Electroacupuncture ameliorates chronic unpredictable mild stress-induced depression-like behavior and cognitive impairment through suppressing oxidative stress and neuroinflammation in rats.

BACKGROUND: Depression is associated with lowered mood, anxiety, anhedonia, cognitive impairments, and even suicidal tendencies in severe cases. Yet few studies have directed acupuncture's mechanism toward enhancing axonal repair correlated with synaptic plasticity and anti-inflammatory effects related to oxidative stress in the hippocampus. METHODS: Male Sprague-Dawley (SD) rats were randomly divided into control group (CON), chronic unpredictable mild stress (CUMS) group, CUMS + electroacupuncture group (EA), and CUMS + fluoxetine group (FLX) (n = 10/group). Rats were given a 28-day treatment at the Shangxing (GV23) and Fengfu (GV16) acupoints with electroacupuncture or fluoxetine (2.1 mg/kg). RESULTS: Rats exposed to CUMS induced depression-like behaviors and spatial learning-memory impairment, changed the ionized calcium binding adaptor molecule 1 (IBA-1), Vglut1, myelin basic protein (MBP), and postsynaptic density protein 95 (PSD95) level of hippocampal, increased the Nod-like receptor protein 3 (NLRP3), atypical squamous cell (ASC), Caspase level and hippocampal reactive oxygen species (ROS), and prompted the activation of Epha4-mediated signaling and an inflammatory response. Conversely, electroacupuncture administration reduced these changes and prevented depression-like behaviors and cognitive impairment. Electroacupuncture also promoted hippocampal expression of Sirtuin1(SIRT1), Nuclear factor erythroid 2-like (Nrf2), Heme oxygenase-1 (HO-1); reduced the expression of interleukin-1ß (IL-1ß), interleukin-18 (IL-18), and tumor necrosis factor-alpha (TNF-α); and prevented neural damage, particularly the synaptic myelin sheath, and neuroinflammation by regulating Eph receptor A4 (EphA4) in the hippocampal. CONCLUSION: These results indicate that electroacupuncture prevents depression-like behaviors with cognitive impairment and synaptic and neuronal damage, probably by reducing EphA4, which mediates ROS hyperfunction and the inflammatory response.

Acupuncture alleviates CUMS-induced depression-like behaviors of rats by regulating oxidative stress, neuroinflammation and ferroptosis.

BACKGROUND: The treatment of depression with acupuncture has been documented. The mechanism behind acupuncture's curative and preventative effects is still unknown. METHODS: The current study examined the effects of acupuncture on depression-like behaviors in a rat model of chronic unpredictable mild stress (CUMS), while also exploring its potential mechanisms. A total of six groups of rats were randomly assigned: control, CUMS, acupuncture, fluoxetine, acupoint catgut embedding and sham acupoint catgut embedding. Fluoxetine (2.1 mg/kg) and acupoint catgut embedding were used for comparative research to acupuncture. The modelling evaluation is measured by body weight and behavior tests. Western blotting and reverse transcription-polymerase chain reaction were used to detect the proteins and mRNA expression of Silent information regulator 1 (Sirt1)/ nuclear factor-erythroid 2-related factor 2 (Nrf2)/ heme oxygenase-1 (HO-1)/ Glutathione peroxidase 4 (GPX4) pathway in the hippocampus. The expression of oxidative stress (OS)-related proteins and inflammatory cytokines in the serum was detected with ELISA. Immunofluorescence showed microglia and astrocytes activity in the hippocampus. RESULTS: Acupuncture and fluoxetine could alleviate CUMS-induced depression-like behaviors. Acupuncture was also found to effectively reverse the levels of MDA, SOD, GSH, GSH-PX and T-AOC, IL-1ß, IL-6 and TNF-α in the serum of CUMS-induced rats. Rats with CUMS showed decreased levels of Sirt1, Nrf2, HO-1 and GPX4 in the hippocampus, while acupuncture treatment could partly reverse the diminished effects. In addition, acupuncture treatment significantly reduced the activation of hippocampal microglia and astrocytes in CUMS-induced rats. CONCLUSION: The study's findings indicate that acupuncture has the potential to mitigate depression-like behaviors in rats induced with CUMS by mitigating OS and reducing neuroinflammation.

A high-resolution haplotype-resolved Reference panel constructed from the China Kadoorie Biobank Study.

Precision medicine depends on high-accuracy individual-level genotype data. However, the whole-genome sequencing (WGS) is still not suitable for gigantic studies due to budget constraints. It is particularly important to construct highly accurate haplotype reference panel for genotype imputation. In this study, we used 10 000 samples with medium-depth WGS to construct a reference panel that we named the CKB reference panel. By imputing microarray datasets, it showed that the CKB panel outperformed compared panels in terms of both the number of well-imputed variants and imputation accuracy. In addition, we have completed the imputation of 100 706 microarrays with the CKB panel, and the after-imputed data is the hitherto largest whole genome data of the Chinese population. Furthermore, in the GWAS analysis of real phenotype height, the number of tested SNPs tripled and the number of significant SNPs doubled after imputation. Finally, we developed an online server for offering free genotype imputation service based on the CKB reference panel (https://db.cngb.org/imputation/). We believe that the CKB panel is of great value for imputing microarray or low-coverage genotype data of Chinese population, and potentially mixed populations. The imputation-completed 100 706 microarray data are enormous and precious resources of population genetic studies for complex traits and diseases.

The fusion of multiple scale data indicates that the carbon sink function of the Qinghai-Tibet Plateau is substantial.

BACKGROUND: The Qinghai-Tibet Plateau is the "sensitive area" of climate change, and also the "driver" and "amplifier" of global change. The response and feedback of its carbon dynamics to climate change will significantly affect the content of greenhouse gases in the atmosphere. However, due to the unique geographical environment characteristics of the Qinghai-Tibet Plateau, there is still much controversy about its carbon source and sink estimation results. This study designed a new algorithm based on machine learning to improve the accuracy of carbon source and sink estimation by integrating multiple scale carbon input (net primary productivity, NPP) and output (soil heterotrophic respiration, Rh) information from remote sensing and ground observations. Then, we compared spatial patterns of NPP and Rh derived from the fusion of multiple scale data with other widely used products and tried to quantify the differences and uncertainties of carbon sink simulation at a regional scale. RESULTS: Our results indicate that although global warming has potentially increased the Rh of the Qinghai-Tibet Plateau, it will also increase its NPP, and its current performance is a net carbon sink area (carbon sink amount is 22.3 Tg C/year). Comparative analysis with other data products shows that CASA, GLOPEM, and MODIS products based on remote sensing underestimate the carbon input of the Qinghai-Tibet Plateau (30-70%), which is the main reason for the severe underestimation of the carbon sink level of the Qinghai-Tibet Plateau (even considered as a carbon source). CONCLUSIONS: The estimation of the carbon sink in the Qinghai-Tibet Plateau is of great significance for ensuring its ecological barrier function. It can deepen the community's understanding of the response to climate change in sensitive areas of the plateau. This study can provide an essential basis for assessing the uncertainty of carbon sources and sinks in the Qinghai-Tibet Plateau, and also provide a scientific reference for helping China achieve "carbon neutrality" by 2060.

Crucial roles of the optimal time-scale of water condition on grassland biomass estimation on Qinghai-Tibet Plateau.

The effect of the time-scale of water conditions on vegetation productivity has been widely studied by the academic community. However, the relationship between the time-scale of water conditions and the vegetation growth rhythm and the effect of this relationship on vegetation biomass estimation have rarely been discussed. Here, we analyzed the occurrence times of major phenological events on alpine grasslands using the widely distributed "site-dominant species" dataset and set a series of time-scales for accumulated precipitation and standardized precipitation evapotranspiration index based on phenological information. Then, we combined large-scale aboveground/belowground biomass datasets to evaluate the role of the optimal time-scale for water conditions in aboveground/belowground biomass estimation. The results showed that (1) the optimal time-scale for water conditions with the greatest effects on aboveground biomass was on the month before the end of flowering or the onset of fruit maturity. The optimal time-scale for water condition effects on belowground biomass was earlier and longer than that for the aboveground biomass. The optimal time-scales for accumulated precipitation and standardized precipitation evapotranspiration index effects on belowground biomass were at five months before the end of flowering or the beginning of fruit ripening and the three months before the first flowering, respectively. (2) The aboveground and belowground biomass were underestimated by 11 % and 9 %, respectively, when the water conditions at the optimal time-scales were ignored. (3) The interannual variability in aboveground/belowground biomass was more effectively captured by considering the optimal time-scales of water conditions, especially in water-restricted areas. Overall, this study indicated that terrestrial carbon cycle models should incorporate information on the lag-effects of the water conditions in previous periods. In the future, increasing the number of belowground biomass observations and conducting monthly belowground biomass monitoring sooner will be key to revealing the mechanisms of the belowground biomass response to climate change.

The effect of acupuncture on lateral habenular nucleus and intestinal microflora in depression model rats.

BACKGROUND: Depression is a severe emotional condition that significantly affects the quality of life. Acupuncture exerts preventive effects on depression in rats with post-chronic unpredictable mild stress (CUMS). Methods The study involved chronic unpredictable mild stress (CUMS) depression model mice to administer acupuncture as a preventative measure to investigate the mechanism of acupuncture's antidepressant and observe the effect of acupuncture on impact via the Lateral Habenula (LHb) and Gut-Liver-Brain Axis. The researcher investigated molecules correlating with a nitric oxide/cyclic guanosine monophosphate (NO/cGMP) pathway and assessed inflammation in the LHb and liver. In addition, 16 S rDNA bioinformatics study revealed the quantity and variety of gut microbiota. Rats were randomly divided into five groups: control (CON), CUMS, CUMS + acupuncture (AP), CUMS + fluoxetine (FX) and CUMS + N(G) -nitro -L- arginine methyl ester (LNAME) group. Except for the CON group, other rats were exposed to CUMS condition for 28 days. Simultaneously, manual acupuncture (at Fengfu and Shangxing acupoints, once every other day) and fluoxetine gavage (2.1 mg/kg, 0.21 mg/mL, daily) were conducted to the groups of AP and FX, respectively, after stressors. Rats in LNAME group were treated with LNAME normal saline (10 mg/kg, 1 mg/mL, i.p.) solution. Behavioural tests and biological detection methods were conducted sequentially to evaluate depressionlike phenotype in rats. RESULTS: The results showed CUMS induced depression-like behaviours, hyper-activation of NO/cGMP signaling pathway, inflammation in serum, LHb and liver, and dysbiosis of the gut microbiota. These changes could be prevented and ameliorated by acupuncture to varying extents. CONCLUSION: Acupuncture prevented and attenuated depression-like phenotype induced by CUMS, possibly via regulating the NO/cGMP signaling pathway and thus improving inflammation in serum, LHb and liver, and gut microbiota dysbiosis. In addition, these can be evidence of the existence of the gut-liver-brain axis.

An improved global vegetation health index dataset in detecting vegetation drought.

Due to global warming, drought events have become more frequent, which resulted in aggravated crop failures, food shortage, larger and more energetic wildfires, and have seriously affected socio-economic development and agricultural production. In this study, a global long-term (1981-2021), high-resolution (4 km) improved vegetation health index (VHI) dataset integrating climate, vegetation and soil moisture was developed. Based on drought records from the Emergency Event Database, we compared the detection efficiency of the VHI before and after its improvement in the occurrence and scope of observed drought events. The global drought detection efficiency of the improved high-resolution VHI dataset reached values as high as 85%, which is 14% higher than the original VHI dataset. The improved VHI dataset was also more sensitive to mild droughts and more accurate regarding the extent of droughts. This improved dataset can play an important role in long-term drought monitoring but also has the potential to assess the impact of drought on the agricultural, forestry, ecological and environmental sectors.

The effects of acupuncture on depression by regulating BDNF-related balance via lateral habenular nucleus BDNF/TrkB/CREB signaling pathway in rats.

Depression is a major mental disease worldwide, causing dysfunction of Lateral Habenular (LHb). As a non-invasive alternative, acupuncture (AP) has been widely used to treat depression in clinic, yet few basic studies have been focused on the effects and mechanism of acupuncture on synaptic plasticity in LHb. Therefore, this study aimed to explore the potential mechanism of the antidepressant effect of acupuncture. Male Sprague-Dawley (SD) rats were randomly divided into control, chronic unpredictable mild stress (CUMS), AP, fluoxetine (FLX), acupoint catgut embedding (ACE), sham-ACE groups (n = 9/group). Rats were given a 28-day treatment at the Shangxing (GV23) and Fengfu (GV16) acupoints with acupuncture, ACE, sham-ACE or fluoxetine (2.1 mg/kg). The results showed that AP, FLX and ACE suppressed the behavioral deficits, increased the level of the 5-hydroxytryptamine and FNDC5/IRISIN in serum, also reduced the expression of pro-BDNF impacted by CUMS. Both AP and FLX ameliorated the %area of IBA-1, GFAP, BrdU and DCX in the LHb and increased the expression of BDNF/TrkB/CREB, with non-significant difference between the two groups These findings suggest that AP therapy relieves depression-related manifestations in depressed rats, suggesting a potential mechanism via the BDNF/TrkB/CREB pathway in LHb.

Arsenic contents, speciation and bioaccessibility in rice grains from China: Regional and variety differences.

As the staple food for Asian countries and with its ability in arsenic accumulation, rice consumption becomes a dominant pathway for As exposure to humans. Here, we collected 108 rice samples from local markets and online sources in 13 major rice-producing regions in China, and determined As contents, speciation and bioaccessibility in the samples. Total As contents were 25-327 µg kg-1 (averaging 120), showing regional differences, with Hunan province being greater than other provinces at 180 vs 110. In rice grains, inorganic As was the dominant species, being 39.9-88.5 (61.1 %), but all being within the Chinese standard at 200 µg kg-1. Based on the modified physiologically-based extraction test (MPEBT), arsenic bioaccessibility in rice samples was 20.1-82.2 (52.3 %) in the gastric phase and 47.2-113 (81.2 %) in the intestinal phase. Strong positive correlation between total As and bioaccessible As suggested bioaccessible As was content-dependent. Based on the intestinal phase, the rice samples from northern region had lower As bioaccessibility than other regions (59.2 vs 83.2 %), and Japonica variety had lower As bioaccessibility than Indica variety (71.1 vs 83.1 %). This study suggests that rice from markets in China is safe, with their As contents and bioaccessibility showing regional and variety differences.

Does PET scan have any role in the diagnosis of perineural spread associated with the head and neck tumors?

BACKGROUND: Perineural spread of head and neck tumors is linked to a worse chance of survival as well as a higher risk of local recurrence and metastasis. Particle emission tomography/computed tomography (PET/CT) using 2-[fluorine-18]fluoro-2-deoxy-d-glucose (FDG) is part of the work-up and follow-up of many afflicted patients, and radiologists play an essential role in the assessment and management of head and neck cancer. OBJECTIVES: The purpose of the current study was to investigate the diagnostic performance of 18F-FDG PET in detecting perineural spread among patients with head and neck tumors through a meta-analysis. MATERIAL AND METHODS: Relevant articles were searched using appropriate keywords from PubMed, MEDLINE and PubMed Central (PMC) databases. Retrospective and prospective studies were included as per the predefined PICOS criteria. Demographic summary and event data for diagnostic accuracy of 18F-FDG PET were determined, and odds ratio (OR), sensitivity, specificity, likelihood ratios, and predictive values were calculated using RevMan software. The bias risk was analyzed with Egger's and Begg's tests using MedCalc software. RESULTS: Fourteen clinical trials performed between 2000 and 2021, with 977 head and neck cancer patients with perineural spread, were included according to the inclusion criteria. Included studies used 18F-FDG PET imaging of tumors and reported its high sensitivity. In the current study, we obtained the pooled OR = 3.088 (95% confidence interval (95% CI): [1.486; 6.419]), pooled sensitivity of 91.7%, pooled specificity of 92.35%, positive predictive value (PPV) of 92.27%, negative predictive value (NPV) of 91.13%, positive likelihood ratio of 7.45, negative likelihood ratio of 0.28, disease prevalence of 95.8%, and accuracy of 91.5%. Data was heterogeneous, with Q value of 33.8%, degrees of freedom (df) value of 13, I2 value of 61.5% (31.23-78.5), and p-value = 0.0013. The risk of publication bias was low, with a p = 0.7490 (Egger's test) and p = 0.7843 (Begg's test). CONCLUSION: The present meta-analysis highly recommends 18F-FDG PET as an effective imaging method for patients with head and neck tumors with perineural spread.

An improved daily standardized precipitation index dataset for mainland China from 1961 to 2018.

The standardized precipitation index (SPI), one of the most commonly used drought indicators, is widely used in the research areas of drought analysis and drought prediction in different fields such as meteorology, agriculture, and hydrology. However, its main disadvantage is the relatively coarse time resolution of one month. To improve the time resolution of SPI to identify flash droughts, we have refined the traditional SPI calculation method and developed a new multi-scale daily SPI dataset based on data from 484 meteorological stations in mainland China from 1961 to 2018. SPI data from three different sites (located in Henan, Yunnan, and Fujian Provinces) at the three-month timescale were analyzed by comparing with historically recorded drought events. We found that the new multi-scale daily SPI can effectively capture drought events in different periods and locations and identify the specific start and end times of drought events. In short, our SPI dataset appears reasonable and capable of facilitating drought research in different fields.

A Chinese host genetic study discovered IFNs and causality of laboratory traits on COVID-19 severity.

The COVID-19 pandemic has caused over 220 million infections and 4.5 million deaths worldwide. Current risk factor cannot fully explain the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients' laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory traits and used Mendelian randomization (MR) analysis to further investigate the causality of traits on disease severity. Two causal traits, WBC counts and cholesterol levels, were identified based on MR study, and their functional genes are located at genes MHC complex and ApoE, respectively. Our gene-based analysis and GSEA revealed four interferon pathways, including type I interferon receptor binding and SARS coronavirus and innate immunity. We hope that our work will contribute to studying the genetic mechanisms of disease and serve as a useful reference for COVID-19 diagnosis and treatment.

Accumulation and health implications of metals in topsoil of an urban riparian zone adjacent to different functional areas in a subtropical city.

The riparian zone is a river-land ecotone, and its environmental conditions have a significant effect on the river ecosystem and population health. In this study, As, Cu, Cr, Cd, Mn, Fe, Ni, Pb, and Zn in the topsoils of urban riparian zones in a subtropical city in southeast China were quantitatively estimated by inductively coupled plasma-optical emission spectrometry. The geoaccumulation index and health risk evaluation model were adopted to assess the accumulation characteristic and health risk of residents' exposure to metals. Principle component analysis was used to determine the source of metals. The results showed that the mean contents of metals (except Fe) were higher than the soil background value, but none of the metal contents exceeded the mass limit of environmental quality standards. The order of the geoaccumulation index was Cd > Mn > Cu > Cr > Pb > Zn > As > Ni > Fe. The contamination level of Cd was classified as slight, whereas the other metals did not contribute to pollution. The spatial distribution of metals in the riparian zone was compatible with the pattern of functional zones in the adjacent urban areas, where levels of Cr, Cd, Fe, Mn, and Ni were higher in commercial areas, as were Pb and Zn in under-construction land and As in residential and industrial areas. Carcinogenic risks of Cr, As, and Pb were acceptable. The hazard index indicated no significant noncarcinogenic risks from any metals. However, noncarcinogenic risks of metals other than Mn were higher for children than for adults, and the primary exposure route of metal into the human body was ingestion for children and inhalation for adults. Principle component analysis indicated that the primary sources of Cr, Ni, Mn, Cu, and Fe were pedogenic processes and mineral weathering, whereas Zn, As, Pb, and Cd mainly originated from anthropogenic sources, specifically, Zn from transportation emission, Pb from transportation emission and industry waste, As from coal combustion and residential waste, and Cd from pigments/paint used in commercial buildings, urban greening, consumer waste, and transportation emission.

FifBase: a comprehensive fertility-associated indicators factor database for domestic animals.

Fertility refers to the ability of animals to maintain reproductive function and give birth to offspring, which is an important indicator to measure the productivity of animals. Fertility is affected by many factors, among which environmental factors may also play key roles. During the past years, substantial research studies have been conducted to detect the factors related to fecundity, including genetic factors and environmental factors. However, the identified genes associated with fertility from countless previous studies are randomly dispersed in the literature, whereas some other novel fertility-related genes are needed to detect from omics-based datasets. Here, we constructed a fertility index factor database FifBase based on manually curated published literature and RNA-Seq datasets. During the construction of the literature group, we obtained 3301 articles related to fecundity for 13 species from PubMed, involving 2823 genes, which are related to 75 fecundity indicators or 47 environmental factors. Eventually, 1558 genes associated with fertility were filtered in 10 species, of which 1088 and 470 were from RNA-Seq datasets and text mining data, respectively, involving 2910 fertility-gene pairs and 58 fertility-environmental factors. All these data were cataloged into FifBase (http://www.nwsuaflmz.com/FifBase/), where the fertility-related factor information, including gene annotation and environmental factors, can be browsed, retrieved and downloaded with the user-friendly interface.

Self-adapting extraction of cropland phenological transitions of rotation agroecosystems using dynamically fused NDVI images.

Remote sensing can be used to monitor cropland phenological characteristics; however, tradeoffs between the spatial and temporal resolutions of cloudless satellite images limit the accuracy of their retrieval. In this study, an improved enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) was applied to human-dominated Xiong'an New Area to develop a self-adapting algorithm automating the extraction of main phenological transition points (greenup, maturity, senescence, and dormancy). The analyses of cropland phenological characteristics were performed utilizing the Softmax classification method. By examining three different phases of fusion images, it was found that the improved ESTARFM was more accurate than the original ESTARFM (correlation coefficient > 0.76; relative root mean square error < 0.25; structural similarity index > 0.79). The reconstructed normalized difference vegetation indexes were consistent with that acquired by the Moderate Resolution Imaging Spectroradiometer (average discrepancy: 0.1136, median absolute deviation: 0.0110). The greenup, maturity, senescence, and dormancy points were monitored in 5-day resolution and 50-day length on a 30-m grid scale, and their average day of year (DOY) were 67, 119, 127, and 166 for wheat; 173, 224, 232, and 283 for single-season corn; and 189, 227, 232, and 285 for rotation corn, respectively. The corresponding median absolute deviations were 2, 3, 2, and 2 days for wheat; 2, 5, 3, and 4 days for single-season corn; and 2, 5, 2, and 2 days for rotation corn, respectively, while all coefficients of variation did not exceed 6%. The proposed self-adapting approach can be used for identifying the planting modes at grid level in rotation agroecosystems and cropland phenological dynamics on a global or regional scale.

Health Risk Assessment and Source Apportionment for Heavy Metals in a Southern Chinese Reservoir Impacted by Stone Mining Activities.

Metal contaminants in drinking water pose a potential threat to human health. Metal elements (Fe, Mn, Cu, Cr, Cd, As, and Pb) in Shanzi Reservoir, China, a drinking water source for nearby cities, were measured in 2013 and 2014. The distribution characteristics of metal elements in water were identified and a health risk assessment model was used to evaluate potential harm. Principal component analysis and cluster analysis were used to determine the main sources of metal pollutants. The results showed that Pb and As exceeded the standard at some sampling sites, whereas other metal elements met the drinking water standards. The spatial distribution of metal elements was extremely uneven and might be affected by either the geochemical environment or human activities in the study region. The total risk value of metals (5 × 10-5 a-1 ) was below the recommended value of the United States Environmental Protection Agency (USEPA), the total cancer risk was higher than the total noncancer risk, and both risks were higher for children than for adults. Arsenic was the priority control pollutant, and the priority control site was located upstream of the reservoir. Source analysis showed that Fe, Mn, and Cu were mainly from soil formation and stone mining and processing industries; Pb and As were mainly from agricultural activities, free dumping and burning of domestic garbage, and atmospheric deposition from transportation emissions; Cd was mainly from agricultural application of fertilizers and pesticides; and Cr was from the stone mining and processing industry and from the electroplating and metal manufacturing industries. Integr Environ Assess Manag 2020;16:342-352. © 2019 SETAC.