A Real-Time Contact-Free Atrial Fibrillation Detection System for Mobile Devices.

As the global population ages, the death and prevalence of atrial fibrillation (AF) continue to rise, posing significant concerns due to its strong association with stroke-related disabilities. Detecting AF early before a stroke occurs has become paramount. However, existing methods face challenges in achieving quick, easy, and affordable detection in complex environments characterized by motion interference and varying light conditions. To address these challenges, we propose a system that is employable for edge computing devices like smartphones, tablets, or laptops. Meanwhile, to ensure that the dataset reflects real-world scenarios, we collect 7,216 30-second segments from 452 subjects, categorized into Atrial Fibrillation (AF), Normal Sinus Rhythm (NSR), and Other Arrhythmias (Others), with a subject ratio of 105:116:231. Our lightweight non-contact facial rPPG atrial fibrillation detection system utilizes a Convolution Neural Network (CNN) with a large receptive field and a bidirectional spatial mapping augmented attention module (BiSME-ATT) coupled with a bidirectional feature pyramid network layer (BiFPN), optimized for deployment on mobile devices by reducing model parameters and floating-point operations per second (FLOPs). Our approach significantly improves AF detection accuracy, sensitivity, specificity, positive predictive value, and negative predictive value to 94.39%, 91.57%, 95.44%, 88.06%, and 96.93%, respectively, in AF vs. Non-AF scenarios. Furthermore, the results demonstrate notable enhancements in AF detection across various motion and light intensity levels.

Serum 25-hydroxyvitamin D concentrations, vitamin D receptor polymorphisms, and risk of infections among individuals with type 2 diabetes: a prospective cohort study.

BACKGROUND: Evidence on the association between serum 25-hydroxyvitamin D [25(OH)D] and infections among patients with type 2 diabetes (T2D), a group susceptible to vitamin D deficiency and infections, is limited. OBJECTIVES: We aimed to examine this association in individuals with T2D, and to evaluate whether genetic variants in vitamin D receptor (VDR) would modify this association. METHODS: This study included 19,851 participants with T2D from United Kingdom Biobank. Infections were identified by linkage to hospital inpatient and death registers. Negative binomial regression models were used to estimate incidence rate ratios (IRRs) and 95% confidence intervals (CIs), with adjustment of potential confounders. RESULTS: In patients with T2D, the incidence rate of infections was 29.3/1000 person-y. Compared with those with 25(OH)D of 50.0-74.9 nmol/L, the multivariable-adjusted IRRs and 95% CIs of total infections, pneumonia, gastrointestinal infections, and sepsis were 1.44 (1.31, 1.59), 1.49 (1.27, 1.75), 1.47 (1.22, 1.78), and 1.41 (1.14, 1.73), respectively, in patients with 25(OH)D <25.0 nmol/L. Nonlinear inverse associations between 25(OH)D concentrations and the risks of total infections (P-overall < 0.001; P-nonlinear = 0.002) and gastrointestinal infections (P-overall < 0.001; P-nonlinear = 0.040) were observed, with a threshold effect at ∼50.0 nmol/L. The vitamin D-infection association was not modified by genetic variants in VDR (all P-interaction > 0.050). CONCLUSIONS: In patients with T2D, lower serum 25(OH)D concentration (<50 nmol/L) was associated with higher risks of infections, regardless of genetic variants in VDR. Notably, nonlinear inverse associations between 25(OH)D concentrations and the risks of infections were found, with a threshold effect at ∼50.0 nmol/L. These findings highlighted the importance of maintaining adequate vitamin D in reducing the risk of infections in patients with T2D.

Contact-Free Atrial Fibrillation Screening with Attention Network.

Atrial Fibrillation (AF) screening from face videos has become popular with the trend of telemedicine and telehealth in recent years. In this study, the largest facial image database for camera-based AF detection is proposed. There are 657 participants from two clinical sites and each of them is recorded for about 10 minutes of video data, which can be further processed as over 10,000 segments around 30 seconds, where the duration setting is referred to the guideline of AF diagnosis. It is also worth noting that, 2,979 segments are segment-wise labeled, that is, every rhythm is independently labeled with AF or not. Besides, all labels are confirmed by the cardiologist manually. Various environments, talking, facial expressions, and head movements are involved in data collection, which meets the situations in practical usage. Specific to camera-based AF screening, a novel CNN-based architecture equipped with an attention mechanism is proposed. It is capable of fusing heartbeat consistency, heart rate variability derived from remote photoplethysmography, and motion features simultaneously to reliable outputs. With the proposed model, the performance of intra-database evaluation comes up to 96.62% of sensitivity, 90.61% of specificity, and 0.96 of AUC. Furthermore, to check the capability of adaptation of the proposed method thoroughly, the cross-database evaluation is also conducted, and the performance also reaches about 90% on average with the AUCs being over 0.94 in both clinical sites.

Contactless Blood Pressure Measurement Via Remote Photoplethysmography With Synthetic Data Generation Using Generative Adversarial Networks.

Remote photoplethysmography (rPPG) has been used to measure vital signs such as heart rate, heart rate variability, blood pressure (BP), and blood oxygen. Recent studies adopt features developed with photoplethysmography (PPG) to achieve contactless BP measurement via rPPG. These features can be classified into two groups: time or phase differences from multiple signals, or waveform feature analysis from a single signal. Here we devise a solution to extract the time difference information from the rPPG signal captured at 30 FPS. We also propose a deep learning model architecture to estimate BP from the extracted features. To prevent overfitting and compensate for the lack of data, we leverage a multi-model design and generate synthetic data. We also use subject information related to BP to assist in model learning. For real-world usage, the subject information is replaced with values estimated from face images, with performance that is still better than the state-of-the-art. To our best knowledge, the improvements can be achieved because of: 1) the model selection with estimated subject information, 2) replacing the estimated subject information with the real one, 3) the InfoGAN assistance training (synthetic data generation), and 4) the time difference features as model input. To evaluate the performance of the proposed method, we conduct a series of experiments, including dynamic BP measurement for many single subjects and nighttime BP measurement with infrared lighting. Our approach reduces the MAE from 15.49 to 8.78 mmHg for systolic blood pressure (SBP) and 10.56 to 6.16 mmHg for diastolic blood pressure(DBP) on a self-constructed rPPG dataset. On the Taipei Veterans General Hospital(TVGH) dataset for nighttime applications, the MAE is reduced from 21.58 to 11.12 mmHg for SBP and 9.74 to 7.59 mmHg for DBP, with improvement ratios of 48.47% and 22.07% respectively.

Efficacy, safety and dose selection of AZD3759 in patients with untreated EGFR-mutated non-small-cell lung cancer and central nervous system metastases in China (CTONG1702-Arm 8): a multi-center, single-arm, phase 2 trial.

Background: Central nervous system (CNS) metastases is inevitable for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC). AZD3759 is a novel EGFR-TKI with impressive CNS penetration. Methods: We initiated a phase 2, multi-center, umbrella trial (CTONG1702, NCT03574402). The eighth arm assessed the efficacy and safety of AZD3759 in untreated EGFR-mutated NSCLC with CNS metastases. The primary objective was the objective response rate (ORR). Simon's minimax two-stage design was used to calculate the sample size. Dose optimal selection was performed using 200- and 300-mg bid cohorts. Findings: Between Oct 18, 2018 and Sep 14, 2020, 30 patients received AZD3759 at 200 mg (n = 15) or 300 mg (n = 15) bid. At data cutoff (Dec 31, 2022), median follow-up was 35.4 months. The primary endpoint was reached, with a confirmed ORR of 70% (21/30) (200 mg, 80%; 300 mg, 60%). The median progression-free survival was 12.9 months (200 mg, 15.8 months; 300 mg, 10.7 months). Grade 3 or 4 treatment-related adverse events occurred in 73% (22/30) of the patients (200 mg: 60%; 300 mg: 87%). 59% (10/17) of the patients developed a T790M mutation at disease progression. The median overall survival was 33.7 months, and 34.1 months and 25.3 months in patient treated with or without osimertinib in a later-line setting, respectively. Interpretation: AZD3759 showed promising efficacy and tolerable safety as a first-line therapy in EGFR-mutated NSCLC with CNS metastases. The 200-mg bid cohort had better clinical outcomes. Sequential use of AZD3759 and third-generation EGFR-TKIs represents a new option. Funding: Chinese Thoracic Oncology Group (CTONG).

Identification of tophi in ultrasound imaging based on transfer learning and clinical practice.

Gout is a common metabolic disorder characterized by deposits of monosodium urate monohydrate crystals (tophi) in soft tissue, triggering intense and acute arthritis with intolerable pain as well as articular and periarticular inflammation. Tophi can also promote chronic inflammatory and erosive arthritis. 2015 ACR/EULAR Gout Classification criteria include clinical, laboratory, and imaging findings, where cases of gout are indicated by a threshold score of ≥ 8. Some imaging-related findings, such as a double contour sign in ultrasound, urate in dual-energy computed tomography, or radiographic gout-related erosion, generate a score of up to 4. Clearly, the diagnosis of gout is largely assisted by imaging findings; however, dual-energy computed tomography is expensive and exposes the patient to high levels of radiation. Although musculoskeletal ultrasound is non-invasive and inexpensive, the reliability of the results depends on expert experience. In the current study, we applied transfer learning to train a convolutional neural network for the identification of tophi in ultrasound images. The accuracy of predictions varied with the convolutional neural network model, as follows: InceptionV3 (0.871 ± 0.020), ResNet101 (0.913 ± 0.015), and VGG19 (0.918 ± 0.020). The sensitivity was as follows: InceptionV3 (0.507 ± 0.060), ResNet101 (0.680 ± 0.056), and VGG19 (0.747 ± 0.056). The precision was as follows: InceptionV3 (0.767 ± 0.091), ResNet101 (0.863 ± 0.098), and VGG19 (0.825 ± 0.062). Our results demonstrate that it is possible to retrain deep convolutional neural networks to identify the patterns of tophi in ultrasound images with a high degree of accuracy.

Associations of Clinical Risk Factors and Novel Biomarkers With Age at Onset of Type 2 Diabetes.

CONTEXT: Younger onset of type 2 diabetes (T2D) was associated with higher risks of vascular complications and mortality. OBJECTIVE: To prospectively assess risk profiles for incident T2D stratified by age at onset. METHODS: A total of 471 269 participants free of T2D at baseline were included from the UK Biobank. Approximately 70 clinical, lipid, lipoprotein, inflammatory, and metabolic markers, and genetic risk scores (GRSs) were analyzed. Stratified Cox proportional-hazards regression models were used to estimate hazard ratios (HRs) for T2D with age of diagnosis divided into 4 groups (≤50.0, 50.1-60.0, 60.1-70.0, and >70.0 years). RESULTS: During 11 years of follow-up, 15 805 incident T2D were identified. Among clinical risk factors, obesity had the highest HR at any age, ranging from 13.16 (95% CI, 9.67-17.91) for 50.0 years and younger to 4.13 (3.78-4.51) for older than 70.0 years. Other risks associated with T2D onset at age 50.0 years and younger included dyslipidemia (3.50, 2.91-4.20), hypertension (3.21, 2.71-3.80), cardiovascular disease (2.87, 2.13-3.87), parental history of diabetes (2.42, 2.04-2.86), education lower than college (1.89, 1.57-2.27), physical inactivity (1.73, 1.43-2.10), smoking (1.38, 1.13-1.68), several lipoprotein particles, inflammatory markers, liver enzymes, fatty acids, amino acids, as well as GRS. Associations of most risk factors and biomarkers were markedly attenuated with increasing age at onset (P interaction <.05), and some were not significant for onset at age older than 70.0 years, such as smoking, systolic blood pressure, and apolipoprotein B. CONCLUSION: Most risk factors or biomarkers had stronger relative risks for T2D at younger ages, which emphasizes the necessity of promoting primary prevention among younger individuals. Moreover, obesity should be prioritized.

First-line pyrotinib in advanced HER2-mutant non-small-cell lung cancer: a patient-centric phase 2 trial.

To explore targeted treatment options in patients with non-small-cell lung cancer (NSCLC) with rare genetic mutations in the context of a patient-centric clinical trial, we initiated, in parallel, a phase 2 adaptive umbrella trial consisting of a criteria-fulfilled (CF) cohort and a compassionate use (CU) cohort under expanded eligibility criteria, and a prospective real-world study (RWS). Here, we present efficacy and safety data from 48 patients with treatment-naive, advanced HER2-mutant NSCLC treated with the pan-HER receptor tyrosine kinase inhibitor pyrotinib (CF and CU cohorts) or physician's therapy of choice (RWS cohort). In the phase 2 trial CF cohort (n = 28), the primary endpoint was reached with an objective response rate of 35.7% after pyrotinib treatment. Secondary endpoints included disease control rate (89.3%), median progression-free survival (PFS) (7.3 months), median overall survival (OS) (14.3 months) and toxicity, which was acceptable, with grade 3 or 4 treatment-related adverse events occurring in three patients (10.7%). The phase 2 trial CU cohort (n = 12) showed an objective response rate of 16.7%, disease control rate of 83.4%, median PFS of 4.7 months and median OS of 14.2 months after pyrotinib treatment. The RWS cohort (n = 8) had no responses to physician's therapy of choice, while median PFS and OS were 3.0 and 12.2 months, respectively. Phase 2 umbrella trial, clinicaltrials.gov identifier: NCT03574402 . RWS, clinicaltrials.gov identifier: NCT03605602 .

Trends in the Prevalence of Metabolically Healthy Obesity Among US Adults, 1999-2018.

Importance: Improved understanding of trends in the proportion of individuals with metabolically healthy obesity (MHO) may facilitate stratification and management of obesity and inform policy efforts. Objectives: To characterize trends in the prevalence of MHO among US adults with obesity, overall and by sociodemographic subgroups. Design, Setting, and Participants: This survey study included 20 430 adult participants from 10 National Health and Nutrition Examination Survey (NHANES) cycles between 1999-2000 and 2017-2018. The NHANES is a series of cross-sectional and nationally representative surveys of the US population conducted continuously in 2-year cycles. Data were analyzed from November 2021 to August 2022. Exposures: National Health and Nutrition Examination Survey cycles from 1999-2000 to 2017-2018. Main Outcomes and Measures: Metabolically healthy obesity was defined as a body mass index of 30.0 (calculated as weight in kilograms divided by height in meters squared) without any metabolic disorders in blood pressure, fasting plasma glucose (FPG), high-density lipoprotein cholesterol (HDL-C), or triglycerides based on established cutoffs. Trends in the age-standardized prevalence of MHO were estimated using logistic regression analysis. Results: This study included 20 430 participants. Their weighted mean (SE) age was 47.1 (0.2) years; 50.8% were women, and 68.8% self-reported their race and ethnicity as non-Hispanic White. The age-standardized prevalence (95% CI) of MHO increased from 3.2% (2.6%-3.8%) in the 1999-2002 cycles to 6.6% (5.3%-7.9%) in the 2015-2018 cycles (P < .001 for trend). There were 7386 adults with obesity. Their weighted mean (SE) age was 48.0 (0.3) years, and 53.5% were women. The age-standardized proportion (95% CI) of MHO among these 7386 adults increased from 10.6% (8.8%-12.5%) in the 1999-2002 cycles to 15.0% (12.4%-17.6%) in the 2015-2018 cycles (P = .02 for trend). Substantial increases in the proportion of MHO were observed for adults aged 60 years or older, men, non-Hispanic White individuals, and those with higher income, private insurance, or class I obesity. In addition, there were significant decreases in the age-standardized prevalence (95% CI) of elevated triglycerides (from 44.9% [40.9%-48.9%] to 29.0% [25.7%-32.4%]; P < .001 for trend) and reduced HDL-C (from 51.1% [47.6%-54.6%] to 39.6% [36.3%-43.0%]; P = .006 for trend). There was also a significant increase in elevated FPG (from 49.7% [95% CI, 46.3%-53.0%] to 58.0% [54.8%-61.3%]; P < .001 for trend) but no significant change in elevated blood pressure (from 57.3% [53.9%-60.7%] to 54.0% [50.9%-57.1%]; P = .28 for trend). Conclusions and Relevance: The findings of this cross-sectional study suggest that the age-standardized proportion of MHO increased among US adults from 1999 to 2018, but differences in trends existed across sociodemographic subgroups. Effective strategies are needed to improve metabolic health status and prevent obesity-related complications in adults with obesity.

Motion-Robust Atrial Fibrillation Detection Based on Remote-Photoplethysmography.

Atrial fibrillation (AF) has been proven highly correlated to stroke; more than 43 million people suffer from AF worldwide. However, most of these patients are unaware of their disease. There is no convenient tool by which to conduct a comprehensive screening to identify asymptomatic AF patients. Hence, we provide a non-contact AF detection approach based on remote photoplethysmography (rPPG). We address motion disturbance, the most challenging issue in rPPG technology, with the NR-Net, ATT-Net, and SQ-Mask modules. NR-Net is designed to eliminate motion noise with a CNN model, and ATT-Net and SQ-Mask utilize channel-wise and temporal attention to reduce the influence of poor signal segments. Moreover, we present an AF dataset collected from hospital wards which contains 452 subjects (mean age, 69.3 ±13.0 years; women, 46%) and 7,306 30-second segments to verify the proposed algorithm. To our best knowledge, this dataset has the most participants and covers the full age range of possible AF patients. The proposed method yields accuracy, sensitivity, and specificity of 95.69%, 96.76%, and 94.33%, respectively, when discriminating AF from normal sinus rhythm. More than previous studies, other arrhythmias are also taken into consideration, leading to a further investigation of AF vs. Non-AF and AF vs. Other scenarios. For the three scenarios, the proposed approach outperforms the benchmark algorithms. Additionally, the accuracy of the slight motion data improves to 95.82%, 92.39%, and 89.18% for the three scenarios, respectively, while that of full motion data increases by over 3%.

Constructions and advances of animal models of Pseudomonas aeruginosa infection / 中华预防医学杂志

Pseudomonas aeruginosa (P. aeruginosa) is an opportunistic pathogenic bacterium with complex pathogenesis and drug resistance mechanisms. It has high morbidity and mortality and can cause acute and chronic infections in immunocompromised individuals, with lung infections, wound infections, and bloodstream infections being the most common. The animal infection model of P. aeruginosa is of great value for in-depth research on the pathogenicity, drug resistance, and therapeutic measures of P. aeruginosa by simulating the pathways of human bacterial infections. This article firstly summarizes the selection, anesthesia, and disposal of experimental animals in the construction of animal models of P. aeruginosa infection, and then reviews the methods of construction, model evaluation, and applications of animal models of P. aeruginosa pulmonary infection, wound infection, and bloodstream infection, in order to provide a reference for scientific research related to P. aeruginosa infectious diseases.

[Clinical phenotype and genetic features of 16p11.2 microdeletion-related epilepsy in children]. / 16p11.2å¾®ç¼ºå¤±ç›¸å ³å„¿ç«¥ç™«ç—«çš„ä¸´åºŠè¡¨åž‹ä¸Žé—ä¼ å­¦ç‰¹å¾åˆ†æž.

OBJECTIVES: To study the clinical phenotype and genetic features of 16p11.2 microdeletion-related epilepsy in children. METHODS: The medical data of 200 children with epilepsy who underwent a genetic analysis of epilepsy by the whole exon sequencing technology were collected retrospectively, of whom 9 children with epilepsy had 16p11.2 microdeletion. The clinical phenotype and genetic features of the 9 children with 16p11.2 microdeletion were analyzed. RESULTS: The detection rate of 16p11.2 microdeletion was 4.5% (9/200). The 9 children with 16p11.2 microdeletion were 3-10 months old. They experienced focal motor seizures with consciousness disturbance, and some of the seizures developed into generalized tonic-clonic seizures. The interictal electroencephalogram showed focal or multifocal epileptiform discharge, and all 9 children responded well to antiepileptic drugs. The 9 children had a 16p11.2 deletion fragment size of 398-906 kb, and the number of deleted genes was 23-33 which were all pathogenic mutations. The mutation was of maternal origin in 2 children, of paternal origin in 1 child, and de novo in the other children. CONCLUSIONS: 16p11.2 microdeletion can be detected in some children with epilepsy. Most of the 16p11.2 microdeletion is de novo mutation and large gene fragment deletion. The onset of 16p11.2 microdeletion-related epilepsy in children is mostly within 1 year of life, and the epilepsy is drug-responsive.

[Retracted] Silencing NOB1 enhances doxorubicin antitumor activity of the papillary thyroid carcinoma in vitro and in vivo.

Following the publication of this paper, it was drawn to the Editors' attention by a concerned reader that certain of the western blotting assay data shown in Figs. 2 and 5, and the tumour images shown in Fig. 6A, were strikingly similar to data appearing in different form in other articles by different authors. Owing to the fact that the contentious data in the above article had already been published elsewhere, or were already under consideration for publication, prior to its submission to Oncology Reports, the Editor has decided that this paper should be retracted from the Journal. After having been in contact with the authors, they agreed with the decision to retract the paper. The Editor apologizes to the readership for any inconvenience caused. [the original article was published in Oncology Reports 33: 1551-1559, 2015; DOI: 10.3892/or.2015.3730].

Contactless facial video recording with deep learning models for the detection of atrial fibrillation.

Atrial fibrillation (AF) is often asymptomatic and paroxysmal. Screening and monitoring are needed especially for people at high risk. This study sought to use camera-based remote photoplethysmography (rPPG) with a deep convolutional neural network (DCNN) learning model for AF detection. All participants were classified into groups of AF, normal sinus rhythm (NSR) and other abnormality based on 12-lead ECG. They then underwent facial video recording for 10 min with rPPG signals extracted and segmented into 30-s clips as inputs of the training of DCNN models. Using voting algorithm, the participant would be predicted as AF if > 50% of their rPPG segments were determined as AF rhythm by the model. Of the 453 participants (mean age, 69.3 ± 13.0 years, women, 46%), a total of 7320 segments (1969 AF, 1604 NSR & 3747others) were analyzed by DCNN models. The accuracy rate of rPPG with deep learning model for discriminating AF from NSR and other abnormalities was 90.0% and 97.1% in 30-s and 10-min recording, respectively. This contactless, camera-based rPPG technique with a deep-learning model achieved significantly high accuracy to discriminate AF from non-AF and may enable a feasible way for a large-scale screening or monitoring in the future.

Genetic Profiling of Cell-Free DNA From Pleural Effusion in Advanced Lung Cancer as a Surrogate for Tumor Tissue and Revealed Additional Clinical Actionable Targets.

BACKGROUND: Pleural effusion (PE) has been one of the promising sources of liquid biopsy in advanced lung cancer patients. However, its clinical utility is not widely accepted due to the lack of full estimation of its potential versus routine clinical samples. METHOD: A total of 164 advanced lung cancer patients were enrolled with 164 matched tumor tissue and PE-cfDNA, 153 accompanied plasma and 63 1PE-sDNA. RESULT: PE-cfDNA displayed significantly higher median mutant allele frequency and an overall mutation concordance rate of 65% to tissue, which was higher than PE-sDNA (43%) and plasma-cfDNA (43%). The discrepancies between PE-cfDNA and tumor tissue were high in several genes, including SMARCA4, PIK3CA, ERBB2, KM T2A, ALK and NF1. For clinically actionable mutations, the concordance rate between PE-cfDNA and tumor tissue is 87%. Eleven patients were identified with actionable mutations in PE-cfDNA and four patients benefited from PE-cfDNA-guided targeted. Meanwhile, PE-cfDNA recapitulated mutations of diverse tissue origins and provided more mutational information under the circumstance that tumor tissue or tumor tissue of different origins were unavailable. The combination of tumor tissue and PE-cfDNA profiling increased positive detection rates of patients compared to tumor tissue alone. Our finding highlighted the importance of PE-cfDNA in the optimal selection of patients for targeted therapy. CONCLUSION: The PE-cfDNA-based liquid biopsy displays better performance in the characterization of gene alterations than PE-sDNA and plasma-cfDNA. PE-cfDNA together with tumor tissue profiling optimizes comprehensively genomic profiling of lung cancer patients, which might be important for selecting patients for better treatment management.

Discovery of Potent and Selective 2-(Benzylthio)pyrimidine-based DCN1-UBC12 Inhibitors for Anticardiac Fibrotic Effects.

DCN1, a co-E3 ligase, interacts with UBC12 and activates cullin-RING ligases (CRLs) by catalyzing cullin neddylation. Although DCN1 has been recognized as an important therapeutic target for human diseases, its role in the cardiovascular area remains unknown. Here, we first found that DCN1 was upregulated in isolated cardiac fibroblasts (CFs) treated by angiotensin (Ang) II and in mouse hearts after pressure overload. Then, structure-based optimizations for DCN1-UBC12 inhibitors were performed based on our previous work, yielding compound DN-2. DN-2 specifically targeted DCN1 at molecular and cellular levels as shown by molecular modeling studies, HTRF, cellular thermal shift and co-immunoprecipitation assays. Importantly, DN-2 effectively reversed Ang II-induced cardiac fibroblast activation, which was associated with the inhibition of cullin 3 neddylation. Our findings indicate a potentially unrecognized role of DCN1 inhibition for anticardiac fibrotic effects. DN-2 may be used as a lead compound for further development.

Clinical phenotype and genetic features of 16p11.2 microdeletion-related epilepsy in children / 中国当代儿科杂志

OBJECTIVES@#To study the clinical phenotype and genetic features of 16p11.2 microdeletion-related epilepsy in children.@*METHODS@#The medical data of 200 children with epilepsy who underwent a genetic analysis of epilepsy by the whole exon sequencing technology were collected retrospectively, of whom 9 children with epilepsy had 16p11.2 microdeletion. The clinical phenotype and genetic features of the 9 children with 16p11.2 microdeletion were analyzed.@*RESULTS@#The detection rate of 16p11.2 microdeletion was 4.5% (9/200). The 9 children with 16p11.2 microdeletion were 3-10 months old. They experienced focal motor seizures with consciousness disturbance, and some of the seizures developed into generalized tonic-clonic seizures. The interictal electroencephalogram showed focal or multifocal epileptiform discharge, and all 9 children responded well to antiepileptic drugs. The 9 children had a 16p11.2 deletion fragment size of 398-906 kb, and the number of deleted genes was 23-33 which were all pathogenic mutations. The mutation was of maternal origin in 2 children, of paternal origin in 1 child, and de novo in the other children.@*CONCLUSIONS@#16p11.2 microdeletion can be detected in some children with epilepsy. Most of the 16p11.2 microdeletion is de novo mutation and large gene fragment deletion. The onset of 16p11.2 microdeletion-related epilepsy in children is mostly within 1 year of life, and the epilepsy is drug-responsive.

Clinical and electroencephalogram characteristics and treatment outcomes in children with benign epilepsy and centrotemporal spikes.

BACKGROUND: Epilepsy is a syndrome characterized by transient, rigid, paroxysmal, and repetitive central nervous system dysfunction. Prevention, control, and improvement of cognitive and behavioral dysfunction are of great significance for improving the patients' intellectual development and quality of life. Electroencephalograms (EEG) can predict an accelerated decline in cognitive function. AIM: To determine the clinical and EEG characteristics and treatment results of benign epilepsy in spiking children. METHODS: A total of 106 cases of benign epilepsy in children with myocardial spines treated at our hospital from January 2017 to January 2020 were selected. Differences in clinical data and EGG characteristics between treatment-effective/-ineffective patients were analyzed, and children's intellectual development before and after treatment evaluated using the Gesell Development Diagnostic Scale. RESULTS: EEG showed that the discharge proportion in the awake and sleep periods was 66.04%, and the peak/peak discharge was mainly single-sided, accounting for 81.13%, while the discharge generalization accounted for 31.13%. There was no significant difference in any of these variables between sexes and ages (P > 0.05). The proportion of patients with early onset (< 5 years old) and seizure frequency > 3 times/half a year was 40.00% and 60.00%, respectively; the incidence rate and seizure frequency in the younger age group (< 5 years old) were significantly higher than those in the treatment-effective group (P < 0.05), while the discharge index was significantly lower than that in the treatment-effective group (P < 0.05). The discharge index was negatively correlated with fine motor skill and language development (r = -0.274 and -0.247, respectively; P < 0.05), but not with the rest (P > 0.05). Logistic regression analysis showed that low age onset (< 5 years old) and seizure frequency were the factors affecting ineffective-treatment of benign epilepsy in children (odds ratio = 11.304 and 5.784, respectively; P < 0.05). The discharge index of the responsive group after treatment was significantly lower than that of the unresponsive group (P < 0.05). However, there was no significant difference between groups after treatment in gross and fine motor skills, adaptability, language, and personal social development (P > 0.05). CONCLUSION: The EEG of children with benign epilepsy due to spinal wave in central time zone has characteristic changes, and the therapeutic effect is influenced by age of onset and attack frequency.

Terpenoids from the Marine-Derived Fungus Aspergillus sp. RR-YLW-12, Associated with the Red Alga Rhodomela confervoides.

Two new meroterpenoids, aspermeroterpenes D and E (1 and 2), two new ophiobolin-type sesterterpenoids, the C-18 epimers of 18,19-dihydro-18-methoxy-19-hydroxyophiobolin P (6 and 7), and two new drimane-type sesquiterpenoids, 3S-hydroxystrobilactone A (8) and 6-epi-strobilactone A (9), along with 11 known terpenoids (3-5 and 10-17) were isolated from the cultures of the algicolous fungus Aspergillus sp. RR-YLW-12, derived from the red alga Rhodomela confervoides. The structures and relative configurations of new compounds were established by detailed spectroscopic analysis of NMR and HRMS experiments, and the absolute configurations were assigned by X-ray diffraction experiments and comparison of their experimental and calculated ECD spectra. Compound 1 features a rare 6/6/6/6/5 pentacyclic system with a meroterpenoid skeleton, and the structure of terretonin E (3) was revised in this study. Compound 4 showed significant inhibitory activities against three microalgae, Prorocentrum donghaiense, Heterosigma akashiwo, and Chattonella marina, with IC50 values of 10.5, 5.2, and 3.1 µg/mL, respectively.

Clinical outcomes of non-small cell lung cancer patients with leptomeningeal metastases after immune checkpoint inhibitor treatments.

OBJECTIVE: Leptomeningeal metastases (LM) occur in up to 5% of non-small cell lung cancer (NSCLC) patients and often develop after previous systemic treatments. In this article, we explored whether immune checkpoint inhibitors (ICIs) enhanced the dismal survival of patients with LM. MATERIALS AND METHODS: Data on NSCLC patients with LM prescribed ICIs were collected at the Guangdong Lung Cancer Institute. Furthermore, relevant literature was reviewed. RESULTS: A total of 255 NSCLC patients diagnosed with LM were screened from January 2015 to March 2020 at our institute. Cases reported by literature were also included. Finally, 32 NSCLC patients received ICIs after LM diagnosis; their median age was 55 years. Druggable genes were detected in 37.5% of all patients. The ICI regimens included nivolumab (n = 21), pembrolizumab (n = 9), and atezolizumab (n = 2). Ultimately, 62.5% of patients evidenced neurological symptom controlled. Two patients exhibited both intracranial and extracranial complete tumour response; one patient showed both intracranial and extracranial partial response (PR), one patient indicated intracranial PR and a systemic PR, and one patient showed central nervous system PR without extracranial response reported. The median progression-free survival (PFS) in the single-agent subgroup was 2.1 months (95% confidence interval [CI]: 1.4-2.9 months), and the median overall survival (OS) was 4.0 months (95% CI: 0.1-13.3 months). In the combined subgroup, the median PFS and OS were 3.0 months (95% CI: 1.1-4.9 months) and 5.4 months (95% CI: 0.5-10.3 months), respectively. Three patients exhibited remarkable PFS of over 20 months: all patients had ICI single agent, received cranial radiotherapy before ICI prescription, and took ICIs as second-line therapy, and two patients were EGFR/ALK wild type. Multivariate analysis showed that a better Eastern Cooperative Oncology Group Performance Status (ECOG-PS) score was associated with prolonged PFS (P = 0.04). No difference in survival was seen between monotherapy and combination therapy groups. CONCLUSION: NSCLC patients with LM may benefit from ICIs of both monotherapy and combination with other therapies, especially those with good ECOG-PS scores. Further work in this regard is required.