Unveiling the impact of soil methane sink on atmospheric methane concentrations in 2020.

In 2020, anthropogenic methane (CH4) emissions decreased due to COVID-19 containment policies, but there was a substantial increase in the concentration of atmospheric CH4. Previous research suggested that this abnormal increase was linked to higher wetland CH4 emissions and a decrease in the atmospheric CH4 sink. However, the impact of changes in the soil CH4 sink remained unknown. To address this, we utilized a process-based model to quantify alterations in the soil CH4 sink of terrestrial ecosystems between 2019 and 2020. By implementing the model with various datasets, we consistently observed an increase in the global soil CH4 sink, reaching up to 0.35 ± 0.06 Tg in 2020 compared to 2019. This increase was primarily attributed to warmer soil temperatures in northern high latitudes. Our results emphasize the importance of considering the CH4 sink in terrestrial ecosystems, as neglecting this component can lead to an underestimation of both emission increases and reductions in atmospheric CH4 sink capacity. Furthermore, these findings highlight the potential role of increased soil warmth in terrestrial ecosystems in slowing the growth of CH4 concentrations in the atmosphere.

Experimental realization of a three-photon asymmetric maximally entangled state and its application to quantum state transfer.

Quantum entanglement is crucial for quantum information processing, prominently used in quantum communication, computation, and metrology. Recent studies have shifted toward high-dimensional entangled states, offering greater information capacity and enabling more complex applications. Here, we experimentally prepared a three-photon asymmetric maximally entangled state, comprising two two-dimensional photons and one four-dimensional photon. Using this state, we conducted a proof-of-principle experiment, successfully transferring a four-dimensional quantum state from two photons to another photon with fidelities ranging from 0.78 to 0.86. These results exceed theoretical limits, demonstrating genuine four-dimensional quantum state transfer. The asymmetric entangled state demonstrated here holds promise for future quantum networks as a quantum interface facilitating information transfer across quantum systems with different dimensions.

Association between milk consumption and kidney stones in U.S. adults: results from NHANES 2007-2018.

Background: Dietary strategies play a crucial role in the prevention of kidney stones. While milk is known for its rich nutritional content, its impact on kidney stone formation remains unclear. This study aimed to examine the relationship between milk consumption and the risk of kidney stones among U.S. adults. Methods: We included 24,620 participants aged 20 and older from the National Health and Nutrition Examination Survey (2007-2018). Milk consumption was defined based on each participant's response to the questionnaire item on "Past 30 day milk product consumption." Kidney stones history was self-reported by participants. The analysis employed weighted multivariate logistic regression models, followed by subgroup analyses for result validation, and explored the age-related dynamics of milk consumption's effect on kidney stone risk using a restricted cubic spline model. Results: Adjusted findings revealed that higher milk intake was associated with a decreased risk of kidney stones (odds ratio [OR] = 0.90, 95% confidence interval [CI] 0.85-0.96), notably among women (OR = 0.86, 95% CI 0.80-0.92) but not significantly in men (OR = 0.94, 95% CI 0.86-1.02). Smoothed curves across all ages showed that women consuming milk had a lower incidence of kidney stones than those who did not, particularly with regular consumption. Conclusion: This study uncovered that across all age groups, higher frequency of milk consumption in women is associated with a reduced risk of kidney stones. However, further prospective cohort studies are needed to confirm this finding.

Multi-omics analysis of kidney, bone and bone marrow explored potential mechanisms of Erzhi Wan against osteoporosis with kidney-Yin deficiency.

Osteoporosis (OP) is a metabolic bone disease that can lead to major health challenges. The theory of Traditional Chinese medicine believes that kidney-Yin deficiency (KYD) is the main cause of postmenopausal osteoporosis. This study was aimed to investigate the effect of EZW on anti-osteoporosis with KYD, and explore potential mechanisms from the perspective of the kidney, bone and bone marrow through analysis of metabolomics and proteomics. The model of OP with KYD was established by rats treated with bilateral ovariectomy (OVX), and then given intragastric administration of thyroid and reserpine to induce. Micro-CT was applied to determine the microstructures of bone. Serum levels associated with bone turnover markers and kidney-Yin deficiency were detected by enzyme-linked immunosorbent (ELISA) assay. The differential metabolites in the kidney, bone and bone marrow were analyzed by metabolomics. The differentially expressed proteins in these three tissues were detected via proteomics. The findings suggested that EZW could alleviate a variety of metabolites and proteins among the kidney, bone and bone marrow, primarily in amino acid metabolism, carbohydrate metabolism, nucleotide metabolism and lipid metabolism, thus leading to improvements of OP with KYD, which provided theoretical basis for clinical treatment of EZW on OP with KYD.

Integrated component identification, network pharmacology, and experimental verification revealed mechanism of Dendrobium officinale Kimura et Migo against lung cancer.

BACKGROUND: Dendrobium officinale Kimura et Migo (DO), a valuable Chinese herbal medicine, has been reported to exhibit potential effects in the prevention and treatment of lung cancer. However, its material basis and mechanism of action have not been comprehensively analyzed. PURPOSE: The objective of this study was to preliminarily elucidate the active components and pharmacological mechanisms of DO in treating lung cancer, according to UPLC-Q/TOF-MS, HPAEC-PAD, network pharmacology, molecular docking, and experimental verification. METHODS: The chemical components of DO were identified via UPLC-Q/TOF-MS, while the monosaccharide composition of Dendrobium officinale polysaccharide (DOP) was determined by HPAEC-PAD. The prospective active constituents of DO as well as their respective targets were predicted in the combined database of Swiss ADME and Swiss Target Prediction. Relevant disease targets for lung cancer were searched in OMIM, TTD, and Genecards databases. Further, the active compounds and potential core targets of DO against lung cancer were found by the C-T-D network and the PPI network, respectively. The core targets were then subjected to enrichment analysis in the Metascape database. The main active compounds were molecularly docked to the core targets and visualized. Finally, the viability of A549 cells and the relative quantity of associated proteins within the major signaling pathway were detected. RESULTS: 249 ingredients were identified from DO, including 39 flavonoids, 39 bibenzyls, 50 organic acids, 8 phenanthrenes, 27 phenylpropanoids, 17 alkaloids, 17 amino acids and their derivatives, 7 monosaccharides, and 45 others. Here, 50 main active compounds with high degree values were attained through the C-T-D network, mainly consisting of bibenzyls and monosaccharides. Based on the PPI network analysis, 10 core targets were further predicted, including HSP90AA1, SRC, ESR1, CREBBP, MAPK3, AKT1, PIK3R1, PIK3CA, HIF1A, and HDAC1. The results of the enrichment analysis and molecular docking indicated a close association between the therapeutic mechanism of DO and the PI3K-Akt signaling pathway. It was confirmed that the bibenzyl extract and erianin could inhibit the multiplication of A549 cells in vitro. Furthermore, erianin was found to down-regulate the relative expressions of p-AKT and p-PI3K proteins within the PI3K-Akt signaling pathway. CONCLUSIONS: This study predicted that DO could treat lung cancer through various components, multiple targets, and diverse pathways. Bibenzyls from DO might exert anti-lung cancer activity by inhibiting cancer cell proliferation and modulating the PI3K-Akt signaling pathway. A fundamental reference for further studies and clinical therapy was given by the above data.

Integrated chemical characterization, metabolite profiling, and pharmacokinetics analysis of Zhijun Tangshen Decoction by UPLC-Q/TOF-MS.

Diabetic nephropathy (DN) is the main cause of end-stage renal disease worldwide and a major public issue affecting the health of people. Therefore, it is essential to explore effective drugs for the treatment of DN. In this study, the traditional Chinese medicine (TCM) formula, Zhijun Tangshen Decoction (ZJTSD), a prescription modified from the classical formula Didang Decoction, has been used in the clinical treatment of DN. However, the chemical basis underlying the therapeutic effects of ZJTSD in treating DN remains unknown. In this study, compounds of ZJTSD and serum after oral administration in rats were identified and analyzed using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS). Meanwhile, a semi-quantitative approach was used to analyze the dynamic changes in the compounds of ZJTSD in vivo. UPLC-Q/TOF-MS analysis identified 190 compounds from ZJTSD, including flavonoids, anthraquinones, terpenoids, phenylpropanoids, alkaloids, and other categories. A total of 156 xenobiotics and metabolites, i.e., 51 prototype compounds and 105 metabolites, were identified from the compounds absorbed into the blood of rats treated with ZJTSD. The results further showed that 23 substances with high relative content, long retention time, and favorable pharmacokinetic characteristics in vivo deserved further investigations and validations of bioactivities. In conclusion, this study revealed the chemical basis underlying the complexity of ZJTSD and investigated the metabolite profiling and pharmacokinetics of ZJTSD-related xenobiotics in rats, thus providing a foundation for further investigation into the pharmacodynamic substance basis and metabolic regulations of ZJTSD.

Predicting One-year Recurrence of HCC based on Gadoxetic Acid-enhanced MRI by Machine Learning Models.

OBJECTIVE: Accurate prediction of recurrence risk after resction in patients with Hepatocellular Carcinoma (HCC) may help to individualize therapy strategies. This study aimed to develop machine learning models based on preoperative clinical factors and multiparameter Magnetic Resonance Imaging (MRI) characteristics to predict the 1-year recurrence after HCC resection. METHODS: Eighty-two patients with single HCC who underwent surgery were retrospectively analyzed. All patients underwent preoperative gadoxetic acidenhanced MRI examination. Preoperative clinical factors and MRI characteristics were collected for feature selection. Least Absolute Shrinkage and Selection Operator (LASSO) was applied to select the optimal features for predicting postoperative 1-year recurrence of HCC. Four machine learning algorithms, Multilayer Perception (MLP), random forest, support vector machine, and k-nearest neighbor, were used to construct the predictive models based on the selected features. A Receiver Operating Characteristic (ROC) curve was used to assess the performance of each model. RESULTS: Among the enrolled patients, 32 patients experienced recurrences within one year, while 50 did not. Tumor size, peritumoral hypointensity, decreasing ratio of liver parenchyma T1 value (ΔT1), and α-fetoprotein (AFP) levels were selected by using LASSO to develop the machine learning models. The area under the curve (AUC) of each model exceeded 0.72. Among the models, the MLP model showed the best performance with an AUC, accuracy, sensitivity, and specificity of 0.813, 0.742, 0.570, and 0.853, respectively. CONCLUSION: Machine learning models can accurately predict postoperative 1-year recurrence in patients with HCC, which may help to provide individualized treatment.

Hepatic Pecoma versus Hepatocellular Carcinoma In The Noncirrhotic Liver on Gd-EOB-DTPA-Enhanced MRI: A Diagnostic Challenge.

AIM: Hepatic perivascular epithelioid cell tumors (PEComa) often mimic hepatocellular carcinoma (HCC) in patients without cirrhosis. This study aimed to develop a nomogram using imaging characteristics on Gd-EOB-DTPA-enhanced MRI and to distinguish PEComa from HCC in a noncirrhotic liver. METHODS: Forty patients with non-cirrhotic Gd-EOB-DTPA-enhanced magnetic resonance imaging(MRI) were included in our study. A multivariate logistic regression model was used to select significant variables to distinguish PEComa from HCC. A nomogram was developed based on the regression model. The performance of the nomogram was assessed with respect to the ROC curve and calibration curve. Decision curve analysis (DCA) was performed to evaluate the clinical usefulness of the nomogram. RESULTS: Two significant predictors were identified: the appearance of an early draining vein and the T1D value of tumors. The ROC curve showed that the area under the curve (AUC) of the model to predict the risk of PEComa was 0.91 (95% CI: 0.80~1) and showed that the model had high specificity (92.3%) and sensitivity (88.9%). The nomogram incorporating these two predictors showed favorable calibration, which was validated using 1000 resampling procedures, and the corrected C-index of this model was 0.90. Furthermore, DCA analysis showed that the model had clinical practicability. CONCLUSION: In conclusion, the nomogram model showed favorable predictive accuracy for distinguishing PEComa from HCC in non-cirrhotic patients and may aid in clinical decision-making.

Prediction of immunocyte infiltration and prognosis in postoperative hepatitis B virus-related hepatocellular carcinoma patients using magnetic resonance imaging.

Background: The immune microenvironment (IME) is closely associated with prognosis and therapeutic response of hepatitis B virus-related hepatocellular carcinoma (HBV-HCC). Multi-parametric magnetic resonance imaging (MRI) enables non-invasive assessment of IME and predicts prognosis in HBV-HCC. We aimed to construct an MRI prediction model of the immunocyte-infiltration subtypes and explore its prognostic significance. Methods: HBV-HCC patients at the First Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) with radical surgery (between 1 October and 30 December 2021) were prospectively enrolled. Patients with pathologically proven HCC (between 1 December 2013 and 30 October 2019) were retrospectively enrolled. Pearson correlation analysis was used to examine the relationship between the immunocyte-infiltration counts and MRI parameters. An MRI prediction model of immunocyte-infiltration subtypes was constructed in prospective cohort. Kaplan-Meier survival analysis was used to analyse its prognostic significance in the retrospective cohort. Results: Twenty-four patients were prospectively enrolled to construct the MRI prediction model. Eighty-nine patients were retrospectively enrolled to determine its prognostic significance. MRI parameters (relative enhancement, ratio of the apparent diffusion coefficient value of tumoral region to peritumoral region [rADC], T1 value) correlated significantly with the immunocyte-infiltration counts (leukocytes, T help cells, PD1+Tc cells, B lymphocytes). rADC differed significantly between high and low immunocyte-infiltration groups (1.47 ± 0.36 vs 1.09 ± 0.25, P = 0.009). The area under the curve of the MRI model was 0.787 (95% confidence interval 0.587-0.987). Based on the MRI model, the recurrence-free time was longer in the high immunocyte-infiltration group than in the low immunocyte-infiltration group (P = 0.026). Conclusions: MRI is a non-invasive method for assessing the IME and immunocyte-infiltration subtypes, and predicting prognosis in post-operative HBV-HCC patients.

Quantitative assessment of inflammation and evaluation of spatial heterogeneity for non-alcoholic fatty liver disease in mice based on iron-adjustive T1.

Background: A sensitive and non-invasive method is necessary to diagnose non-alcoholic fatty liver disease (NAFLD). We explored the iron-adjustive T1 (aT1) ability to quantify the degree of liver inflammation and evaluate the spatial heterogeneity. Methods: Male C57BL/6J mice were randomly categorized as the NAFLD model (n=40), NAFLD-related liver cirrhosis model (n=20), and normal mice (n=10). T1 and T2* maps were acquired using a 3.0T scanner of magnetic resonance imaging (MRI) and aT1 maps through post-processing corrected iron's effect on T1 using T2*. Pathological changes in the left and right liver lobes were assessed using the Non-alcoholic Steatohepatitis-Clinical Research Network scoring system, though hepatic ballooning lesion were rare in models. Spearman's and partial correlation analyses were used to evaluate correlations, and the receiver operating characteristic curve was used to analyze the diagnostic performance. Results: aT1 was highly correlated with NAFLD activity score (NAS) (r=0.747, P<0.001) but not with the fibrosis stage when adjusted by NAS (r=-0.135, P=0.147). The area under the curve (AUC) of the aT1 value distinguishing groups with 0< NAS <4 and NAS ≥4 was 0.802. On analyzing the histogram features of aT1, the entropy, interquartile range, range, and variance were significantly different between the groups with 0< NAS <4 and NAS ≥4 (P<0.05). The entropy was the risk factor of NAS ≥4. Conclusions: aT1 could help evaluate the inflammatory activity in NAFLD mice unaffected by mild fibrosis, and the higher the degree of inflammation, the higher the heterogeneity of the aT1 map.

ACE2-independent SARS-CoV-2 virus entry through cell surface GRP78 on monocytes - evidence from a translational clinical and experimental approach.

BACKGROUND: SARS-CoV-2 infects host cells via an ACE2/TMPRSS2 entry mechanism. Monocytes and macrophages, which play a key role during severe COVID-19 express only low or no ACE2, suggesting alternative entry mechanisms in these cells. In silico analyses predicted GRP78, which is constitutively expressed on monocytes and macrophages, to be a potential candidate receptor for SARS-CoV-2 virus entry. METHODS: Hospitalized COVID-19 patients were characterized regarding their pro-inflammatory state and cell surface GRP78 (csGRP78) expression in comparison to healthy controls. RNA from CD14+ monocytes of patients and controls were subjected to transcriptome analysis that was specifically complemented by bioinformatic re-analyses of bronchoalveolar lavage fluid (BALF) datasets of COVID-19 patients with a focus on monocyte/macrophage subsets, SARS-CoV-2 infection state as well as GRP78 gene expression. Monocyte and macrophage immunohistocytochemistry on GRP78 was conducted in post-mortem lung tissues. SARS-CoV-2 spike and GRP78 protein interaction was analyzed by surface plasmon resonance, GST Pull-down and Co-Immunoprecipitation. SARS-CoV-2 pseudovirus or single spike protein uptake was quantified in csGRP78high THP-1 cells. FINDINGS: Cytokine patterns, monocyte activation markers and transcriptomic changes indicated typical COVID-19 associated inflammation accompanied by upregulated csGRP78 expression on peripheral blood and lung monocytes/macrophages. Subsequent cell culture experiments confirmed an association between elevated pro-inflammatory cytokine levels and upregulation of csGRP78. Interaction of csGRP78 and SARS-CoV-2 spike protein with a dissociation constant of KD = 55.2 nM was validated in vitro. Infection rate analyses in ACE2low and GRP78high THP-1 cells showed increased uptake of pseudovirus expressing SARS-CoV-2 spike protein. INTERPRETATION: Our results demonstrate that csGRP78 acts as a receptor for SARS-CoV-2 spike protein to mediate ACE2-independent virus entry into monocytes. FUNDING: Funded by the Sino-German-Center for Science Promotion (C-0040) and the Germany Ministry BMWi/K [DLR-grant 50WB1931 and RP1920 to AC, DM, TW].

Preoperative assessment of peripheral vascular invasion of pancreatic ductal adenocarcinoma based on high-resolution MRI.

OBJECTIVES: Preoperative imaging of vascular invasion is important for surgical resection of pancreatic ductal adenocarcinoma (PDAC). However, whether MRI and CT share the same evaluation criteria remains unclear. This study aimed to compare the diagnostic accuracy of high-resolution MRI (HR-MRI), conventional MRI (non-HR-MRI) and CT for PDAC vascular invasion. METHODS: Pathologically proven PDAC with preoperative HR-MRI (79 cases, 58 with CT) and non-HR-MRI (77 cases, 59 with CT) were retrospectively collected. Vascular invasion was confirmed surgically or pathologically. The degree of tumour-vascular contact, vessel narrowing and contour irregularity were reviewed respectively. Diagnostic criteria 1 (C1) was the presence of all three characteristics, and criteria 2 (C2) was the presence of any one of them. The diagnostic efficacies of different examination methods and criteria were evaluated and compared. RESULTS: HR-MRI showed satisfactory performance in assessing vascular invasion (AUC: 0.87-0.92), especially better sensitivity (0.79-0.86 vs. 0.40-0.79) than that with non-HR-MRI and CT. HR-MRI was superior to non-HR-MRI. C2 was superior to C1 on CT evaluation (0.85 vs. 0.79, P = 0.03). C1 was superior to C2 in the venous assessment using HR-MRI (0.90 vs. 0.87, P = 0.04) and in the arterial assessment using non-HR-MRI (0.69 vs. 0.68, P = 0.04). The combination of C1-assessed HR-MRI and C2-assessed CT was significantly better than that of CT alone (0.96 vs. 0.86, P = 0.04). CONCLUSIONS: HR-MRI more accurately assessed PDAC vascular invasion than conventional MRI and may contribute to operative decision-making. C1 was more applicable to MRI scans, and C2 to CT scans. The combination of C1-assessed HR-MRI and C2-assessed CT outperformed CT alone and showed the best efficacy in preoperative examination of PDAC.

Influence of skill relatedness on the location choice of heterogeneous labor force in Chinese prefecture-level cities.

High-quality regional development should be promoted by facilitating inter-regional mobility of heterogeneous labor force to optimize its spatial allocation. This study incorporates skill relatedness into spatial categorization and selection effects, and explores how skill-relatedness affects the location choice of heterogeneous labor force. To do so, we use labor force migration data and employee data by occupation subcategory from the 2000 National Population Census and 2015 National Population Sample Survey. The empirical evidence provides three major findings. First, there are significant regional differences in labor migration rates by the occupational group between cities in China, and the trend is increasing. Regional concentration of location choice is increasing and six significant agglomerations are formed. Second, skill relatedness positively affects the location choice of the heterogeneous labor force in Chinese cities. When cities' skill-relatedness is more robust, influence on labor location choice is more remarkable. In cities with high-size classes, the effect of high-skill relatedness on labor location choice is higher. Third, labor force with solid skill relatedness with regional employment moves to the location owing to the spatial sorting effect. Labor force without skill relatedness or weak relatedness moves out or does not move to the location owing to the spatial selection effect.

Urban human settlements' resilience measurement and characteristics and their mechanism model in China.

This study introduces the principle of resilience into the study of human settlements. In this study, a comprehensive evaluation model of urban human settlements' resilience based on the provincial region of China was constructed using the Driver-Pressure-State-Impact-Response framework. The spatio-temporal evolution characteristics of urban human settlements' resilience was explored. The influencing factors were analysed by geographical detectors, and the driving mechanism was constructed. Results show that the following. (1) The resilience level of human settlements in China continued to increase, and the resilience level of each province and city changed significantly. The overall clustering effect showed a tendency to fluctuate and weaken. The distribution of cold spot areas became less and less, and the hot spots were moving from northeast China to southeast China. (2) Significant differences existed in the intensity of the impact of different indicators on the resilience system. The value of the impact factor showed an overall upward trend, and the number of key impact factors increased. (3) Improving the ability of scientific and technological innovation, accelerating the transformation and upgrading of the regional economy, increasing the training of talents and making financial inclination in scientific and technological development and industrial pollution control were all important ways for developing and maintaining the resilience of urban human settlements. This study not only introduces a new evaluation of urban human settlements from the perspective of resilience but also explores key impact indices and driving mechanisms, which provides new ideas for studying urban human settlements.

Clinical Interpretability of Deep Learning for Predicting Microvascular Invasion in Hepatocellular Carcinoma by Using Attention Mechanism.

Preoperative prediction of microvascular invasion (MVI) is essential for management decision in hepatocellular carcinoma (HCC). Deep learning-based prediction models of MVI are numerous but lack clinical interpretation due to their "black-box" nature. Consequently, we aimed to use an attention-guided feature fusion network, including intra- and inter-attention modules, to solve this problem. This retrospective study recruited 210 HCC patients who underwent gadoxetate-enhanced MRI examination before surgery. The MRIs on pre-contrast, arterial, portal, and hepatobiliary phases (hepatobiliary phase: HBP) were used to develop single-phase and multi-phase models. Attention weights provided by attention modules were used to obtain visual explanations of predictive decisions. The four-phase fusion model achieved the highest area under the curve (AUC) of 0.92 (95% CI: 0.84-1.00), and the other models proposed AUCs of 0.75-0.91. Attention heatmaps of collaborative-attention layers revealed that tumor margins in all phases and peritumoral areas in the arterial phase and HBP were salient regions for MVI prediction. Heatmaps of weights in fully connected layers showed that the HBP contributed the most to MVI prediction. Our study firstly implemented self-attention and collaborative-attention to reveal the relationship between deep features and MVI, improving the clinical interpretation of prediction models. The clinical interpretability offers radiologists and clinicians more confidence to apply deep learning models in clinical practice, helping HCC patients formulate personalized therapies.

The relationship between mushroom consumption and cognitive performance among middle-aged and older adults: a cross-sectional study.

Objectives: Bioactive compounds in mushrooms may protect the brain from neurodegeneration by inhibiting the production of amyloid-ß and playing an antioxidant role. This study aimed at examining the associations of mushroom consumption with cognitive function and mild cognitive impairment (MCI) among middle-aged and older adults in China. Design: A cross-sectional study. Setting and participants: This study was conducted in seven cities in China and included 2203 middle-aged and older adults. Methods: Data on mushroom consumption were collected using a semi-quantitative food frequency questionnaire. Cognitive function was evaluated by the Auditory Verbal Learning Test (AVLT), Verbal Fluency Test (VFT), Digit Symbol Substitution Test (DSST), and Trail Making Test-B (TMT-B). The composite z score was used to reflect global cognition. MCI was determined according to the Petersen criteria. Multiple linear regression and logistic regression were used to examine the relationship between mushroom consumption and cognitive performance. Results: This study included 2203 participants aged 55 years and above (mean age = 63.43 years). After controlling demographic characteristics, lifestyle factors, other dietary factors, and history of chronic disease, higher mushroom consumption was associated with better global cognition. Compared to the lowest quartile (Q1, 0-4.00 g day-1), the ßs (95% confidence intervals, 95% CIs) were 0.10 (0.03, 0.18) for Q2 (4.01-10.42 g day-1), 0.13 (0.06, 0.20) for Q3 (10.43-20.84 g day-1), and 0.13 (0.06, 0.20) for Q4 (>20.84 g day-1). The higher mushroom consumption was positively related to better performance in DSST and TMT-B (P-values < 0.05). A 10 g day-1 increment in mushroom consumption was related to 12% lower odds of MCI (odds ratio = 0.88, 95% CI: 0.80-0.97). Conclusions: Higher mushroom consumption was positively related to better cognitive function and associated with lower odds of MCI. Further studies are needed to replicate our findings in other populations and determine the underlying mechanisms.

Gut microbiome characteristics in subjective cognitive decline, mild cognitive impairment and Alzheimer's disease: a systematic review and meta-analysis.

BACKGROUND AND PURPOSE: The gut microbiome has been reported to be closely related to Alzheimer's disease (AD) progression. Here, a comprehensive meta-analysis of gut microbial characteristics in AD, mild cognitive impairment (MCI) and subjective cognitive decline (SCD) was performed to compare gut microbial alterations at each stage. METHODS: A total of 10 databases (CNKI, WanFang, VIP, SinoMed, WOS, PubMed, Embase, Cochrane Library, PsycINFO and Void) were searched and 34 case-control studies were included. α and ß diversity and the relative abundance of gut microbiota were analysed as outcome indices. Data analysis was performed using Review Manager (5.4.1) and R. RESULTS: Chao1 and Shannon index levels in AD were significantly lower compared with healthy controls (HCs), and the Chao1 index was significantly lower in MCI compared with HCs. There was a significant difference in ß diversity of gut microbiomes in patients (SCD, MCI, AD) compared with HCs. The relative abundance of Firmicutes at the phylum level was significantly lower in patients with AD and MCI than HCs. However, the relative abundance of Bacteroidetes at the phylum level was significantly higher in patients with MCI than HCs. There was an increasing trend for Enterobacteriaceae and a decreasing trend for Ruminococcaceae, Lachnospiraceae and Lactobacillus during AD; Lactobacillus showed a decreasing trend early in SCD. CONCLUSION: Our results indicated that there were gut microbiological abnormalities in AD, even as early as the SCD stage. The dynamic, consistent changes in gut microbes with the disease process showed that they might serve as potential biomarkers for early identification and diagnosis of AD.

Sanghuangporus vaninii ethanol extract alleviates hyperuricemic renal injury by regulating the uric acid transporters and inhibiting HK-2 apoptosis.

AIM OF THE STUDY: To investigate the acute toxicity of Sanghuangporus ethanol extract (SHEE) on ICR mice and the underlying mechanism of anti-hyperuricemic renal injury. MATERIALS AND METHODS: ICR mice were given a single gavage of 1250, 2500, and 5000 mg/kg SHEE, and the general behavior, mortality, body weight, dietary, and water intake were evaluated within 14 days to determine the acute toxicity level. The hyperuricemic kidney injury model in ICR mice was induced with potassium oxonate (PO) and adenine, and the mice were subsequently treated with SHEE (125, 250, 500 mg/kg). HE and hexamine silver staining (PASM) were used to observe the pathology of the kidney. Biochemical markers were tested by uric acid (UA), creatinine (Cr), blood urea nitrogen (BUN), xanthine oxidase (XOD), alanine transferase (ALT), and aspartate transaminase (AST) kits. An MTT assay was used to measure the effects of SHEE on the proliferation of HK-2 damaged by UA. Western blotting and RT-PCR were used to determine the expression of Bcl-2 family-related proteins and major UA transporters, including URAT1, GLUT9, OAT1, OAT3, and ABCG2, respectively. RESULTS: Firstly, the acute toxicity study data showed that the median lethal dose (LD50) of SHEE was above 5000 mg/kg, and its oral administration was nontoxic at 2500 mg/kg and below. In addition, SHEE alleviated HUA and its renal injury in ICR mice. SHEE reduced the contents of UA, Cr, BUN and XOD in blood and the contents of ALT and AST in the liver. Furthermore, SHEE inhibited the expression of URAT1 and GLUT9 and promoted the expression of OAT1, OAT3, and ABCG2. More importantly, SHEE could downregulate the apoptosis level and caspase-3 activity. CONCLUSIONS: Overall, an oral dose of SHEE below 2500 mg/kg is safe. SHEE inhibits HUA-induced kidney injury by regulating the UA transporters URAT1, GLUT9, OAT1, OAT3 and ABCG2 and inhibiting HK-2 apoptosis.

Long-term plant diversity increases soil extractable organic carbon and nitrogen contents in a subtropical forest.

Plant diversity is one of the various factors influencing ecosystem functions such as soil carbon (C) and nitrogen (N) stocks. Soil extractable organic carbon (EOC) and nitrogen (EON) contents are active fractions in soil organic matter, but little is known about the impact of variations in long-term plant diversity on soil EOC and EON contents in forest ecosystems. Utilizing the Biodiversity-Ecosystem Functioning Experiment China platform, we selected long-term plant diversity level treatments, distinguished the functional types of evergreen and deciduous plants, and explored their effects on soil EOC and EON contents. The results showed that soil EOC and EON contents increased significantly with greater plant diversity, which is mainly attributed to proportional increases in complementary effects. After distinguishing plant functional types, we did not find the strong complementary effects at the mixed planting of evergreen and deciduous tree species. Within two-species planting mixtures, evergreen tree species can increase soil EON compared to deciduous tree species. Cyclobalanopsis have a strong carbon and nitrogen storage capacity, suggesting that increasing the plant diversity and the proportion of Cyclobalanopsis planting in forest management will promote carbon and nitrogen accumulation in forest soil. These findings enhance our understanding of long-term forest C and N cycling processes and also provide theoretical support for managing forest soil C sinks.

Evaluation of Hypoxia in Hepatocellular Carcinoma Using Quantitative MRI: Significances, Challenges, and Advances.

This review aimed to perform a scoping review of promising MRI methods in assessing tumor hypoxia in hepatocellular carcinoma (HCC). The hypoxic microenvironment and upregulated hypoxic metabolism in HCC are determining factors of poor prognosis, increased metastatic potential, and resistance to chemotherapy and radiotherapy. Assessing hypoxia in HCC is essential for personalized therapy and predicting prognoses. Oxygen electrodes, protein markers, optical imaging, and positron emission tomography can evaluate tumor hypoxia. These methods lack clinical applicability because of invasiveness, tissue depth, and radiation exposure. MRI methods, including blood oxygenation level-dependent, dynamic contrast-enhanced MRI, diffusion-weighted imaging, MRI spectroscopy, chemical exchange saturation transfer MRI, and multinuclear MRI, are promising noninvasive methods that evaluate the hypoxic microenvironment by observing biochemical processes in vivo, which may inform on therapeutic options. This review summarizes the recent challenges and advances in MRI techniques for assessing hypoxia in HCC and highlights the potential of MRI methods for examining the hypoxic microenvironment via specific metabolic substrates and pathways. Although the utilization of MRI methods for evaluating hypoxia in patients with HCC is increasing, rigorous validation is needed in order to translate these MRI methods into clinical use. Due to the limited sensitivity and specificity of current quantitative MRI methods, their acquisition and analysis protocols require further improvement. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 4.