Vulto-van Silfhout-de Vries syndrome caused by de novo variants of DEAF1 gene: a case report and literature review

Vulto-van Silfhout-de Vries syndrome (VSVS; MIM 615828) is an extremely rare autosomal dominant disorder with unknown incidence. It is always caused by de novo heterozygous pathogenic variants in the DEAF1 gene, which encodes deformed epidermal autoregulatory factor-1 homology. VSVS is characterized by mild to severe intellectual disability (ID) and/or global developmental delay (GDD), seriously limited language expression, behavioral abnormalities, somnipathy, and reduced pain sensitivity. In this study, we present a Chinese boy with moderate GDD and ID, severe expressive language impairment, behavioral issues, autism spectrum disorder (ASD), sleeping dysfunction, high pain threshold, generalized seizures, imbalanced gait, and recurrent respiratory infections as clinical features. A de novo heterozygous pathogenic missense variant was found in the 5th exon of DEAF1 gene, NM_021008.4 c.782G>C (p. Arg261Pro) variant by whole exome sequencing (WES). c.782G>C had not been previously reported in genomic databases and literature. According to the ACMG criteria, this missense variant was considered to be “Likely Pathogenic”. We diagnosed the boy with VSVS both genetically and clinically. At a follow-up of 2.1 years, his seizures were well controlled after valproic acid therapy. In addition, the child’s recurrent respiratory infections improved at 3.5 years of age, which has not been reported in previous individuals. Maybe the recurrent respiratory infections like sleep problems reported in the literature are not permanent but may improve naturally over time. The literature review showed that there were 35 individuals with 28 different de novo pathogenic variants of DEAF1-related VSVS. These variants were mostly missense and the clinical manifestations were similar to our patient. Our study expands the genotypic and phenotypic profiles of de novo DEAF1

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Dechlorination of Hexachlorobenzene in Contaminated Soils Using a Nanometallic Al/CaO Dispersion Mixture: Optimization through Response Surface Methodology

Hexachlorobenzene (HCB) contamination of soils remains a significant environmental challenge all over the world. Reductive stabilization is a developing technology that can decompose the HCB with a dechlorination process. A nanometallic Al/CaO (n-Al/CaO) dispersion mixture was developed utilizing ball-milling technology in this study. The dechlorination efficiency of HCB in contaminated soils by the n-Al/CaO grinding treatment was evaluated. Response surface methodology (RSM) was employed to investigate the effects of three variables (soil moisture content, n-Al/CaO dosage and grinding time) and the interactions between these variables under the Box-Behnken Design (BBD). A high regression coefficient value (R2 = 0.9807) and low p value (<0.0001) of the quadratic model indicated that the model was accurate in predicting the experimental results. The optimal soil moisture content, n-Al/CaO dosage, and grinding time were found to be 7% (m/m), 17.7% (m/m), and 24 h, respectively, in the experimental ranges and levels. Under optimal conditions, the dechlorination efficiency was 80%. The intermediate product analysis indicated that dechlorination was the process by stepwise loss of chloride atoms. The main pathway observed within 24 h was HCB → pentachlorobenzene (PeCB) → 1,2,3,4-tetrachlorobenzene (TeCB) and 1,2,4,5-TeCB. The results indicated that the moderate soil moisture content was crucial for the hydrodechlorination of HCB. A probable mechanism was proposed wherein water acted like a hydrogen donor and promoted the hydrodechlorination process. The potential application of n-Al/CaO is an environmentally-friendly and cost-effective option for decontamination of HCB-contaminated soils

Snow Depth Estimation with GNSS-R Dual Receiver Observation

Two estimation methods using a dual GNSS (Global Navigation Satellite System) receiver system are proposed. The dual-frequency combination method combines the carrier phase observations of dual-frequency signals, whereas the single-frequency combination method combines the pseudorange and carrier phase observations of a single-frequency signal, both of which are geometry-free strictly combination and free of the effect of ionospheric delay. Theoretical models are established in the offline phase to describe the relationship between the spectral peak frequency of the combined sequence and the antenna height. A field experiment was conducted recently and the data processing results show that the root mean squared error (RMSE) of the dual-frequency combination method is 5.04 cm with GPS signals and 6.26 cm with BDS signals, which are slightly greater than the RMSE of 4.16 cm produced by the single-frequency combination method of L1 band with GPS signals. The results also demonstrate that the proposed two combination methods and the SNR method achieve similar performance. A dual receiver system enables the better use of GNSS signal carrier phase observations for snow depth estimation, achieving increased data utilization

Micro-Three-Coil Sensor with Dual Excitation Signals Use Asymmetric Magnetic Fields to Distinguish between Non-Ferrous Metals

Intelligent operation and maintenance technology for vessels can ensure the safety of the entire system, especially for the development of intelligent and unmanned marine technology. The material properties of metal abrasive particles in oil could demonstrate the wear areas of the marine mechanical system because different components consist of different materials. However, most sensors can only roughly separate metallic contaminants into ferromagnetic and non-ferromagnetic particles but cannot differentiate them in greater detail. A micro-three-coil sensor is designed in this paper; the device applies different excitation signals to two excitation coils to differentiate materials, based on the different effects of different material particles in the asymmetric magnetic field. Therefore, a particle’s material can be judged by the shape of the induction electromotive force output signal from the induction coil, while the particle size can be judged by the amplitude of the signal. Experimental results show that the material differentiation of four different types of particles can be achieved, namely, of aluminum, iron, 304 stainless steel, and carbon steel. This newly designed sensor provides a new research prospect for the realization of an inductive detection method to distinguish non-ferrous metals and a reference for the subsequent detection of metal contaminants in oil and other liquids

Trend of Surface Air Temperature in Eastern China and Associated Large-Scale Climate Variability over the Last 100 Years

Abstract Using the reconstructed continuous and homogenized surface air temperature (SAT) series for 16 cities across eastern China (where the greatest industrial developments in China have taken place) back to the nineteenth century, the authors examine linear trends of SAT. The regional-mean SAT over eastern China shows a warming trend of 1.52°C (100 yr)−1 during 1909–2010. It mainly occurred in the past 4 decades and this agrees well with the variability in another SAT series developed from a much denser station network (over 400 sites) across this part of China since 1951. This study collects population data for 245 sites (from these 400+ locations) and split these into five equally sized groups based on population size. Comparison of these five groups across different durations from 30 to 60 yr in length indicates that differences in population only account for between 9% and 24% of the warming since 1951. To show that a larger urbanization impact is very unlikely, the study additionally determines how much can be explained by some large-scale climate indices. Anomalies of large-scale climate indices such as the tropical Indian Ocean SST and the Siberian atmospheric circulation systems account for at least 80% of the total warming trends.</jats:p

The Comparison of Seven Models to Simulate the Transport and Deposition of Polydisperse Particles under Favorable Conditions in a Saturated Medium

Polydisperse particles are ubiquitous in both the natural and engineered environment, and the precise prediction of the transport and capture of polydisperse particles in a saturated medium is crucial. Several efforts (Yao model, RT model, TE model, MPFJ model, NG model, MHJ model, and MMS model) were developed to obtain accurate correlation equations for the particle capture probability (single-collector removal efficiency), but the applicability of the existing models to the entire porous medium and the retention characteristic of the polydisperse particles are still unclear. In this study, sand column experiments were undertaken to investigate the transport and capture processes of the polydisperse particles in the saturated medium. The mass density was employed to quantize the effects of particle polydispersity and incorporated into the depth-dependent deposition rate. The experimental results showed that the polydisperse particles formed a hyper-exponential retention profile even under favorable conditions (no repulsion). The excellent agreement between the results obtained from the MMS model and the experimentally observed results of the breakthrough curves (BTCs), as well as the retention profiles demonstrated the validation of the MMS model, as the correlation coefficient and the standard average relative error were 0.99 and 0.005, respectively. The hyper-exponential retention profile is caused by the uneven capture of the polydisperse particles by the porous medium. This study highlights the influences of particle polydispersity on particle transport and capture in a saturated porous medium

Identification of pyroptosis-associated genes with diagnostic value in calcific aortic valve disease

BackgroundCalcific aortic valve disease (CAVD) is one of the most prevalent valvular diseases and is the second most common cause for cardiac surgery. However, the mechanism of CAVD remains unclear. This study aimed to investigate the role of pyroptosis-related genes in CAVD by performing comprehensive bioinformatics analysis.MethodsThree microarray datasets (GSE51472, GSE12644 and GSE83453) and one RNA sequencing dataset (GSE153555) were obtained from the Gene Expression Omnibus (GEO) database. Pyroptosis-related differentially expressed genes (DEGs) were identified between the calcified and the normal valve samples. LASSO regression and random forest (RF) machine learning analyses were performed to identify pyroptosis-related DEGs with diagnostic value. A diagnostic model was constructed with the diagnostic candidate pyroptosis-related DEGs. Receiver operating characteristic (ROC) curve analysis was performed to estimate the diagnostic performances of the diagnostic model and the individual diagnostic candidate genes in the training and validation cohorts. CIBERSORT analysis was performed to estimate the differences in the infiltration of the immune cell types. Pearson correlation analysis was used to investigate associations between the diagnostic biomarkers and the immune cell types. Immunohistochemistry was used to validate protein concentration.ResultsWe identified 805 DEGs, including 319 down-regulated genes and 486 up-regulated genes. These DEGs were mainly enriched in pathways related to the inflammatory responses. Subsequently, we identified 17 pyroptosis-related DEGs by comparing the 805 DEGs with the 223 pyroptosis-related genes. LASSO regression and RF algorithm analyses identified three CAVD diagnostic candidate genes (TREM1, TNFRSF11B, and PGF), which were significantly upregulated in the CAVD tissue samples. A diagnostic model was constructed with these 3 diagnostic candidate genes. The diagnostic model and the 3 diagnostic candidate genes showed good diagnostic performances with AUC values &gt;0.75 in both the training and the validation cohorts based on the ROC curve analyses. CIBERSORT analyses demonstrated positive correlation between the proportion of M0 macrophages in the valve tissues and the expression levels of TREM1, TNFRSF11B, and PGF.ConclusionThree pyroptosis-related genes (TREM1, TNFRSF11B and PGF) were identified as diagnostic biomarkers for CAVD. These pyroptosis genes and the pro-inflammatory microenvironment in the calcified valve tissues are potential therapeutic targets for alleviating CAVD