Dual-layer probiotic encapsulation using metal phenolic network with gellan gum-tamarind gum coating for colitis treatment.

Probiotic oral therapy has been recognised as an effective treatment for inflammatory bowel disease (IBD). However, the efficacy of probiotics is often diminished due to their limited resistance to harsh gastrointestinal conditions. Therefore, the importance of designing innovative strategies for oral probiotic delivery for the effective treatment of IBD is increasingly recognised. In this study, we present a novel encapsulation strategy of Lactobacillus plantarum (L.P) using the dual-layer system consisting of a tannic acid­calcium network and polysaccharide coating (gellan gum-tamarind gum) named L.P-C/T-G/T. This double-layer encapsulation system not only does not affect the normal proliferation of probiotics and provide protection, but also endows probiotics with more functions. More specifically, the acid resistance ability of the encapsulated probiotics is increased by 10 times, the free radical scavenging rate is enhanced by 5 times, and the intestinal retention time can be prolonged by 6-12 h. In the DSS-induced murine colitis model, it significantly alleviated colon shortening, inhibited ROS overexpression, and promoted the repair and regeneration of the mucus layer. This dual-layer encapsulation approach for a single probiotic demonstrates a significant advancement in probiotic delivery technology, offering hope for a comprehensive approach to the treatment of colitis and potentially other gastrointestinal disorders.

Bcl-xL is translocated to the nucleus via CtBP2 to epigenetically promote metastasis.

Nuclear Bcl-xL is found to promote cancer metastasis independently of its mitochondria-based anti-apoptotic activity. How Bcl-xL is translocated into the nucleus and how nuclear Bcl-xL regulates histone H3 trimethyl Lys4 (H3K4me3) modification have yet to be understood. Here, we report that C-terminal Binding Protein 2 (CtBP2) binds to Bcl-xL via its N-terminus and translocates Bcl-xL into the nucleus. Knockdown of CtBP2 by shRNA decreases the nuclear portion of Bcl-xL and reverses Bcl-xL-induced invasion and metastasis in mouse models. Furthermore, knockout of CtBP2 not only reduces the nuclear portion of Bcl-xL but also suppresses Bcl-xL transcription. The binding between Bcl-xL and CtBP2 is required for their interaction with MLL1, a histone H3K4 methyltransferase. Pharmacologic inhibition of the MLL1 enzymatic activity reverses Bcl-xL-induced H3K4me3 and TGFß mRNA upregulation, as well as invasion. Moreover, the cleavage under targets and release using nuclease (CUT&RUN) assay coupled with next-generation sequencing reveals that H3K4me3 modifications are particularly enriched in the promotor regions of genes encoding TGFß and its signaling pathway members in cancer cells overexpressing Bcl-xL. Altogether, the metastatic function of Bcl-xL is mediated by its interaction with CtBP2 and MLL1 and this study offers new therapeutic strategies to treat Bcl-xL-overexpressing cancer.

Outcomes of pregnancy in Wilson's disease: a population-based study from multiple centres of the Han population in China.

Objectives: Wilson's disease is an autosomal recessive disorder related to copper metabolism which mostly patients occurs in adolescents, fertility has become a problem that WD needs to face. Methods: A 21 years retrospective follow up study was conducted and a total of 220 female patients were included to identify patients with outcomes of pregnancy. Results: Untreated female patients with WD had a spontaneous abortion rate of 44%. During the study period, 146 female patients with WD from multicenter, 75 patients (51.4%) had successful outcomes of pregnancy. Notably, urinary copper levels below 616 µg/24 h were strongly associated with successful pregnancy. The nomogram built on these variables were age, urinary copper, haemoglobin and Child-Pugh classification, internally validated and showed good performance. Conclusion: The spontaneous abortion rate was 44% in untreated females with WD and developed a four-variable risk prediction model to accurately predict the likelihood of a successful pregnancy.

Variation in Root-Associated Microbial Communities among Three Different Plant Species in Natural Desert Ecosystem.

The process and function that underlie the assembly of root-associated microbiomes may be strongly linked to the survival strategy of plants. However, the assembly and functional changes of root-associated microbial communities in different desert plants in natural desert ecosystems are still unclear. Thus, we studied the microbial communities and diversity of root endosphere (RE), rhizosphere soil (RS), and bulk soil (BS) among three representative desert plants (Alhagi sparsifolia, Tamarix ramosissima, and Calligonum caput-medusae) in three Xinjiang desert regions {Taklimakan (CL), Gurbantünggüt (MSW), and Kumtag (TLF)} in China. This study found that the soil properties {electrical conductivity (EC), soil organic carbon (SOC), total nitrogen (TN) and phosphorus (TP), available nitrogen (AN) and phosphorus (AP)} of C. caput-medusae were significantly lower than those of A. sparsifolia and T. ramosissima, while the root nutrients (TN and TP) of A. sparsifolia were significantly higher compared to C. caput-medusae and T. ramosissima. The beta diversity of bacteria and fungi (RE) among the three desert plants was significantly different. The common OTU numbers of bacteria and fungi in three compartments (RE, RS, and BS) of the three desert plants were ranked as RS > BS > RE. The bacterial and fungal (RE) Shannon and Simpson indexes of C. caput-medusae were significantly lower as compared to those of A. sparsifolia and T. ramosissima. Additionally, bacterial and fungal (RE and RS) node numbers and average degree of C. caput-medusae were lower than those found in A. sparsifolia and T. ramosissima. Root and soil nutrients collectively contributed to the composition of root-associated bacterial (RE, 12.4%; RS, 10.6%; BS, 16.6%) and fungal communities (RE, 34.3%; RS, 1.5%; BS, 17.7%). These findings demonstrate variations in the bacterial and fungal populations across different plant species with distinct compartments (RE, RS, and BS) in arid environments. More importantly, the study highlights how much soil and plant nutrients contribute to root-associated microbial communities.

Modulation of Kondo Behavior in a Two-Dimensional Epitaxial Bilayer Bi(111)/Fe3GeTe2 Moiré Heterostructure.

Artificial two-dimensional (2D) moiré superlattices provide a platform for generating exotic quantum matter or phenomena. Here, an epitaxial heterostructure composed of bilayer Bi(111) and an Fe3GeTe2 substrate with a zero-twist angle is acquired by molecular beam epitaxy. Scanning tunneling microscopy and spectroscopy studies reveal the spatially tailored Kondo resonance and interfacial magnetism within this moiré superlattice. Combined with first-principles calculations, it is found that the modulation effect of the moiré superlattice originates from the interfacial orbital hybridization between Bi and Fe atoms. Our work provides a tunable platform for strong electron correlation studies to explore 2D artificial heavy Fermion systems and interface magnetism.

Dynamic Behavior of Above-Room-Temperature Robust Skyrmions in 2D Van der Waals Magnet.

Magnetic skyrmions are swirl-like spin configurations that present topological properties, which have great potential as information carriers for future high-density and low-energy-consumption devices. The optimization of skyrmion-hosting materials that can be integrated with semiconductor-based circuits is the primary challenge for their industrialization. Two-dimensional van der Waals ferromagnets are emerging materials that have excellent carrier mobility and compatibility with integrated circuits, making them an ideal candidate for spintronic devices. Here, we report the realization of skyrmions at above room temperature in the 2D ferromagnet Fe3GaTe2. The thickness tunability of their skyrmion size and the formation of the skyrmion lattice are revealed. Furthermore, we demonstrate that the skyrmions can be moved by a low-density current at room temperature, together with an apparent skyrmion Hall effect, which is consistent with our quantitative micromagnetic simulation. Our work offers a promising 2D material platform for harnessing magnetic skyrmions in practical device applications.

Seasonal Patterns of Injury Characteristics Among Farmers and Ranchers in the U.S. Central States.

OBJECTIVE: In high-risk agricultural environments, tasks, weather, and work conditions vary throughout the year. Also, injuries peak during certain periods. The primary objective of this study was to examine operator- and farm-level characteristics as risk factors for injuries within each of the four seasons. The secondary objective was to examine seasonal differences in the incident location and primary cause of these injuries. METHOD: We analyzed data from the 2018 and 2020 Farm and Ranch Health and Safety Surveys (FRHSS), conducted in seven U.S. states by the Central States Center for Agricultural Safety and Health (CS-CASH), which were collected using a stratified random sampling approach to ensure representativeness. The survey data were merged with operation-level data from the Farm Market iD database. We employed Generalized Estimating Equations (GEE) to examine the association of seasonal injuries with individual and operation-level characteristics. The chi-square test of independence was used to assess the association between injury incident location and season, as well as injury cause and season. Pairwise Z-tests of proportions were conducted to evaluate the differences in the proportions of injuries due to specific combinations of injury location and cause across each pair of seasons. RESULTS: Surveys conducted in 2018 and 2020 yielded a combined response rate of 15.9%, with 5,428 responses and 7,915 unique operators. Of these, 903 operators reported at least one injury during the past 12 months. Seasonally, most injuries occurred in spring (34.2%), followed by summer (24.7%). Male operators had higher injury odds in the spring (adjusted OR = 1.42) and summer (aOR = 2.41). Those managing both a farm and a ranch reported increased injury risks in winter (aOR = 1.73) and spring (aOR = 1.48). Operators in cow-calf operations faced higher springtime injury risks (aOR = 1.45). High stress and exhaustion were consistent risk factors across all seasons. The highest proportion of injury incidents occurred in the farmyard (43.6%), and livestock were the most common cause of injury (24.9%). CONCLUSION: Results highlight the need for season-specific prevention and intervention strategies, considering farmers' and ranchers' risk characteristics, injury locations, and causes. These findings can inform targeted measures for high-risk populations at optimal times and locations.

Unveiling the core functional networks of cognition: An ontology-guided machine learning approach.

Deciphering the functional architecture that underpins diverse cognitive functions is fundamental quest in neuroscience. In this study, we employed an innovative machine learning framework that integrated cognitive ontology with functional connectivity analysis to identify brain networks essential for cognition. We identified a core assembly of functional connectomes, primarily located within the association cortex, which showed superior predictive performance compared to two conventional methods widely employed in previous research across various cognitive domains. Our approach achieved a mean prediction accuracy of 0.13 across 16 cognitive tasks, including working memory, reading comprehension, and sustained attention, outperforming the traditional methods' accuracy of 0.08. In contrast, our method showed limited predictive power for sensory, motor, and emotional functions, with a mean prediction accuracy of 0.03 across 9 relevant tasks, slightly lower than the traditional methods' accuracy of 0.04. These cognitive connectomes were further characterized by distinctive patterns of resting-state functional connectivity, structural connectivity via white matter tracts, and gene expression, highlighting their neurogenetic underpinnings. Our findings reveal a domain-general functional network fingerprint that pivotal to cognition, offering a novel computational approach to explore the neural foundations of cognitive abilities.

ZnO nanoparticles induce melanoma-like lesions via recruiting dermal dendritic cells in barrier-damaged skin in mice.

ZnO nanoparticles (NPs) are used in skin treatments and cosmetics, the toxicity of long-term and continuous exposure to ZnO NPs is unknown. Mice with epidermal barrier dysfunction revealed melanoma-like lesions after continuous exposure to ZnO NPs. However, the effects of metallic NPs on the skin microenvironment and immune system remain poorly understood. Mice with epidermal barrier failure were given continuous exposure to ZnO NPs for 7 weeks. The malignant transformation of melanocytes was induced with ZnO NPs 2.5 µg/ml for 72 h exposure. The supernatant of the culture medium from dendritic cells after being exposed to 10 µg/ml ZnO NPs for 24 h was applied to melanocytes to explore the effect of recruitment of DCs. The expressure of ZnO NPs resulted in a tendency of malignant transformation of melanocytes, the recruitment of DCs induces this process by produce inflammatory factors such as TNF-α. These DC-produced inflammatory factors, which were induced by ZnO NP exposure, increased the production of matrix metalloproteinases in melanocytes and expedited the malignant transformation process. Our findings revealed that the disrupted cutaneous microenvironment by ZnO NPs penetrated directly promoted the malignant transformation of melanocytes, which process also indirectly enhanced by the TNF-αsecreted from the recruited DCs.

Music Therapy and Music Intervention for NSCLC Patients Undergoing PET with Fear of Cancer Recurrence.

Background: Cancer and psychiatric symptoms are associated. Fear of cancer recurrence (FCR) is the most common psychological problem for cancer survivors. Pharmacological interventions can help, but also have major drawbacks. Music therapy and music interventions have been shown to be a safe and practical complementary treatment. Objective: This randomized, controlled trial aimed to investigate the effects of music therapy and music intervention in attenuating non-small cell lung cancer (NSCLC) patients' anxiety related to FCR. Methods: NSCLC patients with FCR were randomly allocated to a music therapy and intervention group (G1) and Control group (G2). Patients' anxiety was measured using the State-Trait Anxiety Inventory scores and heart rates. Primary outcome measure were PET scans. Secondary measures were salivary cortisol, salivary α-amylase levels and heart rate. Findings: Patients in G1 showed higher glucose metabolism of 18F-FDG in the superior frontal gyrus, anterior cingulate, superior temporal gyrus, and parahippocampal gyrus, compared to those in G2 (all P < .001). Heart rates and salivary α-amylase area under the curve (AUC) and relative variation (VAR) in G1 were significantly lower than those in G2 (all P < .05). State-Trait Anxiety Inventory scores and cortisol AUC in G1 were significantly lower than those in G2 (all P < .05). Conclusions: Music therapy and interventions can reduce anxiety and endocrinological responses and change glucose metabolism of 18F-FDG in fear-related brain regions.Trial registration: Registered retrospectively, ISRCTN Registry, www.isrctn.com, ISRCTN23276302Clinical Implications: Cancer treatment centers and physical examination centers should consider providing music therapy and intervention to the appropriate patients as a routine component of a comprehensive clinical care during medical examinations.

Macroscale brain states support the control of semantic cognition.

A crucial aim in neuroscience is to understand how the human brain adapts to varying cognitive demands. This study investigates network reconfiguration during controlled semantic retrieval in differing contexts. We analyze brain responses to two semantic tasks of varying difficulty - global association and feature matching judgments - which are contrasted with non-semantic tasks on the cortical surface and within a whole-brain state space. Demanding semantic association tasks elicit activation in anterior prefrontal and temporal regions, while challenging semantic feature matching and non-semantic tasks predominantly activate posterior regions. Task difficulty also modulates activation along different dimensions of functional organization, suggesting different mechanisms of cognitive control. More demanding semantic association judgments engage cognitive control and default mode networks together, while feature matching and non-semantic tasks are skewed towards cognitive control networks. These findings highlight the brain's dynamic ability to tailor its networks to support diverse neurocognitive states, enriching our understanding of controlled cognition.

Design, synthesis and biological evaluation of a novel PAK1 degrader for the treatment of triple negative breast cancer.

Triple-negative breast cancer is one of the most malignant subtypes in clinical practice, and it is urgent to find new therapies. The p21-activated kinase I (PAK1) has been considered to be an attractive therapeutic target for TNBC. In this study, we designed and synthesized a series of novel PROTAC PAK1 degraders by conjugating VHL or CRBN ligase ligands to PAK1 inhibitors which are connected by alkyl chains or PEG chains. The most promising compound, 19s, can significantly degrade PAK1 protein at concentrations as low as 0.1 µM, and achieves potent anti-proliferative activity with an IC50 value of 1.27 µM in MDA-MB-231 cells. Additionally, 19s exhibits potent anti-migration activity in vitro and induces rapid tumor regression in vivo. Collectively, these findings document that 19s is a potent and novel PAK1 degrader with promising potential for TNBC treatment.

Bombesin protects myocardium against ischemia/reperfusion injury via activation of the Keap1-Nrf2-HO-1 signaling pathway.

AIMS: It has been reported that some peptides released by the gastro-intestinal tract play important roles in the prevention of myocardial ischemia/reperfusion injury (MIRI). Bombesin (BN) is a biologically active peptide released by non-adrenergic non-cholinergic nerves on the gastric antrum mucosa controlled by the vagus nerve. However, there is a lack of reports on the impact of BN on MIRI. This study aimed to explore the influence of BN on MIRI and its underlying mechanism. MATERIALS AND METHODS: MIRI was induced by either 30 min of global ischemia in Langendorff perfused rat hearts, or by ligation of the descending coronary artery for 30 min in anesthetized Spraque-Dawley rats, and both were followed by 120 min reperfusion. Infarct size and left ventricular function were assessed, and lactate dehydrogenase (LDH), superoxide dismutase (SOD), malondialdehyde (MDA), and glutathione (GSH) levels were measured spectrophotometrically, while cardiomyocyte apoptosis was detected by TUNEL assay. The content of BN in plasma was measured with enzyme-linked immunosorbent assays (ELISA). The expression of caspase 3, Kelch-like ECH-associated protein 1 (Keap1), nuclear factor erythroid 2-related factor 2 (Nrf2), and heme oxygenase-1 (HO-1) were quantified. KEY FINDINGS: BN and vagus nerve stimulation improved cardiac contractile function and reduced myocardial infarct size, attenuated oxidative stress damage and myocardial cell apoptosis, increased the expression of Keap1, Nrf2, and HO-1. and these effects were blocked by using a BN receptor antagonist. SIGNIFICANCE: BN provides protection against MIRI, and its underlying mechanism is through activation of the Keap1/Nrf2/HO-1 pathway. This research provides more reliable evidence for the "gut-heart axis dialogue" and explores potential therapeutic approaches for MIRI.

Physical properties and antioxidant activity of curcumin­zinc metal-organic frameworks.

Metal-organic frameworks (MOFs) offer diverse applications in the food industry, facilitating loading, protection, and controlled release of functional ingredients despite encountering loading capacity and functional activity limitations. This study focuses on curcumin­zinc MOFs, harnessing curcumin's renowned health benefits and zinc to enhance pharmacological properties. We evaluated their synthesis efficiency, stability under varying conditions (pH, salt concentration, temperature), loading and antioxidant capacity. The results showed that microwave synthesis yielded MOFs with a 23.2 ± 4.5% yield, stable within pH 4-10, gradually decomposing in PBS. DPPH, ABTS, and H2O2 assays revealed varying free radical scavenging abilities. MOFs disintegrate in either acidic environments or contain H2O2 (at a concentration threshold of 10 µM). Post-disintegration, these MOFs significantly inhibiting the secretion of TNF-α by RAW264.7 cells induced by LPS. These findings highlight the potential of novel curcumin­zinc MOF materials for nutrient delivery, addressing challenges in effectively delivering functional ingredients.

Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT.

BACKGROUND AND PURPOSE: Delayed cerebral ischemia is hard to diagnose early due to gradual, symptomless development. This study aimed to develop an automated model for predicting delayed cerebral ischemia following aneurysmal SAH on NCCT. MATERIALS AND METHODS: This retrospective study included 400 patients with aneurysmal SAH (156 with delayed cerebral ischemia) who underwent NCCT. The study used ATT-Deeplabv3+ for automatically segmenting hemorrhagic regions using semisupervised learning. Principal component analysis was used for reducing the dimensionality of deep learning features extracted from the average pooling layer of ATT-DeepLabv3+. The classification model integrated clinical data, radiomics, and deep learning features to predict delayed cerebral ischemia. Feature selection involved Pearson correlation coefficients, least absolute shrinkage, and selection operator regression. We developed models based on clinical features, clinical-radiomics, and a combination of clinical, radiomics, and deep learning. The study selected logistic regression, Naive Bayes, Adaptive Boosting (AdaBoost), and multilayer perceptron as classifiers. The performance of segmentation and classification models was evaluated on their testing sets using the Dice similarity coefficient for segmentation, and the area under the receiver operating characteristic curve (AUC) and calibration curves for classification. RESULTS: The segmentation process achieved a Dice similarity coefficient of 0.91 and the average time of 0.037 s/image. Seventeen features were selected to calculate the radiomics score. The clinical-radiomics-deep learning model with multilayer perceptron achieved the highest AUC of 0.84 (95% CI, 0.72-0.97), which outperformed the clinical-radiomics model (P = .002) and the clinical features model (P = .001) with multilayer perceptron. The performance of clinical-radiomics-deep learning model using AdaBoost was significantly superior to its clinical-radiomics model (P = .027). The performance of the clinical-radiomics-deep learning model and the clinical-radiomics model with logistic regression notably exceeded that of the model based solely on clinical features (P = .028; P = .046). The AUC of the clinical-radiomics-deep learning model with multilayer perceptron (P < .001) and the clinical-radiomics model with logistic regression (P = .046) were significantly higher than the clinical model with logistic regression. Of all models, the clinical-radiomics-deep learning model with multilayer perceptron showed best calibration. CONCLUSIONS: The proposed 2-stage end-to-end model not only achieves rapid and accurate segmentation but also demonstrates superior diagnostic performance with high AUC values and good calibration in the clinical-radiomics-deep learning model, suggesting its potential to enhance delayed cerebral ischemia detection and treatment strategies.

Localized fine-tuning and clinical evaluation of deep-learning based auto-segmentation (DLAS) model for clinical target volume (CTV) and organs-at-risk (OAR) in rectal cancer radiotherapy.

BACKGROUND AND PURPOSE: Various deep learning auto-segmentation (DLAS) models have been proposed, some of which have been commercialized. However, the issue of performance degradation is notable when pretrained models are deployed in the clinic. This study aims to enhance precision of a popular commercial DLAS product in rectal cancer radiotherapy by localized fine-tuning, addressing challenges in practicality and generalizability in real-world clinical settings. MATERIALS AND METHODS: A total of 120 Stage II/III mid-low rectal cancer patients were retrospectively enrolled and divided into three datasets: training (n = 60), external validation (ExVal, n = 30), and generalizability evaluation (GenEva, n = 30) datasets respectively. The patients in the training and ExVal dataset were acquired on the same CT simulator, while those in GenEva were on a different CT simulator. The commercial DLAS software was first localized fine-tuned (LFT) for clinical target volume (CTV) and organs-at-risk (OAR) using the training data, and then validated on ExVal and GenEva respectively. Performance evaluation involved comparing the LFT model with the vendor-provided pretrained model (VPM) against ground truth contours, using metrics like Dice similarity coefficient (DSC), 95th Hausdorff distance (95HD), sensitivity and specificity. RESULTS: LFT significantly improved CTV delineation accuracy (p < 0.05) with LFT outperforming VPM in target volume, DSC, 95HD and specificity. Both models exhibited adequate accuracy for bladder and femoral heads, and LFT demonstrated significant enhancement in segmenting the more complex small intestine. We did not identify performance degradation when LFT and VPM models were applied in the GenEva dataset. CONCLUSIONS: The necessity and potential benefits of LFT DLAS towards institution-specific model adaption is underscored. The commercial DLAS software exhibits superior accuracy once localized fine-tuned, and is highly robust to imaging equipment changes.

Virtual clinical trial-based study for clinical evaluation of projection-reduced low-dose cone-beam CT for image guided radiotherapy.

Purpose: Repeated cone-beam CT (CBCT) scans for image-guided radiotherapy (IGRT) increase the health risk of radiation-induced malignancies. Patient-enrolled studies to optimize scan protocols are inadequate. We proposed a virtual clinical trial-based approach to evaluate projection-reduced low-dose CBCT for IGRT. Materials and methods: A total of 71 patients were virtually enrolled with 26 head, 23 thorax and 22 pelvis scans. Projection numbers of full-dose CBCT scans were reduced to 1/2, 1/4, and 1/8 of the original to simulate low-dose scans. Contrast-to-noise ratio (CNR) values in fat and muscle were measured in the full-dose and low-dose images. CBCT images were registered to planning CT to derive 6-degree-of-freedom couch shifts. Registration errors were statistically analyzed with the Wilcoxon paired signed-rank test. Results: As projection numbers were reduced, CNR values descended and the magnitude of registration errors increased. The mean CNR values of full-dose and half-dose CBCT were >3.0. For full-dose and low-dose CBCT (i.e. 1/2, 1/4 and 1/8 full-dose), the mean registration errors were< ± 0.4 mm in translational directions (LAT, LNG, VRT) and ±0.2 degree in rotational directions (Pitch, Roll, Yaw); the mean magnitude of registration errors were< 1 mm in translation and< 0.5 degree in rotation. The couch shift differences between full-dose and low-dose CBCT were not statistically significant (p>0.05) in all the directions. Conclusion: The results indicate that while the impact of dose-reduction on CBCT couch shifts is not significant, the impact on CNR values is significant. Further validation on optimizing CBCT imaging dose is required.

Impact of COVID-19 on emotional and behavioral problems among preschool children: a meta-analysis.

The impact of the Coronavirus Disease 2019 (COVID-19) on society is continuous, resulting in negative psychological consequences. Given the vulnerability and sensitivity to the environment among preschool children, their emotional and behavioral problems deserve more attention. The current study aimed to explore the impact of the epidemic on preschool children's mental health by determining the pooled prevalence of emotional and behavioral problems amidst the Coronavirus Disease 2019 pandemic and to reveal potential reasons for variations between studies. Published studies were searched in Embase, PubMed, ProQuest, PsycINFO, Web of Science, CNKI, and Wanfang. Based on the inclusion criteria outlined in this study, a total of 10 studies encompassing 38,059 participants were incorporated. Employing a random-effect model for estimating the prevalence of emotional and behavioral problems, the results revealed a pooled prevalence rate of 24.3% (95% CI, 0.15-0.38; I²=99.9%) among preschool children. This rate surpasses the pre-outbreak prevalence observed in different countries, signifying a detrimental influence of the epidemic on the mental well-being of preschoolers. Therefore, mental health care and recovery are essential for the vulnerable group during and after the public health crisis. Specific emotional and behavioral problems among preschool children are expected to be researched in the future to provide more targeted guidance for intervention.

Stepwise increase of fidaxomicin in an engineered heterologous host Streptomyces albus through multi-level metabolic engineering.

The anti-Clostridium difficile infection (CDI) drug fidaxomicin is a natural polyketide metabolite mainly produced by Micromonosporaceae, such as Actinoplanes deccanensis, Dactylosporangium aurantiacum, and Micromonospora echinospora. In the present study, we employed a stepwise strategy by combining heterologous expression, chassis construction, promoter engineering, activator and transporters overexpression, and optimization of fermentation media for high-level production of fidaxomicin. The maximum yield of 384 mg/L fidaxomicin was achieved with engineered Streptomyces albus D7-VHb in 5 L-tank bioreactor, and it was approximately 15-fold higher than the native strain Actinoplanes deccanensis YP-1 with higher strain stability and growth rate. This study developed an enhanced chassis strain, and for the first time, achieved the heterologous synthesis of fidaxomicin through a combinatorial metabolic engineering strategy.