Ruptured giant omphalocele with congenital short small intestine: a case report.

We herein present a case of a ruptured giant omphalocele with congenital short small intestine. Vacuum-sealing drainage and carboxymethylcellulose silver dressing promoted wound healing after repair, avoided abdominal compartment syndrome, and reduced the risks of multiple procedures. We review the perioperative management of omphaloceles in congenital short small intestines.

Nrf2 Signaling Pathway: Focus on Oxidative Stress in Spinal Cord Injury.

Spinal cord injury (SCI) is a serious, disabling injury to the central nervous system that can lead to motor, sensory, and autonomic dysfunction below the injury plane. SCI can be divided into primary injury and secondary injury according to its pathophysiological process. Primary injury is irreversible in most cases, while secondary injury is a dynamic regulatory process. Secondary injury involves a series of pathological events, such as ischemia, oxidative stress, inflammatory events, apoptotic pathways, and motor dysfunction. Among them, oxidative stress is an important pathological event of secondary injury. Oxidative stress causes a series of destructive events such as lipid peroxidation, DNA damage, inflammation, and cell death, which further worsens the microenvironment of the injured site and leads to neurological dysfunction. The nuclear factor erythrocyte 2-associated factor 2 (Nrf2) is considered to be a key pathway of antioxidative stress and is closely related to the pathological process of SCI. Activation of this pathway can effectively inhibit the oxidative stress process and promote the recovery of nerve function after SCI. Therefore, the Nrf2 pathway may be a potential therapeutic target for SCI. This review deeply analyzed the generation of oxidative stress in SCI, the role and mechanism of Nrf2 as the main regulator of antioxidant stress in SCI, and the influence of cross-talk between Nrf2 and related pathways that may be involved in the pathological regulation of SCI on oxidative stress, and summarized the drugs and other treatment methods based on Nrf2 pathway regulation. The objective of this paper is to provide evidence for the role of Nrf2 activation in SCI and to highlight the important role of Nrf2 in alleviating SCI by elucidating the mechanism, so as to provide a theoretical basis for targeting Nrf2 pathway as a therapy for SCI.

Profiles, drivers, and prioritization of antibiotics in China's major rivers.

Through a systematic review of literature references from 2007 to 2022, we compiled a comprehensive national dataset comprising over 67,000 records and covering information on 129 antibiotics detected in the surface water and sediments of China's major rivers. Our analysis revealed notably high antibiotic concentrations in the Liaohe and Yellow Rivers. Among the antibiotics examined, sulfonamides, quinolones, and tetracyclines exhibited relatively high median concentrations in river water. Regional distribution analysis highlighted increased antibiotic levels in Shandong and Tianjin compared to other areas. Partial least squares path modeling revealed that animal production and pollution discharge positively influenced antibiotic levels in river water, whereas natural and socioeconomic factors had negative impacts. Based on the ecological risk assessment, we formulated a prioritized national list of antibiotics, with sulfonamides having the largest number of entries, followed by quinolones. Importantly, our analysis revealed a declining trend in antibiotic concentrations and the associated risk levels across China during the study period. This study not only enhances our understanding of antibiotic distribution in China's water systems, but also contributes to the development of a scientifically sound approach for prioritizing antibiotics. Ultimately, these findings will inform targeted antibiotic management and control strategies. ENVIRONMENTAL IMPLICATION: Antibiotics, posing threats to ecosystems and human health, exhibit pseudo-persistence in the environment. we compiled a national dataset of over 67,000 records on antibiotics, our study scrutinized antibiotic distribution in China's major river water and sediment. Through this analysis, we identified key factors influencing distribution patterns and crafted a national priority ranking for antibiotics. These findings deepen our understanding of antibiotic presence and contribute to the development of targeted management strategies aimed at minimizing environmental impact.

Elevation of IL-8 secretion induced by PEDV infection via NF-κB signaling pathway.

Porcine epidemic diarrhea virus (PEDV) is associated with severe enteritis, which contributes to high mortality in piglets. The aim of this study was to describe molecular mechanisms associated with proinflammatory cytokine(s) production during PEDV infection. We showed that infection of porcine intestine epithelial cell clone J2 (IPEC-J2) with PEDV induces a gradual increase in interleukin 8 (IL-8) production at different time points, as well as infection of Vero E6 with PEDV. The secretion of IL-8 in these two cell lines infected with PEDV is related to the activation of NF-κB. Furthermore, the cells expressing PEDV M or E protein can induce the upregulation of IL-8. These findings suggest that the IL-8 production can be the initiator of inflammatory response by the host cells upon PEDV infection.

Efficacy and safety of multikinase inhibitors for patients with refractory thyroid cancer: Systematic review and network meta-analysis.

CONTEXT: Multikinase inhibitors (MKIs) improve the treatment of refractory thyroid cancer, included radioactive iodine-refractory differentiated thyroid cancer (RAIR-DTC) and advanced medullary thyroid carcinoma (aMTC). OBJECTIVE: This study aims to compare the efficacy of MKIs in improving survival outcomes and safety. DATA SOURCES: Comprehensive database searches of MEDLINE via PubMed, EMBASE and Cochrane performed from inception to December 2023. STUDY SELECTION: Three independent authors selected these studies. Randomised-controlled trials that compared the use of a MKI to other MKIs or placebo were included. DATA EXTRACTION AND SYNTHESIS: This review followed PRISMA guidelines. Risk of bias was analyzed using the Cochrane RoB 2 tool. Bayesian network meta-analysis was performed. Treatments were grouped into common nodes based on the type of MKI. MAIN OUTCOMES AND MEASURES: Primary outcomes were progression-free survival (PFS) and overall survival (OS). Secondary outcomes included objective response rate, disease control rate, clinical benefit rate, and adverse events. RESULTS: Cabozantinib 60 mg/d (CAB60) was associated with the highest prolonged PFS in RAIR-DTC patients, followed by lentivatinib 18 or 24 mg/d (LEN18 or LEN24), and apatinib. PFS was also improved in in aMTC patients received CAB 140 mg/d (CAB140), CAB60, or anlotinib. A significantly greater improvement on the performance of OS was seen in CAB60, LEN24, anlotinib, and sorafenib in RAIR-DTC patients, but which in aMTC patients were lack of statistical differences. Compared with the low-dose of MKIs, high-dose of MKIs such as CAB, LEN, and vandetanib increased the incidence of adverse events. CONCLUSION: CAB60, LEN, and apatinib are promising topical MKIs with statistically significant primary outcomes in RAIR-DTC patients, while CAB and anlotinib are effective in prolonging PFS in aMTC patients.

The crosstalk between copper-induced oxidative stress and cuproptosis: a novel potential anticancer paradigm.

Copper is a crucial trace element that plays a role in various pathophysiological processes in the human body. Copper also acts as a transition metal involved in redox reactions, contributing to the generation of reactive oxygen species (ROS). Under prolonged and increased ROS levels, oxidative stress occurs, which has been implicated in different types of regulated cell death. The recent discovery of cuproptosis, a copper-dependent regulated cell death pathway that is distinct from other known regulated cell death forms, has raised interest to researchers in the field of cancer therapy. Herein, the present work aims to outline the current understanding of cuproptosis, with an emphasis on its anticancer activities through the interplay with copper-induced oxidative stress, thereby providing new ideas for therapeutic approaches targeting modes of cell death in the future.

Dissecting the Interplay Mechanism among Process Parameters toward the Biofabrication of High-Quality Shapes in Embedded Bioprinting.

Embedded bioprinting overcomes the barriers associated with the conventional extrusion-based bioprinting process as it enables the direct deposition of bioinks in 3D inside a support bath by providing in situ self-support for deposited bioinks during bioprinting to prevent their collapse and deformation. Embedded bioprinting improves the shape quality of bioprinted constructs made up of soft materials and low-viscosity bioinks, leading to a promising strategy for better anatomical mimicry of tissues or organs. Herein, the interplay mechanism among the printing process parameters toward improved shape quality is critically reviewed. The impact of material properties of the support bath and bioink, printing conditions, cross-linking mechanisms, and post-printing treatment methods, on the printing fidelity, stability, and resolution of the structures is meticulously dissected and thoroughly discussed. Further, the potential scope and applications of this technology in the fields of bioprinting and regenerative medicine are presented. Finally, outstanding challenges and opportunities of embedded bioprinting as well as its promise for fabricating functional solid organs in the future are discussed.

Mechanically Stable and Biocompatible Polymer Brush Coated Dental Materials with Lubricious and Antifouling Properties.

Surface modification plays a crucial role in enhancing the functionality of implanted interventional medical devices, offering added advantages to patients, particularly in terms of lubrication and prevention of undesired adsorption of biomolecules and microorganisms, such as proteins and bacteria, on the material surfaces. Utilizing polymer brushes for surface modification is currently a promising approach to maintaining the inherent properties of materials while introducing new functionalities to surfaces. Here, surface-initiated atom transfer radical polymerization (SI-ATRP) technology to effectively graft anionic, cationic, and neutral polymer brushes from a mixed silane initiating layer is employed. The presence of a polymer brush layer significantly enhances the lubrication performance of the substrates and ensures a consistently low coefficient of friction over thousands of friction cycles in aqueous environments. The antimicrobial efficacy of polymer brushes is evaluated against gram-positive Staphylococcus aureus (S. aureus) and gram-negative Escherichia coli (E. coli). It is observed that polym er brushes grafted to diverse substrate surfaces displays notable antibacterial properties, effectively inhibiting bacterial attachment. Furthermore, the polymer brush layer shows favorable biocompatibility and anti-inflammatory characteristics, which shows potential applications in dental materials, and other fields such as catheters and food packaging.

A review of tire wear particles: Occurrence, adverse effects, and control strategies.

Tire wear particles (TWPs), common mixed particulate emerging contaminants in the environment, have global per capita emissions accounting for 0.23-1.9 kg/year, attracting global attention recently due to their wide detection, small size, mobility, and high toxicity. This review focuses on the occurrence characteristics of TWPs in multiple environmental media, adverse effects on organisms, potential toxicity mechanisms, and environmental risk prevention and control strategies of TWPs. The environmental fate of TWPs throughout the entire process is systematically investigated by the bibliometric analysis function of CiteSpace. This review supplements the gap in the joint toxicity and related toxicity mechanisms of TWPs with other environmental pollutants. Based on the risks review of TWPs and their additives, adverse impacts have been found in organisms from aquatic environments, soil, and humans, such as the growth inhibition effect on Chironomus dilutes. A multi-faceted and rationalized prevention and control treatment of "source-process-end" for the whole process can be achieved by regulating the use of studded tires, improving the tire additive formula, growing plants roadside, encouraging micro-degradation, and other methods, which are first reviewed. By addressing the current knowledge gaps and exploring prospects, this study contributes to developing strategies for reducing risks and assessing the fate of TWPs in multiple environmental media.

Effects of environmental concentrations of 6PPD and its quinone metabolite on the growth and reproduction of freshwater cladoceran.

The widespread occurrence and accumulation of N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) and its quinone metabolite, 6PPD quinone (6PPD-Q), have been globally recognized as a critical environmental issue. However, knowledge on the adverse effects of 6PPD and 6PPD-Q on freshwater invertebrates is limited. This study investigated the effects of 6PPD and its oxidative byproduct, 6PPD-Q, on the growth and reproduction of Daphnia pulex. Through 21-day exposure experiments, we measured the uptake of 0.1, 1, and 10 µg/L 6PPD and 6PPD-Q by D. pulex and assessed the effects on growth and fecundity of D. pulex. While 6PPD and 6PPD-Q did not affect the mortality rate of D. pulex, 6PPD-Q exposure inhibited the growth of D. pulex, indicating potential ecological risks. In particular, the reproductive capacity of D. pulex remained unaffected across the tested concentrations of 6PPD and 6PPD-Q, suggesting specific toxicological pathways that warrant further investigation. This study underscored the importance of evaluating the sublethal effects of emerging contaminants such as 6PPD and 6PPD-Q on aquatic invertebrates, and highlighted the need for comprehensive risk assessments to better understand their environmental impacts.

Enhanced Air Quality Prediction Using a Coupled DVMD Informer-CNN-LSTM Model Optimized with Dung Beetle Algorithm.

Accurate prediction of air quality is crucial for assessing the state of the atmospheric environment, especially considering the nonlinearity, volatility, and abrupt changes in air quality data. This paper introduces an air quality index (AQI) prediction model based on the Dung Beetle Algorithm (DBO) aimed at overcoming limitations in traditional prediction models, such as inadequate access to data features, challenges in parameter setting, and accuracy constraints. The proposed model optimizes the parameters of Variational Mode Decomposition (VMD) and integrates the Informer adaptive sequential prediction model with the Convolutional Neural Network-Long Short Term Memory (CNN-LSTM). Initially, the correlation coefficient method is utilized to identify key impact features from multivariate weather and meteorological data. Subsequently, penalty factors and the number of variational modes in the VMD are optimized using DBO. The optimized parameters are utilized to develop a variationally constrained model to decompose the air quality sequence. The data are categorized based on approximate entropy, and high-frequency data are fed into the Informer model, while low-frequency data are fed into the CNN-LSTM model. The predicted values of the subsystems are then combined and reconstructed to obtain the AQI prediction results. Evaluation using actual monitoring data from Beijing demonstrates that the proposed coupling prediction model of the air quality index in this paper is superior to other parameter optimization models. The Mean Absolute Error (MAE) decreases by 13.59%, the Root-Mean-Square Error (RMSE) decreases by 7.04%, and the R-square (R2) increases by 1.39%. This model surpasses 11 other models in terms of lower error rates and enhances prediction accuracy. Compared with the mainstream swarm intelligence optimization algorithm, DBO, as an optimization algorithm, demonstrates higher computational efficiency and is closer to the actual value. The proposed coupling model provides a new method for air quality index prediction.

Antioxidant Activity and the Therapeutic Effect of Sinomenine Hydrochloride-Loaded Liposomes-in-Hydrogel on Atopic Dermatitis.

Sinomenine hydrochloride is an excellent drug with anti-inflammatory, antioxidant, immune-regulatory, and other functions. Atopic dermatitis is an inherited allergic inflammation that causes itchiness, redness, and swelling in the affected area, which can have a significant impact on the life of the patient. There are many therapeutic methods for atopic dermatitis, and sinomenine with immunomodulatory activity might be effective in the treatment of atopic dermatitis. In this study, the atopic dermatitis model was established in experimental mice, and physical experiments were carried out on the mice. In the experiment, sinomenine hydrochloride liposomes-in-hydrogel as a new preparation was selected for delivery. In this case, liposomes were dispersed in the colloidal hydrogel on a mesoscopic scale and could provide specific transfer properties. The results showed that the sinomenine hydrochloride-loaded liposomes-in-hydrogel system could effectively inhibit atopic dermatitis.

Identification of effective diagnostic genes and immune cell infiltration characteristics in small cell lung cancer by integrating bioinformatics analysis and machine learning algorithms.

OBJECTIVES: To identify potential diagnostic markers for small cell lung cancer (SCLC) and investigate the correlation with immune cell infiltration. METHODS: GSE149507 and GSE6044 were used as the training group, while GSE108055 served as validation group A and GSE73160 served as validation group B. Differentially expressed genes (DEGs) were identified and analyzed for functional enrichment. Machine learning (ML) was used to identify candidate diagnostic genes for SCLC. The area under the receiver operating characteristic curves was applied to assess diagnostic efficacy. Immune cell infiltration analyses were carried out. RESULTS: There were 181 DEGs identified. The gene ontology analysis showed that DEGs were enriched in 455 functional annotations, some of which were associated with immunity. The kyoto encyclopedia of genes and genomes analysis revealed that there were 9 signaling pathways enriched. The disease ontology analysis indicated that DEGs were related to 116 diseases. The gene set enrichment analysis results displayed multiple items closely related to immunity. ZWINT and NRCAM were screened using ML and further validated as diagnostic genes. Significant differences were observed in SCLC with normal lung tissue samples among immune cell infiltration characteristics. Strong associations were found between the diagnostic genes and immune cell infiltration. CONCLUSION: This study identified 2 diagnostic genes, ZWINT and NRCAM, that were related to immune cell infiltration by integrating bioinformatics analysis and ML algorithms. These genes could serve as potential diagnostic biomarkers and provide possible molecular targets for immunotherapy in SCLC.

Genome-wide fine-mapping improves identification of causal variants.

Fine-mapping refines genotype-phenotype association signals to identify causal variants underlying complex traits. However, current methods typically focus on individual genomic segments without considering the global genetic architecture. Here, we demonstrate the advantages of performing genome-wide fine-mapping (GWFM) and develop methods to facilitate GWFM. In simulations and real data analyses, GWFM outperforms current methods in error control, mapping power and precision, replication rate, and trans-ancestry phenotype prediction. For 48 well-powered traits in the UK Biobank, we identify causal variants that collectively explain 17% of the SNP-based heritability, and predict that fine-mapping 50% of that would require 2 million samples on average. We pinpoint a known causal variant, as proof-of-principle, at FTO for body mass index, unveil a hidden secondary variant with evolutionary conservation, and identify new missense causal variants for schizophrenia and Crohn's disease. Overall, we analyse 600 complex traits with 13 million SNPs, highlighting the efficacy of GWFM with functional annotations.

Exploring the neurocognitive correlates of suicidal ideation in major depressive disorder: The role of frontoparietal and default mode networks.

Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD), often accompanied by cognitive alterations and emotional dysregulation. However, it is unclear whether cognitive dysfunction in patients with MDD is related to the presence or absence of SI and impaired connectivity within or between large-scale neurocognitive networks. Previous studies have shown that the frontoparietal network (FPN) and default mode network (DMN) are critical for cognitive control and emotional regulation. Participants were 51 MDD patients with suicidal ideation (MDDSI), 52 MDD patients without suicidal ideation (MDDNSI), and 55 healthy controls (HC). Using areas located within FPN and DMN networks as regions of interest (ROIs), we compared the cognitive performance of the three groups and the strength of the resting state functional connections (RSFC) within and between the FPN and DMN networks. Additionally, we examined the correlation between the strength of FC within the FPN and cognitive function in the SI group. Furthermore, network-based statistics (NBS) were used to correct for the strength of FPN and DMN functional connections. The study identified significant cognitive deficits in MDD patients. Reduced strength of FC was observed within the FPN and DMN networks in the SI group compared to the NSI group. In the SI group, the strength of FC within the FPN network was positively correlated with attention/vigilance. These insights underscore the critical roles of the FPN and DMN in the suicidal ideation, shedding light on the cognitively relevant neurobiological characteristics of MDDSI, providing new insights into the neural mechanisms of MDDSI. URL: https://www.chictr.org.cn/bin/project/edit?pid=131537. Registration number: ChiCTR2100049646.

Immuno-inflammatory pathogenesis in ischemic heart disease: perception and knowledge for neutrophil recruitment.

Ischemic heart disease (IHD) can trigger responses from the innate immune system, provoke aseptic inflammatory processes, and result in the recruitment and accumulation of neutrophils. Excessive recruitment of neutrophils is a potential driver of persistent cardiac inflammation. Once recruited, neutrophils are capable of secreting a plethora of inflammatory and chemotactic agents that intensify the inflammatory cascade. Additionally, neutrophils may obstruct microvasculature within the inflamed region, further augmenting myocardial injury in the context of IHD. Immune-related molecules mediate the recruitment process of neutrophils, such as immune receptors and ligands, immune active molecules, and immunocytes. Non-immune-related molecular pathways represented by pro-resolving lipid mediators are also involved in the regulation of NR. Finally, we discuss novel regulating strategies, including targeted intervention, agents, and phytochemical strategies. This review describes in as much detail as possible the upstream molecular mechanism and external intervention strategies for regulating NR, which represents a promising therapeutic avenue for IHD.

Sclerotherapy for the intraoral ranula with bleomycin: technical considerations and preliminary experience.

Ranula is a mucous cyst that occurs in the sublingual gland (SLG) in the floor of the mouth. It can be classified into two types based on origins: One is the the lesser sublingual gland (LSLG) in the anterior segment and the Rivini duct, which is connected to it, and the other is the greater sublingual gland (GSLG) in the posterior segment. Because of the anatomical characteristics, surgical resection of the cysts carries the risk of damaging adjacent tissues and has a high recurrence rate. Intralesional injection of sclerotherapy may be a better alternative treatment. We summarized 65 cases of ranula treated with intralesional injections of bleomycin(BML). According to the origin of the ranula, 60 cases were from the LSLG and the Rivini duct, and 5 cases were from the GSLG. The results showed that 60 cases of ranula from LSLG and Rivini ducts were 100% cured during the follow-up period. The median number of injections for all patients was 1.16. All 5 cases of ranula from the GSLG did not wholly recover. This study confirmed that BLM intralesional injection is a safe and effective treatment modality for cysts from LSLG or the ducts of Rivini rather than GSLG. Therefore, before treatment, it is necessary to determine the type and origin of the cyst by characterizing its morphology to ensure the effectiveness of the treatment.

Enterprise financial sharing and risk identification model combining recurrent neural networks with transformer model supported by blockchain.

The objective of this study is to investigate methodologies concerning enterprise financial sharing and risk identification to mitigate concerns associated with the sharing and safeguarding of financial data. Initially, the analysis examines security vulnerabilities inherent in conventional financial information sharing practices. Subsequently, blockchain technology is introduced to transition various entity nodes within centralized enterprise financial networks into a decentralized blockchain framework, culminating in the formulation of a blockchain-based model for enterprise financial data sharing. Concurrently, the study integrates the Bi-directional Long Short-Term Memory (BiLSTM) algorithm with the transformer model, presenting an enterprise financial risk identification model referred to as the BiLSTM-fused transformer model. This model amalgamates multimodal sequence modeling with comprehensive understanding of both textual and visual data. It stratifies financial values into levels 1 to 5, where level 1 signifies the most favorable financial condition, followed by relatively good (level 2), average (level 3), high risk (level 4), and severe risk (level 5). Subsequent to model construction, experimental analysis is conducted, revealing that, in comparison to the Byzantine Fault Tolerance (BFT) algorithm mechanism, the proposed model achieves a throughput exceeding 80 with a node count of 146. Both data message leakage and average packet loss rates remain below 10 %. Moreover, when juxtaposed with the recurrent neural networks (RNNs) algorithm, this model demonstrates a risk identification accuracy surpassing 94 %, an AUC value exceeding 0.95, and a reduction in the time required for risk identification by approximately 10 s. Consequently, this study facilitates the more precise and efficient identification of potential risks, thereby furnishing crucial support for enterprise risk management and strategic decision-making endeavors.

Identifying drug candidates for pancreatic ductal adenocarcinoma based on integrative multiomics analysis.

Background: Due to a lack of early diagnosis methods and effective drugs, pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis. DNA methylation, transcriptome expression and gene copy number variation (CNV) have critical relationships with development and progression of various diseases. The purpose of the study was to screen reliable early diagnostic biomarkers and potential drugs based on integrative multiomics analysis. Methods: We used methylation, transcriptome and CNV profiles to build a diagnostic model for PDAC. The protein expression of three model-related genes were externally validated using PDAC samples. Then, potential therapeutic drugs for PDAC were identified by interaction information related to existing drugs and genes. Results: Four significant differentially methylated regions (DMRs) were selected from 589 common DMRs to build a high-performance diagnostic model for PDAC. Then, four hub genes, PHF12, FXYD3, PRKCB and ZNF582, were obtained. The external validation results showed that PHF12, FXYD3 and PRKCB protein expression levels were all upregulated in tumor tissues compared with adjacent normal tissues (P<0.05). Promising candidate drugs with activity against PDAC were screened and repurposed through gene expression analysis of online datasets. The five drugs, including topotecan, PD-0325901, panobinostat, paclitaxel and 17-AAG, with the highest activity among 27 PDAC cell lines were filtered. Conclusions: Overall, the diagnostic model built based on four significant DMRs could accurately distinguish tumor and normal tissues. The five drug candidates might be repurposed as promising therapeutics for particular PDAC patients.