Identifying the importance of PCK1 in maintaining ileal epithelial barrier integrity in Crohn's disease.

BACKGROUND: Crohn's disease (CD) is marked by disruption of intestinal epithelial barrier, with unclear underlying molecular mechanisms. This study aimed to investigate key genes regulating the intestinal barrier in CD patients. METHODS: Differential gene expression analysis and gene set enrichment analysis were conducted to identify potential key genes involved in CD within the GEO database. Single-cell RNA sequencing from ileum samples in GSE134809 of 59,831 inflamed and uninflamed cells from 11CD patients and microarray data from ileal tissues in GSE69762 (3 controls and 4CD patients) and GSE75214 (11 controls and 51CD patients) with GSE179285 (49 uninflamed and 33 inflamed from CD patients) as the validation set. Protein-protein interaction and logistic regression analyses identified key downregulated genes in CD. A key gene was then investigated through immunohistochemistry of ileal tissues from 5CD patients and in the Caco-2 cell line with RNA interference and treatment with IFN-γ and TNF-α to stimulate inflammation. RESULTS: Single-cell RNA-seq identified 33 genes and microarray identified 167 genes with significant downregulation in inflamed CD samples. PCK1 was identified and validated as one of the most promising candidate genes. Reduced PCK1 expression was evident in inflamed ileal tissues. In vitro, knockdown of PCK1 resulted in decreased cell viability, increased apoptosis, and reduced nectin-2 production, while combination of IFN-γ and TNF-α significantly reduced PCK1. CONCLUSIONS: PCK1 is downregulated in inflamed ileal tissues of CD patients and may be a key factor in maintaining epithelial integrity during inflammation in Crohn's disease.

Zr(OH)4-Catalyzed Semi-Hydrogenation of Phenylacetylene with Terminal Zr-O-H as Active Site: Inactive for Free Styrene.

In the field of industrial semi-hydrogenation of trace alkynes amidst alkene feedstocks, the pivotal challenge lies in circumventing the hydrogenation of alkenes. Herein, we present Zr(OH)4 as an innovative catalyst for the semi-hydrogenation of phenylacetylene, demonstrating remarkable selectivity towards styrene (>96%), while exhibiting inactivity towards free styrene. Notably, Zr(OH)4 achieves a 95% conversion of quasi-industry 1 mol% phenylacetylene within styrene, with a mere 0.44% styrene loss. Experimental and theoretical results confirm both terminal Zr-O-H and bridge Zr-O-H can dissociate H2, while the terminal Zr-O-H plays a crucial role on activating phenylacetylene through the sequential hydrogenation process of C6H5C≡CH→C6H5C=CH2→C6H5CH=CH2. The high rate of phenylacetylene removal is attributed to its strong adsorption capacity, while Zr(OH)4 has a significantly weaker adsorption capacity for styrene.

Does "National Civilized City" policy mitigate air pollution in China? A spatial Durbin difference-in-differences analysis.

"National Civilized City" (NCC) is regarded as China's highest honorary title and most valuable city brand. To win and maintain the "golden city" title, municipal governments must pay close attention to various key appraisal indicators, mainly environmental ones. In this study we verify whether cities with the title are more likely to mitigate SO2 pollution. We adopt the spatial Durbin difference-in-differences (DID) model and use panel data of 283 Chinese cities from 2003 to 2018 to analyze the local (direct) and spillover effects (indirect) of the NCC policy on SO2 pollution. We find that SO2 pollution in Chinese cities is not randomly distributed in geography, suggesting the existence of spatial spillovers and possible biased estimates. Our study treats the NCC policy as a quasi-experiment and incorporates spatial spillovers of NCC policy into a classical DID model to verify this assumption. Our findings show: (1) The spatial distribution of SO2 pollution represents strong spatial spillovers, with the most highly polluted regions mainly situated in the North China Plain. (2) The Moran's I test results confirms significant spatial autocorrelation. (3) Results of the spatial Durbin DID models reveal that the civilized cities have indeed significantly mitigated SO2 pollution, indicating that cities with the honorary title are acutely aware of the environment in their bid to maintain the golden city brand. As importantly, we notice that the spatial DID term is also significant and negative, implying that neighboring civilized cities have also mitigated their own SO2 pollution. Due to demonstration and competition effects, neighboring cities that won the title ostensibly motivates local officials to adopt stringent policies and measures for lowering SO2 pollution and protecting the environment in competition for the golden title. The spatial autoregressive coefficient was significant and positive, indicating that SO2 pollution of local cities has been deeply affected by neighbors. A series of robustness check tests also confirms our conclusions. Policy recommendations based on the findings for protecting the environment and promoting sustainable development are proposed.

A mix & act liposomes of phospholipase A2-phosphatidylserine for acute brain detoxification by blood‒brain barrier selective-opening.

In the treatment of central nervous system disease, the blood-brain barrier (BBB) is a major obstruction to drug delivery that must be overcome. In this study, we propose a brain-targeted delivery strategy based on selective opening of the BBB. This strategy allows some simple bare nanoparticles to enter the brain when mixed with special opening material; however, the BBB still maintains the ability to completely block molecules from passing through. Based on the screening of BBB opening and matrix delivery materials, we determined that phospholipase A2-catalyzed 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoserine liposomes can efficiently carry drugs into the brain immediately. At an effective dose, this delivery system is safe, especially with its effect on the BBB being reversible. This mix & act delivery system has a simple structure and rapid preparation, making it a strong potential candidate for drug delivery across the BBB.

Wi-CHAR: A WiFi Sensing Approach with Focus on Both Scenes and Restricted Data.

Significant strides have been made in the field of WiFi-based human activity recognition, yet recent wireless sensing methodologies still grapple with the reliance on copious amounts of data. When assessed in unfamiliar domains, the majority of models experience a decline in accuracy. To address this challenge, this study introduces Wi-CHAR, a novel few-shot learning-based cross-domain activity recognition system. Wi-CHAR is meticulously designed to tackle both the intricacies of specific sensing environments and pertinent data-related issues. Initially, Wi-CHAR employs a dynamic selection methodology for sensing devices, tailored to mitigate the diminished sensing capabilities observed in specific regions within a multi-WiFi sensor device ecosystem, thereby augmenting the fidelity of sensing data. Subsequent refinement involves the utilization of the MF-DBSCAN clustering algorithm iteratively, enabling the rectification of anomalies and enhancing the quality of subsequent behavior recognition processes. Furthermore, the Re-PN module is consistently engaged, dynamically adjusting feature prototype weights to facilitate cross-domain activity sensing in scenarios with limited sample data, effectively distinguishing between accurate and noisy data samples, thus streamlining the identification of new users and environments. The experimental results show that the average accuracy is more than 93% (five-shot) in various scenarios. Even in cases where the target domain has fewer data samples, better cross-domain results can be achieved. Notably, evaluation on publicly available datasets, WiAR and Widar 3.0, corroborates Wi-CHAR's robust performance, boasting accuracy rates of 89.7% and 92.5%, respectively. In summary, Wi-CHAR delivers recognition outcomes on par with state-of-the-art methodologies, meticulously tailored to accommodate specific sensing environments and data constraints.

The Failure Mechanism of Micro Thermoelectric Devices under the Action of the Temperature Field.

The micro thermoelectric device (m-TED) boasts features such as adjustable volume, straightforward structure, and precise, rapid temperature control, positioning it as the only current solution for managing the temperature of microelectronic systems. It is extensively utilized in 5G optical modules, laser lidars, and infrared detection. Nevertheless, as the size of the m-TED diminishes, the growing proportion of interface damages the device's operational reliability, constraining the advancement of the m-TED. In this study, we used commercially available bismuth telluride materials to construct the m-TED. The device's reliability was tested under various temperatures: -40, 85, 125, and 150 °C. By deconstructing and analyzing the devices that failed during the tests, we discovered that the primary cause of device failure was the degradation of the solder layer. Moreover, we demonstrated that encapsulating the device with polydimethylsiloxane (PDMS) could effectively delay the deterioration of its performance. This study sparks new insights into the service reliability of m-TEDs and paves the way for further optimizing device interface design and enhancing the device manufacturing process.

Urticaria in infants: A single-institution retrospective study.

Urticaria in infants can cause significant anxiety in parents, especially if a trigger cannot be identified. In a retrospective study of 246 infants seen for urticaria of unknown etiology at Boston Children's Hospital, 88.2% had resolution of urticaria within 6 weeks. The etiology of urticaria was ultimately established in 62.6% (72/115) of acute urticaria and 12.5% (2/16) of chronic urticaria cases with follow-up data. Pediatric healthcare providers can counsel families that while etiology of urticaria is never determined in over 40% of infants, symptoms are most likely to resolve spontaneously.

Development and evaluation of acceptance scale for artificial intelligence in digestive endoscopy by subjects. / å—æ£€è€ å¯¹æ¶ˆåŒ–å† é•œäººå·¥æ™ºèƒ½æŽ¥å—åº¦é‡è¡¨çš„ç¼–åˆ¶åŠè¯„ä»·.

OBJECTIVES: Digestive endoscopy is an important diagnostic and therapeutic tool for digestive system diseases. The artificial intelligence (AI)-assisted system in endoscopy (hereinafter referred to as AI in digestive endoscopy) has broad application prospects in the field of digestive endoscopy. The trust and acceptance of endoscopic subjects are the cornerstone of the research, application, and promotion of AI in digestive endoscopy. Currently, the tools for measuring the acceptance of AI in digestive endoscopy by subjects are limited at home and abroad. This study aims to develop a scale for measuring the acceptance of AI in digestive endoscopy by subjects, then to evaluate its reliability and validity. METHODS: By conducting literature research, an item pool and dimensions were constructed, and a preliminary scale was constructed using Delphi method. Through the first stage of the survey on the subjects, the reliability and validity of the scale were tested, and the revised scale was used for the second stage of survey on the subjects to further verify the structural validity of the scale. RESULTS: The acceptance scale for AI in digestive endoscopy included 11 items in 3 dimensions: accuracy, ethics, benefit and willingness. In the first stage of the survey, 351 valid questionnaires were collected, and the Cronbach's α was 0.864. The correlation coefficient between the total score of the scale and the score of the test item was 0.636, and the Kaiser-Meyer-Olkin (KMO) value in exploratory factor analysis was 0.788. In the second stage of the survey, 335 valid questionnaires were collected, and in confirmatory factor analysis, the χ2/df was 3.774, while the root mean squared error of approximation (RMSEA) was 0.091. CONCLUSIONS: Acceptance scale for AI in digestive endoscopy by subjects developed in this study has good reliability and validity.