Novel therapeutic strategies for spinal osteosarcomas

At the dawn of the third millennium, cancer has become the bane of twenty-first century man, and remains a predominant public health burden, affecting welfare and life expectancy globally. Spinal osteogenic sarcoma, a primary spinal malignant tumor, is a rare and challenging neoplastic disease to treat. After the conventional therapeutic modalities of chemotherapy, radiation and surgery have been exhausted, there is currently no available alternative therapy in managing cases of spinal osteosarcoma. The defining signatures of tumor survival are characterised by cancer cell ability to stonewall immunogenic attrition and apoptosis by various means. Some of these biomarkers, namely immune-checkpoints, have recently been exploited as druggable targets in osteosarcoma and many other different cancers. These promising strides made by the use of reinvigorated immunotherapeutic approaches may lead to significant reduction in spinal osteosarcoma disease burden and corresponding reciprocity in increase of survival rates. In this review, we provide the background to spinal osteosarcoma, and proceed to elaborate on contribution of the complex ecology within tumor microenvironment giving arise to cancerous immune escape, which is currently receiving considerable attention. We follow this section on the tumor microenvironment by a brief history of cancer immunity. Also, we draw on the current knowledge of treatment gained from incidences of osteosarcoma at other locations of the skeleton (long bones of the extremities in close proximity to the metaphyseal growth plates) to make a case for application of immunity-based tools, such as immune-checkpoint inhibitors and vaccines, and draw attention to adverse upshots of immune-checkpoint blockers as well. Finally, we describe the novel biotechnique of CRISPR/Cas9 that will assist in treatment approaches for personalized medication.This work is funded by a grant (MPP 320133) from the American University of Beirut to Dr. Ali H. Eid

An artificial fish swarm filter-based Method for constrained global optimization

Ana Maria A.C. Rocha, M. Fernanda P. Costa and Edite M.G.P. Fernandes, An Artificial Fish Swarm Filter-Based Method for Constrained Global Optimization, B. Murgante, O. Gervasi, S. Mirsa, N. Nedjah, A.M. Rocha, D. Taniar, B. Apduhan (Eds.), Lecture Notes in Computer Science, Part III, LNCS 7335, pp. 57–71, Springer, Heidelberg, 2012.An artificial fish swarm algorithm based on a filter methodology for trial solutions acceptance is analyzed for general constrained global optimization problems. The new method uses the filter set concept to accept, at each iteration, a population of trial solutions whenever they improve constraint violation or objective function, relative to the current solutions. The preliminary numerical experiments with a wellknown benchmark set of engineering design problems show the effectiveness of the proposed method.Fundação para a Ciência e a Tecnologia (FCT

Global forest management data for 2015 at a 100 m resolution

Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (https://www.geo-wiki.org/). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services

Hemorrhagic Transformation in Patients With Acute Ischemic Stroke and Atrial Fibrillation: Time to Initiation of Oral Anticoagulant Therapy and Outcomes.

Background In patients with acute ischemic stroke and atrial fibrillation, early anticoagulation prevents ischemic recurrence but with the risk of hemorrhagic transformation ( HT ). The aims of this study were to evaluate in consecutive patients with acute stroke and atrial fibrillation (1) the incidence of early HT, (2) the time to initiation of anticoagulation in patients with HT , (3) the association of HT with ischemic recurrences, and (4) the association of HT with clinical outcome at 90 days. Methods and Results HT was diagnosed by a second brain computed tomographic scan performed 24 to 72 hours after stroke onset. The incidence of ischemic recurrences as well as mortality or disability (modified Rankin Scale scores >2) were evaluated at 90 days. Ischemic recurrences were the composite of ischemic stroke, transient ischemic attack, or systemic embolism. Among the 2183 patients included in the study, 241 (11.0%) had HT . Patients with and without HT initiated anticoagulant therapy after a mean 23.3 and 11.6 days, respectively, from index stroke. At 90 days, 4.6% (95% confidence interval, 2.3-8.0) of the patients with HT had ischemic recurrences compared with 4.9% (95% confidence interval, 4.0-6.0) of those without HT ; 53.1% of patients with  HT were deceased or disabled compared with 35.8% of those without HT . On multivariable analysis, HT was associated with mortality or disability (odds ratio, 1.71; 95% confidence interval, 1.24-2.35). Conclusions In patients with HT , anticoagulation was initiated about 12 days later than patients without HT . This delay was not associated with increased detection of ischemic recurrence. HT was associated with increased mortality or disability

The Cholecystectomy As A Day Case (CAAD) Score: A Validated Score of Preoperative Predictors of Successful Day-Case Cholecystectomy Using the CholeS Data Set

Background Day-case surgery is associated with significant patient and cost benefits. However, only 43% of cholecystectomy patients are discharged home the same day. One hypothesis is day-case cholecystectomy rates, defined as patients discharged the same day as their operation, may be improved by better assessment of patients using standard preoperative variables. Methods Data were extracted from a prospectively collected data set of cholecystectomy patients from 166 UK and Irish hospitals (CholeS). Cholecystectomies performed as elective procedures were divided into main (75%) and validation (25%) data sets. Preoperative predictors were identified, and a risk score of failed day case was devised using multivariate logistic regression. Receiver operating curve analysis was used to validate the score in the validation data set. Results Of the 7426 elective cholecystectomies performed, 49% of these were discharged home the same day. Same-day discharge following cholecystectomy was less likely with older patients (OR 0.18, 95% CI 0.15–0.23), higher ASA scores (OR 0.19, 95% CI 0.15–0.23), complicated cholelithiasis (OR 0.38, 95% CI 0.31 to 0.48), male gender (OR 0.66, 95% CI 0.58–0.74), previous acute gallstone-related admissions (OR 0.54, 95% CI 0.48–0.60) and preoperative endoscopic intervention (OR 0.40, 95% CI 0.34–0.47). The CAAD score was developed using these variables. When applied to the validation subgroup, a CAAD score of ≤5 was associated with 80.8% successful day-case cholecystectomy compared with 19.2% associated with a CAAD score >5 (p < 0.001). Conclusions The CAAD score which utilises data readily available from clinic letters and electronic sources can predict same-day discharges following cholecystectomy

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease