Subliminal versus supraliminal stimuli activate neural responses in anterior cingulate cortex, fusiform gyrus and insula:a meta-analysis of fMRI studies

Background: Non-conscious neural activation may underlie various psychological functions in health and disorder. However, the neural substrates of non-conscious processing have not been entirely elucidated. Examining the differential effects of arousing stimuli that are consciously, versus unconsciously perceived will improve our knowledge of neural circuitry involved in non-conscious perception. Here we conduct preliminary analyses of neural activation in studies that have used both subliminal and supraliminal presentation of the same stimulus. Methods: We use Activation Likelihood Estimation (ALE) to examine functional Magnetic Resonance Imaging (fMRI) studies that uniquely present the same stimuli subliminally and supraliminally to healthy participants during functional magnetic resonance imaging (fMRI). We included a total of 193 foci from 9 studies representing subliminal stimulation and 315 foci from 10 studies representing supraliminal stimulation. Results: The anterior cingulate cortex is significantly activated during both subliminal and supraliminal stimulus presentation. Subliminal stimuli are linked to significantly increased activation in the right fusiform gyrus and right insula. Supraliminal stimuli show significantly increased activation in the left rostral anterior cingulate. Conclusions: Non-conscious processing of arousing stimuli may involve primary visual areas and may also recruit the insula, a brain area involved in eventual interoceptive awareness. The anterior cingulate is perhaps a key brain region for the integration of conscious and non-conscious processing. These preliminary data provide candidate brain regions for further study in to the neural correlates of conscious experience

Improved annotation with <i>de novo</i> transcriptome assembly in four social amoeba species

Background: Annotation of gene models and transcripts is a fundamental step in genome sequencing projects. Often this is performed with automated prediction pipelines, which can miss complex and atypical genes or transcripts. RNA sequencing (RNA-seq) data can aid the annotation with empirical data. Here we present de novo transcriptome assemblies generated from RNA-seq data in four Dictyostelid species: D. discoideum, P. pallidum, D. fasciculatum and D. lacteum. The assemblies were incorporated with existing gene models to determine corrections and improvement on a whole-genome scale. This is the first time this has been performed in these eukaryotic species. Results: An initial de novo transcriptome assembly was generated by Trinity for each species and then refined with Program to Assemble Spliced Alignments (PASA). The completeness and quality were assessed with the Benchmarking Universal Single-Copy Orthologs (BUSCO) and Transrate tools at each stage of the assemblies. The final datasets of 11,315-12,849 transcripts contained 5,610-7,712 updates and corrections to >50% of existing gene models including changes to hundreds or thousands of protein products. Putative novel genes are also identified and alternative splice isoforms were observed for the first time in P. pallidum, D. lacteum and D. fasciculatum. Conclusions: In taking a whole transcriptome approach to genome annotation with empirical data we have been able to enrich the annotations of four existing genome sequencing projects. In doing so we have identified updates to the majority of the gene annotations across all four species under study and found putative novel genes and transcripts which could be worthy for follow-up. The new transcriptome data we present here will be a valuable resource for genome curators in the Dictyostelia and we propose this effective methodology for use in other genome annotation projects

The impact of the COVID-19 pandemic on the provision & utilisation of primary health care services in Goma, Democratic Republic of the Congo, Kambia district, Sierra Leone & Masaka district, Uganda.

INTRODUCTION: This study aimed to determine whether the COVID-19 pandemic had an impact on essential primary healthcare services at public primary healthcare facilities. METHODS: The number of weekly consultations for antenatal care (ANC), outpatient (OPD), immunisations (EPI), family planning (FP) and HIV services, between January 2018 and December 2020, were collected from 25 facilities in Masaka district, Uganda, 21 in Goma, and 29 in Kambia district, Sierra Leone. Negative binomial regression models accounting for clustering and season were used to analyse changes in activity levels between 2018, 2019 and 2020. RESULTS: In Goma, we found no change in OPD, EPI or ANC consultations, FP was 17% lower in March-July 2020 compared to 2019, but this recovered by December 2020. New diagnoses of HIV were 34% lower throughout 2020 compared to 2019. In Sierra Leone, compared to the same periods in 2019, facilities had 18-29% fewer OPD consultations throughout 2020, and 27% fewer DTP3 doses in March-July 2020. There was no evidence of differences in other services. In Uganda there were 20-35% fewer under-5 OPD consultations, 21-66% fewer MCV1 doses, and 48-51% fewer new diagnoses of HIV throughout 2020, compared to 2019. There was no difference in the number of HPV doses delivered. CONCLUSIONS: The level of disruption varied across the different settings and qualitatively appeared to correlate with the strength of lockdown measures and reported attitudes towards the risk posed by COVID-19. Mitigation strategies such as health communications campaigns and outreach services may be important to limit the impact of lockdowns on primary healthcare services

The fragmented COVID-19 therapeutics research landscape: a living systematic review of clinical trial registrations evaluating priority pharmacological interventions. [version 1; peer review: 1 approved]

Background: Many available medicines have been evaluated as potential repurposed treatments for coronavirus disease 2019 (COVID-19). We summarise the registered study landscape for 32 priority pharmacological treatments identified following consultation with external experts of the COVID-19 Clinical Research Coalition. Methods: All eligible trial registry records identified by systematic searches of the World Health Organisation International Clinical Trials Registry Platform as of 26th May 2021 were reviewed and extracted. A descriptive summary of study characteristics was performed. Results: We identified 1,314 registered studies that included at least one of the 32 priority pharmacological interventions. The majority (1,043, 79%) were randomised controlled trials (RCTs). The sample size of the RCTs identified was typically small (median (25th, 75th percentile) sample size = 140 patients (70, 383)), i.e. individually powered only to show very large effects. The most extensively evaluated medicine was hydroxychloroquine (418 registered studies). Other widely studied interventions were convalescent plasma (n=208), ritonavir (n=189) usually combined with lopinavir (n=181), and azithromycin (n=147). Very few RCTs planned to recruit participants in low-income countries (n=14; 1.3%). A minority of studies (348, 26%) indicated a willingness to share individual participant data. The living systematic review data are available at https://iddo.cognitive.city Conclusions: There are many registered studies planning to evaluate available medicines as potential repurposed treatments of COVID-19. Most of these planned studies are small, and therefore substantially underpowered for most relevant endpoints. Very few are large enough to have any chance of providing enough convincing evidence to change policies and practices. The sharing of individual participant data (IPD) from these studies would allow pooled IPD meta-analyses which could generate definitive conclusions, but most registered studies did not indicate that they were willing to share their data

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging

Influenza vaccination for immunocompromised patients: systematic review and meta-analysis from a public health policy perspective.

Immunocompromised patients are vulnerable to severe or complicated influenza infection. Vaccination is widely recommended for this group. This systematic review and meta-analysis assesses influenza vaccination for immunocompromised patients in terms of preventing influenza-like illness and laboratory confirmed influenza, serological response and adverse events

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

Global variation in anastomosis and end colostomy formation following left-sided colorectal resection

Background End colostomy rates following colorectal resection vary across institutions in high-income settings, being influenced by patient, disease, surgeon and system factors. This study aimed to assess global variation in end colostomy rates after left-sided colorectal resection. Methods This study comprised an analysis of GlobalSurg-1 and -2 international, prospective, observational cohort studies (2014, 2016), including consecutive adult patients undergoing elective or emergency left-sided colorectal resection within discrete 2-week windows. Countries were grouped into high-, middle- and low-income tertiles according to the United Nations Human Development Index (HDI). Factors associated with colostomy formation versus primary anastomosis were explored using a multilevel, multivariable logistic regression model. Results In total, 1635 patients from 242 hospitals in 57 countries undergoing left-sided colorectal resection were included: 113 (6·9 per cent) from low-HDI, 254 (15·5 per cent) from middle-HDI and 1268 (77·6 per cent) from high-HDI countries. There was a higher proportion of patients with perforated disease (57·5, 40·9 and 35·4 per cent; P < 0·001) and subsequent use of end colostomy (52·2, 24·8 and 18·9 per cent; P < 0·001) in low- compared with middle- and high-HDI settings. The association with colostomy use in low-HDI settings persisted (odds ratio (OR) 3·20, 95 per cent c.i. 1·35 to 7·57; P = 0·008) after risk adjustment for malignant disease (OR 2·34, 1·65 to 3·32; P < 0·001), emergency surgery (OR 4·08, 2·73 to 6·10; P < 0·001), time to operation at least 48 h (OR 1·99, 1·28 to 3·09; P = 0·002) and disease perforation (OR 4·00, 2·81 to 5·69; P < 0·001). Conclusion Global differences existed in the proportion of patients receiving end stomas after left-sided colorectal resection based on income, which went beyond case mix alone

Capability of CAM5.1 in simulating maximum air temperature patterns over West Africa during boreal spring

This study classifies maximum air temperature patterns over West Africa into six&nbsp;groups and evaluates the capability of a global climate model (Community Atmospheric Model version 5.1; CAM) to simulate them. We analyzed 45-year (1961–2005) multi-ensemble (50 members) simulations from CAM and compared the results with those of the Climate Research Unit (CRU) and the twentieth Century Reanalysis data sets.&nbsp;Using Self Organizing Map algorithm&nbsp;to classify the spatial patterns of maximum air temperature during boreal spring, the study reveals&nbsp;the temperature patterns that CAM can simulate well&nbsp;and those the model&nbsp;struggles to reproduce. The results show that the best agreements between the composites of observation and CAM occur in the first temperature pattern&nbsp;group (which features positive&nbsp;temperatures&nbsp;anomalies over the&nbsp;Sahel) and Node 2 (which features&nbsp;near-normal temperature) pattern of the third group. CAM succeeded in reproducing some of the associated regional atmospheric dynamics and thermodynamic features in winds&nbsp;(horizontal and vertical), temperature fields, the cloud fractions, and the mean sea-level pressure. Although CAM struggles to capture the relationship between air temperature&nbsp;patterns and tele-connection indices during the boreal spring season over West Africa, it agrees with observations that temperature patterns over the sub-region cannot be associated with a single climate index. An&nbsp;ensemble member (SIM48) captures the inter-annual variation of the observed temperaure patterns with high sycronization (ɳ &gt; 44%), much better than that of&nbsp;ensembles mean (ɳ &lt; 30%). SIM48 also captures adequately four of the spatial patterns in comparison to three captured by the ensembles mean. This indicates that, for better seasonal forecasts and more reliable future climate projections, the practice whereby an ensemble mean is based on uniformly averaging the members rather than the performance of individual ensemble members needs to be reviewed. The results of the study&nbsp;may be used to improve the perfomance of CAM over West Africa, thereby&nbsp;strengthening the on-going efforts to include CAM as part of multi-model forecasting system over West Africa