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To bolster the dual-circulation development model and green economy, this study delves into the spatiotemporal dynamics of implied carbon transfer in China’s inter-provincial and inter-industrial trade, emphasizing its significance for the \"dual carbon\" objectives. Utilizing multi-regional input-output data from 2012, 2015, and 2017, we employed the multi-region input-output model to gauge embodied carbon transfers across 31 provinces and 28 industries. The Structural Decomposition Analysis (SDA) model further decomposed the growth of trade-related carbon emissions. Key findings include: (1) The electricity and thermal power sectors dominate carbon transfers, with secondary industries seeing rapid growth; (2) Northern provinces significantly outweigh southern ones in carbon transfers and the main direction of it is towards affluent southern coastal regions; (3) Scale effect plays a pivotal role in these transfers. Conclusively, it is crucial for regulatory authorities to rationally formulate region-specific emission policies for inter-regional coordination, and future studies can focus on industrial and spatial clustering effects.

Cholera, as an acute, high-risk and widespread infectious disease, has been studied by many scholars. Based on the data from , this research investigated the spatial distribution of the cholera epidemic and natural environment mechanism of the cholera epidemic in the Jiangnan area, from the year 1820 to 1821. We applied a set of spatial statistical analyses to investigate the spatial heterogeneity and the factors that influence the cholera epidemic in the Jiangnan area. Results show that: 1) Spatial distribution of cholera epidemic lied at different geographical scales. The cholera epidemic was highly concentrated in Shanghai, Nanjing and Hangzhou; There was a north-south difference of cholera epidemic distribution at the regional scale. The cholera epidemic was more concentrated in the north part than in the south part of the Jiangnan area; Meanwhile, there was an east-west difference in cholera epidemic distribution where the intensity of the cholera epidemic decreased from east to northwest and southwest. 2) A land-sea distribution of cholera can be also found. The Chang-Hang line and the Hu-Jia line were the two boundaries of the cholera epidemic in the Jiangnan area. 3) There was a close relationship between the distribution of the cholera epidemic and natural environment in the Jiangnan area. The influence intensity of natural factors on epidemic disasters followed the order of temperature (0.760) > precipitation (0.663) > river distance (0.413) > river density (0.398) > elevation (0.395). The present investigation is conductive to establish a prevention system for public health emergencies, which contributes to the sustainable development of society and human health.

Plasma cell-free DNA (cfDNA) are small molecules generated through a non-random fragmentation procedure. Despite commendable translational values in cancer liquid biopsy, however, the biology of cfDNA, especially the principles of cfDNA fragmentation, remains largely elusive. Through orientation-aware analyses of cfDNA fragmentation patterns against the nucleosome structure and integration with multidimensional functional genomics data, here we report a DNA methylation – nuclease preference – cutting end – size distribution axis, demonstrating the role of DNA methylation as a functional molecular regulator of cfDNA fragmentation. Hence, low-level DNA methylation could increase nucleosome accessibility and alter the cutting activities of nucleases during DNA fragmentation, which further leads to variation in cutting sites and size distribution of cfDNA. We further develop a cfDNA ending preference-based metric for cancer diagnosis, whose performance has been validated by multiple pan-cancer datasets. Our work sheds light on the molecular basis of cfDNA fragmentation towards broader applications in cancer liquid biopsy. Cell free DNA is produced through a non-random process. Here, the authors use orientation-aware fragmentation analysis to identify DNA methylation as a regulator of nuclease function.

Background The NLRP3 inflammasome activation and neuroinflammation are known to be involved in the pathology of depression, whereas autophagy has multiple effects on immunity, which is partly mediated by the regulation of inflammasome and clearance of proinflammatory cytokines. Given the emerging evidence that autophagy dysfunction plays an essential role in depression, it is very likely that autophagy may interact with the inflammatory process in the development and treatment of depression. Salvianolic acid B (SalB), a naturally occurring compound extracted from Salvia miltiorrhiza , contains anti-inflammatory and antidepression properties and has recently been proven to modulate autophagy. In this study, we sought to investigate whether autophagy is involved in the inflammation-induced depression and the antidepressant effects of SalB. Methods The effects of prolonged lipopolysaccharide (LPS) treatment and SalB administration on behavioral changes, neuroinflammation, autophagic markers and NLRP3 activation in rat hippocampus were determined by using behavioral tests, real-time PCR analysis, western blot, and immunostaining. Results Our data showed that periphery immune challenge by LPS for 2 weeks successfully induced the rats to a depression-like state, accompanied with enhanced expression of pro-inflammatory cytokines and NLRP3 inflammasome activation. Interestingly, autophagic markers, including Beclin-1, and the ratio of LC3II to LC3I were suppressed following prolonged LPS exposure. Meanwhile, co-treatment with SalB showed robust antidepressant effects and ameliorated the LPS-induced neuroinflammation. Additionally, SalB restored the compromised autophagy and overactivated NLRP3 inflammasome in LPS-treated rats. Conclusions Collectively, these data suggest that autophagy may interact with NLRP3 activation to contribute to the development of depression, whereas SalB can promote autophagy and induce the clearance of NLRP3, thereby resulting in neuroprotective and antidepressant actions.

Background The present study aimed to further explore the potential interaction between oxidative stress and autophagy in the progression of traumatic brain injury (TBI) and therapeutic mechanism of calcitriol, the active form of vitamin D (VitD). Methods Neuroprotective effects of calcitriol were examined following TBI. We further evaluated the impacts of TBI and calcitriol treatment on autophagic process and nuclear factor E2-related factor 2 (Nrf2) signaling. Results We found that treatment of calcitriol markedly ameliorated the neurological deficits and histopathological changes following TBI. The brain damage impaired autophagic flux and impeded Nrf2 signaling, the major regulator in antioxidant response, consequently leading to uncontrolled and excessive oxidative stress. Meanwhile, calcitriol promoted autophagic process and activated Nrf2 signaling as evidenced by the reduced Keap1 expression and enhanced Nrf2 translocation, thereby mitigating TBI-induced oxidative damage. In support, we further found that chloroquine (CQ) treatment abrogated calcitriol-induced autophagy and compromised Nrf2 activation with increased Keap1 accumulation and reduced expression of Nrf2-targeted genes. Additionally, both CQ treatment and Nrf2 genetic knockout abolished the protective effects of calcitriol against both TBI-induced neurological deficits and neuronal apoptosis. Conclusions Therefore, our work demonstrated a neuroprotective role of calcitriol in TBI by triggering Nrf2 activation, which might be mediated by autophagy.

IntroductionThe factors that significantly and negatively impact carbon dioxide (CO2) emissions and coastal water quality (CWQ) must be continuously monitored and thoroughly evaluated. Among these, tourism (TR) volume stands out as one of the primary contributors to such effects. In contrast, green fiscal policy (GFP) and fintech (FT) can be considered proactive and modern efforts contributing to the improvement of these environmental indicators. Exploring whether the impacts of these factors exhibit uniformity across quantiles will greatly benefit strategic solutions aimed at avoiding resource waste.MethodsThis paper aims to calibrate procedures to apply the method of moment quantile regression (MMQR) model to address this issue. Firstly, cross-sectional dependence (CSD) among the variables is examined. Next, a stable long-term relationship between the variables is assessed using stationarity analysis. Finally, the MMQR estimation is conducted to thoroughly investigate the impact of independent variables on CWQ and CO2 across different quantiles.ResultsThe results from both the fixed effects (FE-OLS) and dynamic ordinary least squares (D-OLS) models reveal stable and significant correlations between the regressors and response variables. The research findings indicate that GFP and FT exert a significant impact on improving both CWQ and reducing CO2. In contrast, the favorable growth of the TR sector contributes negatively to CWQ and CO2.DiscussionThe paper recommends that the government increase spending and investment in green projects utilizing renewable energy, green transportation, blockchain technology, and advanced techniques. It also advocates for a strategic approach to controlling TR, focusing on enhanced waste management, in order to improve CWQ and CO2 indicators across most quantiles.

Some studies have shown that plasma metabolites may be associated with myocardial infarction (MI); however, the causal relationship between plasma metabolites and MI, as well as the potential mediating role of immune cells, remains unclear. This Mendelian randomisation (MR) study utilised large-scale genome-wide association study (GWAS) summary data encompassing 1400 plasma metabolites (n = 8299), 731 immune cell traits from the GWAS Catalog consortium (n = 3757), and MI cases and controls from the FinnGen consortium (cases: n = 26,060; controls: n = 343,079). Using bidirectional MR analysis, we assessed the causal links between plasma metabolites and MI, and between immune cells and MI, excluding reverse causality. Five MR methods were applied, with inverse variance weighting used as the primary analytical approach. In addition, we conducted two-step MR to identify potential immune cell mediators. We identified 44 positive and 33 negative causal associations between genetic liability to plasma metabolites and MI. Of these, only the association between 3β-hydroxy-5-cholestenoate (OR = 0.909; 95% CI 0.871–0.950; P = 1.84 × 10 –5 ) and MI remained statistically significant after Bonferroni correction. Additionally, eight positive and five negative causal associations were observed between immune cells and MI. Among them, HLA-DR on dendritic cells (OR = 1.039; 95% CI 1.020–1.057; P = 2.84 × 10 –5 ) and HLA-DR on plasmacytoid dendritic cells (OR = 1.031; 95% CI 1.016–1.047; P = 4.33 × 10 –5 ) were identified as risk factors for MI after correction. Notably, bidirectional MR revealed that the glutamine conjugate of C6H10O2 (1) (OR = 1.125; 95% CI 1.042–1.215; P = 0.003) was causally associated with increased MI risk, with no evidence of reverse causality or heterogeneity. In the two-step MR analysis, positive associations were found between this metabolite and HLA-DR on CD33-HLA-DR + cells (OR = 1.302; 95% CI 1.014–1.671; P = 0.038), and between the immune trait HLA-DR on CD33-HLA-DR + (OR = 1.035; 95% CI 1.010–1.060; P = 0.005) and MI. Furthermore, mediation analysis indicated that 7.68% of the effect of the metabolite on MI was mediated through HLA-DR on CD33-HLA-DR + . Plasma metabolites and immune cells demonstrated causal associations with myocardial infarction. Moreover, immune cells acted as mediators in the causal pathway from plasma metabolites to myocardial infarction.

Massive multiple‐input multiple‐output and non‐orthogonal multiple access (MIMO‐NOMA) with low‐resolution analog‐to‐digital converters (ADCs) have been widely considered for the next‐generation wireless communication systems. However, the performance of the system including power‐scaling law has not been well investigated for the practical low complexity receivers. Employing the additive quantization noise model, we derive asymptotic approximate expressions of the spectrum efficiency for the system with group successive interference cancellation (GSIC) receivers over Rician fading channels. Based on these approximations, we conduct a unified asymptotic analysis for the system with linear, SIC, and GSIC receivers. The analysis reveals the transmission power can be scaled by the number of antennas for the system with GSIC receivers and shows the effects of crucial parameters including the number of groups, resolution bits, and antennas on the performance. Given a quality of service, the minimum data transmission power is also calculated for each user and the corresponding approximate power allocation is derived. The asymptotic analysis and the accuracy of the power allocation approximation are then verified by simulation results. Numerical results also demonstrate that high spectrum efficiency and energy efficiency can be achieved by the system with medium‐resolution ADCs and low complexity maximum ratio combining‐GSIC receivers with a small number of groups. This paper studies the performance of massive multiple‐input multiple‐output and non‐orthogonal multiple access systems with group successive interference cancellation receivers using low‐resolution analog‐to‐digital converters. For the implementation concern, a fast power allocation scheme is designed for a given quality of service.

Background Several previous observational studies have shown that abnormal sphingomyelin metabolism may be implicated in the pathogenesis of Alzheimer’s disease. To determine the causal relationship between sphingolipid abundance and gut microbiota abundance at the genetic level, we conducted a Mendelian randomization (MR) investigation. Methods We first used the TwoSampleMR and MRPRESSO packages for conducting two-sample MR studies. Second, we utilized random effect inverse variance weighting (IVW) as the principal method of analysis and used MR‒Egger, the weighted median, the simple mode and the weighted mode as supplementary methods. Finally, we performed tests for heterogeneity and horizontal pleiotropy. These analyses were also conducted to evaluate the impact of individual SNPs on the outcomes of our analysis. A Bonferroni-corrected threshold of p  = 2.4e-4(0.05/211) was considered significant, and p values less than 0·05 were considered to be suggestive of an association. Results The results showed that sphingolipid levels were suggestively associated with the abundance of 6 gut microbiota taxa. Specifically, two taxa were positively correlated with sphingolipid levels, including the family Alcaligenaceae ( p  = 0.006, OR 95% CI = 1.109 [1.030–1.194]) and the species Ruminococcus callidus ( p  = 0.034, OR 95% CI = 1.217 [1.015–1.460]). In contrast, negative correlations were observed with the abundances of 4 gut microbiota taxa, including the genus Flavonifractor ( p  = 0.026, OR 95% CI = 0.804 [0.663–0.974]), the genus Streptococcus ( p  = 0.014, OR 95% CI = 0.909 [0.842–0.981]), the species Bacteroides caccae ( p  = 0.037, OR 95% CI = 0.870 [0.763–0.992]), and the species Haemophilus parainfluenzae ( p  = 0.006, beta 95% CI = -0.269 [-0.462, -0.076]). The results presented a normal distribution, with no anomalous values, heterogeneity, or horizontal pleiotropic effects detected. Conclusions This two-sample MR study revealed a potential causal relationship between sphingomyelin levels and gut microbiota abundance.

The association between the fluctuation in blood pressure (BP) and the early outcomes of patients with subarachnoid hemorrhage (SAH) remains unclear. Our study aimed to evaluate the value of blood pressure variability (BPV) for predicting the short-term outcomes of patients with acute spontaneous SAH. We collected data from 303 patients hospitalized for acute spontaneous SAH. BP values were recorded at admission and subsequently every 2 h during the initial 24 h of hospitalization. BPV was determined as the standard deviation (SD), the difference between the maximum and the minimum (ΔBP), the coefficient of variation (CV), and successive variation (SV). The outcome at discharge was assessed according to the Glasgow Outcome Scale (GOS). The association between BPV and the outcome was identified by multivariable analysis. The findings showed that the parameters of systolic BPV were independently associated with the outcome in a graded fashion. The odds ratios (OR) for the highest tertiles were as follows: SD 13.9 (95% confidence interval [CI], 4.8-40.4), ΔBP 4.4 (95% CI, 1.6-11.9), CV 16.4 (95% CI, 5.6-48.8), SV 15.8 (95% CI, 5.3-46.9). However, there was no association between a poor outcome and diastolic BPV (all p > 0.05). In conclusion, systolic BPV within the first 24 h after admission was independently associated with the outcomes in SAH patients; the greater the variability was, the worse the outcome.