Characterization of neutralizing chimeric heavy-chain antibodies against tetanus toxin.

Tetanus toxin (TeNT) is one of the most toxic proteins. Neutralizing antibodies against TeNT are effective in prevention and treatment. In this study, 14 anti-tetanus nanobodies were obtained from a phage display nanobody library by immunizing a camel with the C-terminal receptor-binding domain of TeNT (TeNT-Hc) as the antigen. After fusion with the human Fc fragment, 11 chimeric heavy-chain antibodies demonstrated nanomolar binding toward TeNT-Hc. The results of toxin neutralization experiments showed that T83-7, T83-8, and T83-13 completely protected mice against 20 × the median lethal dose (LD50) at a low concentration. The neutralizing potency of T83-7, T83-8, and T83-13 against TeNT is 0.4 IU/mg, 0.4 IU/mg and 0.2 IU/mg, respectively. In the prophylactic setting, we found that 5 mg/kg of T83-13 provided the mice with full protection from tetanus, even when they were injected 14 days before exposure to 20 × LD50 TeNT. T83-7 and T83-8 were less effective, being fully protective only when challenged 7 or 10 days before exposure, respectively. In the therapeutic setting, 12 h after exposure to TeNT, 1 ~ 5 mg/kg of T83-7, and T83-8 could provide complete protection for mice against 5 × LD50 TeNT, while 1 mg/kg T83-13 could provide complete protection 24 h after exposure to 5 × LD50 TeNT. Our results suggested that these antibodies represent prophylactic and therapeutic activities against TeNT in a mouse model. The T83-7, T83-8, and T83-13 could form the basis for the subsequent development of drugs to treat TeNT toxicity.

Control of Fusarium Head Blight of Wheat with Bacillus velezensis E2 and Potential Mechanisms of Action.

Wheat plants are impacted by Fusarium head blight (FHB) infection, which poses a huge threat to wheat growth, development, storage and food safety. In this study, a fungal strain was isolated from diseased wheat plants and identified as Fusarium asiaticum F1, known to be a member of the Fusarium graminearum species complex, agents causally responsible for FHB. In order to control this disease, new alternatives need to be developed for the use of antagonistic bacteria. Bacillus velezensis E2 (B. velezensis E2), isolated from a previous investigation in our laboratory, showed a notable inhibitory effect on F. asiaticum F1 growth and deoxynivalenol (DON) synthesis in grains. The spore germination of F. asiaticum F1 was significantly reduced and the spores showed vesicular structures when treated with B. velezensis E2. Observations using scanning electron microscopy (SEM) showed that the hyphae of F. asiaticum F1 were shrunken and broken when treated with B. velezensis E2. The RNA-seq results of F1 hyphae treated with B. velezensis E2 showed that differentially expressed genes (DEGs), which were involved in multiple metabolic pathways such as toxin synthesis, autophagy process and glycan synthesis, especially the genes associated with DON synthesis, were significantly downregulated. In summary, those results showed that B. velezensis E2 could inhibit F. asiaticum F1 growth and reduce the gene expression of DON synthesis caused by F1. This study provides new insights and antagonistic mechanisms for the biological control of FHB during wheat growth, development and storage.

Prediction of short-term progression of COVID-19 pneumonia based on chest CT artificial intelligence: during the Omicron epidemic.

BACKGROUND AND PURPOSE: The persistent progression of pneumonia is a critical determinant of adverse outcomes in patients afflicted with COVID-19. This study aimed to predict personalized COVID-19 pneumonia progression between the duration of two weeks and 1 month after admission by integrating radiological and clinical features. METHODS: A retrospective analysis, approved by the Institutional Review Board, encompassed patients diagnosed with COVID-19 pneumonia between December 2022 and February 2023. The cohort was divided into training and validation groups in a 7:3 ratio. A trained multi-task U-Net network was deployed to segment COVID-19 pneumonia and lung regions in CT images, from which quantitative features were extracted. The eXtreme Gradient Boosting (XGBoost) algorithm was employed to construct a radiological model. A clinical model was constructed by LASSO method and stepwise regression analysis, followed by the subsequent construction of the combined model. Model performance was assessed using ROC and decision curve analysis (DCA), while Shapley's Additive interpretation (SHAP) illustrated the importance of CT features. RESULTS: A total of 214 patients were recruited in our study. Four clinical characteristics and four CT features were identified as pivotal components for constructing the clinical and radiological models. The final four clinical characteristics were incorporated as well as the RS_radiological model to construct the combined prediction model. SHAP analysis revealed that CT score difference exerted the most significant influence on the predictive performance of the radiological model. The training group's radiological, clinical, and combined models exhibited AUC values of 0.89, 0.72, and 0.92, respectively. Correspondingly, in the validation group, these values were observed to be 0.75, 0.72, and 0.81. The DCA curve showed that the combined model exhibited greater clinical utility than the clinical or radiological models. CONCLUSION: Our novel combined model, fusing quantitative CT features with clinical characteristics, demonstrated effective prediction of COVID-19 pneumonia progression from 2 weeks to 1 month after admission. This comprehensive model can potentially serve as a valuable tool for clinicians to develop personalized treatment strategies and improve patient outcomes.

A review of the pollution signatures of polycyclic aromatic hydrocarbons in the sediments of the East China Sea.

Marine sediments serve as crucial reservoirs for polycyclic aromatic hydrocarbons (PAHs), and their PAH signatures offer valuable historical pollution records. This article provides a comprehensive review of the pollution status of 16 priority PAHs in more than 1000 sediments from the East China Sea (ECS). It focuses on the PAH sources, spatiotemporal distributions, driving factors, and ecological risks, with information derived from peer-reviewed papers published between 2003 and 2023. The results revealed that vehicular emissions, mixed combustion sources of coal, biomass, and coke, as well as petrogenic sources, were the primary contributors to PAH pollution in the ECS sediments, accounting for 50%, 34%, and 16%, respectively. Human activities, hydrodynamic mechanisms, and environmental variables such as particle size and organic matter, collectively influenced the distribution of PAHs. Additionally, the population size and economic development played a key role in the temporal distribution of PAHs in the ECS sediments. The ecotoxicity assessment of PAHs in sediments indicated a low risk level. These outcomes are expected to provide environmentalists with detailed and up-to-date insights into sedimentary PAHs in the ECS, helping to develop suitable monitoring plans and strategies for promoting better management of ECS environment.

Association of body mass index with rapid eye movement sleep behavior disorder in Parkinson's disease.

Background: The association between body mass index (BMI) and rapid eye-movement (REM) sleep-related behavioral disorder (RBD) in Parkinson's disease (PD) remains unknown. Our study was to investigate the association of BMI with RBD in PD patients. Methods: In this cross-sectional study, a total of 1,115 PD participants were enrolled from Parkinson's Progression Markers Initiative (PPMI) database. BMI was calculated as weight divided by height squared. RBD was defined as the RBD questionnaire (RBDSQ) score with the cutoff of 5 or more assessed. Univariable and multivariable logistic regression models were performed to examine the associations between BMI and the prevalence of RBD. Non-linear correlations were explored with use of restricted cubic spline (RCS) analysis. And the inflection point was determined by the two-line piecewise linear models. Results: We identified 426 (38.2%) RBD. The proportion of underweight, normal, overweight and obese was 2.61, 36.59, 40.36, and 20.44%, respectively. In the multivariate logistic regression model with full adjustment for confounding variables, obese individuals had an odds ratio of 1.77 (95% confidence interval: 1.21 to 2.59) with RBD compared with those of normal weight. In the RCS models with three knots, BMI showed a non-linear association with RBD. The turning points of BMI estimated from piecewise linear models were of 28.16 kg/m2, 28.10 kg/m2, and 28.23 kg/m2 derived from univariable and multivariable adjusted logistic regression models. The effect modification by depression on the association between BMI and RBD in PD was also found in this study. Furthermore, the sensitivity analyses linked with cognition, education, and ethnic groups indicated the robustness of our results. Conclusion: The current study found a significant dose-response association between BMI and RBD with a depression-based difference in the impact of BMI on RBD in PD patients.

Predicting lymphovascular invasion in non-small cell lung cancer using deep convolutional neural networks on preoperative chest CT.

RATIONALE AND OBJECTIVES: Lymphovascular invasion (LVI) plays a significant role in precise treatments of non-small cell lung cancer (NSCLC). This study aims to build a non-invasive LVI prediction diagnosis model by combining preoperative CT images with deep learning technology. MATERIALS AND METHODS: This retrospective observational study included a series of consecutive patients who underwent surgical resection for non-small cell lung cancer (NSCLC) and received pathologically confirmed diagnoses. The cohort was randomly divided into a training group comprising 70 % of the patients and a validation group comprising the remaining 30 %. Four distinct deep convolutional neural network (DCNN) prediction models were developed, incorporating different combination of two-dimensional (2D) and three-dimensional (3D) CT imaging features as well as clinical-radiological data. The predictive capabilities of the models were evaluated by receiver operating characteristic curves (AUC) values and confusion matrices. The Delong test was utilized to compare the predictive performance among the different models. RESULTS: A total of 3034 patients with NSCLC were recruited in this study including 106 LVI+ patients. In the validation cohort, the Dual-head Res2Net_3D23F model achieved the highest AUC of 0.869, closely followed by the models of Dual-head Res2Net_3D3F (AUC, 0.868), Dual-head Res2Net_3D (AUC, 0.867), and EfficientNet-B0_2D (AUC, 0.857). There was no significant difference observed in the performance of the EfficientNet-B0_2D model when compared to the Dual-head Res2Net_3D3F and Dual-head Res2Net_3D23F. CONCLUSION: Findings of this study suggest that utilizing deep convolutional neural network is a feasible approach for predicting pathological LVI in patients with NSCLC.

3D embedded bioprinting of large-scale intestine with complex structural organization and blood capillaries.

Accurate reproduction of human intestinal structure and function in vitro is of great significance for understanding the development and disease occurrence of the gut. However, most in vitro studies are often confined to 2D models, 2.5D organ chips or 3D organoids, which cannot fully recapitulate the tissue architecture, microenvironment and cell compartmentalization found in vivo. Herein, a centimeter-scale intestine tissue that contains intestinal features, such as hollow tubular structure, capillaries and tightly connected epithelium with in vivo-like ring folds, crypt-villi, and microvilli is constructed by 3D embedding bioprinting. In our strategy, a novel photocurable bioink composed of methacrylated gelatin, methacrylated sodium alginate and poly (ethylene glycol) diacrylate is developed for the fabrication of intestinal model. The Caco-2 cells implanted in the lumen are induced by the topological structures of the model to derive microvilli, crypt-villi, and tight junctions, simulating the intestinal epithelial barrier. The human umbilical vein endothelial cells encapsulated within the model gradually form microvessels, mimicking the dense capillary network in the intestine. This intestine-like tissue, which closely resembles the structure and cell arrangement of the human gut, can act as a platform to predict the therapeutic and toxic side effects of new drugs on the intestine.

Lactobacillus rhamnosus GG triggers intestinal epithelium injury in zebrafish revealing host dependent beneficial effects.

Lactobacillus rhamnosus GG (LGG), the well-characterized human-derived probiotic strain, possesses excellent properties in the maintenance of intestinal homeostasis, immunoregulation and defense against gastrointestinal pathogens in mammals. Here, we demonstrate that the SpaC pilin of LGG causes intestinal epithelium injury by inducing cell pyroptosis and gut microbial dysbiosis in zebrafish. Dietary SpaC activates Caspase-3-GSDMEa pathways in the intestinal epithelium, promotes intestinal pyroptosis and increases lipopolysaccharide (LPS)-producing gut microbes in zebrafish. The increased LPS subsequently activates Gaspy2-GSDMEb pyroptosis pathway. Further analysis reveals the Caspase-3-GSDMEa pyroptosis is initiated by the species-specific recognition of SpaC by TLR4ba, which accounts for the species-specificity of the SpaC-inducing intestinal pyroptosis in zebrafish. The observed pyroptosis-driven gut injury and microbial dysbiosis by LGG in zebrafish suggest that host-specific beneficial/harmful mechanisms are critical safety issues when applying probiotics derived from other host species and need more attention.

Molecular engineering design of twisted-backbone pure Type-I organic photosensitizers for hypoxic photodynamic therapy.

Photodynamic therapy (PDT), an emerging tumor therapeutic strategy has received tremendous attention. Enslaved by the high dependence of oxygen, Type-II photosensitizers (PSs) mediated PDT is restricted by the hypoxic environment of tumors. By transferring electrons to water or other substrates instead of oxygen, Type-I PSs hold the promise of achieving an ideal therapeutic effect under hypoxic conditions. In this study, three twisted-backbone PSs (CBz-TQs-1, CBz-TQs-2 and CBz-TQs-3) are synthesized and studied. Owing to different substituent effects, the ROS generation mechanism transfers from pure Type-II of their prototype PSs (TQs-1, TQs-2 and TQs-3) to mixed Type-I/II of CBz-TQs-1 and CBz-TQs-2 to pure Type-I of CBz-TQs-3. Moreover, CBz-TQs-3 exhibits an ultra-high ROS quantum yield (∼1.0). The in vitro and in vivo PDT effects of water-dissolvable nanoparticles (NPs) of CBz-TQs-3 are investigated. The results show that the phototoxicity of CBz-TQs-3 is not affected by hypoxic environments. In addition, a remarkable tumor ablation can be found after CBz-TQs-3 NPs mediated PDT on Balb/c mice with xenograft tumors. It proves that a twisted backbone strategy is beneficial for designing pure Type-I PSs with high-efficient hypoxic PDT.

Diabetes mellitus as a risk factor for severe dengue fever and West Nile fever: A meta-analysis.

BACKGROUND: Dengue fever (DF) and West Nile fever (WNF) have become endemic worldwide in the last two decades. Studies suggest that individuals with diabetes mellitus (DM) are at a higher risk of developing severe complications from these diseases. Identifying the factors associated with a severe clinical presentation is crucial, as prompt treatment is essential to prevent complications and fatalities. This article aims to summarize and assess the published evidence regarding the link between DM and the risk of severe clinical manifestations in cases of DF and WNF. METHODOLOGY/PRINCIPAL FINDINGS: A systematic search was conducted using the PubMed and Web of Science databases. 27 studies (19 on DF, 8 on WNF) involving 342,873 laboratory-confirmed patients were included in the analysis. The analysis showed that a diagnosis of DM was associated with an increased risk for severe clinical presentations of both DF (OR 3.39; 95% CI: 2.46, 4.68) and WNF (OR 2.89; 95% CI: 1.89, 4.41). DM also significantly increased the risk of death from both diseases (DF: OR 1.95; 95% CI: 1.09, 3.52; WNF: OR 1.74; 95% CI: 1.40, 2.17). CONCLUSIONS/SIGNIFICANCE: This study provides strong evidence supporting the association between DM and an increased risk of severe clinical manifestations in cases of DF and WNF. Diabetic individuals in DF or WNF endemic areas should be closely monitored when presenting with febrile symptoms due to their higher susceptibility to severe disease. Early detection and appropriate management strategies are crucial in reducing the morbidity and mortality rates associated with DF and WNF in diabetic patients. Tailored care and targeted public health interventions are needed to address this at-risk population. Further research is required to understand the underlying mechanisms and develop effective preventive and therapeutic approaches.

Treg-Derived Extracellular Vesicles: Roles in Diseases and Theranostics.

Regulatory T cells (Tregs), a subset of CD4+ T cells, are indispensable in maintaining immune self-tolerance and have been utilized in various diseases. Treg-derived extracellular vesicles (Treg-EVs) have been discovered to play an important role in the mechanism of Treg functions. As cell-derived membranous particles, EVs carry multiple bioactive substances that possess tremendous potential for theranostics. Treg-EVs are involved in numerous physiological and pathological processes, carrying proteins and miRNAs inherited from the parental cells. To comprehensively understand the function of Treg-EVs, here we reviewed the classification of Treg-EVs, the active molecules in Treg-EVs, their various applications in diseases, and the existing challenges for Treg-EVs based theranostics. This Review aims to clarify the feasibility and potential of Treg-EVs in diseases and theranostics, facilitating further research and application of Treg-EVs.

Seasonal human coronavirus NL63 epidemics in children in Guilin, China, reveal the emergence of a new subgenotype of HCoV-NL63.

Introduction: Seasonal human coronavirus NL63 (HCoV-NL63) is a frequently encountered virus linked to mild upper respiratory infections. However, its potential to cause more severe or widespread disease remains an area of concern. This study aimed to investigate a rare localized epidemic of HCoV-NL63-induced respiratory infections among pediatric patients in Guilin, China, and to understand the viral subtype distribution and genetic characteristics. Methods: In this study, 83 pediatric patients hospitalized with acute respiratory infections and positive for HCoV-NL63 were enrolled. Molecular analysis was conducted to identify the viral subgenotypes and to assess genetic variations in the receptor-binding domain of the spiking protein. Results: Among the 83 HCoV-NL63-positive children, three subgenotypes were identified: C4, C3, and B. Notably, 21 cases exhibited a previously unreported subtype, C4. Analysis of the C4 subtype revealed a unique amino acid mutation (I507L) in the receptor-binding domain of the spiking protein, which was also observed in the previously reported C3 genotype. This mutation may suggest potential increases in viral transmissibility and pathogenicity. Discussion: The findings of this study highlight the rapid mutation dynamics of HCoV-NL63 and its potential for increased virulence and epidemic transmission. The presence of a unique mutation in the C4 subtype, shared with the C3 genotype, raises concerns about the virus's evolving nature and its potential public health implications. This research contributes valuable insights into the understanding of HCoV-NL63's epidemiology and pathogenesis, which is crucial for effective disease prevention and control strategies. Future studies are needed to further investigate the biological significance of the observed mutation and its potential impact on the virus's transmissibility and pathogenicity.

Isolation and characterization of Hc-targeting chimeric heavy chain antibodies neutralizing botulinum neurotoxin type B.

Background: Botulinum neurotoxin (BoNT) produced by Clostridium botulinum is one of the most potent known toxins. Moreover, BoNT is classified as one of the most important biological warfare agents that threatens the biosafety of the world. Currently, the approved treatment for botulism in humans is the use of polyvalent horse serum antitoxins. However, they are greatly limited because of insufficient supply and adverse reactions. Thus, treatment of human botulism requires the development of effective toxin-neutralizing antibodies. Considering their advantages, neutralizing nanobodies will play an increasing role as BoNTs therapeutics. Methods: Herein, neutralizing nanobodies binding to the heavy chain (Hc) domain of BoNT/B (BHc) were screened from a phage display library. Then, BoNT/B-specific clones were identified and fused with the human Fc fragment (hFc) to form chimeric heavy chain antibodies. Finally, the affinity, specificity, and neutralizing activity of antibodies against BoNT/B in vivo were evaluated. Results: The B5-hFc, B9-hFc and B12-hFc antibodies demonstrated high affinity for BHc in the nanomolar range. The three antibodies were proven to have potent neutralizing activity against BoNT/B in vivo. Conclusion: The results demonstrate that inhibiting toxin binding to the host receptor is an efficient strategy and the three antibodies could be used as candidates for the further development of drugs to prevent and treat botulism.

Feasibility and reproducibility of cardiovascular magnetic resonance-feature tracking for quantitative right atrial function in dilated cardiomyopathy patients.

Background: The importance of right heart assessment in dilated cardiomyopathy (DCM) is increasingly recognized. The development of cardiovascular magnetic resonance-feature tracking (CMR-FT) has provided a novel approach to quantify myocardial deformation and evaluate cardiac function. In this study, we aimed to evaluate the feasibility and reproducibility of CMR-FT for the quantitative derivation of right atrial (RA) strain and strain rate (SR) in patients with DCM. Methods: A total of 68 DCM patients (84% male; aged 50.6±13.2 years) and 58 healthy controls (81% male; aged 48.4±11.2 years) were retrospectively enrolled from September 2018 to August 2022 at the First Affiliated Hospital of Zhejiang Chinese Medical University and Shenzhen Clinical Medical College of Guangzhou University of Chinese Medicine. RA reservoir, conduit, and booster strain (εs, εe, and εa) and peak positive, peak early negative, and peak late negative SR (SRs, SRe, and SRa) were measured using CMR-FT and compared between 2 groups using Student's t-test. Intra- and inter-observer reproducibility was evaluated using intraclass correlation coefficients (ICC) and Bland-Altman plots. Results: Compared to healthy controls, DCM patients showed significantly lower RA strain (εs: 19.7%±9.0% vs. 44.4%±9.7%; εe: 7.9%±5.3% vs. 25.8%±8.6%; εa: 11.8%±6.2% vs. 18.6%±5.1%, all P<0.001) and SR (SRs: 1.17±0.48 vs. 1.92±0.62 s-1; SRe: -0.85±0.56 vs. -1.94±0.63 s-1; SRa: -1.39±0.71 vs. -2.01±0.65 s-1, all P<0.001). There was no significant difference in RA maximum volume index between the 2 groups. Simple linear regression analysis demonstrated a significant correlation between N-terminal B-type natriuretic peptide (NT-proBNP), RA emptying fraction passive (RAEF passive), and RA εe [(NT-proBNP and εe): r=-0.48, P<0.001, 95% confidence interval (CI): -0.64 to -0.26; and (RAEF passive and εe): r=0.41, P=0.001, 95% CI: 0.22 to 0.56, respectively] in DCM patients. Intra- and inter-observer reproducibility was excellent (all ICCs >0.85) for RA deformation measurements. Conclusions: CMR-FT is a promising, noninvasive approach for the quantitative assessment of RA phasic function in patients with DCM. DCM patients exhibit impaired RA reservoir, conduit, and booster pump function prior to visible RA enlargement.

Role of microbiota-gut-brain axis in natural aging-related alterations in behavior.

Introduction: Aging is a complex, time-dependent biological process that involves a decline of overall function. Over the past decade, the field of intestinal microbiota associated with aging has received considerable attention. However, there is limited information surrounding microbiota-gut-brain axis (MGBA) to further reveal the mechanism of aging. Methods: In this study, locomotory function and sensory function were evaluated through a series of behavioral tests.Metabolic profiling were determined by using indirect calorimetry.16s rRNA sequence and targeted metabolomics analyses were performed to investigate alterations in the gut microbiota and fecal short-chain fatty acids (SCFAs). The serum cytokines were detected by a multiplex cytokine assay.The expression of proinflammatory factors were detected by western blotting. Results: Decreased locomotor activity, decreased pain sensitivity, and reduced respiratory metabolic profiling were observed in aged mice. High-throughput sequencing revealed that the levels of genus Lactobacillus and Dubosiella were reduced, and the levels of genus Alistipes and Bacteroides were increased in aged mice. Certain bacterial genus were directly associated with the decline of physiological behaviors in aged mice. Furthermore, the amount of fecal SCFAs in aged mice was decreased, accompanied by an upregulation in the circulating pro-inflammatory cytokines and increased expression of inflammatory factors in the brain. Discussion: Aging-induced microbial dysbiosis was closely related with the overall decline in behavior, which may attribute to the changes in metabolic products, e.g., SCFAs, caused by an alteration in the gut microbiota, leading to inflammaging and contributing to neurological deficits. Investigating the MGBA might provide a novel viewpoint to exploring the pathogenesis of aging and expanding appropriate therapeutic targets.

Predictive value of radiomic features extracted from primary lung adenocarcinoma in forecasting thoracic lymph node metastasis: a systematic review and meta-analysis.

BACKGROUND: The application of radiomics in thoracic lymph node metastasis (LNM) of lung adenocarcinoma is increasing, but diagnostic performance of radiomics from primary tumor to predict LNM has not been systematically reviewed. Therefore, this study sought to provide a general overview regarding the methodological quality and diagnostic performance of using radiomic approaches to predict the likelihood of LNM in lung adenocarcinoma. METHODS: Studies were gathered from literature databases such as PubMed, Embase, the Web of Science Core Collection, and the Cochrane library. The Radiomic Quality Score (RQS) and the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) were both used to assess the quality of each study. The pooled sensitivity, specificity, and area under the curve (AUC) of the best radiomics models in the training and validation cohorts were calculated. Subgroup and meta-regression analyses were also conducted. RESULTS: Seventeen studies with 159 to 1202 patients each were enrolled between the years of 2018 to 2022, of which ten studies had sufficient data for the quantitative evaluation. The percentage of RQS was between 11.1% and 44.4% and most of the studies were considered to have a low risk of bias and few applicability concerns in QUADAS-2. Pyradiomics and logistic regression analysis were the most commonly used software and methods for radiomics feature extraction and selection, respectively. In addition, the best prediction models in seventeen studies were mainly based on radiomics features combined with non-radiomics features (semantic features and/or clinical features). The pooled sensitivity, specificity, and AUC of the training cohorts were 0.84 (95% confidence interval (CI) [0.73-0.91]), 0.88 (95% CI [0.81-0.93]), and 0.93(95% CI [0.90-0.95]), respectively. For the validation cohorts, the pooled sensitivity, specificity, and AUC were 0.89 (95% CI [0.82-0.94]), 0.86 (95% CI [0.74-0.93]) and 0.94 (95% CI [0.91-0.96]), respectively. CONCLUSIONS: Radiomic features based on the primary tumor have the potential to predict preoperative LNM of lung adenocarcinoma. However, radiomics workflow needs to be standardized to better promote the applicability of radiomics. TRIAL REGISTRATION: CRD42022375712.

Melatonin promotes hair regeneration by modulating the Wnt/ß-catenin signalling pathway.

Melatonin (MLT) is a circadian hormone that reportedly influences the development and cyclic growth of secondary hair follicles; however, the mechanism of regulation remains unknown. Here, we systematically investigated the role of MLT in hair regeneration using a hair depilation mouse model. We found that MLT supplementation significantly promoted hair regeneration in the hair depilation mouse model, whereas supplementation of MLT receptor antagonist luzindole significantly suppressed hair regeneration. By analysing gene expression dynamics between the MLT group and luzindole-treated groups, we revealed that MLT supplementation significantly up-regulated Wnt/ß-catenin signalling pathway-related genes. In-depth analysis of the expression of key molecules in the Wnt/ß-catenin signalling pathway revealed that MLT up-regulated the Wnt/ß-catenin signalling pathway in dermal papillae (DP), whereas these effects were facilitated through mediating Wnt ligand expression levels in the hair follicle stem cells (HFSCs). Using a DP-HFSCs co-culture system, we verified that MLT activated Wnt/ß-catenin signalling in DPs when co-cultured with HFSCs, whereas supplementation of DP cells with MLT alone failed to activate Wnt/ß-catenin signalling. In summary, our work identified a critical role for MLT in promoting hair regeneration and will have potential implications for future hair loss treatment in humans.

The predictive value of γ-glutamyl transferase to serum albumin ratio in hepatocellular carcinoma patients after liver transplantation.

Background: Elevated preoperative γ-glutamyl transferase (GGT) levels or reduced serum albumin levels have been established as negative prognostic factors for patients with hepatocellular carcinoma (HCC) and various other tumors. Nonetheless, the prognostic significance of the GGT to serum albumin ratio (GAR) in liver transplantation (LT) therapy for HCC is still not well-defined. Methods: A retrospective analysis was conducted on the clinical data of 141 HCC patients who underwent LT at Shulan (Hangzhou) Hospital from June 2017 to November 2020. Using the receiver operating characteristic (ROC) curve, the optimal GAR cutoff value to predict outcomes following LT was assessed. Univariate and multivariate Cox proportional hazards regression analyses were used to identify independent risk factors associated with both overall survival (OS) and recurrence-free survival (RFS). Results: A GAR value of 2.04 was identified as the optimal cutoff for predicting both OS and RFS, with a sensitivity of 63.2% and a specificity of 74.8%. Among these patients, 80 (56.7%) and 90 (63.8%) met the Milan and the University of California San Francisco (UCSF) criteria, respectively. Univariate Cox regression analysis showed that microvascular invasion (MVI), maximum tumor size (>5 cm), total tumor size (>8 cm), liver cirrhosis, TNM stage (III), and GAR (≥2.04) were significantly associated with both postoperative OS and RFS in patients with HCC (all p < 0.05). Multivariate Cox regression analysis indicated that GAR (≥2.04) was independently linked with RFS and OS. Conclusion: Pre-transplant GAR ≥2.04 is an independent correlate of prognosis and survival outcomes after LT for HCC and can be used as a prognostic indicator for both mortality and tumor recurrence following LT.

Deficit Irrigation Effects on Cotton Growth Cycle and Preliminary Optimization of Irrigation Strategies in Arid Environment.

With the changing global climate, drought stress will pose a considerable challenge to the sustainable development of agriculture in arid regions. The objective of this study was to explore the resistance and water demand of cotton plants to water stress during the flowering and boll setting stage. The experimental plot was in Huaxing Farm of Changji city. The plots were irrigated, respectively, at 100% (as the control), 90%, 85% and 80% of the general irrigation amount in the local area. The relationship between the various measured indexes and final yield under different deficit irrigation (DI) treatments was studied. The results showed that deficit irrigation impacted the growth and development processes of cotton during the flowering and boll setting stage. There was a high negative correlation (R2 > 0.95) between the maximum leaf area index and yield. Similarly, there was a high correlation between malondialdehyde content and yield. Meanwhile, 90% of the local cotton irrigation contributed to water saving and even increasing cotton yield. Furthermore, based on the results, the study made an initial optimization to the local irrigation scheme by utilizing the DSSAT model. It was found that changing the irrigation interval to 12 days during the stage could further enhance cotton yield and conserve resources.

Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine.

Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.