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Esophageal squamous cell carcinoma (ESCC) shows remarkable variation in incidence that is not fully explained by known lifestyle and environmental risk factors. It has been speculated that an unknown exogenous exposure(s) could be responsible. Here we combine the fields of mutational signature analysis with cancer epidemiology to study 552 ESCC genomes from eight countries with varying incidence rates. Mutational profiles were similar across all countries studied. Associations between specific mutational signatures and ESCC risk factors were identified for tobacco, alcohol, opium and germline variants, with modest impacts on mutation burden. We find no evidence of a mutational signature indicative of an exogenous exposure capable of explaining differences in ESCC incidence. Apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like (APOBEC)-associated mutational signatures single-base substitution (SBS)2 and SBS13 were present in 88% and 91% of cases, respectively, and accounted for 25% of the mutation burden on average, indicating that APOBEC activation is a crucial step in ESCC tumor development.

Objectives The sensitivities of the pituitary to thyroxine feedback, and the thyroid to thyrotropin stimulation determine the free thyroxine /thyrotropin feedback loop and can be described mathematically by two curves. It is not well understood how the two curves combine in a healthy population with normal thyroid function to express the individual balance points that are observed. This study was directed at this issue testing the possibilities of random combination and directed linkage between the two curves. Methods We reverse-engineered two sets of population data, on the assumption of independent combinations of thyroid and pituitary sensitivities, to obtain estimates of the curve describing thyroid sensitivity. Sensitivity studies were performed. Results No analysis resulted in a physiologically feasible estimate of the curve describing thyroid sensitivity. There was evidence of linkage of the two curves in terms of their combination throughout the normal range. Thyroid response curves reflecting a low free thyroxine response to thyrotropin tended to be combined in individuals with thyrotropin curves reflecting a high thyrotropin response to free thyroxine, and vice versa. Conclusions Thyroid and pituitary sensitivities are linked, being combined in individuals in a non-random directed pattern. Direct mutual interaction may contribute to this linkage. This linkage precludes the derivation of the curves describing these sensitivities from population data of the free thyroxine and thyrotropin relationship and complicates their derivation by physiological experimentation. This linkage and probable interaction may also bestow evolutionary advantage by minimising inter-individual variation in free thyroxine levels and by augmenting homeostasis.

In recent years, large-scale whole genome sequencing of multiple types of cancer across multiple continents has been conducted as part of the “Mutographs” Cancer Grand Challenge to uncover unknown causes of cancer through detection of signatures of mutational processes operative during cancer development. Distinct mutational signatures have recently been detected by “Mutographs” in Renal Clear Cell Carcinomas (RCC) from different parts of the world. However, whether the detected mutational signatures are present in normal tissues or are initiated after tumorigenesis remains unknown. In general, there has been a lack of knowledge of somatic mutations in normal cells primarily due to technological barriers to detection of somatic mutations in highly polyclonal normal tissues. However, a recently developed duplex sequencing technology, NanoSeq, uses copies of both strands of each DNA molecule to reduce sequencing errors to 10−9. With NanoSeq, we are able to detect somatic mutations in polyclonal tissues including the normal kidney. In this study, we used NanoSeq to sequence 288 tumor-adjacent normal kidney samples from multiple countries with varying RCC incidence. Subsequently, we conducted agnostic signature extraction using a Hierarchical Dirichlet Process to investigate whether the region specific mutational signatures found in cancers can be extracted from normal kidney tissue. The normal kidney tissues we sequenced have paired RCC whole genome sequencing data from the same individual. Therefore, the mutational profiles of normal kidney can be compared to paired cancer samples to ascertain the timing of the mutational processes causing the mutational signatures found in the cancers. We confirmed that a predominantly T>C mutational signature that is highly enriched in Japanese RCC is present in normal kidney samples. A strong transcriptional strand bias in this signature provides circumstantial evidence that it is likely to have been caused by DNA damaging agents causing bulky DNA adducts which may be of environmental origin. A subset of RCC samples from Serbia and Romania had mutational signatures caused by aristolochic acids (AA). We found different dominant AA-related signatures in tumors compared to their matched normal tissues, potentially indicating different mutagenic or repair mechanisms between normal and cancer cells. Levels of SBS40, which is of unknown cause, were elevated in normal kidneys from the Czech Republic compared to other countries, and may contribute to the high RCC incidence in this country. In summary, this study provides the first systematic investigation of somatic mutations in normal kidney, revealing different mutational processes in different geographic regions and in cancer versus normal kidneys. Citation Format: Yichen Wang, Sarah Moody, Behnoush Abedi-Ardekani, Calli Latimer, Saamin Cheema, Jingwei Wang, Stephen Fitzgerald, Laura Humphreys, Paul Brennan, Michael R. Stratton. Mutational processes in tumour-adjacent normal kidneys across countries with varying cancer incidence rates [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1168.

Personal recovery (PR) is a recovery-oriented framework expanding beyond symptomatic remission and functional reattainment. Personal recovery in people with schizophrenia is built on the understanding, that people with schizophrenia can live meaningful lives despite remaining symptoms. Frameworks for PR such as CHIME (Leamy, Bird. Boutillier, Williams & Slade, 2011) and enhanced sense of self (Schrank, Riches, Bird, Murray, Tylee & Slade, 2014) have emerged. Prior reviews on interventions for personal recovery have focused on people with disorders of the psychotic spectrum. No review has examined psychosocial interventions on personal recovery for people with schizophrenia, or the harms and benefits of such interventions. Search strings for the following databases have been developed: PubMed, EMBASE, PsycINFO, CINAHL, MEDLINE, Google Scholar, Web of Science, and Cochrane. Additionally, the Networked Digital Library of Theses and Dissertations (NDLTD) will be searched for gray literature. Two reviewers will individually screen and extract data. An overview of the variety of psychosocial interventions on personal recovery for people with schizophrenia. The results of a qualitative content analysis will be used to categorize benefits and harms of aforementioned interventions for people with schizophrenia. A scoping review protocol will be submitted to a peer-reviewed journal.

As part of the global response to the 2019 novel Coronavirus (SARS-CoV-2) pandemic, it was determined that SARS-CoV-2 RNA was detectable in the faeces of both symptomatic and asymptomatic patients (1). Further analysis demonstrated that a wastewater epidemiological (WWE) approach, similar to that used to track other viruses (i.e. Poliovirus), could be employed to monitor the spread of SARS-CoV-2. The presence of, or changes in concentration of viral RNA within the wastewater network can assist in monitoring the emergence of further viral peaks (2). Thus, monitoring the spread of Covid-19 using the WWE approach has been extensively explored in several countries (3). This procedure, developed by the Scottish Environment Protection Agency (SEPA) based upon work of the Corbishley group at the Roslin Institute, University of Edinburgh, outlines the method for the concentration of viral RNA in wastewater, as well as in other types of environmental and potable water samples. In this method, a known volume of sample is concentrated using a centrifugal filter to allow further extraction and detection of SARS-CoV-2 RNA. For further analysis using RT-qPCR please search for "RT-qPCR for detection of SARS-CoV-2 in wastewater" by the same authors of this protocol on protocols.io References: 1. Jones, D. L., Baluja, M. Q., Graham, D. W., Corbishley, A., McDonald, J. E., Malham, S. K., Hillary, L. S., Connor, T. R., Gaze , W. H., Moura , I. B., Wilcox, M. H., & Farkas , K. (2020).Shedding of SARS-CoV-2 in feces and urine and its potential role in person-to-person transmission and the environment-based spread of COVID-19.Science of the Total Environment.https://doi.org/10.1016/j.scitotenv.2020.1413644. 2. Fitzgerald, S., Rossi, G., Low, A., McAteer, S., O’Keefe, B., Findlay, D., Cameron, G. J., Pollard, P., Singleton, P. T. R., Ponton, G., Singer, A. C., Farkas, K., Jones, D., Graham, D. W., Quintela-Baluja, M., Tait-Burkard, C., Gally, D., Kao, R., & Corbishley, A.(2021).Site specific relationships between COVID-19 cases and SARS-CoV-2 viral load in wastewater treatment plant influent. Environmental Science and Technology. https://doi.org/10.1021/acs.est.1c05029 3. Wastewater SARS Public Health Environmental Response (W-SPHERE). https://sphere.waterpathogens.org/about

Esophageal squamous cell carcinoma (ESCC) shows a remarkable variation in incidence which is not fully explained by known lifestyle and environmental risk factors. It has been speculated that an unknown exogenous exposure(s) could be responsible. Here we combine the fields of mutational signature analysis with cancer epidemiology to study 552 ESCC genomes from eight countries with varying incidence rates. The mutational profiles of ESCC were similar across all countries studied. Associations between specific mutational signatures and ESCC risk factors were identified for tobacco, alcohol, opium and germline variants, with modest impacts on mutation burden. We find no evidence of a mutational signature indicative of an exogenous exposure capable of explaining the differences in ESCC incidence. APOBEC associated mutational signatures SBS2 and SBS13 were present in 88% and 91% of cases respectively and accounted for a quarter of the mutation burden on average, indicating that activation of APOBEC is a crucial step in ESCC tumor development.

Coordinatively-unsaturated metal sites within certain zeolites and metal–organic frameworks can strongly adsorb various molecules. While many classical examples involve electron-poor metal cations that interact with adsorbates largely through electrostatic interactions, unsaturated electron-rich metal centers housed within porous frameworks can often chemisorb guests amenable to redox activity or covalent bond formation. Despite the promise that materials bearing such sites hold in addressing myriad challenges in gas separations and storage, very few studies have directly interrogated mechanisms of chemisorption at open metal sites within porous frameworks. Here, we show that H2chemisorption at the trigonal pyramidal Cu+sites in the metal–organic framework CuI‑MFU-4l occurs via the intermediacy of a metastable physisorbed precursor species. In situpowder neutron diffraction experiments enable crystallographic characterization of this intermediate, the first time that this has been accomplished for any material. Support for a precursor intermediate is also afforded from temperature-programmed desorption and density functional theory calculations. The activation barrier separating the precursor species from the chemisorbed state is shown to correlate with a change in the Cu+coordination environment that enhances π-backbonding with H2. Ultimately, these findings demonstrate that adsorption at framework metal sites does not always follow a concerted pathway and underscore the importance of probing kinetics in the design of next-generation adsorbents.

Background Olfactory receptor (OR) genes are the largest multi-gene family in the mammalian genome, with 874 in human and 1483 loci in mouse (including pseudogenes). The expansion of the OR gene repertoire has occurred through numerous duplication events followed by diversification, resulting in a large number of highly similar paralogous genes. These characteristics have made the annotation of the complete OR gene repertoire a complex task. Most OR genes have been predicted in silico and are typically annotated as intronless coding sequences. Results Here we have developed an expert curation pipeline to analyse and annotate every OR gene in the human and mouse reference genomes. By combining evidence from structural features, evolutionary conservation and experimental data, we have unified the annotation of these gene families, and have systematically determined the protein-coding potential of each locus. We have defined the non-coding regions of many OR genes, enabling us to generate full-length transcript models. We found that 13 human and 41 mouse OR loci have coding sequences that are split across two exons. These split OR genes are conserved across mammals, and are expressed at the same level as protein-coding OR genes with an intronless coding region. Our findings challenge the long-standing and widespread notion that the coding region of a vertebrate OR gene is contained within a single exon. Conclusions This work provides the most comprehensive curation effort of the human and mouse OR gene repertoires to date. The complete annotation has been integrated into the GENCODE reference gene set, for immediate availability to the research community.

The most widely appreciated role of DNA is to encode protein, yet the exact portion of the human genome that is translated remains to be ascertained. We previously developed PhyloCSF, a widely used tool to identify evolutionary signatures of protein-coding regions using multispecies genome alignments. Here, we present the first whole-genome PhyloCSF prediction tracks for human, mouse, chicken, fly, worm, and mosquito. We develop a workflow that uses machine learning to predict novel conserved protein-coding regions and efficiently guide their manual curation. We analyze more than 1000 high-scoring human PhyloCSF regions and confidently add 144 conserved protein-coding genes to the GENCODE gene set, as well as additional coding regions within 236 previously annotated protein-coding genes, and 169 pseudogenes, most of them disabled after primates diverged. The majority of these represent new discoveries, including 70 previously undetected protein-coding genes. The novel coding genes are additionally supported by single-nucleotide variant evidence indicative of continued purifying selection in the human lineage, coding-exon splicing evidence from new GENCODE transcripts using next-generation transcriptomic data sets, and mass spectrometry evidence of translation for several new genes. Our discoveries required simultaneous comparative annotation of other vertebrate genomes, which we show is essential to remove spurious ORFs and to distinguish coding from pseudogene regions. Our new coding regions help elucidate disease-associated regions by revealing that 118 GWAS variants previously thought to be noncoding are in fact protein altering. Altogether, our PhyloCSF data sets and algorithms will help researchers seeking to interpret these genomes, while our new annotations present exciting loci for further experimental characterization.

The developmental and epileptic encephalopathies (DEE) are a group of rare, severe neurodevelopmental disorders, where even the most thorough sequencing studies leave 60–65% of patients without a molecular diagnosis. Here, we explore the incompleteness of transcript models used for exome and genome analysis as one potential explanation for a lack of current diagnoses. Therefore, we have updated the GENCODE gene annotation for 191 epilepsy-associated genes, using human brain-derived transcriptomic libraries and other data to build 3,550 putative transcript models. Our annotations increase the transcriptional ‘footprint’ of these genes by over 674 kb. Using SCN1A as a case study, due to its close phenotype/genotype correlation with Dravet syndrome, we screened 122 people with Dravet syndrome or a similar phenotype with a panel of exon sequences representing eight established genes and identified two de novo SCN1A variants that now - through improved gene annotation - are ascribed to residing among our exons. These two (from 122 screened people, 1.6%) molecular diagnoses carry significant clinical implications. Furthermore, we identified a previously classified SCN1A intronic Dravet syndrome-associated variant that now lies within a deeply conserved exon. Our findings illustrate the potential gains of thorough gene annotation in improving diagnostic yields for genetic disorders.

The early infantile epileptic encephalopathies (EIEE) are a group of rare, severe neurodevelopmental disorders, where even the most thorough sequencing studies leave 60-65% of patients without a molecular diagnosis. Here, we explore the incompleteness of transcript models used for exome and genome analysis as one potential explanation for lack of current diagnoses. Therefore, we have updated the GENCODE gene annotation for 191 epilepsy-associated genes, using human brain-derived transcriptomic libraries and other data to build 3,550 novel putative transcript models. The extended transcriptional footprint of these genes allowed for 294 intronic or intergenic variants, found in human mutation databases, to be reclassified as exonic, while a further 70 intronic variants were reclassified as splice-site proximal. Using SCN1A as a case study due to its close phenotype/genotype correlation with Dravet syndrome, we screened 122 people with Dravet syndrome, or a similar phenotype, with a panel of novel exon sequences representing eight established genes and identified two de novo SCN1A variants that now, through improved gene annotation can be ascribed to residing among novel exons. These two (from 122 screened patients, 1.6%) new molecular diagnoses carry significant clinical implications. Furthermore, we identified a previously-classified SCN1A intronic Dravet-associated variant that now lies within a deeply conserved novel exon. Our findings illustrate the potential gains of thorough gene annotation in improving diagnostic yields for genetic disorders. We would expect to find new molecular diagnoses in our 191 genes that were originally suspected by clinicians for patients, with a negative diagnosis.

Knee osteoarthritis (OA) is a significant problem in the aging population, causing pain, impaired mobility, and decreased quality of life. Conservative treatment methods are necessary to reduce rapidly increasing rates of knee joint surgery. Recommended strategies include weight loss and knee bracing to unload knee joint forces. Although weight loss can be beneficial for joint unloading, knee OA patients often find it difficult to lose weight or begin exercise due to knee pain, and not all patients are overweight. Unicompartment offloader knee braces can redistribute joint forces away from one tibiofemoral (TF) compartment; however

The developmental and epileptic encephalopathies (DEE) are a group of rare, severe neurodevelopmental disorders, where even the most thorough sequencing studies leave 60–65% of patients without a molecular diagnosis. Here, we explore the incompleteness of transcript models used for exome and genome analysis as one potential explanation for a lack of current diagnoses. Therefore, we have updated the GENCODE gene annotation for 191 epilepsy-associated genes, using human brain-derived transcriptomic libraries and other data to build 3,550 putative transcript models. Our annotations increase the transcriptional ‘footprint’ of these genes by over 674 kb. Using SCN1A as a case study, due to its close phenotype/genotype correlation with Dravet syndrome, we screened 122 people with Dravet syndrome or a similar phenotype with a panel of exon sequences representing eight established genes and identified two de novo SCN1A variants that now - through improved gene annotation - are ascribed to residing among our exons. These two (from 122 screened people, 1.6%) molecular diagnoses carry significant clinical implications. Furthermore, we identified a previously classified SCN1A intronic Dravet syndrome-associated variant that now lies within a deeply conserved exon. Our findings illustrate the potential gains of thorough gene annotation in improving diagnostic yields for genetic disorders.

Symmetry breaking has been recently observed in the endofullerenes M@C

Ensembl (http://www.ensembl.org) is a genomic interpretation system providing the most up-to-date annotations, querying tools and access methods for chordates and key model organisms. This year we released updated annotation (gene models, comparative genomics, regulatory regions and variation) on the new human assembly, GRCh38, although we continue to support researchers using the GRCh37.p13 assembly through a dedicated site (http://grch37.ensembl.org). Our Regulatory Build has been revamped to identify regulatory regions of interest and to efficiently highlight their activity across disparate epigenetic data sets. A number of new interfaces allow users to perform large-scale comparisons of their data against our annotations. The REST server (http://rest.ensembl.org), which allows programs written in any language to query our databases, has moved to a full service alongside our upgraded website tools. Our online Variant Effect Predictor tool has been updated to process more variants and calculate summary statistics. Lastly, the WiggleTools package enables users to summarize large collections of data sets and view them as single tracks in Ensembl. The Ensembl code base itself is more accessible: it is now hosted on our GitHub organization page (https://github.com/Ensembl) under an Apache 2.0 open source license.