SAGA: Stability-Aware Gait Analysis in constraint-free environments.

BACKGROUND: Gait abnormality detection is a challenging task in clinical practice. The majority of the current frameworks for gait abnormality detection involve the individual processes of segmentation, feature estimation, feature learning, and similarity assessment. Since each component of these modules is fixed and they are mutually independent, their performance under difficult circumstances is not ideal. We combine those processes into a single framework, a gait abnormality detection system with an end-to-end network. METHODS: It is made up of convolutional neural networks and Deep-Q-learning methods: one for coordinate estimation and the other for classification. In a single joint learning technique that may be trained together, the two networks are modeled. This method is significantly more efficient for use in real life since it drastically simplifies the conventional step-by-step approach. RESULTS: The proposed model is experimented on MATLAB R2020a. While considering into consideration the stability factor, our proposed model attained an average case accuracy of 95.3%, a sensitivity of 96.4%, and a specificity of 94.1%. SIGNIFICANCE: Our paradigm for quantifying gait analysis using commodity equipment will improve access to quantitative gait analysis in medical facilities and rehabilitation centers while also allowing academics to conduct large-scale investigations for gait-related disorders. Numerous experimental findings demonstrate the effectiveness of the proposed strategy and its ability to provide cutting-edge outcomes.

Antibiotic resistance and virulence genes profile of Non typhodial Salmonella species isolated from poultry enteritis in India.

Salmonella species (spp) is the most important gastrointestinal pathogen present ubiquitously. Non typhoidal Salmonella (NTS) is commonly associated with gastroenteritis in humans. Layer birds once get infection with NTS, can become persistently infected with Salmonella Typhimurium and intermittently shed the bacteria. It results in a high risk of potential exposure of eggs to the bacteria. The current study was conducted to determine the serotype diversity, presence of virulence genes, antibiotic resistance pattern, and genes of NTS from poultry enteritis. Out of 151 intestinal swabs from poultry total 118 NTS were isolated, which were characterized serologically as S. Typhimurium (51 strains), S. Weltevreden (57 strains) and untypable (10 strains). Most effective antibiotics were amikacin, gentamycin and ceftriaxone (33.05%) followed by ampicillin, azithromycin and ciprofloxacin (16.69%), co-trimoxazole (13.55%), and tetracycline (6.78%). Multidrug resistance recorded in 17.70% (N = 21/118) strains. Antimicrobial-resistant genes i.e. blaTEM, blaSHV, blaCTX-M, tet(A), tet(B), tet(C), sul1, sul2, sul3. blaTEM and tet(A) were present in 95% (20/21). Eleven virulence genes i.e. invA, hilA, sivH, tolC, agfA, lpfA, spaN, pagC, spiA, iroN and fliC 2 were present in all the 30 isolates. While, sopE was present in only 2 isolates, NTS strains with characteristics of pathogenicity and multidrug resistance from poultry enteritis were detected. Multidrug resistance showed the necessity of prudent use of antibiotics in the poultry industry.

Identification of miR-29a as a novel biomarker for lumpy skin disease virus exposure in cattle.

Micro RNAs (miRNAs) have been implicated in the regulation of maturation, proliferation, differentiation, and activation of immune cells. In this study, we demonstrated that miR-29a antagonizes IFN-γ production at early times post-LSDV infection in cattle. miR-29a was predicted to target upstream IFN-γ regulators, and its inhibition resulted in enhanced IFN-γ production in sensitized peripheral blood mononuclear cells (PBMCs). Further, stimulation of PBMCs with LSDV antigen exhibited lower levels of miR-29a, concomitant with a potent cell-mediated immune response (CMI), characterized by an increase in LSDV-specific CD8+ T cell counts and enhanced levels of IFN-γ, which eventually facilitated virus clearance. In addition, a few immunocompromised cattle (developed secondary LSDV infection at ~ 6 months) that failed to mount a potent cell-mediated immune response, were shown to maintain higher miR-29a levels. Furthermore, as compared to the sensitized crossbred cattle, PBMCs from sensitized Rathi (a native Indian breed) animals exhibited lower levels of miR-29a along with an increase in CD8+ T cell counts and enhanced levels of IFN-γ. Finally, we analysed that a ≥ 60% decrease in miR-29a expression levels in the PBMCs of sensitized cattle correlated with a potent CMI response. In conclusion, miR-29a expression is involved in antagonizing the IFN-γ response in LSDV-infected cattle and may serve as a novel biomarker for the acute phase of LSDV infection, as well as predicting the functionality of T cells in sensitized cattle. In addition, Rathi cattle mount a more potent CMI response against LSDV than crossbred cattle.

BIDS: Blockchain and Intrusion Detection System Coalition for Securing Internet of Medical Things Networks.

The benefits of the Internet of Medical Things (IoMT) in providing seamless healthcare to the world are at the forefront of technological advancement. However, security concerns of any IoMT systems are high since they threaten to compromise personal information of patients and can even cause health hazards. Researchers are exploring the use of various techniques to ensure a high level of security of IoMT systems. One key concern is that the computing power of any Internet of Things (IoT) device is relatively low, hence mechanisms that require low computational power are appropriate for designing Intrusion Detection Systems (IDS). In this research work, a blockchain IDS coalition is proposed for securing IoMT networks and devices. The blockchain ledger is compact and uses less processing resources. Additionally, the ledger requires less communication overhead. The cryptographic hashes in the suggested architecture ensure complete data secrecy and integrity between parties who are trusted and those who are untrustworthy. Peer-to-peer networks in both central and cluster networks are also included in this work for complete decentralization. The proposed model can counter various attacks, including Denial of Service (DoS), anonymity attacks, impersonation attacks, Man-In-The-Middle (MITM), and Cross-Site Scripting (XSS). The proposed method achieved an F1- score as high as 100% and reported an AUC value of over 99%.

Evaluation of the safety, immunogenicity and efficacy of a new live-attenuated lumpy skin disease vaccine in India.

Lumpy skin disease (LSD) was reported for the first time in India in 2019 and since then, it has become endemic. Since a homologous (LSD-virus based) vaccine was not available in the country, goatpox virus (GPV)-based heterologous vaccine was authorized for mass immunization to induce protection against LSD in cattle. This study describes the evaluation of safety, immunogenicity and efficacy of a new live-attenuated LSD vaccine developed by using an Indian field strain, isolated in 2019 from cattle. The virus was attenuated by continuous passage (P = 50) in Vero cells. The vaccine (50th LSDV passage in Vero cells, named as Lumpi-ProVacInd) did not induce any local or systemic reaction upon its experimental inoculation in calves (n = 10). At day 30 post-vaccination (pv), the vaccinated animals were shown to develop antibody- and cell-mediated immune responses and exhibited complete protection upon virulent LSDV challenge. A minimum Neethling response (0.018% animals; 5 out of 26,940 animals) of the vaccine was observed in the field trials conducted in 26,940 animals. There was no significant reduction in the milk yield in lactating animals (n = 10108), besides there was no abortion or any other reproductive disorder in the pregnant animals (n = 2889). Sero-conversion was observed in 85.18% animals in the field by day 30 pv.

A Novel Lightweight Deep Learning-Based Histopathological Image Classification Model for IoMT.

The unavailability of appropriate mechanisms for timely detection of diseases and successive treatment causes the death of a large number of people around the globe. The timely diagnosis of grave diseases like different forms of cancer and other life-threatening diseases can save a valuable life or at least extend the life span of an afflicted individual. The advancement of the Internet of Medical Things (IoMT) enabled healthcare technologies can provide effective medical facilities to the population and contribute greatly towards the recuperation of patients. The usage of IoMT in the diagnosis and study of histopathological images can enable real-time identification of diseases and corresponding remedial actions can be taken to save an affected individual. This can be achieved by the use of imaging apparatus with the capacity of auto-analysis of captured images. However, most deep learning-based image classifying models are bulk in size and are inappropriate for use in IoT based imaging devices. The objective of this research work is to design a deep learning-based lightweight model suitable for histopathological image analysis with appreciable accuracy. This paper presents a novel lightweight deep learning-based model "ReducedFireNet", for auto-classification of histopathological images. The proposed method attained a mean accuracy of 96.88% and an F1 score of 0.968 on evaluating an actual histopathological image data set. The results are encouraging, considering the complexity of histopathological images. In addition to the high accuracy the lightweight design (size in few KBs) of the ReducedFireNet model, makes it suitable for IoMT imaging equipment. The simulation results show the proposed model has computational requirement of 0.201 GFLOPS and has a mere size of only 0.391 MB.

Ambient intelligence-based multimodal human action recognition for autonomous systems.

Human activity recognition can deduce the behaviour of one or more people from a set of sensor measurements. Despite its widespread applications in monitoring activities, robotics, and visual surveillance, accurate, meticulous, precise and efficient human action recognition remains a challenging research area. As human beings are moving towards the establishment of a smarter planet, human action recognition using ambient intelligence has become an area of huge potential. This work presents a method based on Bi-Convolutional Recurrent Neural Network (Bi-CRNN) -based Feature Extraction and then Random Forest classification for achieving outcomes utilizing Ambient Intelligence that are at the cutting edge of human action recognition for Autonomous Robots. The auto fusion technique used has improved fusion for utilizing and processing data from various sensors. This paper has drawn comparisons with already existing algorithms for Human Action Recognition (HAR) and tried to propose a heuristic and constructive hybrid deep learning-based algorithm with an accuracy of 94.7%.

Hit or Miss: The Dilemma of Specimen Selection for Microbiological Diagnosis of Rhino-Orbital-Cerebral- COVID-Associated Mucormycosis (ROCM-CAM).

BACKGROUND: We diagnosed various cases of rhino-orbital-cerebral- COVID-associated Mucormycosis (ROCM-CAM) during India's second wave of COVID-19. This helped formulate novel suggestions for improving laboratory output, applicable anywhere in the world. METHODS: To diagnose ROCM-CAM by microbiological methods, we used direct microscopy and conventional culture on various clinical samples within the shortest turn-around time. DESIGN: Prospective single-center observational study. PARTICIPANTS: Patients with ROCM-CAM. RESULTS: Of 113 suspected cases of ROCM-CAM during May 2021, direct microscopy and culture could confirm the disease in 87.61% and 44.25% of patients, respectively. The highest pathogen isolation was seen from maxillary bone fragments, FESS-guided biopsy from pterygopalatine fossae, nasal turbinates and nasal mucosal biopsy. Direct microscopy could diagnose the disease in almost 40% of patients within 24 hours and 60% within two days. Conventional cultures yielded Rhizopus spp. (86%) as the commonest fungal pathogen followed by Mucor spp. (12%) within 7 days. Deep tissue biopsies are more useful for rapid diagnosis than superficial specimens. Routine fungal cultures can supplement case detection and help prognosticate survivors. CONCLUSION: The management of ROCM is a surgical emergency. The diagnosis of the condition must therefore be prompt and precise. Despite ongoing antifungal therapy, nasal mucosal tissue, FESSguided, and intra-operative tissue biopsies showed the pathogen's highest diagnostic yield. The diagnostic index improved further when multiple (4-5) high-quality specimens were collected. Nasal swabs and crusts, among the most commonly requested specimens worldwide, were found to have an overall low diagnostic potential.

Splenic Infarct as the Presenting Manifestation of Essential Thrombocythemia.

Background: Essential thrombocythemia is a chronic myeloproliferative neoplasm characterized by thrombotic and hemorrhagic complications. Essential thrombocythemia can be considered a risk factor for thrombotic events. Case Report: A 34-year-old female presented with sudden onset of abdominal pain from splenic infarction for which she underwent splenectomy. Bone marrow examination performed because of increasing thrombocytosis led to a diagnosis of essential thrombocythemia. Postoperatively, she was maintained on low-dose aspirin and doing well at follow-up. Conclusion: Our patient had an undiagnosed case of essential thrombocythemia and presented with symptoms related to splenic infarction. To the best of our knowledge, few cases of splenic infarction consequent to essential thrombocythemia have been reported.

Annotated protein network analysis linking oral diseases.

Oral cancer is becoming more common, and it threatens to be a serious worldwide medical issue. Hence, it is of interest to elucidate the networks between proteins and biologically active compounds, as well as their functional annotations, and cell signaling pathways. The online STRING software was used to create a molecular genetics interaction network named AZURIN on oral bacterial proteins. We also used the cystoscope software to identify 11 nodes and 16 edges with an average node order of 2.91. Thus, we document data on the interaction of protein networks with other proteins for identifying potential therapeutic drug candidates linked to oral disease.

Blockchain-enabled access control to prevent cyber attacks in IoT: Systematic literature review.

Internet of Things (IoT) enables communication among objects to collect information and make decisions to improve the quality of life. There are several unresolved security and privacy concerns in IoT due to multiple resource constrained devices, which lead to various cyber attacks. The conventional access control techniques depend on a central authority that further poses privacy and scalability issues in IoT. Various problems with access control in IoT can be resolved to prevent various cyber attacks using the decentralization and immutability properties of the blockchain. This study explored the current research trends in blockchain-enabled secure access control mechanisms and also identifies their applicability in creating reliable access control solutions for IoT. The basic properties of blockchain, such as decentralization, auditability, transparency, and immutability, act as the propulsion that provides integrity and security, disregarding the participation of an external entity. Initially, the application of blockchain was created only for cryptocurrencies but with the introduction of Ethereum, which allows the writiting and execution of smart contracts, applications other than cryptocurrencies are also being created. As various research articles have been written on the usage of different types of blockchains for creating secure access control solutions for IoT, this study intends to find and examine such primary researches as well as come up with a systematic review of various findings. This study perceives the most frequently utilized blockchain for creating blockchain-based access control solutions to prevent various cyber attacks and also discusses the improvement in access control mechanisms using blockchain along with smart contracts in IoT. The present study also discusses the obstacles in building decentralized access control solutions for IoT systems as well as future research areas. For new researchers, this article is a nice place to start and a strong reference point.

High-power solid-state amplifier for superconducting radio frequency cavity test facility.

A horizontal test facility is set up at the Raja Ramanna Centre for Advanced Technology to test the superconducting radio frequency dressed cavities. Along with the cryomodule, control instrumentation, and the power coupler, this facility incorporates a high-power solid-state amplifier for establishing the desired cavity voltage gradient during the testing. This article describes the design, construction, rigorous testing, and measured results of this high-power solid-state radio frequency amplifier and its constituent components. Its maximum output power is 36 kW (average) at the operating frequency of 650 MHz. Its main features are its modular and scalable design with in-house developed constituent components. These components include 500 W, 20 dB gain modules, novel two-tier radial dividers, combiners, power sensors, and aperture-coupled directional couplers. Their excellent reprise performance for the multiple quantities confirms the design methodology presented here. The measured wall plug efficiency of this 36 kW amplifier is 43.6%, and its power gain is 86 dB. The designed radial combiner is highly efficient (power-combining efficiency of 98.4%), and the directional coupler exhibits a very low loss (insertion loss of 0.05 dB).

Deep learning assisted COVID-19 detection using full CT-scans.

The ongoing pandemic of COVID-19 has shown the limitations of our current medical institutions. There is a need for research in automated diagnosis for speeding up the process while maintaining accuracy and reducing the computational requirements. This work proposes an automated diagnosis of COVID-19 infection from CT scans of the patients using deep learning technique. The proposed model, ReCOV-101, uses full chest CT scans to detect varying degrees of COVID-19 infection. To improve the detection accuracy, the CT-scans were preprocessed by employing segmentation and interpolation. The proposed scheme is based on the residual network that takes advantage of skip connection, allowing the model to go deeper. The model was trained on a single enterprise-level GPU. It can easily be provided on a network's edge, reducing communication with the cloud, often required for larger neural networks. This work aims to demonstrate a less hardware-intensive approach for COVID-19 detection with excellent performance that can be combined with medical equipment and help ease the examination procedure. With the proposed model, an accuracy of 94.9% was achieved.

Out Patient Department practices in orthopaedics amidst COVID-19: The evolving model.

Severe Acute Respiratory Syndrome COVID-19 was declared as a pandemic on 11th March 2020 by the World Health Organization and consequent lockdown imposed in several areas resulted in a marked reduction in orthopaedic practices. Although some guidelines for patient care in orthopaedic practice have been published, overall, publications focusing exclusively on guidelines on starting orthopaedic outpatient departments (OPD) after the COVID-19 lockdown amidst the on-going pandemic are lacking. We hereby propose the evolving knowledge in changes in OPD management practices for orthopaedic surgeons in the COVID- 19 era. The emphasis on online registration (e-registration) should be given impetus and become the new norm supplemented by telephonic and spot registration for the uneducated patients. The review highlights the safety of patient and orthopaedic surgeons in OPD by screening and maintaining hygiene at various levels. The article also mentions the duties of the help desk, OPD hall supervisor and the new norms of air conditioning, ventilation, safe use of elevators, sanitization of OPD premises and biomedical waste disposal. The optimum and safe utilization of human & material resources, DO's and DON'Ts for patients & health staff have also been proposed. The reorganization of plaster room, the precaution during plastering, fracture clinic, dressing and injection room services are discussed as per evolving guidelines. This article will also give deep insight into the OPD plan & telemedicine graphically. The authors suggest updating and downward permeation of existing e-infrastructure of government health services that is up-gradation of existing tertiary level online registration services, a paperless model of OPD consultation & dispensation. The future updating of Aarogya Setu App (https://mygov.in/aarogya-setu-app/) for convenient online OPD registration and dispensation has been discussed and proposed. This review will help in containing the spread of COVID 19 and build upon the health gains achieved after lockdown. The easy concept of CCCATTT has been introduced, and the OPD Plan has also been suggested. We have endeavoured to holistically detail an orthopaedic OPD setup and its upkeep in COVID-19 pandemic, but since the knowledge of COVID 19 is ever-evolving it needs replenishment by regular education for health staff.

The D2Refine Platform for the Standardization of Clinical Research Study Data Dictionaries: Usability Study.

BACKGROUND: D2Refine provides a Web-based environment to create clinical research study data dictionaries and enables standardization and harmonization of its variable definitions with controlled terminology resources. OBJECTIVE: To assess the usability of the functions D2Refine offers, a usability study was designed and executed. METHODS: We employed the TURF (task, user, representation, and function) Usability Framework of electronic health record usability to design, configure, and execute the usability study and performed quantitative analyses. D2Refine was compared for its usability metrics against two other comparable solutions, OntoMaton and RightField, which have very similar functionalities for creating, managing, and standardizing data dictionaries. We first conducted the function analysis by conducting one-on-one interviews armed with questionnaires to catalog expected functionality. The enrolled participants carried out the steps for selected tasks to accomplish specific goals and their feedback was captured to conduct the task analysis. RESULTS: We enrolled a group (n=27) of study developers, managers, and software professionals to execute steps of analysis as specified by the TURF framework. For the within-model domain function saturation, D2Refine had 96% saturation, which was 4 percentage points better than OntoMaton and 28 percentage points better than RightField. The manual examination and statistical analysis of the data were conducted for task analysis, and the results demonstrated a significant difference for favorability toward D2Refine (P<.001) with a 95% CI. Overall, 17 out of 27 (63%) participants indicated that D2Refine was their favorite of the three options. CONCLUSIONS: D2Refine is a useful and promising platform that can help address the emerging needs related to clinical research study data dictionary standardization and harmonization.

Osteochondritis dissecans-Does platelet rich plasma really help.

Osteochondritis dissecans is a common disorder of knee and can be treated by various methods, depending on age of patient and stability of chondral fragment. In Osteochondritis dissecans ICRS type III lesion i.e. articular cartilage discontinuity but no dislocation, variable rate of union as well as high rate of non-union was observed in previous studies when treated with arthroscopic or open reduction and fixation. In previous study it has been also shown that platelet rich plasma help in fracture healing. In this study we are trying to extend the benefit of platelet rich plasma to Osteochondritis dissecans lesion. We took six patients with OCD, ICRS scale of OCD type III lesion. All Patients were operated Arthroscopiclly. Chondral flap of OCD lesion were fixed with stainless steel cannulated cancellous screw. To enhance union we used platelet rich plasma injections. .We access the union of chondral fragment to parent bone and knee function. Chondral fragment united to parent bone in all patients. To access knee function we used Tagner- Lysholm knee scoring system, in this study preoperatively score was 52.8 where as postoperatively it was 91.8. This study showed PRP is helpful in healing of chondral flap as all the chondral flap of osteochondral lesion united in this study.

Mediastinal Teratoma with Pulmonary Parenchyma Fistula: A Rare Diagnostic Endeavour.

Teratoma is the most frequent mediastinal germ cell tumour amongst young population. They are often detected due to pressure symptoms or as an incidental finding on chest X-ray done for any other reason. Mediastinal teratoma is usually benign and rarely possesses diagnostic or therapeutic challenge unless they rupture into surrounding viscera. In such scenario, they may lead to acute life threatening condition and need prompt diagnosis and surgical extirpation. Here, we are reporting our experience of managing a young lady, who presented with short duration breathing difficulty and cough, and was diagnosed with ruptured mediastinal teratoma on imaging, which was further confirmed intraoperatively and histopathologically.

Cayler Cardio-Facial Syndrome: An Uncommon Condition in Newborns.

INTRODUCTION: Cayler cardio-facial syndrome is a rare syndrome associated with asymmetric crying faces with congenital heart disease. We report a newborn that was diagnosed as case of Cayler Cardio-facial syndrome based on clinical features and was confirmed with FISH analysis. CASE PRESENTATION: A term male baby, born to non-consanguineous couple through normal vaginal delivery was diagnosed to have asymmetric crying faces with deviation of angle of mouth to left side at the time of birth. The baby had normal faces while sleeping or silent. Mother was known case of hypothyroidism and was on treatment. Baby was diagnosed as case of Cayler Cardio-facial Syndrome and was investigated with echocardiogram, brain ultrasound, total body X-ray examination, X-ray of cervico-thoracic vertebral column and fundus examination. Echocardiogram showed muscular VSD, brain ultrasound was normal and fundus examination showed tortuous retinal vessels. Whole body X-ray and lateral X-ray of cervico-thoracic vertebral column were not suggestive of any skeletal abnormalities. The other associated malformation was right ear microtia. Baby FISH karyotype analysis showed deletion of 22q11.2 deletion. Baby was discharged and now on follow-up. CONCLUSIONS: Cayler syndrome is a rare syndrome which must be suspected if a baby has asymmetrical cry pattern and normal facies when baby sleeps. Patient must be evaluated with echocardiography to find out associated cardiac malformations. These infants should undergo FISH analysis for 22q11.2 deletion syndrome.

Real-time PCR carried out on DNA extracted from serum or blood sample is not a good method for surveillance of bovine brucellosis.

Bovine brucellosis is endemic in many parts of the world including India. The disease diagnosis and surveillance are usually carried out by serological tests, which however have drawbacks. This study was undertaken to evaluate the potential of real-time PCR (RT-PCR) targeting bcsp31 gene for surveillance of bovine brucellosis. A total of 461 samples, which included 408 stored serum and 53 prospective blood samples, were used. It was found that 33 (7.15 %) samples were positive by RT-PCR, whereas 149 (32.32 %) and 132 (28.63 %) were positive by Rose Bengal plate test (RBPT) or standard agglutination test (STAT), respectively. The results of this study suggest that RT-PCR targeting bcsp31 gene carried out on DNA extracted from serum or blood may not be a suitable method for surveillance of brucellosis in bovines.

Plate mouse.

Fracture shaft humerus when surgically fixed is known to go into non-union and one of the main reasons of this is implant failure. The causes of implant failure may lie in the fracture personality, faulty implant material or choice, dubious surgical technique & faulty mechanics of fixation. Implants may break and cut-through but a unique type of implant migration from one surgical compartment to the other or one anatomical part of body to the other has not been hitherto reported. A 45-year-old male, farmer by occupation, was operated for fracture shaft of humerus 15 years back. He presented to us because of pain due to subcutaneous presence of plate in forearm. X-ray of the elbow with forearm showed that the plate used for fixation of humerus had migrated from one body part to another that is from arm to forearm. The patient on deliberation regarding the pros and cons of surgical treatment options, chose not to get his humerus non-union resolved surgically. This was because he could do his activities related to farming reasonably well.