Notes

Effect on expansion of experience of maternal antiretroviral treatments throughout breastmilk as opposed to extended toddler nevirapine prophylaxis amongst HIV-exposed perinatally uninfected babies inside the PROMISE randomized trial.
with T-ALL without excess relapse.
The study of rare diseases, such as multiple myeloma (MM), often experiences unique research hurdles that can delay or prevent lifesaving discoveries. HealthTree Cure Hub is a first-in-class software program designed to overcome these potential research hurdles.

We assessed whether HealthTree Cure Hub improved four commonly experienced research hurdles such as (1) small numbers of patient accrual to clinical trials and research studies, (2) shallow and isolated data sets, (3) high costs to answer research questions, and (4) lack of long-term follow-up patient data.

As of June 2021, HealthTree Cure Hub, with its unique portal features, has attracted 9,225 patients with MM and diverse demographic backgrounds. While completing an online health profile, patients shared comprehensive data, as well as provided consent to contribute data from electronic medical records. Portal use answered research questions using patient-driven real-world data. This also cultivated relationships with patients and established communication channels that enabled continual patient contact to allow for long-term follow-up.

These results suggest that a patient-driven data capture tool such as HealthTree Cure Hub will help alleviate common research hurdles, which, in turn, will accelerate MM research, develop new hypotheses, and ultimately improve survival.
These results suggest that a patient-driven data capture tool such as HealthTree Cure Hub will help alleviate common research hurdles, which, in turn, will accelerate MM research, develop new hypotheses, and ultimately improve survival.
Deep learning (DL) models have rapidly become a popular and cost-effective tool for image classification within oncology. A major limitation of DL models is their vulnerability to adversarial images, manipulated input images designed to cause misclassifications by DL models. The purpose of the study is to investigate the robustness of DL models trained on diagnostic images using adversarial images and explore the utility of an iterative adversarial training approach to improve the robustness of DL models against adversarial images.

We examined the impact of adversarial images on the classification accuracies of DL models trained to classify cancerous lesions across three common oncologic imaging modalities. The computed tomography (CT) model was trained to classify malignant lung nodules. The mammogram model was trained to classify malignant breast lesions. The magnetic resonance imaging (MRI) model was trained to classify brain metastases.

Oncologic images showed instability to small pixel-level changebustness of DL models to such pixel-level changes. learn more Before clinical implementation, adversarial training should be considered to proposed DL models to improve overall performance and safety.Recurrent novae are repeating thermonuclear explosions in the outer layers of white dwarfs, due to the accretion of fresh material from a binary companion. The shock generated when ejected material slams into the companion star's wind can accelerate particles. We report very-high-energy (VHE; [Formula see text]) gamma rays from the recurrent nova RS Ophiuchi, up to 1 month after its 2021 outburst, observed using the High Energy Stereoscopic System (H.E.S.S.). The temporal profile of VHE emission is similar to that of lower-energy giga-electron volt emission, indicating a common origin, with a 2-day delay in peak flux. These observations constrain models of time-dependent particle energization, favoring a hadronic emission scenario over the leptonic alternative. Shocks in dense winds provide favorable environments for efficient acceleration of cosmic rays to very high energies.This month in Geneva, the 196 parties to the United Nations (UN) Convention on Biological Diversity will discuss the post-2020 Global Biodiversity Framework, in preparation for part two of the UN Biodiversity Conference (COP 15) in Kunming, China. By driving biodiversity actions worldwide through 2030 and beyond, this is arguably the most important biodiversity policy process of our time.On 14 August 2021, the moment magnitude (Mw) 7.2 Nippes earthquake in Haiti occurred within the same fault zone as its devastating 2010 Mw 7.0 predecessor, but struck the country when field access was limited by insecurity and conventional seismometers from the national network were inoperative. A network of citizen seismometers installed in 2019 provided near-field data critical to rapidly understand the mechanism of the mainshock and monitor its aftershock sequence. Their real-time data defined two aftershock clusters that coincide with two areas of coseismic slip derived from inversions of conventional seismological and geodetic data. Machine learning applied to data from the citizen seismometer closest to the mainshock allows us to forecast aftershocks as accurately as with the network-derived catalog. This shows the utility of citizen science contributing to our understanding of a major earthquake.Cytokines signal through cell surface receptor dimers to initiate activation of intracellular Janus kinases (JAKs). We report the 3.6-angstrom-resolution cryo-electron microscopy structure of full-length JAK1 complexed with a cytokine receptor intracellular domain Box1 and Box2 regions captured as an activated homodimer bearing the valine→phenylalanine (VF) mutation prevalent in myeloproliferative neoplasms. The seven domains of JAK1 form an extended structural unit, the dimerization of which is mediated by close-packing of the pseudokinase (PK) domains from the monomeric subunits. The oncogenic VF mutation lies within the core of the JAK1 PK interdimer interface, enhancing packing complementarity to facilitate ligand-independent activation. The carboxy-terminal tyrosine kinase domains are poised for transactivation and to phosphorylate the receptor STAT (signal transducer and activator of transcription)-recruiting motifs projecting from the overhanging FERM (four-point-one, ezrin, radixin, moesin)-SH2 (Src homology 2)-domains. Mapping of constitutively active JAK mutants supports a two-step allosteric activation mechanism and reveals opportunities for selective therapeutic targeting of oncogenic JAK signaling.
Biomarkers on the basis of tumor-infiltrating lymphocytes (TIL) are potentially valuable in predicting the effectiveness of immune checkpoint inhibitors (ICI). However, clinical application remains challenging because of methodologic limitations and laborious process involved in spatial analysis of TIL distribution in whole-slide images (WSI).

We have developed an artificial intelligence (AI)-powered WSI analyzer of TIL in the tumor microenvironment that can define three immune phenotypes (IPs) inflamed, immune-excluded, and immune-desert. These IPs were correlated with tumor response to ICI and survival in two independent cohorts of patients with advanced non-small-cell lung cancer (NSCLC).

Inflamed IP correlated with enrichment in local immune cytolytic activity, higher response rate, and prolonged progression-free survival compared with patients with immune-excluded or immune-desert phenotypes. At the WSI level, there was significant positive correlation between tumor proportion score (TPS) as determined by the AI model and control TPS analyzed by pathologists (
< .001). Overall, 44.0% of tumors were inflamed, 37.1% were immune-excluded, and 18.9% were immune-desert. Incidence of inflamed IP in patients with programmed death ligand-1 TPS at < 1%, 1%-49%, and ≥ 50% was 31.7%, 42.5%, and 56.8%, respectively. Median progression-free survival and overall survival were, respectively, 4.1 months and 24.8 months with inflamed IP, 2.2 months and 14.0 months with immune-excluded IP, and 2.4 months and 10.6 months with immune-desert IP.

The AI-powered spatial analysis of TIL correlated with tumor response and progression-free survival of ICI in advanced NSCLC. This is potentially a supplementary biomarker to TPS as determined by a pathologist.
The AI-powered spatial analysis of TIL correlated with tumor response and progression-free survival of ICI in advanced NSCLC. This is potentially a supplementary biomarker to TPS as determined by a pathologist.SARS-CoV-2 primarily replicates in mucosal sites, and more information is needed about immune responses in infected tissues. Here, we used rhesus macaques to model protective primary immune responses in tissues during mild COVID-19. Viral RNA levels were highest on days 1-2 post-infection and fell precipitously thereafter. 18F-fluorodeoxyglucose (FDG)-avid lung abnormalities and interferon (IFN)-activated monocytes and macrophages in the bronchoalveolar lavage (BAL) were found on days 3-4 post-infection. Virus-specific effector CD8+ and CD4+ T cells became detectable in the BAL and lung tissue on days 7-10, after viral RNA, radiologic evidence of lung inflammation, and IFN-activated myeloid cells had substantially declined. Notably, SARS-CoV-2-specific T cells were not detectable in the nasal turbinates, salivary glands, and tonsils on day 10 post-infection. Thus, SARS-CoV-2 replication wanes in the lungs of rhesus macaques prior to T cell responses, and in the nasal and oral mucosa despite the apparent lack of antigen-specific T cells, suggesting that innate immunity efficiently restricts viral replication during mild COVID-19.The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology, to patients seen in their own clinical practice.The disruption of polynucleotide kinase/phosphatase (PNKP) in colorectal cancer (CRC) cells deficient in phosphatase and tensin homolog (PTEN) is expected to lead to the loss of cell viability by a process known as synthetic lethality. In previous studies, we have reported on the encapsulation of a novel inhibitor of PNKP, namely, A83B4C63, in polymeric micelles and its activity in slowing the growth of PTEN-deficient CRC cells as well as subcutaneous xenografts. In this study, to enhance drug delivery and specificity to CRC tumors, the surface of polymeric micelles carrying A83B4C63 was modified with GE11, a peptide targeting epidermal growth factor receptor (EGFR) overexpressed in about 70% of CRC tumors. Using molecular dynamics (MD) simulations, we assessed the binding site and affinity of GE11 for EGFR. The GE11-modified micelles, tagged with a near-infrared fluorophore, showed enhanced internalization by EGFR-overexpressing CRC cells in vitro and a trend toward increased primary tumor homing in an orthotopic CRC xenograft in vivo. In line with these observations, the GE11 modification of polymeric micelles was shown to positively contribute to the improved therapeutic activity of encapsulated A83B4C63 against HCT116-PTEN-/- cells in vitro and that of orthotopic CRC xenograft in vivo. In conclusion, our results provided proof of principle evidence for the potential benefit of EGFR targeted polymeric micellar formulations of A83B4C63 as monotherapeutics for aggressive and metastatic CRC tumors but at the same time highlighted the need for the development of EGFR ligands with improved physiological stability and EGFR binding.
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