Identification and analysis of JHBP/TO family genes and their roles in the reproductive fitness cost of resistance in Frankliniella occidentalis (Pergande).

The juvenile hormone binding protein (JHBP) and takeout (TO) genes, mediated by the juvenile hormone (JH), play a crucial role in regulating the reproductive physiology of insects. Our previous study revealed that spinosad-resistant Frankliniella occidentalis (NIL-R) exhibited reduced fecundity and significant changes in JHBP/TO family gene expression. We hypothesized that these genes were involved in regulating the fitness costs associated with resistance. In this study, 45 JHBP/TO genes were identified in F. occidentalis, among which FoTO2 and FoTO10 were duplicates. Additionally, eight genes exhibited significant down-regulation in the NIL-R population. Two genes (FoTO6 and FoTO24) that exhibited the most significant differential expression between the spinosad-susceptible (Ivf03) and NIL-R populations were selected to investigate their roles in resistance fitness using RNA interference (RNAi). Following interference with FoTO6, FoTO24, and their combination, the expression levels of vitellogenin (Vg) were downregulated by 3%-30%, 13%-28%, and 14%-32% from the 2nd day to the 5th day, respectively; Krüppel-homolog 1 (Kr-h1) expression was down-regulated by 3%-65%, 11%-34%, and 11%-39% from the 2nd day to the 5th day, respectively; ovariole length was shortened by approximately 18%, 21%, and 24%, respectively; and the average number of eggs decreased from 407 to 260, 148, and 106, respectively. Additionally, a JH supplementation experiment on the NIL-R population revealed that the expression levels of both FoTO6, FoTO24, Vg and Kr-h1 were significantly upregulated compared with those observed in the Ivf03 population, resulting in increased fecundity. These results suggest that FoTO6 and FoTO24 are involved in JH-mediated regulation of the reproductive fitness cost of resistance to spinosad. Further, FoTO6 and FoTO24 can be considered potential target genes for applying RNAi technology in the scientific management of F. occidentalis.

Artificial intelligence automated surgical phases recognition in intraoperative videos of laparoscopic pancreatoduodenectomy.

BACKGROUND: Laparoscopic pancreatoduodenectomy (LPD) is one of the most challenging operations and has a long learning curve. Artificial intelligence (AI) automated surgical phase recognition in intraoperative videos has many potential applications in surgical education, helping shorten the learning curve, but no study has made this breakthrough in LPD. Herein, we aimed to build AI models to recognize the surgical phase in LPD and explore the performance characteristics of AI models. METHODS: Among 69 LPD videos from a single surgical team, we used 42 in the building group to establish the models and used the remaining 27 videos in the analysis group to assess the models' performance characteristics. We annotated 13 surgical phases of LPD, including 4 key phases and 9 necessary phases. Two minimal invasive pancreatic surgeons annotated all the videos. We built two AI models for the key phase and necessary phase recognition, based on convolutional neural networks. The overall performance of the AI models was determined mainly by mean average precision (mAP). RESULTS: Overall mAPs of the AI models in the test set of the building group were 89.7% and 84.7% for key phases and necessary phases, respectively. In the 27-video analysis group, overall mAPs were 86.8% and 71.2%, with maximum mAPs of 98.1% and 93.9%. We found commonalities between the error of model recognition and the differences of surgeon annotation, and the AI model exhibited bad performance in cases with anatomic variation or lesion involvement with adjacent organs. CONCLUSIONS: AI automated surgical phase recognition can be achieved in LPD, with outstanding performance in selective cases. This breakthrough may be the first step toward AI- and video-based surgical education in more complex surgeries.

Dual Guardians of Immunity: FoRab10 and FoRab29 in Frankliniella occidentalis Confer Resistance to Tomato Spotted Wilt Orthotospovirus.

Rab GTPase is critical for autophagy processes and is implicated in insect immunity against viruses. In this study, we aimed to investigate the role of FoRabs in the autophagic regulation of antiviral defense against tomato spotted wilt orthotospovirus (TSWV) in Frankliniella occidentalis. Transcriptome analysis revealed the downregulation of FoRabs in viruliferous nymph and adults of F. occidentalis in response to TSWV infection. Manipulation of autophagy levels with 3-MA and Rapa treatments resulted in a 5- to 15-fold increase and a 38-64% decrease in viral titers, respectively. Additionally, interference with FoRab10 in nymphs and FoRab29 in adults led to a 20-90% downregulation of autophagy-related genes, a decrease in ATG8-II (an autophagy marker protein), and an increase in the TSWV titers by 1.5- to 2.5-fold and 1.3- to 2.0-fold, respectively. In addition, the leaf disk and the living plant methods revealed increased transmission rates of 20.8-41.6 and 68.3-88.3%, respectively. In conclusion, FoRab10 and FoRab29 play a role in the autophagic regulation of the antiviral defense in F. occidentalis nymphs and adults against TSWV, respectively. These findings offer insights into the intricate immune mechanisms functional in F. occidentalis against TSWV, suggesting potential targeted strategies for F. occidentalis and TSWV management.

Association between triglyceride to high-density lipoprotein cholesterol ratio and nonalcoholic fatty liver disease and liver fibrosis in American adults: an observational study from the National Health and Nutrition Examination Survey 2017-2020.

Objective: This study investigated the link between triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio and nonalcoholic fatty liver disease (NAFLD) and liver fibrosis in American adults. Methods: Information for 6495 participants from the National Health and Nutrition Examination Survey (NHANES) 2017-2020.03 was used for this cross-sectional study. The link between TG/HDL-C ratios and NAFLD and liver fibrosis was assessed by multiple linear regression before evaluating nonlinear correlations based on smoothed curve fitting models. Stratification analysis was then applied to confirm whether the dependent and independent variables displayed a stable association across populations. Results: TG/HDL-C ratios were positively correlated with NAFLD, with higher ratios being linked to increased prevalence of NAFLD. After adjusting for potential confounders, the odds ratios (OR) for NAFLD patients in the fourth TG/HDL-C quartile were 3.61 (95% confidence interval [CI], 2.94-4.38) (P for trend < 0.001) in comparison with those in the first quartile after adjusting for clinical variables. However, no statistical significance was noted for the ratio for liver fibrosis after adjusting for potential confounders (P for trend = 0.07). A nonlinear correlation between TG/HDL-C ratios and NAFLD was observed based on smoothed curve fitting models. However, a nonlinear relationship between the ratios and liver fibrosis was not established. In subgroup analyses, there was an interaction between smoking status and TG/HDL-C ratio in relation to the prevalence of liver fibrosis (P for interaction < 0.001). Conclusions: Among American adults, the TG/HDL-C ratio was noted to be nonlinearly positively associated with the prevalence of NAFLD; however, this relationship was not present in liver fibrosis.

Relationship of triglyceride-glucose index to gallstone prevalence and age at first gallstone surgery in American adults.

The triglyceride-glucose (TyG) index is a novel marker of insulin resistance that has been strongly associated with many diseases related to metabolic disorders, such as diabetes, coronary heart disease, myocardial infarction, obesity, nonalcoholic fatty liver disease, and stroke. However, whether the TyG index is associated with the prevalence of gallstones has not been determined. Therefore, the purpose of this study was to evaluate the relationship between the TyG index and the prevalence of gallstones in American adults, as well as the age at which adults in America undergo their first gallstone surgery. We selected individuals from the National Health and Nutrition Examination Survey (NHANES) database from 2017 to March 2020. Based on the goal of our study, comprehensive inclusion and exclusion criteria were created. A logistic regression analysis, dose-response curve, and subgroup analysis were computed to assess the relationship between the TyG index and gallstone prevalence and age at first surgery for gallstone. A total of 3905 participants aged > 20 years were included in our study, of whom 421 had a self-reported history of gallstones. A total of 1884 (48.2%) males and 2021 (51.8%) females were included. After confounders adjustment, it was found single-unit increases in the TyG index were linked with a 25.0% increase in gallstone prevalence (odds ratio [OR] = 1.25, 95% confidence interval [95%CI]: 1.04, 1.51). After conversion of the TyG index values from continuous to categorical variables with tertiles, a marked 48% increase in gallstone incidence was found in tertile 3 relative to tertile 1 (OR = 1.48, 95% CI: 1.09, 1.99). The dose-response curve results indicated positive associations between gallstone prevalence and the TyG index, while the latter was negatively associated with age at first gallstone surgery. Based on subgroup analysis, the positive association between TyG index and high-incidence of gallstones was more significant in females (OR = 1.39, 95% CI: 1.09, 1.77), age < 40 years (OR = 2.02, 95% CI: 1.23, 3.29), and other race (OR = 1.46, 95% CI: 1.06, 2.02). A higher TyG index is associated with a higher incidence of gallstones and may lead to an earlier age of first gallstone surgery. However, a causal relationship between TyG and gallstones cannot be established.

Calibration of contact parameters of sandy soil for planting tiger nut based on non-linear tools.

A methodology combining physical experiments with simulation was employed to acquire contact parameters of sandy soil precisely for planting tiger nuts in the desert area of Xinjiang. The stacking angle under different parameter combinations was applied as a response value. Through the Plackett-Burman test, several factors that have a significant influence were determined. The steepest ascent test was conducted to establish the finest scope of values for these parameters. The stacking angle was considered the response variable, and non-linear tools were used to optimize these parameters for simulation. The findings showed that applying response surface methodology (RSM) resulted in a relative error of 1.24%. In the case of BP-GA, the relative error compared to the physical test value was 0.34%, while for BP, it was 2.18%. After optimization using Wavelet Neural Network (WNN), the relative error was reduced to only 0.15%. Results suggest that WNN outperforms the RSM model, and the sandy soil model and parameters generated using WNN can be effectively utilized for discrete element simulation research.

naRNA-LL37 composite DAMPs define sterile NETs as self-propagating drivers of inflammation.

Neutrophil extracellular traps (NETs) are a key antimicrobial feature of cellular innate immunity mediated by polymorphonuclear neutrophils (PMNs). NETs counteract microbes but are also linked to inflammation in atherosclerosis, arthritis, or psoriasis by unknown mechanisms. Here, we report that NET-associated RNA (naRNA) stimulates further NET formation in naive PMNs via a unique TLR8-NLRP3 inflammasome-dependent pathway. Keratinocytes respond to naRNA with expression of psoriasis-related genes (e.g., IL17, IL36) via atypical NOD2-RIPK signaling. In vivo, naRNA drives temporary skin inflammation, which is drastically ameliorated by genetic ablation of RNA sensing. Unexpectedly, the naRNA-LL37 'composite damage-associated molecular pattern (DAMP)' is pre-stored in resting neutrophil granules, defining sterile NETs as inflammatory webs that amplify neutrophil activation. However, the activity of the naRNA-LL37 DAMP is transient and hence supposedly self-limiting under physiological conditions. Collectively, upon dysregulated NET release like in psoriasis, naRNA sensing may represent both a potential cause of disease and a new intervention target.

Heterogeneity of myeloid cells in common cancers: Single cell insights and targeting strategies.

Tumor microenvironment (TME), is characterized by a complex and heterogenous composition involving a substantial population of immune cells. Myeloid cells comprising over half of the solid tumor mass, are undoubtedly one of the most prominent cell populations associated with tumors. Studies have unambiguously established that myeloid cells play a key role in tumor development, including immune suppression, pro-inflammation, promote tumor metastasis and angiogenesis, for example, tumor-associated macrophages promote tumor progression in a variety of common tumors, including lung cancer, through direct or indirect interactions with the TME. However, due to previous technological constraints, research on myeloid cells often tended to be conducted as studies with low throughput and limited resolution. For example, the conventional categorization of macrophages into M1-like and M2-like subsets based solely on their anti-tumor and pro-tumor roles has disregarded their continuum of states, resulting in an inadequate analysis of the high heterogeneity characterizing myeloid cells. The widespread adoption of single-cell RNA sequencing (scRNA-seq) in tumor immunology has propelled researchers into a new realm of understanding, leading to the establishment of novel subsets and targets. In this review, the origin of myeloid cells in high-incidence cancers, the functions of myeloid cell subsets examined through traditional and single-cell perspectives, as well as specific targeting strategies, are comprehensively outlined. As a result of this endeavor, we will gain a better understanding of myeloid cell heterogeneity, as well as contribute to the development of new therapeutic approaches.

Carbon emission prediction models: A review.

Amidst growing concerns over the greenhouse effect, especially its consequential impacts, establishing effective Carbon Emission Prediction Models (CEPMs) to comprehend and predict CO2 emission trends is imperative for climate change mitigation. A review of 147 Carbon Emission Prediction Model (CEPM) studies revealed three predominant functions-prediction, optimization, and prediction factor selection. Statistical models, comprising 75 instances, were the most prevalent among prediction models, followed by neural network models at 21.8 %. The consistent rise in neural network model usage, particularly feedforward architectures, was observed from 2019 to 2022. A majority of CEPMs incorporated optimized approaches, with 94.4 % utilizing metaheuristic models. Parameter optimization was the primary focus, followed by structure optimization. Prediction factor selection models, employing Grey Relational Analysis (GRA) and Principal Component Analysis (PCA) for statistical and machine learning models, respectively, filtered factors effectively. Scrutinizing accuracy, pre-optimized CEPMs exhibited varied performance, Root Mean Square Error (RMSE) values spanned from 0.112 to 1635 Mt, while post-optimization led to a notable improvement, the minimum RMSE reached 0.0003 Mt, and the maximum was 95.14 Mt. Finally, we summarized the pros and cons of existing models, classified and counted the factors that influence carbon emissions, clarified the research objectives in CEPM and assessed the applied model evaluation methods and the spatial and temporal scales of existing research.

Association between serum creatinine to albumin ratio and short- and long-term all-cause mortality in patients with acute pancreatitis admitted to the intensive care unit: a retrospective analysis based on the MIMIC-IV database.

Background: Serum creatinine (Cr) and albumin (Alb) are important predictors of mortality in individuals with various diseases, including acute pancreatitis (AP). However, most previous studies have only examined the relationship between single Cr or Alb levels and the prognosis of patients with AP. To our knowledge, the association between short- and long-term all-cause mortality in patients with AP and the blood creatinine to albumin ratio (CAR) has not been investigated. Therefore, this study aimed to evaluate the short- and long-term relationships between CAR and all-cause mortality in patients with AP. Methods: We conducted a retrospective study utilizing data from the Medical Information Market for Intensive Care (MIMIC-IV) database. The study involved analyzing various mortality variables and obtaining CAR values at the time of admission. The X-tile software was used to determine the optimal threshold for the CAR. Kaplan-Meier (K-M) survival curves and multivariate Cox proportional hazards regression models were used to assess the relationship between CAR and both short- and long-term all-cause mortality. The predictive power, sensitivity, specificity, and area under the curve (AUC) of CAR for short- and long-term mortality in patients with AP after hospital admission were investigated using Receiver Operating Characteristic analysis. Additionally, subgroup analyses were conducted. Results: A total of 520 participants were included in this study. The CAR ideal threshold, determined by X-tile software, was 0.446. The Cox proportional hazards model revealed an independent association between CAR≥0.446 and all-cause mortality at 7-day (d), 14-d, 21-d, 28-d, 90-d, and 1-year (y) before and after adjustment for confounders. K-M survival curves showed that patients with CAR≥0.446 had lower survival rates at 7-d, 14-d, 21-d, 28-d, 90-d, and 1-y. Additionally, CAR demonstrated superior performance, with higher AUC values than Cr, Alb, serum total calcium, Glasgow Coma Scale, Systemic Inflammatory Response Syndrome score, and Sepsis-related Organ Failure Assessment score at 7-d, 14-d, 21-d, 28-d, 90-d, and 1-y intervals. Subgroup analyses showed that CAR did not interact with a majority of subgroups. Conclusion: The CAR can serve as an independent predictor for short- and long-term all-cause mortality in patients with AP. This study enhances our understanding of the association between serum-based biomarkers and the prognosis of patients with AP.

Self-Interested Coalitional Crowdsensing for Multi-Agent Interactive Environment Monitoring.

As a promising paradigm, mobile crowdsensing (MCS) takes advantage of sensing abilities and cooperates with multi-agent reinforcement learning technologies to provide services for users in large sensing areas, such as smart transportation, environment monitoring, etc. In most cases, strategy training for multi-agent reinforcement learning requires substantial interaction with the sensing environment, which results in unaffordable costs. Thus, environment reconstruction via extraction of the causal effect model from past data is an effective way to smoothly accomplish environment monitoring. However, the sensing environment is often so complex that the observable and unobservable data collected are sparse and heterogeneous, affecting the accuracy of the reconstruction. In this paper, we focus on developing a robust multi-agent environment monitoring framework, called self-interested coalitional crowdsensing for multi-agent interactive environment monitoring (SCC-MIE), including environment reconstruction and worker selection. In SCC-MIE, we start from a multi-agent generative adversarial imitation learning framework to introduce a new self-interested coalitional learning strategy, which forges cooperation between a reconstructor and a discriminator to learn the sensing environment together with the hidden confounder while providing interpretability on the results of environment monitoring. Based on this, we utilize the secretary problem to select suitable workers to collect data for accurate environment monitoring in a real-time manner. It is shown that SCC-MIE realizes a significant performance improvement in environment monitoring compared to the existing models.

Uridine diphosphate glucosyltransferases are involved in spinosad resistance in western flower thrips Frankliniella occidentalis (Pergande).

Uridine diphosphate glucosyltransferases (UGTs) play crucial roles in the insect detoxification system and are associated with pesticide resistance. Our previous transcriptomic analysis of spinosad-susceptible (Ivf03) and resistant (NIL-R) Frankliniella occidentalis revealed numerous upregulated UGT genes in the NIL-R strain, suggesting their potential contribution to spinosad resistance. To investigate this hypothesis, here we conducted UGT activity assays and spinosad induction experiments, employing RNA interference (RNAi) techniques for gene function validation. We found significantly elevated UGT activity in the NIL-R strain compared to Ivf03, with 5-nitrouracil showing a substantial synergistic effect on the resistant strain. Eighteen UGT genes were identified in F. occidentalis, with gene expansion and duplication observed within families UGT466, 467, and 468. Ten out of the eighteen UGTs exhibited higher expression levels in NIL-R, specifically FoUGT466B1, FoUGT468A3, and FoUGT468A4 consistently being upregulated across nymphs, males, and females. RNAi-based functional validation targeting these three UGT genes led to increased susceptibility to spinosad in a life stage-, sex-, and dose-dependent manner. These results indicate that UGTs are indeed involved in spinosad resistance in F. occidentalis, and the effects are dependent on life stage, sex, and dose. Therefore, sustainable control for F. occidentalis resistance should always consider these differential responses.

AFF4 regulates osteogenic potential of human periodontal ligament stem cells via mTOR-ULK1-autophagy axis.

Scaffold protein AF4/FMR2 family member 4 (AFF4) has been found to play a role in osteogenic commitment of stem cells. However, function of AFF4 in human periodontal ligament stem cells (hPDLSCs) has not been studied yet. This present study aims to investigate the biological effect of AFF4 on osteogenic differentiation of hPDLSCs and potential mechanistic pathway. First, AFF4 expression profile was evaluated in conditions of periodontitis and osteogenic differentiation of hPDLSCs by immunohistochemical staining, western blot and qRT-PCR. Next, si-RNA mediated knockdown and lentiviral transduction mediated overexpression of AFF4 were adopted to explore impact of AFF4 on osteogenic capacity of hPDLSCs. Then, possible mechanistic pathway was identified. At last, pharmacological agonist of autophagy, rapamycin, was utilized to affirm the role of autophagy in AFF4-regulated osteogenesis of hPDLSCs. First, AFF4 expressions were significantly lower in inflamed periodontal tissues and lipopolysaccharides-treated hPDLSCs than controls, and were up-regulated during osteogenic differentiation of hPDLSCs. Next, osteogenic potential of hPDLSCs was impaired by AFF4 knockdown and potentiated by AFF4 overexpression. Moreover, AFF4 was found to positively regulate autophagic activity in hPDLSCs. At last, rapamycin treatment was shown to be able to partly restore AFF4 knockdown-suppressed osteogenic differentiation. Our study demonstrates that AFF4 regulates osteogenic potential of hPDLSCs via targeting autophagic activity. The involvement of AFF4 in periodontal homeostasis was identified for the first time.

Improving microbial production of value-added products through the intervention of magnetic fields.

The magnetic field application is emerging as an auxiliary physical strategy to facilitate rapid biomass accumulation and intracellular production of compounds. However, the underlying mechanisms and principles governing the application of magnetic fields for microbial growth and biotransformation are not yet fully understood. Therefore, a better understanding of interdisciplinary technologies integration, expanded magnetic field application, and scaled-up industrial implementation is crucial. In this review, the magnetic field characteristics, magnetic field-assisted fermentation devices, and the working mechanism of magnetic field have been reviewed comprehensively from both physical and microbiological perspectives. The review suggests that magnetic fields affect the biochemical processes in microorganisms by mediating nutrient transport across membranes, electron transfer during photosynthesis and respiration, enzyme activity and gene expression. Moreover, the recent advances in magnetic field application for microbial fermentation and conversion in biochemical, food and agricultural fields have been summarized.

Identifying the cancer-associated fibroblast signature to predict the prognosis and immunotherapy response in patients with lung squamous cell carcinoma.

Cancer-associated fibroblasts (CAFs) are an important component of the tumor microenvironment that contribute toward the development of tumors. This study aimed to establish a new algorithm based on CAF scores to predict the prognosis and immunotherapy response in patients with lung squamous cell carcinoma (LUSC). The RNA-seq data of LUSC patients were obtained from two databases and merged after removing inter-batch differences. The CAF-related data for each sample were obtained through three different algorithms. Consistency cluster analysis was performed to obtain different CAF clusters, which were analyzed to identify differentially expressed genes. These were subjected to uniform cluster analysis to obtain different gene clusters. The Boruta algorithm was used to calculate the CAF score. Three CAF clusters and two gene clusters were obtained, all of which differed in their patient prognoses and the content of infiltrating immune cells. Patients with high CAF scores exhibited worse overall survival, higher expression of biomarkers related to immune checkpoints and immune activity, and lower tumor mutation burden. The CAF score could also predict the immunotherapy response of patients. This study suggests that the CAF score can accurately predict the prognosis and immunotherapy response of LUSC patients.

Knockdown of GNL3L Alleviates the Progression of COPD Through Inhibiting the ATM/p53 Pathway.

Background: Chronic obstructive pulmonary disease (COPD) is a persistent chronic bronchitis disease, and its potential biomarkers have not been fully expounded. This study aims to explore the role of Guanine nucleotide binding protein like-3-like (GNL3L) in COPD induced by cigarette smoking (CS) in vivo. Methods: Two microarray datasets of COPD were selected to screen differentially expressed genes (DEGs). A protein-protein interaction network was constructed to find hub genes. The COPD model was conducted using CS/LPS-induced mouse and cigarette smoke extract induced human bronchial epithelial cells. The pathological changes of lung tissue in mice were observed by hematoxylin-eosin staining and mean linear intercept. Cell viability was measured by CCK8 assay. Oxidative stress-related indicators, inflammatory factors, and ATM/p53 related-proteins were assessed using ELISA and Western blot. Results: In this study, there were 110 common DEGs identified from the two datasets (GSE5058 and GSE38974). The key gene GNL3L was the optimal indicator to distinguish between samples with COPD and healthy controls. Through the in vivo and in vitro experiments, GNL3L knockdown significantly improved the pathological features of CS/LPS-induced COPD mice, promoted cell viability, inhibited inflammation (IL-1ß, IL-8, and TNF-α), oxidative stress (MDA, SOD, and CAT), and ATM/p53 related-proteins (ATM, p53, and p21). Conclusion: GNL3L is a novel biomarker of COPD, and knockdown of GNL3L participates in the progression of COPD by inhibiting ATM/p53 pathway.

Enhanced adsorption of diclofenac onto activated carbon derived from PET plastic by one-step pyrolysis with KOH.

Plastic pollution is a severe threat to the health of ecosystems, and recycling plastics is recognized as a key control strategy. This study used the one-step pyrolysis assisted with KOH activation to recycle the widely used polyethylene terephthalate (PET) plastic as activated carbon (PET-AC) which was subsequently applied to adsorb diclofenac (DCF), a frequently detected emerging contaminant in water, for the first time. It was found that both the pyrolysis temperature and the addition of KOH can effectively regulate the pore sizes and volumes of PET-AC. PET-AC obtained at 700 °C demonstrated a high adsorption capacity of DCF up to 179.42 mg g-1 at 45 °C. The adsorption kinetics was conducted with both static jar and dynamic column tests and analyzed with various models. Thermodynamic results demonstrated that the adsorption of DCF was spontaneous and endothermic. The material also presented an excellent potential to adsorb other pharmaceuticals and personal care products in water. XPS and FTIR analysis indicated that the adsorption might be mainly driven by the physical forces, especially π-π interaction and hydrogen bonding. This study provided a reference for recycling waste plastic as an efficient adsorbent to eliminate organic contaminants from water.

The impact of MIF deficiency on alterations of fecal microbiota in C57BL/6 mice induced by Trichinella spiralis infection.

Trichinellosis caused by Trichinella spiralis (T. spiralis) is a major food-borne parasitic zoonosis worldwide. Prevention of trichinellosis is an effective strategy to improve patient quality of life. Macrophage migration inhibitory factor (MIF) is closely related to the occurrence and development of several parasitic diseases. Studying the impact of MIF deficiency (Mif-/- ) on the alterations in host fecal microbiota due to T. spiralis infection may contribute to proposing a novel dual therapeutic approach for trichinellosis. To reveal the diversity and differences in fecal microbial composition, feces were collected from T. spiralis-uninfected and T. spiralis-infected wild-type (WT) and MIF knockout (KO) C57BL/6 mice at 0, 7, 14, and 35 days post-infection (dpi), and the samples were sent for 16S rRNA amplicon sequencing on the Illumina NovaSeq platform. Flow cytometry was used to determine the expression levels of IFN-γ and IL-4 in the CD4+ /CD8+ T-cell sets of mouse spleens. The results showed that operational taxonomic unit (OTU) clustering, relative abundance of microbial composition, alpha diversity, and beta diversity exhibited significant changes among the eight groups. The LEfSe analysis selected several potential biomarkers at the genus or species level, including Akkermansia muciniphila, Lactobacillus murinus, Coprococcus catus, Firmicutes bacterium M10_2, Parabacteroides sp. CT06, and Bacteroides between the KTs and WTs groups. The predicted bacterial functions of the fecal microbiota were mainly involved in metabolism, such as the metabolism of carbohydrates, amino acids, energy, cofactors, vitamins, nucleotides, glycans, and lipids. Flow cytometry revealed an increased CD3+ CD8- /CD3+ CD8+ T-cell ratio and increased IFN-γ and IL-4 levels in CD3+ CD8- T-cell sets from WT and MIF KO mice at 7 dpi. The results indicated that both MIF KO and infection time have a significant influence on the CD3+ CD8- IFN-γ+ and CD3+ CD8- IL-4+ response in mice after T. spiralis. In conclusion, this research showed alterations of the fecal microbiota and immune response in both WT and MIF KO mice before and after T. spiralis infection. These results revealed a potential role of MIF in regulating the pathogenesis of trichinellosis related to the intestinal microbiota. Importantly, the selected potential biomarkers combined with MIF will also offer a novel therapeutic approach to treat trichinellosis in the future.

Delivery of Small-Molecule Drugs and Protein Drugs by Injectable Acid-Responsive Self-Assembled COF Hydrogels for Combinatorial Lung Cancer Treatment.

Covalent organic frameworks (COFs) have revealed enormous application prospects for cancer therapeutics recently, but their assembly systems face considerable challenges, such as the codelivery of hydrophobic and hydrophilic protein drugs with different physicochemical properties for in vivo delivery and release, as well as endosomal/lysosomal escape of protein drugs. To address these issues, we leveraged the high specific surface area, lipotropism, and structural tunability of boronate ester-linked COFs (COF-1) for the construction of advanced drug delivery systems. We first encapsulated the small-molecule drug doxorubicin (DOX) into a lipophilic COF (COF-1@DOX) and immobilized the functional protein drug ribonuclease A (RNase A) on the surface of the COF (RNase A-COF-1@DOX). We then created a novel composite delivery system (RNase A-COF-1@DOX gel) by cross-linking an albumin-oxygenated hydrogel (gel) network into the pores of COFs, allowing targeted codelivery of protein and small-molecule drugs in vivo. Using in-living body and multichannel fluorescence imaging, we analyzed the in vivo codelivery of protein and small-molecule drugs in a Lewis lung carcinoma (LLC) model. Finally, we applied the RNase A-COF-1@DOX gel to treat lung cancer in mice. This study paves an avenue for constructing COF-based drug delivery systems for lung cancer treatment and holds the potential to be extended to other types of cancer for more effective and targeted therapeutic treatments.

Overview of Avian Sex Reversal.

Sex determination and differentiation are processes by which a bipotential gonad adopts either a testicular or ovarian cell fate, and secondary sexual characteristics adopt either male or female developmental patterns. In birds, although genetic factors control the sex determination program, sex differentiation is sensitive to hormones, which can induce sex reversal when disturbed. Although these sex-reversed birds can form phenotypes opposite to their genotypes, none can experience complete sex reversal or produce offspring under natural conditions. Promising evidence indicates that the incomplete sex reversal is associated with cell autonomous sex identity (CASI) of avian cells, which is controlled by genetic factors. However, studies cannot clearly describe the regulatory mechanism of avian CASI and sex development at present, and these factors require further exploration. In spite of this, the abundant findings of avian sex research have provided theoretical bases for the progress of gender control technologies, which are being improved through interdisciplinary co-operation and will ultimately be employed in poultry production. In this review, we provide an overview of avian sex determination and differentiation and comprehensively summarize the research progress on sex reversal in birds, especially chickens. Importantly, we describe key issues faced by applying gender control systems in poultry production and chronologically summarize the development of avian sex control methods. In conclusion, this review provides unique perspectives for avian sex studies and helps scientists develop more advanced systems for sex regulation in birds.