I n situ tumor vaccine with optimized nanoadjuvants and lymph node targeting capacity to treat ovarian cancer and metastases.

Tumor vaccine, a promising modality of tumor immunotherapy, needs to go through the process of tumor antigen generation and loading, antigen drainage to lymph nodes (LNs), antigen internalization by dendritic cells (DCs), DC maturation, and antigen cross-presentation to activate T-cells. However, tumor vaccines are often unable to satisfy all the steps, leading to the limitation of their application and efficacy. Herein, based on a smart nanogel system, an in situ nano-vaccine (CpG@Man-P/Tra/Gel) targeting LNs was constructed to induce potent anti-tumor immune effects and inhibit the recurrence and metastasis of ovarian cancer. The CpG@Man-P/Tra/Gel exhibited MMP-2-sensitive release of trametinib (Tra) and nano-adjuvant CPG@Man-P, which generated abundant in situ depot of whole-cell tumor antigens and formed in situ nano-vaccines with CpG@Man-P. Benefiting from mannose (Man) modification, the nano-vaccines targeted to LNs, promoted the uptake of antigens by DCs, further inducing the maturation of DCs and activation of T cells. Moreover, CpG@Man-P with different particle sizes were prepared and the effective size was selected to evaluate the antitumor effect and immune response in vivo. Notably, combined with PD-1 blocking, the vaccine effectively inhibited primary tumor growth and induced tumor-specific immune response against tumor recurrence and metastasis of ovarian cancer.

Association of mid-pregnancy ferritin levels with postpartum glucose metabolism in women with gestational diabetes.

BACKGROUND: Ferritin, a key indicator of body iron levels, has been reported to associate with type 2 diabetes (T2DM) and the onset of Gestational diabetes mellitus (GDM). However, limited research explores the association between mid-pregnancy ferritin levels and the risk of postpartum abnormal glucose metabolism (AGM) in patients with GDM. METHODS: A retrospective cohort study was conducted in 1514 women with GDM recruited from January 2016 to January 2021, and 916 women were included. Demographic characteristics, medical history and family history, pregnancy complications were recorded. Multiple logistic regression models were performed to assess the association between mid-pregnancy ferritin levels and the risk of postpartum AGM. RESULTS: Following the postpartum oral glucose tolerance test, 307 (33.5%) exhibited AGM. The AGM group had higher mid-pregnancy serum ferritin levels [AGM vs NGT: 23 (11.7, 69) µg/L vs 17.80 (9.85, 40.7) µg/L, P < 0.001] and had a larger proportion of women with ferritin levels ≥30 µg/L (AGM vs NGT: 43.6% vs 31.4%, P < 0.001). Logistic regression analysis demonstrated that women with ferritin levels≥ 30 µg/L had a 1.566 times higher risk of developing postpartum AGM. CONCLUSIONS: These findings indicate that elevated mid-pregnancy ferritin levels are significantly and independently associated with increased postpartum AGM risk in women with previous GDM. Consequently, cautious consideration is necessary for prescribing iron supplements in prenatal care, particularly for non-anemic women with GDM at high risk of developing diabetes after delivery.

The bifunctional impact of polylactic acid microplastics on composting processes and soil-plant systems: Dynamics of microbial communities and ecological niche competition.

Although extensive research has been conducted on the environmental impact of microplastics (MPs), their effects on microorganisms during the composting process and on the compost-soil system remain unclear. Our research investigates the microbial response to polylactic acid microplastics (PLAMPs) during aerobic composting and examines how compost enriched with PLAMPs affects plants. Our findings reveal that PLAMPs play a dual role in the composting process, influencing microorganisms differently depending on the composting phase. PLAMPs reduce the relative abundance of sensitive bacterial ASVs, specifically those belonging to Limnochordaceae and Enterobacteriaceae, during composting, while increasing the relative abundance of ASVs belonging to Steroidobacteriaceae and Bacillaceae. The impact of PLAMPs on microbial community assembly and niche width was found to be phase-dependent. In the stabilization phase (S5), the presence of PLAMPs caused a shift in the core microbial network from bacterial dominance to fungal dominance, accompanied by heightened microbial antagonism. Additionally, these intricate microbial interactions can be transferred to the soil ecosystem. Our study indicates that composting, as a method of managing PLAMPs, is also influenced by PLAMPs. This influence is transferred to the soil through the use of compost, resulting in severe oxidative stress in plants. Our research is pivotal for devising future strategies for PLAMPs management and predicting the subsequent changes in compost quality and environmental equilibrium.

Sliding Ferroelectricity Induced Ultrafast Switchable Photovoltaic Response in ε-InSe Layers.

2D sliding ferroelectric semiconductors have greatly expanded the ferroelectrics family with the flexibility of bandgap and material properties, which hold great promise for ultrathin device applications that combine ferroelectrics with optoelectronics. Besides the induced different resistance states for non-volatile memories, the switchable ferroelectric polarizations can also modulate the photogenerated carriers for potentially ultrafast optoelectronic devices. Here, it is demonstrated that the room temperature sliding ferroelectricity can be used for ultrafast switchable photovoltaic response in ε-InSe layers. By first-principles calculations and experimental characterizations, it is revealed that the ferroelectricity with out-of-plane (OOP) polarization only exists in even layer ε-InSe. The ferroelectricity is also demonstrated in ε-InSe-based vertical devices, which exhibit high on-off ratios (≈104) and non-volatile storage capabilities. Moreover, the OOP ferroelectricity enables an ultrafast (≈3 ps) bulk photovoltaic response in the near-infrared band, rendering it a promising material for self-powered reconfigurable and ultrafast photodetector. This work reveals the essential role of ferroelectric polarization on the photogenerated carrier dynamics and paves the way for hybrid multifunctional ferroelectric and optoelectronic devices.

Decreased complexity of glucose time series index associated with adverse pregnancy outcomes in gestational diabetes mellitus.

AIM: We investigated the relationship between the complexity of the glucose time series index (CGI) during pregnancy and adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM). MATERIALS AND METHODS: In this retrospective cohort study, 388 singleton pregnant women with GDM underwent continuous glucose monitoring (CGM) at a median of 26.86 gestational weeks. CGI was calculated using refined composite multiscale entropy based on CGM data. The participants were categorized into tertiles according to their baseline CGI (CGI <2.32, 2.32-3.10, ≥3.10). Logistic regression was used to assess the association between CGI and composite adverse outcomes or large for gestational age (LGA). The discrimination performance of CGI was estimated using receiver operating characteristic analysis. RESULTS: Of the 388 participants, 71 (18.3%) had LGA infants and 63 (16.2%) had composite adverse outcomes. After adjustments were made for confounders, compared with those with a high CGI (CGI ≥3.10), participants with a low CGI (CGI <2.32) had a higher risk of composite adverse outcomes (odds ratio: 12.10, 95% confidence interval: 4.41-33.18) and LGA (odds ratio: 12.68, 95% confidence interval: 4.04-39.75). According to the receiver operating characteristic analysis, CGI was significantly better than glycated haemoglobin and conventional CGM indicators for the prediction of adverse pregnancy outcomes (all p < .05). CONCLUSION: A lower CGI during pregnancy was associated with composite adverse outcomes and LGA. CGI, a novel glucose homeostasis predictor, seems to be superior to conventional glucose indicators for the prediction of adverse pregnancy outcomes in women with GDM.

Metadata information and fundus image fusion neural network for hyperuricemia classification in diabetes.

OBJECTIVE: In diabetes mellitus patients, hyperuricemia may lead to the development of diabetic complications, including macrovascular and microvascular dysfunction. However, the level of blood uric acid in diabetic patients is obtained by sampling peripheral blood from the patient, which is an invasive procedure and not conducive to routine monitoring. Therefore, we developed deep learning algorithm to detect noninvasively hyperuricemia from retina photographs and metadata of patients with diabetes and evaluated performance in multiethnic populations and different subgroups. MATERIALS AND METHODS: To achieve the task of non-invasive detection of hyperuricemia in diabetic patients, given that blood uric acid metabolism is directly related to estimated glomerular filtration rate(eGFR), we first performed a regression task for eGFR value before the classification task for hyperuricemia and reintroduced the eGFR regression values into the baseline information. We trained 3 deep learning models: (1) metadata model adjusted for sex, age, body mass index, duration of diabetes, HbA1c, systolic blood pressure, diastolic blood pressure; (2) image model based on fundus photographs; (3)hybrid model combining image and metadata model. Data from the Shanghai General Hospital Diabetes Management Center (ShDMC) were used to develop (6091 participants with diabetes) and internally validated (using 5-fold cross-validation) the models. External testing was performed on an independent dataset (UK Biobank dataset) consisting of 9327 participants with diabetes. RESULTS: For the regression task of eGFR, in ShDMC dataset, the coefficient of determination (R2) was 0.684±0.07 (95 % CI) for image model, 0.501±0.04 for metadata model, and 0.727±0.002 for hybrid model. In external UK Biobank dataset, a coefficient of determination (R2) was 0.647±0.06 for image model, 0.627±0.03 for metadata model, and 0.697±0.07 for hybrid model. Our method was demonstrably superior to previous methods. For the classification of hyperuricemia, in ShDMC validation, the area, under the curve (AUC) was 0.86±0.013for image model, 0.86±0.013 for metadata model, and 0.92±0.026 for hybrid model. Estimates with UK biobank were 0.82±0.017 for image model, 0.79±0.024 for metadata model, and 0.89±0.032 for hybrid model. CONCLUSION: There is a potential deep learning algorithm using fundus photographs as a noninvasively screening adjunct for hyperuricemia among individuals with diabetes. Meanwhile, combining patient's metadata enables higher screening accuracy. After applying the visualization tool, it found that the deep learning network for the identification of hyperuricemia mainly focuses on the fundus optic disc region.

A Bayesian Tensor Decomposition Method for Joint Estimation of Channel and Interference Parameters.

Bayesian tensor decomposition has been widely applied in channel parameter estimations, particularly in cases with the presence of interference. However, the types of interference are not considered in Bayesian tensor decomposition, making it difficult to accurately estimate the interference parameters. In this paper, we present a robust tensor variational method using a CANDECOMP/PARAFAC (CP)-based additive interference model for multiple input-multiple output (MIMO) with orthogonal frequency division multiplexing (OFDM) systems. A more realistic interference model compared to traditional colored noise is considered in terms of co-channel interference (CCI) and front-end interference (FEI). In contrast to conventional algorithms that filter out interference, the proposed method jointly estimates the channel and interference parameters in the time-frequency domain. Simulation results validate the correctness of the proposed method by the evidence lower bound (ELBO) and reveal the fact that the proposed method outperforms traditional information-theoretic methods, tensor decomposition models, and robust model based on CP (RCP) in terms of estimation accuracy. Further, the interference parameter estimation technique has profound implications for anti-interference applications and dynamic spectrum allocation.

Effects of biochar and magnesium oxide on cadmium immobilized by microbially induced carbonate: Mobilization or immobilization in alkaline agricultural soils?

Microbially induced carbonate precipitation (MICP) is a promising technique for remediating heavy metal-contaminated soils. However, the effectiveness of MICP in immobilizing Cd in alkaline calcareous soils, especially when applied in agricultural soils, remains unclear. Biochar and magnesium oxide are two environmentally friendly passivating materials, and there are few reports on the combined application of MICP with passivating materials for remediating heavy metal-contaminated soils. Additionally, the number of treatments with MICP cement and the concentration of calcium chloride during the MICP process can both affect the effectiveness of heavy metal immobilization by MICP. Therefore, we conducted MICP and MICP-biochar-magnesium oxide treatments on agricultural soils collected from Baiyin, Gansu Province (pH = 8.62), and analyzed the effects of the number of treatments with cement and the concentration of calcium chloride on the immobilization of Cd by MICP and combined treatments. The results showed that early-stage MICP could immobilize exchangeable cadmium and increase the residual cadmium content, especially with high-concentration calcium chloride MICP treatment. However, in the later stage, soil nitrification and exchange processes led to the dissolution of carbonate-bound cadmium and cadmium activation. The fixing effect of MICP influence whether the MICP-MgO-biochar is superior to the MgO-biochar. Four treatments with cement were more effective than single treatment in MICP-biochar-magnesium oxide treatment, and the MICP-biochar-magnesium oxide treatment with four treatments was the most effective, with passivation rates of 40.7% and 46.6% for exchangeable cadmium and bioavailable cadmium, respectively. However, attention should be paid to the increase in soil salinity. The main mechanism of MICP-magnesium oxide-biochar treatment in immobilizing cadmium was the formation of Cd(OH)2, followed by the formation of cadmium carbonate.

The impact of lipoprotein(a) level on cardiac pathologies in diabetes: a cardiac CT study.

OBJECTIVES: We aimed to explore the imaging profile of coronary atherosclerosis, perivascular inflammation, myocardial perfusion, and interstitial fibrosis in diabetes stratified by lipoprotein(a) [Lp(a)] levels. METHODS: In this prospective study, we enrolled diabetic patients who had undergone computed tomography (CT) angiography, stress CT-myocardial perfusion imaging, and late iodine enhancement in 20 months. Then, we categorized them into elevated and normal groups based on an Lp(a) cutoff level of 30 mg/dL. All imaging data, including coronary atherosclerosis parameters, pericoronary adipose tissue (PCAT) density, stress myocardial blood flow (MBF), and extracellular volume (ECV), were collected for further analysis. RESULTS: In total, 207 participants (mean age: 59.1 ± 12.0 years, 111 males) were included in this study. Patients with elevated Lp(a) level had more pronounced percent atheroma volume (2.55% (1.01-9.01%) versus 1.30% (0-4.95%), p = 0.010), and demonstrated a higher incidence of positive remodeling, spotty calcification, and high-risk plaque (HRP) than those with normal Lp(a) levels (75.6% versus 54.8%, p = 0.015; 26.8% versus 9.6%, p = 0.003; 51.2% versus 30.1%, p = 0.011, respectively). Results of the multivariate analysis revealed that after adjusting for all clinical characteristics, elevated Lp(a) levels were an independent parameter associated with HRP (odds ratio = 2.608; 95% confidence interval: 1.254-5.423, p = 0.010). However, no significant difference was found between the two groups in terms of PCAT density, stress MBF, and ECV. CONCLUSIONS: Elevated Lp(a) levels are associated with extensive coronary atherosclerosis and HRP development. However, they are not related to perivascular inflammation, decreased myocardial perfusion, and interstitial fibrosis in diabetes. CLINICAL RELEVANCE STATEMENT: Elevated lipoprotein(a) levels are associated with extensive coronary atherosclerosis and a high incidence of HRPs. However, they are not related to perivascular inflammation, decreased myocardial perfusion, and interstitial fibrosis in diabetes. KEY POINTS: Diabetes is a known risk factor that accelerates cardiovascular disease progression. Diabetics with elevated lipoprotein(a) (Lp(a)) levels had a higher percent atheroma volume and positive remodeling, spotty calcification, and HRPs. Patients with diabetes should be screened for elevated Lp(a) using CCTA for comprehensive evaluation of atherosclerotic characteristics.

Machine Learning-Based Prediction of Large-for-Gestational Age Infants in Mothers with Gestational Diabetes Mellitus.

CONTEXT: Large-for-gestational-age (LGA), one of the most common complications of gestational diabetes mellitus (GDM), has become a global concern. The predictive performance of common continuous glucose monitoring (CGM) metrics for LGA is limited. OBJECTIVE: We aimed to develop and validate an artificial intelligence (AI) based model to determine the probability of women with GDM giving birth to LGA infants during pregnancy using CGM measurements together with demographic data and metabolic indicators. METHODS: A total of 371 women with GDM from a prospective cohort at a university hospital were included. CGM was performed during 20-34 gestational weeks, and glycemic fluctuations were evaluated and visualized in women with GDM who gave birth to LGA and non-LGA infants. A convolutional neural network (CNN)-based fusion model was developed to predict LGA. Comparisons among the novel fusion model and three conventional models were made using the area under the receiver-operating characteristic curve (AUCROC) and accuracy. RESULTS: Overall, 76 (20.5%) out of 371 GDM women developed LGA neonates. The visualized 24-h glucose profiles differed at midmorning. This difference was consistent among subgroups categorized by pregestational BMI, therapeutic protocol and CGM administration period. The AI based fusion prediction model using 24-h CGM data and 15 clinical variables for LGA prediction (AUCROC 0.852, 95% CI 0.680-0.966, accuracy 84.4%) showed superior discriminative power compared with the three classic models. CONCLUSIONS: We demonstrated better performance in predicting LGA infants among women with GDM using the AI based fusion model. The characteristics of the CGM profiles allowed us to determine the appropriate window for intervention.

Analysis and comparison of blood metabolome of forest musk deer in musk secretion and non-secretion periods.

Musk is an important animal product, but the musk secretion mechanism of forest musk deer (Moschus berezovskii) is still unclear. The musk synthesis process in forest musk deer is extremely complex, and many raw materials are directly or indirectly derived from forest musk deer blood. In this study, metabolomics was used to analyze the blood of forest musk deer in secretory and non-secretory phases for the first time, aim at explaining the secretion mechanism from the perspective of blood metabolism. We found that P450-related, choline-related, axonal regeneration and other pathways and related metabolites were significantly enriched during the musk secretion of forest musk deer. These pathways and metabolites related to P450 and choline in blood may have important implications for the mechanism of musk secretion in forest musk deer, because blood components were closely related to musk components and could provide raw materials for musk synthesis in musk gland cells.

Effectiveness of Psychobiotic Bifidobacterium breve BB05 in Managing Psychosomatic Diarrhea in College Students by Regulating Gut Microbiota: A Randomized, Double-Blind, Placebo-Controlled Trial.

Diarrhea of college students (DCS) is a prevalent issue among college students, affecting their daily lives and academic performance. This study aims to explore the potential effect of Bifidobacterium breve BB05 supplements on the DCS. Initially, fifty healthy and fifty diarrheal students were recruited in the observational experiment and allocated into control and diarrhea groups, respectively. Subsequently, one hundred diarrheal students were newly recruited in the intervention experiment and randomly allocated into placebo and probiotic groups, both treated for 2 weeks. Questionnaires (BSS, HAMA-14, and HDRS-17) were performed to assess the students' diarrheal states and mental health at baseline and post-treatment. Fecal samples underwent 16S rRNA sequencing and Enzyme-Linked Immunosorbent Assay to evaluate gut microbiota and fecal metabolite alternations. Results indicated that B. breve BB05 supplementation significantly enriched (p < 0.05) the reduced gut microbial diversity caused by diarrhea. Diarrhea resulted in notable alterations in gut microbiota composition, as exhibited by elevated Collinsella and Streptococcus, alongside substantially decreased Bifidobacterium, Bacteroides, and Prevotella, while B. breve BB05 supplementation partially restored the compromised gut microbiota at both the phylum and genus levels, particularly by increasing Bifidobacterium and Roseburia (p < 0.05). Importantly, questionnaire results suggested that B. breve BB05 administration achieved superior efficacy in relieving diarrhea symptoms and the associated anxiety and depression in college students. An increased fecal concentration of 5-hydroxytryptamine (5-HT) was also observed in the probiotic group, while Acetylcholine (ACH), Epinephrine (EPI), and Noradrenaline/Norepinephrine (NANE) reduced, revealing the potential of B. breve BB05 in alleviating anxiety and depression via modulating the microbiota-gut-brain axis. Furthermore, correlation analysis suggested that the altered microbiota and fecal neurotransmitters were closely associated with the mental symptoms. These results endorse B. breve BB05 intervention as a promising and innovative approach to alleviate both diarrhea and mental health conditions among college students.

Updated fiducial distribution of parameters in the associated delta-lognormal population.

In this paper we consider a special kind of semicontinous distribution. We try to concern with the situation where the probability of zero observation is associated with the location and scale parameters in lognormal distribution. We first propose a goodness-of-fit test to ensure that the data can be fit by the associated delta-lognormal distribution. Then we define the updated fiducial distributions of the parameters and establish the results that the confidence interval has asymtotically correct level while the significance level of the hypothesis testing is also asymtotically correct. We propose an exact sampling method to sample from the updated fiducial distribution. It can be seen in our simulation study that the inference on the parameters is largely improved. A real data example is also used to illustrate our method.

Dual polarization-enabled ultrafast bulk photovoltaic response in van der Waals heterostructures.

The bulk photovoltaic effect (BPVE) originating from spontaneous charge polarizations can reach high conversion efficiency exceeding the Shockley-Queisser limit. Emerging van der Waals (vdW) heterostructures provide the ideal platform for BPVE due to interfacial interactions naturally breaking the crystal symmetries of the individual constituents and thus inducing charge polarizations. Here, we show an approach to obtain ultrafast BPVE by taking advantage of dual interfacial polarizations in vdW heterostructures. While the in-plane polarization gives rise to the BPVE in the overlayer, the charge carrier transfer assisted by the out-of-plane polarization further accelerates the interlayer electronic transport and enhances the BPVE. We illustrate the concept in MoS2/black phosphorus heterostructures, where the experimentally observed intrinsic BPVE response time achieves 26 ps, orders of magnitude faster than that of conventional non-centrosymmetric materials. Moreover, the heterostructure device possesses an extrinsic response time of approximately 2.2 ns and a bulk photovoltaic coefficient of 0.6 V-1, which is among the highest values for vdW BPV devices reported so far. Our study thus points to an effective way of designing ultrafast BPVE for high-speed photodetection.

Comparative Analysis of Human-Chimpanzee Divergence in Brain Connectivity and its Genetic Correlates.

Chimpanzees (Pan troglodytes) are humans' closest living relatives, making them the most directly relevant comparison point for understanding human brain evolution. Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occured along the human lineage. However, conducting comparisons of brain connectivity between humans and chimpanzees remains challenging, as cross-species brain atlases established within the same framework are currently lacking. Without the availability of cross-species brain atlases, the region-wise connectivity patterns between humans and chimpanzees cannot be directly compared. To address this gap, we built the first Chimpanzee Brainnetome Atlas (ChimpBNA) by following a well-established connectivity-based parcellation framework. Leveraging this new resource, we found substantial divergence in connectivity patterns across most association cortices, notably in the lateral temporal and dorsolateral prefrontal cortex between the two species. Intriguingly, these patterns significantly deviate from the patterns of cortical expansion observed in humans compared to chimpanzees. Additionally, we identified regions displaying connectional asymmetries that differed between species, likely resulting from evolutionary divergence. Genes associated with these divergent connectivities were found to be enriched in cell types crucial for cortical projection circuits and synapse formation. These genes exhibited more pronounced differences in expression patterns in regions with higher connectivity divergence, suggesting a potential foundation for brain connectivity evolution. Therefore, our study not only provides a fine-scale brain atlas of chimpanzees but also highlights the connectivity divergence between humans and chimpanzees in a more rigorous and comparative manner and suggests potential genetic correlates for the observed divergence in brain connectivity patterns between the two species. This can help us better understand the origins and development of uniquely human cognitive capabilities.

Simultaneous application of oral and intravaginal probiotics for Helicobacter pylori and its antibiotic-therapy-induced vaginal dysbacteriosis.

Helicobacter pylori is a prevalent bacterial pathogen globally, implicated in various gastrointestinal disorders. Current recommended antibiotic therapies for H. pylori infection have been proven to be therapeutically insufficient, with low eradication rates and high recurrence rates. Emerging evidence suggests that antibiotic therapy for H. pylori can lead to gastrointestinal and subsequent vaginal dysbiosis, posing challenges for conventional antibiotic approaches. Thus, this article proposes a novel probiotic therapy involving simultaneous oral and intra-vaginal probiotic administration alongside antibiotics for H. pylori treatment, aiming to enhance eradication rates and mitigate dysbiosis. We begin by providing an overview of gastrointestinal and vaginal microbiota and their interconnectedness through the vagina-gut axis. We then review the efficacy of current antibiotic regimens for H. pylori and discuss how antibiotic treatment impacts the vaginal microenvironment. To explore the feasibility of this approach, we evaluate the effectiveness of oral and intra-vaginal probiotics in restoring normal microbiota in the gastrointestinal and vaginal tracts, respectively. Additionally, we analyze the direct mechanisms by which oral and intra-vaginal probiotics act on their respective tracts and discuss potential cross-tract mechanisms. Considering the potential synergistic therapeutic effects of probiotics in both the gastrointestinal and vaginal tracts, dual-channel probiotic therapy holds promise as a more effective approach for H. pylori eradication and dysbiosis mitigation, presenting a novel concept in the collaborative treatment of gastrointestinal and genital disorders.

Polydopamine modified multifunctional carboxymethyl chitosan/pectin hydrogel loaded with recombinant human epidermal growth factor for diabetic wound healing.

The development of a multifunctional wound dressing that can adapt to the shape of wounds and provide controlled drug release is crucial for diabetic patients. This study developed a carboxymethyl chitosan-based hydrogel dressing with enhanced mechanical properties and tissue adherence that were achieved by incorporating pectin (PE) and polydopamine (PDA) and loading the hydrogel with recombinant human epidermal growth factor (rhEGF). This EGF@PDA-CMCS-PE hydrogel demonstrated robust tissue adhesion, enhanced mechanical properties, and superior water retention and vapor permeability. It also exhibited significant antioxidant capacity. The results showed that EGF@PDA-CMCS-PE could effectively scavenge 2,2'-Azinobis-(3-ethylbenzthiazoline-6-sulphonate)， (1,1-diphenyl-2-picrylhydrazyl), and superoxide anions and increase superoxide dismutase and catalase levels in vivo. In vitro cytotoxicity and antibacterial assays showed good biocompatibility and antimicrobial properties. The sustained release of EGF by the hydrogel was confirmed, with a gradual release profile over 120 h. In vivo studies in diabetic mice showed that the hydrogel significantly accelerated wound healing, with a wound contraction rate of 97.84% by day 14. Histopathological analysis revealed that the hydrogel promoted fibroblast proliferation, neovascularization, and orderly connective tissue formation, leading to a more uniform and compact wound-healing process. Thus, EGF@PDA-CMCS-PE hydrogel presents a promising tool for managing chronic diabetic wounds, offering a valuable strategy for future clinical applications.

Soil microorganisms play an important role in the detrimental impact of biodegradable microplastics on plants.

Biodegradable plastics were developed to mitigate environmental pollution caused by conventional plastics. Research indicates that biodegradable microplastics still have effects on plants and microorganisms as their non-biodegradable counterparts, yet the effects on vegetable crops are not well-documented. Additionally, the function of soil microorganisms affected by biodegradable microplastics on the fate of microplastics remains unverified. In this study, Brassica chinensis was cultivated in soil previously incubated for one year with low-density polyethylene (LDPE-MPs) and poly (butylene adipate-co-terephthalate) microplastics (PBAT-MPs) at 0.05 % and 2 % concentrations. High concentrations of PBAT-MPs significantly reduced the biomass to 5.83 % of the control. The abundance of Methyloversatilis, IS-44, and UTCFX1 in the rhizosphere bacterial community increased significantly in the presence of PBAT-MPs. Moreover, these microplastics significantly enhanced soil enzyme activity. Incubation tests were performed with three PBAT plastic sheets to assess the function of the altered bacterial community in the soil of control (Control-soil) and soil treated with high concentrations of PBAT-MPs (PBAT-MPs-soil). Scanning Electron Microscopy and Atomic Transfer Microscopy (SEM/ATM) results confirmed enhanced PBAT degradation in the PBAT-MPs-soil. PICRUST2 analysis revealed that pathways related to substance degradation were upregulated in the PBAT-MPs-soil. Furthermore, a higher percentage of strains with PBAT-MPs-degrading ability was found in PBAT-MPs-soil. Our results confirm that PBAT-MPs significantly inhibit the growth of vegetable crops and that soil bacterial communities affected by PBAT-MPs are instrumental in degrading them.

Nanoscale zero-valent iron reverses resistance of Pseudomonas aeruginosa to chloramphenicol.

Zero-valent iron (ZVI) has been extensively studied for its capacity to remove various contaminants in the environments. However, whether ZVI affects bacterial resistance to antibiotics has not been fully explored. Herein, it was unexpected that, compared with microscale ZVI (mZVI), nanoscale ZVI (nZVI) facilitated the susceptibility of Pseudomonas aeruginosa (P. aeruginosa) to chloramphenicol (CAP), with a decrease in the minimal inhibitory concentration (MIC) of about 60 %, demonstrating a nanosize-specific effect. nZVI enhanced CAP accumulation in P. aeruginosa via inhibitory effect on efflux pumps activated by MexT, thus conferring the susceptibility of P. aeruginosa to CAP. Circular dichroism spectroscopy revealed that the structure of MexT was changed during the evolution. More importantly, molecular dynamic simulations uncovered that, once the structure of MexT changed, it would be more likely to interact with nZVI, resulting in more serious changes in its secondary structure, which was consistent with the increasing susceptibility of P. aeruginosa to CAP. Collectively, this study elucidated the size-specific effect and the underlying mechanism of ZVI on the bacterial evolution of susceptibility toward antibiotics, highlighting the potentials of nZVI-based technologies on the prevention of bacterial resistance to antibiotics, one of the most important issue for globally public health.