COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study

Background: Individuals with cancer, particularly those who are receiving systemic anticancer treatments, have been postulated to be at increased risk of mortality from COVID-19. This conjecture has considerable effect on the treatment of patients with cancer and data from large, multicentre studies to support this assumption are scarce because of the contingencies of the pandemic. We aimed to describe the clinical and demographic characteristics and COVID-19 outcomes in patients with cancer. / Methods: In this prospective observational study, all patients with active cancer and presenting to our network of cancer centres were eligible for enrolment into the UK Coronavirus Cancer Monitoring Project (UKCCMP). The UKCCMP is the first COVID-19 clinical registry that enables near real-time reports to frontline doctors about the effects of COVID-19 on patients with cancer. Eligible patients tested positive for severe acute respiratory syndrome coronavirus 2 on RT-PCR assay from a nose or throat swab. We excluded patients with a radiological or clinical diagnosis of COVID-19, without a positive RT-PCR test. The primary endpoint was all-cause mortality, or discharge from hospital, as assessed by the reporting sites during the patient hospital admission. / Findings: From March 18, to April 26, 2020, we analysed 800 patients with a diagnosis of cancer and symptomatic COVID-19. 412 (52%) patients had a mild COVID-19 disease course. 226 (28%) patients died and risk of death was significantly associated with advancing patient age (odds ratio 9·42 [95% CI 6·56–10·02]; p<0·0001), being male (1·67 [1·19–2·34]; p=0·003), and the presence of other comorbidities such as hypertension (1·95 [1·36–2·80]; p<0·001) and cardiovascular disease (2·32 [1·47–3·64]). 281 (35%) patients had received cytotoxic chemotherapy within 4 weeks before testing positive for COVID-19. After adjusting for age, gender, and comorbidities, chemotherapy in the past 4 weeks had no significant effect on mortality from COVID-19 disease, when compared with patients with cancer who had not received recent chemotherapy (1·18 [0·81–1·72]; p=0·380). We found no significant effect on mortality for patients with immunotherapy, hormonal therapy, targeted therapy, radiotherapy use within the past 4 weeks. / Interpretation: Mortality from COVID-19 in cancer patients appears to be principally driven by age, gender, and comorbidities. We are not able to identify evidence that cancer patients on cytotoxic chemotherapy or other anticancer treatment are at an increased risk of mortality from COVID-19 disease compared with those not on active treatment. / Funding: University of Birmingham, University of Oxford

Karyotypic description of the stingless bee Oxytrigona cf. flaveola (Hymenoptera, Apidae, Meliponina) of a colony from Tangará da Serra, Mato Grosso State, Brazil

The aim was to broaden knowledge on the cytogenetics of the subtribe Meliponina, by furnishing cytogenetic data as a contribution to the characterization of bees from the genus Oxytrigona. Individuals of the species Oxytrigona cf. flaveola, members of a colony from Tangará da Serra, Mato Grosso State, Brazil, were studied. The chromosome number was 2n = 34, distributed among four chromosomal morphologies, with the karyotype formula 8m+8sm+16st+2t. Size heteromorphism in the first metacentric pair, subsequently confirmed by sequential staining with fluorochrome (DA/DAPI/CMA3 ), was apparent in all the examined individuals The nucleolar organizing regions (NORs) are possibly located in this metacentric chromosome pair. These data will contribute towards a better understanding of the genus Oxytrigona. Given that species in this group are threatened, the importance of their preservation and conservation can be shown in a sensible, concise fashion through studies such as this

Does the revised cardiac risk index predict cardiac complications following elective lung resection?

Background: Revised Cardiac Risk Index (RCRI) score and Thoracic Revised Cardiac Risk Index (ThRCRI) score were developed to predict the risks of postoperative major cardiac complications in generic surgical population and thoracic surgery respectively. This study aims to determine the accuracy of these scores in predicting the risk of developing cardiac complications including atrial arrhythmias after lung resection surgery in adults. Methods: We studied 703 patients undergoing lung resection surgery in a tertiary thoracic surgery centre. Observed outcome measures of postoperative cardiac morbidity and mortality were compared against those predicted by risk. Results: Postoperative major cardiac complications and supraventricular arrhythmias occurred in 4.8% of patients. Both index scores had poor discriminative ability for predicting postoperative cardiac complications with an area under receiver operating characteristic (ROC) curve of 0.59 (95% CI 0.51-0.67) for the RCRI score and 0.57 (95% CI 0.49-0.66) for the ThRCRI score. Conclusions: In our cohort, RCRI and ThRCRI scores failed to accurately predict the risk of cardiac complications in patients undergoing elective resection of lung cancer. The British Thoracic Society (BTS) recommendation to seek a cardiology referral for all asymptomatic pre-operative lung resection patients with > 3 RCRI risk factors is thus unlikely to be of clinical benefit

Overcoming multiple drug resistance mechanisms in medulloblastoma

Introduction: Medulloblastoma (MB) is the most common malignant paediatric brain tumour. Recurrence and progression of disease occurs in 15-20% of standard risk and 30-40% of high risk patients. We analysed whether circumvention of chemoresistance pathways (drug export, DNA repair and apoptotic inhibition) can restore chemotherapeutic efficacy in a panel of MB cell lines. Results: We demonstrate, by immunohistochemistry in patient tissue microarrays, that ABCB1 is expressed in 43% of tumours and is significantly associated with high-risk. We show that ABCB1, O6-methylguanine-DNA-methyltransferase (MGMT) and BCL2 family members are differentially expressed (by quantitative reverse transcription polymerase chain reaction, Western blotting and flow cytometry) in MB cell lines. Based on these findings, each pathway was then inhibited or circumvented and cell survival assessed using clonogenic assays. Inhibition of ABCB1 using vardenafil or verapamil resulted in a significant increase in sensitivity to etoposide in ABCB1-expressing MB cell lines. Sensitivity to temozolomide (TMZ) was MGMT-dependent, but two novel imidazotetrazine derivatives (N-3 sulfoxide and N-3 propargyl TMZ analogues) demonstrated ≥7 fold and ≥3 fold more potent cytotoxicity respectively compared to TMZ in MGMT-expressing MB cell lines. Activity of the BAD mimetic ABT-737 was BCL2A1 and ABCB1 dependent, whereas the pan-BCL2 inhibitor obatoclax was effective as a single cytotoxic agent irrespective of MCL1, BCL2, BCL2A1, or ABCB1 expression. Conclusions: ABCB1 is associated with high-risk MB; hence, inhibition of ABCB1 by vardenafil may represent a valid approach in these patients. Imidazotetrazine analogues of TMZ and the BH3 mimetic obatoclax are promising clinical candidates in drug resistant MB tumours expressing MGMT and BCL2 anti-apoptotic members respectively

Innate recognition of apoptotic cells:novel apoptotic cell-associated molecular patterns revealed by crossreactivity of anti-LPS antibodies

Cells dying by apoptosis are normally cleared by phagocytes through mechanisms that can suppress inflammation and immunity. Molecules of the innate immune system, the pattern recognition receptors (PRRs), are able to interact not only with conserved structures on microbes (pathogen-associated molecular patterns, PAMPs) but also with ligands displayed by apoptotic cells. We reasoned that PRRs might therefore interact with structures on apoptotic cells-apoptotic cell-associated molecular patterns (ACAMPs)-that are analogous to PAMPs. Here we show that certain monoclonal antibodies raised against the prototypic PAMP, lipopolysaccharide (LPS), can crossreact with apoptotic cells. We demonstrate that one such antibody interacts with a constitutively expressed intracellular protein, laminin-binding protein, which translocates to the cell surface during apoptosis and can interact with cells expressing the prototypic PRR, mCD14 as well as with CD14-negative cells. Anti-LPS cross reactive epitopes on apoptotic cells colocalised with annexin V-and C1q-binding sites on vesicular regions of apoptotic cell surfaces and were released associated with apoptotic cell-derived microvesicles (MVs). These results confirm that apoptotic cells and microbes can interact with the immune system through common elements and suggest that anti-PAMP antibodies could be used strategically to characterise novel ACAMPs associated not only with apoptotic cells but also with derived MVs

Genetic variability in five populations of Partamona helleri (Hymenoptera, Apidae) from Minas Gerais State, Brazil

Partamona is a Neotropical genus of stingless bees that comprises 33 species distributed from Mexico to southern Brazil. These bees are well-adapted to anthropic environments and build their nests in several substrates. In this study, 66 colonies of Partamona helleri from five localities in the Brazilian state of Minas Gerais (São Miguel do Anta, Teixeiras, Porto Firme, Viçosa and Rio Vermelho) were analyzed using nine microsatellite loci in order to assess their genetic variability. Low levels of observed (Ho = 0.099-0.137) and expected (H e = 0.128-0.145) heterozygosity were encountered and revealed discrete genetic differentiation among the populations (F ST = 0.025). AMOVA further showed that most of the total genetic variation (94.24%) in P. helleri was explained by the variability within local populations

Garden and landscape-scale correlates of moths of differing conservation status: significant effects of urbanization and habitat diversity

Moths are abundant and ubiquitous in vegetated terrestrial environments and are pollinators, important herbivores of wild plants, and food for birds, bats and rodents. In recent years, many once abundant and widespread species have shown sharp declines that have been cited by some as indicative of a widespread insect biodiversity crisis. Likely causes of these declines include agricultural intensification, light pollution, climate change, and urbanization; however, the real underlying cause(s) is still open to conjecture. We used data collected from the citizen science Garden Moth Scheme (GMS) to explore the spatial association between the abundance of 195 widespread British species of moth, and garden habitat and landscape features, to see if spatial habitat and landscape associations varied for species of differing conservation status. We found that associations with habitat and landscape composition were species-specific, but that there were consistent trends in species richness and total moth abundance. Gardens with more diverse and extensive microhabitats were associated with higher species richness and moth abundance; gardens near to the coast were associated with higher richness and moth abundance; and gardens in more urbanized locations were associated with lower species richness and moth abundance. The same trends were also found for species classified as increasing, declining and vulnerable under IUCN (World Conservation Union) criteria

High local substrate availability stabilizes a cooperative trait

Cooperative behavior is widely spread in microbial populations. An example is the expression of an extracellular protease by the lactic acid bacterium Lactococcus lactis, which degrades milk proteins into free utilizable peptides that are essential to allow growth to high cell densities in milk. Cheating, protease-negative strains can invade the population and drive the protease-positive strain to extinction. By using multiple experimental approaches, as well as modeling population dynamics, we demonstrate that the persistence of the proteolytic trait is determined by the fraction of the generated peptides that can be captured by the cell before diffusing away from it. The mechanism described is likely to be relevant for the evolutionary stability of many extracellular substrate-degrading enzymes

Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error

BACKGROUND: Here, we outline a method of applying existing machine learning (ML) approaches to aid citation screening in an on-going broad and shallow systematic review of preclinical animal studies. The aim is to achieve a high-performing algorithm comparable to human screening that can reduce human resources required for carrying out this step of a systematic review. METHODS: We applied ML approaches to a broad systematic review of animal models of depression at the citation screening stage. We tested two independently developed ML approaches which used different classification models and feature sets. We recorded the performance of the ML approaches on an unseen validation set of papers using sensitivity, specificity and accuracy. We aimed to achieve 95% sensitivity and to maximise specificity. The classification model providing the most accurate predictions was applied to the remaining unseen records in the dataset and will be used in the next stage of the preclinical biomedical sciences systematic review. We used a cross-validation technique to assign ML inclusion likelihood scores to the human screened records, to identify potential errors made during the human screening process (error analysis). RESULTS: ML approaches reached 98.7% sensitivity based on learning from a training set of 5749 records, with an inclusion prevalence of 13.2%. The highest level of specificity reached was 86%. Performance was assessed on an independent validation dataset. Human errors in the training and validation sets were successfully identified using the assigned inclusion likelihood from the ML model to highlight discrepancies. Training the ML algorithm on the corrected dataset improved the specificity of the algorithm without compromising sensitivity. Error analysis correction leads to a 3% improvement in sensitivity and specificity, which increases precision and accuracy of the ML algorithm. CONCLUSIONS: This work has confirmed the performance and application of ML algorithms for screening in systematic reviews of preclinical animal studies. It has highlighted the novel use of ML algorithms to identify human error. This needs to be confirmed in other reviews with different inclusion prevalence levels, but represents a promising approach to integrating human decisions and automation in systematic review methodology