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These results were echoed in both scenarios of the sensitivity analysis, except for the orthopedic specialty which was found to not be cost-effective when testing an increased discount rate.

The cost-effectiveness of short-term surgical missions provided by NGOs can be cost-effective, but limitations include inconsistent data from a societal perspective and lack of an appropriate counterfactual. Future studies should examine the capacity for NGOs to collect adequate data and conduct rigorous economic evaluations.

The cost-effectiveness of short-term surgical missions provided by NGOs can be cost-effective, but limitations include inconsistent data from a societal perspective and lack of an appropriate counterfactual. Future studies should examine the capacity for NGOs to collect adequate data and conduct rigorous economic evaluations.

Chronic respiratory diseases (CRD), are common public health problems with high prevalence, disability and mortality rates worldwide. Further uneven distribution of the health workforce is a major barrier to the effective diagnosis and treatment of CRDs. Teleconsultation between a specialist and non-specialist could possibly bridge the gap in access to health care and decrease CRD burden in remote areas. This review investigates the evidence for the effective use of specialist to non-specialist teleconsultation in the management of CRDs in remote areas and identifies instances of good practice and knowledge gaps.

We searched for articles till November 2020, which focused on specialist to non-specialist teleconsultations for CRD diagnosis or management. Two independent reviewers conducted the title and abstract screening and extracted data from the selected papers and the quality was assessed by Joanna Briggs Institute's (JBI) tool. A descriptive and narrative approach was used due to the heterogeneous nat in management of CRDs, and no controlled trials. Two of the included papers described systems, which were used for other diseases in addition to the CRD. The available literature although not generalisable, encourages the use of specialist to non-specialist teleconsultation for diagnosis and management of CRDs.

We found relatively few, papers which explored specialist to non-specialist teleconsultation in management of CRDs, and no controlled trials. Two of the included papers described systems, which were used for other diseases in addition to the CRD. The available literature although not generalisable, encourages the use of specialist to non-specialist teleconsultation for diagnosis and management of CRDs.The aim of this study was to investigate the proteins found in tear film of healthy domestic cats. Schirmer tear test strips were used to collect tear samples of twelve healthy cats, which were mixed, centrifuged, and placed in a single 1.5 mL microtube that was frozen at -20°C, until analysis by two-dimensional polyacrylamide gel and mass spectrometry associated with high-performance liquid chromatography. The resulting spectra were analyzed and compared with the Swiss-Prot search tool. Forty peptides were detected in the analyzed protein fragments of 90 spots, with 16 proteins identified. Of these, the authors confirmed what has been already found in other studies lactotransferrin, serum albumin, allergenic lipocalins, and neutrophil gelatinase-associated lipocalin. Others were considered novel in tear film samples of all species cyclin-dependent protein kinase, serine/arginine repetitive matrix protein, apelin receptor, secretory protein related to C1q/TNF, Wee1, α-1,4 glucan phosphorylase, and WD repeat domain 1. The network was divided into 11 clusters, and a biological function was assigned. Most of the proteins have functions in the defense and maintenance of feline ocular surface homeostasis. Serum albumin is a bottleneck protein, with a high betweenness value. This paper is a pioneer in reporting, in-depth, the tear film proteome of domestic cats.Toxoplasma gondii is one of the most common meat-born zoonoses that infect all warm-blooded animals and humans. Sheep (Ovis aries) is one of the main reservoirs of T. gondii worldwide, and the infections induce various sequels, such as abortion and stillbirth. The present study aimed to identify the effects of humidity on the prevalence of T. gondii in sheep in high- and low-humidity regions. Heart samples from 200 slaughtered sheep (140 samples from a high-humidity region and 60 samples from a low-humidity region) were collected from Hormozgan Province (south of Iran). The samples were tested by nested PCR targeting the RE gene. Genotyping was performed by the PCR-RFLP method using the SAG3 and GRA6 genes. Some isolates were sequenced and recorded in the GenBank. T. gondii DNA was detected in 10.71 percent of the samples from the highly humid region, whereas no positive samples were detected in the low-humidity region. Genotyping revealed that all isolates belonged to the T. gondii type III genotype. Our study indicated that humidity is an important factor for the prevalence of T. gondii in sheep. Additionally, our study also showed the dominance of type III strain of T. gondii in sheep in the south of Iran.Stroke is a major disease that seriously endangers the lives and health of middle-aged and elderly people in our country, but its implementation of secondary prevention needs to be improved urgently. The application of IoT technology in home health monitoring and telemedicine, as well as the popularization of cloud computing, contributes to the early identification of ischemic stroke and provides intelligent, humanized, and preventive medical and health services for patients at high risk of stroke. This article clarifies the networking structure and networking objects of the rehabilitation system Internet of Things, clarifies the functions of each part, and establishes an overall system architecture based on smart medical care; the design and optimization of the mechanical part of the stroke rehabilitation robot are carried out, as well as kinematics and dynamic analysis. According to the functions of different types of stroke rehabilitation robots, strategies are given for the use of lower limb rehabilitatiomonitoring, and collaborative consultation within the base.Dermatological problems are the most widely spread skin diseases amongst human beings. They can be infectious, chronic, and sometimes may also lead to serious health problems such as skin cancer. Generally, rural area clinics lack trained dermatologists and mostly rely on the analysis of remotely accessible experts through mobile-based networks for sharing the images and other related information. Under such circumstances, poor image quality introduced due to the capturing device results in misleading diagnosis. Here, a genetic-algorithm- (GA-) based approach used as an image enhancement technique has been explored to improve the low quality of the dermatological images received from the rural clinic. The diagnosis is performed on the enhanced images using convolutional neural network (CNN) classifier for the identification of the diseases. The scope of this paper is limited to only motion blurred images, which is the most prevalent problem in capturing of the images, specifically when any of the two (device or the object) may move unpredictably. Seven types of skin diseases, namely, melanoma, melanocytic nevus, basal cell carcinoma, actinic keratosis, benign keratosis, vascular lesion, and squamous cell carcinoma, have been investigated using ResNet-152 giving an overall accuracy of 87.40% for the blurred images. Use of GA-enhanced images increased the accuracy to 95.85%. The results were further analyzed using a confusion matrix and t-test-based statistical investigations. The advantage of the proposed technique is that it reduces the analysis time and errors due to manual diagnosis. Furthermore, speedy and reliable diagnosis at the earliest stage reduces the risk of developing more severe skin problems.Early diagnosis of pandemic diseases such as COVID-19 can prove beneficial in dealing with difficult situations and helping radiologists and other experts manage staffing more effectively. The application of deep learning techniques for genetics, microscopy, and drug discovery has created a global impact. It can enhance and speed up the process of medical research and development of vaccines, which is required for pandemics such as COVID-19. However, current drugs such as remdesivir and clinical trials of other chemical compounds have not shown many impressive results. Therefore, it can take more time to provide effective treatment or drugs. In this paper, a deep learning approach based on logistic regression, SVM, Random Forest, and QSAR modeling is suggested. QSAR modeling is done to find the drug targets with protein interaction along with the calculation of binding affinities. Then deep learning models were used for training the molecular descriptor dataset for the robust discovery of drugs and feature extraction for combating COVID-19. Results have shown more significant binding affinities (greater than -18) for many molecules that can be used to block the multiplication of SARS-CoV-2, responsible for COVID-19.Geriatric patients undergoing mastectomy have a weakened organism and slow recovery of gastrointestinal function after surgery, which may lead to various complications, affect the absorption of intestinal nutrients, and prolong the healing rate of wounds. Therefore, it is necessary to find an effective nursing program to promote the recovery of gastrointestinal function and prevent postoperative complications in elderly patients undergoing mastectomy. With the continuous development and advancement of computer and communication technologies, telecare is gaining more and more attention and has become an important part of medical information technology construction. Falls endanger the elderly and other special populations, especially after a sudden but unassisted fall, which may be life-threatening. Timely fall detection and rescue can win valuable time for treatment and rescue, which is very important to protect users' health and improve medical monitoring. In order to provide better medical care to the elderly population and reduce the harm caused by falls, this paper will focus on the fall problem of the elderly in telecare. In order to facilitate the detection of falls of the elderly, we design an Android sensor-based data acquisition scheme, using the built-in acceleration sensor in the Android system to collect the human acceleration information, and through the JMS middleware technology, the collected data are transmitted to MATLAB for analysis and processing in real time. selleck chemicals llc This paper preprocesses and synthesizes the collected human body data and visualizes the acceleration changes of various typical daily activities of the human body and breast cancer, then extracts the relevant data features according to the synthesized SVM curve, constructs a pattern recognition algorithm using the extracted features, and verifies the effectiveness of the pattern recognition algorithm through experiments.In recent years, point-of-care testing has played an important role in immunoassay, biochemical analysis, and molecular diagnosis, especially in low-resource settings. Among various point-of-care-testing platforms, microfluidic chips have many outstanding advantages. Microfluidic chip applies the technology of miniaturizing conventional laboratory which enables the whole biochemical process including reagent loading, reaction, separation, and detection on the microchip. As a result, microfluidic platform has become a hotspot of research in the fields of food safety, health care, and environmental monitoring in the past few decades. Here, the state-of-the-art application of microfluidics in immunoassay in the past decade will be reviewed. According to different driving forces of fluid, microfluidic platform is divided into two parts passive manipulation and active manipulation. In passive manipulation, we focus on the capillary-driven microfluidics, while in active manipulation, we introduce pressure microfluidics, centrifugal microfluidics, electric microfluidics, optofluidics, magnetic microfluidics, and digital microfluidics.