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Molecular genetic analysis of the cytochrome P450 family 21 subfamily A member 2 (CYP21A2) gene is challenging owing to the highly homologous with its pseudogene. A reliable approach for the large-scale population screening of CYP21A2 is required. This study aimed to establish and evaluate a capillary electrophoresis-based assay for hotspot mutation carrier screening of the CYP21A2 gene. A total of 22 different variants in the CYP21A2 gene were detected by a capillary electrophoresis-based assay consisting of single nucleotide primer extension (SNaPshot) and high-throughput ligation-dependent probe amplification (HLPA) in the Chinese population, and the results were validated by alternative methods. Among the 5376 subjects, 1.51 % (81/5376) individuals were identified as CYP21A2 pathogenic variant carriers, with a carrier rate of 1/66. A total of 11 different variants were identified, of which c.293-13A/C > G (33.33 %) was the most common variant, followed by c.844C > T (19.75 %), c.518T > A (19.75 %), and Del/Con (16.05 %). There was a 100 % concordance between capillary electrophoresis and alternative method results. Furthermore, a total of 63 individuals (1.17 %, 63/5376) carried the c.955C > T (p. Q319∗) variant, among which 61 (61/63, 96.83 %) had a duplicated CYP21A2 gene and are therefore not carriers of a CYP21A2 allele. In conclusion, the capillary electrophoresis-based assay is an accurate and effective approach for genotyping the CYP21A2 gene and has the potential for the large-scale population screening of CYP21A2.

Tripartite motif-containing protein 59 (TRIM59) is a biomarker for multiple tumors with crucial roles. However, the specific role of TRIM59 in germ cells remains largely unknown. Here, we investigated the effects and underlying regulatory mechanisms of TRIM59 on germ cells using the mouse spermatogonial cell line GC-1. Our results demonstrated that TRIM59 promoted proliferation and inhibited apoptosis of GC-1 cells. Mechanistically, TRIM59 maintained GC-1 cell behaviors through ubiquitination of AXIN1 to activate β-catenin signaling. Furthermore, activation of β-catenin signaling reversed the effects mediated by Trim59 knockdown in GC-1 cells. Collectively, our study revealed a major role and regulatory mechanism of TRIM59 in GC-1 cells, which sheds new light on the molecular pathogenesis of defects in spermatogenesis and may provide therapeutic targets for treatment of male infertility.

AbstractObjectives Chromosomal microarray analysis (CMA) has been widely applied to genetic diagnosis in miscarriages in clinical practice. However, the prognostic value of CMA testing of products of conception (POCs) after the first clinical miscarriage remains unknown. The aim of this study was to evaluate the reproductive outcomes after embryonic genetic testing by CMA in SM couples.Methods In this retrospective study, a total of 1142 SM couples referred for embryonic genetic testing by CMA, and 1022 couples were successfully followed up after CMA.Results Among 1130 cases without significant maternal cell contamination, pathogenic chromosomal abnormalities were detected in 680 cases (60.2%). The subsequent live birth rate did not differ significantly between couples with chromosomally abnormal and normal miscarriage (88.6% vs. 91.1%, p = .240), as well as the cumulative live birth rate (94.5% vs. 96.7%, p = .131). Couples with partial aneuploid miscarriage had a higher likelihood of spontaneous abortion both in the subsequent pregnancy (19.0% vs. 6.5%, p = .037) and cumulative pregnancies (19.0% vs. 6.8%, p = .044) when compared with couples with chromosomally normal miscarriage.Conclusions SM couples with chromosomally abnormal miscarriage manifested with a similar reproductive prognosis to couples with chromosomally normal miscarriage. Key messagesCMA testing of POCs could provide an accurate genetic diagnosis for couples with SM.The live birth rate of couples with partial aneuploid miscarriage was as high as couples with chromosomally normal miscarriage, despite a higher risk of adverse pregnancy event.Among couples with the most common single aneuploid miscarriage, the cumulative live birth rates of couples with trisomy 16, sex chromosomal abnormalities and trisomy 22 were 94.1%, 95.8% and 84.0%, respectively.

Although traditional fault diagnosis methods are proficient in extracting signal features, their diagnostic interpretability remains challenging. Consequently, this article proposes a conditionally interpretable generative adversarial network (C-InGAN) model for the interpretable feature fault diagnosis of bearings. Initially, the vibration signal is denoised and transformed into a frequency domain signal. The model consists of the two primary networks, each employing a convolutional layer and an attention module, generator (G) and discriminator (D), respectively. Latent code was incorporated into G to constrain the generated samples, and a discriminant layer was added to D to identify the interpretable features. During training, the two networks were alternately trained, and the feature mapping relationship of the pre-normalized encoder was learned by maximizing the information from the latent code and the discriminative result. The encoding that represents specific features in the vibration signal was extracted from the random noise. Ultimately, after completing adversarial learning, G is capable of generating a simulated signal of the specified feature, and D can assess the interpretable features in the vibration signal. The effectiveness of the model is validated through three typical experimental cases. This method effectively separates the discrete and continuous feature coding in the signal.

The rapid and accurate estimation of crop yield is of great importance for large-scale agricultural production and national food security. Using winter wheat as the research object, the effects of color indexes, texture feature and fusion index on yield estimation were investigated based on unmanned aerial vehicle (UAV) high-definition digital images, which can provide a reliable technical means for the high-precision yield estimation of winter wheat. In total, 22 visible color indexes were extracted using UAV high-resolution digital images, and a total of 24 texture features in red, green, and blue bands extracted by ENVI 5.3 were correlated with yield, while color indexes and texture features with high correlation and fusion indexes were selected to establish yield estimation models for flagging, flowering and filling stages using partial least squares regression (PLSR) and random forest (RF). The yield estimation model constructed with color indexes at the flagging and flowering stages, along with texture characteristics and fusion indexes at the filling stage, had the best accuracy, with R2 values of 0.70, 0.71 and 0.76 and RMSE values of 808.95 kg/hm2, 794.77 kg/hm2 and 728.85 kg/hm2, respectively. The accuracy of winter wheat yield estimation using PLSR at the flagging, flowering, and filling stages was better than that of RF winter wheat estimation, and the accuracy of winter wheat yield estimation using the fusion feature index was better than that of color and texture feature indexes; the distribution maps of yield results are in good agreement with those of the actual test fields. Thus, this study can provide a scientific reference for estimating winter wheat yield based on UAV digital images and provide a reference for agricultural farm management.

Continuous spring cropping of Qingke (Hordeum viilgare L. var. nudum Hook. f.) results in a reduction in grain yield in the Xizang autonomous region. However, knowledge on the influence of continuous cropping on grain yield caused by reactive oxygen species (ROS)-induced stress remains scarce. A systematic comparison of the antioxidant defensive profile at seedling, tillering, jointing, flowering, and filling stages (T1 to T5) of Qingke was conducted based on a field experiment including 23-year continuous cropping (23y-CC) and control (the first year planted) treatments. The results reveal that the grain yield and superoxide anion (SOA) level under 23y-CC were significantly decreased (by 38.67% and 36.47%), when compared to the control. The hydrogen peroxide content under 23y-CC was 8.69% higher on average than under the control in the early growth stages. The higher ROS level under 23y-CC resulted in membrane lipid peroxidation (LPO) and accumulation of malondialdehyde (MDA) at later stages, with an average increment of 29.67% and 3.77 times higher than that in control plants. Qingke plants accumulated more hydrogen peroxide at early developmental stages due to the partial conversion of SOA by glutathione (GSH) and superoxide dismutase (SOD) and other production pathways, such as the glucose oxidase (GOD) and polyamine oxidase (PAO) pathways. The reduced regeneration ability due to the high oxidized glutathione (GSSG) to GSH ratio resulted in GSH deficiency while the reduction in L-galactono-1,4-lactone dehydrogenase (GalLDH) activity in the AsA biosynthesis pathway, higher enzymatic activities (including ascorbate peroxidase, APX; and ascorbate oxidase, AAO), and lower activities of monodehydroascorbate reductase (MDHAR) all led to a lower AsA content under continuous cropping. The lower antioxidant capacity due to lower contents of antioxidants such as flavonoids and tannins, detected through both physiological measurement and metabolomics analysis, further deteriorated the growth of Qingke through ROS stress under continuous cropping. Our results provide new insights into the manner in which ROS stress regulates grain yield in the context of continuous Qingke cropping.

The non-linearity and non-stationarity of wind power data have brought great challenges to the safe operation of the power system. It is particularly important to effectively improve the accuracy of ultra-short-term prediction of wind power. Therefore, we propose an ultra-short-term wind power prediction method that particle swarm optimization-variational mode decomposition (PVMD), enhanced slime mold algorithm (ESMA) for elite opposition-based learning strategy (EOBL) and deep extreme learning machine (DELM). First, the particle swarm optimization algorithm (PSO) is used to optimize the two core parameters of the variational mode decomposition (VMD) to obtain the PVMD algorithm. The PVMD is used to decompose the original wind power data into a series of stable sub-sequences, and the rolling time series is used to analyze the sub-sequences decomposed by PVMD. Then the DELM predictive model is established and the input weights (e) and thresholds (bc) in DELM are optimized through ESMA, and the EOBL is used to improve the diversity and population quality of the slime mold population, thereby improving the global optimization performance and convergence accuracy of the slime mold algorithm (SMA), and further improving the prediction accuracy of the DELM model. Finally, each subsequence is substituted into the DELM optimized by the elite opposition based learning-slime mold algorithm (ESMA-DELM), and the prediction components are superimposed to obtain the final prediction result. Comparing the effects of several different forecasting models with the evaluation of calculation examples proves the effectiveness of the PVMD-ESMA-DELM blended forecasting model proposed in this paper, and gives a new approach for ultra-short-term wind power prediction.

Hydrogen production and refueling integrated station can play an important role in the development of hydrogen transportation and fuel cell vehicles, and actively promote the energy transformation. By using DC system for hydrogen production and refueling, the conversion links can be reduced and the system efficiency can be effectively improved. In this paper, a new scheme of DC interconnection for hydrogen production and refueling integrated station is proposed, and the modular modeling and operation capability evaluation method are proposed, including the characteristic analysis of integrated station, the modular modeling and evaluation method for multiple integrated stations under DC interconnection. The DC interconnection system of five integrated stations is constructed, and operation capability improvement of integrated stations after adopting the innovative DC interconnection scheme is analyzed. On this basis, the system simulation model based on MATLAB/Simulink and physical test platform are built to verify the effectiveness of the theoretical analysis.

Abstract Expanded carrier screening, a type of reproductive genetic testing for couples, has gained tremendous popularity for assessing the risk of passing on certain genetic conditions to offspring. Here, a carrier screening assay for 448 pathogenic variants was developed using capillary electrophoresis-based multiplex PCR technology. The capillary electrophoresis-based multiplex PCR assay achieved a sensitivity, specificity, and accuracy of 97.4%, 100%, and 99.6%, respectively, in detecting the specific variants. Among the 1915 couples (3830 individuals), 708 individuals (18.5%) were identified as carriers for at least one condition. Of the 708 carriers, 633 (89.4%) were heterozygous for one condition, 71 (10.0%) for two disorders, 3 (0.4%) for three disorders, and 1 (0.1%) for four disorders. Meanwhile, 30 (1.57%) couples were identified as at‐risk couples. This study describes an inexpensive and effective method for expanded carrier screening. The simplicity and accuracy of this approach will facilitate the clinical implementation of expanded carrier screening.

The security of power systems and electrical grids can be affected by the stochastic nature of wind energy. Therefore, reliable techniques for load forecasting and planning must be developed. This paper presents a model for short-term regional wind power forecasting based on small datasets. The model comprises three steps: input data correction, a hybrid neural network, and error analysis. First, regional numerical weather predictions (NWP) are corrected by using a stacked multilevel-denoising autoencoder (SMLDAE) to generate more effective inputs; this is the first study to use SMLDAE for NWP data correction. Second, a neural network-based hybrid model is employed for regional wind power forecasting to predict the wind power in the region. The proposed hybrid model employs three processes: multiscale mathematical morphological decomposition (MMMD), k-means clustering, and a stacked denoising autoencoder. MMMD can decompose the data directly in the time domain, thus, the signal does not need to be transferred from the time domain to the frequency domain to accomplish the decomposition. Third, a long short-term memory network is used for error analysis of the preliminary forecasted data. The preliminary results and error series are aggregated to generate the final forecasting result. For small datasets, we use multi-distribution mega-trend diffusion to augment the dataset. The proposed model was validated using a dataset consisting of data generated by regional wind farms in northern China. The results show that the proposed model enables wind forecasting at both the regional and single-farm level. Moreover, whereas most benchmark models require almost one year of data, the model requires only approximately three months of NWP data to produce reliable forecasting within the next 24 h.

The effect of pathogenic fungal infestation on berry quality and volatile organic compounds (VOCs) of Cabernet Sauvignon (CS) and Petit Manseng (PM) were investigated by using biochemical assays and gas chromatography-ion mobility spectrometry. No significant difference in diseases-affected grapes for 100-berry weight. The content of tannins and vitamin C decreased significantly in disease-affected grapes, mostly in white rot-affected PM, which decreased by 71.67% and 66.29%. The reduced total flavonoid content in diseases-affected grape, among which the least and most were anthracnose-affected PM (1.61%) and white rot-affected CS (44.74%). All diseases-affected CS had much higher titratable acid, a maximum (18.86 g/100 ml) was observed in the gray mold-affected grapes, while only anthracnose-affected grapes with a higher titratable acid level (21.8 g/100 mL) were observed in PM. A total of 61 VOCs were identified, including 14 alcohols, 13 esters, 12 aldehydes, 4 acids, 4 ketones, 1 ether, and 13 unknown compounds, which were discussed from different functional groups, such as C6-VOCs, alcohols, ester acetates, aldehydes, and acids. The VOCs of CS changed more than that of Petit Manseng’s after infection, while gray mold-affected Cabernet Sauvignon had the most change. C6-VOCs, including hexanal and (E)-2-hexenal were decreased in all affected grapes. Some unique VOCs may serve as hypothetical biomarkers to help us identify specific varieties of pathogenic fungal infestation.

Health concerns and financial losses caused by mushroom poisoning have been reported worldwide. Amanita citrinoannulata, a poisonous mushroom commonly found in China, results in a toxic reaction in humans after mistaken ingestion. To reduce the mistaken ingestion of poisonous mushrooms and to improve clinical diagnosis of mushroom poisoning, a rapid mushroom species identification method is required. Such identification methods could be advantageous in the identification of other poisonous mushroom species. This study developed two rapid and sensitive methods for the detection of A. citrinoannulata utilizing colorimetric and real-time loop-mediated isothermal amplification (LAMP) technology and specifically designed primers for the internal transcribed spacer (ITS) genes of A. citrinoannulata. The methods demonstrated high sensitivity as 0.2 ng of A. citrinoannulata DNA could be detected, with no cross-reaction with 41 non-target mushroom species. The entire detection process could be completed within 40 min without requiring complex instruments and can be observed by the naked eye. Therefore, these novel methods can be used for the identification of fresh and cooked mushroom samples and vomit samples, which contain only 1% A. citrinoannulata. Furthermore, these methods facilitate the detection of mushroom poisoning, and thus, have potential to reduce the number of mushroom poisoning-related deaths worldwide.

Abstract Background Adipocyte accumulation is a predominant feature of age-related thymic involution, but the mechanisms responsible for thymic adipogenesis remain to be elucidated. The aim of this study was to identify key regulators in thymic adipogenesis. We used rosiglitazone, a potent peroxisome proliferator-activated receptor γ (PPARγ) agonist, to induce adipogenic differentiation of OP9-DL1 cells, and investigated the differentially expressed proteins during adipogenic differentiation by using label-free quantitative proteomics. Furthermore, the effects of transforming growth factor β1 (TGF-β1) on rosiglitazone-induced adipogenic differentiation of OP9-DL1 cells as well as the underlying mechanisms were also investigated. Results Proteomic analysis identified 139 proteins differed significantly in rosiglitazone-treated cells compared with dimethyl sulphoxide (DMSO)-treated cells. Rosiglitazone-induced adipogenic differentiation was inhibited by TGF-β1 treatment in OP9-DL1 cells and primary thymic stromal cells. Real-time PCR analysis showed significant increases in PPARγ and fatty acid binding protein 4 mRNA levels in rosiglitazone-treated cells, which were inhibited by TGF-β1 treatment. TGF-β1 down-regulated PPARγ expression at both mRNA and protein levels in OP9-DL1 cells. Chromatin immunoprecipitation analysis demonstrated that TGF-β1 enhanced the binding of Smad2/3 and histone deacetylase 1, but reduced the binding of H3K14ac to the promoter of PPARγ gene. TGF-β1 partially reversed the inhibitory effects of rosiglitazone on the expression of Axin2 and β-catenin protein levels. TGF-β1 inhibited rosiglitazone-induced adipogenic transformation in OP9-DL1 cells by down-regulation of PPARγ and activation of the canonical Wnt/β-catenin signaling pathway. Conclusion Taken together, activation of TGF-β pathway may serve as a useful strategy to prevent thymic adiposity in age-related thymic involution.

It is urgently necessary to develop convenient, reliable, ultrasensitive and specific methods of ochratoxin A determination in food safety owing to its high toxicity. In the present study, an ultrasensitive and labeled-free fluorescent aptamer sensor combining real-time fluorescence with strand displacement amplification (SDA) was fabricated for the determination of OTA. In the presence of OTA, the OTA–aptamer combines with OTA, thus opening hairpins. Then, SDA primers specifically bind to the hairpin stem, which is used for subsequent amplification as a template. SDA amplification is initiated under the action of Bst DNA polymerase and nicking endonuclease. The amplified products (ssDNA) are dyed with SYBR Green II and detected with real-time fluorescence. The method has good linearity in the range of 0.01–50 ng mL−1, with the lowest limit of detection of 0.01 ng mL−1. Additionally, the fluorescent aptamer sensor shows outstanding specificity and reproducibility. Furthermore, the sensor shows excellent analytical performance in the artificial labeled detection of wheat and oat samples, with a recovery rate of 96.1~100%. The results suggest that the developed sensor has a promising potential application for the ultrasensitive detection of contaminants in food.

A method for the quantitative determination of ganoderic acid A was constructed using the principle of indirect competitive enzyme-linked immunosorbent assay (ELISA), and this method was used to determine the ganoderic A contents of Ganoderma lucidum samples in the market. The conjugate of ganoderic acid A and bovine serum albumin was used for four rounds of immunization on test rabbits to obtain rabbit antiganoderic acid A antibody IgG. The enzyme-labeled plate was coated with the conjugate of ganoderic acid A and ovalbumin. The first stage reaction in the indirect competitive ELISA was that the conjugate of ganoderic acid A in the sample competed with the conjugate coated on the enzyme-labeled plate to bind rabbit antibodies. The second stage reaction was the combination of goat anti-rabbit IgG–horseradish peroxidase and rabbit antiganoderic acid A antibody IgG. The results of the determination of ganoderic acid A standard by this method showed that the coefficient of variation of repeated wells in the group was

Agaricus bisporus lectin (ABL), which is one of the antinutritional factors in A. bisporus, is an important allergen and harmful to human health. Due to the shortcomings of the current detection methods, it is extremely urgent to establish a rapid and sensitive detection method for ABL in foods. To isolate the ssDNA aptamer of ABL, 13 rounds of subtractive systematic evolution of ligands by exponential enrichment (SELEX) selection were carried out. As a result, six candidate aptamers were selected and further examined for their binding affinity and specificity by enzyme-linked aptamer method. One aptamer (seq-41) against ABL with a high affinity and specificity was isolated and demonstrated to be the optimal aptamer whose dissociation constant reaches the nanomolar level, Kd = 31.17 ± 0.1070 nM. Based on seq-41, an aptamer-AuNPs colorimetric method was established to detect ABL with a linear range of 0.08∼1.70 μg/mL and the detection limit is 0.062 μg/mL. This study provides a novel aptamer-AuNPs colorimetric method with high sensitivity and specificity for detection of ABL and a novel strategy for development of detection method of fungal or plant allergens.

Pulmonary hypertension (PH) is characterized by vascular remodeling caused by marked proliferation of pulmonary artery smooth muscle cells (PASMCs). Andrographolide (ANDRO) is a potent anti-inflammatory agent which possesses antioxidant, and has anticarcinogenic activity. The present study examined potential therapeutic effects of ANDRO on PH in both chronic hypoxia and Sugen5416/hypoxia mouse PH models. Effects of ANDRO were also studied in cultured human PASMCs isolated from either healthy donors or PH patients. In vivo, ANDRO decreased distal pulmonary arteries (PAs) remodeling, mean PA pressure and right ventricular hypertrophy in chronic hypoxia- and Sugen/hypoxia-induced PH in mice. ANDRO reduced cell viability, proliferation and migration, but increased cell apoptosis in the PASMCs isolated from PH patients. ANDRO also reversed the dysfunctional bone morphogenetic protein receptor type-2 (BMPR2) signaling, suppressed [Ca2+]i elevation, reactive oxygen species (ROS) generation, and the upregulated expression of IL-6 and IL-8, ET-1 and VEGF in PASMCs from PH patients. Moreover, ANDRO significantly attenuated the activation of TLR4/NF-κB, ERK- and JNK-MAPK signaling pathways and reversed the inhibition of p38-MAPK in PASMCs of PH patients. Further, ANDRO blocked hypoxia-triggered ROS generation by suppressing NADPH oxidase (NOX) activation and augmenting nuclear factor erythroid 2-related factor 2 (Nrf2) expression both in vitro and in vivo. Conventional pulmonary vasodilators have limited efficacy for the treatment of severe PH. We demonstrated that ANDRO may reverse pulmonary vascular remodeling through modulation of NOX/Nrf2-mediated oxidative stress and NF-κB-mediated inflammation. Our findings suggest that ANDRO may have therapeutic value in the treatment of PH.

Abstract Background X‐linked intellectual disability type Nascimento (XIDTN), caused by mutations in ubiquitin‐conjugating enzyme E2A (UBE2A) gene, is characterized by moderate to severe intellectual disability, impaired speech, urogenital anomalies, skin abnormalities, and dysmorphic facial features. Methods Whole‐exome sequence was carried out in the patients, and the variant of disease‐associated gene in the patient and his parents was confirmed by Sanger sequencing. RNA transcript analysis by reverse transcription (RT)‐PCR was performed to assess the potential effects of the splice site mutation. Results A novel splicing mutation (c.331‐2A>G) in UBE2A gene, inherited from his mother, was identified in a Chinese boy with intellectual disability and impaired speech. Furthermore, brain magnetic resonance imaging showed multiple patchy hyperintensity in bilateral centrum ovale. RT‐PCR demonstrated that this variant generated a novel transcript with a deletion of 29 nucleotides in exon 6 (r.331_359del), resulting in a frameshift mutation (p.L112SfsX17). Conclusion Ultimately, he was diagnosed with XIDTN by genetic analysis. To the best of our knowledge, this is the first case report of this syndrome in China with a confirmed molecular diagnosis. Our case not only expands the mutation spectrum of UBE2A, but also provides additional insights into the genetic and phenotypic heterogeneity of XIDTN as well as phenotype–genotype correlations in this disease.

Abstract Background Next‐generation sequencing has been invaluable to delineate the genetic etiology of neurodevelopmental disorders (NDDs) in recent years. BCL11B, encoding Cys2His2 zinc finger transcription factor, is essential for the development of immune and neural systems. Methods Herein, we describe a Chinese girl presenting craniofacial abnormalities, developmental delay and intellectual disability with speech impairment. Exomes of genes were enriched with the Agilent SureSelect QXT ALL Human Exon V6 kit and sequenced on Illumina Hiseq 2500 platform. Results After variants filtering and annotation, we identified a de novo heterozygous 11bp frameshift mutation NM_138576.4: c.2190_2200delGGACGCACGAC (p.Thr730Thrfs*151) in exon 4 of BCL11B, which is expected to escape nonsense‐mediated mRNA decay and probably result in a truncated protein with lack of the C‐terminal DNA‐binding zinc‐finger domains. Conclusion This is the first report of NDD caused by a BCL11B variant in a Chinese population. The mutation identified in this report broadens the knowledge of mutation spectrum of BCL11B and might help in genetic counseling and reducing reproductive risk.

Microdeletions in Y-chromosomal azoospermia factor (AZF) regions have been regarded as the risk factor of spermatogenic failure (SF). However, AZF-linked duplications or complex copy number variants (CNVs) (deletion + duplication) were rarely studied. In this study, we performed multiplex ligation-dependent probe amplification (MLPA) analysis on 402 fertile healthy male controls and 423 idiopathic infertile SF patients (197 azoospermia and 226 oligozoospermia) in Han Chinese population. In total, twenty-four types of AZF-linked CNVs were identified in our study, including eleven novel CNVs (one deletion, seven duplications, and three complex CNVs). Our study revealed that AZFc-linked duplications and the instability of Y chromosome might be associated with spermatogenesis. Besides, the complex CNVs (b2/b3 deletion + DAZ1/2 duplication) were confirmed to increase genetic risks for SF in Han Chinese population. This study illustrated a spectrum of AZF-linked CNVs and presented valuable information for understanding the clinical significance of AZF-linked CNVs in male infertility.

Periconceptional folic acid (FA) supplementation is recommended to prevent neural tube defects and other birth defects. After 20 years mandate food fortification with FA, serum concentration of folate and unmetabolized FA increased significantly in the North American population. But whether excess FA intake impairs neurodevelopment and behavior is still controversial. Here, we treated mice with approximately 2.5-fold (moderate dose of FA, MFA) or 10-fold (high dose of FA, HFA) the dietary requirement of FA 1 week before mating and throughout pregnancy and lactation, and examined behaviors in adult male offspring using open field test, three-chamber sociability and social novelty test, elevated plus maze, rotarod and Morris water maze. We found that early life MFA supplementation increased long-term body weight gain in adults, elevated anxiety-like behavior, and impaired social preference, motor learning and spatial learning ability without modifying motor ability and spatial memory. In contrast, HFA supplementation only induced mild behavioral abnormality. RNA sequencing revealed that FA supplementation altered the expression of brain genes at weaning, among which Fos and related genes were significantly up-regulated in MFA mice compared with control and HFA mice. Quantitative real time-PCR (qRT-PCR) and western blots confirmed the increase of these genes. Our results suggested that FA supplementation during early life stage affected gene expression in weaning mice, and exhibited long-term impairments in adult behaviors in a dose-sensitive manner.

Adipocyte deposition is believed to be a primary characteristic of age-related thymic involution. Herein, we cultured primary thymic stromal cells (TSCs), used rosiglitazone, a potent peroxisome proliferator-activated receptor γ (PPARγ) agonist, to induce adipogenic differentiation, and investigated the differentially expressed genes during adipogenic differentiation by using RNA-sequencing analysis. Furthermore, the effects of Notch1 on rosiglitazone-induced adipogenic differentiation of TSCs as well as the underlying mechanisms were also investigated. As a result, we identified a total of 1737 differentially expressed genes, among which 965 genes were up-regulated and 772 genes were down-regulated in rosiglitazone-treated cells compared with control cells. Gene ontology (GO) enrichment analysis showed that the GO terms were enriched in metabolic process, intracellular, and protein binding. Kyoto encyclopedia of genes and genomes (KEGG) analysis showed that a number of pathways, including ubiquitin mediated proteolysis, PPAR signaling pathway, and mammalian target of rapamycin (mTOR) signaling pathway were predominantly over-represented. Meanwhile, overexpression of Notch1 suppressed and inhibition of Notch1 promoted rosiglitazone-induced adipogenic differentiation in TSCs, and the pro-adipogenic effects of the Notch inhibitor DAPT were associated with the activation of autophagy. Taken together, our results suggest that Notch1 is a key regulator in thymic adipogenesis and may serve as a potential target to hinder thymic adiposity in age-related thymic involution.

Merosin-deficient CMD type 1A (MDC1A), caused by mutations of laminin subunit alpha 2 (LAMA2), is a predominant subtype of congenital muscular dystrophy (CMD). Herein, we described a Chinese patient with MDC1A who was admitted to hospital 17 days after birth because of marasmus and feeding difficulties. Mutations were identified by targeted capture and next generation sequencing (NGS) and further confirmed by Sanger sequencing. Paternity was confirmed by short tandem repeat analysis. Physical examination showed malnutrition, poor suck and appendicular hypotonia. Her serum CK levels were 2483 and 1962 U/L at 2 and 4 months of age, respectively. Brain magnetic resonance imaging performed at 1 month of age presented hyperintensity on T2-weighted images, T1-weighted images in parietal and occipital lobes, and diffusion-weighted image (DWI) as well as hypointensity on fluid attenuated inversion recovery (FLAIR) image; however, the cerebellum and corpus arenaceum were normal. At 7 months of age, delayed developmental milestones were observed, and she failed to turn her body over and raise her head up. A point mutation (c.1782+2T > G) and a frameshift duplication (c.8217dupT) in the LAMA2 gene were identified by targeted capture and NGS and further confirmed by Sanger sequencing. Moreover, genotyping with multiple short tandem repeat markers confirmed paternity to demonstrate that the point mutation is de novo. The frameshift duplication (c.8217dupT), inherited from her mother, was predicted to cause a substitution of Pro (P) to Ser (S) at the 2740th amino-acid residue and generate a prematurely truncated protein. The in silico analysis suggests that the mutation (c.1782+2T > G) may lead to aberrant splicing of LAMA2. Our case further confirms the heterogeneous clinical spectrum of MDC1A and presents two novel LAMA2 mutations to expand the mutation spectrum of MDC1A.

Asthma is a common chronic respiratory disease. In a previous study, we found several circulating microRNA signatures associated with childhood asthma and selected miR-3162-3p for subsequent studies. Since the target proteins and underlying molecular mechanisms of miR-3162-3p in asthma etiopathogenesis are not well characterized, we designed this study to clarify its role. We employed bioinformatics and quantitative PCR methods as a first step to determine the target of miR-3162-3p, and we elucidated β-catenin. Luciferase assays and western blot analysis confirmed β-catenin as a direct target of miR-3162-3p as the 3'-untranslated region of β-catenin mRNA possesses a specific miR-3162-3p pairing site. The correlation between the expression levels of miR-3162-3p and β-catenin is confirmed by quantitative PCR and western blot studies in A549, Beas-2B and H1299 cell lines and OVA-induced asthma mouse model. Of note, upregulation of the endogenous miR-3162-3p level is concomitant with the reduction of β-catenin mRNA and protein expression levels. MiR-3162-3p antagomir treatment antagonizes the endogenous miR-3162-3p and effectively rescues the attenuation of endogenous β-catenin in OVA-induced asthmatic mice, which alleviates airway hyperresponsiveness and ameliorates airway inflammation. Collectively, our findings suggest a novel relationship between miR-3162-3p and β-catenin and clarify their mechanistic role in asthma etiopathogenesis.

Most of the Alzheimer's disease (AD)-linked mutations in amyloid precursor protein (APP), which cause abnormal production of β-amyloid (Aβ), are localized at the major β-secretase-and γ-secretase cleavage sites. In this study, using an APP-knockout mouse neuronal cell line, our data demonstrated that at the P2-P1 positions of the ɛ-cleavage site at Aβ49 and the ζ-cleavage site at Aβ46, aromatic amino acids caused a strong reduction in total Aβ. On the other hand, residues with a long side chain caused a decrease in Aβ40 and a concomitant increase in Aβ42 and Aβ38. These findings indicate that the structures of the substituting residues at these key positions strongly determine the efficiency and preference of γ-secretase-mediated APP processing, which determines the ratio of different secreted Aβ species, a crucial factor in the disease development. Our findings provide new insight into the mechanisms of γ-secretase-mediated APP processing and, specifically, into why most AD-linked APP mutations are localized at major γ-secretase cleavage sites. This information may contribute to the development of methods of prevention and treatment of Alzheimer's disease aimed at modulating γ-secretase activity.

Abstract The influence maximization problem that has drawn a great deal of attention from researchers aims to identify a subset of influential spreaders that can maximize the expected influence spread in social networks. Existing works on the problem primarily concentrate on developing non-adaptive policies, where all seeds will be ignited at the very beginning of the diffusion after the identification. However, in non-adaptive policies, budget redundancy could occur as a result of some seeds being naturally infected by other active seeds during the diffusion process. In this paper, the adaptive seeding policies are investigated for the intractable adaptive influence maximization problem. Based on deep learning model, a novel approach named graph convolutional networks with self-attention mechanism (ATGCN) is proposed to address the adaptive influence maximization as a regression task. A controlling parameter is introduced for the adaptive seeding model to make a tradeoff between the spreading delay and influence coverage. The proposed approach leverages the self-attention mechanism to dynamically assign importance weight to node representations efficiently to capture the node influence feature information relevant to the adaptive influence maximization problem. Finally, intensive experimental findings on six real-world social networks demonstrate the superiorities of the adaptive seeding policy over the state-of-the-art baseline methods to the conventional influence maximization problem. Meanwhile, the proposed adaptive seeding policy ATGCN improves the influence spread rate by up to 7% in comparison to the existing state-of-the-art greedy-based adaptive seeding policy.

Abstract Reducing interface nonradiative recombination is important for realizing highly efficient perovskite solar cells. In this work, we develop a synergistic bimolecular interlayer (SBI) strategy via 4-methoxyphenylphosphonic acid (MPA) and 2-phenylethylammonium iodide (PEAI) to functionalize the perovskite interface. MPA induces an in-situ chemical reaction at the perovskite surface via forming strong P-O-Pb covalent bonds that diminish the surface defect density and upshift the surface Fermi level. PEAI further creates an additional negative surface dipole so that a more n-type perovskite surface is constructed, which enhances electron extraction at the top interface. With this cooperative surface treatment, we greatly minimize interface nonradiative recombination through both enhanced defect passivation and improved energetics. The resulting p-i-n device achieves a stabilized power conversion efficiency of 25.53% and one of the smallest nonradiative recombination induced V oc loss of only 59 mV reported to date. We also obtain a certified efficiency of 25.05%. This work sheds light on the synergistic interface engineering for further improvement of perovskite solar cells.

Exploring effective and efficient strategies for identifying influential nodes from social networks as seeds to promote the propagation of influence remains a crucial challenge in the field of influence maximization (IM), which has attracted significant research efforts. Deep learning-based approaches have been adopted as an alternative promising solution to the IM problem. However, a robust model that captures the associations between network information and node influence needs to be investigated, while concurrently considering the effects of the overlapped influence on training labels. To address these challenges, a GCNT model, which integrates Graph Convolutional Networks with Graph Transformers, is introduced in this paper to capture the intricate relationships among the topology of the network, node attributes, and node influence effectively. Furthermore, an innovative method called Greedy-LIE is proposed to generate labels to alleviate the issue of overlapped influence spread. Moreover, a Mask mechanism specially tailored for the IM problem is presented along with an input embedding balancing strategy. The effectiveness of the GCNT model is demonstrated through comprehensive experiments conducted on six real-world networks, and the model shows its competitive performance in terms of both influence maximization and computational efficiency over state-of-the-art methods.