Soil heavy metal pollution promotes extracellular enzyme production by mediating microbial community structure during vegetation restoration of metallic tailing reservoir.

Vegetation restoration in metallic tailing reservoirs is imperative to restore the post-mining degraded ecosystems. Extracellular enzymes determine microbial resource acquisition in soils, yet the mechanisms controlling the enzyme activity and stoichiometry during vegetation restoration in metallic tailing reservoirs remain elusive. Here, we investigated the variations and drivers of C-, N- and P-acquiring enzymes together with microbial community along a 50-year vegetation restoration chronosequence in the China's largest vanadium titano-magnetite tailing reservoir. We found a parabolic pattern in the enzyme activity and efficiency along the chronosequence, peaking at the middle restoration stage (~30 years) with approximately six-fold increase relative to the initial 1-year site. The enzyme ratios of C:P and N:P decreased by 33 % and 68 % along the chronosequence, respectively, indicating a higher microbial demand of C and N at the early stage and a higher demand of P at the later stage. Soil nutrients directly determined the enzyme activities and stoichiometry, whereas microbial biomass and community structure regulated the temporal pattern of the enzyme efficiency. Surprisingly, increased heavy metal pollution imposed a positive effect on the enzyme efficiency indirectly by altering microbial community structure. This was evidenced by the increased microbial diversity and the conversion of copiotrophic to oligotrophic and stress-tolerant taxa along the chronosequence. Our findings provide new insights into microbial functioning in soil nutrient dynamics during vegetation restoration under increasing heavy metal pollution.

Microbial nutrient limitation and carbon use efficiency changes under different degrees of litter decomposition.

Alpine ecosystems are important terrestrial carbon (C) pools, and microbial decomposers play a key role in litter decomposition. Microbial metabolic limitations in these ecosystems, however, remain unclear. The objectives of this study aim to elucidate the characteristics of microbial nutrient limitation and their C use efficiency (CUE), and to evaluate their response to environmental factors. Five ecological indicators were utilized to assess and compare the degree of microbial elemental homeostasis and the nutrient limitations of the microbial communities among varying stages of litter decomposition (L, F, and H horizon) along an altitudinal gradient (2800, 3000, 3250, and 3500 m) under uniform vegetation (Abies fabri) on Gongga Mountain, eastern Tibetan Plateau. In this study, microorganisms in the litter reached a strictly homeostatic of C content exclusively during the middle stage of litter decomposition (F horizon). Based on the stoichiometry of soil enzymes, we observed that microbial N- and P-limitation increased during litter degradation, but that P-limitation was stronger than N-limitation at the late stages of degradation (H horizon). Furthermore, an increase in microbial CUE corresponded with a reduction in microbial C-limitation. Additionally, redundancy analysis (RDA) based on forward selection further showed that microbial biomass C (MBC) is closely associated with the enzyme activities and their ratios, and MBC was also an important factor in characterizing changes in microbial nutrient limitation and CUE. Our findings suggest that variations in MBC, rather than N- and P-related components, predominantly influence microbial metabolic processes during litter decomposition on Gongga Mountain, eastern Tibetan Plateau.

Analysis of extreme ultraviolet radiation and hydrodynamics simulation at the core of laser-produced nickel plasmas.

The non-uniformity and transient nature of laser-produced plasma are critical factors that affect the analysis of the extreme ultraviolet spectra of highly charged ions and the diagnosis of plasma states. This paper systematically investigates the characteristics of extreme ultraviolet radiation and the hydrodynamic evolution of laser-produced nickel plasmas from two perspectives: high-spatio-temporal-resolution extreme-ultraviolet spectroscopic measurement and radiation hydrodynamics simulation. The consistency between the four-band experimental spectra and their theoretically simulated spectra confirms the accuracy of the atomic structure parameters and plasma state parameters. We also analyze the significant contribution of the 3d-4f double-excited state radiation to the spectral profile and discuss the influence of the self-absorption caused by plasma opacity on the characteristics of extreme ultraviolet radiation. The findings are crucial for accurately understanding the characteristics of extreme ultraviolet radiation, the hydrodynamic evolution, and the application of medium- and high-Z laser-produced plasma as a pulsed short-wavelength light source.

Association of Pro-Inflammatory Diet, Smoking, and Alcohol Consumption with Bladder Cancer: Evidence from Case-Control and NHANES Studies from 1999 to 2020.

BACKGROUND AND PURPOSE: Diet might be a modifiable factor in preventing cancer by modulating inflammation. This study aims to explore the association between the dietary inflammatory index (DII) score and the risk of bladder cancer (BC). METHODS: A total of 112 BC patients and 292 control subjects were enrolled in a case-control trial. Additionally, we tracked a total of 109 BC patients and 319 controls, whose propensity scores were obtained from the Nutrition Examination Survey (NHANES) database spanning from 1999 to 2020. The baseline index and dietary intake data were assessed using a food frequency questionnaire (FFQ). DII scores were calculated based on the dietary intake of 20 nutrients obtained from participants and categorized into four groups. The association between the inflammatory potential of the diet and BC risk was investigated using multivariate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: High DII scores were associated with a pro-inflammatory diet and a higher risk of BC, with higher DII scores positively associated with a higher risk of BC (quartiles 4 vs. 1, ORs 4.89, 95% CIs 2.09-11.25 p < 0.001). Specifically, this might promote BC development by inducing oxidative stress and affecting DNA repair mechanisms. This result was consistent with the NHANES findings (quartiles 4 vs. 1, ORs 2.69, 95% CIs 1.25-5.77, p = 0.006) and further supported the association of pro-inflammatory diet and lifestyle factors with the risk of BC. CONCLUSIONS: Diets with the highest pro-inflammatory potential were associated with an increased risk of BC. By adjusting lifestyle factors, individuals might effectively lower their DII, thereby reducing the risk of developing BC. The results are consistent with the NHANES cohort.

HCCDB v2.0: Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC.

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). Integrated 15 transcriptomic datasets of HCC clinical samples, the first version of HCC database (HCCDB v1.0) was released in 2018. Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets, it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. With four years having passed, the database now needs integration of recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

Diverse amdoparvoviruses infection of farmed Asian badgers (Meles meles).

Amdoparvoviruses infect various carnivores, including mustelids, canids, skunks, and felids. Aleutian mink disease virus (AMDV) belongs to the prototypical species Amdoparvovirus carnivoran1. Here, we identified a novel amdoparvovirus in farmed Asian badgers (Meles meles), and we named this virus "Meles meles amdoparvovirus" (MMADV). A total of 146 clinical samples were collected from 134 individual badgers, and 30.6% (41/134) of the sampled badgers tested positive for amdoparvovirus by PCR. Viral DNA was detected in feces, blood, spleen, liver, lung, and adipose tissue from these animals. Viral sequences from eight samples were determined, five of which represented nearly full-length genome sequences (4,237-4,265 nt). Six serum samples tested positive by PCR, CIEP, and IAT, four of which had high antibody titers (> 512) against AMDV-G. Twenty-six of the 41 amdoparvovirus-positive badgers showed signs of illness, and necropsy revealed lesions in their organs. Sequence comparisons and phylogenetic analysis of the viral NS1 and VP2 genes of these badger amdoparvoviruses showed that their NS1 proteins shared 62.6%-88.8% sequence identity with known amdoparvoviruses, and they clustered phylogenetically into two related clades. The VP2 proteins shared 76.6%-97.2% identity and clustered into two clades, one of which included raccoon dog and arctic fox amdoparvovirus (RFAV), and the other of which did not include other known amdoparvoviruses. According to the NS1-protein-based criterion for parvovirus species demarcation, the MMADV isolate from farm YS should be classified as a member of a new species of the genus Amdoparvovirus. In summary, we have discovered a novel MMADV and other badger amdoparvoviruses that naturally infect Asian badgers and are possibly pathogenic in badgers.

A high-resolution dataset of water bodies distribution over the Tibetan Plateau.

Water body (WB) extraction is the basic work of water resources management. Tibetan Plateau is one of the largest alpine lake systems in the world. However, research on the characteristics of water bodies (WBs) is mainly focused on large and medium WBs due to spatial resolution. This research presents a dataset containing a 2-m resolution map of WBs in 2020 based on Gaofen-1 data, and morphometric and landscape indices of WBs across the Tibetan Plateau. The Swin-UNet model is well performed with overall accuracy at 98%. The total area of WBs is 56354.6 km2 across Tibetan Plateau in 2020. The abundance compared with that from size-abundance relationship indicate WBs in the Tibetan Plateau conformed to the classic power scaling law. We evaluate the influence of spatial-resolution in WB extraction, which shows the dataset could be valuable to fill the gap of existing WBs map, especially for small waters. The dataset is valuable for revealing the spatial patterns of WBs, and understanding the impacts of climate change on water resources in Plateau.

Warming-induced shifts in alpine soil microbiome: An ecosystem-scale study with environmental context-dependent insights.

Climate warming is a pressing global issue with substantial impacts on soil health and function. However, the influence of environmental context on the responses of soil microorganisms to warming remains largely elusive, particularly in alpine ecosystems. This study examined the responses of the soil microbiome to in situ experimental warming across three elevations (3850 m, 4100 m, and 4250 m) in the meadow of Gongga Mountain, eastern Tibetan Plateau. Our findings demonstrate that soil microbial diversity is highly resilient to warming, with significant impacts observed only at specific elevations. Furthermore, the influence of warming on the composition of the soil microbial community is also elevation-dependent, underscoring the importance of local environmental context in shaping microbial evolution in alpine soils under climate warming. Notably, we identified soil moisture at 3850 m and carbon-to-nitrogen ratio at 4250 m as indirect predictors regulating the responses of microbial diversity to warming at specific elevations. These findings underscore the paramount importance of considering pre-existing environmental conditions in predicting the response of alpine soil microbiomes to climate warming. Our study provides novel insights into the intricate interactions between climate warming, soil microbiome, and environmental context in alpine ecosystems, illuminating the complex mechanisms governing soil microbial ecology in these fragile and sensitive environments.

Occurrence and fate of current-use pesticides in Chinese forest soils.

Pesticides play a crucial role in securing global food production to meet increasing demands. However, because of their pervasive use, they are now ubiquitous environmental pollutants that have adverse effects on both ecosystems and human health. In this study, the environmental occurrence and fate of 16 current-use pesticides (CUPs) were investigated in 93 forest soil samples obtained from 11 distinct mountains in China. The concentrations of the target pesticides ranged from 0.36 to 55 ng/g dry weight. Cypermethrin, dicofol, chlorpyrifos, chlorothalonil, and trifluralin were the most frequently detected CUPs. The CUP concentrations were generally higher in the O-horizon than in the A-horizon. Chlorpyrifos, chlorothalonil, and dicofol were detected in most deep layers in soil profiles from three mountains selected to represent distinct climate zones. No clear altitudinal trend in organic carbon-normalized concentrations of CUPs was observed in the O- or A-horizons within individual mountains. A negative correlation was noted between the CUP concentrations and the altitudes across all sampling sites. This indicated that proximity to emission sources was a key factor affecting the spatial distribution of CUPs in mountain forest soil on a national scale. The ecological risk assessment showed that dicofol and cypermethrin pose potential risks to earthworms. This study emphasizes the importance of source control when setting management strategies for CUPs.

Ultrasonic Evaluation of the Asian Nasal Soft Tissue Envelope.

OBJECTIVE: The thickness of the nasal soft tissue envelope (STE) plays a crucial role in the final rhinoplasty results. The Asian nasal contour is typically characterized by a thicker STE and broader nasal tip, but objective data are lacking. The purpose of this study was to objectively measure nasal dermal thickness and overall STE thickness and to determine any demographic differences. METHODS: From July to September 2023, 110 patients presenting for consultation underwent ultrasound evaluation of their nasal STE. STE thickness was measured at predetermined subsites and compared with published data on white patients. RESULTS: The thickness of the STE in Asian patients was greater than that in white patients. The STE was thickest at the supratip (mean [SD]), (4.88 [0.74] mm) rather than at the nasion and thinnest at the rhinion (2.25 [0.51] mm). The nasal tip (4.07 [0.72] mm) showed comparable STE thickness with the nasion (4.13 [0.72] mm) but had a significantly thicker dermis than the nasion (2.35 ± 0.49 mm vs. 1.35 ± 0.35 mm, P < 0.05). Male sex and higher BMI tended to be correlated with a thicker nasal STE, but age did not show any relationship. A thicker nasal tip STE showed significantly greater nasal tip width and nasal alar thickness. CONCLUSION: STE thickness at different nasal subsites varies and affects external nasal contour and rhinoplasty outcomes. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The volumetric ADC histogram analysis in differentiating stage IA endometrial carcinoma from endometrial polyp.

OBJECTIVE: This study aimed to explore the value of apparent diffusion coefficient (ADC) histogram based on whole lesion volume in distinguishing stage IA endometrial carcinoma from the endometrial polyp. METHODS: MRI of 108 patients with endometrial lesions confirmed by pathology were retrospectively analysed, including 65 cases of stage IA endometrial carcinoma and 43 cases of endometrial polyp. The volumetric ADC histogram metrics and general imaging features were evaluated and measured simultaneously. All the features were compared between the 2 groups. The receiver operating characteristic curve was utilized to evaluate the diagnostic performance. RESULTS: The mean, max, min, and percentiles (10th, 25th, 50th, 75th, 95th) ADC values of endometrial carcinoma were significantly lower than that of polyp (all P < .05). The skewness and kurtosis of ADC values in the endometrial carcinoma group were significantly higher than those in the endometrial polyp group, and the variance of ADC values in the endometrial carcinoma group was lower than those in the endometrial polyp group (all P < .05). Endometrial carcinoma demonstrated more obvious myometrial invasion combined with intralesion haemorrhage than polyp (all P < .05). The 25th percentile of ADC values achieved the largest areas under the curve (0.861) among all the ADC histogram metrics and general imaging features, and the sensitivity and specificity were 83.08% and 76.74%, with the cut-off value of 1.01 × 10-3 mm2/s. CONCLUSION: The volumetric ADC histogram analysis was an effective method in differentiating endometrial carcinoma from an endometrial polyp. The 25th percentile of ADC values has satisfactory performance for detecting malignancy in the endometrium. ADVANCES IN KNOWLEDGE: The ADC histogram metric based on whole lesion is a promising imaging-maker in differentiating endometrial benign and malignant lesions.

Comparison of pregnancy outcomes among patients of different ages who underwent frozen-thawed high-quality single blastocyst transfer.

OBJECTIVE: To investigate the feasibility of performing frozen-thawed high-quality single blastocyst transfer in women of different ages. METHODS: A total of 1,279 women were divided into four groups: a 38-40-year-old group (n = 147), 35-37-year-old group (n = 164), 30-34-year-old group (n = 483), and < 30-year-old group (n = 485). Intergroup comparisons of baseline characteristics and pregnancy and neonatal outcomes were made. RESULTS: The clinical pregnancy rate (47.6%), and live birth rate (34.0%) in the 38-40-year-old group were significantly lower than those in the 30-34-year-old group (64.4%, 50.9%, respectively; all P < 0.001) and < 30-year-old group (62.9%, 50.7%, respectively; all P < 0.001). However, the 35-37-year-old group did not differ from the other three groups in these two dimensions (all P > 0.05). Moreover, there were no differences in the rates of biochemical pregnancy, miscarriage, or obstetric or neonatal complications among the four groups (all P > 0.05). According to the multivariate logistic regression analysis, the 35-37-year-old group was not associated with non-live birth outcomes, adverse pregnancy outcomes, or obstetric or neonatal complications. However, being 38-40 years of age was a risk factor for non-live birth (OR = 2.121, 95% CI: 1.233-3.647) and adverse pregnancy outcomes (OR = 1.630, 95% CI: 1.010-2.633). Post hoc power analysis showed that the study was sufficiently powered to detect meaningful differences. CONCLUSION: Frozen-thawed high-quality single blastocyst transfer produces the same satisfactory pregnancy outcomes for women aged 35-37 years as younger patients. Future prospective randomized controlled studies with larger populations are needed to verify the feasibility and safety of this method.

miR-21-5p-loaded bone mesenchymal stem cell-derived exosomes repair ovarian function in autoimmune premature ovarian insufficiency by targeting MSX1.

RESEARCH QUESTION: What is the effect of micro-RNA (miR)-21-5p-loaded bone marrow mesenchymal stem cell-derived exosomes (miR-21-Exo) on autoimmune premature ovarian insufficiency (POI)? DESIGN: The Cell Counting Kit 8 (CCK8) assay, fluorescence-activated cell sorting, western blotting, quantitative reverse transcriptase (qRT)-PCR and enzyme-linked immunosorbent assay (ELISA) verified the effect of miR-21-Exo on interferon-γ (IFN-γ)-induced KGN cells. qRT-PCR, western blotting and dual-luciferase reporter gene assays verified that miR-21-Exo mediated Msh homeobox 1 (MSX1) regulation of the Notch signalling pathway and that miR-21 interacted directly with MSX1. The effects of miR-21-Exo on the ovaries were verified by monitoring of the oestrous cycle, haematoxylin and eosin staining, follicle counts, ELISA, immunohistochemistry, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labelling (TUNEL), western blotting and qRT-PCR. RESULTS: The results showed that miR-21-Exo promoted IFN-γ-induced KGN cell proliferation and hormone synthesis, and inhibited apoptosis. Using dual-luciferase reporter gene assays, miR-21 and MSX1 were shown to have direct interactions. Moreover, the findings elucidated that miR-21-Exo inhibited cell apoptosis and promoted hormone synthesis by mediating MSX1 to regulate the Notch signalling pathway. miR-21-Exo restored the ovarian structure in a mouse model of autoimmune POI, promoted endocrine function and proliferation, and inhibited apoptosis and inflammation in vivo. CONCLUSIONS: This study demonstrates that miR-21-Exo regulates the MSX1-mediated Notch signalling pathway to inhibit granulosa cell apoptosis and improve hormone synthesis function, providing insight into a potential mechanism of molecular therapy for the treatment of autoimmune POI.

RNA M6A modification shaping cutaneous melanoma tumor microenvironment and predicting immunotherapy response.

Recent years have seen rising mortality rates linked to cutaneous melanoma (SKCM), despite advances in immunotherapy. Understanding RNA N6-methyladenosine (M6A) significance in SKCM is crucial for prognosis, tumor microenvironment (TME), immune cell presence, and immunotherapy efficacy. We analyzed 23 M6A regulators using SKCM samples from TCGA and GEO databases, identifying three M6A modification patterns linked to TME cell infiltration. Principal component analysis (PCA) yielded an M6A score for individual tumors, utilizing patient gene expression profiles and CNV data from TCGA. M6A modification patterns play a crucial role in SKCM development and progression, influencing tumor attributes such as inflammatory stage, subtype, TME interstitial activity, and genetic mutations. The M6A score independently predicts patient outcomes and correlates with improved response to immunotherapy, validated across anti-PD-1 and anti-PD-L1 therapy cohorts. M6A modifications significantly impact the TME landscape, with the M6A score serving as a predictive marker for immunotherapy response. Integrating M6A-related information into clinical practice could revolutionize SKCM management and treatment strategies.

Pollution and mobility of heavy metals in the soils of a typical agricultural zone in eastern China.

The pollution of heavy metals (HMs) in agricultural soils profoundly threatens national food safety, and the mobility and environmental behaviors of HMs are closely implicated in crop safety. Here, we assessed the pollution level and mobility of ten HMs and explored their environmental behaviors in the soils of three different land uses from a main crop production zone in eastern China. The concentrations of HMs in the soils were higher in the farmland than the woodland and wasteland, and Cd showed a relatively higher pollution and ecological risk levels compared to other metals. Cadmium was dominated by the reducible (41%) and exchangeable (23%) fractions, and the rest of HMs were mainly in the residual fraction (> 60%). The significant correlation between the exchangeable and DGT-labile Cd indicates relatively higher mobility of Cd in the soils. Soil pH, organic matters and mineral elements had significant correlation with the exchangeable and reducible fractions of most of the HMs (e.g., Cd, Co, Mn, Ni, Pb and V; p < 0.05), indicating their good predictors of the HMs mobility. However, this was not the case for the DGT-labile fraction, which suggests a marked difference in the controlling mechanisms of the mobility versus potential bioavailability of HMs in the soils. The results of this study indicate that both the chemically extracted fractions and the bioavailable fractions of HMs need be considered when effectively assessing the safety of agricultural soils.

Reconstruction and analysis of transient evolution images of laser-produced plasma plumes.

We introduce a method for the analysis and simulation of transient images of laser-produced plasma (LPP) plumes. This method comprises three steps: (i) calculating the two-dimensional distribution of plasma parameters using a radiation hydrodynamics model, (ii) constructing radiation paths through ray tracing, and (iii) solving the radiation transport equation along these paths. In our simulations, we have meticulously considered factors that could influence the imaging results, including the quantum efficiency to different radiation wavelengths, the imaging lens' transmittance, the target surface's reflectivity, and the absorption, emission, and scattering quantum effect of the detector processes occurring in the plasma. We applied this method to analyze and simulate the transient images of aluminum plasma plumes in a background air environment at a pressure of 2000 Pa. The results demonstrate that our method not only produces simulated images that align with experimental results but also provides a reliable distribution of plasma state parameters and clearly identifies the ion species radiating in different bands. Given its capability in transient image reconstruction and its adaptability as a tool for spectral simulation and analysis of LPPs, we believe this method holds significant potential for spectral diagnostics in fields such as laser-induced breakdown spectroscopy, extreme ultraviolet lithography sources, and high-energy-density physics, among others.

scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution.

SUMMARY: Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different approaches or criteria to define the cell subtypes for the same major cell lineages. The relationships between the cell subtypes defined in different studies should be carefully evaluated. In this updated package scCancer2, designed for integrative tumor scRNA-seq data analysis, we developed a supervised machine learning framework to annotate TME cells with annotated cell subtypes from 15 scRNA-seq datasets with 594 samples in total. Based on the trained classifiers, we quantitatively constructed the similarity maps between the cell subtypes defined in different references by testing on all the 15 datasets. Secondly, to improve the identification of malignant cells, we designed a classifier by integrating large-scale pan-cancer TCGA bulk gene expression datasets and scRNA-seq datasets (10 cancer types, 175 samples, 663 857 cells). This classifier shows robust performances when no internal confidential reference cells are available. Thirdly, scCancer2 integrated a module to process the spatial transcriptomic data and analyze the spatial features of TME. AVAILABILITY AND IMPLEMENTATION: The package and user documentation are available at http://lifeome.net/software/sccancer2/ and https://doi.org/10.5281/zenodo.10477296.

STEM enables mapping of single-cell and spatial transcriptomics data with transfer learning.

Profiling spatial variations of cellular composition and transcriptomic characteristics is important for understanding the physiology and pathology of tissues. Spatial transcriptomics (ST) data depict spatial gene expression but the currently dominating high-throughput technology is yet not at single-cell resolution. Single-cell RNA-sequencing (SC) data provide high-throughput transcriptomic information at the single-cell level but lack spatial information. Integrating these two types of data would be ideal for revealing transcriptomic landscapes at single-cell resolution. We develop the method STEM (SpaTially aware EMbedding) for this purpose. It uses deep transfer learning to encode both ST and SC data into a unified spatially aware embedding space, and then uses the embeddings to infer SC-ST mapping and predict pseudo-spatial adjacency between cells in SC data. Semi-simulation and real data experiments verify that the embeddings preserved spatial information and eliminated technical biases between SC and ST data. We apply STEM to human squamous cell carcinoma and hepatic lobule datasets to uncover the localization of rare cell types and reveal cell-type-specific gene expression variation along a spatial axis. STEM is powerful for mapping SC and ST data to build single-cell level spatial transcriptomic landscapes, and can provide mechanistic insights into the spatial heterogeneity and microenvironments of tissues.

Human Bone Marrow Derived-Mesenchymal Stem Cells Treatment for Autoimmune Premature Ovarian Insufficiency.

BACKGROUND: Premature ovarian insufficiency (POI) is a relatively common gynecologic endocrine disorder, which is hypogonadism associated with amenorrhea, increased levels of gonadotropins, and hypoestrogenism. POI resulting from ovarian autoimmunity is a poorly understood clinical condition lacking effective treatments. This study is aimed to investigate the therapeutic effect of mesenchymal stem cells (MSCs) on autoimmune premature ovarian insufficiency. METHODS: In this study, in vivo and in vitro experiments were conducted to clarify the therapeutic effects and possible mechanisms of human bone marrow-derived MSCs (hBMSCs) on autoimmune POI, and to provide an experimental evidence for the treatment of autoimmune POI by hBMSCs. Noteworthy, in this study, we used interferon-gamma (IFN-γ) to induce autoimmune inflammation in human granulosa cell line KGN, simulating the pathophysiological changes of granulosa cells in autoimmune POI, and therefore sought to establish an in vitro cell model of autoimmune POI, which is still lacking in experimental methodology. RESULTS: And we found that, in vitro, co-culture of hBMSCs could promote granulosa cell proliferation, inhibit apoptosis, improve hormone synthesis capacity, and reduce the occurrence of pyroptosis; and in vivo, hBMSCs resulted in improved estrous cycle disorders in autoimmune POI mice, increased serum estradiol, decreased follicle-stimulating hormone, improved ovarian morphology, increased number of primordial and primary follicles, decreased number of atretic follicles, and decreased ovarian granulosa cell apoptosis. CONCLUSIONS: hBMSCs have therapeutic effects on autoimmune POI both in vitro and in vivo.

Clinical efficacy of blood derivatives on wound healing: A systematic review and network meta-analysis.

This study aims to evaluate the clinical effects of different blood derivatives on wound healing using network meta-analysis. PubMed, Embase, OVID, Web of Science, SCOPUS and Cochrane Central were searched to obtain studies about blood derivatives on wound healing until October 2023. R 4.2.0 and Stata 15.0 softwares were used for data analysis. Forty-four studies comprising 5164 patients were included. The results of network meta-analysis showed that the healing area from high to low was GF + ORCCB, ORCCB, GF, PRF, Unnas paste dressing, APG, PRP injection, PRP, PRP + thrombin gel, PPP, HPL, CT. The healing time from low to high was PRP + thrombin gel, GF, PRP, PC + K, PC, APG, PRF, CT, Silver sulfadiazine ointment. The number of patients cured from high to low was APG, PRP injection, PRP, Aurix, PRF, Leucopatch, HPL, Antimicrobial Ointment Dressing, CT, 60 µg/cm2 repifermin, 120 µg/cm2 repifermin, AFG, PPP. The order of analgesic effect from high to low was AFG, Aminogam gel, PRF, PRP, Oxidised oil, APG, GF, CT. The order of the number of wound infection cases from low to high is APG, 20 µg/cm2 repifermin, 60 µg/cm2 repifermin, PRP, LeucoPatch, CT, PPP, Antiseptic ointment dressing. Healing area: GF + ORCCB had the best effect; Healing time: PRP + thrombin gel took the shortest time. The number of cured patients and the reduction of wound infection: APG has the best effect. Analgesic effect: AFG has the best effect. More studies with large sample sizes are needed to confirm the above findings.