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Blockchain technology has gained considerable attention, with an escalating interest in a plethora of numerous applications, ranging from data management, financial services, cyber security, IoT, and food science to healthcare industry and brain research. There has been a remarkable interest witnessed in utilizing applications of blockchain for the delivery of safe and secure healthcare data management. Also, blockchain is reforming the traditional healthcare practices to a more reliable means, in terms of effective diagnosis and treatment through safe and secure data sharing. In the future, blockchain could be a technology that may potentially help in personalized, authentic, and secure healthcare by merging the entire real-time clinical data of a patient’s health and presenting it in an up-to-date secure healthcare setup. In this paper, we review both the existing and latest developments in the field of healthcare by implementing blockchain as a model. We also discuss the applications of blockchain, along with the challenges faced and future perspectives.

Skin cancer, particularly melanoma, has remained a severe issue for many years due to its increasing incidences. The rising mortality rate associated with melanoma demands immediate attention at early stages to facilitate timely diagnosis and effective treatment. Due to the similar visual appearance of malignant tumors and normal cells, the detection and classification of melanoma are considered to be one of the most challenging tasks. Detecting melanoma accurately and promptly is essential to diagnosis and treatment, which can contribute significantly to patient survival. A new dataset, Nailmelonma, is presented in this study in order to train and evaluate various deep learning models applying transfer learning for an indigenous nail melanoma localization dataset. Using the dermoscopic image datasets, seven CNN-based DL architectures (viz., VGG19, ResNet101, ResNet152V2, Xception, InceptionV3, MobileNet, and MobileNetv2) have been trained and tested for the classification of skin lesions for melanoma detection. The trained models have been validated, and key performance parameters (i.e., accuracy, recall, specificity, precision, and F1-score) are systematically evaluated to test the performance of each transfer learning model. The results indicated that the proposed workflow could realize and achieve more than 95% accuracy. In addition, we show how the quantization of such models can enable them for memory-constrained mobile/edge devices. To facilitate an accurate, timely, and faster diagnosis of nail melanoma and to evaluate the early detection of other types of skin cancer, the proposed workflow can be readily applied and robust to the early detection of nail melanoma.

Temporal lobe epilepsy (TLE) is the most prevalent type of focal epilepsy. Recent developments in sequencing, proteomics and network analysis tools provide new avenues for investigating potential molecular therapeutic targets. Both the TGF- β /SMAD signaling pathways and subsets of microRNAs (including miR-21a-5p, miR-142a-5p, and miR-10a-5p) have been shown to be altered in several preclinical models of epilepsy and were mathematically modeled in this study. Using prior systems-based findings, a changeover between ‘seizure’ and ‘anti-seizure’ cellular states has been identified upon inhibition of microRNA activity achieved by the injection of antagomirs. Methods for seizure suppression were explored under various antagomir dosages as well as the regulatory effect of each microRNA in order to ascertain intracellular responses. Promising antagomir administration strategies were then identified, which may offer new avenues for seizure suppression.

Laboratory experiments were conducted to examine the efficacy of fertilizer priming on seed germination behavior and vigor of two maize cultivars \"Azam and Phari\" at Agronomy Research Laboratory, University of Agriculture, Peshawar- Pakistan during 2015. Studied treatments include hydropriming (distilled water) and osmopriming with Calcium Ammonium Nitrate (CAN) at 0.5% for 24 hours. Non primed seed were used as control. Data were recorded on germination and vigor parameters according to standard procedures. Results showed that both hydro and osmo-priming significantly improved germination %, mean germination time, germination index, plumule and radical length, seedling fresh and dry weight of both cultivars as compared to control treatment. Cultivar Azam performed better in all germination and vigor attributes than Phari. It was concluded that both hydro and osmopriming with Calcium Ammonium Nitrate (CAN) at 0.5% for 24 hours are practical approaches for improving growth and vigor of maize crop under harsh environment.

Brain function requires a constant supply of glucose. However, the brain has no known energy stores, except for glycogen granules in astrocytes. In the present study, we report that continuous oligodendroglial lipid metabolism provides an energy reserve in white matter tracts. In the isolated optic nerve from young adult mice of both sexes, oligodendrocytes survive glucose deprivation better than astrocytes. Under low glucose, both axonal ATP levels and action potentials become dependent on fatty acid β-oxidation. Importantly, ongoing oligodendroglial lipid degradation feeds rapidly into white matter energy metabolism. Although not supporting high-frequency spiking, fatty acid β-oxidation in mitochondria and oligodendroglial peroxisomes protects axons from conduction blocks when glucose is limiting. Disruption of the glucose transporter GLUT1 expression in oligodendrocytes of adult mice perturbs myelin homeostasis in vivo and causes gradual demyelination without behavioral signs. This further suggests that the imbalance of myelin synthesis and degradation can underlie myelin thinning in aging and disease. Brain functions require a constant supply of glucose. However, the brain energy stores are unclear. Here, the authors show that oligodendroglial fatty acid metabolism can be an energy reserve for white matter axons, supporting their function.

ObjectivesTo estimate COVID-19 infections and deaths in healthcare workers (HCWs) from a global perspective during the early phases of the pandemic.DesignSystematic review.MethodsTwo parallel searches of academic bibliographic databases and grey literature were undertaken until 8 May 2020. Governments were also contacted for further information where possible. There were no restrictions on language, information sources used, publication status and types of sources of evidence. The AACODS checklist or the National Institutes of Health study quality assessment tools were used to appraise each source of evidence.Outcome measuresPublication characteristics, country-specific data points, COVID-19-specific data, demographics of affected HCWs and public health measures employed.ResultsA total of 152 888 infections and 1413 deaths were reported. Infections were mainly in women (71.6%, n=14 058) and nurses (38.6%, n=10 706), but deaths were mainly in men (70.8%, n=550) and doctors (51.4%, n=525). Limited data suggested that general practitioners and mental health nurses were the highest risk specialities for deaths. There were 37.2 deaths reported per 100 infections for HCWs aged over 70 years. Europe had the highest absolute numbers of reported infections (119 628) and deaths (712), but the Eastern Mediterranean region had the highest number of reported deaths per 100 infections (5.7).ConclusionsCOVID-19 infections and deaths among HCWs follow that of the general population around the world. The reasons for gender and specialty differences require further exploration, as do the low rates reported in Africa and India. Although physicians working in certain specialities may be considered high risk due to exposure to oronasal secretions, the risk to other specialities must not be underestimated. Elderly HCWs may require assigning to less risky settings such as telemedicine or administrative positions. Our pragmatic approach provides general trends, and highlights the need for universal guidelines for testing and reporting of infections in HCWs.

The aim of this manuscript is to initiate the study of the Banach contraction in R-fuzzy b-metric spaces and discuss some related fixed point results to ensure the existence and uniqueness of a fixed point. A nontrivial example is imparted to illustrate the feasibility of the proposed methods. Finally, to validate the superiority of the provided results, an application is presented to solve the first kind of a Fredholm-type integral equation.

There has been an increase in the adoption of mobile payment systems worldwide in the past few years. However, poor Internet connection in rural regions continues to be an obstacle to the widespread use of such technologies. On top of that, there are significant problems with the currently available offline wallets; for instance, the payee cannot verify the number of coins received without access to the Internet. Additionally, it has been demonstrated that some existing systems are susceptible to false token generation, and some do not even permit the user to divide the offline token into smaller portions to be used as change. This paper proposes a blockchain-based wallet system that provides a secure mobile payment service even if a user cannot access a reliable Internet connection. Our approach relies on Bluetooth and digital signatures to establish and build a trust connection between the parties. The proposed solution overcomes the main limitations of existing systems that use offline transactions, such as the generation of fake offline tokens and the indivisibility of offline tokens. The user buys Offline Tokens (OTs) from a server called an Offline Token Manager (OTM) to use them later to perform offline transactions. Each mobile device must store a single, signed offline token transaction to prevent fake tokens. On the other hand, all offline transactions will be kept as a history in a particular local database. Finally, when the receiver becomes online, it will send a convert request to the OTM to change the value of the OTs to the appropriate amount in real coins. This step requires a connection to the Internet. To evaluate the effectiveness of the system, the Solidity programming language was used to develop a smart contract on the Ethereum blockchain with a backend application programming interface (API) and an android mobile application. The proposed method has an advantage over other prominent wallets.

Hydrological data in general and water quality (WQ) data in particular frequently suffer from missing records and/or short-gauged monitoring/sampling sites. Many statistical regression techniques are employed to substitute missing values or to extend records at short-gauged sites, such as the Kendall-Theil robust line (KTRL), its modified version (KTRL2), ordinary least squares regression (OLS), four MOVE techniques, and the robust line of organic correlation (RLOC). In this study, in aspiring to achieve better accuracy and precision, the À Trous-Haar wavelet transform (WT) was adopted as a data denoising preprocessing step prior to applying record extension techniques. An empirical study was performed using real WQ data, from the National WQ monitoring network in the Nile Delta in Egypt, to evaluate the performance of these eight record-extension techniques with and without the WT data preprocessing step. Evaluations included the accuracy and precision of the techniques when used for the restoration of WQ missing values and for the extension of the WQ short-gauged variable. The results indicated that for the restoration of missing values, the KTRL and WT-KTRL outperformed other techniques. However, for the extension of short-gauged variables, WT-KTRL2, WT-MOVE3, and WT-MOVE4 techniques showed more accurate and precise results compared with both other techniques and their counterparts without the WT.

Starch hydrogels are highly available, biocompatible and biodegradable materials that have promising applications in medical and pharmaceutical industries. However, their applications are very limited due to their poor mechanical properties and fragility. Here, we investigated, for the first time, conventional corn and waxy corn starch-based hydrogels for loading patchouli essential oil. The essential oil extracted by supercritical carbon dioxide with a yield reached 8.37 ± 1.2 wt.% (wet sample) at 80 °C temperature and 10 MPa pressure. Patchouli essential oil exhibited a 23 to 28 mm zone of inhibition against gram-positive and gram-negative bacteria. Waxy starch hydrogels had better properties in term of viscosity, water evaporation stability and the delivery of essential oil than conventional starch hydrogels. The viscosity and spreadability of a 6% waxy starch sample were 15,016 ± 59 cP and 4.02 ± 0.34 g·cm/s, respectively, compared with those of conventional starch hydrogel (13,008 ± 29 cP and 4.59 ± 0.88 g·cm/s). Waxy starch-based hydrogels also provided slower in vitro biodegradation behavior and sustained release of essential oil compared with conventional starch hydrogels. All the samples were biocompatible and non-cytotoxic to fibroblast cells; the addition of patchouli essential oil enhances the proliferation of the cells. The enhanced viscosity, good antibacterial and improved biocompatibility results of prepared hydrogels confirm their suitability for wound healing applications.