The Easily Overlooked Effect of Global Warming: Diffusion of Heavy Metals.

Since industrialization, global temperatures have continued to rise. Human activities have resulted in heavy metals being freed from their original, fixed locations. Because of global warming, glaciers are melting, carbon dioxide concentrations are increasing, weather patterns are shifting, and various environmental forces are at play, resulting in the movement of heavy metals and alteration of their forms. In this general context, the impact of heavy metals on ecosystems and organisms has changed accordingly. For most ecosystems, the levels of heavy metals are on the rise, and this rise can have a negative impact on the ecosystem as a whole. Numerous studies have been conducted to analyze the combined impacts of climate change and heavy metals. However, the summary of the current studies is not perfect. Therefore, this review discusses how heavy metals affect ecosystems during the process of climate change from multiple perspectives, providing some references for addressing the impact of climate warming on environmental heavy metals.

Integrated Analysis of scRNA-Seq and Bulk RNA-Seq Reveals Metabolic Reprogramming of Liver Cancer and Establishes a Prognostic Risk Model.

Liver cancer manifests as a profoundly heterogeneous malignancy, posing significant challenges in terms of both therapeutic intervention and prognostic evaluation. Given that the liver is the largest metabolic organ, a prognostic risk model grounded in single-cell transcriptome analysis and a metabolic perspective can facilitate precise prevention and treatment strategies for liver cancer. Hence, we identified 11 cell types in a scRNA-seq profile comprising 105,829 cells and found that the metabolic activity of malignant cells increased significantly. Subsequently, a prognostic risk model incorporating tumor heterogeneity, cell interactions, tumor cell metabolism, and differentially expressed genes was established based on eight genes; this model can accurately distinguish the survival outcomes of liver cancer patients and predict the response to immunotherapy. Analyzing the immune status and drug sensitivity of the high- and low-risk groups identified by the model revealed that the high-risk group had more active immune cell status and greater expression of immune checkpoints, indicating potential risks associated with liver cancer-targeted drugs. In summary, this study provides direct evidence for the stratification and precise treatment of liver cancer patients, and is an important step in establishing reliable predictors of treatment efficacy in liver cancer patients.

Peptides Used for Heavy Metal Remediation: A Promising Approach.

In recent years, heavy metal pollution has become increasingly prominent, severely damaging ecosystems and biodiversity, and posing a serious threat to human health. However, the results of current methods for heavy metal restoration are not satisfactory, so it is urgent to find a new and effective method. Peptides are the units that make up proteins, with small molecular weights and strong biological activities. They can effectively repair proteins by forming complexes, reducing heavy metal ions, activating the plant's antioxidant defense system, and promoting the growth and metabolism of microorganisms. Peptides show great potential for the remediation of heavy metal contamination due to their special structure and properties. This paper reviews the research progress in recent years on the use of peptides to remediate heavy metal pollution, describes the mechanisms and applications of remediation, and provides references for the remediation of heavy metal pollution.

Soil Microplastic Pollution and Microbial Breeding Techniques for Green Degradation: A Review.

Microplastics (MPs), found in many places around the world, are thought to be more detrimental than other forms of plastics. At present, physical, chemical, and biological methods are being used to break down MPs. Compared with physical and chemical methods, biodegradation methods have been extensively studied by scholars because of their advantages of greenness and sustainability. There have been numerous reports in recent years summarizing the microorganisms capable of degrading MPs. However, there is a noticeable absence of a systematic summary on the technology for breeding strains that can degrade MPs. This paper summarizes the strain-breeding technology of MP-degrading strains for the first time in a systematic way, which provides a new idea for the breeding of efficient MP-degrading strains. Meanwhile, potential techniques for breeding bacteria that can degrade MPs are proposed, providing a new direction for selecting and breeding MP-degrading bacteria in the future. In addition, this paper reviews the sources and pollution status of soil MPs, discusses the current challenges related to the biodegradation of MPs, and emphasizes the safety of MP biodegradation.

Estimation of Photosynthetic Induction Is Significantly Affected by Light Environments of Local Leaves and Whole Plants in Oryza Genus.

Photosynthetic induction and stomatal kinetics are acknowledged as pivotal factors in regulating both plant growth and water use efficiency under fluctuating light conditions. However, the considerable variability in methodologies and light regimes used to assess the dynamics of photosynthesis (A) and stomatal conductance (gs) during light induction across studies poses challenges for comparison across species. Moreover, the influence of stomatal morphology on both steady-state and non-steady-state gs remains poorly understood. In this study, we show the strong impact of IRGA Chamber Illumination and Whole Plant Illumination on the photosynthetic induction of two rice species. Our findings reveal that these illuminations significantly enhance photosynthetic induction by modulating both stomatal and biochemical processes. Moreover, we observed that a higher density of smaller stomata plays a critical role in enhancing the stomatal opening and photosynthetic induction to fluctuating light conditions, although it exerts minimal influence on steady-state gs and A under constant light conditions. Therefore, future studies aiming to estimate photosynthetic induction and stomatal kinetics should consider the light environments at both the leaf and whole plant levels.

Porosity and surface curvature effects on the permeability and wall shear stress of trabecular bone: Guidelines for biomimetic scaffolds for bone repair.

Scaffolds are an essential component of bone tissue engineering to provide support and create a physiological environment for cells. Biomimetic scaffolds are a promising approach to fulfill the requirements. Bone allografts are widely used scaffolds due to their mechanical and structural characteristics. The scaffold geometry is well known to be an important determinant of induced mechanical stimulation felt by the cells. However, the impact of allograft geometry on permeability and wall shear stress distribution is not well understood. This information is essential for designing biomimetic scaffolds that provide a suitable environment for cells to proliferate and differentiate. The present study investigates the effect of geometry on the permeability and wall shear stress of bone allografts at both macroscopic and microscopic scales. Our results concluded that the wall shear stress was strongly correlated with the porosity of the allograft. The level of wall shear stress at a local scale was also determined by the surface curvature characteristics. The results of this study can serve as a guideline for future biomimetic scaffold designs that provide a mechanical environment favorable for osteogenesis and bone repair.

Impact of Vanadium-Titanium-Magnetite Mining Activities on Endophytic Bacterial Communities and Functions in the Root Systems of Local Plants.

This study utilized 16S rRNA high-throughput sequencing technology to analyze the community structure and function of endophytic bacteria within the roots of three plant species in the vanadium-titanium-magnetite (VTM) mining area. The findings indicated that mining activities of VTM led to a notable decrease in both the biodiversity and abundance of endophytic bacteria within the root systems of Eleusine indica and Carex (p < 0.05). Significant reductions were observed in the populations of Nocardioides, concurrently with substantial increments in the populations of Pseudomonas (p < 0.05), indicating that Pseudomonas has a strong adaptability to this environmental stress. In addition, ß diversity analysis revealed divergence in the endophytic bacterial communities within the roots of E. indica and Carex from the VTM mining area, which had diverged to adapt to the environmental stress caused by mining activity. Functional enrichment analysis revealed that VTM mining led to an increase in polymyxin resistance, nicotinate degradation I, and glucose degradation (oxidative) (p < 0.05). Interestingly, we found that VTM mining did not notably alter the endophytic bacterial communities or functions in the root systems of Dodonaea viscosa, indicating that this plant can adapt well to environmental stress. This study represents the primary investigation into the influence of VTM mining activities on endophytic bacterial communities and the functions of nearby plant roots, providing further insight into the impact of VTM mining activities on the ecological environment.

Application of Strain Selection Technology in Alcoholic Beverages: A Review.

The diversity of alcohol beverage microorganisms is of great significance for improving the brewing process and the quality of alcohol beverage products. During the process of making alcoholic beverages, a group of microorganisms, represented by yeast and lactic acid bacteria, conducts fermentation. These microorganisms have complex synergistic or competitive relationships, and the participation of different microorganisms has a major impact on the fermentation process and the flavor and aroma of the product. Strain selection is one of the key steps. Utilizing scientific breeding technology, the relationship between strains can be managed, the composition of the alcoholic beverage microbial community can be improved, and the quality and flavor of the alcoholic beverage products can be increased. Currently, research on the microbial diversity of alcohol beverages has received extensive attention. However, the selection technology for dominant bacteria in alcohol beverages has not yet been systematically summarized. To breed better-quality alcohol beverage strains and improve the quality and characteristics of wine, this paper introduces the microbial diversity characteristics of the world's three major brewing alcohols: beer, wine, and yellow wine, as well as the breeding technologies of related strains. The application of culture selection technology in the study of microbial diversity of brewed wine was reviewed and analyzed. The strain selection technology and alcohol beverage process should be combined to explore the potential application of a diverse array of alcohol beverage strains, thereby boosting the quality and flavor of the alcohol beverage and driving the sustainable development of the alcoholic beverage industry.

Intraspecific and interspecific variations in the synonymous codon usage in mitochondrial genomes of 8 pleurotus strains.

In this study, we investigated the codon bias of twelve mitochondrial core protein coding genes (PCGs) in eight Pleurotus strains, two of which are from the same species. The results revealed that the codons of all Pleurotus strains had a preference for ending in A/T. Furthermore, the correlation between codon base compositions and codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) indices was also detected, implying the influence of base composition on codon bias. The two P. ostreatus species were found to have differences in various base bias indicators. The average effective number of codons (ENC) of mitochondrial core PCGs of Pleurotus was found to be less than 35, indicating strong codon preference of mitochondrial core PCGs of Pleurotus. The neutrality plot analysis and PR2-Bias plot analysis further suggested that natural selection plays an important role in Pleurotus codon bias. Additionally, six to ten optimal codons (ΔRSCU > 0.08 and RSCU > 1) were identified in eight Pleurotus strains, with UGU and ACU being the most widely used optimal codons in Pleurotus. Finally, based on the combined mitochondrial sequence and RSCU value, the genetic relationship between different Pleurotus strains was deduced, showing large variations between them. This research has improved our understanding of synonymous codon usage characteristics and evolution of this important fungal group.

The Diversity and Community Composition of Three Plants' Rhizosphere Fungi in Kaolin Mining Areas.

Mining activities in the kaolin mining area have led to the disruption of the ecological health of the mining area and nearby soils, but the effects on the fungal communities in the rhizosphere soils of the plants are not clear. Three common plants (Conyza bonariensis, Artemisia annua, and Dodonaea viscosa) in kaolin mining areas were selected and analyzed their rhizosphere soil fungal communities using ITS sequencing. The alpha diversity indices (Chao1, Shannon, Simpson, observed-species, pielou-e) of the fungal communities decreased to different extents in different plants compared to the non-kauri mining area. The ß-diversity (PCoA, NMDS) analysis showed that the rhizosphere soil fungal communities of the three plants in the kaolin mine area were significantly differentiated from those of the control plants grown in the non-kaolin mine area, and the extent of this differentiation varied among the plants. The analysis of fungal community composition showed that the dominant fungi in the rhizosphere fungi of C. bonariensis and A. annua changed, with an increase in the proportion of Mycosphaerella (genus) by about 20% in C. bonariensis and A. annua. An increase in the proportion of Didymella (genus) by 40% in D. viscosa was observed. At the same time, three plant rhizosphere soils were affected by kaolin mining activities with the appearance of new fungal genera Ochrocladosporium and Plenodomus. Predictive functional potential analysis of the samples revealed that a significant decrease in the potential of functions such as biosynthesis and glycolysis occurred in the rhizosphere fungal communities of kaolin-mined plants compared to non-kaolin-mined areas. The results show that heavy metals and plant species are the key factors influencing these changes, which suggests that selecting plants that can bring more abundant fungi can adapt to heavy metal contamination to restore soil ecology in the kaolin mining area.

Association between diabetes mellitus and primary biliary cholangitis: a two-sample Mendelian randomization study.

Background: Previous observational studies have demonstrated a link between diabetes mellitus(DM) and primary biliary cholangitis (PBC). Nevertheless, since these relationships might be confused, whether there is any causal connection or in which direction it exists is unclear. Our investigation aimed to identify the causal associations between DM and PBC. Methods: We acquired genome-wide association study (GWAS) datasets for PBC, Type 1 diabetes(T1DM), and Type 2 diabetes(T2DM) from published GWASs. Inverse variance-weighted (IVW), MR-Egger, weighted median (WM), Simple mode, and weighted mode methods were used to determine the causal relationships between DM(T1DM or T2DM) and PBC. Sensitivity analyses were also carried out to ensure the results were robust. To determine the causal relationship between PBC and DM(T1DM or T2DM), we also used reverse MR analysis. Results: T1DM was associated with a higher risk of PBC (OR 1.1525; 95% CI 1.0612-1.2517; p = 0.0007) in the IVW method, but no evidence of a causal effect T2DM on PBC was found (OR 0.9905; 95% CI 0.8446-1.1616; p = 0.9071) in IVW. Results of the reverse MR analysis suggested genetic susceptibility that PBC was associated with an increased risk of T1DM (IVW: OR 1.1991; 95% CI 1.12-1.2838; p = 1.81E-07), but no evidence of a causal effect PBC on T2DM was found (IVW: OR 1.0101; 95% CI 0.9892-1.0315; p = 0.3420). Conclusion: The current study indicated that T1DM increased the risk of developing PBC and vice versa. There was no proof of a causal connection between PBC probability and T2DM. Our results require confirmation through additional replication in larger populations.

Identification and functional analysis of the hub Ferroptosis-Related gene EZH2 in diabetic kidney disease.

BACKGROUND: Diabetic kidney disease (DKD) is a common microvascular complication and one of the main causes of death in diabetes. Ferroptosis, an iron-dependent mode of cell death characterized by lipid ROS accumulation, was found to be associated with a number of diseases and has great potential for kidney diseases. It has great value to identify potential ferroptosis-related genes and their biological mechanisms in DKD. METHODS: We obtained the GSE30122 dataset from Gene Expression Omnibus (GEO) database and ferroptosis-related genes from the Ferrdb database. After differential expression analysis, and three machine learning algorithms, the hub ferroptosis-related gene EZH2 was identified. In order to investigate the function of EZH2, Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA) and single cell analysis were conducted. The expression of EZH2 was validated in DKD patients, HK-2 cell models and DKD mouse models. EZH2 knockdown HK-2 cells and HK-2 cells treated with GSK126 were performed to verify whether EZH2 affected ferroptosis in DKD. CHIP assay was used to detect whether EZH2 regulated ferroptosis by suppressing SLC7A11. Molecular docking was performed to explore EZH2 and four traditional Chinese medicine (Sennoside A, Berberine, Umbelliferone, Platycodin D) related to ferroptosis in DKD treatment. RESULTS: According to the GSE30122 dataset in GEO and ferroptosis-related genes from the Ferrb database, we obtained the hub ferroptosis-related gene EZH2 in DKD via diversified machine learning methods. The increasing of EZH2 expression was shown in single cell analysis, DKD patients, DKD mouse models and high glucose induced DKD cell models. Further study showed that EZH2 knockdown and inhibition can alleviate HG-induced ferroptosis in vitro. CHIP assay showed EZH2-mediated epigenetic silencing regulated the expression of SLC7A11. Molecular docking results showed that EZH2 had strong binding stability with Sennoside A, Berberine, Umbelliferone, and Platycodin D. CONCLUSION: Overall, our data shouwed that histone H3K27 methyltransferase EZH2 could regulate the renal tubular epithelial cell ferroptosis by suppressing SLC7A11 in DKD, which may serve as a credible reliable indicator for diagnosing DKD and a potential target for treatment.

Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks.

Quantitative susceptibility mapping (QSM) is a post-processing technique for deriving tissue magnetic susceptibility distribution from MRI phase measurements. Deep learning (DL) algorithms hold great potential for solving the ill-posed QSM reconstruction problem. However, a significant challenge facing current DL-QSM approaches is their limited adaptability to magnetic dipole field orientation variations during training and testing. In this work, we propose a novel Orientation-Adaptive Latent Feature Editing (OA-LFE) module to learn the encoding of acquisition orientation vectors and seamlessly integrate them into the latent features of deep networks. Importantly, it can be directly Plug-and-Play (PnP) into various existing DL-QSM architectures, enabling reconstructions of QSM from arbitrary magnetic dipole orientations. Its effectiveness is demonstrated by combining the OA-LFE module into our previously proposed phase-to-susceptibility single-step instant QSM (iQSM) network, which was initially tailored for pure-axial acquisitions. The proposed OA-LFE-empowered iQSM, which we refer to as iQSM+, is trained in a simulated-supervised manner on a specially-designed simulation brain dataset. Comprehensive experiments are conducted on simulated and in vivo human brain datasets, encompassing subjects ranging from healthy individuals to those with pathological conditions. These experiments involve various MRI platforms (3T and 7T) and aim to compare our proposed iQSM+ against several established QSM reconstruction frameworks, including the original iQSM. The iQSM+ yields QSM images with significantly improved accuracies and mitigates artifacts, surpassing other state-of-the-art DL-QSM algorithms. The PnP OA-LFE module's versatility was further demonstrated by its successful application to xQSM, a distinct DL-QSM network for dipole inversion. In conclusion, this work introduces a new DL paradigm, allowing researchers to develop innovative QSM methods without requiring a complete overhaul of their existing architectures.

Quantitative susceptibility mapping through model-based deep image prior (MoDIP).

The data-driven approach of supervised learning methods has limited applicability in solving dipole inversion in Quantitative Susceptibility Mapping (QSM) with varying scan parameters across different objects. To address this generalization issue in supervised QSM methods, we propose a novel training-free model-based unsupervised method called MoDIP (Model-based Deep Image Prior). MoDIP comprises a small, untrained network and a Data Fidelity Optimization (DFO) module. The network converges to an interim state, acting as an implicit prior for image regularization, while the optimization process enforces the physical model of QSM dipole inversion. Experimental results demonstrate MoDIP's excellent generalizability in solving QSM dipole inversion across different scan parameters. It exhibits robustness against pathological brain QSM, achieving over 32 % accuracy improvement than supervised deep learning methods. It is also 33 % more computationally efficient and runs 4 times faster than conventional DIP-based approaches, enabling 3D high-resolution image reconstruction in under 4.5 min.

Modular Synthesis of 1,2-Benzothiazines and 1,2-Benzothiazine 1-Imines via Palladium-Catalyzed C-H/C-C Activation Reactions.

In this study, a modular approach toward cyclic sulfoximines and sulfondiimines via palladium-catalyzed intramolecular C-H/C-C activation reactions was reported. Various 1,2-benzothiazines including bicyclic, tricyclic, highly fused ones, ones of the seven-membered ring, along with 1,2-benzothiazine 1-imines were accessed in good yields. KIE experiment demonstrated that the C-H bond cleavage at the position ortho to the sulfoximine group is not the rate-determining step in the coupling reaction.

New chromone derivatives bearing thiazolidine-2,4-dione moiety as potent PTP1B inhibitors: Synthesis and biological activity evaluation.

A series of chromone derivatives bearing thiazolidine-2,4-dione moiety (5 âˆ¼ 37) were synthesized and evaluated for their PTP1B inhibitory activity, interaction analysis and effects on insulin pathway in palmitic acid (PA)-induced HepG2 cells. The results showed that all derivatives presented potential PTP1B inhibitory activity with IC50 values of 1.40 ± 0.04 âˆ¼ 16.83 ± 0.54 µM comparing to that of positive control lithocholic acid (IC50: 9.62 ± 0.14 µM). Among them, compound 9 had the strongest PTP1B inhibitory activity with the IC50 value of 1.40 ± 0.04 µM. Inhibition kinetic study revealed that compound 9 was a reversible mixed-type inhibitor against PTP1B. CD spectra results confirmed that compound 9 changed the secondary structure of PTP1B by their interaction. Molecular docking explained the detailed binding between compound 9 and PTP1B. Compound 9 also showed 19-fold of selectivity for PTP1B over TCPTP. Moreover compound 9 could recovery PA-induced insulin resistance by increasing the phosphorylation of IRSI and AKT. CETSA results showed that compound 9 significantly increased the thermal stability of PTP1B.

CROST: a comprehensive repository of spatial transcriptomics.

The development of spatial transcriptome sequencing technology has revolutionized our comprehension of complex tissues and propelled life and health sciences into an era of spatial omics. However, the current availability of databases for accessing and analyzing spatial transcriptomic data is limited. In response, we have established CROST (https://ngdc.cncb.ac.cn/crost), a comprehensive repository of spatial transcriptomics. CROST encompasses high-quality samples and houses 182 spatial transcriptomic datasets from diverse species, organs, and diseases, comprising 1033 sub-datasets and 48 043 tumor-related spatially variable genes (SVGs). Additionally, it encompasses a standardized spatial transcriptome data processing pipeline, integrates single-cell RNA sequencing deconvolution spatial transcriptomics data, and evaluates correlation, colocalization, intercellular communication, and biological function annotation analyses. Moreover, CROST integrates the transcriptome, epigenome, and genome to explore tumor-associated SVGs and provides a comprehensive understanding of their roles in cancer progression and prognosis. Furthermore, CROST provides two online tools, single-sample gene set enrichment analysis and SpatialAP, for users to annotate and analyze the uploaded spatial transcriptomics data. The user-friendly interface of CROST facilitates browsing, searching, analyzing, visualizing, and downloading desired information. Collectively, CROST offers fresh and comprehensive insights into tissue structure and a foundation for understanding multiple biological mechanisms in diseases, particularly in tumor tissues.

HALL: a comprehensive database for human aging and longevity studies.

Diverse individuals age at different rates and display variable susceptibilities to tissue aging, functional decline and aging-related diseases. Centenarians, exemplifying extreme longevity, serve as models for healthy aging. The field of human aging and longevity research is rapidly advancing, garnering significant attention and accumulating substantial data in recent years. Omics technologies, encompassing phenomics, genomics, transcriptomics, proteomics, metabolomics and microbiomics, have provided multidimensional insights and revolutionized cohort-based investigations into human aging and longevity. Accumulated data, covering diverse cells, tissues and cohorts across the lifespan necessitates the establishment of an open and integrated database. Addressing this, we established the Human Aging and Longevity Landscape (HALL), a comprehensive multi-omics repository encompassing a diverse spectrum of human cohorts, spanning from young adults to centenarians. The core objective of HALL is to foster healthy aging by offering an extensive repository of information on biomarkers that gauge the trajectory of human aging. Moreover, the database facilitates the development of diagnostic tools for aging-related conditions and empowers targeted interventions to enhance longevity. HALL is publicly available at https://ngdc.cncb.ac.cn/hall/index.

Synthesis and biological evaluation of indole derivatives containing thiazolidine-2,4-dione as α-glucosidase inhibitors with antidiabetic activity.

In order to develop potential α-glucosidase inhibitors with antidiabetic activity, twenty-six indole derivatives containing thiazolidine-2,4-dione were synthesized. All compounds presented potential α-glucosidase inhibitory activities with IC50 values ranging from 2.35 ± 0.11 to 24.36 ± 0.79 µM, respectively compared to acarbose (IC50 = 575.02 ± 10.11 µM). Especially, compound IT4 displayed the strongest α-glucosidase inhibitory activity (IC50 = 2.35 ± 0.11 µM). The inhibition mechanism of compound IT4 on α-glucosidase was clarified by the investigation of kinetics studies, fluorescence quenching, CD spectra, 3D fluorescence spectra, and molecular docking. In vivo antidiabetic experiments demonstrated that oral administration of compound IT4 would suppress fasting blood glucose level and ameliorate their glucose tolerance and dyslipidemia in diabetic mice.

Homogenized NiOx nanoparticles for improved hole transport in inverted perovskite solar cells.

The power conversion efficiency (PCE) of inverted perovskite solar cells (PSCs) is still lagging behind that of conventional PSCs, in part because of inefficient carrier transport and poor morphology of hole transport layers (HTLs). We optimized self-assembly of [4-(3,6-dimethyl-9H-carbazol-9-yl)butyl]phosphonic acid (Me-4PACz) onto nickel oxide (NiOx) nanoparticles as an HTL through treatment with hydrogen peroxide, which created a more uniform dispersion of nanoparticles with high conductivity attributed to the formation of Ni3+ as well as surface hydroxyl groups for bonding. A 25.2% certified PCE for a mask size of 0.074 square centimeters was obtained. This device maintained 85.4% of the initial PCE after 1000 hours of stabilized power output operation under 1 sun light irradiation at about 50°C and 85.1% of the initial PCE after 500 hours of accelerated aging at 85°C. We obtained a PCE of 21.0% for a minimodule with an aperture area of 14.65 square centimeters.