The rockefeller university

Elective single embryo transfer (eSET) was first introduced to IVF in 1999, and its subsequent integration into mainstream reproductive endocrinology and infertility has been hugely consequential. It can be viewed as the first (among many since) 'add-ons' to IVF that has significantly and adversely affected how IVF is practised, resulting in astonishing declines in live birth rates after fresh non-donor IVF cycles worldwide. We propose that, like most 'addons' to IVF over recent years, the almost universal use of eSET worldwide lacks proper validation of its underlying hypothesis and is based on statistically incorrect assumptions and incorrect data interpretation. As with most recent 'add-ons' to IVF, eSET lacks evidentiary support, and, therefore, its remarkable success in the marketplace must be based on expert opinions, the lowest level of evidence in medicine and widely recognized as frequently biased. Like other 'add-ons' to IVF, eSET-practice must be reassessed because it does not offer the benefits it has widely claimed to provide, prolongs time to conception and adversely affects live birth chances for many women. Moreover, by ignoring that infertile women value quick conception over most other considerations, provider-insistence on eSET frequently deprives them of the right to self-determination.

Crucial metabolic functions of peroxisomes rely on a variety of peroxisomal membrane proteins (PMPs). While mRNA transcripts of PMPs were shown to be colocalized with peroxisomes, the process by which PMPs efficiently couple translation with targeting to the peroxisomal membrane remained elusive. Here, we combine quantitative electron microscopy with proximity-specific ribosome profiling and reveal that translation of specific PMPs occurs on the surface of peroxisomes in the yeast Saccharomyces cerevisiae. This places peroxisomes alongside chloroplasts, mitochondria, and the endoplasmic reticulum as organelles that use localized translation for ensuring correct insertion of hydrophobic proteins into their membranes. Moreover, the correct targeting of these transcripts to peroxisomes is crucial for peroxisomal and cellular function, emphasizing the importance of localized translation for cellular physiology.

Background Studies in vertebrate genomics require sampling from a broad range of tissue types, taxa, and localities. Recent advancements in long-read and long-range genome sequencing have made it possible to produce high-quality chromosome-level genome assemblies for almost any organism. However, adequate tissue preservation for the requisite ultra-high molecular weight DNA (uHMW DNA) remains a major challenge. Here we present a comparative study of preservation methods for field and laboratory tissue sampling, across vertebrate classes and different tissue types. Results We find that storage temperature was the strongest predictor of uHMW fragment lengths. While immediate flash-freezing remains the sample preservation gold standard, samples preserved in 95% EtOH or 20-25% DMSO-EDTA showed little fragment length degradation when stored at 4 degrees C for 6 hours. Samples in 95% EtOH or 20-25% DMSO-EDTA kept at 4 degrees C for 1 week after dissection still yielded adequate amounts of uHMW DNA for most applications. Tissue type was a significant predictor of total DNA yield but not fragment length. Preservation solution had a smaller but significant influence on both fragment length and DNA yield. Conclusion We provide sample preservation guidelines that ensure sufficient DNA integrity and amount required for use with long-read and long-range sequencing technologies across vertebrates. Our best practices generated the uHMW DNA needed for the high-quality reference genomes for phase 1 of the Vertebrate Genomes Project, whose ultimate mission is to generate chromosome-level reference genome assemblies of all similar to 70,000 extant vertebrate species.

Mirman et al. report that the primary function of the shieldin complex in double-strand break repair in BRCA1-deficient cells is the recruitment of the CST-Pol alpha-primase complex to conduct fill-in synthesis. The efficacy of poly(ADP)-ribose polymerase 1 inhibition (PARPi) in BRCA1-deficient cells depends on 53BP1 and shieldin, which have been proposed to limit single-stranded DNA at double-strand breaks (DSBs) by blocking resection and/or through CST-Pol alpha-primase-mediated fill-in. We show that primase (like 53BP1-shieldin and CST-Pol alpha) promotes radial chromosome formation in PARPi-treated BRCA1-deficient cells and demonstrate shieldin-CST-Pol alpha-primase-dependent incorporation of BrdU at DSBs. In the absence of 53BP1 or shieldin, radial formation in BRCA1-deficient cells was restored by the tethering of CST near DSBs, arguing that in this context, shieldin acts primarily by recruiting CST. Furthermore, a SHLD1 mutant defective in CST binding (SHLD1 Delta) was non-functional in BRCA1-deficient cells and its function was restored after reconnecting SHLD1 Delta to CST. Interestingly, at dysfunctional telomeres and at DNA breaks in class switch recombination where CST has been implicated, SHLD1 Delta was fully functional, perhaps because these DNA ends carry CST recognition sites that afford SHLD1-independent binding of CST. These data establish that in BRCA1-deficient cells, CST-Pol alpha-primase is the major effector of shieldin-dependent DSB processing.

This essay critiques the fiercely utilitarian allocation scheme of Cameron et al. Children have no hope of recovery if their lives are cut short based on administrative protocols that misrepresent the nature of their conditions. Unilateral futility judgements - especially those based on a false predicate - are discriminatory. When considering the best interests of children, we should see possibility in disability and not advance ill-informed utilitarianism.

Generalized pustular psoriasis (GPP) is a rare, severe neutrophilic skin disorder characterized by sudden widespread eruption of superficial sterile pustules with or without systemic inflammation. GPP flares can be life-threatening if untreated due to potential severe complications such as cardiovascular failure and serious infections. Currently, there are no GPP-specific therapies approved in the USA or Europe. Retinoids, cyclosporine, and methotrexate are the most commonly used non-biologic therapies for GPP. The evidence that supports the currently available treatment options is mainly based on case reports and small, open-label, single-arm studies. However, recent advances in our understanding of the pathogenic mechanisms of GPP and the identification of gene mutations linked to the disease have paved the way for the development of specific targeted therapies that selectively suppress the autoinflammatory and autoimmune mechanisms induced during GPP flares. Several biologic agents that target key cytokines involved in the activation of inflammatory pathways, such as tumor necrosis factor-alpha blockers and interleukin (IL)-17, IL-23, and IL-12 inhibitors, have emerged as potential treatments for GPP, with several being approved in Japan. The evidence supporting the efficacy of these agents is mainly derived from small, uncontrolled trials. A notable recent advance is the discovery of IL36RN mutations and the central role of IL-36 receptor ligands in the pathogenesis of GPP, which has defined key therapeutic targets for the disease. Biologic agents that target the IL-36 pathway have demonstrated promising efficacy in patients with GPP, marking the beginning of a new era of targeted therapy for GPP.

We now know RNA can survive the harsh environment of biofluids when encapsulated in vesicles or by associating with lipoproteins or RNA binding proteins. These extracellular RNA (exRNA) play a role in intercellular signaling, serve as biomarkers of disease, and form the basis of new strategies for disease treatment. The Extracellular RNA Communication Consortium (ERCC) hosted a two-day online workshop (April 19-20, 2021) on the unique challenges of exRNA data analysis. The goal was to foster an open dialog about best practices and discuss open problems in the field, focusing initially on small exRNA sequencing data. Video recordings of workshop presentations and discussions are available (https://exRNA.org/exRNAdata2021-video). There were three target audiences: experimentalists who generate exRNA sequencing data, computational and data scientists who work with those groups to analyze their data, and experimental and data scientists new to the field. Here we summarize issues explored during the workshop, including progress on an effort to develop an exRNA data analysis challenge to engage the community in solving some of these open problems.

Background: The ring-tailed lemur (Lemur catta) is a charismatic strepsirrhine primate endemic to Madagascar. These lemurs are of particular interest, given their status as a flagship species and widespread publicity in the popular media. Unfortunately, a recent population decline has resulted in the census population decreasing to <2,500 individuals in the wild, and the species's classification as an endangered species by the IUCN. As is the case for most strepsirrhine primates, only a limited amount of genomic research has been conducted on L. catta, in part owing to the lack of genomic resources. Results: We generated a new high-quality reference genome assembly for L. catta (mLemCat1) that conforms to the standards of the Vertebrate Genomes Project. This new long-read assembly is composed of Pacific Biosciences continuous long reads (CLR data), Optical Mapping Bionano reads, Arima HiC data, and 10X linked reads. The contiguity and completeness of the assembly are extremely high, with scaffold and contig N50 values of 90.982 and 10.570 Mb, respectively. Additionally, when compared to other high-quality primate assemblies, L. catta has the lowest reported number of Alu elements, which results predominantly from a lack of AluS and AluY elements. Conclusions: mLemCat1 is an excellent genomic resource not only for the ring-tailed lemur community, but also for other members of the Lemuridae family, and is the first very long read assembly for a strepsirrhine.

Background Accurate cancer classification is essential for correct treatment selection and better prognostication. microRNAs (miRNAs) are small RNA molecules that negatively regulate gene expression, and their dyresgulation is a common disease mechanism in many cancers. Through a clearer understanding of miRNA dysregulation in cancer, improved mechanistic knowledge and better treatments can be sought. Results We present a topology-preserving deep learning framework to study miRNA dysregulation in cancer. Our study comprises miRNA expression profiles from 3685 cancer and non-cancer tissue samples and hierarchical annotations on organ and neoplasticity status. Using unsupervised learning, a two-dimensional topological map is trained to cluster similar tissue samples. Labelled samples are used after training to identify clustering accuracy in terms of tissue-of-origin and neoplasticity status. In addition, an approach using activation gradients is developed to determine the attention of the networks to miRNAs that drive the clustering. Using this deep learning framework, we classify the neoplasticity status of held-out test samples with an accuracy of 91.07%, the tissue-of-origin with 86.36%, and combined neoplasticity status and tissue-of-origin with an accuracy of 84.28%. The topological maps display the ability of miRNAs to recognize tissue types and neoplasticity status. Importantly, when our approach identifies samples that do not cluster well with their respective classes, activation gradients provide further insight in cancer subtypes or grades. Conclusions An unsupervised deep learning approach is developed for cancer classification and interpretation. This work provides an intuitive approach for understanding molecular properties of cancer and has significant potential for cancer classification and treatment selection.