UBR5 forms ligand-dependent complexes on chromatin to regulate nuclear hormone receptor stability.

Nuclear hormone receptors (NRs) are ligand-binding transcription factors that are widely targeted therapeutically. Agonist binding triggers NR activation and subsequent degradation by unknown ligand-dependent ubiquitin ligase machinery. NR degradation is critical for therapeutic efficacy in malignancies that are driven by retinoic acid and estrogen receptors. Here, we demonstrate the ubiquitin ligase UBR5 drives degradation of multiple agonist-bound NRs, including the retinoic acid receptor alpha (RARA), retinoid x receptor alpha (RXRA), glucocorticoid, estrogen, liver-X, progesterone, and vitamin D receptors. We present the high-resolution cryo-EMstructure of full-length human UBR5 and a negative stain model representing its interaction with RARA/RXRA. Agonist ligands induce sequential, mutually exclusive recruitment of nuclear coactivators (NCOAs) and UBR5 to chromatin to regulate transcriptional networks. Other pharmacological ligands such as selective estrogen receptor degraders (SERDs) degrade their receptors through differential recruitment of UBR5 or RNF111. We establish the UBR5 transcriptional regulatory hub as a common mediator and regulator of NR-induced transcription.

Publisher Correction: Whole-genome sequencing of a sporadic primary immunodeficiency cohort.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Whole-genome sequencing of a sporadic primary immunodeficiency cohort.

Primary immunodeficiency (PID) is characterized by recurrent and often life-threatening infections, autoimmunity and cancer, and it poses major diagnostic and therapeutic challenges. Although the most severe forms of PID are identified in early childhood, most patients present in adulthood, typically with no apparent family history and a variable clinical phenotype of widespread immune dysregulation: about 25% of patients have autoimmune disease, allergy is prevalent and up to 10% develop lymphoid malignancies1-3. Consequently, in sporadic (or non-familial) PID genetic diagnosis is difficult and the role of genetics is not well defined. Here we address these challenges by performing whole-genome sequencing in a large PID cohort of 1,318 participants. An analysis of the coding regions of the genome in 886 index cases of PID found that disease-causing mutations in known genes that are implicated in monogenic PID occurred in 10.3% of these patients, and a Bayesian approach (BeviMed4) identified multiple new candidate PID-associated genes, including IVNS1ABP. We also examined the noncoding genome, and found deletions in regulatory regions that contribute to disease causation. In addition, we used a genome-wide association study to identify loci that are associated with PID, and found evidence for the colocalization of-and interplay between-novel high-penetrance monogenic variants and common variants (at the PTPN2 and SOCS1 loci). This begins to explain the contribution of common variants to the variable penetrance and phenotypic complexity that are observed in PID. Thus, using a cohort-based whole-genome-sequencing approach in the diagnosis of PID can increase diagnostic yield and further our understanding of the key pathways that influence immune responsiveness in humans.

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.

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.

Homozygous IL37 mutation associated with infantile inflammatory bowel disease.

Interleukin (IL)-37, an antiinflammatory IL-1 family cytokine, is a key suppressor of innate immunity. IL-37 signaling requires the heterodimeric IL-18R1 and IL-1R8 receptor, which is abundantly expressed in the gastrointestinal tract. Here we report a 4-mo-old male from a consanguineous family with a homozygous loss-of-function IL37 mutation. The patient presented with persistent diarrhea and was found to have infantile inflammatory bowel disease (I-IBD). Patient cells showed increased intracellular IL-37 expression and increased proinflammatory cytokine production. In cell lines, mutant IL-37 was not stably expressed or properly secreted and was thus unable to functionally suppress proinflammatory cytokine expression. Furthermore, induced pluripotent stem cell-derived macrophages from the patient revealed an activated macrophage phenotype, which is more prone to lipopolysaccharide and IL-1ß stimulation, resulting in hyperinflammatory tumor necrosis factor production. Insights from this patient will not only shed light on monogenic contributions of I-IBD but may also reveal the significance of the IL-18 and IL-37 axis in colonic homeostasis.

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.

Risk assessment based on dose-responsive and time-responsive genes to build PLS-DA models for exogenously induced lung injury.

Xenobiotics can easily harm human lungs owing to the openness of the respiratory system. Identifying pulmonary toxicity remains challenging owing to several reasons: 1) no biomarkers for pulmonary toxicity are available that might help to detect lung injury; 2) traditional animal experiments are time-consuming; 3) traditional detection methods solely focus on poisoning accidents; 4) analytical chemistry methods hardly achieve universal detection. An in vitro testing system able to identify the pulmonary toxicity of contaminants from food, the environment, and drugs is urgently needed. Compounds are virtually infinite, whereas toxicological mechanisms are countable. Therefore, universal methods to identify and predict the risks of contaminants can be designed based on these well-known toxicity mechanisms. In this study, we established a dataset based on transcriptome sequencing of A549 cells upon treatment with different compounds. The representativeness of our dataset was analyzed using bioinformatics methods. Artificial intelligence methods, namely partial least squares discriminant analysis (PLS-DA) models, were employed for toxicity prediction and toxicant identification. The developed model predicted the pulmonary toxicity of compounds with a 92 % accuracy. These models were submitted to an external validation using highly heterogeneous compounds, which supported the accuracy and robustness of our developed methodology. This assay exhibits universal potential applications for water quality monitoring, crop pollution detection, food and drug safety evaluation, as well as chemical warfare agent detection.

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.

Can visceral adipose tissue and skeletal muscle predict recurrence of newly diagnosed Crohn's disease in different treatments.

BACKGROUND AND AIMS: It is crucial to manage the recurrence of Crohn's disease (CD). This study is aimed to explore whether visceral adipose tissue (VAT) and skeletal muscle (SM) are associated with the recurrence of CD upon different treatments. METHODS: All patients with a definite diagnosis of CD were retrospectively divided into three groups according to distinct treatment regimens: 5-amino salicylic acid group (Group A), steroids + azathioprine (Group B) and biologics (Group C). The pretreatment computerized tomography (CT) images and clinical data were collected. The VAT area, mesenteric fat index (MFI), the ratio of VAT area to fat mass (VAT area/FM) were assessed. The primary end point was the recurrence of CD within 1 year of follow-up. RESULTS: A total of 171 CD patients were enrolled, including 57 (33.33%) patients in Group A, 70 (40.94%) patients in Group B and 44 (25.73%) patients in Group C. Patients with 1-year recurrence had higher MFI (P = 0.011) and VAT area/FM (P = 0.000). ROC curve demonstrated that patients with the ratio of VAT area/FM and MFI higher than 0.578 and 1.394 tended to have recurrence with the AUC of 0.707 and 0.709. Similar results could be observed in Group A & B but not in Group C. CONCLUSIONS: High VAT area/FM and MFI are related to recurrence within 1 year for newly diagnosed CD patients treated by 5-amino salicylic or azathioprine + steroids rather than biologics. We could not observe any radiological data associated with the recurrence of CD patients under biological treatment.

Through-focus EUV multilayer defect compensation considering optical proximity correction.

Extreme ultraviolet (EUV) multilayer defects result in the degradation of through-focus imaging quality. The optical proximity effect is another crucial factor that degrades the imaging quality. Both the impacts of the defects and the optical proximity effects could be mitigated by modifying the original mask patterns. A heuristic-based defect compensation method considering optical proximity correction and through-focus optimization is proposed in this paper. The edge of the mask pattern and the insertion of sub-resolution assist features (SRAFs) are optimized by covariance matrix adaptation evolution strategy (CMA-ES) to compensate for the degradation of the imaging quality with a certain defocus range. New encoding strategies for the edge pixels of the mask pattern and the SRAFs are proposed and utilized in this paper to ensure the manufacturability of the mask and the efficiency of the optimization at the same time. The rigorous database approach based on the scattering matrix is adopted to simulate the mask diffraction spectrum efficiently. Simulations verify that the through-focus imaging quality of both the defective masks with bump defects and pit defects could be obviously improved by the proposed defect compensation method.

Fast heuristic-based source mask optimization for EUV lithography using dual edge evolution and partial sampling.

Extreme ultraviolet (EUV) lithography is essential in the advanced technology nodes. Source mask optimization (SMO) for EUV lithography, especially the heuristic-based SMO, is one of the vital resolution enhancement techniques (RET). In this paper, a fast SMO method for EUV based on dual edge evolution and partial sampling strategies is proposed to improve the optimization efficiency and speed of the heuristic algorithm. In the source optimization (SO) stage, the position and intensity of the source points are optimized in turn. Using the sparsity of the optimized source, a partial sampling encoding method is applied to decrease the variables' dimension in optimization. In the mask optimization (MO) stage, the main features (MF) and the sub-resolution assistant features (SRAF) are optimized in turn. A dual edge evolution strategy is used in the MF optimization and the partial sampling encoding method is used in SRAF optimization. Besides, the imaging qualities at different focal planes are improved by SRAF optimization. The optimization efficiency is greatly improved by the dimensionality reduction strategies. Simulations are carried out with various target patterns. Results show the superiority of the proposed method over the previous method, especially for large complex patterns.

Source mask optimization for extreme-ultraviolet lithography based on thick mask model and social learning particle swarm optimization algorithm.

Extreme ultraviolet (EUV) lithography plays a vital role in the advanced technology nodes of integrated circuits manufacturing. Source mask optimization (SMO) is a critical resolution enhancement technique (RET) or EUV lithography. In this paper, an SMO method for EUV lithography based on the thick mask model and social learning particle swarm optimization (SL-PSO) algorithm is proposed to improve the imaging quality. The thick mask model's parameters are pre-calculated and stored, then SL-PSO is utilized to optimize the source and mask. Rigorous electromagnetic simulation is then carried out to validate the optimization results. Besides, an initialization parameter of the mask optimization (MO) stage is tuned to increase the optimization efficiency and the optimized mask's manufacturability. Optimization is carried out with three target patterns. Results show that the pattern errors (PE) between the print image and target pattern are reduced by 94.7%, 76.9%, 80.6%, respectively.

Fast mask model for extreme ultraviolet lithography with a slanted absorber sidewall.

A fast mask model for extreme ultraviolet (EUV) lithography is vital to process simulation and resolution enhancement techniques. As the target pattern sizes have decreased, the impact of the absorber sidewall angle (SWA) has become a serious problem. In order to model the EUV mask with a slanted absorber sidewall quickly and accurately, a fast mask model based on the absorber sublayer decomposition is proposed. Since the absorber sidewall is slanted but not perpendicular to the multilayer surface, the absorber is decomposed into several thin pattern layers. For each thin layer, the diffraction is calculated by the edge point pulses model. The light propagation between two layers is calculated by spectrum superposition in the frequency domain with Hopkins frequency shift. The fast EUV mask model with slanted absorber sidewall is established by combining the accurate absorber model and the equivalent layer multilayer model. Simulations and comparisons validate the effectiveness of the proposed model. For the 22 nm vertical line-space pattern, the calculation errors of critical dimension via the proposed model are lower than 0.05 nm for different SWA values.

Extreme ultraviolet phase defect characterization based on complex amplitudes of the aerial images.

The profile deformation of a phase defect in an extreme ultraviolet (EUV) mask blank is the key factor to simulate its optical effects accurately and to compensate for it precisely. This paper provides a new, to the best of our knowledge, profile characterization method based on complex amplitudes of the aerial images for phase defects in EUV mask blanks. Fourier ptychography is adopted to retrieve the complex amplitudes of the aerial images and improve the lateral resolution. Both amplitude and phase impacted by the defect are taken into consideration to reconstruct the defect profile parameters (the height and the full width at half maxima of the defect's top and bottom profiles). A conformal convolutional neural network model is constructed to map the amplitudes and phases of aerial images to the defect profile parameters. The Gaussian-shaped defect models with the mapped profile parameters can be used to simulate the amplitude and phase properties of the defects when compensating for them. The proposed method is verified to reconstruct the defect profile parameters of both bump defects and pit defects accurately. The involvement of both the amplitude and phase information makes the reconstructed defect profile parameters more appropriate to simulate the optical effects of the defects.

Pharmacological perturbation of CDK9 using selective CDK9 inhibition or degradation.

Cyclin-dependent kinase 9 (CDK9), an important regulator of transcriptional elongation, is a promising target for cancer therapy, particularly for cancers driven by transcriptional dysregulation. We characterized NVP-2, a selective ATP-competitive CDK9 inhibitor, and THAL-SNS-032, a selective CDK9 degrader consisting of a CDK-binding SNS-032 ligand linked to a thalidomide derivative that binds the E3 ubiquitin ligase Cereblon (CRBN). To our surprise, THAL-SNS-032 induced rapid degradation of CDK9 without affecting the levels of other SNS-032 targets. Moreover, the transcriptional changes elicited by THAL-SNS-032 were more like those caused by NVP-2 than those induced by SNS-032. Notably, compound washout did not significantly reduce levels of THAL-SNS-032-induced apoptosis, suggesting that CDK9 degradation had prolonged cytotoxic effects compared with CDK9 inhibition. Thus, our findings suggest that thalidomide conjugation represents a promising strategy for converting multi-targeted inhibitors into selective degraders and reveal that kinase degradation can induce distinct pharmacological effects compared with inhibition.

Nbr1-regulated autophagy in Lactoferrin-induced osteoblastic differentiation.

The molecular mechanism of autophagy in Lactoferrin (LF) induced osteoblast differentiation is not fully demonstrated. In this study, alkaline phosphatase (ALP) activity, alizarin red S staining and ELISA were used to study N-terminal propeptide of type I procollagen (PINP) expression. mRFP-GFP-LC3 adenoviruses, mono-dansylcadaverine (MDC) staining, scanning electron microscopy, and western blot analysis was employed to probe the LF induced autophagy. The interaction between autophagy receptor Neighbor of Brca1 gene (Nbr1) and pp38 was studied. 3-methyladenine (3-MA) and chloroquine (CQ) could inhibit the activity of ALP, PINP and the autophagy in LF group. LF treatment could up-regulate and down-regulate the expressions of pp38 and Nbr1with a dose-dependent manner, respectively. LF could inhibit the recognition of pp38 and Nbr1. In addition, LF can prompt Nbr1-medicated autophagy and prevent pp38 degradation by autophagy. LF can induce Nbr1-mediated autophagy and inhibit pp38 entering into autophagy flux in the physiological process of osteoblast differentiation.Abbreviations: CQ:chloroquine；LF: Lactoferrin; 3-MA: 3-methyladenine; ALP: Alkaline phosphatase; ANOVA: Analysis of variance; CCK-8: Cell Counting Kit-8; LC3: Microtubule-associated protein light chain3; MDC: Monodansylcadaverine; Nbr1: neighbor of Brca1 gene; PINP: N-terminal propeptide of type I procollagen; PVDF: Polychlorotrifluoroethylene; pp38: phosphorylation p38; RAPA: Rapamycin; SDS: sodium dodecyl sulfate.

Fast rigorous mask model for extreme ultraviolet lithography.

The calculation of extreme ultraviolet (EUV) mask diffraction spectrum is the key of EUV lithography simulation. In this paper, a fast rigorous EUV mask model is proposed to calculate the diffraction spectrum fast and accurately. Based on the mask structure decomposition method, the relationship among the region diffraction, the boundary diffraction of the absorber, and the direction of incident light is analyzed at first. Then the frequency-domain functions related to angle of incidence and diffraction angle are established to model the geometrical and boundary diffraction of the absorber. The fast rigorous EUV mask model is established by combining the equivalent layer multilayer model based on the Fresnel formula and the accurate absorber model. Simulations and comparisons show the effectiveness of the proposed model. For the 14 nm vertical line-space pattern, the calculation errors of critical dimension (CD) via the proposed model are reduced by 80.6% and 93.9% compared with the structure decomposition method for dense and isolate features.

Effects of prescription restrictive interventions on antibiotic procurement in primary care settings: a controlled interrupted time series study in China.

BACKGROUND: The overuse of antibiotics has been identified as a major challenge in regard to the rational prescription of medicines in low and middle income countries. Extensive studies on the effectiveness of persuasive interventions, such as guidelines have been undertaken. There is a dearth of research pertaining to the effects of restrictive interventions. This study aimed to evaluate the impacts of prescription restrictions in relation to types and administration routes of antibiotics on antibiotic procurement in primary care settings in China. METHODS: Data were drawn from the monthly procurement records of medicines for primary care institutions in Hubei province over a 31-month period from May 2011 to November 2013. We analyzed the monthly procurement volume and costs of antibiotics. Interrupted time series analyses with a difference-in-difference approach were performed to evaluate the effect of the restrictive intervention (started in August 2012) on antibiotic procurement in comparison with those for cardiovascular conditions. Sensitivity tests were performed by replacing outliers using a simple linear interpolation technique. RESULTS: Over the entire study period, antibiotics accounted for 33.65% of the total costs of medicines procured for primary care institutions: mostly non-restricted antibiotics (86.03%) and antibiotics administered through parenteral routes (79.59%). On average, 17.14 million defined daily doses (DDDs) of antibiotics were procured per month, with the majority (93.09%) for non-restricted antibiotics and over half (52.38%) for parenteral administered antibiotics. The restrictive intervention was associated with a decline in the secular trend of costs for non-restricted oral antibiotics (- 0.36 million Yuan per month, p = 0.029), and for parenteral administered restricted antibiotics (- 0.28 million Yuan per month, p = 0.019), as well as a decline in the secular trend of procurement volume for parenteral administered non-restricted antibiotics (- 0.038 million DDDs per month, p = 0.05). CONCLUSIONS: Restrictive interventions are effective in reducing the procurement of antibiotics. However, the effect size is relatively small and antibiotic consumptions remain high, especially parenteral administered antibiotics.