Observational study to preliminarily characterize the audiological profile of chinese children with williams syndrome

Purpose It is essential to investigate the audiological profiles of Williams syndrome in a multicultural context. This study aims to examine the characteristics and management of hearing loss in Chinese children with Williams syndrome and provide references for future clinical management. Method Between January 2007 and March 2022, families with at least 1 WS patient was recruited from the Newborn Cohort Study of Hearing Loss. Audiological tests were performed, and then appropriate medical management was offered. Furthermore, an overview of the hearing loss phenotype in Williams syndrome in different locations was reviewed. Results A total of two families with at least 1 Williams syndrome patient were recruited from the Newborn Cohort Study of Hearing Loss (ChiCTR2100049765). We identified moderately severe sensorineural or conductive hearing loss that emerged as early as the infancy period in Williams syndrome subjects in Chinese children. Our results extended the reported onset ages of hearing loss in WS from late childhood or early adulthood to the infancy period. We also found that with early diagnosis, proper management, and regular monitoring, children with Williams syndrome could return to a normal or near-normal school life. Conclusions Our study demonstrated the distinct hearing profile in Chinese children with Williams syndrome for the first time. This cohort of WS subjects extends the reported onset ages of hearing loss in WS from late childhood or early adulthood to the infancy period, indicating the importance of clinicians screening and monitoring the hearing status of individuals with WS as early as possible. These data provide references for otolaryngologists and paediatricians to inform the clinical understanding and management of hearing loss in Williams syndrome

Perinatal risk factors and preliminary prediction of conductive hearing loss in infancy

Purpose To investigate the perinatal risk factors for conductive hearing loss (CHL) in infancy and develop an initial prediction model to facilitate accurate diagnosis and early detection of CHL. Method This retrospective study utilized data from the Newborn Cohort Study of Hearing Loss (ChiCTR2100049765). Infants who underwent diagnostic audiological assessments at our hospital between January 2003 and June 2024 were included. Data analysis was conducted using R (version 4.4.1) to construct an initial prediction model for CHL in infancy, applying the LASSO regression technique. Results A total of 661 infants (1322 ears) were included, with 1253 ears in the normal hearing group and 69 ears in the CHL group. Statistically significant differences were observed between the groups in the following factors: parent-reported infant response to sound, craniofacial deformities, neonatal hemolysis, jaundice treatment, and neonatal hypoglycemia. A multivariate prediction model and nomogram for CHL in infancy were developed and validated, achieving an accuracy of 92.5% and a specificity of 91.3%. ConclusionsThis study identified key risk factors for CHL in infancy and developed a preliminary predictive model, improving the diagnostic accuracy for CHL. Improved diagnostic precision can decrease misdiagnoses, reduce delays in treatment, and limit unnecessary antimicrobial prescriptions for infants

A triplex crystal digital PCR for the detection of genotypes I and II African swine fever virus

African swine fever (ASF) is a highly contagious and lethal viral disease that causes severe hemorrhagic fever in pigs. It keeps spreading around the world, posing a severe socioeconomic risk and endangering biodiversity and domestic food security. ASF first outbroke in China in 2018, and has spread to most provinces nationwide. Genotypes I and II ASF virus (ASFV) as the etiological pathogens have been found in China. In this study, three pairs of specific primers and probes targeting the ASFV B646L gene, F1055L gene, and E183L gene were designed to detect universal, genotype I, and genotype II strains, respectively. A triplex crystal digital PCR (cdPCR) was established on the basis of optimizing various reaction conditions. The assay demonstrated remarkably sensitive with low limits of detection (LODs) of 5.120, 4.218, 4.588 copies/reaction for B646L, F1055L, and E183L gene, respectively; excellent repeatability with 1.24–2.01% intra-assay coefficients of variation (CVs) and 1.32–2.53% inter-assay CVs; good specificity for only detection of genotypes I and II ASFV, without cross-reactivity with PCV2, PRV, SIV, PRRSV, PEDV, FMDV, and CSFV. The triplex cdPCR was used to test 1,275 clinical samples from Guangxi province of China, and the positivity rates were 5.05, 3.22, and 1.02% for genotype I, genotype II, and co-infection of genotypes I and II, respectively. These 1,275 clinical samples were also detected using a reported reference triplex real-time quantitative PCR (qPCR), and the agreements of detection results between these two methods were more than 98.98%. In conclusion, the developed triplex cdPCR could be used as a rapid, sensitive, and accurate method to detect and differentiate genotypes I and II strains of ASFV

Decoupling and antiresonance in electronic transport through a quantum dot chain embodied in an Aharonov-Bohm interferometer

Electronic transport through a quantum dot chain embodied in an Aharonov-Bohm interferometer is theoretically investigated. In such a system, it is found that only for the configurations with the same-numbered quantum dots side-coupled to the quantum dots in the arms of the interferometer, some molecular states of the quantum dot chain decouple from the leads. Namely, in the absence of magnetic flux all odd molecular states decouple from the leads, but all even molecular states decouple from the leads when an appropriate magnetic flux is introduced. Interestingly, the antiresonance position in the electron transport spectrum is independent of the change of the decoupled molecular states. In addition, when considering the many-body effect within the second-order approximation, we show that the emergence of decoupling gives rise to the apparent destruction of electron-hole symmetry. By adjusting the magnetic flux through either subring, some molecular states decouple from one lead but still couple to the other, and then some new antiresonances occur.Comment: 7 pages, 7 figure

Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report

The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing. In this Mobile AI challenge, the target was to develop an efficient end-to-end AI-based image signal processing (ISP) pipeline replacing the standard mobile ISPs that can run on modern smartphone GPUs using TensorFlow Lite. The participants were provided with a large-scale Fujifilm UltraISP dataset consisting of thousands of paired photos captured with a normal mobile camera sensor and a professional 102MP medium-format FujiFilm GFX100 camera. The runtime of the resulting models was evaluated on the Snapdragon's 8 Gen 1 GPU that provides excellent acceleration results for the majority of common deep learning ops. The proposed solutions are compatible with all recent mobile GPUs, being able to process Full HD photos in less than 20-50 milliseconds while achieving high fidelity results. A detailed description of all models developed in this challenge is provided in this paper

The prognostic value of whole-genome DNA methylation in response to Leflunomide in patients with Rheumatoid Arthritis

ObjectiveAlthough Leflunomide (LEF) is effective in treating rheumatoid arthritis (RA), there are still a considerable number of patients who respond poorly to LEF treatment. Till date, few LEF efficacy-predicting biomarkers have been identified. Herein, we explored and developed a DNA methylation-based predictive model for LEF-treated RA patient prognosis.MethodsTwo hundred forty-five RA patients were prospectively enrolled from four participating study centers. A whole-genome DNA methylation profiling was conducted to identify LEF-related response signatures via comparison of 40 samples using Illumina 850k methylation arrays. Furthermore, differentially methylated positions (DMPs) were validated in the 245 RA patients using a targeted bisulfite sequencing assay. Lastly, prognostic models were developed, which included clinical characteristics and DMPs scores, for the prediction of LEF treatment response using machine learning algorithms.ResultsWe recognized a seven-DMP signature consisting of cg17330251, cg19814518, cg20124410, cg21109666, cg22572476, cg23403192, and cg24432675, which was effective in predicting RA patient’s LEF response status. In the five machine learning algorithms, the support vector machine (SVM) algorithm provided the best predictive model, with the largest discriminative ability, accuracy, and stability. Lastly, the AUC of the complex model(the 7-DMP scores with the lymphocyte and the diagnostic age) was higher than the simple model (the seven-DMP signature, AUC:0.74 vs 0.73 in the test set).ConclusionIn conclusion, we constructed a prognostic model integrating a 7-DMP scores with the clinical patient profile to predict responses to LEF treatment. Our model will be able to effectively guide clinicians in determining whether a patient is LEF treatment sensitive or not

Structural, Stability, Dynamic and Binding Properties of the ALS-Causing T46I Mutant of the hVAPB MSP Domain as Revealed by NMR and MD Simulations

T46I is the second mutation on the hVAPB MSP domain which was recently identified from non-Brazilian kindred to cause a familial amyotrophic lateral sclerosis (ALS). Here using CD, NMR and molecular dynamics (MD) simulations, we characterized the structure, stability, dynamics and binding capacity of the T46I-MSP domain. The results reveal: 1) unlike P56S which we previously showed to completely eliminate the native MSP structure, T46I leads to no significant disruption of the native secondary and tertiary structures, as evidenced from its far-UV CD spectrum, as well as Cα and Cβ NMR chemical shifts. 2) Nevertheless, T46I does result in a reduced thermodynamic stability and loss of the cooperative urea-unfolding transition. As such, the T46I-MSP domain is more prone to aggregation than WT at high protein concentrations and temperatures in vitro, which may become more severe in the crowded cellular environments. 3) T46I only causes a 3-fold affinity reduction to the Nir2 peptide, but a significant elimination of its binding to EphA4. 4) EphA4 and Nir2 peptide appear to have overlapped binding interfaces on the MSP domain, which strongly implies that two signaling networks may have a functional interplay in vivo. 5) As explored by both H/D exchange and MD simulations, the MSP domain is very dynamic, with most loop residues and many residues on secondary structures highly fluctuated or/and exposed to bulk solvent. Although T46I does not alter overall dynamics, it does trigger increased dynamics of several local regions of the MSP domain which are implicated in binding to EphA4 and Nir2 peptide. Our study provides the structural and dynamic understanding of the T46I-causing ALS; and strongly highlights the possibility that the interplay of two signaling networks mediated by the FFAT-containing proteins and Eph receptors may play a key role in ALS pathogenesis