Vaccines provide disproportional protection to the increased hospitalisation risk posed by the Delta variant of SARS-CoV2: a meta-analysis

Variants of SARS-CoV2 that achieved global dominance (Alpha and Delta) have been associated with increased hospitalisation risk. A quantification of this risk across studies is currently lacking for Delta. Furthermore, how risk for severe disease changes in both vaccinated and unvaccinated individuals is important as the underlying risks determine public health impact. The surplus risk of Delta versus Alpha on hospitalisation was determined using random-effects meta-analysis. Infection with the Delta compared to the Alpha variant increased hospitalisation risk (unvaccinated: log HR 0.62, CI: 0.41 -- 0.84, P < 0.0001; linear HR 1.87). This finding should inform our response to future variants of concern, currently Omicron. SARS-CoV2 variants that achieve dominance, have achieved this through a higher rate of infection and this evolutionary trajectory has also come with a correlated higher risk of severe disease. The surplus risk posed by Delta was significantly lower however in the vaccinated (model estimate -0.40, CI: -0.73 -- -0.07, P = 0.017). Vaccination thus provided a disproportionate level of protection to hospitalisation with the Delta variant and provides further rationale for vaccination for SARS-CoV2 as a durable public health measure.

Model-based assessment of Chikungunya and O’nyong-nyong virus circulation in Mali in a serological cross-reactivity context

Serological surveys are essential to quantify immunity in a population but serological cross-reactivity often impairs estimates of the seroprevalence. Here, we show that modeling helps addressing this key challenge by considering the important cross-reactivity between Chikungunya (CHIKV) and O’nyong-nyong virus (ONNV) as a case study. We develop a statistical model to assess the epidemiology of these viruses in Mali. We additionally calibrate the model with paired virus neutralization titers in the French West Indies, a region with known CHIKV circulation but no ONNV. In Mali, the model estimate of ONNV and CHIKV prevalence is 30% and 13%, respectively, versus 27% and 2% in non-adjusted estimates. While a CHIKV infection induces an ONNV response in 80% of cases, an ONNV infection leads to a cross-reactive CHIKV response in only 22% of cases. Our study shows the importance of conducting serological assays on multiple cross-reactive pathogens to estimate levels of virus circulation.

Identification and validation of a novel zinc finger protein-related gene-based prognostic model for breast cancer

Background Breast invasive carcinoma (BRCA) is a commonly occurring malignant tumor. Zinc finger proteins (ZNFs) constitute the largest transcription factor family in the human genome and play a mechanistic role in many cancers’ development. The prognostic value of ZNFs has yet to be approached systematically for BRCA. Methods We analyzed the data of a training set from The Cancer Genome Atlas (TCGA) database and two validation cohort from GSE20685 and METABRIC datasets, composed of 3,231 BRCA patients. After screening the differentially expressed ZNFs, univariate Cox regression, LASSO, and multiple Cox regression analysis were performed to construct a risk-based predictive model. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and gene set enrichment analyses (GSEA) were utilized to assess the potential relations among the tumor immune microenvironment and ZNFs in BRCA. Results In this study, we profiled ZNF expression in TCGA based BRCA cohort and developed a novel prognostic model based on 14 genes with ZNF relations. This model was composed of high and low-score groups for BRCA classification. Based upon Kaplan-Meier survival curves, risk-status-based prognosis illustrated significant differences. We integrated the 14 ZNF-gene signature with patient clinicopathological data for nomogram construction with accurate 1-, 3-, and 5-overall survival predictive capabilities. We then accessed the Genomics of Drug Sensitivity in Cancer database for therapeutic drug response prediction of signature-defined BRCA patient groupings for our selected TCGA population. The signature also predicts sensitivity to chemotherapeutic and molecular-targeted agents in high- and low-risk patients afflicted with BRCA. Functional analysis suggested JAK STAT, VEGF, MAPK, NOTCH TOLL-like receptor, NOD-like receptor signaling pathways, apoptosis, and cancer-based pathways could be key for ZNF-related BRCA development. Interestingly, based on the results of ESTIMATE, ssGSEA, and GSEA analysis, we elucidated that our ZNF-gene signature had pivotal regulatory effects on the tumor immune microenvironment for BRCA. Conclusion Our findings shed light on the potential contribution of ZNFs to the pathogenesis of BRCA and may inform clinical practice to guide individualized treatment.

Control-Oriented Model of the Mean and Dispersion of Diesel Combustion Phasing With Ignition Assist

Diesel engines equipped with ignition assist devices such as glow plugs may improve combustion behavior at low temperatures and with low cetane fuels found in remote fields. The coordination of injection timing and the energy input of the ignition assist needs to continuously adjust to maintain the best combustion phasing at all conditions. However, most diesel engines do not use closed-loop combustion control and operate in a sub-optimal manner because the dispersion of combustion phasing, also known as cycle-to-cycle variability, requires careful feedback controller design. This work presents an initial investigation of a control-oriented model that captures the average and statistical influence of commercial glow plugs used for ignition assist beyond the start-up phase. Experiments were conducted at a single speed and load operating point as a proof of concept to obtain a model that quantifies the combustion phasing statistics and thus can guide feedback control design. The developed phenomenological model includes the engine’s thermal state because it impacts combustion behavior over the course of repeated experiments. The 3-term mean phasing model and 2-term standard deviation model estimate start of combustion within 0.6 and 0.2 crank angle degrees, respectively, and can be readily expanded to more operating conditions.

Developing a Precautionary Management Approach for the Eastern Canada-West Greenland Population of Bowhead Whales (Balaena mysticetus)

Bowhead whales (Balaena mysticetus L., 1758) of the Eastern Canada-West Greenland population have been hunted by Inuit for millennia. Significant commercial harvests, conducted by European and American whalers for about 400 years, ended ca. 1915. A small co-managed subsistence harvest from this population has occurred inconsistently in Canada and Greenland, since 1996 and 2009, respectively. Since near extirpation from commercial whaling, population size has increased and the Inuit subsistence hunt now requires a harvest management framework that incorporates knowledge of abundance trends, population dynamics, and carrying capacity. Here, we use a model estimate of pre-commercial exploitation abundance to approximate carrying capacity and develop a management framework with reference points and corresponding stock status zones. When applied to recent abundance estimates, our framework indicates that the population is likely within the healthy (N50–N70) zone. Thus, an appropriate management objective is to support continued population increase, with concurrent marginal harvesting, while maintaining the population level above the target reference point (N70) of ca 12,000 whales. However, there remains large uncertainty about current population size and growth rate. The resulting data gaps require a plan for future research to monitor this population in the context of climate changes.

Evaluating the Relationship between Stakeholder Pressure and Innovation in Ghanaian SMEs: Moderating Role of Firm Size

The study examines the relationship between stakeholder pressure and innovation (Technological and non-technological) in Ghanaian SMEs. Further, it explores the moderating role of firm size in this relationship. This is in response to the ongoing debate on the role of innovation in the performance and survival of small businesses in Ghana. Using the survey response of 523 registered SMEs, the SmartPLS model estimate reveals that; stakeholder pressure influences both technological and non-technological innovation in Ghanaian SMEs. Further, the size of the SMEs has no significant moderation in the positive relationship between stakeholder pressure and innovation in Ghana. Consequently, SMEs in Ghana can take advantage of the pressure from internal and external stakeholders to innovate for sustainable growth. Again, the government should provide avenues for innovative collaborations between universities, government agencies, and SMEs. Finally, studies should focus on inexpensive innovation channels capable of transforming the SME industry of Ghana.

Model Estimates and In-situ Measurements of the Concentrations of Some Gaseous Pollutants in Some Selected Standard Kitchens in Makurdi-Nigeria

This work assessed and compared the concentrations of some gaseous pollutants in some selected standard kitchens in Makurdi-Nigeria using in-situ measurements and models estimates. Mean concentrations of CO, NO2 and SO2 were measured using Crowcon gasman meters in all the selected kitchens. The results obtained show that CO and NO2 concentrations were observed in all the selected kitchens in concentrations below the permissible limit of 20 ppm and 0.6 ppm respectively set by National Ambient Air Quality Standard and SO2 was not observed. The mean concentrations for model estimates were found to be slightly higher compared to that of in-situ measurement in all the study kitchens for both pollutants, which is an indication of the strength of the model estimate. Pearson product moment correlation coefficient (r) was also computed to be 0.99 and 0.36 for CO and NO2respectively. The correlation is very strong and positive for CO (r = 0.99) and is weak but also positive for NO2 (r = 0.37). This implies that the model estimates used in this work has 99 % validity estimating indoor concentrations of CO where in-situ measurements are not possible. However, the positive correlation between the in-situ measurements and models estimates indicate that both are positively related.

Medical students' attitudes towards psychiatry improve following psychiatry clinical placements: the ATPP study

Purpose In previous research, personality and exposure to psychiatry were independently shown to shape medical students attitudes towards psychiatry (ATP). This paper aims to investigate the role of psychiatry placements and personality types on medical student attitudes towards psychiatry (ATP). Design/methodology/approach All medical students from four consecutive years at Cambridge University, UK were invited to take part in an online questionnaire including the ATP-30 Questionnaire and The Big Five Factor personality Inventory (BFI). Findings Students who had completed their psychiatry placement had more positive ATP than students who had not (t = −3.24, adjusted p = 0.004). However, this was not reflected in an increased self-reported likelihood of choosing psychiatry as a career (t = 0.28, adjusted p = 0.78). Higher agreeable personality scores were associated with both a higher willingness to take up psychiatry as a career (linear model estimate 0.06; p = 0.03), and more positive ATP (linear model estimate 0.14; p < 0.0001). Originality/value This work seems to confirm that exposure to psychiatry improves attitudes towards psychiatry. Agreeable personality traits were also associated with a higher willingness to take up psychiatry postgraduate training. These findings might help shape future campaigns to improve the profile of psychiatry training. Future research on this topic is needed to address whether improved ATP among medical students can longitudinally improve recruitment into post-graduate psychiatry training.

Spatial Estimation of Soil Erosion Using RUSLE Modeling: the Case of kaffa Zone, South western Ethiopia

This research was administered to spatially predict the soil loss rate of kaffa zone using model estimate and GIS. Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was accustomed estimate potential soil losses by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using DSMW soil map, vegetation cover (C) using Sentinel-2A satellite images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P ) using DEM and satellite images. supported the analysis, the mean and total annual soil loss potential of the study area was 30 tons ha-1 year-1 and 36264.5tons ha-1 year-1, respectively. The result also showed that about 2.89, 8.02, 15.31 and 73.78% of the study area were classified a slight, moderate, high and very high with values ranging 0 to 15 ,15 to50,50 to 200, and > 200 tons ha-1 year-1, respectively. The study demonstrates that the RUSLE using GIS and RS provides great advantage to spatially analyze multi-layer of knowledge. The expected amount of soil loss and its spatial distribution could facilitate sustainable land use and management.

Introduction of the Hessian in joint migration inversion and improved recovery of structural information using an image-based regularization

Joint migration inversion (JMI) is a method based on the one-way wave equations that aims at fitting seismic reflection data to estimate an image and a background velocity. The depth-migrated image describes the high spatial-frequency content of the subsurface and, in principle, is true amplitude. The background velocity model accounts mainly for the large spatial-scale kinematic effects of the wave propagation. Looking for a deeper understanding of the method, we briefly review the continuous equations that compose the forward modeling engine of JMI for acoustic media and angle-independent scattering. Then, we use these equations together with the first-order adjoint-state method to arrive at a new formulation of the model gradients. To estimate the image, we combine the second-order adjoint-state method with the truncated-Newton method to obtain the image updates. For the model (velocity) estimation, in comparison to the image update, we reduce the computational cost by simply adopting a diagonal preconditioner for the corresponding gradient in combination with an image-based regularizing function. Based on this formulation, we build our implementation of the JMI algorithm. The proposed image-based regularization of the model estimate allows us to carry over structural information from the estimated image to the jointly estimated background model. As demonstrated by our numerical experiments, this procedure can help to improve the resolution of the estimated model and make it more consistent with the image.