with a peak at ZT10 and a trough at ZT22 (Per2 mRNA) and ZT18 (PER2 protein). We conclude that Per2 expression and PER2 protein levels in the LHb have rhythmic oscillation in vivo. This study provides a basis for further study on the role of the LHb in the circadian rhythm system.

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