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Acetylene and aldehydes are coupled through cyclometallation and silane-mediated σ-bond metathesis to synthesize various vinyl-substituted alcohols. This reaction features good functional group tolerance using acetylene as a C2 synthon.

The highly efficient homo-dimerization and cross-coupling of propargyl esters via migratory insertion of the copper-allenylidenes have been developed to give various 1-en-3,5-diynes, [5]cumulenes and 1,3-diynes with moderate to excellent yields.

Background Biomedical language translation requires multi-lingual fluency as well as relevant domain knowledge. Such requirements make it challenging to train qualified translators and costly to generate high-quality translations. Machine translation represents an effective alternative, but accurate machine translation requires large amounts of in-domain data. While such datasets are abundant in general domains, they are less accessible in the biomedical domain. Chinese and English are two of the most widely spoken languages, yet to our knowledge, a parallel corpus does not exist for this language pair in the biomedical domain. Description We developed an effective pipeline to acquire and process an English-Chinese parallel corpus from the New England Journal of Medicine (NEJM). This corpus consists of about 100,000 sentence pairs and 3,000,000 tokens on each side. We showed that training on out-of-domain data and fine-tuning with as few as 4000 NEJM sentence pairs improve translation quality by 25.3 (13.4) BLEU for en$$\rightarrow$$ → zh (zh$$\rightarrow$$ → en) directions. Translation quality continues to improve at a slower pace on larger in-domain data subsets, with a total increase of 33.0 (24.3) BLEU for en$$\rightarrow$$ → zh (zh$$\rightarrow$$ → en) directions on the full dataset. Conclusions The code and data are available at https://github.com/boxiangliu/ParaMed.

A copper-catalyzed three-component carboboration of acetylene with B2Pin2 and Michael acceptors was achieved. The small acetylene molecule enabled faster rate of borylcupration and easier C–C bond formation compared with substituted alkynes.

Genome-wide association studies (GWAS) of neurological diseases have identified thousands of variants associated with disease phenotypes. However, the majority of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atlas of the adult human brain through profiling of single-cell chromatin accessibility landscapes and three-dimensional (3D) chromatin interactions of diverse adult brain regions across a cohort of cognitively healthy individuals. We developed a machine-learning classifier to integrate this multi-omic framework and predict dozens of functional single-nucleotide polymorphisms (SNPs) for Alzheimer’s disease (AD) and Parkinson’s disease (PD), nominating target genes and cell types for previously orphaned GWAS loci. Moreover, we dissected the complex inverted haplotype of the MAPT (encoding tau) PD risk locus, identifying putative ectopic regulatory interactions in neurons that may mediate this disease association. This work expands our understanding of inherited variation and provides a roadmap for the epigenomic dissection of causal regulatory variation in disease.

Correction for ‘Synthesis of vinyl-substituted alcohols using acetylene as a C2 building block’ by Zhicong Lin et al., Chem. Sci., 2023, https://doi.org/10.1039/d2sc06400f.

Non-small cell lung cancer (NSCLC) metastatic to the brain leptomeninges is rapidly fatal, cannot be biopsied, and cancer cells in the cerebrospinal fluid (CSF) are few; therefore, available tissue samples to develop effective treatments are severely limited. This study aimed to converge single-cell RNA-seq and cell-free RNA (cfRNA) analyses to both diagnose NSCLC leptomeningeal metastases (LM), and to use gene expression profiles to understand progression mechanisms of NSCLC in the brain leptomeninges. NSCLC patients with suspected LM underwent withdrawal of CSF via lumbar puncture. Four cytology-positive CSF samples underwent single-cell capture (n = 197 cells) by microfluidic chip. Using robust principal component analyses, NSCLC LM cell gene expression was compared to immune cells. Massively parallel qPCR (9216 simultaneous reactions) on human CSF cfRNA samples compared the relative gene expression of patients with NSCLC LM (n = 14) to non-tumor controls (n = 7). The NSCLC-associated gene, CEACAM6, underwent in vitro validation in NSCLC cell lines for involvement in pathologic behaviors characteristic of LM. NSCLC LM gene expression revealed by single-cell RNA-seq was also reflected in CSF cfRNA of cytology-positive patients. Tumor-associated cfRNA (e.g., CEACAM6, MUC1) was present in NSCLC LM patients’ CSF, but not in controls (CEACAM6 detection sensitivity 88.24% and specificity 100%). Cell migration in NSCLC cell lines was directly proportional to CEACAM6 expression, suggesting a role in disease progression. NSCLC-associated cfRNA is detectable in the CSF of patients with LM, and corresponds to the gene expression profile of NSCLC LM cells. CEACAM6 contributes significantly to NSCLC migration, a hallmark of LM pathophysiology.

Formaldehyde (CH2O) is the most common volatile organic pollutant in the indoor environment, which can directly cause respiratory system diseases of humans. As a new type of material, graphene-based single atom adsorbent has the advantages of large specific surface and high adsorption activity, which can provide a new direction for formaldehyde removal. In this paper, the adsorption characteristics of formaldehyde on graphene-based single atom adsorbents were investigated through density functional theory (DFT) calculations. According to the analysis of geometric structure, electron transfer and density of states (DOS), the adsorption of formaldehyde belongs to a stable chemisorption and the largest adsorption energy of formaldehyde is −2.27 eV, which is a combined action of electron transfer and hybridization effect. Formaldehyde will be preferentially adsorbed on single atom adsorbent in side-on model. The effect of N doping and desorption temperature were studied through searching for linear relationship and Gibbs free energy calculation, respectively. Doping N atoms into graphene plane can significantly improve the adsorption strength of formaldehyde through modulating the charge of metal atoms. The charge of metal atoms can be an efficient descriptor for adsorption energy of formaldehyde. CH2O plays a dominant role in competitive adsorption between O2, N2 and CH2O. We expect that this theoretical study can lay a foundation for the experimental investigations.

Background Molecular and cellular changes are intrinsic to aging and age-related diseases. Prior cross-sectional studies have investigated the combined effects of age and genetics on gene expression and alternative splicing; however, there has been no long-term, longitudinal characterization of these molecular changes, especially in older age. Results We perform RNA sequencing in whole blood from the same individuals at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging at a population and individual level. We observe that individuals are more similar to their own expression profiles later in life than profiles of other individuals their own age. We identify 1291 and 294 genes differentially expressed and alternatively spliced with age, as well as 529 genes with outlying individual trajectories. Further, we observe a strong correlation of genetic effects on expression and splicing between the two ages, with a small subset of tested genes showing a reduction in genetic associations with expression and splicing in older age. Conclusions These findings demonstrate that, although the transcriptome and its genetic regulation is mostly stable late in life, a small subset of genes is dynamic and is characterized by a reduction in genetic regulation, most likely due to increasing environmental variance with age.

Mealworms are commercially reared on diets comprising of mixed grains. Substituting grains with agro-food industry by-products creates opportunities to valorize by-products and lowers the cost of insect rearing practices. In this study, three by-products (mushroom spent corn stover, highly denatured soybean meal, and spirit distillers’ grains) as treatments and wheat bran as control were used to rear mealworms. For growth performance, mealworms dry weights reared on three by-products were 53–67% of control. Feed conversion and utilization ratios ranged from 36 to 45% and 50 to 57% of control, respectively. For nutritional profile, protein and fat fractions ranged from 70 to 76% and 6 to 12% of mealworm dry weight, respectively. Leucine, lysine, methionine + cysteine, threonine, and valine were the limiting amino acids comparing with FAO/WHO requirements. The major fatty acids were linoleic acid (C18:2, 30–38%), oleic acid (C18:1, 24–34%), and palmitic acid (C16:0, 14–17%). The comparable nutritional profile demonstrated the potential to rear mealworms using these three cheap by-products. The results provide a reference for insect farmers to formulate the diets for obtaining specific insect products with desired nutrient composition.

In response to various stimuli, vascular smooth muscle cells (SMCs) can de-differentiate, proliferate and migrate in a process known as phenotypic modulation. However, the phenotype of modulated SMCs in vivo during atherosclerosis and the influence of this process on coronary artery disease (CAD) risk have not been clearly established. Using single-cell RNA sequencing, we comprehensively characterized the transcriptomic phenotype of modulated SMCs in vivo in atherosclerotic lesions of both mouse and human arteries and found that these cells transform into unique fibroblast-like cells, termed 'fibromyocytes', rather than into a classical macrophage phenotype. SMC-specific knockout of TCF21-a causal CAD gene-markedly inhibited SMC phenotypic modulation in mice, leading to the presence of fewer fibromyocytes within lesions as well as within the protective fibrous cap of the lesions. Moreover, TCF21 expression was strongly associated with SMC phenotypic modulation in diseased human coronary arteries, and higher levels of TCF21 expression were associated with decreased CAD risk in human CAD-relevant tissues. These results establish a protective role for both TCF21 and SMC phenotypic modulation in this disease.

It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene1. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches2–5. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases6–8. This includes muscle biopsies from patients with undiagnosed rare muscle disorders6,9, and cultured fibroblasts from patients with mitochondrial disorders7. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution. A diagnostic tool based on blood RNA-seq is shown to identify causal genes and variants linked to clinical phenotypes in individuals with rare diseases for which whole-exome genetic sequencing was uninformative.

Octenylsuccinate starch ester, also called pure gum, is non-toxic and odourless modified starch which is widely used in many food fields. This study synthesized pure gum in a reaction kettle using the low molecular weight trehalose and octenyl succinic acid. An orthogonal test was carried out to find how the reaction factors affect the synthetization of octenylsuccinic acid polysaccharide ester and to optimize the reaction at single factor level. The optimal products were obtained using 1:2 of octenylsuccinic acid: alginic acid, catalysed by 0.1% p-toluenesulfonic acid catalyst for 1.5 h at 200°C under vacuum conditions. The gained product contains up to 46% of seaweed gel monoesters. The degree of esterification of the polysaccharide is controlled by the use of the small-molecule trehalose. Compared with the traditional methods, our process can reduce raw material cost and improve emulsification stability of pure gum. These all can significantly improve the market competitiveness of pure gum products.

Additional file 10 Review history

Leakage problems are common in the water supply pipeline system, which will threaten the health of residents and cause economic losses. Negative pressure wave (NPW) technology calculates the time difference through the inflection point to locate the leak. However, due to the nonlinear and nonstationary characteristics of the pressure signal, it is difficult to obtain an accurate inflection point of the NPW by the traditional method. Therefore, the advantages of applying variational mode decomposition (VMD) in NPW technology are explored. Firstly, the correlation coefficient and permutation entropy (PE) are used for effective intrinsic mode function (IMF) component selection and parameter optimization. Thus, an adaptive denoising method based on VMD (AD-VMD) is presented. Then, to effectively separate the detail features of the NPW, a novel inflection point extraction method based on VMD (IPE-VMD) is proposed. Simulation and experimental results show that AD-VMD can effectively suppress noise interference and conserve the mutation characteristic of the leakage. IPE-VMD can obtain a distinct maximum peak at the inflection point and has good robustness to noise interference. This method can calculate the time difference precisely and stably. In addition, the accuracy of the leak location is verified. The average relative positioning error is 5.13%.

Background COVID-19 became a global pandemic not long after its identification in late 2019. The genomes of SARS-CoV-2 are being rapidly sequenced and shared on public repositories. To keep up with these updates, scientists need to frequently refresh and reclean data sets, which is an ad hoc and labor-intensive process. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. Objective To address these challenges, we developed CoV-Seq, an integrated web server that enables simple and rapid analysis of SARS-CoV-2 genomes. Methods CoV-Seq is implemented in Python and JavaScript. The web server and source code URLs are provided in this article. Results Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are displayed in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is available for high-throughput processing. In addition, we aggregated all publicly available SARS-CoV-2 sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID), National Center for Biotechnology Information (NCBI), European Nucleotide Archive (ENA), and China National GeneBank (CNGB), and extracted genetic variants from these sequences for download and downstream analysis. The CoV-Seq database is updated weekly. Conclusions We have developed CoV-Seq, an integrated web service for fast and easy analysis of custom SARS-CoV-2 sequences. The web server provides an interactive module for the analysis of custom sequences and a weekly updated database of genetic variants of all publicly accessible SARS-CoV-2 sequences. We believe CoV-Seq will help improve our understanding of the genetic underpinnings of COVID-19.

BACKGROUND COVID-19 became a global pandemic not long after its identification in late 2019. The genomes of SARS-CoV-2 are being rapidly sequenced and shared on public repositories. To keep up with these updates, scientists need to frequently refresh and reclean data sets, which is an ad hoc and labor-intensive process. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. OBJECTIVE To address these challenges, we developed CoV-Seq, an integrated web server that enables simple and rapid analysis of SARS-CoV-2 genomes. METHODS CoV-Seq is implemented in Python and JavaScript. The web server and source code URLs are provided in this article. RESULTS Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are displayed in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is available for high-throughput processing. In addition, we aggregated all publicly available SARS-CoV-2 sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID), National Center for Biotechnology Information (NCBI), European Nucleotide Archive (ENA), and China National GeneBank (CNGB), and extracted genetic variants from these sequences for download and downstream analysis. The CoV-Seq database is updated weekly. CONCLUSIONS We have developed CoV-Seq, an integrated web service for fast and easy analysis of custom SARS-CoV-2 sequences. The web server provides an interactive module for the analysis of custom sequences and a weekly updated database of genetic variants of all publicly accessible SARS-CoV-2 sequences. We believe CoV-Seq will help improve our understanding of the genetic underpinnings of COVID-19.

Background To investigate the epigenetic and transcriptional mechanisms of coronary artery disease (CAD) risk, as well as the functional regulation of chromatin structure and function, we create a catalog of genetic variants associated with three stages of transcriptional cis-regulation in primary human coronary artery vascular smooth muscle cells (HCASMCs). Results We use a pooling approach with HCASMC lines to map regulatory variants that mediate binding of the CAD-associated transcription factor TCF21 with ChIPseq studies (bQTLs), variants that regulate chromatin accessibility with ATACseq studies (caQTLs), and chromosomal looping with Hi-C methods (clQTLs). We examine the overlap of these QTLs and their relationship to smooth muscle-specific genes and transcription factors. Further, we use multiple analyses to show that these QTLs are highly associated with CAD GWAS loci and correlate to lead SNPs where they show allelic effects. By utilizing genome editing, we verify that identified functional variants can regulate both chromatin accessibility and chromosomal looping, providing new insights into functional mechanisms regulating chromatin state and chromosomal structure. Finally, we directly link the disease-associated TGFB1-SMAD3 pathway to the CAD-associated FN1 gene through a response QTL that modulates both chromatin accessibility and chromosomal looping. Conclusions Together, these studies represent the most thorough mapping of multiple QTL types in a highly disease-relevant primary cultured cell type and provide novel insights into their functional overlap and mechanisms that underlie these genomic features and their relationship to disease risk.

Human neurodegenerative disorders often exhibit similar pathologies, suggesting a shared aetiology. Key pathological features of Parkinson’s disease (PD) are also observed in other neurodegenerative diseases. Pantothenate Kinase-Associated Neurodegeneration (PKAN) is caused by mutations in the human PANK2 gene, which catalyzes the initial step of de novo CoA synthesis. Here, we show that fumble (fbl), the human PANK2 homolog in Drosophila, interacts with PINK1 genetically. fbl and PINK1 mutants display similar mitochondrial abnormalities, and overexpression of mitochondrial Fbl rescues PINK1 loss-of-function (LOF) defects. Dietary vitamin B5 derivatives effectively rescue CoA/acetyl-CoA levels and mitochondrial function, reversing the PINK1 deficiency phenotype. Mechanistically, Fbl regulates Ref(2)P (p62/SQSTM1 homolog) by acetylation to promote mitophagy, whereas PINK1 regulates fbl translation by anchoring mRNA molecules to the outer mitochondrial membrane. In conclusion, Fbl (or PANK2) acts downstream of PINK1, regulating CoA/acetyl-CoA metabolism to promote mitophagy, uncovering a potential therapeutic intervention strategy in PD treatment.

SummaryCOVID-19 has become a global pandemic not long after its inception in late 2019. SARS-CoV-2 genomes are being sequenced and shared on public repositories at a fast pace. To keep up with these updates, scientists need to frequently refresh and reclean datasets, which is ad hoc and labor-intensive. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. In order to address these challenges, we developed CoV-Seq, a webserver to enable simple and rapid analysis of SARS-CoV-2 genomes. Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are presented in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is also available for high-throughput processing.Availability and ImplementationCoV-Seq is implemented in Python and Javascript. The webserver is available at http://covseq.baidu.com/ and the source code is available from https://github.com/boxiangliu/covseq.Contactjollier.liu@gmail.comSupplementary informationSupplementary information are available at bioRxiv online.

BackgroundSingle-cell RNA-sequencing (scRNA-seq) is a rapidly evolving technology that enables measurement of gene expression levels at an unprecedented resolution. Despite the explosive growth in the number of cells that can be assayed by a single experiment, scRNA-seq still has several limitations, including high rates of dropouts, which result in a large number of genes having zero read count in the scRNA-seq data, and complicate downstream analyses.MethodsTo overcome this problem, we treat zeros as missing values and develop nonparametric deep learning methods for imputation. Specifically, our LATE (Learning with AuToEncoder) method trains an autoencoder with random initial values of the parameters, whereas our TRANSLATE (TRANSfer learning with LATE) method further allows for the use of a reference gene expression data set to provide LATE with an initial set of parameter estimates.ResultsOn both simulated and real data, LATE and TRANSLATE outperform existing scRNA-seq imputation methods, achieving lower mean squared error in most cases, recovering nonlinear gene-gene relationships, and better separating cell types. They are also highly scalable and can efficiently process over 1 million cells in just a few hours on a GPU.ConclusionsWe demonstrate that our nonparametric approach to imputation based on autoencoders is powerful and highly efficient.

BackgroundTo investigate the epigenetic and transcriptional mechanisms of coronary artery disease (CAD) risk, as well as the functional regulation of chromatin structure and function, we have created a catalog of genetic variants associated with three stages of transcriptionalcis-regulation in primary human coronary artery vascular smooth muscle cells (HCASMC).ResultsTo this end, we have used a pooling approach with HCASMC lines to map regulatory variation that mediates binding of the CAD associated transcription factor TCF21 with ChIPseq studies (bQTLs), variation that regulates chromatin accessibility with ATACseq studies (caQTLs), and chromosomal looping with HiC methods (clQTLs). We show significant overlap of the QTLs, and their relationship to smooth muscle specific genes and the binding of smooth muscle transcription factors. Further, we use multiple analyses to show that these QTLs are highly associated with CAD GWAS loci and correlated to lead SNPs in these loci where they show allelic effects. We have verified with genome editing that identified functional variants can regulate both chromatin accessibility and chromosomal looping, providing new insights into functional mechanisms regulating chromatin state and chromosomal structure. Finally, we directly link the disease associatedTGFβ1-SMAD3pathway to the CAD associatedFN1gene through a response QTL that modulates both chromatin accessibility and chromosomal looping.ConclusionsTogether, these studies represent the most thorough mapping of multiple QTL types in a highly disease relevant primary cultured cell type, and provide novel insights into their functional overlap and mechanisms that underlie these genomic features and their relationship to disease risk.

Additional file 7. Review history.

Additional file 1. Supplemental figures and related figure legends.