Reduction of bitter taste receptor gene family in folivorous colobine primates relative to omnivorous cercopithecine primates.

Bitter taste perception is important in preventing animals from ingesting potentially toxic compounds. Whole-genome assembly (WGA) data have revealed that bitter taste receptor genes (TAS2Rs) comprise a multigene family with dozens of intact and disrupted genes in primates. However, publicly available WGA data are often incomplete, especially for multigene families. In this study, we employed a targeted capture (TC) approach specifically probing TAS2Rs for ten species of cercopithecid primates with diverse diets, including eight omnivorous cercopithecine species and two folivorous colobine species. We designed RNA probes for all TAS2Rs that we modeled to be intact in the common ancestor of cercopithecids ("ancestral-cercopithecid TAS2R gene set"). The TC was followed by short-read and high-depth massive-parallel sequencing. TC retrieved more intact TAS2R genes than found in WGA databases. We confirmed a large number of gene "births" at the common ancestor of cercopithecids and found that the colobine common ancestor and the cercopithecine common ancestor had contrasting trajectories: four gene "deaths" and three gene births, respectively. The number of intact TAS2R genes was markedly reduced in colobines (25-28 detected via TC and 20-26 detected via WGA analysis) as compared with cercopithecines (27-36 via TC and 19-30 via WGA). Birth or death events occurred at almost every phylogenetic-tree branch, making the composition of intact genes variable among species. These results show that evolutionary change in intact TAS2R genes is a complex process, refute a simple general prediction that herbivory favors more TAS2R genes, and have implications for understanding dietary adaptations and the evolution of detoxification abilities.

Triglyceride-glucose Index as a Valuable Marker to Predict Severity of Coronary Artery Disease: A Retrospective Cohort Study.

BACKGROUND AND AIMS: The diagnostic standard of coronary artery disease (CAD) is coronary angiography (CAG). Since CAG is an invasive procedure underscores the need for identifying non-invasive, effective, and innovative biomarkers. Our study aimed to retrospectively analyze hematological markers for predicting the severity of CAD. METHODS AND RESULTS: Case data were collected from 195 CAD patients admitted to the hospital for CAG. According to Gensini score, patients were divided into mild, moderate, and severe CAD groups. Blood indexes and predictive efficacy of the triglyceride-glucose (TyG) index were retrospectively analyzed. Among 195 CAD patients, 81 had mild CAD, 60 had moderate CAD, and 54 had severe CAD. Sex, fast blood glucose (FBG), TyG index, and high-sensitivity C-reactive protein (hs-CRP) significantly differed among the three groups. The TyG index demonstrated higher values in patients with moderate (9.07[8.62-9.44]) and severe (8.98[8.46-9.45]) CAD compared to those with mild CAD (8.75[8.49-9.14]). The AUC of the TyG index was 0.615 (95% confidence interval (CI): 0.536-0.694, P =.004), with a cut-off value of 8.997, specificity of 0.704, and sensitivity of 0.535. Logistics analysis showed the risk of moderate and severe CAD with an odds ratio (OR) value of 2.595 (95% CI: 1.199-5.619, adjusted P = .016) following regrouping by the TyG index optimal cut-off value of 8.997. The TyG index combined with FBG and hs-CRP had an elevated AUC value, significantly higher than other combinations (P = .011 and 0.02, respectively). CONCLUSIONS: The severity of CAD is positively correlated with an increased TyG index value. A combination of TyG, FBG, and hs-CRP has demonstrated improved diagnostic efficiency, suggesting its potential as a novel indicator for predicting and diagnosing CAD progression.

A nomogram based on CT intratumoral and peritumoral radiomics features preoperatively predicts poorly differentiated invasive pulmonary adenocarcinoma manifesting as subsolid or solid lesions: a double-center study.

Background: The novel International Association for the Study of Lung Cancer (IASLC) grading system suggests that poorly differentiated invasive pulmonary adenocarcinoma (IPA) has a worse prognosis. Therefore, prediction of poorly differentiated IPA before treatment can provide an essential reference for therapeutic modality and personalized follow-up strategy. This study intended to train a nomogram based on CT intratumoral and peritumoral radiomics features combined with clinical semantic features, which predicted poorly differentiated IPA and was tested in independent data cohorts regarding models' generalization ability. Methods: We retrospectively recruited 480 patients with IPA appearing as subsolid or solid lesions, confirmed by surgical pathology from two medical centers and collected their CT images and clinical information. Patients from the first center (n =363) were randomly assigned to the development cohort (n = 254) and internal testing cohort (n = 109) in a 7:3 ratio; patients (n = 117) from the second center served as the external testing cohort. Feature selection was performed by univariate analysis, multivariate analysis, Spearman correlation analysis, minimum redundancy maximum relevance, and least absolute shrinkage and selection operator. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the model performance. Results: The AUCs of the combined model based on intratumoral and peritumoral radiomics signatures in internal testing cohort and external testing cohort were 0.906 and 0.886, respectively. The AUCs of the nomogram that integrated clinical semantic features and combined radiomics signatures in internal testing cohort and external testing cohort were 0.921 and 0.887, respectively. The Delong test showed that the AUCs of the nomogram were significantly higher than that of the clinical semantic model in both the internal testing cohort(0.921 vs 0.789, p< 0.05) and external testing cohort(0.887 vs 0.829, p< 0.05). Conclusion: The nomogram based on CT intratumoral and peritumoral radiomics signatures with clinical semantic features has the potential to predict poorly differentiated IPA manifesting as subsolid or solid lesions preoperatively.

Cumulative live birth rate of in vitro fertilization cycle via progestin-primed ovarian stimulation versus gonadotropin-releasing hormone antagonist protocol in infertile women with normal ovarian reserve: an open-label, randomized controlled trial.

This study aimed to evaluate the cumulative live birth rate (cLBR) of progestin-primed ovarian stimulation (PPOS) protocol versus gonadotropin-releasing hormone antagonist (GnRH-ant) protocol for in vitro fertilization (IVF) cycle in infertile women with normal ovarian reserve (NOR). Infertile women with NOR who underwent their first IVF cycle were enrolled in an open-label randomized controlled trial. Patients were randomly assigned 1:1 to receive a freeze-all strategy with delayed embryo transfer (PPOS group, n = 174) and fresh embryo transfer first (GnRH-ant group, n = 174). The primary outcome was the cLBR per aspiration. The cLBR between the PPOS group and GnRH-ant group were comparable (55.75% vs. 52.87%, p = 0.591). A premature luteinizing hormone surge was not observed in the PPOS group, while there were six cases (3.45%) in the GnRH-ant group, but no premature ovulation in either of the groups. The pregnancy outcomes, including implantation rate, clinical pregnancy rate and miscarriage rate, were all comparable. In addition, the number of retrieved oocytes, mature oocytes and viable embryos were similar (all p > 0.05) between the two groups.

Machine learning-based model for prediction of deep vein thrombosis after gynecological laparoscopy: A retrospective cohort study.

Successful monitoring of deep vein thrombosis (DVT) remains a challenging problem after gynecological laparoscopy. Thus, this study aimed to create and validate predictive models for DVT with the help of machine learning (ML) algorithms. A total of 489 patients from the Cancer Biology Research Center, Tongji Hospital were included in the study between January 2017 and February 2023, and 35 clinical indicators from electronic health records (EHRs) were collected within 24h of patient admission. Risk factors were identified using the least absolute shrinkage and selection operator (LASSO) regression. Then, the three commonly used DVT prediction models are random forest model (RFM), generalized linear regression model (GLRM), and artificial neural network model (ANNM). In addition, the predictive performance of various prediction models (i.e. the robustness and accuracy of predictions) is evaluated through the receiver operating characteristic curve (ROC) and decision curve analysis (DCA), respectively. We found postoperative DVT in 41 (8.38%) patients. Based on the ML algorithm, a total of 13 types of clinical data were preliminarily screened as candidate variables for DVT prediction models. Among these, age, body mass index (BMI), operation time, intraoperative pneumoperitoneum pressure (IPP), diabetes, complication and D-Dimer independent risk factors for postoperative DVT and can be used as variables in ML prediction models. The RFM algorithm can achieve the optimal DVT prediction performance, with AUC values of 0.851 (95% CI: 0.793-0.909) and 0.862 (95% CI: 0.804-0.920) in the training and validation sets, respectively. The AUC values of the other two prediction models (ANNM and GLRM) range from 0.697 (95% CI: 0.639-0.755) and 0.813 (95% CI: 0.651-0.767). In summary, we explored the potential risk of DVT after gynecological laparoscopy, which helps clinicians identify high-risk patients before gynecological laparoscopy and make nursing interventions. However, external validation will be needed in the future.

Interaction between adolescent sleep rhythms and gender in an obese population.

BACKGROUND: The obesity rate of adolescents is gradually increasing, which seriously affects their mental health, and sleep plays an important role in adolescent obesity. AIM: To investigate the relationship between sleep rhythm and obesity among adolescents and further explores the interactive effect of sleep rhythm and gender on adolescent obesity, providing a theoretical basis for developing interventions for adolescent obesity. METHODS: Research data source Tianjin Mental Health Promotion Program for Students. From April to June 2022, this study selected 14201 students from 13 middle schools in a certain district of Tianjin as the research subject using the convenient cluster sampling method. Among these students, 13374 accepted and completed the survey, with an effective rate of 94.2%.The demographic data and basic information of adolescents, such as height and weight, were collected through a general situation questionnaire. The sleep rhythm of adolescents was evaluated using the reduced version of the morningness-eveningness questionnaire. RESULTS: A total of 13374 participants (6629 females, accounting for 49.56%; the average age is 15.21 ± 1.433 years) were analyzed. Among them, the survey showed that 2942 adolescent were obesity, accounting for 22% and 2104 adolescent were overweight, accounting for 15.7%. Among them, 1692 male adolescents are obese, with an obesity rate of 25.1%, higher than 18.9% of female adolescents. There is a statistically significant difference between the three groups (χ2 = 231.522, P < 0.000). The obesity group has the smallest age (14.94 ± 1.442 years), and there is a statistical difference in age among the three groups (F = 69.996, P < 0.000).Obesity rates are higher among individuals who are not-only-child, have residential experience within six months, have family economic poverty, and have evening-type sleep (P < 0.05). Logistic regression analysis shows a correlation between sleep rhythm and adolescent obesity. Evening-type sleep rhythm can increase the risk of obesity in male adolescents [1.250 (1.067-1.468)], but the effect on female obesity is not remarkable. Further logistic regression analysis in the overall population demonstrates that the interaction between evening-type sleep rhythm and the male gender poses a risk of adolescent obesity [1.122 (1.043-1.208)]. CONCLUSION: Among adolescents, the incidence of obesity in males is higher than in females. Evening-type sleep rhythm plays an important role in male obesity but has no significant effect on female obesity. Progressive analysis suggests an interactive effect of sleep rhythm and gender on adolescent obesity, and the combination of evening-type sleep and the male gender promotes the development of adolescent obesity. In formulating precautions against adolescent obesity, obesity in male adolescents with evening-type sleep should be a critical concern.

Exploration of street space architectural color measurement based on street view big data and deep learning-A case study of Jiefang North Road Street in Tianjin.

Urban space architectural color is the first feature to be perceived in a complex vision beyond shape, texture and material, and plays an important role in the expression of urban territory, humanity and style. However, because of the difficulty of color measurement, the study of architectural color in street space has been difficult to achieve large-scale and fine development. The measurement of architectural color in urban space has received attention from many disciplines. With the development and promotion of information technology, the maturity of street view big data and deep learning technology has provided ideas for the research of street architectural color measurement. Based on this background, this study explores a highly efficient and large-scale method for determining architectural colors in urban space based on deep learning technology and street view big data, with street space architectural colors as the research object. We conducted empirical research in Jiefang North Road, Tianjin. We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. Based on K-Means clustering model, we identified the colors of the architectural elements in the street view. The accuracy of the building color measurement results was cross-sectionally verified by means of a questionnaire survey. The validation results show that the method is feasible for the study of architectural colors in street space. Finally, the overall coordination, sequence continuity, and primary and secondary hierarchy of architectural colors of Jiefang North Road in Tianjin were analyzed. The results show that the measurement model can realize the intuitive expression of architectural color information, and also can assist designers in the analysis of architectural color in street space with the guidance of color characteristics. The method helps managers, planners and even the general public to summarize the characteristics of color and dig out problems, and is of great significance in the assessment and transformation of the color quality of the street space environment.

Targeted Protein Degradation Mediated by Genetically Engineered Lysosome-Targeting Exosomes.

Protein-degrading chimeras are superior drug modalities compared to traditional protein inhibitors because of their effective therapeutic performance. So far, various targeted protein degradation strategies, including proteolysis-targeting chimeras and lysosome-targeting chimeras, have emerged as essential technologies for tackling diseases caused by abnormal protein expression. Here, we report the development and application of lysosome-targeting exosomes (LYTEXs) for the selective degradation of membrane protein targets. LYTEXs are genetically engineered exosomes expressing multivalent single-chain fragment variables, simultaneously recognizing cell-surface lysosome-targeting and to-be-degraded protein. We show that by targeting the lysosome-directing asialoglycoprotein receptor, bispecific LYTEXs can induce lysosomal degradation of membrane-associated therapeutic targets. This strategy provides a generalizable, easy-to-prepare platform for modulating surface protein expression, with the advantage of therapeutic delivery.

Dexmedetomidine against intestinal ischemia/reperfusion injury: A systematic review and meta-analysis of preclinical studies.

BACKGROUND: Intestinal ischemia/reperfusion injury (IRI) is a multifactorial, complex pathophysiological process in clinical settings. In recent years, intestinal IRI has received increasing attention due to increased morbidity and mortality. To date, there are no effective treatments. Dexmedetomidine (DEX), a highly selective α2-adrenergic receptor agonist, has been demonstrated to be effective against intestinal IRI. In this systematic review and meta-analysis, we evaluated the efficacy and potential mechanisms of DEX as a treatment for intestinal IRI in animal models. METHODS: Five databases (PubMed, Embase, Web of Science, Cochrane Library, and Scopus) were searched until March 15, 2023. Using the SYRCLE risk bias tool, we assessed methodological quality. Statistical analysis was conducted using STATA 12 and R 4.2.2. We analyzed the related outcomes (mucosa damage-related indicators; inflammation-relevant markers, oxidative stress markers) relied on the fixed or random-effects models. RESULTS: There were 15 articles including 18 studies included, and 309 animals were involved in the studies. Compared to the model groups, DEX improved intestinal IRI. DEX decreased Chiu's score and serum diamine oxidase (DAO) level. DEX reduced the level of inflammation-relevant markers (interleukin (IL)-1ß, IL-6, tumor necrosis factor (TNF)-α). DEX also improved oxidative stress (decreased malondialdehyde (MDA), increased superoxide dismutase (SOD)). CONCLUSIONS: DEX's effectiveness in ameliorating intestinal IRI has been demonstrated in animal models. Antioxidation, anti-inflammation, anti-apoptotic, anti-pyroptosis, anti-ferroptosis, enhancing mitophagy, reshaping the gut microbiota, and gut barrier protection are possible mechanisms. However, in light of the heterogeneity and methodological quality of these studies, further well-designed preclinical studies are warranted before clinical implication.

Who can help me? Understanding the antecedent and consequence of medical information seeking behavior in the era of bigdata.

Introduction: The advent of bigdata era fundamentally transformed the nature of medical information seeking and the traditional binary medical relationship. Weaving stress coping theory and information processing theory, we developed an integrative perspective on information seeking behavior and explored the antecedent and consequence of such behavior. Methods: Data were collected from 573 women suffering from infertility who was seeking assisted reproductive technology treatment in China. We used AMOS 22.0 and the PROCESS macro in SPSS 25.0 software to test our model. Results: Our findings demonstrated that patients' satisfaction with information received from the physicians negatively predicted their behavior involvement in information seeking, such behavior positively related to their perceived information overload, and the latter negatively related to patient-physician relationship quality. Further findings showed that medical information seeking behavior and perceived information overload would serially mediate the impacts of satisfaction with information received from physicians on patient-physician relationship quality. Discussion: This study extends knowledge of information seeking behavior by proposing an integrative model and expands the application of stress coping theory and information processing theory. Additionally, it provides valuable implications for patients, physicians and public health information service providers.

PSGL-1 is an evolutionarily conserved antiviral restriction factor.

IMPORTANCE: Studying the co-evolution between viruses and humans is important for understanding why we are what we are now as well as for developing future antiviral drugs. Here we pinned down an evolutionary arms race between retroviruses and mammalian hosts at the molecular level by identifying the antagonism between a host antiviral restriction factor PSGL-1 and viral accessory proteins. We show that this antagonism is conserved from mouse to human and from mouse retrovirus to HIV. Further studying this antagonism might provide opportunities for developing new antiviral therapies.

Ultra-Processed Food as Mediator of the Association between Birthweight and Childhood Body Weight Outcomes: A Retrospective Cohort Study.

Previous studies have shown conflicting findings regarding the association between birthweight and childhood adiposity. We aimed to explore the interaction between ultra-processed food (UPF) and birthweight and its associations with bodyweight markers. The retrospective analysis of data from a Multicity Cohort Study across eastern China was conducted. UPF was computed as percentage of the energy intake and categorized into quartiles. Birthweight was categorized into low (LBW), normal (NBW) and high (HBW). The BMI z-score was calculated using the lambda-mu-sigma method. The sex- and age-specific BMI cutoff points were used to define weight status. Generalized linear models were used to examine modification effects and were performed after adjustment for covariates. The mean percentage of energy intake from UPF was 27.7% among 1370 children. Of all children, 2.3% and 21.4% were born with LBW and HBW, respectively. HBW was a permanent risk for high BMI measures, while LBW was associated with increased BMI measurements only by the addition of the interaction term. The subgroup analysis revealed that HBW and LBW were positively associated with BMI measurements in the lowest UPF intake (Q1), while HBW was related to high BMI measures in Q4. Our findings support efforts to recommend limiting UPF intake, especially for LBW children.

The machine learning methods to analyze the using strategy of antiplatelet drugs in ischaemic stroke patients with gastrointestinal haemorrhage.

BACKGROUND: For ischaemic stroke patients with gastrointestinal haemorrhage, stopping antiplatelet drugs or reducing the dose of antiplatelet drugs was a conventional clinical therapy method. But not a study to prove which way was better. And the machinery learning methods could help to obtain which way more suit for some patients. METHODS: Data from consecutive ischaemic stroke patients with gastrointestinal haemorrhage were prospectively collected. The outcome was a recurrent stroke rate, haemorrhage events, mortality and favourable functional outcome (FFO). We analysed the data using conventional logistic regression methods and a supervised machine learning model. We used unsupervised machine learning to group and analyse data characters. RESULTS: The patients of stopping antiplatelet drugs had a lower rate of bleeding events (p = 0.125), mortality (p = 0.008), rate of recurrence of stroke (p = 0.161) and distribution of severe patients (mRS 3-6) (p = 0.056). For Logistic regression, stopping antiplatelet drugs (OR = 2.826, p = 0.030) was related to lower mortality. The stopping antiplatelet drugs in the supervised machine learning model related to mortality (AUC = 0.95) and FFO (AUC = 0.82). For group by unsupervised machine learning, the patients of better prognosis had more male (p < 0.001), younger (p < 0.001), had lower NIHSS score (p < 0.001); and had a higher value of serum lipid level (p < 0.001). CONCLUSIONS: For ischemic stroke patients with gastrointestinal haemorrhage, stopping antiplatelet drugs had a better prognosis. Patients who were younger, male, with lesser NIHSS scores at admission, with the fewest history of a medical, higher value of diastolic blood pressure, platelet, blood lipid and lower INR could have a better prognosis.

Preparation of Biomass Biochar with Components of Similar Proportions and Its Methylene Blue Adsorption.

Rapeseed straw, bagasse, and walnut peel have a large amount of resource reserves, but there are few technologies for high value-added utilization. In the research of biochar, walnut green husk is rarely used as raw material. In addition, the three main components of biomass (lignin, cellulose, and hemicellulose) are present in similar proportions, and the differences between the physical and chemical properties of biochar prepared with similar amounts of biomass raw materials are not clear. Using three kinds of biomass of the same quality as raw materials, biochar was prepared via pyrolysis at 400 °C, and activated carbon was prepared via CO2 activation at 800 °C. The results showed that the pore numbers of the three kinds of biochar increased after activation, resulting in the increase of the specific surface area. The resulting numbers were 352.99 m2/g for sugarcane bagasse biochar (SBB)-CO2, 215.04 m2/g for rapeseed straw biochar (RSB)-CO2, and 15.53 m2/g for walnut green husk biochar (WGB)-CO2. Ash increased the amount of carbon formation, but a large amount of ash caused biochar to form a perforated structure and decreased the specific surface area (e.g., WGB), which affected adsorption ability. When the three main components were present in similar proportions, a high content of cellulose and lignin was beneficial to the preparation of biochar. The adsorption value of MB by biochar decreased with the increase of biomass ash content. After activation, the maximum adsorption value of MB for bagasse biochar was 178.17 mg/g, rapeseed straw biochar was 119.25 mg/g, and walnut peel biochar was 85.92 mg/g when the concentration of methene blue solution was 300 mg/L and the biochar input was 0.1 g/100 mL at room temperature. The adsorption of MB by biochar in solution occurs simultaneously with physical adsorption and chemical adsorption, with chemical adsorption being dominant. The optimal MB adsorption by SBB-CO2 was dominated by multimolecular-layer adsorption. This experiment provides a theoretical basis for the preparation of biochar and research on its applications in the future.

Is epinephrine still the drug of choice during cardiac arrest in the emergency department of the hospital? A meta-analysis.

Epinephrine is the first-line emergency drug for cardiac arrest and anaphylactic reactions but is reported to be associated with many challenges resulting in its under- or improper utilization. Therefore, in this meta-analysis, the efficacy and safety of epinephrine as a first-line cardiac emergency drug for both out-of-hospital and in-hospital patients was assessed. Pertinent articles were searched in central databases like PubMed, Scopus, and Web of Science, using appropriate keywords as per the PRISMA guidelines. Retrospective and prospective studies were included according to the predefined PICOS criteria. RevMan and MedCalc software were used and statistical parameters such as odds ratio and risk ratio were calculated. Twelve clinical trials with a total of 208,690 cardiac arrest patients from 2000 to 2022 were included, in accordance with the chosen inclusion criteria. In the present meta-analysis, a high odds ratio (OR) value of 3.67 (95 % CI 2.32-5.81) with a tau2 value of 0.64, a chi2 value of 12,446.86, df value of 11, I2 value of 100 %, Z-value 5.53, and a p-value < 0.00001 were reported. Similarly, the risk ratio of 1.89 (95 % CI 1.47-2.43) with a tau2 value of 0.19, chi2 value of 11,530.67, df value of 11, I2 value of 100 %, Z-value of 4.95, and p-value < 0.000001. The present meta-analysis strongly prefers epinephrine injection as the first cardiac emergency drug for both out-of-hospital and in-hospital patients during cardiac arrest.

A target-based discovery from a parasitic helminth as a novel therapeutic approach for autoimmune diseases.

BACKGROUND: Regulatory T cells (Tregs) can alleviate the development of autoimmune and inflammatory diseases, thereby proposing their role as a new therapeutic strategy. Parasitic helminths have co-evolved with hosts to generate immunological privilege and immune tolerance through inducing Tregs. Thus, constructing a "Tregs-induction"-based discovery pipeline from parasitic helminth is a promising strategy to control autoimmune and inflammatory diseases. METHODS: The gel filtration chromatography and reverse-phase high-performance liquid chromatography (RP-HPLC) were used to isolate immunomodulatory components from the egg extracts of Schistosoma japonicum. The extracted peptides were evaluated for their effects on Tregs suppressive functions using flow cytometry, ELISA and T cell suppression assay. Finally, we carried out colitis and psoriasis models to evaluate the function of Tregs induced by helminth-derived peptide in vivo. FINDINGS: Here, based on target-driven discovery strategy, we successfully identified a small 3 kDa peptide (SjDX5-53) from egg extracts of schistosome, which promoted both human and murine Tregs production. SjDX5-53 presented immunosuppressive function by arresting dendritic cells (DCs) at an immature state and augmenting the proportion and suppressive capacity of Tregs. In mouse models, SjDX5-53 protected mice against autoimmune-related colitis and psoriasis through inducing Tregs and inhibiting inflammatory T-helper (Th) 1 and Th17 responses. INTERPRETATION: SjDX5-53 exhibited the promising therapeutic effects in alleviating the phenotype of immune-related colitis and psoriasis. This study displayed a screening and validation pipeline of the inducer of Tregs from helminth eggs, highlighting the discovery of new biologics inspired by co-evolution of hosts and their parasites. FUNDING: This study was supported by the Natural Science Foundation of China (82272368) and Natural Science Foundation of Jiangsu Province (BK20211586).

Astragalus membranaceus as a Drug Candidate for Inflammatory Bowel Disease: The Preclinical Evidence.

Inflammatory bowel disease (IBD) is a group of chronic inflammatory disorders that include Crohn's disease (CD) and ulcerative colitis (UC). Today, IBD has no successful treatment. As a result, it is of paramount importance to develop novel therapeutic agents for IBD prevention and treatment. Astragalus membranaceus (AMS) is a traditional Chinese medicine found in the AMS root. Modern pharmacological studies indicate that AMS and its constituents exhibit multiple bioactivities, such as anti-inflammatory, anti-oxidant, immune regulatory, anticancer, hypolipidemic, hypoglycemic, hepatoprotective, expectorant, and diuretic effects. AMS and its active constituents, which have been reported to be effective in IBD treatment, are believed to be viable candidate drugs for IBD treatment. These underlying mechanisms are associated with anti-inflammation, anti-oxidation, immunomodulation, intestinal epithelial repair, gut microbiota homeostasis, and improved energy metabolism. In this review, we summarize the efficacy and underlying mechanisms involved in IBD treatment with AMS and its active constituents in preclinical studies.

An AIE-Active NIR Fluorescent Probe with Good Water Solubility for the Detection of Aß1-42 Aggregates in Alzheimer's Disease.

Alzheimer's disease (AD), an amyloid-related disease, seriously endangers the health of elderly individuals. According to current research, its main pathogenic factor is the amyloid protein, which is a kind of fibrillar aggregate formed by noncovalent self-assembly of proteins. Based on the characteristics of aggregation-induced emission (AIE), a bislactosyl-decorated tetraphenylethylene (TPE) molecule TMNL (TPE + malononitrile + lactose), bearing two malononitrile substituents, was designed and synthesized in this work. The amphiphilic TMNL could self-assemble into fluorescent organic nanoparticles (FONs) with near-infrared (NIR) fluorescence emission in physiological PBS (phosphate buffered saline), achieving excellent fluorescent enhancement (47-fold) upon its combination with Aß1-42 fibrils. TMNL was successfully applied to image Aß1-42 plaques in the brain tissue of AD transgenic mice, and due to the AIE properties of TMNL, no additional rinsing process was necessary. It is believed that the probe reported in this work should be useful for the sensitive detection and accurate localization mapping of Aß1-42 aggregates related to Alzheimer's disease.

Multiplex CRISPR editing of wood for sustainable fiber production.

The domestication of forest trees for a more sustainable fiber bioeconomy has long been hindered by the complexity and plasticity of lignin, a biopolymer in wood that is recalcitrant to chemical and enzymatic degradation. Here, we show that multiplex CRISPR editing enables precise woody feedstock design for combinatorial improvement of lignin composition and wood properties. By assessing every possible combination of 69,123 multigenic editing strategies for 21 lignin biosynthesis genes, we deduced seven different genome editing strategies targeting the concurrent alteration of up to six genes and produced 174 edited poplar variants. CRISPR editing increased the wood carbohydrate-to-lignin ratio up to 228% that of wild type, leading to more-efficient fiber pulping. The edited wood alleviates a major fiber-production bottleneck regardless of changes in tree growth rate and could bring unprecedented operational efficiencies, bioeconomic opportunities, and environmental benefits.