Genetically supported causality between gut microbiota and frailty: a two-sample Mendelian randomization study.

Background: A mounting body of evidence suggests a strong connection between gut microbiota and the risk of frailty. However, the question of causality remains unanswered. In this study, we employed a Mendelian randomization (MR) approach to assess potential causal relationships between gut microbiota and the risk of frailty. Materials and methods: Summary statistics for the gut microbiome were obtained from a genome wide association study (GWAS) meta-analysis of the MiBioGen consortium (N = 18,340). Summary statistics for frailty were obtained from a GWAS meta-analysis, including the UK Biobank and TwinGene (N = 175,226). Our primary analysis utilized the inverse variance weighted (IVW) method. To enhance the robustness of our results, we also applied weighted median methods, MR Egger regression, and MR pleiotropy residual sum and outlier test. Finally, we conducted reverse MR analysis to investigate the potential for reverse causality. Results: IVW method identified 7 bacterial taxa nominally associated with the risk of FI. Class Bacteroidia (p = 0.033) and genus Eubacterium ruminantium group (p = 0.028) were protective against FI. In addition, class Betaproteobacteria (p = 0.042), genus Allisonella (p = 0.012), genus Bifidobacterium (p = 0.013), genus Clostridium innocuum group (p = 0.036) and genus Eubacterium coprostanoligenes group (p = 0.003) were associated with a higher risk of FI. No pleiotropy or heterogeneity were found. Conclusion: The MR analysis indicates a causal relationship between specific gut microbiota and FI, offering new insights into the mechanisms underlying FI mediated by gut microbiota.

Developing a geographical-meteorological indicator system and evaluating prediction models for alveolar echinococcosis in China.

BACKGROUND: Geographical and meteorological factors have been reported to influence the prevalence of echinococcosis, but there's a lack of indicator system and model. OBJECTIVE: To provide further insight into the impact of geographical and meteorological factors on AE prevalence and establish a theoretical basis for prevention and control. METHODS: Principal component and regression analysis were used to screen and establish a three-level indicator system. Relative weights were examined to determine the impact of each indicator, and five mathematical models were compared to identify the best predictive model for AE epidemic levels. RESULTS: By analyzing the data downloaded from the China Meteorological Data Service Center and Geospatial Data Cloud, we established the KCBIS, including 50 basic indicators which could be directly obtained online, 15 characteristic indicators which were linear combination of the basic indicators and showed a linear relationship with AE epidemic, and 8 key indicators which were characteristic indicators with a clearer relationships and fewer mixed effects. The relative weight analysis revealed that monthly precipitation, monthly cold days, the difference between negative and positive temperature anomalies, basic air temperature conditions, altitude, the difference between positive and negative atmospheric pressure anomalies, monthy extremely hot days, and monthly fresh breeze days were correlated with the natural logarithm of AE prevalence, with sequential decreases in their relative weights. The multinomial logistic regression model was the best predictor at epidemic levels 1, 3, 5, and 6, whereas the CART model was the best predictor at epidemic levels 2, 4, and 5.

Backscatter measurement of cancellous bone using the ultrasound transit time spectroscopy.

Recently, ultrasound transit time spectroscopy (UTTS) was proposed as a promising method for bone quantitative ultrasound measurement. Studies have showed that UTTS could estimate the bone volume fraction and other trabecular bone structure in ultrasonic through-transmission measurements. The goal of this study was to explore the feasibility of UTTS to be adapted in ultrasonic backscatter measurement and further evaluate the performance of backscattered ultrasound transit time spectrum (BS-UTTS) in the measurement of cancellous bone density and structure. First, taking ultrasonic attenuation into account, the concept of BS-UTTS was verified on ultrasonic backscatter signals simulated from a set of scatterers with different positions and intensities. Then, in vitro backscatter measurements were performed on 26 bovine cancellous bone specimens. After a logarithmic compression of the BS-UTTS, a linear fitting of the log-compressed BS-UTTS versus ultrasonic propagated distance was performed and the slope and intercept of the fitted line for BS-UTTS were determined. The associations between BS-UTTS parameters and cancellous bone features were analyzed using simple linear regression. The results showed that the BS-UTTS could make an accurate deconvolution of the backscatter signal and predict the position and intensity of the simulated scatterers eliminating phase interference, even the simulated backscatter signal was with a relatively low signal-to-noise ratio. With varied positions and intensities of the scatterers, the slope of the fitted line for the log-compressed BS-UTTS versus ultrasonic propagated distance (i.e., slope of BS-UTTS for short) yield a high agreement (r2 = 99.84%-99.96%) with ultrasonic attenuation in simulated backscatter signal. Compared with the high-density cancellous bone, the low-density specimen showed more abundant backscatter impulse response in the BS-UTTS. The slope of BS-UTTS yield a significant correlation with bone mineral density (r = 0.87; p < 0.001), BV/TV (r = 0.87; p < 0.001), and cancellous bone microstructures (r up to 0.87; p < 0.05). The intercept of BS-UTTS was also significantly correlated with bone densities (r = -0.87; p < 0.001) and trabecular structures (|r|=0.43-0.80; p < 0.05). However, the slope of the BS-UTTS underestimated attenuation when measurements were performed experimentally. In addition, a significant non-linear relationship was observed between the measured attenuation and the attenuation estimated by the slope of the BS-UTTS. This study demonstrated that the UTTS method could be adapted to ultrasonic backscatter measurement of cancellous bone. The derived slope and intercept of BS-UTTS could be used in the measurement of bone density and microstructure. The backscattered ultrasound transit time spectroscopy might have potential in the diagnosis of osteoporosis in the clinic.

Super-resolution reconstruction of ultrasound image using a modified diffusion model.

OBJECTIVE: This study aims to perform super-resolution (SR) reconstruction of ultrasound images using a modified diffusion model, designated as the Diffusion Model for Ultrasound Image Super-Resolution (DMUISR). SR involves converting low-resolution images to high-resolution ones, and the proposed model is designed to enhance the suitability of diffusion models for this task in the context of ultrasound imaging. APPROACH: DMUISR incorporates a multi-layer self-attention (MLSA) mechanism and a wavelet-transform based low-resolution image (WTLR) encoder to enhance its suitability for ultrasound image SR tasks. The model takes interpolated and magnified images as input and outputs high-quality, detailed SR images. The study utilized 1,334 ultrasound images from the public fetal head-circumference dataset (HC18) for evaluation. MAIN RESULTS: Experiments were conducted at 2×, 4×, and 8× magnification factors. DMUISR outperformed mainstream ultrasound SR methods (Bicubic, VDSR, DECUSR, DRCN, REDNet, SRGAN) across all scales, providing high-quality images with clear structures and rich detailed textures in both hard and soft tissue regions. DMUISR successfully accomplished multiscale SR reconstruction while suppressing over-smoothing and mode collapse problems. Quantitative results showed that DMUISR achieved the best performance in terms of learned perceptual image patch similarity (LPIPS), with a significant decrease of over 50% at all three magnification factors (2×, 4×, and 8×), as well as improvements in peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). Ablation experiments validated the effectiveness of the MLSA mechanism and WTLR encoder in improving DMUISR's SR performance. Furthermore, by reducing the number of diffusion steps, the computational time of DMUISR was shortened to nearly one-tenth of its original while maintaining image quality without significant degradation. SIGNIFICANCE: This study demonstrates that the modified diffusion model, DMUISR, provides superior performance for SR reconstruction of ultrasound images and has potential in improving imaging quality in the medical ultrasound field.

Efficient learning of mixed-state tomography for photonic quantum walk.

Noise-enhanced applications in open quantum walk (QW) has recently seen a surge due to their ability to improve performance. However, verifying the success of open QW is challenging, as mixed-state tomography is a resource-intensive process, and implementing all required measurements is almost impossible due to various physical constraints. To address this challenge, we present a neural-network-based method for reconstructing mixed states with a high fidelity (∼97.5%) while costing only 50% of the number of measurements typically required for open discrete-time QW in one dimension. Our method uses a neural density operator that models the system and environment, followed by a generalized natural gradient descent procedure that significantly speeds up the training process. Moreover, we introduce a compact interferometric measurement device, improving the scalability of our photonic QW setup that enables experimental learning of mixed states. Our results demonstrate that highly expressive neural networks can serve as powerful alternatives to traditional state tomography.

Immunogenic cell death related mRNAs associated signature to predict immunotherapeutic response in osteosarcoma.

Background: Immunogenic cell death (ICD) is related to cancer prognosis, which has a synergic effect in combination with chemotherapy or immunotherapy. Yet, the relationship between ICD and osteosarcoma remained unclear. Materials and methods: Three osteosarcoma datasets including therapeutically applicable research to generate effective treatments (TARGET), GSE126209 and GSE21257 datasets were included. A protein-protein interaction network was constructed based on ICD-related genes. We performed unsupervised consensus clustering to classify molecular subtypes (clusters). Survival analysis, Estimation of stromal and immune cells in malignant tumour tissues using expression data (ESTIMATE), Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), and differential analysis were employed to characterize the molecular differences between different clusters. Univariate Cox regression analysis was conducted to confirm prognostic genes. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to demonstrate the aberrant expression of ICD-correlated signature genes in osteosarcoma. A series of cellular experiments, including cell counting kit-8 (CCK-8), transwell, and flow cytometry, were used to demonstrate the regulatory role of key genes in the ICD model on the malignant phenotype of osteosarcoma. Results: Three clusters (cluster1, 2, 3) were constructed and they showed distinct overall survival and immune infiltration. ICD-related genes were highly expressed in cluster1. Moreover, Cluster1 had the best prognosis, high immune score and high expression of human leukocyte antigen (HLA)-related genes. TLR4, LY96, IFNGR1, CD4, and CASP1 were identified as prognostic genes for establishing an ICD-related risk signature. According to the risk signature, two risk groups (high and low risks) showing differential prognosis and response to immunotherapy. The low risks group had a better prognosis but was not sensitive to immunotherapy. Molecular assays verified that prognostic genes were abnormally under-expressed in osteosarcoma. Cellular assays demonstrated that LY96, the most significantly down-regulated gene in osteosarcoma, inhibited the migration, invasion, and proliferation phenotypes of osteosarcoma cells and prolonged the cell cycle. Analysis of oxidative stress related pathway enrichment in tumor microenvironment was conducted by single-sample gene set enrichment analysis (ssGSEA). Conclusions: This study demonstrated the prognostic significance of ICD-correlated genes in osteosarcoma patients. The five-gene risk signature facilitate prognostic evaluation and prediction of osteosarcoma patients' response to immunotherapy. The risk signature also offered a possibility for the exploit of novel ICD-related treatment.

Identification of dynamic changes in volatile compounds and metabolites during the smoking process of Zhenba bacon by GC-IMS combined metabolomics.

Zhenba bacon is a traditional cured bacon product with a rich history that originated from Zhenba County, Shaanxi Province. This study aimed to investigate the patterns of volatile compound formation and changes in metabolites during the smoking process in Zhenba bacon. Firstly, the sensory properties and physicochemical properties of Zhenba bacon were analyzed. Gas chromatography-ion mobility spectrometry (GC-IMS) and nontargeted metabolomics technology were used to analyze Zhenba bacon from different smoking stages. The results show a gradual increase in the sensory acceptance and volatile flavor compounds such as aldehydes, ketones, and esters with the prolongation of smoking of Zhenba bacon. LC-MS analysis identified 191 co-expressed differentially metabolites, with amino acid and lipid metabolism being the main metabolic pathways according to KEGG enrichment analysis. Temporal expression analysis of bacon metabolites at each stage revealed a decrease in harmful steroid hormones such as cortisone and an increase in amino acids and lipid metabolites, such as arginine, lysine, acid, and cholesterol, that contribute to the flavor of bacon. In summary, duration of smoking increased, the amount of flavor substances in Zhenba bacon gradually increased, and the safety and quality of bacon reached the optimal level after 32 days of smoking. This study provides valuable insights into the dynamic changes in volatile flavor compounds in Zhenba bacon and establishes a theoretical foundation for quality control during its production.

Retinol dehydrogenase 12 (RDH12) knock out may cause hyperuricemia phenotype in mice.

Hyperuricemia is a chronic metabolic disease caused by purine metabolism disorder. And several gene loci and transporter proteins that associated with uric acid transport functions have been identified. Retinol Dehydrogenase 12 (RDH12), recognized for its role in safeguarding photoreceptors, and our study investigated the potential impact of Rdh12 mutations on other organs and diseases, particularly hyperuricemia. We assessed Rdh12 mRNA expression levels in various tissues and conducted serum biochemical analyses in Rdh12-/- mice. Compared with the wild type, significant alterations in serum uric acid levels and kidney-related biochemical indicators have been revealed. Then further analysis, including quantitative RT-PCR of gene expression in the liver and kidney, highlighted variations in the expression levels of specific genes linked to hyperuricemia. And renal histology assessment exposed mild pathological lesions in the kidneys of Rdh12-/- mice. In summary, our study suggests that Rdh12 mutations impact not only retinal function but also contribute to hyperuricemia and renal disease phenotypes in mice. Our finding implies that individuals with Rdh12 mutations may be prone to hyperuricemia and gout, emphasizing the significance of preventive measures and regular examinations in daily life.

[Analysis of effectiveness of one-hole split endoscopy technique in treatment of lumbar spinal stenosis].

Objective: To investigate the effectiveness of one-hole split endoscope (OSE) technique in the treatment of single segment lumbar spinal stenosis (LSS). Methods: The clinical data of 32 single segment LSS patients treated with OSE technique for simple spinal canal decompression between January 2022 and December 2022, who met the selection criteria, were retrospectively analysed. There were 18 males and 14 females, the age ranged from 45 to 82 years, with an average of 65.1 years. The disease duration was 9-72 months, with an average of 34.9 months. The surgical segments included L 3, 4 in 3 cases, L 4, 5 in 19 cases, and L 5, S 1 in 10 cases. The incision length, operation time, intraoperative blood loss, intraoperative radiation exposure frequency, postoperative mobilization time, and the area of the patient's lesion segment dural sac before operation and at 1 month after operation were recorded. Low back pain and leg pain were assessed by visual analogue scale (VAS) score before operation and at 3 days, 3 months, and 12 months after operation; functional recovery was assessed by Oswestry disability index (ODI) before operation and at 3 months and 12 months after operation; the effectiveness was assessed by modified MacNab criteria at last follow-up. Results: All 32 patients successfully completed the operation, with an average incision length of 2.05 cm, an average operation time of 88.59 minutes, an average intraoperative blood loss of 46.72 mL, an average intraoperative radiation exposure frequency of 3.84 times, and an average postoperative mobilization time of 11.66 hours. All patients were followed up 12-16 months, with an average of 13.5 months. One patient experienced lower limb numbness, pain, and decreased muscle strength after operation, while the remaining patients did not experience complications such as dural tear or important nerve damage. The VAS scores of low back pain and leg pain and ODI in patients at various time points after operation were significantly better than preoperative ones, and each indicator further improved with time. The differences between time points were significant ( P<0.05). At 1 month after operation, the area of the patient's lesion segment dural sac was (123.13±19.66) mm 2, which significantly increased compared to preoperative (51.25±9.50) mm 2 ( t=-18.616, P<0.001). At last follow-up, the improved MacNab criteria were used to evaluate the effectiveness, with 18 cases achieving excellent results, 11 cases being good, and 3 cases being fair, with an excellent and good rate of 90.6%. Conclusion: The effectiveness of using OSE technique for simple spinal canal decompression treatment of single segment LSS is satisfactory, with the advantages of minimal surgical trauma and fast recovery.

[Adsorption Properties of Magnetic Phosphorous Camellia Oleifera Shells Biochar to Sulfamethoxazole in Water].

Magnetic phosphorous biochar （MPBC） was prepared from Camellia oleifera shells using phosphoric acid activation and iron co-deposition. The materials were characterized and analyzed through scanning electron microscopy （SEM）， X-ray diffractometry （XRD）， specific surface area and pore size analysis （BET）， Fourier infrared spectroscopy （FT-IR）， and X-ray photoelectron spectroscopy （XPS）. MPBC had a high surface area （1 139.28 m2·g-1） and abundant surface functional groups， and it could achieve fast solid-liquid separation under the action of an external magnetic field. The adsorption behavior and influencing factors of sulfamethoxazole （SMX） in water were investigated. The adsorbent showed excellent adsorption properties for SMX under acidic and neutral conditions， and alkaline conditions and the presence of CO32- had obvious inhibition on adsorption. The adsorption process conformed to the quasi-second-order kinetics and Langmuir model. The adsorption rate was fast， and the maximum adsorption capacity reached 356.49 mg·g-1. The adsorption process was a spontaneous exothermic reaction， and low temperature was beneficial to the adsorption. The adsorption mechanism was mainly the chemisorption of pyrophosphate surface functional groups （C-O-P bond） between the SMX molecule and MPBC and also included hydrogen bonding， π-π electron donor-acceptor （π-πEDA） interaction， and a pore filling effect. The development of MPBC adsorbent provides an effective way for resource utilization of waste Camellia oleifera shells and treatment of sulfamethoxazole wastewater.

Assessment and analysis of accents in air traffic control speech: a fusion of deep learning and information theory.

Introduction: Enhancing the generalization and reliability of speech recognition models in the field of air traffic control (ATC) is a challenging task. This is due to the limited storage, difficulty in acquisition, and high labeling costs of ATC speech data, which may result in data sample bias and class imbalance, leading to uncertainty and inaccuracy in speech recognition results. This study investigates a method for assessing the quality of ATC speech based on accents. Different combinations of data quality categories are selected according to the requirements of different model application scenarios to address the aforementioned issues effectively. Methods: The impact of accents on the performance of speech recognition models is analyzed, and a fusion feature phoneme recognition model based on prior text information is constructed to identify phonemes of speech uttered by speakers. This model includes an audio encoding module, a prior text encoding module, a feature fusion module, and fully connected layers. The model takes speech and its corresponding prior text as input and outputs a predicted phoneme sequence of the speech. The model recognizes accented speech as phonemes that do not match the transcribed phoneme sequence of the actual speech text and quantitatively evaluates the accents in ATC communication by calculating the differences between the recognized phoneme sequence and the transcribed phoneme sequence of the actual speech text. Additionally, different levels of accents are input into different types of speech recognition models to analyze and compare the recognition accuracy of the models. Result: Experimental results show that, under the same experimental conditions, the highest impact of different levels of accents on speech recognition accuracy in ATC communication is 26.37%. Discussion: This further demonstrates that accents affect the accuracy of speech recognition models in ATC communication and can be considered as one of the metrics for evaluating the quality of ATC speech.

RPL35A promotes the progression of cholangiocarcinoma by mediating HSPA8 ubiquitination.

BACKGROUND: Cholangiocarcinoma (CCA) is a biliary epithelial malignant tumor with an increasing incidence worldwide. Therefore, further understanding of the molecular mechanisms of CCA progression is required to identify new therapeutic targets. METHODS: The expression of RPL35A in CCA and para-carcinoma tissues was detected by immunohistochemical staining. IP-MS combined with Co-IP identified downstream proteins regulated by RPL35A. Western blot and Co-IP of CHX or MG-132 treated CCA cells were used to verify the regulation of HSPA8 protein by RPL35A. Cell experiments and subcutaneous tumorigenesis experiments in nude mice were performed to evaluate the effects of RPL35A and HSPA8 on the proliferation, apoptosis, cell cycle, migration of CCA cells and tumor growth in vivo. RESULTS: RPL35A was significantly upregulated in CCA tissues and cells. RPL35A knockdown inhibited the proliferation and migration of HCCC-9810 and HUCCT1 cells, induced apoptosis, and arrested the cell cycle in G1 phase. HSPA8 was a downstream protein of RPL35A and overexpressed in CCA. RPL35A knockdown impaired HSPA8 protein stability and increased HSPA8 protein ubiquitination levels. RPL35A overexpression promoted CCA cell proliferation and migration. HSPA8 knockdown inhibited CCA cell proliferation and migration, and reversed the promoting effect of RPL35A. Furthermore, RPL35A promoted tumor growth in vivo. In contrast, HSPA8 knockdown suppressed tumor growth, while was able to restore the effects of RPL35A overexpression. CONCLUSION: RPL35A was upregulated in CCA tissues and promoted the progression of CCA by mediating HSPA8 ubiquitination.

Analysis of Epidemiological and Issues Encountered in Case Reports on Echinococcosis - China, 2022.

What is already known about this topic?: Echinococcosis is classified as a Class C infectious disease in China. It is endemic in 370 counties located in the agricultural and pastoral regions of western China. What is added by this report?: This report provides a comprehensive overview of the cases of echinococcosis reported in China in 2022. Following a thorough evaluation conducted by provincial CDCs, it was identified that 105 new cases were not reported through the National Notifiable Disease Reporting System. Furthermore, there were 1,051 cases that were reported among patients who had been previously diagnosed with echinococcosis. What are the implications for public health practice?: The reported cases of echinococcosis in non-endemic counties of provincial-level administrative divisions where the disease is endemic need to be given more attention, as there is a potential risk of it spreading within the non-endemic areas. Inadequate reporting practices by clinical medical institutions are hindering the subsequent investigations carried out by CDCs. It is important to implement enhanced health promotion efforts that focus on high-risk populations to address unhealthy lifestyles.

Genetically supported causality between gut microbiota, immune cells and morphine tolerance: a two-sample Mendelian randomization study.

Background: Previous researches have suggested a significant connection between the gut microbiota/immune cells and morphine tolerance (MT), but there is still uncertainty regarding their causal relationship. Hence, our objective is to inverstigate this causal association and reveal the impact of gut microbiota/immune cells on the risk of developing MT using a two-sample Mendelian randomization (MR) study. Methods: We conducted a comprehensive analysis using genome-wide association study (GWAS) summary statistics for gut microbiota, immune cells, and MT. The main approach employed was the inverse variance-weighted (IVW) method in MR. To assess horizontal pleiotropy and remove outlier single-nucleotide polymorphisms (SNPs), we utilized the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) technique as well as MR-Egger regression. Heterogeneity detection was performed using Cochran's Q-test. Additionally, leave-one-out analysis was carried out to determine if any single SNP drove the causal association signals. Finally, we conducted a reverse MR to evaluate the potential of reverse causation. Results: We discovered that 6 gut microbial taxa and 16 immune cells were causally related to MT (p < 0.05). Among them, 2 bacterial features and 9 immunophenotypes retained a strong causal relationship with lower risk of MT: genus. Lachnospiraceae NK4A136group (OR: 0.962, 95% CI: 0.940-0.987, p = 0.030), genus. RuminococcaceaeUCG011 (OR: 0.960, 95% CI: 0.946-0.976, p = 0.003), BAFF-R on B cell (OR: 0.972, 95% CI: 0.947-0.998, p = 0.013). Furthermore, 4 bacterial features and 7 immunophenotypes were identified to be significantly associated with MT risk: genus. Flavonifractor (OR: 1.044, 95% CI: 1.017-1.069, p = 0.029), genus. Prevotella9 (OR: 1.054, 95% CI: 1.020-1.090, p = 0.037), B cell % CD3-lymphocyte (OR: 1.976, 95% CI: 1.027-1.129, p = 0.026). The Cochrane's Q test revealed no heterogeneity (p > 0.05). Furthermore, the MR-Egger and MR-PRESSO analyses reveal no instances of horizontal pleiotropy (p > 0.05). Besides, leave-one-out analysis confirmed the robustness of MR results. After adding BMI to the multivariate MR analysis, the gut microbial taxa and immune cells exposure-outcome effect were attenuated. Conclusion: Our research confirm the potential link between gut microbiota and immune cells with MT, shedding light on the mechanism by which gut microbiota and immune cells may contribute to MT. These findings lay the groundwork for future investigations into targeted prevention strategies.

MAPK1 Mediates MAM Disruption and Mitochondrial Dysfunction in Diabetic Kidney Disease via the PACS-2-Dependent Mechanism.

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease (ESRD). Mitochondrial dysfunction in renal tubules, occurring early in the disease, is linked to the development of DKD, although the underlying pathways remain unclear. Here, we examine diabetic human and mouse kidneys, and HK-2 cells exposed to high glucose, to show that high glucose disrupts mitochondria-associated endoplasmic reticulum membrane (MAM) and causes mitochondrial fragmentation. We find that high glucose conditions increase mitogen-activated protein kinase 1(MAPK1), a member of the MAP kinase signal transduction pathway, which in turn lowers the level of phosphofurin acidic cluster sorting protein 2 (PACS-2), a key component of MAM that tethers mitochondria to the ER. MAPK1-induced disruption of MAM leads to mitochondrial fragmentation but this can be rescued in HK-2 cells by increasing PACS-2 levels. Functional studies in diabetic mice show that inhibition of MAPK1 increases PACS-2 and protects against the loss of MAM and the mitochondrial fragmentation. Taken together, these results identify the MAPK1-PACS-2 axis as a key pathway to therapeutically target as well as provide new insights into the pathogenesis of DKD.

Forecasting environmental water availability of lakes using temporal fusion transformer: case studies of China's two largest freshwater lakes.

Preserving lacustrine ecosystems is vital for sustainable watershed development, and forecasting the environmental water availability of lakes would support policymakers in developing sound management strategies. This study proposed a methodology that merges the lake water level prediction and environmental water availability evaluation. The temporal fusion transformer (TFT) model forecasted the lake water levels for the next 7 days by inputting the streamflow and lake water level data for the past 30 days. The environmental water availability was assessed by comparing the forecasted lake water levels with the environmental water requirements, resulting in adequate, regular, scarce, and severely scarce environmental water availability. The methodology was tested in two case studies: Poyang Lake and Dongting Lake, the two largest freshwater lakes in the Yangtze River Basin, China. The TFT model performed well in forecasting the lake water levels, as shown by the high coefficient of determination and finite root mean square error. The coefficients of determination exceeded 0.98 during the model training, validation, and test for both Poyang Lake and Dongting Lake, and the root mean square errors ranged from 0.06 to 0.46 m. The accurate prediction of lake water level promoted the precise forecasting of the environmental water availability with the high Kappa coefficient exceeding 0.90. Results indicated the rationality and effectiveness of integrating the lake water level prediction and environmental water availability evaluation. Future research includes the applicability of the TFT model to other lakes worldwide to test the proposed approach and investigate strategies to cope with environmental water scarcity.

Highly Efficient Spatially-Temporally Synchronized Construction of Robust Li3 PO4 -rich Solid-Electrolyte Interphases in Aqueous Li-ion Batteries.

Solid electrolyte interphase (SEI) makes the electrochemical window of aqueous electrolytes beyond the thermodynamics limitation of water. However, achieving the energetic and robust SEI is more challenging in aqueous electrolytes because the low SEI formation efficiency (SFE) only contributed from anion-reduced products, and the low SEI formation quality (SFQ) negatively impacted by the hydrogen evolution, resulting in a high Li loss to compensate for SEI formation. Herein, we propose a highly efficient strategy to construct Spatially-Temporally Synchronized (STS) robust SEI by the involvement of synergistic chemical precipitation-electrochemical reduction. In this case, a robust Li3 PO4 -rich SEI enables intelligent inherent growth at the active site of the hydrogen by the chemical capture of the OH- stemmed from the HER to trigger the ionization balance of dihydrogen phosphate (H2 PO4 - ) shift to insoluble solid Li3 PO4 . It is worth highlighting that the Li3 PO4 formation does not extra-consume lithium derived from the cathode but makes good use of the product of HER (OH- ), prompting the SEI to achieve 100 % SFE and pushing the HER potential into -1.8 V vs. Ag/AgCl. This energetic and robust SEI offers a new way to achieve anion/concentration-independent interfacial chemistry for the aqueous batteries.

Whole grain germinated brown rice intake modulates the gut microbiota and alleviates hypertriglyceridemia and hypercholesterolemia in high fat diet-fed mice.

Hyperlipidemia is a common clinical disorder of lipid metabolism in modern society and is considered to be one of the major risk factors leading to cardiovascular-related diseases. Germinated brown rice (GBR) is a typical whole grain food. The lipid-lowering effect of GBR has received increasing attention, but its mechanism of action is not fully understood. The gut microbiota has been proposed as a novel target for the treatment of hyperlipidemia. The aim of this study was to investigate the effects of GBR on the gut microbiota and lipid metabolism in high-fat diet (HFD)-fed C57BL/6J mice. The effect of GBR on hyperlipidemia was evaluated by measuring blood lipid levels and by pathological examination. The gut microbiota was detected by 16S rRNA sequencing, and the protein and mRNA expression levels involved in cholesterol metabolism were detected by western blotting and RT-qPCR to find potential correlations. The results showed that GBR supplementation could effectively reduce the levels of TC, TG, LDL-C and HDL-C in the serum and alleviate the excessive accumulation of fat droplets caused by HFD. Moreover, GBR intervention improved HFD-fed gut microbiota disorder via increasing the diversity of the gut microbiota, reducing the Firmicutes/Bacteroidetes ratio, and improving gut barrier damage. In addition, GBR could inhibit endogenous cholesterol synthesis and promote cholesterol transport and excretion. These findings suggest that GBR may be a competitive candidate for the development of functional foods to prevent abnormal lipid metabolism.