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Oral wounds under diabetic conditions display a significant delay during the healing process, mainly due to oxidative stress-induced inflammatory status and abnormal immune responses. Besides, the wet and complicated dynamic environment of the oral cavity impedes stable treatment of oral wounds. To overcome these, a biomimetic hydrogel adhesive was innovatively developed based on a mussel-inspired multifunctional structure. The adhesive displays efficient adhesion and mechanical harmony on the oral mucosa through enhanced bonding in an acidic proinflammatory environment. The bioadhesive hydrogel exhibits excellent antioxidative properties by mimicking antioxidative enzymatic activities to reverse reactive oxygen species (ROS)-mediated immune disorders. Experiments on oral wounds of diabetic rats showed that this hydrogel adhesive could effectively protect against mucosal wounds and obviously shorten the inflammatory phase, thus promoting the wound-healing process. Therefore, this study offers a promising therapeutic choice with the potential to advance the clinical treatment of diabetic oral wounds.

With the change of social consumption concept, women have gradually become the largest consumer group in the advertising audience. Based on this change in consumption concept, in the past two years, advertisements featuring men have been overwhelming. The Internet has brought about the interconnection of everything. Mobile terminals have made information spread faster and more widely. New media platforms such as Weibo, WeChat and Tiktok have developed rapidly and become an important way for users to obtain information. As a new media platform with the fastest growth rate of daily active users, short video has attracted a large influx of capital, and major brands and enterprises have adjusted their advertising media delivery strategies to layout short video. People's understanding of masculinity is also quietly changing. Masculinity is no longer rigid and single. With the diversified development of masculinity images, the endorsement images in male cosmetics advertisements are increasingly rich and diversified. Gender reverse advertising has developed rapidly, especially in the cosmetics industry. According to this hot phenomenon, this paper specifically analyzes the development history, reasons, development status, advantages and disadvantages of gender reverse advertising, points out a series of problems existing in gender reverse advertising, and then puts forward corresponding development countermeasures.

BACKGROUND: Known genetic causes of congenital heart disease (CHD) explain METHODS: We tested de novo variants from trio studies of 2649 CHD probands and their parents, as well as rare (allele frequency, − 6 ) variants from 4472 CHD probands in the Pediatric Cardiac Genetics Consortium through a combined computational and in vitro approach. RESULTS: We identified 53 de novo and 74 rare variants in CHD cases that alter splicing and thus are loss of function. Of these, 77 variants are in known dominant, recessive, and candidate CHD genes, including KMT2D and RBFOX2 . In 1 case, we confirmed the variant’s predicted impact on RNA splicing in RNA transcripts from the proband’s cardiac tissue. Two probands were found to have 2 loss-of-function variants for recessive CHD genes HECTD1 and DYNC2H1 . In addition, SpliceAI—a predictive algorithm for altered RNA splicing—has a positive predictive value of ≈93% in our cohort. CONCLUSIONS: Through assessment of RNA splicing, we identified a new loss-of-function variant within a CHD gene in 78 probands, of whom 69 (1.5%; n=4472) did not have a previously established genetic explanation for CHD. Identification of splice-altering variants improves diagnostic classification and genetic diagnoses for CHD. REGISTRATION: URL: https://clinicaltrials.gov ; Unique identifier: NCT01196182.

Pathogenic variants in the CACNA1A gene have been associated with episodic ataxia type 2, familial hemiplegic migraine, and spinocerebellar ataxia 6. With increasing use of clinical genetic testing, associations have expanded to include developmental delay, epilepsy, paroxysmal dystonia, and neuropsychiatric disorders. We report 47 individuals with 33 unique likely pathogenic or pathogenic CACNA1A variants. A machine learning method, funNCion, was used to predict loss-of-function (LoF)/gain-of-function (GoF) impact of genetic variants, and a heuristic severity score was designed to analyze genotype/phenotype correlations. Commonly reported phenotypes include developmental delay/intellectual disability (96%), hemiplegic migraines (36%), episodic ataxia type 2 (32%), epilepsy (55%), autism spectrum disorder (23%), and paroxysmal tonic upward gaze (36%). Severity score was significantly higher for predicted GoF variants, variants in the S5/S6 helices, and the recurrent p.Val1392Met variant. Seizures/status epilepticus were correlated with GoF and were more frequent in those with the p.Val1392Met variant. Our findings demonstrate a breadth of disease severity in CACNA1A-related disease and suggest that the clinical phenotypic heterogeneity likely reflects diverse molecular phenotypes. A better understanding of the natural history of CACNA1A-related disease and genotype/phenotype correlations will help inform prognosis and prepare for future clinical trials.

In the US, newborn screening (NBS) is a unique health program that supports health equity and screens virtually every baby after birth, and has brought timely treatments to babies since the 1960's. With the decreasing cost of sequencing and the improving methods to interpret genetic data, there is an opportunity to add DNA sequencing as a screening method to facilitate the identification of babies with treatable conditions that cannot be identified in any other scalable way, including highly penetrant genetic neurodevelopmental disorders (NDD). However, the lack of effective dietary or drug-based treatments has made it nearly impossible to consider NDDs in the current NBS framework, yet it is anticipated that any treatment will be maximally effective if started early. Hence there is a critical need for large scale pilot studies to assess if and how NDDs can be effectively screened at birth, if parents desire that information, and what impact early diagnosis may have. Here we attempt to provide an overview of the recent advances in NDD treatments, explore the possible framework of setting up a pilot study to genetically screen for NDDs, highlight key technical, practical, and ethical considerations and challenges, and examine the policy and health system implications.

Missense variants have highly variable effects and effect size, which often makes it challenging to distinguish pathogenic and non-pathogenic variants and subsequently implicate new genes for disease association in studies of de novo and inherited rare variants. Importantly, missense variants can be the sole molecular mechanism for some genetic disorders, and so statistical approaches tailored for the analysis of missense variants are critical. Analysis of the clustering of missense variants is a promising approach which leverages the fact that missense variants in protein domains often have similar effects on function. Here we describe a new clustering analysis approach, AlphaCluster, a statistical method which quantifiably analyzes the spatial clustering of de novo variants by mapping missense residues onto the protein tertiary structure. We show that our approach can quantify the evidence supporting pathogenic missense variants and increase the power to detect clustering when compared to available genomic clustering tools. Using AlphaCluster, we identified genes newly implicated in autism spectrum disorder and neurodevelopmental disorders (NDD). We also apply AlphaCluster to protein complexes and detect an association between the gamma aminobutyric acid receptor complex (GABA-A 𝛼1𝛽2𝛾2 receptor).

Bassoon (BSN) is a component of a hetero-dimeric presynaptic cytomatrix protein that orchestrates neurotransmitter release with Piccolo (PCLO) from glutamatergic neurons throughout the brain. Heterozygous missense variants inBSNhave previously been associated with neurodegenerative disorders in humans. We performed an exome-wide association analysis of ultra-rare variants in about 140,000 unrelated individuals from the UK Biobank to search for new genes associated with obesity. We found that rare heterozygous predicted loss of function (pLoF) variants inBSNare associated with higher BMI with log10-p value of 11.78 in the UK biobank cohort. The association was replicated in the All of Us whole genome sequencing data. Additionally, we have identified two individuals (one of whom has ade novovariant) with a heterozygous pLoF variant in a cohort of early onset or extreme obesity at Columbia University. Like the individuals identified in the UKBB and All of us Cohorts, these individuals have no history of neurobehavioral or cognitive disability. Heterozygosity for pLoFBSNvariants constitutes a new etiology for obesity.

To understand the genetic contribution to primary pediatric cardiomyopathy, we performed exome sequencing in a large cohort of 528 children with cardiomyopathy. Using clinical interpretation guidelines and targeting genes implicated in cardiomyopathy, we identified a genetic cause in 32% of affected individuals. Cardiomyopathy sub-phenotypes differed by ancestry, age at diagnosis, and family history. Infants < 1 year were less likely to have a molecular diagnosis (p < 0.001). Using a discovery set of 1,703 candidate genes and informatic tools, we identified rare and damaging variants in 56% of affected individuals. We see an excess burden of damaging variants in affected individuals as compared to two independent control sets, 1000 Genomes Project (p < 0.001) and SPARK parental controls (p < 1 × 10(−16)). Cardiomyopathy variant burden remained enriched when stratified by ancestry, variant type, and sub-phenotype, emphasizing the importance of understanding the contribution of these factors to genetic architecture. Enrichment in this discovery candidate gene set suggests multigenic mechanisms underlie sub-phenotype-specific causes and presentations of cardiomyopathy. These results identify important information about the genetic architecture of pediatric cardiomyopathy and support recommendations for clinical genetic testing in children while illustrating differences in genetic architecture by age, ancestry, and sub-phenotype and providing rationale for larger studies to investigate multigenic contributions.

Background: Congenital heart disease (CHD) is the most common major congenital anomaly and causes significant morbidity and mortality. Epidemiologic evidence supports a role of genetics in the development of CHD. Genetic diagnoses can inform prognosis and clinical management. However, genetic testing is not standardized among individuals with CHD. We sought to develop a list of validated CHD genes using established methods and to evaluate the process of returning genetic results to research participants in a large genomic study. Methods: Two-hundred ninety-five candidate CHD genes were evaluated using a ClinGen framework. Sequence and copy number variants involving genes in the CHD gene list were analyzed in Pediatric Cardiac Genomics Consortium participants. Pathogenic/likely pathogenic results were confirmed on a new sample in a clinical laboratory improvement amendments-certified laboratory and disclosed to eligible participants. Adult probands and parents of probands who received results were asked to complete a post-disclosure survey. Results: A total of 99 genes had a strong or definitive clinical validity classification. Diagnostic yields for copy number variants and exome sequencing were 1.8% and 3.8%, respectively. Thirty-one probands completed clinical laboratory improvement amendments-confirmation and received results. Participants who completed postdisclosure surveys reported high personal utility and no decision regret after receiving genetic results. Conclusions: The application of ClinGen criteria to CHD candidate genes yielded a list that can be used to interpret clinical genetic testing for CHD. Applying this gene list to one of the largest research cohorts of CHD participants provides a lower bound for the yield of genetic testing in CHD.

Accurate variant pathogenicity predictions are important in genetic studies of human diseases. Inframe insertion and deletion variants (indels) alter protein sequence and length, but not as deleterious as frameshift indels. Inframe indel Interpretation is challenging due to limitations in the available number of known pathogenic variants for training. Existing prediction methods largely use manually encoded features including conservation, protein structure and function, and allele frequency to infer variant pathogenicity. Recent advances in deep learning modeling of protein sequences and structures provide an opportunity to improve the representation of salient features based on large numbers of protein sequences. We developed a new pathogenicity predictor for SHort Inframe iNsertion and dEletion (SHINE). SHINE uses pretrained protein language models to construct a latent representation of an indel and its protein context from protein sequences and multiple protein sequence alignments, and feeds the latent representation into supervised machine learning models for pathogenicity prediction. We curated training data from ClinVar and gnomAD, and created two test datasets from different sources. SHINE achieved better prediction performance than existing methods for both deletion and insertion variants in these two test datasets. Our work suggests that unsupervised protein language models can provide valuable information about proteins, and new methods based on these models can improve variant interpretation in genetic analyses.

SUMMARYAside from its role as the universal energy source of the cell, mitochondria also control many aspects of cell behavior. In an intact tissue, whether all cells require mitochondria function to the same extent, and how mitochondria insufficiency impacts cell behavior are poorly understood. Here we show that in the mouse lung epithelium, inactivation of LONP1, an energy ATP-dependent protease that functions in the mitochondria to degrade unfolded and misfolded proteins, led to mitochondria deficiency. In the naïve epithelium of the developing lung, loss ofLonp1obliterated cell proliferation and differentiation. In the adult airway epithelium during homeostasis, loss ofLonp1led to selective death of terminally differentiated multiciliated cells, leading to a cascade of progenitor activation to replace lost cells. In the adult airway epithelium following influenza infection, loss ofLonp1led to failure of airway progenitor migration into the damaged alveolar region. Bulk and single cell transcriptomic analysis revealed that one branch of the ER stress pathways, namely integrated stress response (ISR), is ectopically upregulated in mutants under all three conditions. Inactivation of core ISR transcription factor ATF4 in theLonp1mutant airway reversed abovementioned phenotypes. Taken together, our findings demonstrate that depending on a cellular context, intact mitochondria function is required in either progenitor or progeny cells, and is essential for cell proliferation, survival or migration in the mammalian lung.

A polyethyleneimine (PEI)-functionalized polymer substrate polar stationary phase was prepared for hydrophilic interaction chromatography (HILIC) by grafting PEI onto poly(styrene-divinylbenzene) (PS-DVB) microspheres. The phase shows a U-shape retention profile and it exhibits typical hydrophilic characteristic when the organic solvent fraction in the mobile phase is60%. Hydrogen bonding, anion exchange, and hydrophobic interaction are involved in the retention mechanism. Good separation and unique selectivity for acidic, basic and neutral polar analytes were achieved. It showed extremely low column bleed (comparable to that of blank) under gradient elution mode (even to 50% fraction of water) and wide pH tollerance range (at least 1-13).

Inframe insertion and deletion variants (indels) alter protein sequence and length. Accurate pathogenicity predictions are important in genetic studies of human diseases. Indel Interpretation is challenging due to limitations in the available number of known pathogenic variants for training. Existing methods largely use manually encoded features including conservation, protein structure and function, and allele frequency. Recent advances in deep learning modeling of protein sequences and structures provide an opportunity to improve the representation of salient features based on large numbers of protein sequences. We developed a new pathogenicity predictor for SHort Inframe iNsertion and dEletion (SHINE). SHINE uses pre-trained protein language models to construct a latent representation of an indel and its protein context from protein sequences and multiple protein sequence alignments, and feeds the latent representation into supervised machine learning models for pathogenicity prediction. We curated training data from ClinVar and gnomAD, and created two test datasets from different sources. SHINE achieved better prediction performance than existing methods for both deletion and insertion variants in these two test datasets. Our work suggests that unsupervised protein language models can provide valuable information about proteins, and new methods based on these models can improve variant interpretation in genetic analyses.

Exome sequencing has been widely used in genetic studies of human diseases and clinical genetic diagnosis. Accurate detection of copy number variants (CNVs) is important to fully utilize exome sequencing data. However, due to the nature of noisy data, none of the existing methods can achieve high precision and high recall rate at the same time. A common practice is to perform filtration with quality metrics followed by manual inspection of read depth of candidate CNV regions. This approach does not scale in large studies. To address this issue, we present a deep transfer learning method, CNV-espresso, for confirming rare CNVs from exome sequencing data in silico. CNV-espresso encodes candidate CNV regions from exome sequencing data as images and uses convolutional neural networks to classify the image into different copy numbers. We trained and evaluated CNV-espresso on a large-scale offspring-parents trio exome sequencing dataset, using inherited CNVs in probands as positives and CNVs with mendelian errors as negatives. We further tested the performance using samples that have both exome and whole genome sequencing (WGS) data. Assuming the CNVs detected from WGS data as proxy of ground truth, CNV-espresso significantly improves precision while keeping recall almost intact, especially for CNVs that span small number of exons in exome data. We conclude that CNV-espresso is an effective method to replace most of manual inspection of CNVs in large-scale exome sequencing studies.

Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores (PRS), monogenic risks, family history, and clinical risk assessments via a Genome Informed Risk Assessment (GIRA) report and will assess uptake of care recommendations after return of results.GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.Return of a novel report for communicating monogenic, polygenic, and family history based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Genomic disorders (GDs) are associated with many comorbid outcomes, including CKD. Identification of GDs has diagnostic utility.We examined the prevalence of GDs among participants in the Chronic Kidney Disease in Children (CKiD) cohort II (We found nine out of 248 (3.6%) CKiD II participants carried a GD, replicating prior findings in pediatric CKD. We also identified GDs in 72 out of 6679 (1.1%) adult patients with CKD in the CRIC, CU-CKD, and FIND cohorts, compared with 199 out of 30,746 (0.65%) GDs in controls (OR, 1.7; 95% CI, 1.3 to 2.2). Among adults with CKD, we found recurrent GDs at the 1q21.1, 16p11.2, 17q12, and 22q11.2 loci. The 17q12 GD (diagnostic of renal cyst and diabetes syndrome) was most frequent, present in 1:252 patients with CKD and diabetes. In the PheWAS, dialysis and neuropsychiatric phenotypes were the top associations with GDs. In CRIC participants, GDs were associated with lower serum magnesium, lower educational achievement, and higher mortality risk.Undiagnosed GDs are detected both in children and adults with CKD. Identification of GDs in these patients can enable a precise genetic diagnosis, inform prognosis, and help stratify risk in clinical studies. GDs could also provide a molecular explanation for nephropathy and comorbidities, such as poorer neurocognition for a subset of patients.

Mitochondrial complex V plays an important role in oxidative phosphorylation by catalyzing the generation of ATP. Most complex V subunits are nuclear encoded and not yet associated with recognized Mendelian disorders. Using exome sequencing, we identified a rare homozygous splice variant (c.87+3AG) in ATP5PO, the complex V subunit which encodes the oligomycin sensitivity conferring protein, in three individuals from two unrelated families, with clinical suspicion of a mitochondrial disorder. These individuals had a similar, severe infantile and often lethal multi-systemic disorder that included hypotonia, developmental delay, hypertrophic cardiomyopathy, progressive epileptic encephalopathy, progressive cerebral atrophy, and white matter abnormalities on brain MRI consistent with Leigh syndrome. cDNA studies showed a predominant shortened transcript with skipping of exon 2 and low levels of the normal full-length transcript. Fibroblasts from the affected individuals demonstrated decreased ATP5PO protein, defective assembly of complex V with markedly reduced amounts of peripheral stalk proteins, and complex V hydrolytic activity. Further, expression of human ATP5PO cDNA without exon 2 (hATP5PO-∆ex2) in yeast cells deleted for yATP5 (ATP5PO homolog) was unable to rescue growth on media which requires oxidative phosphorylation when compared to the wild type construct (hATP5PO-WT), indicating that exon 2 deletion leads to a non-functional protein. Collectively, our findings support the pathogenicity of the ATP5PO c.87+3AG variant, which significantly reduces but does not eliminate complex V activity. These data along with the recent report of an affected individual with ATP5PO variants, add to the evidence that rare biallelic variants in ATP5PO result in defective complex V assembly, function and are associated with Leigh syndrome.

We present VBASS, a Bayesian method that integrates single-cell expression and de novo variant (DNV) data to improve power of disease risk gene discovery. VBASS models disease risk prior as a function of expression profiles, approximated by deep neural networks. It learns the weights of neural networks and parameters of Poisson likelihood models of DNV counts jointly from expression and genetics data. On simulated data, VBASS shows proper error rate control and better power than state-of-the-art methods. We applied VBASS to published datasets and identified more candidate risk genes with supports from literature or data from independent cohorts.

The well-established manifestation of mitochondrial mutations in functional cardiac disease (e.g., mitochondrial cardiomyopathy) prompted the hypothesis that mitochondrial DNA (mtDNA) sequence and/or copy number (mtDNAcn) variation contribute to cardiac defects in congenital heart disease (CHD). MtDNAcns were calculated and rare, non-synonymous mtDNA mutations were identified in 1,837 CHD-affected proband-parent trios, 116 CHD-affected singletons, and 114 paired cardiovascular tissue/blood samples. The variant allele fraction (VAF) of heteroplasmic variants in mitochondrial RNA from 257 CHD cardiovascular tissue samples was also calculated. On average, mtDNA from blood had 0.14 rare variants and 52.9 mtDNA copies per nuclear genome per proband. No variation with parental age at proband birth or CHD-affected proband age was seen. mtDNAcns in valve/vessel tissue (320 ± 70) were lower than in atrial tissue (1,080 ± 320, p= 6.8E-21), which were lower than in ventricle tissue (1,340 ± 280, p= 1.4E-4). The frequency of rare variants in CHD-affected individual DNA was indistinguishable from the frequency in an unaffected cohort, and proband mtDNAcns did not vary from those of CHD cohort parents. In both the CHD and the comparison cohorts, mtDNAcns were significantly correlated between mother-child, father-child, and mother-father. mtDNAcns among people with European (mean= 52.0), African (53.0), and Asian haplogroups (53.5) were calculated and were significantly different for European and Asian haplogroups (p= 2.6E-3). Variant heteroplasmic fraction (HF) in blood correlated well with paired cardiovascular tissue HF (r= 0.975) and RNA VAF (r= 0.953), which suggests blood HF is a reasonable proxy for HF in heart tissue. We conclude that mtDNA mutations and mtDNAcns are unlikely to contribute significantly to CHD risk.