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A protocol for extraction of yellow mealworm larvae proteins was established, conditions were evaluated and the resulting protein extract was characterised. The freeze-dried yellow mealworm larvae contained around 33% fat, 51% crude protein and 43% true protein on a dry matter basis. The true protein content of the protein extract was about 75%, with an extraction rate of 70% under optimised extraction conditions using 0.25 M NaOH, a NaOH solution:ethanol defatted worm ratio of 15:1 mL/g, 40°C for 1 h and extraction twice. The protein extract was a good source of essential amino acids. The lowest protein solubility in distilled water solution was found between pH 4 and 5, and increased with either increasing or decreasing pH. Lower solubility was observed in 0.5 M NaCl solution compared with distilled water. The rheological tests indicated that temperature, sample concentration, addition of salt and enzyme, incubation time and pH alterations influenced the elastic modulus of yellow mealworm protein extract (YMPE). These results demonstrate that the functional properties of YMPE can be modified for different food applications.

Intracranial atherosclerotic stenosis (ICAS) is one of the most frequent causes of stroke worldwide and confers one of the greatest risks of recurrent stroke compared with other causes of stroke. Asymptomatic ICAS is increasingly recognised as a risk factor for silent brain infarctions and dementia, magnifying the global burden of ICAS. Although ICAS is a lumen-based diagnosis, newer diagnostic imaging techniques, such as high-resolution MRI, might help to identify high-risk population subgroups to test interventions that might reduce the risk of stroke recurrence. Secondary stroke prevention in patients with ICAS currently consists of intensive management of modifiable risk factors and dual antiplatelet therapy, which is subsequently reduced to aspirin alone. Despite these therapies, the risk of recurrent stroke in patients presenting with stroke related to 70–99% ICAS exceeds 20% at 1 year; as such, better therapies are urgently needed. The optimal duration and combination of dual antiplatelet therapy in patients with ICAS is uncertain and is being investigated in addition to low-dose anticoagulation and aspirin. Other ongoing or planned studies will provide high-quality observational data on the role of transluminal angioplasty and stenting, submaximal balloon angioplasty alone, direct or indirect arterial bypass, and ischaemic conditioning for prevention of stroke in patients with ICAS.

Stroke is the leading cause of disability in the USA and a major cause of mortality worldwide. One out of four strokes is recurrent. Secondary stroke prevention starts with deciphering the most likely stroke mechanism. In general, one of the main goals in stroke reduction is to control vascular risk factors such as hypertension, diabetes, dyslipidemia, and smoking cessation. Changes in lifestyle like a healthy diet and aerobic exercise are also recommended strategies. In the case of cardioembolism due to atrial fibrillation, mechanical valves, or cardiac thrombus, anticoagulation is the mainstay of therapy. The role of anticoagulation is less evident in the case of bioprosthetic valves, patent foramen ovale, and dilated cardiomyopathy with low ejection fraction. Strokes due to larger artery atherosclerosis account for approximately a third of all strokes. In the case of symptomatic extracranial carotid stenosis, surgical intervention as close as possible in time to the index event seems highly beneficial. In the case of intracranial large artery atherosclerosis, the best medical therapy consists of antiplatelets, high-dose statins, aggressive controls of vascular risk factors, and lifestyle modifications, with no role for intracranial arterial stenting or angioplasty. For patients with small artery occlusion (ie, lacunar stroke), the therapy is similar to that used in patients with intracranial large artery atherosclerosis. Despite the constant new evidence on how to best treat patients who have suffered a stroke, the risk of stroke recurrence remains unacceptably high, thus evidencing the need for novel therapies.

Deep learning techniques (in particular convolutional neural networks, CNNs) have recently emerged as a promising approach for statistical downscaling due to their ability to learn spatial features from huge spatiotemporal datasets. However, existing studies are based on complex models, applied to particular case studies and using simple validation frameworks, which makes a proper assessment of the (possible) added value offered by these techniques difficult. As a result, these models are usually seen as black boxes, generating distrust among the climate community, particularly in climate change applications.In this paper we undertake a comprehensive assessment of deep learning techniques for continental-scale statistical downscaling, building on the VALUE validation framework. In particular, different CNN models of increasing complexity are applied to downscale temperature and precipitation over Europe, comparing them with a few standard benchmark methods from VALUE (linear and generalized linear models) which have been traditionally used for this purpose. Besides analyzing the adequacy of different components and topologies, we also focus on their extrapolation capability, a critical point for their potential application in climate change studies. To do this, we use a warm test period as a surrogate for possible future climate conditions.Our results show that, while the added value of CNNs is mostly limited to the reproduction of extremes for temperature, these techniques do outperform the classic ones in the case of precipitation for most aspects considered. This overall good performance, together with the fact that they can be suitably applied to large regions (e.g., continents) without worrying about the spatial features being considered as predictors, can foster the use of statistical approaches in international initiatives such as Coordinated Regional Climate Downscaling Experiment (CORDEX).

This article describes how machine-learning tools were used to design novel protein inhibitors that proved effective against snake-venom toxins in mice.

Snakebite envenoming is a serious global public health problem, and international initiatives, under the coordination of the World Health Organization and its regional offices, are being developed to reduce the impact of this neglected tropical disease. The global availability of safe and effective antivenoms is one of the key aspects in this global strategy. This review discusses the role of public antivenom manufacturing laboratories for ensuring the supply of antivenoms. The difficulties faced by public laboratories are discussed, together with some tasks that need to be implemented for strengthening them. In addition, the concept of ‘redundancy’ in the supply of antivenoms is emphasized, as a way to cope with the risks associated with the provision of antivenoms by few manufacturers. In general, the public sector should play a leading role, in antivenom availability and other aspects as well, within the global struggle to reduce the mortality and morbidity caused by snakebite envenoming.

Mercury is widely known for its detrimental effects on living organisms, whether in its elemental or bonded states. Recent comparative studies have shed light on the biochemical implications of mercury ingestion, both in low, persistent concentrations and in elevated acute dosages. Studies have presented models that elucidate how mercury disrupts healthy cells. Mercury’s unique ability to interfere with crucial enzymatic processes at deposition sites is a vital feature of these models. The strong affinity for the sulfhydryl moieties of enzyme catalytic sites leads to enzyme inactivation through permanent covalent modifications. This inactivation can have catastrophic effects on an organism’s metabolic functions. Moreover, it has been found that mercury’s binding to sulfhydryl moieties is highly nonspecific and can occur in various ways. This review aimed to explore the effects of mercury on a broad spectrum of enzymes with a specific focus on how these alterations can detrimentally affect several metabolic pathways.

Animal-derived antivenoms constitute the mainstay in the therapy of snakebite envenoming. The efficacy of antivenoms to neutralize toxicity of medically-relevant snake venoms has to be demonstrated through meticulous preclinical testing before their introduction into the clinical setting. The gold standard in the preclinical assessment and quality control of antivenoms is the neutralization of venom-induced lethality. In addition, depending on the pathophysiological profile of snake venoms, the neutralization of other toxic activities has to be evaluated, such as hemorrhagic, myotoxic, edema-forming, dermonecrotic, in vitro coagulant, and defibrinogenating effects. There is a need to develop laboratory assays to evaluate neutralization of other relevant venom activities. The concept of the 3Rs (Replacement, Reduction, and Refinement) in Toxinology is of utmost importance, and some advances have been performed in their implementation. A significant leap forward in the study of the immunological reactivity of antivenoms against venoms has been the development of “antivenomics”, which brings the analytical power of mass spectrometry to the evaluation of antivenoms. International partnerships are required to assess the preclinical efficacy of antivenoms against snake venoms in different regions of the world in order to have a detailed knowledge on the neutralizing profile of these immunotherapeutics.

Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bursts from a single frequency channel without considering the effects of multi-channel operation. Our research evaluated the multi-channel performance of four single-channel models with increasing complexity, to include a simple discriminant analysis model and three neural networks. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models can lead to a deterioration in performance from MCC > 0.9 (excellent) down to MCC < 0.05 (random guess), indicating that single-channel models may not maintain performance across all channels used by the transmitter in realistic operation. We proposed a training data selection technique to create multi-channel models which outperform single-channel models, improving the cross-channel average MCC from 0.657 to 0.957 and achieving frequency channel-agnostic performance. When evaluated in the presence of noise, multi-channel discriminant analysis models showed reduced performance, but multi-channel neural networks maintained or surpassed single-channel neural network model performance, indicating additional robustness of multi-channel neural networks in the presence of noise.

The vascular risk attributable to HIV infection is rising. The heterogeneity of the samples studied is an obstacle to understanding whether HIV is a vascular risk across geographic regions. To test the hypothesis that HIV infection is a vascular risk factor, and that the risk conferred by HIV varies by geographical region. A systematic search of publications was carried out in seven electronic databases: PubMed, The Cochrane Library, EMBASE, Web of Science, LILACS, ClinicalTrials.gov, and WHO International Clinical Trials Registry Platform from inception to July 2015. We included longitudinal studies of HIV+ individuals and their risk of vascular outcomes of ≥ 50 HIV+ cases and excluded studies on biomarkers of vascular disease as well as clinical trials. Data was extracted by one of the authors and independently confirmed by the other two authors. We used incidence rate (IR), incidence risk ratio (IRR) and hazard ratio (HR) with their 95% confidence intervals as measures of risk. All-death, myocardial infarction (MI), coronary heart disease (CHD), any stroke, ischemic stroke (IS) or intracranial hemorrhage (ICH). We screened 11,482 references for eligibility, and selected 117 for analysis. Forty-four cohorts represented 334,417 HIV+ individuals, 49% from the United States. Compared with their European counterparts, HIV+ individuals in the United States had higher IR of death (IRR 1.78, 1.69-1.88), MI (IRR 1.61, 1.29-2.01), CHD (IRR 2.27, 1.92-2.68), any stroke (IRR 1.94, 1.59-2.38), IS (IRR 1.56, 1.23-1.98), and ICH (IRR 4.03, 2.72-6.14). Compared with HIV- controls and independent of geographical region, HIV was a risk for death (HR 4.77, 4.55-5.00), MI (HR 1.60, 1.49-1.72), any CHD (HR 1.20, 1.15-1.25), any stroke (HR 1.82, 1.53-2.16), IS (HR 1.27, 1.15-1.39) and ICH (HR 2.20, 1.61-3.02). Use of antiretroviral therapy was a consistent risk for cardiac outcomes, while immunosuppression and unsuppressed viral load were consistent risks for cerebral outcomes. HIV should be considered a vascular risk, with varying magnitudes across geographical and anatomical regions. We think that strategies to reduce the HIV-related vascular burden are urgent, and should incorporate the disparities noted here.