Greenhouse gas emission characteristics and influencing factors of agricultural waste composting process: A review.

China, being a major agricultural nation, employs aerobic composting as an efficient approach to handle agricultural solid waste. Nevertheless, the composting process is often accompanied by greenhouse gas emissions, which are known contributors to global warming. Therefore, it is urgent to control the formation and emission of greenhouse gases from composting. This study provides a comprehensive analysis of the mechanisms underlying the production of nitrous oxide, methane, and carbon dioxide during the composting process of agricultural wastes. Additionally, it proposes an overview of the variables that affect greenhouse gas emissions, including the types of agricultural wastes (straw, livestock manure), the specifications for compost (pile size, aeration). The key factors of greenhouse gas emissions during composting process like physicochemical parameters, additives, and specific composting techniques (reuse of mature compost products, ultra-high-temperature composting, and electric-field-assisted composting) are summarized. Finally, it suggests directions and perspectives for future research. This study establishes a theoretical foundation for achieving carbon neutrality and promoting environmentally-friendly composting practices.

IGF2BP1 facilitates non-small cell lung cancer progression by regulating the KIF2A-mediated Wnt/ß-catenin pathway.

Insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs) are crucially implicated in the cancer progression. The current study intends to excavate and clarify the mechanisms of the key IGF2BPs in non-small cell lung cancer (NSCLC). The expression of IGF2BPs and kinesin family member 2A (KIF2A) was examined using immunohistochemistry, real-time quantitative polymerase chain reaction, and western blot in NSCLC tissue samples or cell lines. NSCLC cell viability was examined using a cell counting kit-8 assay. Cell apoptotic rate was assessed using flow cytometry analysis. The migration and invasion of H1299 cells were subject to scratch test and Transwell assays, respectively. Starbase 2.0 was used to detect the downstream factors of the IGF2BP1 protein. The binding of IGF2BP with KIF2A was detected using RNA binding protein immunoprecipitation assays. Ki-67 immunohistochemistry assay and TUNEL assays were applied for the evaluation of proliferation and apoptosis in vivo, respectively. IGF2BP1 was upregulated in NSCLC tissue samples and cells. Functionally, IGF2BP1 overexpression promoted the proliferative ability, migration, and invasiveness of H1299 cells, while inhibiting cell apoptosis in vitro. In vivo studies revealed that overexpression of IGF2BP1 promoted tumor growth of NSCLC. Mechanistically, IGF2BP1 was involved in KIF2A mRNA stabilization. KIF2A exerted the same functions as IGF2BP1 via the Wnt/ß-catenin signaling. In conclusion, IGF2BP1 enhances NSCLC malignant progression by stabilizing KIF2A to modulate the Wnt/ß-catenin pathway.

Prediction of hyperkalemia in ESRD patients by identification of multiple leads and multiple features on ECG.

BACKGROUND: Patients with end-stage renal disease (ESRD) especially those undergoing dialysis have a high prevalence of hyperkalemia, which must be detected and treated immediately. But the initial symptoms of hyperkalemia are insidious, and traditional laboratory serum potassium concentration testing takes time. Therefore, rapid and real-time measurement of serum potassium is urgently needed. In this study, different machine learning methods were used to make rapid predictions of different degrees of hyperkalemia by analyzing the ECG. METHODS: A total of 1024 datasets of ECG and serum potassium concentrations were analyzed from December 2020 to December 2021. The data were scaled into training and test sets. Different machine learning models (LR, SVM, CNN, XGB, Adaboost) were built for dichotomous prediction of hyperkalemia by analyzing 48 features of chest leads V2-V5. The performance of the models was also evaluated and compared using sensitivity, specificity, accuracy, accuracy, F1 score and AUC. RESULTS: We constructed different machine models to predict hyperkalemia using LR and four other common machine-learning methods. The AUCs of the different models ranged from 0.740 (0.661, 0.810) to 0.931 (0.912,0.953) when different serum potassium concentrations were used as the diagnostic threshold for hyperkalemia, respectively. As the diagnostic threshold of hyperkalemia was raised, the sensitivity, specificity, accuracy and precision of the model decreased to various degrees. And AUC also performed less well than when predicting mild hyperkalemia. CONCLUSION: Noninvasive and rapid prediction of hyperkalemia can be achieved by analyzing specific waveforms on the ECG by machine learning methods. But overall, XGB had a higher AUC in mild hyperkalemia, but SVM performed better in predicting more severe hyperkalemia.

Machine learning-based risk prediction of acute kidney disease and hospital mortality in older patients.

Introduction: Acute kidney injury (AKI) is a prevalent complication in older people, elevating the risks of acute kidney disease (AKD) and mortality. AKD reflects the adverse events developing after AKI. We aimed to develop and validate machine learning models for predicting the occurrence of AKD, AKI and mortality in older patients. Methods: We retrospectively reviewed the medical records of older patients (aged 65 years and above). To explore the trajectory of kidney dysfunction, patients were categorized into four groups: no kidney disease, AKI recovery, AKD without AKI, or AKD with AKI. We developed eight machine learning models to predict AKD, AKI, and mortality. The best-performing model was identified based on the area under the receiver operating characteristic curve (AUC) and interpreted using the Shapley additive explanations (SHAP) method. Results: A total of 22,005 patients were finally included in our study. Among them, 4,434 patients (20.15%) developed AKD, 4,000 (18.18%) occurred AKI, and 866 (3.94%) patients deceased. Light gradient boosting machine (LGBM) outperformed in predicting AKD, AKI, and mortality, and the final lite models with 15 features had AUC values of 0.760, 0.767, and 0.927, respectively. The SHAP method revealed that AKI stage, albumin, lactate dehydrogenase, aspirin and coronary heart disease were the top 5 predictors of AKD. An online prediction website for AKD and mortality was developed based on the final models. Discussion: The LGBM models provide a valuable tool for early prediction of AKD, AKI, and mortality in older patients, facilitating timely interventions. This study highlights the potential of machine learning in improving older adult care, with the developed online tool offering practical utility for healthcare professionals. Further research should aim at external validation and integration of these models into clinical practice.

Construction and characterization of phage display library: recognition of mouse serologically detected male (SDM) antigen.

Improvement of animal embryo sexing depends upon high-titer serologically detected male (SDM) antibody fragments. SDM sera collected from isogenic C57BL/7 female mice after inoculation with male spleen cells were characterized and used for construction of a recombinant Fab antibody library against SDM antigen, and used for analysis of the binding capacity and specificity to SDM antigen. The heavy-chain Fd and full-length light-chain kappa were amplified by RT-PCR from a mouse (#6) that'ed high-titer antiserum. The amplified product was inserted into the pComb3 vector followed by co-infections with the help phage VCSM 13 for construction of the phage library, which gave 1.5x10(7) colonies with the titer of 3.2x10(11) pfu/ml by a recombination rate of 80%. Sequence analysis of the PCR products of plasmid DNA of E5 clones showed that V(H) and V(kappa) had common characteristics shared by other known variable region of antibodies. The Fab antibody libraries against SDM antigen were enriched by three cycles of affinity enrichment with male spleen cells, and two cycles of non-specific absorption with female spleen cells. The ELISA results showed that 9 of 15 clones had binding capacity to the SDM antigen. This is the first report on a phage display library of SDM antigen. The mouse Fab antibody library could be used for identifying SDM antigen, and for the development of sex determination of early embryos in mammals.

Dietary Supplementation of Astragalus Polysaccharides Enhanced Immune Components and Growth Factors EGF and IGF-1 in Sow Colostrum.

Colostrum is the main external resource providing piglets with nutrients and maternal immune molecules. Astragalus polysaccharides (APS) have been used as immunopotentiators in vitro and several animal models. This study aimed to determine the effects of APS on immune factors in sow colostrum and milk. The sow diet was supplemented with APS one week before the expected delivery date. Colostrum and milk were collected and designated as 0 h- (onset of parturition), 12 h-, and 24 h-colostrum and 36 h-milk postpartum. Samples were measured using porcine immunoglobulin (Ig) G, IgM, classical swine fever virus antibody (CSFV Ab), epidermal growth factor (EGF), and insulin-like growth factor- (IGF-) 1 ELISA Quantitation Kits. Dietary supplementation of APS significantly enhanced the presence of IgG, IgM, EGF, and IGF-1 in 0 h-colostrum (P < 0.001). The blocking rates of CSFV Ab were increased in samples from APS-supplemented sow when compared to those from the matched samples without APS treatment. The results indicate that supplement of APS could improve the immune components in sow colostrum and/or milk; and status of some specific vaccination could be determined through using colostrum or early milk in sow.

Uterine cytokine profile in a rat model of endometritis.

PROBLEM: Endometritis is a common reproductive disorder in female domestic animals. Roles of cytokines and chemokines have been implicated in this disease. To date, no comprehensive panel of the cytokine profile in inflammatory sites of endometritis has been reported. METHOD OF STUDY: To address cytokine profiles in endometritis, a bacteria-induced rat model of endometritis was developed and levels of 27 cytokines were measured in paired uterine horn tissues using a multiple cytokine array. RESULTS: Of the 27 cytokines, five pro-inflammatory mediators, including three cytokine-induced neutrophil chemo-attractant (CINC)-1, CINC-2 and CINC-3, interleukin (IL)-1a and CXC family member CXCL5/LIX were increased upon the stimulation of bacteria. CONCLUSIONS: High expression of CINCs as well IL-1a and CXCL5/LIX suggests their potent roles in the pathogenicity of endometritis.

Viral distribution and lesions in Kunming mice experimentally infected with porcine circovirus type 2b.

The viral distribution and lesions in Kunming mice experimentally infected with porcine circovirus type 2b (PCV-2b) were investigated. Seventy special pathogen free mice were divided into 2 groups with 35 mice in each group. The test group (TG) was infected with PCV-2b, the control group (CG) was inoculated with sterile cell cultures. Five mice in each group were sacrificed at 3, 7, 14, 21, 28, 35 and 42 dpi (day post infection), respectively. Necropsies were performed on all mice and tissues were collected for testing by histopathology, immunohistochemistry, transmission electron microscope (TEM) and polymerase chain reaction (PCR). Apoptosis and necrosis in lymphoid organs were observed in virus-infected mice, and became severe from 14 to 28 dpi. The proportion of PCV-2b antigen-positive cells was moderate in lung, heart, thymus, liver or kidney, and low in brain from TG. In spleen and cervical lymph node, the proportions of PCV-2b antigen-positive cells were low to high from 7 to 28 dpi, and moderate from 35 to 42 dpi. PCV-2b DNA was detected in all tissues examined in TG from 7 to 42 dpi. Viral inclusion bodies presented in the cytoplasm of lymphocytes, macrophages, hepatocytes, podocytes, neurocytes, spermatids and uterine epithelial cells in TG. In CG, no viruses and viral lesions were detected. PCV-2b could replicate in mice, and PCV-2b associated lesions in mice were similar to those observed in pigs. The present results indicate that it is possible to use Kunming mouse as an animal model for PMWS research.

Identification of mouse 8-cell embryo stage-specific genes by Digital Differential Display.

Preimplantation development is critical for successful implantation and pregnancy. In the mouse preimplantation embryo, the first event of morphological and cellular differentiation is established during polarization and compaction at the 8-cell stage. The considerable cell surface and cytoplasmic changes and formation of different populations of cells at the 8-cell stage are fundamentally important for the development of all organisms. To determine genes that are specifically expressed at this crucial stage of embryo development and also to shed light on the different mechanisms that could be of importance during embryo development, we investigated mouse 8-cell and 4-cell embryo stage-specific genes using Digital Differential Display (DDD). The 8-cell stage-specific genes were sorted according to their ontology data from the Database for Annotation, Visualization and Integrated Discovery (DAVID), which outlines possible roles for the genes expressed at the 8-cell stage. This study highlights how online tools can be used to identify genes involved in embryo development. Identification of the 8-cell embryo stage-specific genes would open new opportunities for understanding molecular networks during the mid-preimplantation gene activation. Using bioinformatic tools, such as Digital Differential Display and DAVID, it will be possible to identify genes expressed at the 8-cell stage that are likely to be involved in mammalian preimplantation embryo development. Our results may provide a new foundation for molecular control at the onset of embryonic development in mammals, and should be of interest to the scientific community.

[Cloning and analysis of phage Fab antibodies of mouse male specific antigen].

To clone mouse phage antibodies against H-Y antigen from a phage antibody library, three cycles of affinity enrichment of the mouse phage antibody library with male spleen cells and two cycles of nonspecific absorption with female spleen cells were performed. The presence of mouse Fab on the phage surface was determined by ELISA and sequence analysis. 9 of 15 strains can bind to male spleen cells with the specific activity. Recombination rate of the phage antibody library clones is 60%. Sequence analysis of the PCR products of plasmid DNA of E5 clones show VH and Vkappa had common characteristics shared by other known variable region of antibodies. The mouse phage Fab antibody could be used for identifying H-Y antigen, and for the development of sex determination of early embryos in mammals.