Epstein-Barr virus (EBV) is a ubiquitous oncogenic virus that induces many cancers. N6-Methyladenosine (m6A) modification regulates many cellular processes. We explored the role of m6A in EBV gene ...regulation and associated cancers. We have comprehensively defined m6A modification of EBV latent and lytic transcripts. Furthermore, m6A modification demonstrated a functional role in regulation of the stability of viral transcripts. The methyltransferase METTL14 was induced at the transcript and protein levels, and knock-down of METTL14 led to decreased expression of latent EBV transcripts. METTL14 was also significantly induced in EBV-positive tumors, promoted growth of EBV-transformed cells and tumors in Xenograft animal models. Mechanistically, the viral-encoded latent oncoprotein EBNA3C activated transcription of METTL14, and directly interacted with METTL14 to promote its stability. This demonstrated that EBV hijacks METTL14 to drive EBV-mediated tumorigenesis. METTL14 is now a new target for development of therapeutics for treatment of EBV-associated cancers.
Seminal fluid contains potent signaling agents that influence female reproductive physiology to improve the chances of conception and pregnancy success. Cytokines and prostaglandins synthesized in ...the male accessory glands are transferred to the female at insemination, where they bind to receptors on target cells in the cervix and uterus, activating changes in gene expression that lead to modifications in structure and function of the female tissues. The consequences are increased sperm survival and fertilization rates, conditioning of the female immune response to tolerate semen and the conceptus, and molecular and cellular changes in the endometrium that facilitate embryo development and implantation. Male-female tract signaling occurs in rodents, livestock animals, and all other mammals examined thus far, including humans. In mice, the key signaling moieties in seminal plasma are identified as members of the transforming growth factor-beta family. Recent studies indicate a similar signaling function for boar factors in the pig, whereby the sperm and plasma fractions of seminal fluid appear to synergize in activating an inflammatory response and downstream changes in the female tract after insemination. Seminal plasma elicits endometrial changes, with induction of proinflammatory cytokines and cyclooxygenase-2, causing recruitment of macrophages and dendritic cells. Sperm contribute by interacting with seminal plasma factors to modulate neutrophil influx into the luminal cavity. The cascade of changes in local leukocyte populations and cytokine synthesis persists throughout the preimplantation period. Exposure to seminal fluid alters the dynamics of preimplantation embryo development, with an increase in the number of fertilized oocytes attaining the viable blastocyst stage. There is also evidence that seminal factors influence the timing of ovulation, corpus luteum development, and progesterone synthesis. Insight into the molecular basis of seminal fluid signaling in the female reproductive tract may inform new interventions and management practices to ensure maximal fertility and reduce embryo mortality in pigs and, potentially, other livestock species.
Abstract
Background
Previous research found increased COVID-19 spread associated with politics and on-demand testing but not in the same study. The objective of this study is to estimate the ...contribution of each corrected for the other and a variety of known risk factors.
Methods
Using data from 217 U.S. counties of more than 50,000 population where testing data were available in April, 2021, the associations of COVID-19 deaths with politics, testing and other risk factors were examined by Poisson and least squares regression.
Results
Statistical controls for 15 risk factors failed to eliminate the association of COVID mortality risk with percent of vote for Donald Trump in 2016 or negative tests per population. Each is independently predictive of increased mortality.
Conclusion
Apparently, many people who test negative for the SARS-CoV-2 virus engage in activities that increase their risk, a problem likely to increase with the availability of home tests. There is no association of negative tests with the Trump vote but, according to polling data, Trump voters’ past resistance to public health recommendations has been extended to resistance to being vaccinated, threatening the goal of herd immunity.
Protein⁻protein interactions (PPIs) are tremendously important for the function of many biological processes. However, because of the structure of many protein⁻protein interfaces (flat, featureless ...and relatively large), they have largely been overlooked as potential drug targets. In this review, we highlight the current tools used to study the molecular recognition of PPIs through the use of different peptidomimetics, from small molecules and scaffolds to peptides. Then, we focus on constrained peptides, and in particular, ways to constrain α-helices through stapling using both one- and two-component techniques.
A description is given of a sequence of events which would have led to the appearance of the organic compounds and living cells present on Earth, one of which is human cells. The evolutionary events ...involved are proposed as having taken place in phosphate ion-dominated aqueous pools formed in regions associated with volcanoes. The mechanism involved the unique molecular structure variations and chemical properties of polyphosphoric acid and compounds of this acid producing urea as the first organic compound formed on Earth and derivatives of urea giving rise to DNA and RNA. The occurrence of the process in present times is considered possible.
Epstein-Barr virus (EBV) is a ubiquitous human γ-herpesvirus that establishes a life-long asymptomatic infection in immunocompetent hosts. It is also found to be frequently associated with a broad ...spectrum of B-cell lymphomas predominantly seen in immunodeficient patients. Despite many resemblances, these EBV-linked lymphoproliferative disorders display heterogeneity at the clinical and the molecular level. Moreover, EBV-associated lymphoproliferative diseases differ in their differential expression patterns of the EBV-encoded latent antigens, which are directly related to their interactions with the host. EBV-driven primary B-cell immortalization is linked to the cooperative functions of these latent proteins, which are critical for perturbing many important cell-signaling pathways maintaining B-cell proliferation. Additionally, it is used as a surrogate model to explore the underlying mechanisms involved in the development of B-cell neoplasms. Recent discoveries have revealed that a number of sophisticated mechanisms are exploited by EBV during cancer progression. This finding will be instrumental in the design of novel approaches for therapeutic interventions against EBV-associated B-cell lymphomas. This review limits the discussion to the biology and pathogenesis of EBV-associated B-cell lymphomas and the related clinical implications.
The Nottingham histological grade (NHG) is a well-established prognostic factor for breast cancer that is broadly used in clinical decision making. However, ∼50% of patients are classified as grade ...2, an intermediate risk group with low clinical value. To improve risk stratification of NHG 2 breast cancer patients, we developed and validated a novel histological grade model (DeepGrade) based on digital whole-slide histopathology images (WSIs) and deep learning.
In this observational retrospective study, routine WSIs stained with haematoxylin and eosin from 1567 patients were utilised for model optimisation and validation. Model generalisability was further evaluated in an external test set with 1262 patients. NHG 2 cases were stratified into two groups, DG2-high and DG2-low, and the prognostic value was assessed. The main outcome was recurrence-free survival.
DeepGrade provides independent prognostic information for stratification of NHG 2 cases in the internal test set, where DG2-high showed an increased risk for recurrence (hazard ratio HR 2.94, 95% confidence interval CI 1.24-6.97, P = 0.015) compared with the DG2-low group after adjusting for established risk factors (independent test data). DG2-low also shared phenotypic similarities with NHG 1, and DG2-high with NHG 3, suggesting that the model identifies morphological patterns in NHG 2 that are associated with more aggressive tumours. The prognostic value of DeepGrade was further assessed in the external test set, confirming an increased risk for recurrence in DG2-high (HR 1.91, 95% CI 1.11-3.29, P = 0.019).
The proposed model-based stratification of patients with NHG 2 tumours is prognostic and adds clinically relevant information over routine histological grading. The methodology offers a cost-effective alternative to molecular profiling to extract information relevant for clinical decisions.
•A novel deep learning model was developed and validated for improved breast cancer histological grading.•The model uses routine histopathology images and provides independent prognostic value for stratification of the NHG 2 group.•Model-based histological grading offers a cost-effective alternative to molecular profiling for improved risk stratification.
"The idea that the digital age has revolutionized our day-to-day experience of the world is nothing new, and has been amply recognized by cultural historians. In contrast, Stephen Robertson’s BC: ...Before Computers is a work which questions the idea that the mid-twentieth century saw a single moment of rupture. It is about all the things that we had to learn, invent, and understand – all the ways we had to evolve our thinking – before we could enter the information technology revolution of the second half of the twentieth century. Its focus ranges from the beginnings of data processing, right back to such originary forms of human technology as the development of writing systems, gathering a whole history of revolutionary moments in the development of information technologies into a single, although not linear narrative. Treading the line between philosophy and technical history, Robertson draws on his extensive technical knowledge to produce a text which is both thought-provoking and accessible to a wide range of readers. The book is wide in scope, exploring the development of technologies in such diverse areas as cryptography, visual art and music, and the postal system. Through all this, it does not simply aim to tell the story of computer developments but to show that those developments rely on a long history of humans creating technologies for increasingly sophisticated methods of manipulating information. Through a clear structure and engaging style, it brings together a wealth of informative and conceptual explorations into the history of human technologies, and avoids assumptions about any prior knowledge on the part of the reader. As such, it has the potential to be of interest to the expert and the general reader alike."
Plant population density is an important factor for agricultural production systems due to its substantial influence on crop yield and quality. Traditionally, plant population density is estimated by ...using either field assessment or a germination-test-based approach. These approaches can be laborious and inaccurate. Recent advances in deep learning provide new tools to solve challenging computer vision tasks such as object detection, which can be used for detecting and counting plant seedlings in the field. The goal of this study was to develop a deep-learning-based approach to count plant seedlings in the field.
Overall, the final detection model achieved F1 scores of 0.727 (at
) and 0.969 (at
) on the
testing set in which images had large variations, indicating the efficacy of the Faster RCNN model with the Inception ResNet v2 feature extractor for seedling detection. Ablation experiments showed that training data complexity substantially affected model generalizability, transfer learning efficiency, and detection performance improvements due to increased training sample size. Generally, the seedling counts by the developed method were highly correlated (
= 0.98) with that found through human field assessment for 75 test videos collected in multiple locations during multiple years, indicating the accuracy of the developed approach. Further experiments showed that the counting accuracy was largely affected by the detection accuracy: the developed approach provided good counting performance for unknown datasets as long as detection models were well generalized to those datasets.
The developed deep-learning-based approach can accurately count plant seedlings in the field. Seedling detection models trained in this study and the annotated images can be used by the research community and the cotton industry to further the development of solutions for seedling detection and counting.
Epstein-Barr virus (EBV) is the first identified human oncogenic virus that can establish asymptomatic life-long persistence. It is associated with a large spectrum of diseases, including benign ...diseases, a number of lymphoid malignancies, and epithelial cancers. EBV can also transform quiescent B lymphocytes into lymphoblastoid cell lines (LCLs) in vitro. Although EBV molecular biology and EBV-related diseases have been continuously investigated for nearly 60 years, the mechanism of viral-mediated transformation, as well as the precise role of EBV in promoting these diseases, remain a major challenge yet to be completely explored. This review will highlight the history of EBV and current advances in EBV-associated diseases, focusing on how this virus provides a paradigm for exploiting the many insights identified through interplay between EBV and its host during oncogenesis, and other related non-malignant disorders.
PDF
