Heavy metals and elderly kidney health: A multidimensional study through Enviro-target Mendelian Randomization.

Chronic Kidney Disease (CKD), closely linked to environmental factors, poses a significant public health challenge. This study, based on 529 triple-repeated measures from key national environmental pollution area and multiple gene-related public databases, employs various epidemiological and bioinformatics models to assess the impact of combined heavy metal exposure (Chromium [Cr], Cadmium [Cd], and Lead [Pb]) on early renal injury and CKD in the elderly. Introducing the novel Enviro-Target Mendelian Randomization method, our research explores the causal relationship between metals and CKD. The findings indicate a positive correlation between increased levels of metal and renal injury, with combined exposure caused renal damage more significantly than individual exposure. The study reveals that metals primarily influence CKD development through oxidative stress and metal ion resistance pathways, focusing on three related genes (SOD2, MPO, NQO1) and a transcription factor (NFE2L2). Metals were found to regulate oxidative stress levels in the body by increasing the expression of SOD2, MPO, NQO1, and decreasing NFE2L2, leading to CKD onset. Our research establishes a new causal inference framework linking environmental pollutants-pathways-genes-CKD, assessing the impact and mechanisms of metal exposure on CKD. Future studies with more extensive in vitro evidence and larger population are needed to validate.

SLS4D: Sparse Latent Space for 4D Novel View Synthesis.

Neural radiance fields (NeRF) have achieved great success in novel view synthesis and 3D representation for static scenarios. Existing dynamic NeRFs usually exploit a locally dense grid to fit the deformation fields; however, they fail to capture the global dynamics and concomitantly yield models of heavy parameters. We observe that the 4D space is inherently sparse. Firstly, the deformation fields are sparse in spatial but dense in temporal due to the continuity of motion. Secondly, the radiance fields are only valid on the surface of the underlying scene, usually occupying a small fraction of the whole space. We thus represent the 4D scene using a learnable sparse latent space, a.k.a. SLS4D. Specifically, SLS4D first uses dense learnable time slot features to depict the temporal space, from which the deformation fields are fitted with linear multi-layer perceptions (MLP) to predict the displacement of a 3D position at any time. It then learns the spatial features of a 3D position using another sparse latent space. This is achieved by learning the adaptive weights of each latent feature with the attention mechanism. Extensive experiments demonstrate the effectiveness of our SLS4D: It achieves the best 4D novel view synthesis using only about 6% parameters of the most recent work.

Far-Red Aggregation-Induced Emission Hydrogel-Reinforced Tissue Clearing for 3D Vasculature Imaging of Whole Lung and Whole Tumor.

Understanding the vascular formation and distribution in metastatic lung tumors is a significant challenge due to autofluorescence, antibody/dye diffusion in dense tumor, and fluorophore stability when exposed to solvent-based clearing agents. Here, an approach is presented that redefines 3D vasculature imaging within metastatic tumor, peritumoral lung tissue, and normal lung. Specifically, a far-red aggregation-induced emission nanoparticle with surface amino groups (termed as TSCN nanoparticle, TSCNNP) is designed for in situ formation of hydrogel (TSCNNP@Gel) inside vasculatures to provide structural support and enhance the fluorescence in solvent-based tissue clearing method. Using this TSCNNP@Gel-reinforced tissue clearing imaging approach, the critical challenges are successfully overcome and comprehensive visualization of the whole pulmonary vasculature up to 2 µm resolution is enabled, including its detailed examination in metastatic tumors. Importantly, features of tumor-associated vasculature in 3D panoramic views are unveiled, providing the potential to determine tumor stages, predict tumor progression, and facilitate the histopathological diagnosis of various tumor types.

Inflammation as a pathway for heavy metal-induced liver damage-Insights from a repeated-measures study in residents exposed to metals and bioinformatics analysis.

BACKGROUND: Epidemiological studies on heavy metal exposure and liver injury are predominantly cross-sectional, lacking longitudinal data and exploration of potential mechanisms. METHOD: We conducted a repeated-measures study in Northeast China from 2016 to 2019, involving 322 participants. Linear mixed models (LMM) and Bayesian kernel machine regression (BKMR) were employed to explore the associations between individual and mixed blood metal concentrations [chromium (Cr), cadmium (Cd), vanadium (V), manganese (Mn), lead (Pb)] and liver function biomarkers [alanine aminotransferase (ALT), aspartate aminotransferase (AST), albumin (ALB), globulin (GLB), total protein (TP)]. Mediation and enrichment analyses were used to determine whether the inflammatory response is a critical pathway for heavy metal-induced liver damage. RESULT: We obtained a total of 958 observations. The results from LMM and BKMR indicated significant associations between individual and mixed heavy metals and liver function biomarkers. Longitudinal analysis revealed associations between Cd and the annual increase rate of ALT (ß = 2.61; 95% CI: 0.97, 4.26), the annual decrease rate of ALB (ß = -0.21; 95% CI: -0.39, -0.03), Mn and the annual increase rate of GLB (ß = 0.38; 95% CI: 0.05, 0.72), and V and the annual decrease rate of ALB/GLB (ß = -1.15; 95% CI: -2.00, -0.31). Mediation analysis showed that high-sensitivity C-reactive protein (hsCRP) mediated the associations between Cd and AST, TP, with mediation effects of 27.7% and 13.4%, respectively. Additionally, results from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses supported the role of inflammatory response pathways. CONCLUSION: Our findings indicate that heavy metal exposure leads to liver damage, with the inflammatory response potentially serving as a crucial pathway in this process. This study offers a novel perspective on understanding heavy metal-induced liver injury and provides insights for preventive measures against the health damage caused by heavy metals.

The health and economic burden of ozone pollution on Alzheimer's disease and mild cognitive impairment in China.

Ozone pollution is increasingly recognized as a serious environmental threat that exacerbates dementia risks, including Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI). Amid rapid industrialization, China faces significant air quality challenges. However, there has been a scarcity of detailed studies assessing the health and economic impacts of ozone pollution on these conditions. This study aims to address this gap by utilizing the BenMap-CE tool and incorporating parameters obtained from systematic reviews of epidemiological studies, official statistics, and weighted averages, to accurately quantify the effects of ozone exposure in China. This research evaluated the health and economic burdens at both national and provincial levels, focusing on the additional impacts attributed to increased ozone levels. The results reveal that in 2023, compared to 2015, ozone pollution contributed to approximately 110,000 new cases (5.6 per 10,000) of AD and 1.6 million new cases (81.7 per 10,000) of MCI, imposing significant economic costs of about US $1200 million for AD and US $18,000 million for MCI, based on 2015 dollar values. Additionally, our projections indicate that reducing the 2023 ozone concentrations to 70 µg/m3 could significantly curb these conditions, potentially preventing over 210,000 new AD cases (10.7 per 10,000) and 2.9 million (148.1 per 10,000) MCI cases. Such reductions are projected to yield substantial economic benefits, estimated at US $2200 million for AD and US $34,000 million for MCI (2015 dollar values). These findings underscore the profound implications of ozone pollution on public health and the economy in China, highlighting the urgent need for effective ozone management strategies to mitigate these impacts.

A KNOX â ¡ transcription factor suppresses the NLR immune receptor BRG8-mediated immunity in rice.

Nucleotide-binding site and leucine-rich repeat (NLR) proteins are activated by detecting pathogen effectors, which in turn trigger host defenses and cell death. Although many NLRs have been identified, the mechanisms responsible for NLR-triggered defense responses are still poorly understood. In this study, through a genome-wide association study approach, we identified a novel NLR gene, Blast Resistance Gene 8 (BRG8), which confers resistance to rice blast and bacterial blight diseases. BRG8 overexpression and complementation lines exhibit enhanced resistance to both pathogens. Subcellular localization assays showed that BRG8 is localized in both the cytoplasm and the nucleus. Additional evidence revealed that nuclear-localized BRG8 can enhance rice immunity without a hypersensitive response (HR)-like phenotype. We also demonstrated that the coiled-coil domain of BRG8 not only physically interacts with itself but also interacts with the KNOX Ⅱ protein HOMEOBOX ORYZA SATIVA59 (HOS59). Knockout mutants of HOS59 in the BRG8 background show enhanced resistance to Magnaporthe oryzae strain CH171 and Xoo strain CR4, similar to that of the BRG8 background. By contrast, overexpression of HOS59 in the BRG8 background will compromise the HR-like phenotype and resistance response. Further analysis revealed that HOS59 promotes the degradation of BRG8 via the 26S proteasome pathway. Collectively, our study highlights HOS59 as an NLR immune regulator that fine-tunes BRG8-mediated immune responses against pathogens, providing new insights into NLR associations and functions in plant immunity.

Complex interplay of heavy metals and renal injury: New perspectives from longitudinal epidemiological evidence.

BACKGROUND: Epidemiological studies have reported associations between heavy metals and renal function. However, longitudinal studies are required to further validate these associations and explore the interactive effects of heavy metals on renal function and their directional influence. METHOD: This study, conducted in Northeast China from 2016 to 2021, included a four-time repeated measures design involving 384 participants (1536 observations). Urinary concentrations of chromium (Cr), cadmium (Cd), manganese (Mn), and lead (Pb) were measured, along with renal biomarkers including urinary microalbumin (umAlb), urinary albumin-to-creatinine ratio (UACR), N-acetyl-ß-D-glucosaminidase (NAG), and ß2-microglobulin (ß2-MG) levels. Estimated glomerular filtration rate (eGFR) was calculated. A Linear Mixed Effects Model (LME) examined the association between individual metal exposure and renal biomarkers. Subsequently, Quantile g-computation and Bayesian Kernel Machine Regression (BKMR) models assessed the overall effects of heavy metal mixtures. Marginal Effect models examined the directional impact of metal interactions in the BKMR on renal function. RESULT: Results indicate significant impacts of individual and combined exposures of Cr, Cd, Pb, and Mn on renal biomarkers. Metal interactions in the BKMR model were observed, with synergistic effects of Cd-Cr on NAG, umAlb, UACR; Cd-Pb on NAG, UACR; Pb-Cr on umAlb, UACR, eGFR-MDRD, eGFR-EPI; and an antagonistic effect of Mn-Pb-Cr on UACR. CONCLUSION: Both individual and combined exposures to heavy metals are associated with renal biomarkers, with significant synergistic interactions leading to renal damage. Our findings elucidate potential interactions among these metals, offering valuable insights into the mechanisms linking multiple metal exposures to renal injury.

Association between PM2.5 constituents and cardiometabolic risk factors: Exploring individual and combined effects, and mediating inflammation.

BACKGROUND: The individual and combined effects of PM2.5 constituents on cardiometabolic risk factors are sparsely investigated. Besides, the key cardiometabolic risk factor that PM2.5 constituents targeted and the biological mechanisms remain unclear. METHOD: A multistage, stratified cluster sampling survey was conducted in two typically air-polluted Chinese cities. The PM2.5 and its constituents including sulfate, nitrate, ammonium, organic matter, and black carbon were predicted using a machine learning model. Twenty biomarkers in three category were simultaneously adopted as cardiometabolic risk factors. We explored the individual and mixture association of long-term PM2.5 constituents with these markers using generalized additive model and quantile-based g-computation, respectively. To minimize potential confounding effects, we accounted for covariates including demographic, lifestyle, meteorological, temporal trends, and disease-related information. We further used ROC curve and mediation analysis to identify the key subclinical indicators and explore whether inflammatory mediators mediate such association, respectively. RESULT: PM2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. Further, PM2.5 constituent mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. The ROC analysis further reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better identifiable performance for nitrate and ammonium (AUC>0.75). We also found that multiple blood lipid indicators may be affected by PM2.5 and its constituents, possibly mediated through complement C3 or hsCRP. CONCLUSION: Our study suggested associations of individual and combined PM2.5 constituents exposure with cardiometabolic risk factors. PP and CRI-2 were the targeted markers of long-term exposure to nitrate and ammonium. Inflammation may serve as a mediating factor between PM2.5 constituents and dyslipidemia, which enhance current understanding of potential pathways for PM2.5-induced preclinical cardiovascular responses.

Linkage-Mediated Electronic Structure Modulation in Multicomponent Covalent Organic Frameworks for Dramatically Promoted Photocatalytic Hydrogen Evolution.

Linkage chemistry is an essential aspect to covalent organic framework (COF) applications; it is highly desirable to precisely modulate electronic structure mediated directly by linkage for efficient COF-based photocatalytic hydrogen evolution, which however, remains substantially challenging. Herein, as a proof of concept, a collection of robust multicomponent pyrene-based COFs with abundant donor-acceptor (D-A) interactions has been judiciously designed and synthesized through molecularly engineering linkage for photogeneration of hydrogen. Controlled locking and conversion of linkage critically contribute to continuously regulating COFs' electronic structures further to optimize photocatalytic activities. Remarkably, the well-modulated optoelectronic properties turn on the average hydrogen evolution rate from zero to 15.67 mmol g-1 h-1 by the protonated quinoline-linked COF decorated with the trifluoromethyl group (TT-PQCOF-CF3). Using diversified spectroscopy and theoretical calculations, we show that multiple modifications toward linkage synergistically lead to the redistribution of charge on COFs with extended π-conjugation and reinforced D-A effect, making TT-PQCOF-CF3 a promising material with significantly boosted carrier separation and migration. This study provides important guidance for the design of high-performance COF photocatalysts based on the strategy of linkage-mediated electronic structure modulation in COFs.

Associations of metals and metal mixtures with glucose homeostasis: A combined bibliometric and epidemiological study.

This study employs a combination of bibliometric and epidemiological methodologies to investigate the relationship between metal exposure and glucose homeostasis. The bibliometric analysis quantitatively assessed this field, focusing on study design, predominant metals, analytical techniques, and citation trends. Furthermore, we analyzed cross-sectional data from Beijing, examining the associations between 14 blood metals and 6 glucose homeostasis markers using generalized linear models (GLM). Key metals were identified using LASSO-PIPs criteria, and Bayesian kernel machine regression (BKMR) was applied to assess metal mixtures, introducing an "Overall Positive/Negative Effect" concept for deeper analysis. Our findings reveal an increasing research interest, particularly in selenium, zinc, cadmium, lead, and manganese. Urine (27.6%), serum (19.0%), and whole blood (19.0%) were the primary sample types, with cross-sectional studies (49.5%) as the dominant design. Epidemiologically, significant associations were found between 9 metals-cobalt, copper, lithium, manganese, nickel, lead, selenium, vanadium, zinc-and glucose homeostasis. Notably, positive-metal mixtures exhibited a significant overall positive effect on insulin levels, and notable interactions involving nickel were identified. These finding not only map the knowledge landscape of research in this domain but also introduces a novel perspective on the analysis strategies for metal mixtures.

Heterogeneous CNF/MoO3 nanofluidic membranes with tunable surface plasmon resonances for solar-osmotic energy conversion.

Two-dimensional (2D) nanofluidic membranes are competitive candidates for osmotic energy harvesting and have been greatly developed. However, the use of diverse inherent characteristics of 2D nanosheets, such as electronic or optoelectronic properties, to achieve intelligent ion transport, still lacks sufficient exploration. Here, a cellulose nanofiber/molybdenum oxide (CNF/MoO3) heterogeneous nanofluidic membrane with high performance solar-osmotic energy conversion is reported, and how surface plasmon resonances (SPR) regulate selective cation transport is revealed. The SPR of amorphous MoO3 endows the heterogeneous nanofluidic membranes with tunable surface charge and good photothermal conversion. Through DFT calculations and finite element modeling, the regulation of electronic and optoelectronic properties on the surface of materials by SPR and the influence of surface charge density and temperature gradient on ion transport in nanofluidic membranes are demonstrated. By mixing 0.01/0.5 M NaCl solutions using SPR and photothermal effects, the power density can achieve a remarkable value of ≈13.24 W m-2, outperforming state-of-the-art 2D-based nanofluidic membranes. This work first reveals the regulation and mechanism of SPR on ion transport in nanofluidic membranes and systematically studies photon-electron-ion interactions in nanofluidic membranes, which could also provide a new viewpoint for promoting osmotic energy conversion.

Joint and interactive effects of metal mixtures on liver damage: Epidemiological evidence from repeated-measures study.

BACKGROUND: The impact of heavy metals on liver function has been examined in numerous epidemiological studies. However, these findings lack consistency and longitudinal validation. METHODS: In this study, we conducted three follow-up surveys with 426 participants from Northeast China. Blood and urine samples were collected, along with questionnaire information. Urine samples were analyzed for concentrations of four metals (chromium [Cr], cadmium [Cd], lead [Pb], and manganese [Mn]), while blood samples were used to measure five liver function indicators (alanine aminotransferase [ALT], aspartate aminotransferase [AST], albumin [ALB], globulin [GLB], and total protein [TP]). We utilized a linear mixed-effects model (LME) to explore the association between individual heavy metal exposure and liver function. Joint effects of metal mixtures were investigated using quantile g-computation and Bayesian kernel machine regression (BKMR). Furthermore, we employed BKMR and Marginal Effect models to examine the interaction effects between metals on liver function. RESULTS: The LME results demonstrated a significant association between urinary heavy metals (Cr, Cd, Pb, and Mn) and liver function markers. BKMR results indicated positive associations between heavy metal mixtures and ALT, AST, and GLB, and negative associations with ALB and TP, which were consistent with the g-comp results. Synergistic effects were observed between Cd-Cr on ALT, Mn-Cr and Cr-Pb on ALB, while an antagonistic effect was found between Mn-Pb and Mn-Cd on ALB. Additionally, synergistic effects were observed between Mn-Cr on GLB and Cd-Cr on TP. Furthermore, a three-way antagonistic effect of Mn-Pb-Cr on ALB was identified. CONCLUSION: Exposure to heavy metals (Cr, Cd, Mn, Pb) is associated with liver function markers, potentially leading to liver damage. Moreover, there are joint and interaction effects among these metals, which warrant further investigation at both the population and mechanistic levels.

Sulfur-bridged bonds enabled structure modulation and space confinement of MnS for superior sodium-ion capacitors.

Manganese sulfide (MnS) is a promising converion-type anode for sodium storage, owing to the virtues of high theoretical capacity, coupled with it crustal abundance and cost-effectiveness. Nevertheless, MnS suffers from inadequate electronic conductivity, sluggish Na+ reaction kinetics and considerable volume variation during discharge/charge process, thereby impeding its rate capability and capacity retention. Herein, a novel lamellar heterostructured composite of Fe-doped MnS nanoparticles/positively charged reduced graphene oxide (Fe-MnS/PG) was synthesized to overcome these issues. The Fe-doping can accelerate the ion/electron transfer, endowing fast electrochemical kinetics of MnS. Meanwhile, the graphene space confinement with strong MnSC bond interactions can facilite the interfacial electron transfer, hamper volume expansion and aggregation of MnS nanoparticles, stabilizing the structural integrity, thus improving the Na+ storage reversibility and cyclic stability. Combining the synergistic effect of Fe-doping and space confinement with strong MnSC bond interactions, the as-produced Fe-MnS/PG anode presents a remarkable capacity of 567 mAh/g at 0.1 A/g and outstanding rate performance (192 mAh/g at 10 A/g). Meanwhile, the as-assembled sodium-ion capacitor (SIC) can yield a high energy density of 119 Wh kg-1 and a maximum power density of 17500 W kg-1, with capacity retention of 77 % at 1 A/g after 5000 cycles. This work offers a promising strategy to develop MnS-based practical SICs with high energy and long lifespan, and paves the way for fabricating advanced anode materials.

Interfacial Bonding Induced Charge Transfer in Two-Dimensional Amorphous MoO3-x/Graphdiyne Oxide Non-Van der Waals Heterostructures for Dominant SERS Enhancement.

Two-dimensional semiconductor-based nanomaterials have shown to be an effective substrate for Surface-enhanced Raman Scattering (SERS) spectroscopy. However, the enhancement factor (EF) tends to be relatively weak compared to that of noble metals and does not allow for trace detection of molecules. In this work, we report the successful preparation of two-dimensional (2D) amorphous non-van der Waals heterostructures MoO3-x/GDYO nanomaterials using supercritical CO2. Due to the synergistic effect of the localized surface plasmon resonance (LSPR) effect and the charge transfer effect, it exhibits excellent SERS performance in the detection of methylene blue (MB) molecules, with a detection limit as low as 10-14 M while the enhancement factor (EF) can reach an impressive 2.55×1011. More importantly, the chemical bond bridging at the MoO3-x/GDYO heterostructures interface can accelerate the electron transfer between the interfaces, and the large number of defective surface structures on the heterostructures surface facilitates the chemisorption of MB molecules. And the charge recombination lifetime can be proved by a ~1.7-fold increase during their interfacial electron-transfer process for MoO3-x/GDYO@MB mixture, achieving highly sensitive SERS detection.

Multiple cancer cell types release LIF and Gal3 to hijack neural signals.

Neural signals can significantly influence cancer prognosis. However, how cancer cells may proactively modulate the nervous system to benefit their own survival is incompletely understood. In this study, we report an overlapping pattern of brain responses, including that in the paraventricular nucleus of the hypothalamus, in multiple mouse models of peripheral cancers. A multi-omic screening then identifies leukemia inhibitory factor (LIF) and galectin-3 (Gal3) as the key cytokines released by these cancer cell types to trigger brain activation. Importantly, increased plasma levels of these two cytokines are observed in patients with different cancers. We further demonstrate that pharmacologic or genetic blockage of cancer cell-derived LIF or Gal3 signaling abolishes the brain responses and strongly inhibits tumor growth. In addition, ablation of peripheral sympathetic actions can similarly restore antitumor immunity. These results have elucidated a novel, shared mechanism of multiple cancer cell types hijacking the nervous system to promote tumor progression.

A Dataset on Population Activity Patterns in Typical Regions of North China.

This data article describes the "Typical Regional Activity Patterns" (TRAP) dataset, which is based on the Tackling Key Problems in Air Pollution Control Program. In order to explore the interaction between air pollution and physical activity, we collected activity patterns of 9,221 residents with different occupations and lifestyles for three consecutive days in typical regions (Jinan and Baoding) where air pollutant concentrations were higher than those in neighboring areas. The TRAP dataset consists of two aspects of information: demographic indicators (personal information, occupation, personal habits, and living situation) and physical activity pattern data (activity location and intensity); additionally, the exposure measures of physical activity patterns are included, which data users can match to various endpoints for their specific purpose. This dataset provides evidence for exploring the attributes of activity patterns of residents in northern China and for interdisciplinary researchers to develop strategies and measures for health education and health promotion.

CD163-Mediated Small-Vessel Injury in Alzheimer's Disease: An Exploration from Neuroimaging to Transcriptomics.

Patients with Alzheimer's disease (AD) often present with imaging features indicative of small-vessel injury, among which, white-matter hyperintensities (WMHs) are the most prevalent. However, the underlying mechanism of the association between AD and small-vessel injury is still obscure. The aim of this study is to investigate the mechanism of small-vessel injury in AD. Differential gene expression analyses were conducted to identify the genes related to WMHs separately in mild cognitive impairment (MCI) and cognitively normal (CN) subjects from the ADNI database. The WMH-related genes identified in patients with MCI were considered to be associated with small-vessel injury in early AD. Functional enrichment analyses and a protein-protein interaction (PPI) network were performed to explore the pathway and hub genes related to the mechanism of small-vessel injury in MCI. Subsequently, the Boruta algorithm and support vector machine recursive feature elimination (SVM-RFE) algorithm were performed to identify feature-selection genes. Finally, the mechanism of small-vessel injury was analyzed in MCI from the immunological perspectives; the relationship of feature-selection genes with various immune cells and neuroimaging indices were also explored. Furthermore, 5×FAD mice were used to demonstrate the genes related to small-vessel injury. The results of the logistic regression analyses suggested that WMHs significantly contributed to MCI, the early stage of AD. A total of 276 genes were determined as WMH-related genes in patients with MCI, while 203 WMH-related genes were obtained in CN patients. Among them, only 15 genes overlapped and were thus identified as the crosstalk genes. By employing the Boruta and SVM-RFE algorithms, CD163, ALDH3B1, MIR22HG, DTX2, FOLR2, ALDH2, and ZNF23 were recognized as the feature-selection genes linked to small-vessel injury in MCI. After considering the results from the PPI network, CD163 was finally determined as the critical WMH-related gene in MCI. The expression of CD163 was correlated with fractional anisotropy (FA) values in regions that are vulnerable to small-vessel injury in AD. The immunostaining and RT-qPCR results from the verifying experiments demonstrated that the indicators of small-vessel injury presented in the cortical tissue of 5×FAD mice and related to the upregulation of CD163 expression. CD163 may be the most pivotal candidates related to small-vessel injury in early AD.

A study on the relationship between gut microbiota and intrahepatic cholestasis of pregnancy.

Objective: Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disease associated with a high incidence of complications in the mid and late stages of gestation. This study investigates differences in the composition of intestinal flora among pregnant women diagnosed with ICP, employing Illumina MiSeq high-throughput sequencing technology. Methods: This case-control study obtained patient data from the hospital information system (HIS) and the laboratory information system (LIS). Fecal samples were collected from 25 pregnant women who did not undergo intestinal preparation before delivery between December 2020 and March 2021. Whole-genome analysis was performed. PCR was used to amplify the 16S rRNA V3-V4 variable region, which was then sequenced. Alpha and beta diversity were computed, and the maternal intestinal flora's abundance and composition characteristics were analyzed. Differences in intestinal flora between the two sample groups were examined. Results: Bacteroides and Proteobacteria exhibited positive correlations with TBIL and IBIL. Betaproteobacteria, Gammaproteobacteria, and Erysipeiotrichi showed positive correlations with TBIL, IBIL, and DBIL, while Lactobacillus, Delftia, and Odoribacter demonstrated positive correlations with ALT. Conclusion: The ICP group displayed significantly higher levels of total bile acid and ALT compared to the control group. The intestinal flora composition comprised four primary phyla: Firmicutes, Actinobacteria, Bacteroidetes, and Proteobacteria. ICP patients exhibited a lower relative abundance of intestinal flora across different levels of community composition when compared to the control group. Specific correlations between certain intestinal flora and clinical liver parameters were identified.

Monomeric CXCL12-Engineered Adipose-Derived Stem Cells Transplantation for the Treatment of Ischemic Stroke.

Adipose-derived stem cells (ASCs) possess therapeutic potential for ischemic brain injury, and the chemokine CXCL12 has been shown to enhance their functional properties. However, the cumulative effects of ASCs when combined with various structures of CXCL12 on ischemic stroke and its underlying molecular mechanisms remain unclear. In this study, we genetically engineered mouse adipose-derived ASCs with CXCL12 variants and transplanted them to the infarct region in a mice transient middle cerebral artery occlusion (tMCAO) model of stroke. We subsequently compared the post-ischemic stroke efficacy of ASC-mCXCL12 with ASC-dCXCL12, ASC-wtCXCL12, and unmodified ASCs. Neurobehavior recovery was assessed using modified neurological severity scores, the hanging wire test, and the elevated body swing test. Changes at the tissue level were evaluated through cresyl violet and immunofluorescent staining, while molecular level alterations were examined via Western blot and real-time PCR. The results of the modified neurological severity score and cresyl violet staining indicated that both ASC-mCXCL12 and ASC-dCXCL12 treatment enhanced neurobehavioral recovery and mitigated brain atrophy at the third and fifth weeks post-tMCAO. Additionally, we observed that ASC-mCXCL12 and ASC-dCXCL12 promoted angiogenesis and neurogenesis, accompanied by an increased expression of bFGF and VEGF in the peri-infarct area of the brain. Notably, in the third week after tMCAO, the ASC-mCXCL12 exhibited superior outcomes compared to ASC-dCXCL12. However, when treated with the CXCR4 antagonist AMD3100, the beneficial effects of ASC-mCXCL12 were reversed. The AMD3100-treated group demonstrated worsened neurological function, aggravated edema volume, and brain atrophy. This outcome is likely attributed to the interaction of monomeric CXCL12 with CXCR4, which regulates the recruitment of bFGF and VEGF. This study introduces an innovative approach to enhance the therapeutic potential of ASCs in treating ischemic stroke by genetically engineering them with the monomeric structure of CXCL12.

Toward digitally screening and profiling AD: A GAMLSS approach of MemTrax in China.

PURPOSES: To establish a normative range of MemTrax (MTx) metrics in the Chinese population. METHODS: The correct response percentage (MTx-%C) and mean response time (MTx-RT) were obtained and the composite scores (MTx-Cp) calculated. Generalized additive models for location, shape and scale (GAMLSS) were applied to create percentile curves and evaluate goodness of fit, and the speed-accuracy trade-off was investigated. RESULTS: 26,633 subjects, including 13,771 (51.71%) men participated in this study. Age- and education-specific percentiles of the metrics were generated. Q tests and worm plots indicated adequate fit for models of MTx-RT and MTx-Cp. Models of MTx-%C for the low and intermediate education fit acceptably, but not well enough for a high level of education. A significant speed-accuracy trade-off was observed for MTx-%C from 72 to 94. CONCLUSIONS: GAMLSS is a reliable method to generate smoothed age- and education-specific percentile curves of MTx metrics, which may be adopted for mass screening and follow-ups addressing Alzheimer's disease or other cognitive diseases. HIGHLIGHTS: GAMLSS was applied to establish nonlinear percentile curves of cognitive decline. Subjects with a high level of education demonstrate a later onset and slower decline of cognition. Speed-accuracy trade-off effects were observed in a subgroup with moderate accuracy. MemTrax can be used as a mass-screen instrument for active cognition health management advice.