Quality control of elbow joint radiography using a YOLOv8-based artificial intelligence technology.

BACKGROUND: To explore an artificial intelligence (AI) technology employing YOLOv8 for quality control (QC) on elbow joint radiographs. METHODS: From January 2022 to August 2023, 2643 consecutive elbow radiographs were collected and randomly assigned to the training, validation, and test sets in a 6:2:2 ratio. We proposed the anteroposterior (AP) and lateral (LAT) models to identify target detection boxes and key points on elbow radiographs using YOLOv8. These identifications were transformed into five quality standards: (1) AP elbow positioning coordinates (XA and YA); (2) olecranon fossa positioning distance parameters (S17 and S27); (3) key points of joint space (Y3, Y4, Y5 and Y6); (4) LAT elbow positioning coordinates (X2 and Y2); and (5) flexion angle. Models were trained and validated using 2,120 radiographs. A test set of 523 radiographs was used for assessing the agreement between AI and physician and to evaluate clinical efficiency of models. RESULTS: The AP and LAT models demonstrated high precision, recall, and mean average precision for identifying boxes and points. AI and physicians showed high intraclass correlation coefficient (ICC) in evaluating: AP coordinates XA (0.987) and YA (0.991); olecranon fossa parameters S17 (0.964) and S27 (0.951); key points Y3 (0.998), Y4 (0.997), Y5 (0.998) and Y6 (0.959); LAT coordinates X2 (0.994) and Y2 (0.986); and flexion angle (0.865). Compared to manual methods, using AI, QC time was reduced by 43% for AP images and 45% for LAT images (p < 0.001). CONCLUSION: YOLOv8-based AI technology is feasible for QC of elbow radiography with high performance. RELEVANCE STATEMENT: This study proposed and validated a YOLOv8-based AI model for automated quality control in elbow radiography, obtaining high efficiency in clinical settings. KEY POINTS: QC of elbow joint radiography is important for detecting diseases. Models based on YOLOv8 are proposed and perform well in image QC. Models offer objective and efficient solutions for QC in elbow joint radiographs.

Thinking Outside the Energetic Box: Stabilizing and Greening High-Energy Materials with Reticular Chemistry.

ConspectusReticular chemistry has provided intriguing opportunities for systematically designing porous materials with different pores by adjusting the building blocks. Among them, framework materials have demonstrated outstanding performance for the design of new functional materials used in a broad range of fields, including energetic materials. Energetic materials are widely used for rockets, satellites, mining, and tunneling. In terms of energetic materials, explosophores and nitrogen-rich heterocycles are fundamental building blocks for high-energy compounds. However, the traditional strategy of synthesizing HEDMs (high energy density materials) at the molecular level has faced the long-term challenge of balancing energy and stability. Inspired by reticular chemistry, nitrogen-rich heterocycles offer diverse nitrogen sites for designing diversified coordination interactions. Ionic bond interactions exist in a wide range of energetic salts. Furthermore, most metastable explosophores, e.g., nitro, nitramino, and amino groups, can form strong hydrogen-bonding networks. Based on these noncovalent interactions (such as coordination, ionic, and/or hydrogen bonds (HBs)) and/or covalent interactions can determine intermolecular packing/linkage of the energetic fuel and oxidizer components, reticular chemistry provides a new platform evolving from single-molecular design to various energetic frameworks (E of the energetic frameworks with superior comprehensive properties. For example, to achieve coordination with metals or introduce sufficient hydrogen bond donor/acceptor structural units, the host structure of energetic framework materials usually contains less oxygen-rich substituents such as nitro, so the host molecules of the framework, F) at the crystal level, which can enhance the integrated stabilities of EFs.Along with growing concerns about the environment and safety issues, considerable effort has been devoted to pursuing environmentally friendly and insensitive energetic materials. The newly emerging EFs are conducive to introducing explosophores into a green chemical pathway. Benefiting from these cross-disciplinary achievements, taming metastable energetic molecules in specific porous frameworks is a green strategy to desensitize energetic materials while concomitantly retaining excellent energetic properties, which has become one of the most forward and promising investigations. In the past decade, EFs have achieved further results in stabilizing and greening energetic materials using HBs, covalent bonds, and alkaline earth metal-involving coordination bonds to avoid heavy metal toxicity and to employ halogen-free oxidizers. Because this field is still expanding rapidly, it is of great value for researchers and possible users of the work to be able to view all the progress.Through this Account, we intend that more readers will become knowledgeable about EFs, including their definition, history, synthesis, properties, and possible applications. The aim of this Account is to present the latest advances in EFs in recent years and to offer a perspective on the future direction of this field.

Identification of Dementia & Mild Cognitive Impairment in Chinese Elderly Using Machine Learning.

OBJECTIVE: To assess the role of Machine Learning (ML) in identification critical factors of dementia and mild cognitive impairment. METHODS: 371 elderly individuals were ultimately included in the ML analysis. Demographic information (including gender, age, parity, visual acuity, auditory function, mobility, and medication history) and 35 features from 10 assessment scales were used for modeling. Five machine learning classifiers were used for evaluation, employing a procedure involving feature extraction, selection, model training, and performance assessment to identify key indicative factors. RESULTS: The Random Forest model, after data preprocessing, Information Gain, and Meta-analysis, utilized three training features and four meta-features, achieving an area under the curve of 0.961 and a accuracy of 0.894, showcasing exceptional accuracy for the identification of dementia and mild cognitive impairment. CONCLUSIONS: ML serves as a identification tool for dementia and mild cognitive impairment. Using Information Gain and Meta-feature analysis, Clinical Dementia Rating (CDR) and Neuropsychiatric Inventory (NPI) scale information emerged as crucial for training the Random Forest model.

Type 2 herpes simplex virus-induced anti-N-methyl-D-aspartate receptor encephalitis responsive to immunoglobulin monotherapy.

Herpes simplex virus-2 encephalitis (HSV2E) in immunocompetent adults is exceptionally rare, and the subsequent onset of autoimmune encephalitis after HSV2E is even less common. This report presents the inaugural Chinese case of anti-N-methyl-D-aspartate receptor encephalitis (NMDARE) induced by HSV2E, confirmed via metagenomic next-generation sequencing (mNGS). The patient demonstrated a favorable response to intravenous immunoglobulin (IVIG) monotherapy. This case emphasizes the importance of considering autoimmune encephalitis in patients exhibiting new or recurrent neurological symptoms after HSV2E recovery. Comprehensive mNGS and neuronal antibody testing are essential for timely diagnosis. Moreover, IVIG monotherapy can serve as an effective treatment for NMDARE induced by HSV2, providing a viable alternative, particularly when steroid therapy is contraindicated.

Bergenin protects against osteoarthritis by inhibiting STAT3, NF-κB and Jun pathways and suppressing osteoclastogenesis.

Osteoarthritis (OA) is a chronic degenerative disease characterized by articular cartilage destruction and subchondral bone reconstruction in the early stages. Bergenin (Ber) is a cytoprotective polyphenol found in many medicinal plants. It has been proven to have anti-inflammatory, antioxidant, and other biological activities, which may reveal its potential role in the treatment of OA. This study aimed to determine the potential efficacy of Ber in treating OA and explore the possible underlying mechanism through network pharmacology and validation experiments. The potential co-targets and processes of Ber and OA were predicted by using network pharmacology, including a Venn diagram for intersection targets, a protein‒protein interaction (PPI) network to obtain key potential targets, and GO and KEGG pathway enrichment to reveal the probable mechanism of action of Ber on OA. Subsequently, validation experiments were carried out to investigate the effects and mechanisms of Ber in treating OA in vitro and vivo. Ber suppressed IL-1ß-induced chondrocyte apoptosis and extracellular matrix catabolism by inhibiting the STAT3, NF-κB and Jun signalling pathway in vitro. Furthermore, Ber suppressed the expression of osteoclast marker genes and RANKL-induced osteoclastogenesis. Ber alleviated the progression of OA in DMM-induced OA mice model. These results demonstrated the protective efficacy and potential mechanisms of Ber against OA, which suggested that Ber could be adopted as a potential therapeutic agent for treating OA.

Effects of Hypertension on Alzheimer's Disease: Updates in Pathophysiological and Neuroimaging Findings.

Alzheimer's disease (AD) is recognized as the leading cause of dementia, imposing a significant economic toll on society. Despite the emergence of novel therapeutic approaches for AD, their efficacy and safety mandates further validation through rigorous clinical trials. In this context, hypertension (HTN) has garnered considerable attention as an amendable risk factor for AD. Research indicates that hypertension during midlife is associated with an elevated risk of AD in later years, influencing both the onset and progression of the disease. Nevertheless, the relationship between AD and hypertension in the later stages of life remains a subject of debate. Moreover, the consequences of blood pressure reduction on cognitive function, along with the optimal pharmacological interventions and therapeutic thresholds for hypertension, have emerged as pivotal areas of inquiry. This review synthesizes findings on epidemiology, neuroimaging, and biomarkers, and the effects of antihypertensive medications to elucidate the link between hypertension and cognitive performance. We particularly investigate how hypertension and AD are related by plasma sulfide dysregulation, offering possible indicators for future diagnosis and therapy.

Multi-view multiattention graph learning with stack deep matrix factorization for circRNA-drug sensitivity association identification.

Identifying circular RNA (circRNA)-drug sensitivity association (CDsA) is crucial for advancing drug development. As conducting traditional wet experiments for determining CDsA is costly and inefficient, calculation methods have already proven to be a valid approach to cope with this problem. However, there exists limited research addressing the prediction of the CDsA prediction problem, and certain discrepancies persist, particularly concerning false-negative associations. As a consequence, we present a multi-view framework, called MAGSDMF, for identifying latent CDsA. Firstly, MAGSDMF applies Multiple Attention mechanisms and Graph learning methods to dynamically extract features and strengthen the features of inside and across multi-similarity networks of circRNA and drug. Secondly, the Stack Deep Matrix Factorization (SDMF) is devised to directly extract features from CDsAs. We consider multi-similarity networks with the original CDsAs as multi-view information. Thirdly, MAGSDMF utilizes a multiattention channel mechanism to integrate these features for the purpose of reconstructing CDsA. Finally, MAGSDMF performs another DMF based on the reconstruction to identify the latent CDsAs. Simultaneously, contrastive learning (CL) is implemented to enhance the generalization capability of MAGSDMF and oversee the learning process of the underlying links prediction task. In comparative experiments, MAGSDMF achieves superior performance on two datasets with AUC values of 0.9743 and 0.9739 based on 5-fold cross-validation. Moreover, in case studies, the achievements further validate the identification reliability of MAGSDMF.

Baló's concentric sclerosis with spontaneous remission and favorable prognosis.

Introduction: Baló's concentric sclerosis (BCS) is a rare type of central nervous system demyelinating disorder. Most patients with BCS are treated with corticosteroids, and spontaneous remission has seldom been described. Case presentation: A 46-year-old man presented with a subacute-onset headache and memory loss. Brain magnetic resonance imaging (MRI) revealed multiple onion-shaped ring lesions with mild enhancement in the outermost ring. A brain biopsy revealed significant myelin loss. The diagnosis of BCS was established based on the MRI results and pathological findings. Interestingly, the patient recovered almost completely without immunotherapy, with repeated brain MRI at the 1-year follow-up showing an obvious reduction in the extent of the lesions. Conclusion: Neurologists should improve the recognition of the typical MRI features of BCS to avoid unnecessary biopsies. Although rare, spontaneous remission can be observed in clinical practice.

Assembling of Nitropyrazoles into Tetranitroacetimidic Acid (TNAA): A Pathway to High-Performance Energetic Oxidizers through Dual C/N-Functionalization.

In this work, incorporating nitropyraozles into tetranitroacetimidic acid (TNAA) resulted in two analogues of isomeric TNAA-like compounds (3 and 5). These compounds exhibit excellent densities, detonation performance, and high specific impulse, which are promising high-energy oxidizers that are comparable to AP and ADN. This structural modification strategy may have the potential to contribute significantly to the development of versatile, high-performance energetic oxidizers.

The relationship between perihematomal edema and hematoma expansion in acute spontaneous intracerebral hemorrhage: an exploratory radiomics analysis study.

Background: The relationship between early perihematomal edema (PHE) and hematoma expansion (HE) is unclear. We investigated this relationship in patients with acute spontaneous intracerebral hemorrhage (ICH), using radiomics. Methods: In this multicenter retrospective study, we analyzed 490 patients with spontaneous ICH who underwent non-contrast computed tomography within 6 h of symptom onset, with follow-up imaging at 24 h. We performed HE and PHE image segmentation, and feature extraction and selection to identify HE-associated optimal radiomics features. We calculated radiomics scores of hematoma (Radscores_HEA) and PHE (Radscores_PHE) and constructed a combined model (Radscore_HEA_PHE). Relationships of the PHE radiomics features or Radscores_PHE with clinical variables, hematoma imaging signs, Radscores_HEA, and HE were assessed by univariate, correlation, and multivariate analyses. We compared predictive performances in the training (n = 296) and validation (n = 194) cohorts. Results: Shape_VoxelVolume and Shape_MinorAxisLength of PHE were identified as optimal radiomics features associated with HE. Radscore_PHE (odds ratio = 1.039, p = 0.032) was an independent HE risk factor after adjusting for the ICH onset time, Glasgow Coma Scale score, baseline hematoma volume, hematoma shape, hematoma density, midline shift, and Radscore_HEA. The areas under the receiver operating characteristic curve of Radscore_PHE in the training and validation cohorts were 0.808 and 0.739, respectively. After incorporating Radscore_PHE, the integrated discrimination improvements of Radscore_HEA_PHE in the training and validation cohorts were 0.009 (p = 0.086) and -0.011 (p < 0.001), respectively. Conclusion: Radscore_PHE, based on Shape_VoxelVolume and Shape_MinorAxisLength of PHE, independently predicts HE, while Radscore_PHE did not add significant incremental value to Radscore_HEA.

Construction of Adaptive Deformation Block: Rational Molecular Editing of the N-Rich Host Molecule to Remove Water from the Energetic Hydrogen-Bonded Organic Frameworks.

Energetic hydrogen-bonded organic frameworks (E-HOFs), as a type of energetic material, spark fresh vitality to the creation of high energy density materials (HEDMs). However, E-HOFs containing cations and anions face challenges such as reduced energy density due to the inclusion of crystal water. In this work, the modification of amino groups in N-rich organic units could form a smart building block of hydrogen-bonded frameworks capable of changing the volume of the void space in the molecule through adaptive deformation of E-MOF blocks, thus enabling the replacement of water. Based on the above strategy, we report an interesting example of a series of hydrogen-bonded organic frameworks (E-HOF 2a and 3a) synthesized using a facile method. The crystal structure data of all of the compounds were also obtained in this work. Anhydrous 2a and 3a exhibit higher density, good thermal stability, and low mechanical sensitivity. The strategy of covalent bond modification for the host molecules of energetic frameworks shows enormous potential in eliminating the crystalline H2O of hydration and exploring high energy density materials.

Hypomethylation-associated LINC00987 downregulation induced lung adenocarcinoma progression by inhibiting the phosphorylation-mediated degradation of SND1.

DNA methylation, an epigenetic regulatory mechanism dictating gene transcription, plays a critical role in the occurrence and development of cancer. However, the molecular underpinnings of LINC00987 methylation in the regulation of lung adenocarcinoma (LUAD) remain elusive. This study investigated LINC00987 expression in LUAD patients through analysis of The Cancer Genome Atlas data sets. Quantitative real-time polymerase chain reaction (RT-qPCR) and fluorescence in situ hybridization assays were used to assess LINC00987 expression in LUAD. The bisulfite genomic sequence PCR (BSP) assay was used to determine the methylation levels of the LINC00987 promoter. The interaction between LINC00987 and SND1 was elucidated via immunoprecipitation and RNA pull-down assays. The functional significance of LINC00987 and SND1 in Calu-3 and NCI-H1688 cells was evaluated in vitro through CCK-8, EdU, Transwell, flow cytometry, and vasculogenic mimicry (VM) tube formation assays. LINC00987 expression decreased in LUAD concomitant with hypermethylation of the promoter region, while hypomethylation of the LINC00987 promoter in LUAD tissues correlated with tumor progression. Treatment with 5-Aza-CdR augmented LINC00987 expression and inhibited tumor growth. Mechanistically, LINC00987 overexpression impeded LUAD progression and VM through direct binding with SND1, thereby facilitating its phosphorylation and subsequent degradation. Additionally, overexpression of SND1 counteracted the adverse effects of LINC00987 downregulation on cell proliferation, apoptosis, cell migration, invasion, and VM in LUAD in vitro. In conclusion, this pioneering study focuses on the expression and function of LINC00987 and reveals that hypermethylation of the LINC00987 gene may contribute to LUAD progression. LINC00987 has emerged as a potential tumor suppressor gene in tumorigenesis through its binding with SND1 to facilitate its phosphorylation and subsequent degradation.

AP39 through AMPK-ULK1-FUNDC1 pathway regulates mitophagy, inhibits pyroptosis, and improves doxorubicin-induced myocardial fibrosis.

Doxorubicin induces myocardial injury and fibrosis. Still, no effective interventions are available. AP39 is an H2S donor that explicitly targets mitochondria. This study investigated whether AP39 could improve doxorubicin-induced myocardial fibrosis. Doxorubicin induced significant myocardial fibrosis while suppressing mitophagy-related proteins and elevating pyroptosis-related proteins. Conversely, AP39 reverses these effects, enhancing mitophagy and inhibiting pyroptosis. In vitro experiments revealed that AP39 inhibited H9c2 cardiomyocyte pyroptosis, improved doxorubicin-induced impairment of mitophagy, reduced ROS levels, ameliorated the mitochondrial membrane potential, and upregulated AMPK-ULK1-FUNDC1 expression. In contrast, AMPK inhibitor (dorsomorphin) and ULK1 inhibitor (SBI-0206965) reversed AP39 antagonism of doxorubicin-induced FUNDC1-mediated impairment of mitophagy and secondary cardiomyocyte pyroptosis. These results suggest that mitochondria-targeted H2S can antagonize doxorubicin-induced pyroptosis and impaired mitophagy in cardiomyocytes via AMPK-ULK1-FUNDC1 and ameliorated myocardial fibrosis and remodeling.

A Machine-Learning Strategy to Detect Mura Defects in a Low-Contrast Image by Piecewise Gamma Correction.

A detection and classification machine-learning model to inspect Thin Film Transistor Liquid Crystal Display (TFT-LCD) Mura is proposed in this study. To improve the capability of the machine-learning model to inspect panels' low-contrast grayscale images, piecewise gamma correction and a Selective Search algorithm are applied to detect and optimize the feature regions based on the Semiconductor Equipment and Materials International Mura (SEMU) specifications. In this process, matching the segment proportions to gamma values of piecewise gamma is a task that involves derivative-free optimization which is trained by adaptive particle swarm optimization. The detection accuracy rate (DAR) is approximately 93.75%. An enhanced convolutional neural network model is then applied to classify the Mura type through using the Taguchi experimental design method that identifies the optimal combination of the convolution kernel and the maximum pooling kernel sizes. A remarkable defect classification accuracy rate (CAR) of approximately 96.67% is ultimately achieved. The entire defect detection and classification process can be completed in about 3 milliseconds.

Dynamic lymphocyte-CRP ratio as a predictor: a single-centre retrospective study on disease severity and progression in adult COVID-19 patients.

OBJECTIVE: To assess the efficacy of dynamic changes in lymphocyte-C-reactive protein ratio (LCR) on differentiating disease severity and predicting disease progression in adult patients with Coronavirus disease 2019 (COVID-19). METHODS: This single-centre retrospective study enrolled adult COVID-19 patients categorized into moderate, severe and critical groups according to the Diagnosis and Treatment of New Coronavirus Pneumonia (ninth edition). Demographic and clinical data were collected. LCR and sequential organ failure assessment (SOFA) score were calculated. Lymphocyte count and C-reactive protein (CRP) levels were monitored on up to four occasions. Disease severity was determined concurrently with each LCR measurement. RESULTS: This study included 145 patients assigned to moderate (n = 105), severe (n = 33) and critical groups (n = 7). On admission, significant differences were observed among different disease severity groups including age, comorbidities, neutrophil proportion, lymphocyte count and proportion, D-Dimer, albumin, total bilirubin, direct bilirubin, indirect bilirubin, CRP and SOFA score. Dynamic changes in LCR showed significant differences across different disease severity groups at different times, which were significantly inversely correlated with disease severity of COVID-19, with correlation coefficients of -0.564, -0.548, -0.550 and -0.429 at four different times. CONCLUSION: Dynamic changes in LCR can effectively differentiate disease severity and predict disease progression in adult COVID-19 patients.

Predictive and Prognostic Potentials of Lymphocyte-C-Reactive Protein Ratio Upon Hospitalization in Adult Patients with Acute Pancreatitis.

Purpose: In this study, our objective was to investigate the potential utility of lymphocyte-C-reactive protein ratio (LCR) as a predictor of disease progression and a screening tool for intensive care unit (ICU) admission in adult patients with acute pancreatitis (AP). Methods: We included a total of 217 adult patients with AP who were admitted to the First Affiliated Hospital of Harbin Medical University between July 2019 and June 2022. These patients were categorized into three groups: mild AP (MAP), moderately severe AP (MSAP), and severe AP (SAP), based on the presence and duration of organ dysfunction. Various demographic and clinical data were collected and compared among different disease severity groups. Results: Height, diabetes, lymphocyte count (LYMPH), lymphocyte percentage (LYM%), platelet count (PLT), D-Dimer, albumin (ALB), blood urea nitrogen (BUN), serum creatinine (SCr), glucose (GLU), calcium ion (Ca2+), C-reactive protein (CRP), procalcitonin (PCT), hospitalization duration, ICU admission, need for BP, LCR, sequential organ failure assessment (SOFA) score, bedside index for severity in AP (BISAP) score, and modified Marshall score showed significant differences across different disease severity groups upon hospitalization. Notably, there were significant differences in LCR between the MAP group and the MSAP and SAP combined group, and the MAP and MSAP combined group and the SAP group, and adult AP patients with ICU admission and those without ICU admission upon hospitalization. Conclusion: In summary, LCR upon hospitalization can be utilized as a simple and reliable predictor of disease progression and a screening tool for ICU admission in adult patients with AP.

Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS): contemporary advances and current controversies.

Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS) is an inflammatory syndrome with characteristic clinical, radiological, and pathological features, and can be effectively treated with corticosteroid-based immunotherapies. The exact pathogenesis of CLIPPERS remains unclear, and specific diagnostic biomarkers are not available. According to the 2017 diagnostic criteria, probable CLIPPERS should be considered in middle-aged patients with subacute onset of pontocerebellar symptoms and typical punctuate and curvilinear gadolinium enhancement lesions ("salt-and-pepper" appearance) located in the hindbrain (especially pons) on magnetic resonance imaging. In addition, CLIPPERS-mimics, such as central nervous system (CNS) lymphoma, and several antibody-associated autoimmune CNS diseases (e.g., myelin oligodendrocyte glycoprotein antibody-associated disease, autoimmune glial fibrillary acidic protein astrocytopathy, and anti-N-methyl-D-aspartate receptor encephalitis), should be extensively excluded. The prerequisite for definite CLIPPERS is the perivascular T-cell-predominant inflammatory infiltration observed on pathological analysis. A biopsy is strongly suggested when clinical/radiological red flags are present. Most patients with CLIPPERS respond well to corticosteroids and have a good prognosis. Long-term low-dose corticosteroid maintenance therapy or corticosteroids coupled with immunosuppressants are recommended to prevent the recurrence of the syndrome. The potential progression of CLIPPERS to lymphoma has been suggested in some cases; therefore, at least 2-year clinical and radiological follow-up is essential. Here, we critically review the recent developments and provided an update on the clinical characteristics, diagnostic criteria, differential diagnoses, and therapeutic management of CLIPPERS. We also discuss the current controversies in this context that can be resolved in future research studies.

Exploring a Fused Triazole-Tetrazine Binary CN Material for a Promising Initiating Substance.

The pursuit of binary carbon-nitrogen (CN) materials with high density and good thermal stability presents a significant challenge due to the inherent trade-off between high-energy storage and low bond dissociation energy. In this study, we designed and synthesized (S)-1,2-bis(3-azido-1H-1,2,4-triazol-1-yl)diazene (BAzTD) and 2,9-diazidobis([1,2,4]-triazolo)[1,5-d:5',1'-f][1,2,3,4]tetrazine (DAzTT) through a straightforward reaction. Remarkably, DAzTT demonstrated a high density of 1.816 g·cm-3 (at 298 K) and a considerable thermal decomposition temperature of 216.86 °C. These properties outperform those of previously reported binary heterocyclic CN compounds and polyazido heterocyclic compounds. The quantum-chemical methods further substantiated the integral role of aromaticity as the driving force behind this difference. Additionally, the initiation capability of DAzTT was evaluated by a notably low minimum primary charge (MPC = 40 mg), surpassing conventional organic primary explosives, such as commercial 2-diazo-4,6-dinitrophenol (DDNP, MPC = 70 mg). The exceptional priming ability highlights the potential as an environmentally friendly replacement for toxic lead azide. DAzTT sets a new standard for binary CN compounds and provides a valuable precursor for high-nitrogen carbon nitride materials.

Identifying Genetic Factors of Polycystic Ovary Syndrome in Women with Epilepsy: A Whole-Genome Sequencing Study.

INTRODUCTION: Women with epilepsy (WWE) are more likely to develop reproductive endocrine disorders, especially polycystic ovary syndrome (PCOS). This study aimed to explore the genetic factors of PCOS in WWE in hope of improving individual precision diagnosis and treatment. METHODS: WWE registered at West China Hospital between January 2022 and October 2022 were enrolled in this study. Demographic and epilepsy-related characteristics were recorded, and blood samples were collected for hormones, glucose metabolism testing, and whole-genome sequencing. RESULTS: After sample sequencing, quality control, and variants selection, association analyses were performed. Pathway analysis was performed to identify involved biological pathways. The overall and PCOS "burden score" of each individual were calculated to count the deleterious variants. A total of 95 WWE were included in this study and 19 patients were diagnosed with PCOS. WWE with PCOS showed a significantly different hormone profiles and a tendency of impaired glucose metabolism. The most commonly associated genes were ZFYVE28, COL19A1, SIK3, ANKK1, PPIG, and REPIN1. The top 3 canonical pathways are adipogenesis pathway, epoxysqualene biosynthesis signaling, and glutamate degradation signaling. The most significant common variant was rs11914038 located in gene CELSR1 and rs651748 located in gene ZBTB16. In human gene connectome prioritizations, ITGA9, PNPLA2, and DAB2 are the top 3 genes having the shortest distance to known PCOS genes. CONCLUSION: Genetic factors involved in the abnormal regulation of glucose and insulin metabolism are likely to be associated with the comorbidity of PCOS in WWE. Interventions targeting these processes should be given more priority in clinical practice.