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Introduction: The pandemic saw widespread use of home pulse oximeters to patients diagnosed with COVID-19 to support early detection of low oxygen saturation levels and appropriate care. Rapid implementation made conventional evaluation challenging, highlighting the need for rigorous non-randomised methods to support decision-making about future use of these technologies. We used routine data to explore the benefits of pulse oximetry in Greater Manchester, under the 'COVID-19 oximetry at home' (CO@h) programme. Methods: We used data from the Greater Manchester Secure Data Environment and defined study parameters using a 'target trial' model to compare patients receiving pulse oximetry under the CO@h programme, with matched controls using various comparator groups. Primary outcomes were unplanned hospitalisation and all-cause mortality. This study is based on data from the Greater Manchester Care Record (GMCR), using anonymised, routinely collected data provided in a de-identified format for research. Informed written consent is needed for primary care patient data to be collected for service improvement and research, before data extraction to the GMCR. The study was approved under protocol GMCR RQ-048, on 12/05/2022. As indicated by the University of Manchester ethics decision tool, formal ethical approval was not required for this study. Results: The adjusted odds ratios for an unplanned hospitalisation were higher among patients receiving pulse oximetry: OR 1.86 (95% CI 1.54–2.25) at 28 days, 1.5 (95% CI 1.3–1.74) at 90 days and 1.63 (95% CI 1.44–1.83) at 1 year. Overall odds of mortality were lower among patients receiving pulse oximetry: adjusted ORs of 0.5 (95% CI 0.25–0.98) at 28 days, 0.5 (95% CI 0.32–0.78) at 90 days and 0.58 (95% CI 0.44–0.76) at 1 year. The results were robust to different comparison groups. Conclusion: Use of pulse oximetry at home under the CO@h programme, through the resulting prioritisation for appropriate care, was associated with a higher frequency of unplanned admissions and a reduction in the risk of mortality up to 1 year later. Therefore, it is likely effective for early detection of clinical deterioration and timely intervention among patients with COVID-19. Further research is needed to understand whether this is a cost-effective use of healthcare resources. [ABSTRACT FROM AUTHOR]

Renal cell carcinoma (RCC) is among the top ten most common forms of cancer and is the most common malignancy of the kidney. Clear cell renal carcinoma (cc-RCC), the most common type of RCC, is one of the most refractory cancers with an incidence that is on the rise. Screening of plant extracts in search of new anti-cancer agents resulted in the discovery of englerin A, a guaiane sesquiterpene with potent cytotoxicity against renal cancer cells and a small subset of other cancer cells. Though a few cellular targets have been identified for englerin A, it is still not clear what mechanisms account for the cytotoxicity of englerin A in RCC, which occurs at concentrations well below those used to engage the targets previously identified. Unlike any prior study, the current study used a systems biology approach to explore the mechanism(s) of action of englerin A. Metabolomics analyses indicated that englerin A profoundly altered lipid metabolism by 24 h in cc-RCC cell lines and generated significant levels of ceramides that were highly toxic to these cells. Microarray analyses determined that englerin A induced ER stress signaling and an acute inflammatory response, which was confirmed by quantitative PCR and Western Blot analyses. Additionally, fluorescence confocal microscopy revealed that englerin A at 25 nM disrupted the morphology of the ER confirming the deleterious effect of englerin A on the ER. Collectively, our findings suggest that cc-RCC is highly sensitive to disruptions in lipid metabolism and ER stress and that these vulnerabilities can be targeted for the treatment of cc-RCC and possibly other lipid storing cancers. Furthermore, our results suggest that ceramides may be a mediator of some of the actions of englerin A. Lastly, the acute inflammatory response induced by englerin A may mediate anti-tumor immunity.

The INK4A locus codes for two independent tumor suppressors, p14ARF and p16/CDKN2A, and is frequently mutated in many cancers. Here we report a novel deletion/substitution from CC to T in the shared exon 2 of p14ARF/p16 in a melanoma cell line. This mutation aligns the reading frames of p14ARF and p16 mid-transcript, producing one protein which is half p14ARF and half p16, chimera ARF (chARF), and another which is half p16 and half non-p14ARF/non-p16 amino acids, p16-Alternate Carboxyl Terminal (p16-ACT). In an effort to understand the cellular impact of this novel mutation and others like it, we expressed the two protein products in a tumor cell line and analyzed common p14ARF and p16 pathways, including the p53/p21 and CDK4/cyclin D1 pathways, as well as the influence of the two proteins on growth and the cell cycle. We report that chARF mimicked wild-type p14ARF by inducing the p53/p21 pathway, inhibiting cell growth through G2/M arrest and maintaining a certain percentage of cells in G1 during nocodazole-induced G2 arrest. chARF also demonstrated p16 activity by binding CDK4. However, rather than preventing cyclin D1 from binding CDK4, chARF stabilized this interaction through p21 which bound CDK4. p16-ACT had no p16-related function as it was unable to inhibit cyclin D1/CDK4 complex formation and was unable to arrest the cell cycle, though it did inhibit colony formation. We conclude that these novel chimeric proteins, which are very similar to predicted p16/p14ARF chimeric proteins found in other primary cancers, result in maintained p14ARF-p53-p21 signaling while p16-dependent CDK4 inhibition is lost.

Background: Li-Fraumeni syndrome is caused by germline TP53 mutations and is clinically characterized by a predisposition to a range of cancers, most commonly sarcoma, brain tumours and leukemia. Pathogenic mosaic TP53 mutations have only rarely been described. Methods and Findings: We describe a 2 years old child presenting with three separate cancers over a 6 month period; two soft tissue mesenchymal tumors and an aggressive metastatic neuroblastoma. As conventional testing of blood DNA by Sanger sequencing for mutations in TP53, ALK, and SDH was negative, whole exome sequencing of the blood DNA of the patient and both parents was performed to screen more widely for cancer predisposing mutations. In the patient's but not the parents' DNA we found a c.743 G>A, p.Arg248Gln (CCDS11118.1) TP53 mutation in 3–20% of sequencing reads, a level that would not generally be detectable by Sanger sequencing. Homozygosity for this mutation was detected in all tumor samples analyzed, and germline mosaicism was demonstrated by analysis of the child's newborn blood spot DNA. The occurrence of separate tumors derived from different germ layers suggests that this de novo mutation occurred early in embryogenesis, prior to gastrulation. Conclusion: The case demonstrates pathogenic mosaicim, detected by next generation deep sequencing, that arose in the early stages of embryogenesis. [ABSTRACT FROM AUTHOR]

A central challenge of conservation biology is using limited data to predict rare species occurrence and identify conservation areas that play a disproportionate role in regional persistence. Where species occupy discrete patches in a landscape, such predictions require data about environmental quality of individual patches and the connectivity among high quality patches. We present a novel extension to species occupancy modeling that blends traditional predictions of individual patch environmental quality with network analysis to estimate connectivity characteristics using limited survey data. We demonstrate this approach using environmental and geospatial attributes to predict observed occupancy patterns of the Yosemite toad (Anaxyrus (= Bufo) canorus) across >2,500 meadows in Yosemite National Park (USA). A. canorus, a Federal Proposed Species, breeds in shallow water associated with meadows. Our generalized linear model (GLM) accurately predicted ~84% of true presence-absence data on a subset of data withheld for testing. The predicted environmental quality of each meadow was iteratively ‘boosted’ by the quality of neighbors within dispersal distance. We used this park-wide meadow connectivity network to estimate the relative influence of an individual Meadow’s ‘environmental quality’ versus its ‘network quality’ to predict: a) clusters of high quality breeding meadows potentially linked by dispersal, b) breeding meadows with high environmental quality that are isolated from other such meadows, c) breeding meadows with lower environmental quality where long-term persistence may critically depend on the network neighborhood, and d) breeding meadows with the biggest impact on park-wide breeding patterns. Combined with targeted data on dispersal, genetics, disease, and other potential stressors, these results can guide designation of core conservation areas for A. canorus in Yosemite National Park. [ABSTRACT FROM AUTHOR]

A central challenge of conservation biology is using limited data to predict rare species occurrence and identify conservation areas that play a disproportionate role in regional persistence. Where species occupy discrete patches in a landscape, such predictions require data about environmental quality of individual patches and the connectivity among high quality patches. We present a novel extension to species occupancy modeling that blends traditional predictions of individual patch environmental quality with network analysis to estimate connectivity characteristics using limited survey data. We demonstrate this approach using environmental and geospatial attributes to predict observed occupancy patterns of the Yosemite toad (Anaxyrus (= Bufo) canorus) across >2,500 meadows in Yosemite National Park (USA). A. canorus, a Federal Proposed Species, breeds in shallow water associated with meadows. Our generalized linear model (GLM) accurately predicted ~84% of true presence-absence data on a subset of data withheld for testing. The predicted environmental quality of each meadow was iteratively ‘boosted’ by the quality of neighbors within dispersal distance. We used this park-wide meadow connectivity network to estimate the relative influence of an individual Meadow’s ‘environmental quality’ versus its ‘network quality’ to predict: a) clusters of high quality breeding meadows potentially linked by dispersal, b) breeding meadows with high environmental quality that are isolated from other such meadows, c) breeding meadows with lower environmental quality where long-term persistence may critically depend on the network neighborhood, and d) breeding meadows with the biggest impact on park-wide breeding patterns. Combined with targeted data on dispersal, genetics, disease, and other potential stressors, these results can guide designation of core conservation areas for A. canorus in Yosemite National Park. [ABSTRACT FROM AUTHOR]