The Addition of Hot Water Extract of Juncao-Substrate Ganoderma lucidum Residue to Diets Enhances Growth Performance, Immune Function, and Intestinal Health in Broilers.

The purpose of this experiment was to investigate the effects of Hot Water Extract of Juncao-substrate Ganoderma lucidum Residue (HWE-JGLR) on the immune function and intestinal health of yellow-feather broilers. In an animal feeding experiment, 288 male yellow-feather broilers (1 day old) were randomly allocated to four treatment groups with six replicates of 12 birds each. The control (CON) group was fed a basal diet. HJ-1, HJ-2, and HJ-3 were fed a basal diet supplemented with 0.25%, 0.50%, and 1.00% HWE-JGLR, respectively. The feeding trial lasted for 63 d. The results showed increased ADFI (p = 0.033) and ADG (p = 0.045) of broilers in HJ-3, compared with the CON group. Moreover, higher contents of serum IL-4 and IL-10 and gene expression of IL-4 and IL-10 in jejunum mucosa and lower contents of serum IL-1ß and gene expression of IL-1ß in jejunum mucosa in HJ-3 were observed (p < 0.05). Additionally, the jejunal mucosal gene expression of Claudin-1 and ZO-1 in HJ-2 and HJ-3 was higher than that in the CON group (p < 0.05). As for the microbial community, compared with the CON group, the ACE index, Shannon index, and Shannoneven index of cecal microorganisms in HJ-2 and HJ-3 were elevated (p < 0.05). PCoA analysis showed that the cecal microbial structure of broilers in HJ-2 and HJ-3 was different from the CON group (p < 0.05). In contrast with the CON group, the broilers in HJ-2 and HJ-3 possessed more abundant Desulfobacterota at the phylum level and unclassified Lachnospiraceae, norank Clostridia vadinBB60 group and Blautia spp. at the genus level, while Turicibacter spp. and Romboutsia spp. were less (p < 0.05). In conclusion, dietary supplementation with HWE-JGLR can improve growth performance, enhance body immunity and intestinal development, and maintain the cecum microflora balance of yellow-feather broilers.

Reconstructing Molecular Networks by Causal Diffusion Do-Calculus Analysis with Deep Learning.

Quantifying molecular regulations between genes/molecules causally from observed data is crucial for elucidating the molecular mechanisms underlying biological processes at the network level. Presently, most methods for inferring gene regulatory and biological networks rely on association studies or observational causal-analysis approaches. This study introduces a novel approach that combines intervention operations and diffusion models within a do-calculus framework by deep learning, i.e., Causal Diffusion Do-calculus (CDD) analysis, to infer causal networks between molecules. CDD can extract causal relations from observed data owing to its intervention operations, thereby significantly enhancing the accuracy and generalizability of causal network inference. Computationally, CDD has been applied to both simulated data and real omics data, which demonstrates that CDD outperforms existing methods in accurately inferring gene regulatory networks and identifying causal links from genes to disease phenotypes. Especially, compared with the Mendelian randomization algorithm and other existing methods, the CDD can reliably identify the disease genes or molecules for complex diseases with better performances. In addition, the causal analysis between various diseases and the potential factors in different populations from the UK Biobank database is also conducted, which further validated the effectiveness of CDD.

Mapping high-resolution global gridded population distribution from 1870 to 2100.

Long-term global gridded population data is crucial in deepening our understanding of spatiotemporal population dynamics and essential in disaster exposure assessment studies. Several gridded population datasets exist but only cover a single period of observational, historical, or future. Here, based on a unified data and method framework, we created a coherent and consistent gridded population dataset at 1 km resolution with a 10-year interval spanning from 1870 to 2100. Using the observed population maps (2000-2020), historical population hindcast (1870-2000), and future population projection (2020-2100) under the Shared Socioeconomic Pathways (SSPs) were modeled. The validation shows that the constructed dataset achieves a high quantitative agreement with existing datasets and can better distribute the population within the built-up area, resulting in a more reasonable allocation. The constructed gridded population dataset can clearly show the evolution of population distribution over a long period in a spatially explicit way and exhibit high temporal consistency. From 1870 to 2100 (SSPs), the global population showed an S-shaped growth pattern, increasing by about 4.17 to 8.49 times, which has exerted substantial pressure on global sustainable development. At the local scale, the consistent, long-term, high-resolution gridded population data reveals diverse spatial (cluster, linear, and ring) and temporal (emergence, increase, stable, decrease) dynamics of population patterns across distinct regions, periods, and scenarios. Applying the long-term gridded population data, we revealed a substantial increase in the proportion of the global population exposed to floods, rising from 10.61 % in 1870 to 11.98 %-13.93 % in 2100 (SSPs), highlighting a rapid population expansion within flood-prone areas. In general, this study provides a consistent global gridded population dataset spanning over 200 years, which can provide insights into the whole life cycle of the global population spatiotemporal dynamics and holds great application value in various fields.

Invalidating betulinic acid as a potential inhibitor against the main protease of SARS-CoV-2 via combined approaches.

In contrast to an earlier study reporting that betulinic acid is an inhibitor of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro), we demonstrated that beutilinic acid is not a potential Mpro inhibitor via combined approaches, including the fluorescence resonance energy transfer (FRET) assay, the fluorescence polarization (FP) assay, and the protease biosensor cleavage assay. Our results suggest that the addition of detergent to the assay buffers is essential for evaluating natural products as Mpro inhibitors. It is necessary to conduct comprehensive testing of Mpro inhibition via combined approaches for antiviral development.

Red cell distribution width/albumin ratio and mortality risk in rheumatoid arthritis patients: Insights from a NHANES study.

BACKGROUND: Despite the established negative regulatory effects observed in various diseases like cardiovascular disease and diabetes, the distinct impact of red cell distribution width (RDW) to albumin ratio (RAR) on mortality within the realm of rheumatoid arthritis (RA) remains obscure. This study sought to explore the relationship between RAR and mortality in RA patients. METHODS: A cohort of 2151 adults with RA from the National Health and Nutrition Examination Survey (NHANES) spanning 2003-2016 was analyzed for RAR levels derived from red cell distribution width and albumin concentrations. Utilizing Cox regression analysis, Kaplan-Meier curves, and Restricted Cubic Spline (RCS) models, we assessed the association between RAR levels and RA mortality while adjusting for potential confounding variables. RESULTS: Participants with higher RAR had a twofold to threefold increased risk of all-cause (HR = 3.10, 95% CI: 2.26-4.24) and cardiovascular mortality (HR = 2.46, 95%CI: 1.26-4.79) versus lower RAR. Kaplan-Meier analysis revealed that the higher RAR group had a significantly lower survival rate compared to the lower RAR group for both all-cause and cardiovascular mortality (both p < .0001), with a more pronounced effect observed for all-cause mortality. Furthermore, the RCS-fitted Cox regression model illustrated a nonlinear positive correlation between RAR levels and RA mortality. CONCLUSION: Overall, a higher RAR was associated with an increased risk mortality in RA patients. These findings underscore the potential of RAR as a prognostic biomarker in predicting outcomes in RA.

Ganoderma lucidum polysaccharide promotes broiler health by regulating lipid metabolism, antioxidants, and intestinal microflora.

Ganoderma lucidum polysaccharides (GLP) are the primary bioactive macromolecular compounds of Ganoderma lucidum, possessing antioxidant and immunomodulatory effects. Hot water extract of Juncao-substrate Ganoderma Lucidum residue (HWE-JGLR) is abundant in GLP. There are few research reports on the application of HWE-JGLR in animal husbandry. Therefore, this study aims to investigate the effects of HWE-JGLR supplementation on growth performance, serum biochemistry, the antioxidant function of serum and liver, and the intestinal microbiota of yellow-feathered broilers. The control group was fed a corn-soybean meal basal diet, while the HJ I, II, and III groups received diets supplemented with 0.25 %, 0.5 %, and 1 % of HWE-JGLR, respectively. Results showed that HWE-JGLR increased the serum HDL-C content and decreased the TG content in broilers. Moreover, HWE-JGLR enhanced the antioxidant function by the Keap1-Nrf2/ARE signaling pathway and the antioxidative enzyme in broilers. In addition, the cecum of the metagenomic analysis of 16S rRNA showed that the relative abundance of no-rank Ruminococcacea was increased in the HJ I group. Our findings indicate that HWE-JGLR has strong potential for development as a green feed additive based on its functions of lipid-lowering, antioxidation, and the modulation of gut microbiota composition.

Genome-wide association analysis reveal candidate genes and haplotypes related to root weight in cucumber (Cucumis sativus L.).

Background: The plant root system is critical for the absorption of water and nutrients, and have a direct influence on growth and yield. In cucumber, a globally consumed crop, the molecular mechanism of root development remains unclear, and this has implications for developing stress tolerant varieties. This study sought to determine the genetic patterns and related genes of cucumber root weight. A core cucumber germplasms population was used to do the GWAS analysis in three environments. Results: Here, we investigated four root-weight related traits including root fresh weight (RFW), root dry weight (RDW), ratio of root dry weight to root fresh weight (RDFW) and the comprehensive evaluation index, D-value of root weight (DRW) deduced based on the above three traits for the core germplasm of the cucumber global repository. According to the D-value, we identified 21 and 16 accessions with light and heavy-root, respectively. We also found that the East Asian ecotype accessions had significantly heavier root than other three ecotypes. The genome-wide association study (GWAS) for these four traits reveals that 4 of 10 significant loci (gDRW3.1, gDRW3.2, gDRW4.1 and gDRW5.1) were repeatedly detected for at least two traits. Further haplotype and expression analysis for protein-coding genes positioned within these 4 loci between light and heavy-root accessions predicted five candidate genes (i.e., Csa3G132020 and Csa3G132520 both encoding F-box protein PP2-B1 for gDRW3.1, Csa3G629240 encoding a B-cell receptor-associated protein for gDRW3.2, Csa4G499330 encodes a GTP binding protein for gDRW4.1, and Csa5G286040 encodes a proteinase inhibitor for gDRW5.1). Conclusions: We conducted a systematic analysis of the root genetic basis and characteristics of cucumber core germplasms population. We detected four novel loci, which regulate the root weight in cucumber. Our study provides valuable candidate genes and haplotypes for the improvement of root system in cucumber breeding.

Genome-wide identification of Brassinosteroid insensitive 1-associated receptor kinase 1 genes and expression analysis in response to pathogen infection in cucumber (Cucumis sativus L.).

BACKGROUND: BAK1 (Brassinosteroid insensitive 1-associated receptor kinase 1) plays an important role in disease resistance in plants. However, the function of BAK1 family in cucumber and the decisive genes for disease-resistance remain elusive. RESULTS: Here, we identified 27 CsBAK1s in cucumber, and classified them into five subgroups based on phylogenetic analysis and gene structure. CsBAK1s in the same subgroup shared the similar motifs, but different gene structures. Cis-elements analysis revealed that CsBAK1s might respond to various stress and growth regulation. Three segmentally duplicated pairwise genes were identified in cucumber. In addition, Ka/Ks analysis indicated that CsBAK1s were under positive selection during evolution. Tissue expression profile showed that most CsBAK1s in Subgroup II and IV showed constitutive expression, members in other subgroups showed tissue-specific expression. To further explore whether CsBAK1s were involved in the resistance to pathogens, the expression patterns of CsBAK1s to five pathogens (gummy stem blight, powdery mildew, downy mildew, grey mildew, and fusarium wilt) reveled that different CsBAK1s had specific roles in different pathogen infections. The expression of CsBAK1-14 was induced/repressed significantly by five pathogens, CsBAK1-14 might play an important role in disease resistance in cucumber. CONCLUSIONS: 27 BAK1 genes were identified in cucumber from a full perspective, which have important functions in pathogen infection. Our study provided a theoretical basis to further clarify the function of BAK1s to disease resistance in cucumber.

International Trade Reshapes the Decoupling of Emissions from Economic Growth.

Efforts to stabilize the global climate change while also continuing human development depend upon "decoupling" economic growth from fossil fuel CO2 emissions. However, evaluations of such decoupling have typically relied on production-based emissions, which do not account for emissions embodied in international trade. Yet international trade can greatly change emissions accounting and reshape the decoupling between emissions and economic growth. Here, we evaluate decoupling of economic growth from different accounts of emissions in each of the 159 countries and analyze the drivers of decoupling. We find that between 1995 and 2015, although 29 countries exhibited strong decoupling of territorial emissions (growing economies and decreasing emissions), only 19 countries achieved economic growth while their consumption-based emissions decreased. Most developed countries have achieved decoupling of emissions related to domestic goods and services, but have not achieved decoupling of emissions related to imported goods and services. The U-test confirms that the domestic component of consumption-based emissions exhibits a stronger decoupling trend from gross domestic product (GDP) growth than consumption-based emissions, and emissions from imports continue to rise with GDP per capita without a corresponding decline, providing a statistical validation of the decoupling analysis. Moreover, in the countries where economic growth and consumption-based emissions are most decoupled, a key driver is decreasing emissions intensity due to technological progress─and especially reductions in the intensity of imported goods and services. Our results reveal the importance of assessing decoupling using consumption-based emissions; successful decoupling may require international cooperation and coordinated mitigation efforts of trading partners.

The impact of dynamic caudal type homeobox 2 expression on the differentiation of human trophoblast lineage during implantation.

The trophoblast lineage differentiation represents a rate-limiting step in successful embryo implantation. Adhesion, invasion and migration processes within the trophoblast are governed by several transcription factors. Among them, CDX2 is a critical regulator shaping the destiny of the trophoblast. While its altered expression is a linchpin initiating embryo implantation in mice, the precise influence of CDX2 on the functionality and lineage differentiation of early human trophoblast remains unclear. In this study, we employed well-established human trophoblast stem cell (hTSC) lines with CDX2 overexpression coupled with a 3D in vitro culture system for early human embryos. We revealed that the downregulation of CDX2 is a prerequisite for syncytialization during human embryo implantation based on immunofluorescence, transcriptome analysis, CUT-tag sequencing and the construction of 3D human trophoblast organoids. While CDX2 overexpression inhibited syncytialization, it propelled hTSC proliferation and invasive migration. CDX2 exerted its influence by interacting with CGA, PTGS2, GCM1, LEF1 and CDH2, thereby hindering premature differentiation of the syncytiotrophoblast. CDX2 overexpression enhanced the epithelial-mesenchymal transition of human trophoblast organoids. In summary, our study provides insights into the molecular characteristics of trophoblast differentiation and development in humans, laying a theoretical foundation for advancing research in embryo implantation.

Research on the Low-Temperature Oxygen Consumption and Low-Oxygen Gas Emission Law in Goaf of Ultrathick Coal Seams.

Low-oxygen (oxygen concentration below 18.5%) phenomena often occur in the top coal caving working face of ultrathick coal seams, posing a serious threat to the safety of workers. The characteristics of oxygen consumption and gas production at low-constant temperature and the corresponding functional group evolution of residual coal in goaf were studied by temperature-programmed and infrared spectrum experiments. The influence of different factors on the emission of low-oxygen gases was studied through numerical calculation. The results show that low-temperature oxygen consumption and gas production occurred when the coal was about 40 °C. When the temperature was constant, the oxygen consumption and gas production rate increased with the extension of time. In the early stage of coal oxidation, the aliphatic C-H components were attacked by oxygen molecules and reacted with them. The asymmetric methyl and methylene groups were more likely to oxidize and produce carbonyl compounds. With the increase of nitrogen injection, the overall width of the oxidation zone (oxygen concentration was defined as 10-18%) narrowed, and the range of the oxidation zone moved forward from the depth of the goaf. The oxygen concentration in the air return corner decreased gradually, and the low-oxygen area in the air return corner expanded gradually. The distance between the low-oxygen area of the working face and the air intake corner was gradually shortened. With the increase of air intake, the width of the oxidation zone increased and moved to the depth of goaf, and the degree of low oxygen in the air return corner increased. The research results are of great significance for the understanding and prevention of the low-oxygen phenomenon in ultrathick coal seams.

Prediction of daily new COVID-19 cases - Difficulties and possible solutions.

Epidemiological compartmental models, such as SEIR (Susceptible, Exposed, Infectious, and Recovered) models, have been generally used in analyzing epidemiological data and forecasting the trajectory of transmission of infectious diseases such as COVID-19. Experience shows that accurately forecasting the trajectory of COVID-19 transmission curve is a big challenge for researchers in the field of epidemiological modeling because multiple unquantified factors can affect the trajectory of COVID-19 transmission. In the past years, we used a new compartmental model, l-i SEIR model, to analyze the COVID-19 transmission trend in the United States. Unlike the conventional SEIR model and the delayed SEIR model that use or partially use the approximation of temporal homogeneity, the l-i SEIR model takes into account chronological order of infected individuals in both latent (l) period and infectious (i) period, and thus improves the accuracy in forecasting the trajectory of transmission of infectious diseases, especially during periods of rapid rise or fall in the number of infections. This paper describes (1) how to use the new SEIR model (a mechanistic model) combined with fitting methods to simulate or predict trajectory of COVID-19 transmission, (2) how social interventions and new variants of COVID-19 significantly change COVID-19 transmission trends by changing transmission rate coefficient ßn, the fraction of susceptible people (Sn/N), and the reinfection rate, (3) why accurately forecasting COVID-19 transmission trends is difficult, (4) what are the strategies that we have used to improve the forecast outcome and (5) what are some successful examples that we have obtained.

Association between pre-gravid body mass index and clinical outcomes in in vitro fertilization: a multicentered retrospective cohort study.

BACKGROUND: With the increasing incidence of obesity and the childbearing-age delay among women, a debate over obesity's impacts on pregnancy and neonatal outcomes becomes hot. The potential negative effects of obesity and aging on fertility lead to an idea, whether an obese female pursuing IVF treatment can benefit from an ideal BMI achieved over a long-time weight loss process at the cost of aging? We aimed to assess the association between body mass index (BMI) and clinical or neonatal outcomes in patients undergoing in vitro fertilization (IVF) treatment, for answering whether it is necessary to lose weight first for obese patients, particularly those at advanced age. METHODS: A retrospective cohort study was performed using multicentered data from China. The women were stratified into 5 groups in terms of pre-gravid BMI (kg/m2) with the WHO obesity standard (group 1: BMI < 18.5; group 2: 18.5 ≤ BMI < 23.0; group 3: 23.0 ≤ BMI < 25.0; group 4: 25.0 ≤ BMI < 30.0; group 5: BMI ≥ 30.0). The primary outcome was cumulative live birth rate (CLBR), and other clinical and neonatal outcomes were weighed as secondary outcomes. Multivariate logistic regression analyses were carried to evaluate the association between BMI and the CLBR, or between BMI and some neonatal outcomes. Furthermore, we implemented a machine-learning algorithm to predict the CLBR based on age and BMI. RESULTS: A total of 115,287 women who underwent first IVF cycles with autologous oocytes from January 2013 to December 2017 were included in our study. The difference in the CLBR among the five groups was statistically significant (P < 0.001). The multivariate logistic regression analysis showed that BMI had no significant impact on the CLBR, while women's age associated with the CLBR negatively. Further, the calculation of the CLBR in different age stratifications among the five groups revealed that the CLBR lowered with age increasing, quantitatively, it decreased by approximately 2% for each one-year increment after 35 years old, while little difference observed in the CLBR corresponding to the five groups at the same age stratification. The machine-learning algorithm derived model showed that BMI's effect on the CLBR in each age stratification was negligible, but age's impact on the CLBR was overwhelming. The multivariate logistic regression analysis showed that BMI did not affect preterm birth, low birth weight infant, small for gestational age (SGA) and large for gestational age (LGA), while BMI was an independent risk factor for fetal macrosomia, which was positively associated with BMI. CONCLUSIONS: Maternal pre-gravid BMI had no association with the CLBR and neonatal outcomes, except for fetal macrosomia. While the CLBR was lowered with age increasing. For the IVF-pursuing women with obesity plus advanced age, rather than losing weight first, the sooner the treatment starts, the better. A multicentered prospective study with a large size of samples is needed to confirm this conclusion in the future.

Atoh1 overexpression promotes Guinea pig bone marrow mesenchymal stem cells to differentiate into neural stem cell.

Sensorineural hearing loss (SNHL) is a prevalent condition in otolaryngology. A key obstacle is finding effective strategies for regenerating damaged cochlear hair cells in adult animals. A practical and reliable approach has been developed to create a superior cell source for stem cell transplantation in the inner ear to treat SNHL. Atoh1 is involved in the differentiation of neurons, intestinal secretory cells, and mechanoreceptors including auditory hair cells, and thus plays an important role in neurogenesis. Lentivirus-mediated transfection of bone marrow mesenchymal stem cells (BMSCs) was utilized to achieve stable expression of the essential transcription factor Atoh1, which is crucial for developing auditory hair cells without compromising cell survival. By manipulating the induction conditions through altering the cell growth environment using anti-adherent culture, the synergistic impact of basic fibroblast growth factor (bFGF) and epidermal growth factor (EGF) was effectively applied to significantly improve the differentiation efficiency of bone marrow-derived mesenchymal stem cells (BMSC) into neural stem cells (NSCs) following Atoh1 transfection, thereby reducing the induction time. The study indicated that the newly proposed transdifferentiation method effectively transformed BMSCs into NSCs in a controlled environment, presenting a potential approach for stem cell transplantation to promote hair cell regeneration.

Transcriptome Analysis Reveals Genes and Pathways Associated with Drought Tolerance of Early Stages in Sweet Potato (Ipomoea batatas (L.) Lam.).

The yield of sweet potato [Ipomoea batatas (L.) Lam] can be easily threatened by drought stress. Typically, early stages like the seedling stage and tuber-root expansion stage are more vulnerable to drought stress. In this study, a highly drought-tolerant sweet potato cultivar "WanSu 63" was subjected to drought stress at both the seedling stage (15 days after transplanting, 15 DAT) and the tuber-root expansion stage (45 DAT). Twenty-four cDNA libraries were constructed from leaf segments and root tissues at 15 and 45 DAT for Next-Generation Sequencing. A total of 663, 063, and 218 clean reads were obtained and then aligned to the reference genome with a total mapped ratio greater than 82.73%. A sum of 7119, 8811, 5463, and 930 differentially expressed genes were identified from leaves in 15 days (L15), roots in 15 days (R15), leaves in 45 days (L45), and roots in 45 days (R45), respectively, in drought stress versus control. It was found that genes encoding heat shock proteins, sporamin, LEA protein dehydrin, ABA signaling pathway protein gene NCED1, as well as a group of receptor-like protein kinases genes were enriched in differentially expressed genes. ABA content was significantly higher in drought-treated tissues than in the control. The sweet potato biomass declined sharply to nearly one-quarter after drought stress. In conclusion, this study is the first to identify the differentially expressed drought-responsive genes and signaling pathways in the leaves and roots of sweet potato at the seedling and root expansion stages. The results provide potential resources for drought resistance breeding of sweet potato.

Detecting tipping points of complex diseases by network information entropy.

The progression of complex diseases often involves abrupt and non-linear changes characterized by sudden shifts that trigger critical transformations. Identifying these critical states or tipping points is crucial for understanding disease progression and developing effective interventions. To address this challenge, we have developed a model-free method named Network Information Entropy of Edges (NIEE). Leveraging dynamic network biomarkers, sample-specific networks, and information entropy theories, NIEE can detect critical states or tipping points in diverse data types, including bulk, single-sample expression data. By applying NIEE to real disease datasets, we successfully identified critical predisease stages and tipping points before disease onset. Our findings underscore NIEE's potential to enhance comprehension of complex disease development.

Association between oxidative balance score and risk of gout: The NHANES cross-sectional study, 2007-2018.

BACKGROUND: The Oxidative Balance Score (OBS) is a systematic tool to assess the effects of diet and lifestyle in relation to oxidative stress. The association between OBS and gout has not been reported previously. We conducted a cross-sectional study to investigate the complex association between OBS and gout in US adults. METHODS: In all, 10 492 participants were included in this study. The exposure variable was OBS, which was scored by 16 dietary and four lifestyle factors. Multivariate logistic regression, subgroup analysis, and restricted cubic spline (RCS) regression were used to analyze the association between OBS and gout. RESULTS: Compared with the lowest OBS quartile group (Q1), the multivariate corrected odds ratio (OR) (95% confidence interval [C]) for the highest quartile of OBS (Q4) was 0.72 (0.52-1.00) (p = .13 for trend); furthermore, the RCS showed a negative linear relationship between OBS and gout (p-nonlinear = .606). CONCLUSION: In conclusion, the risk of gout is higher with high OBS. The prevalence of gout decreased with higher OBS. Diabetes may alter this negative correlation.

Meta-analysis of intrauterine hCG perfusion efficacy in recurrent implantation failure as defined by ESHRE guidelines.

PURPOSE: This study evaluates the efficacy of intrauterine hCG perfusion for RIF, as defined by ESHRE 2023 guidelines, highlighting hCG as a cost-effective alternative to other immunotherapies, especially suitable for less developed regions. It aims to clarify treatment guidance amidst previous inconsistencies. METHODS: This meta-analysis, registered with PROSPERO (CRD42024443241) and adhering to PRISMA guidelines, assessed the efficacy and safety of intrauterine hCG perfusion in enhancing implantation and pregnancy outcomes in RIF. Comprehensive literature searches were conducted through December 2023 in major databases including PubMed, Web of Science, Embase, the Cochrane Library, and key Chinese databases, without language restrictions. Inclusion and exclusion criteria were strictly aligned with the 2023 ESHRE recommendations, with exclusions for studies lacking robust control, clear outcomes, or adequate data integrity. The risk of bias was evaluated using the Newcastle-Ottawa Scale, ROBINS-I, and RoB2 tools. Data analysis was performed in R using the 'meta' package, employing both fixed and random effect models to account for study variability. Subgroup analyses by dosage, volume, hCG concentration, timing of administration, and type of embryo transfer were conducted to deepen insights, enhancing the reliability and depth of the meta-analysis in elucidating the role of hCG perfusion in RIF treatments. RESULTS: Data from 13 studies, comprising six retrospective and six prospective studies from single centers, along with one multi-center RCT, totaling 2,157 participants, were synthesized to evaluate the effectiveness of intrauterine hCG perfusion in enhancing implantation and pregnancy outcomes in patients with RIF. Significant improvements were observed in clinical pregnancy and embryo implantation rates across various dosages, timing of administration, and embryo developmental stages, without impacting miscarriage rates. Notably, the most significant efficacy within subgroups occurred with a 500 IU dosage and perfusion parameters of ≤ 500µL volume and ≥ 2 IU/µL concentration. Additionally, a limited number of studies showed no significant increases in ectopic pregnancy or multiple pregnancy rates, and a modest improvement in live birth rates, although the small number of these studies precludes definitive conclusions. CONCLUSIONS: The analysis suggests that intrauterine hCG perfusion probably enhances embryo implantation, clinical pregnancy, and live birth rates slightly in RIF patients. Benefits are indicated with a dosage of 500 IU and a maximum volume of 500µL at concentrations of at least 2 IU/µL. However, substantial heterogeneity from varying study types and the limited number of studies necessitate cautious interpretation. These findings underscore the need for more rigorously designed RCTs to definitively assess the efficacy and safety.

Efficient phosphorus recovery from waste activated sludge: Pretreatment with natural deep eutectic solvent and recovery as vivianite.

Recycling phosphorus from waste activated sludge (WAS) is an effective method to address the nonrenewable nature of phosphorus and mitigate environmental pollution. To overcome the challenge of low phosphorus recovery from WAS due to insufficient disintegration, a method using a citric acid-based natural deep eutectic solvent (CA-NADES) assisted with low-temperature pretreatment was proposed to efficiently release and recover phosphorus. The results of 31P nuclear magnetic resonance (NMR) confirmed that low-temperature pretreatment promoted the conversion of organic phosphorus (OP) to inorganic phosphorus (IP) and enhanced the effect of CA-NADES. Changes in the three-dimensional excitation-emission matrix (3D-EEM) and flow cytometry (FCM) indicated that the method of CA-NADES with low-temperature thermal simultaneously release IP and OP by disintegrating sludge flocs, dissolving extracellular polymeric substances (EPS) structure, and cracking cells. When 5 % (v/v) of CA-NADES was added and thermally treated at 60 °C for 30 min, 43 % of total phosphorus (TP) was released from the sludge. The concentrations of proteins and polysaccharides reached 826 and 331 mg/L, respectively, which were 6.30 and 14.43 times higher than those of raw sludge. The dewatering and settling of the sludge were also improved. Metals were either enriched in the solid phase or released into the liquid phase in small quantities (most efficiencies of less than 10 %) for subsequent clean recovery. The released phosphorus was successfully recovered as vivianite with a rate of 90 %. This study develops an efficient, green, and sustainable method for phosphorus recovery from sludge using NADES and provides new insights into the high-value conversion of sludge.

CBioProfiler: A Web and Standalone Pipeline for Cancer Biomarker and Subtype Characterization.

Cancer is a leading cause of death worldwide, and the identification of biomarkers and subtypes that can predict the long-term survival of cancer patients is essential for their risk stratification, treatment, and prognosis. However, there are currently no standardized tools for exploring cancer biomarkers or subtypes. In this study, we introduced Cancer Biomarker and subtype Profiler (CBioProfiler), a web server and standalone application that includes two pipelines for analyzing cancer biomarkers and subtypes. The cancer biomarker pipeline consists of five modules for identifying and annotating cancer survival-related biomarkers using multiple survival-related machine learning algorithms. The cancer subtype pipeline includes three modules for data preprocessing, subtype identification using multiple unsupervised machine learning methods, and subtype evaluation and validation. CBioProfiler also includes CuratedCancerPrognosisData, a novel R package that integrates reviewed and curated gene expression and clinical data from 268 studies. These studies cover 43 common blood and solid tumors and draw upon 47,686 clinical samples. The web server is available at https://www.cbioprofiler.com/ and https://cbioprofiler.znhospital.cn/CBioProfiler/, and the standalone app and source code can be found at https://github.com/liuxiaoping2020/CBioProfiler.