Explore the vast range of titles available.

Sexual dimorphism refers to differences between biological sexes that extend beyond sexual characteristics. In humans, sexual dimorphism in the immune response has been well demonstrated, with females exhibiting lower infection rates than males for a variety of bacterial, viral, and parasitic pathogens. There is also a substantially increased incidence of autoimmune disease in females compared to males. Together, these trends indicate that females have a heightened immune reactogenicity to both self and non-self-molecular patterns. However, the molecular mechanisms driving the sexually dimorphic immune response are not fully understood. The female sex hormones estrogen and progesterone, as well as the male androgens, such as testosterone, elicit direct effects on the function and inflammatory capacity of immune cells. Several studies have identified a sex-specific transcriptome and methylome, independent of the well-described phenomenon of X-chromosome inactivation, suggesting that sexual dimorphism also occurs at the epigenetic level. Moreover, distinct alterations to the transcriptome and epigenetic landscape occur in synchrony with periods of hormonal change, such as puberty, pregnancy, menopause, and exogenous hormone therapy. These changes are also mirrored by changes in immune cell function. This review will outline the evidence for sex hormones and pregnancy-associated hormones as drivers of epigenetic change, and how this may contribute to the sexual dimorphism. Determining the effects of sex hormones on innate immune function is important for understanding sexually dimorphic autoimmune diseases, sex-specific responses to pathogens and vaccines, and how innate immunity is altered during periods of hormonal change (endogenous or exogenous).

The use of elephant ivory as a commodity is a factor in declining elephant populations. Despite recent worldwide elephant ivory trade bans, mammoth ivory trade remains unregulated. This complicates law enforcement efforts, as distinguishing between ivory from extant and extinct species requires costly, destructive and time consuming methods. Elephant and mammoth ivory mainly consists of dentine, a mineralized connective tissue that contains an organic collagenous component and an inorganic component of calcium phosphate minerals, similar in structure to hydroxyapatite crystals. Raman spectroscopy is a non-invasive laser-based technique that has previously been used for the study of bone and mineral chemistry. Ivory and bone have similar biochemical properties, making Raman spectroscopy a promising method for species identification based on ivory. This study aimed to test the hypothesis that it is possible to identify differences in the chemistry of mammoth and elephant ivory using Raman spectroscopy. Mammoth and elephant tusks were obtained from the Natural History Museum in London, UK. Included in this study were eight samples of ivory from Mammuthus primigenius , two samples of carved ivory bangles from Africa ( Loxodonta species ), and one cross section of a tusk from Elephas maximus . The ivory was scanned using an inVia Raman micro spectrometer equipped with a x50 objective lens and a 785nm laser. Spectra were acquired using line maps and individual spectral points were acquired randomly or at points of interest on all samples. The data was then analysed using principal component analysis (PCA) with use of an in-house MATLAB script. Univariate analysis of peak intensity ratios of phosphate to amide I and III peaks, and carbonate to phosphate peaks showed statistical differences (p<0.0001) in the average peak intensity ratios between Mammuthus primigenius , Loxodonta spp . and Elephas maximus . Full width at half maximum hight (FWHM)analysis of the phosphate peak demonstrated higher crystal maturity of Mammuthus primigenius compared to living elephant species. The results of the study have established that spectra acquired by Raman spectroscopy can be separated into distinct classes through PCA. In conclusion, this study has shown that well-preserved mammoth and elephant ivory has the potential to be characterized using Raman spectroscopy, providing a promising method for species identification. The results of this study will be valuable in developing quick and non-destructive methods for the identification of ivory, which will have direct applications in archaeology and the regulation of international trade.

Epidemiological studies have identified many environmental agents that appear to significantly increase cancer risk in human populations. By analyzing tumor genomes from mice chronically exposed to 1 of 20 known or suspected human carcinogens, we reveal that most agents do not generate distinct mutational signatures or increase mutation burden, with most mutations, including driver mutations, resulting from tissue-specific endogenous processes. We identify signatures resulting from exposure to cobalt and vinylidene chloride and link distinct human signatures (SBS19 and SBS42) with 1,2,3-trichloropropane, a haloalkane and pollutant of drinking water, and find these and other signatures in human tumor genomes. We define the cross-species genomic landscape of tumors induced by an important compendium of agents with relevance to human health. A genomic analysis of tumors in mice caused by known or suspected carcinogens shows that most carcinogens do not generate distinct mutational signatures.

This paper describes the automatic identification of ivory using Raman spectroscopy data and deep neural network (DNN) models pre-trained on open-source data from inorganic minerals. The proposed approach uses transfer learning (TL) from foundation models trained on a larger inorganic (minerals) spectroscopy dataset (MLROD). The results demonstrate, for the first time, the ability to transfer machine learning (ML) models from a Raman spectroscopy dataset of geological substances to classify biological ivory samples. Current identification methods, such as DNA analysis and radiocarbon dating, are costly and destructive. Recently, it was demonstrated that the use of Raman spectroscopy, a laser-based, non-destructive technique, in combination with well-known statistical techniques, has the potential to differentiate between mammoth and elephant ivory. However, this previous study had a small sample size due to difficulties in obtaining large amounts of labeled ivory data. To date, there has been no reported work on ivory classification using DNNs, and only limited studies using Raman spectra. The work proposed in this paper suggests that ML can provide high levels of accuracy in the classification of Raman spectroscopy data from ivory samples of different elephant species (up to 99.7%). This has the potential to create a quick and inexpensive method of identifying legal and illegal types of ivory to aid in enforcement of ivory trade bans. This study also demonstrated that DNN models initially pre-trained on inorganic minerals (from the MLROD dataset) that were not finetuned on ivory data had a high accuracy rate of 92%, alleviating the need for large amounts of training data from ivory specimens. Finally, the approach proposed in this paper, provides insight into the decision making and interpretation of the results using prototype-based models. This novel work demonstrates that: (1) ML methods can provide highly accurate classification of ivory from different species of elephant using data obtained using Raman spectroscopy and providing insight into the decision making (2) TL enables re-purposing the models trained on larger mineral datasets of inorganic materials (such as MLROD) to discriminating between the classes of ivory, containing inorganic and organic biological components, for the first time transgressing between non-biological and biological samples (3) the proposed method allows both training from labelled samples of ivory and the identification of unknown ivory samples through prototype-based methods.

Genome-scale CRISPR-Cas9 viability screens performed in cancer cell lines provide a systematic approach to identify cancer dependencies and new therapeutic targets. As multiple large-scale screens become available, a formal assessment of the reproducibility of these experiments becomes necessary. We analyze data from recently published pan-cancer CRISPR-Cas9 screens performed at the Broad and Sanger Institutes. Despite significant differences in experimental protocols and reagents, we find that the screen results are highly concordant across multiple metrics with both common and specific dependencies jointly identified across the two studies. Furthermore, robust biomarkers of gene dependency found in one data set are recovered in the other. Through further analysis and replication experiments at each institute, we show that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length. These results indicate that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings. Integrating independent large-scale pharmacogenomic screens can enable unprecedented characterization of genetic vulnerabilities in cancers. Here, the authors show that the two largest independent CRISPR-Cas9 gene-dependency screens are concordant, paving the way for joint analysis of the data sets.

Background Genome editing by CRISPR-Cas9 technology allows large-scale screening of gene essentiality in cancer. A confounding factor when interpreting CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes within copy number amplified regions of the genome. We have developed the computational tool CRISPRcleanR which is capable of identifying and correcting gene-independent responses to CRISPR-Cas9 targeting. CRISPRcleanR uses an unsupervised approach based on the segmentation of single-guide RNA fold change values across the genome, without making any assumption about the copy number status of the targeted genes. Results Applying our method to existing and newly generated genome-wide essentiality profiles from 15 cancer cell lines, we demonstrate that CRISPRcleanR reduces false positives when calling essential genes, correcting biases within and outside of amplified regions, while maintaining true positive rates. Established cancer dependencies and essentiality signals of amplified cancer driver genes are detectable post-correction. CRISPRcleanR reports sgRNA fold changes and normalised read counts, is therefore compatible with downstream analysis tools, and works with multiple sgRNA libraries. Conclusions CRISPRcleanR is a versatile open-source tool for the analysis of CRISPR-Cas9 knockout screens to identify essential genes.

Background DNA methylation is an epigenetic mark that is influenced by underlying genetic profile, environment, and ageing. In addition to X-linked DNA methylation, sex-specific methylation patterns are widespread across autosomal chromosomes and can be present from birth or arise over time. In individuals where gender identity and sex assigned at birth are markedly incongruent, as in the case of transgender people, feminization or masculinization may be sought through gender-affirming hormone therapy (GAHT). GAHT is a cornerstone of transgender care, yet no studies to date have investigated its effect on genome-wide methylation. We profiled genome-wide DNA methylation in blood of transgender women ( n  = 13) and transgender men ( n  = 13) before and during GAHT (6 months and 12 months into feminizing or masculinizing hormone therapy). Results We identified several thousand differentially methylated CpG sites (DMPs) (Δ β  ≥ 0.02, unadjusted p value < 0.05) and several differentially methylated regions (DMRs) in both people undergoing feminizing and masculinizing GAHT, the vast majority of which were progressive changes over time. X chromosome and sex-specific autosomal DNA methylation patterns established in early development are largely refractory to change in association with GAHT, with only 3% affected (Δ β  ≥ 0.02, unadjusted p value < 0.05). The small number of sex-specific DMPs that were affected by GAHT were those that become sex-specific during the lifetime, known as sex-and-age DMPs, including DMRs in PRR4 and VMP1 genes. The GAHT-induced changes at these sex-associated probes consistently demonstrated a shift towards the methylation signature of the GAHT-naïve opposite sex, and we observed enrichment of previously reported adolescence-associated methylation changes. Conclusion We provide evidence for GAHT inducing a unique blood methylation signature in transgender people. This study advances our understanding of the complex interplay between sex hormones, sex chromosomes, and DNA methylation in the context of immunity. We highlight the need to broaden the field of ‘sex-specific’ immunity beyond cisgender males and cisgender females, as transgender people on GAHT exhibit a unique molecular profile.

Osteoarthritis (OA) is one of the most prevalent conditions in the world, particularly in the developed world with a significant increase in cases and their predicted impact as we move through the twenty-first century and this will be exacerbated by the covid pandemic. The degeneration of cartilage and bone as part of this condition is becoming better understood but there are still significant challenges in painting a complete picture to recognise all aspects of the condition and what treatment(s) are most appropriate in individual causes. OA encompasses many different types and this causes some of the challenges in fully understanding the condition. There have been examples through history where much has been learnt about common disease(s) from the study of rare or extreme phenotypes, particularly where Mendelian disorders are involved. The often early onset of symptoms combined with the rapid and aggressive pathogenesis of these diseases and their predictable outcomes give an often-under-explored resource. It is these “rarer forms of disease” that William Harvey referred to that offer novel insights into more common conditions through their more extreme presentations. In the case of OA, GWAS analyses demonstrate the multiple genes that are implicated in OA in the general population. In some of these rarer forms, single defective genes are responsible. The extreme phenotypes seen in conditions such as Camptodactyly Arthropathy-Coxa Vara-pericarditis Syndrome, Chondrodysplasias and Alkaptonuria all present potential opportunities for greater understanding of disease pathogenesis, novel therapeutic interventions and diagnostic imaging. This review examines some of the rarer presenting forms of OA and linked conditions, some of the novel discoveries made whilst studying them, and findings on imaging and treatment strategies.

Melanins are conjugated biopolymers with varying compositions and functions, found in various tissues throughout the body. Here, the conjugated polymers derived from homogentisic acid (HGA), polyHGA (a simplified model of pyomelanin), formed in an ex vivo tendon model are examined with a view to understanding interactions between melanins and the extracellular matrix (ECM) using a selection of different analytical techniques, including spectroscopy (energy dispersive X‐ray, infrared, and Raman), X‐ray diffraction, and microscopy (electron, optical, and scanning electrochemical). The combination of techniques was used to facilitate an understanding of subtle differences in the composition and distribution of ECM components, hydroxyapatite, and melanin in the tendons for the first time. PolyHGA deposition in connective tissues in patients with alkaptonuria is a significant burden and causes multiple tendon ruptures due to the significant alterations in collagen properties. A similar pathology is seen in the wider population from calcific tendinitis because of hydroxyapatite crystal deposition in tendons of the shoulder and lower limbs, in particular. Polymerization of homogentisic acid in the presence of extracellular matrix (ECM) components (an ex vivo turkey tendon model) yields simplified versions of biologically generated melanins in the ECM, facilitating studies of melanin–ECM interactions. A variety of techniques (X‐ray diffraction, microscopy, and spectroscopy) were employed to understand the potential influence of the ECM in the deposition of melanins in biological tissues.

Thyroid hormones have immunomodulatory roles, but their effects on the transcriptome and epigenome of innate immune cell types remain unexplored. In this study, we investigate the effects of triiodothyronine (T3) on the transcriptome and methylome of human monocytes in vitro, both in resting and lipopolysaccharide (LPS)-stimulated conditions. In resting monocytes, 5 µM T3 affected the expression of a small number of monocyte-to-macrophage differentiation-associated genes, including TLR4 (p-value < 0.05, expression fold change >1.5). T3 attenuated a small proportion of monocyte-to-macrophage differentiation-associated DNA methylation changes, while specifically inducing DNA methylation changes at several hundred differentially methylated CpG probes (DMPs) (p-value < 0.05, Δβ > 0.05). In LPS-stimulated monocytes, the presence of T3 attenuated the effect of 27% of LPS-induced DMPs (p-value < 0.05, Δβ > 0.05). Interestingly, co-stimulation with T3 + LPS induced a unique DNA methylation signature that was not observed in the LPS-only or T3-only exposure groups. Our results suggest that T3 induces limited transcriptional and DNA methylation remodeling in genes enriched in metabolism and immune processes and alters the normal in vitro LPS response. The overlap between differentially expressed genes and genes associated with DMPs was minimal; thus, other epigenetic mechanisms may underpin the expression changes. This research provides insight into the complex interplay between thyroid hormones, epigenetic remodeling, and transcriptional dynamics in monocytes.