Plastic Waste-Derived Carbon Dots: Insights of Recycling Valuable Materials Towards Environmental Sustainability.

Carbon dots (CDs) or carbon quantum dots (CQDs) have emerged as rising stars in the carbon family due to their diverse applications in various fields. CDs are spherical particles with a well-distributed size of less than 10 nm. Functional CDs are promising nanomaterials with low toxicity, low cost, and enormous applications in the field of bioimaging, optoelectronics, photocatalysis, and sensing. Plastic is non-biodegradable and hazardous to the environment, however extremely durable and used in abundance. During the COVID-19 pandemic, the use of plastic waste, particularly masks, goggles, face shields, and shoe cover, has increased tremendously. It needs to be recycled in a productive way as plastic wastes take hundreds or thousands of years to degrade naturally. The conversion of plastic waste into magnificent CDs has been reported as one of the key alternatives for environmental sustainability and socio-economic benefits. In this review, synthetic routes for the conversion of plastic wastes into CDs utilizing hydrothermal, solvothermal, pyrolysis, flash joule heating, and characterization of these CDs using different techniques, such as Fourier-transform infrared spectroscopy, Raman spectroscopy, X-ray diffraction, and transmission electron microscope, have been discussed. Furthermore, potential applications of these plastic-derived CDs in sensing, catalysis, agronomics, and LED lights are summarized herein.

Molecular Insights of MAP4K4 Signaling in Inflammatory and Malignant Diseases.

Mitogen-activated protein kinase (MAPK) cascades are crucial in extracellular signal transduction to cellular responses. The classical three-tiered MAPK cascades include signaling through MAP kinase kinase kinase (MAP3K) that activates a MAP kinase kinase (MAP2K), which in turn induces MAPK activation and downstream cellular responses. The upstream activators of MAP3K are often small guanosine-5'-triphosphate (GTP)-binding proteins, but in some pathways, MAP3K can be activated by another kinase, which is known as a MAP kinase kinase kinase kinase (MAP4K). MAP4K4 is one of the widely studied MAP4K members, known to play a significant role in inflammatory, cardiovascular, and malignant diseases. The MAP4K4 signal transduction plays an essential role in cell proliferation, transformation, invasiveness, adhesiveness, inflammation, stress responses, and cell migration. Overexpression of MAP4K4 is frequently reported in many cancers, including glioblastoma, colon, prostate, and pancreatic cancers. Besides its mainstay pro-survival role in various malignancies, MAP4K4 has been implicated in cancer-associated cachexia. In the present review, we discuss the functional role of MAP4K4 in malignant/non-malignant diseases and cancer-associated cachexia and its possible use in targeted therapy.

Epidemic Prediction using Machine Learning and Deep Learning Models on COVID-19 Data

A catastrophic epidemic of Severe Acute Respiratory Syndrome-Coronavirus, commonly recognised as COVID-19, introduced a worldwide vulnerability to human community. All nations around the world are making enormous effort to tackle the outbreak towards this deadly virus through various aspects such as technology, economy, relevant data, protective gear, lives-risk medications and all other instruments. The artificial intelligence-based researchers apply knowledge, experience and skill set on national level data to create computational and statistical models for investigating such a pandemic condition. In order to make a contribution to this worldwide human community, this paper recommends using machine-learning and deep-learning models to understand its daily accelerating actions together with predicting the future reachability of COVID-19 across nations by using the real-time information from the Johns Hopkins dashboard. In this work, a novel Exponential Smoothing Long-Short-Term Memory Networks Model (ESLSTM) learning model is proposed to predict the virus spread in the near future. The results are evaluated using RMSE and R-Squared values.

Primary septic arthritis of the hip after COVID-19- A case series of six patients (preprint)

Background We aim to report the consecutive patients with primary septic arthritis of the hip associated with COVID-19 and elucidate its unique clinical and radiological features.Methods Six consecutive patients (7 hips) who recovered from COVID-19 and presented with acute hip pain from November 2020 to October 2021 were included. All the patients received corticosteroids as a supportive treatment during COVID-19. Patients were diagnosed with septic arthritis of the hip based on radiographs, MRI, inflammatory markers and hip aspiration culture and synovial fluid analysis. Harris hip score was used to evaluate the functional outcome before and after treatment.Results The mean age was 44.3 years (range, 31 to 54 years). The average cumulative dose of methylprednisolone equivalent was 1328.2 mg (range, 460 to 2500 mg) and the average duration of steroid intake was 3.3 weeks. Two were culture positive and the rest four patients had a culture-negative infection. There was a significant improvement in Harris hip score from 12.5 ± 7.1 at presentation to 72.3 ± 13.6 after treatment (p < 0.05). There was a marked reduction in inflammatory parameters compared to the presenting values after treatment. Four patients (5 hips) underwent debridement and antibiotic-loaded cement spacer application in the first stage and uncemented total hip arthroplasty in the second stage. Other two patients who were treated conservatively had post septic arthritis of the hip and awaiting total hip arthroplasty.Conclusion In patients presenting with acute hip pain after COVID-19 infection, primary septic arthritis should be one of the differential diagnosis. They have features like elevated serological markers and extensive periarticular bone and soft tissue edema. Preoperative hip aspiration is mandatory for diagnosis and the patient may require a two-stage procedure for eradication of infection.

Effectiveness of Needle Tenotomy for Correction of Equinus in Clubfoot.

INTRODUCTION: During the COVID-19 surge, due to a lack of operating room availability, we performed Achilles tendon tenotomy in clubfoot patients using a 16/18 gauge needle to avoid delay in their management. The procedures were performed on an outpatient basis. The current retrospective study aims to investigate the effectiveness of needle tenotomy for the correction of equinus in clubfoot at a minimum of one year of follow-up. METHODS: Clinical records of all clubfoot patients that underwent needle tenotomy of Achilles tendon from March 2020 onwards with at least one year of follow-up were reviewed. We recorded Pirani scores and the equinus deformity at the initial presentation, after Achilles tendon tenotomy, and at the final follow-up. We also recorded any procedure-related complications following the Achilles tendon tenotomy. We compared dorsiflexion after final cast removal and after one year of follow-up. RESULTS: A total of 26 clubfeet in 14 patients underwent needle tenotomy of the Achilles tendon and completed one year of follow-up. Ankle dorsiflexion was achievable in all patients and the mean dorsiflexion of 27.4 degrees. The average Pirani score after tenotomy at final cast removal was 0.16, while the mean dorsiflexion at final cast removal was 24.2 degrees (p = .00084). No tenotomy procedure-related complications were noted. CONCLUSION: Percutaneous needle tenotomy of the Achilles tendon is a simple, safe, and effective technique for equinus correction in clubfoot. Considering the less invasive nature of the procedure, it can be done as a short procedure on an outpatient basis and has a limited risk of hemorrhage and other wound-related complications.

A broadly neutralizing monoclonal antibody overcomes the mutational landscape of emerging SARS-CoV-2 variants of concern.

The emergence of new variants of SARS-CoV-2 necessitates unremitting efforts to discover novel therapeutic monoclonal antibodies (mAbs). Here, we report an extremely potent mAb named P4A2 that can neutralize all the circulating variants of concern (VOCs) with high efficiency, including the highly transmissible Omicron. The crystal structure of the P4A2 Fab:RBD complex revealed that the residues of the RBD that interact with P4A2 are a part of the ACE2-receptor-binding motif and are not mutated in any of the VOCs. The pan coronavirus pseudotyped neutralization assay confirmed that the P4A2 mAb is specific for SARS-CoV-2 and its VOCs. Passive administration of P4A2 to K18-hACE2 transgenic mice conferred protection, both prophylactically and therapeutically, against challenge with VOCs. Overall, our data shows that, the P4A2 mAb has immense therapeutic potential to neutralize the current circulating VOCs. Due to the overlap between the P4A2 epitope and ACE2 binding site on spike-RBD, P4A2 may also be highly effective against a number of future variants.

Modulation of mitochondria by viral proteins.

Mitochondria are dynamic cellular organelles with diverse functions including energy production, calcium homeostasis, apoptosis, host innate immune signaling, and disease progression. Several viral proteins specifically target mitochondria to subvert host defense as mitochondria stand out as the most suitable target for the invading viruses. They have acquired the capability to control apoptosis, metabolic state, and evade immune responses in host cells, by targeting mitochondria. In this way, the viruses successfully allow the spread of viral progeny and thus the infection. Viruses employ their proteins to alter mitochondrial dynamics and their specific functions by a modulation of membrane potential, reactive oxygen species, calcium homeostasis, and mitochondrial bioenergetics to help them achieve a state of persistent infection. A better understanding of such viral proteins and their impact on mitochondrial forms and functions is the main focus of this review. We also attempt to emphasize the importance of exploring the role of mitochondria in the context of SARS-CoV2 pathogenesis and identify host-virus protein interactions.

An Anomaly Detection Framework for Twitter Data

An anomaly indicates something unusual, related to detecting a sudden behavior change, and is also helpful in detecting irregular and malicious behavior. Anomaly detection identifies unusual events, suspicious objects, or observations that differ significantly from normal behavior or patterns. Discrepancies in data can be observed in different ways, such as outliers, standard deviation, and noise. Anomaly detection helps us understand the emergence of specific diseases based on health-related tweets. This paper aims to analyze tweets to detect the unusual emergence of healthcare-related tweets, especially pre-COVID-19 and during COVID-19. After pre-processing, this work collected more than 44 thousand tweets and performed topic modeling. Non-negative matrix factorization (NMF) and latent Dirichlet allocation (LDA) were deployed for topic modeling, and a query set was designed based on resultant topics. This query set was used for anomaly detection using a sentence transformer. K-means was also employed for clustering outlier tweets from the cleaned tweets based on similarity. Finally, an unusual cluster was selected to identify pandemic-like healthcare emergencies. Experimental results show that the proposed framework can detect a sudden rise of unusual tweets unrelated to regular tweets. The new framework was employed in two case studies for anomaly detection and performed with 78.57% and 70.19% accuracy.

Unilateral Purtscher-like retinopathy post-COVID-19.

A 32-year-old male with no known systemic illness presented with unilateral Purtscher-like retinopathy in his left eye 2 weeks after recovering from a severe COVID-19 infection. Fundus examination revealed areas of intraretinal whitening and few cotton wool spots. Multimodal imaging findings were consistent with embolic occlusion of capillaries seen in Purtscher-like retinopathy. The case highlights the effect of virus-directed coagulation cascade activation leading to unilateral microvasculopathy in our patient. The case adds to the spectrum of COVID-19 retinopathy and presses that retina screening strategies should be established for patients suffering from or recovering from severe COVID-19 infection.

Patient Preferences Regarding Telemedicine to In-person Consultation: A Questionnaire-Based Survey.

Introduction: Telemedicine has been evolving over the last two decades; however, with the advent of the COVID 19 pandemic, its utility and acceptance have drastically increased. Most studies report increasing acceptability and satisfaction rates. This study aimed to assess patient preferences regarding telemedicine to in-person consultations and to attempt to assess the factors driving these preferences. Material and Methods: A questionnaire-based cross-sectional study was conducted for patients who had both teleconsultation and in-person consultation in the orthopedic outpatient. After obtaining consent to participate in the study, the patients were divided into broad clinical categories and responses were recorded regarding the treatment of illness by the doctor and opinions regarding telemedicine. Most questions were in yes/no or a Likert-based questionnaire. Mean, median, percentage and proportions were used for statistical analysis of the data. Results: The study group included 264 patients, with the majority with fractures and dislocations. Most patients (55.7%) were comfortable using the software for teleconsultation, and half the respondents found telemedicine convenient. A large percentage of the study group preferred in-person consultation to teleconsultation (58.7%), and the primary reasons for discontinuing teleconsultation were dissatisfaction during the interaction with the doctor and poor connectivity to telecommunication networks. Conclusion: Telecommunication has high acceptance and satisfaction, but many factors limit its acceptance in developing countries.

A novel approach for COVID-19 Infection forecasting based on multi-source deep transfer learning.

COVID-19 is a contagious disease; so, predicting its future infections in a provincial region requires the consideration of the related data (i.e., rates of infection, mortality and recovery, etc.) over a period of time. Clearly, the COVID-19 data of a particular provincial region can be easily modelled as a time-series. However, predicting the future COVID-19 infections in a particular region is quite challenging when the availability of COVID-19 dataset of the province is of little quantity. Accordingly, ML models when deployed for such tasks usually results in low infection prediction accuracy. To overcome such issues of low variance and high bias in a model due to data scarcity, multi-source transfer learning (MSTL) along with deep learning may be quite useful and effective. Therefore, this paper proposes a novel technique based on multi-source deep transfer learning (MSDTL) to efficiently forecast the future COVID-19 infections in the provinces with insufficient COVID-19 data. The proposed approach is a novel contribution as it considers the fact that future COVID-19 transmission in a region also depends on its population density and economic conditions (GDP) for accurate forecasting of the infections to tackle the pandemic efficiently. The importance of this feature selection is experimentally proved in this paper. Our proposed approach employs the well-known recurrent neural network architecture, the Long-short term memory (LSTM), a popular deep-learning model for history-dependent tasks. A comparative analysis has been performed with existing state-of-art algorithms to portray the efficiency of LSTM. Thus, formation of MSDTL approach enhances the predictive precision capability of the LSTM. We evaluate the proposed methodology over the COVID-19 dataset from sixty-two provinces belonging to different nations. We then empirically evaluate the performance of the proposed approach using two different evaluation metrics, viz. The mean absolute percentage error and the coefficient of determination. We show that our proposed MSDTL based approach is better in terms of the accuracy of the future infection prediction, and produces improvements up to 96% over its without-TL counterpart.

Characterization of a broadly cross reactive tetravalent human monoclonal antibody, recognizing conformational epitopes in receptor binding domain of SARS-CoV-2.

We used human semi-synthetic phage antibody gene libraries to select anti-SARS-CoV-2 RBD scFv antibody fragment and subsequent characterization of this novel tetravalent monoclonal antibody targeting conformational epitopes in the receptor binding domain of SARS-CoV-2. Binding studies suggest that II62 tetravalent antibody cross-reacts with RBD protein of SARS-CoV2 and its different variants of concerns. The epitope mapping data reveals that II62 tetravalent antibody targets an epitope that does not directly interferes with RBD: ACE2 interaction. Neutralization studies with live authentic SARS-CoV2 virus suggests that increase in valency of II62 mAb from monovalent to tetravalent doesn't perturbate virus interactions with the ACE2 expressing host cells in cytopathic effect-based (CPE) assay. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03272-6.

Retinal vasoocclusive spectrum following COVID-19.

The coagulation abnormalities and thromboembolic complications of coronavirus 2 (SARS-CoV-2) are now a well-established fact. The hypercoagulable state, the tendency for thromboembolism, and a cytokine surge state have been the exclusive reasons for multiorgan failure and other morbidities that have been regularly reported in COVID-19 patients. Ocular involvement in patients with active disease and those who have recovered is uncommon but not rare. We report a case series of four patients with CRVO, BRVO, CRAO, and vitreous hemorrhage in patients with proven COVID-19 infection and no other systemic ailments. The case series also tries to correlate the elevated D-dimer values, which signify a plausible prothrombotic state with the vaso-occlusive phenomenon in the retina leading to significant visual morbidity.

Semantic Analysis and Topic Modelling of Web-Scrapped COVID-19 Tweet Corpora through Data Mining Methodologies.

The evolution of the coronavirus (COVID-19) disease took a toll on the social, healthcare, economic, and psychological prosperity of human beings. In the past couple of months, many organizations, individuals, and governments have adopted Twitter to convey their sentiments on COVID-19, the lockdown, the pandemic, and hashtags. This paper aims to analyze the psychological reactions and discourse of Twitter users related to COVID-19. In this experiment, Latent Dirichlet Allocation (LDA) has been used for topic modeling. In addition, a Bidirectional Long Short-Term Memory (BiLSTM) model and various classification techniques such as random forest, support vector machine, logistic regression, naive Bayes, decision tree, logistic regression with stochastic gradient descent optimizer, and majority voting classifier have been adapted for analyzing the polarity of sentiment. The effectiveness of the aforesaid approaches along with LDA modeling has been tested, validated, and compared with several benchmark datasets and on a newly generated dataset for analysis. To achieve better results, a dual dataset approach has been incorporated to determine the frequency of positive and negative tweets and word clouds, which helps to identify the most effective model for analyzing the corpora. The experimental result shows that the BiLSTM approach outperforms the other approaches with an accuracy of 96.7%.

An epidemiological study and trend analysis of laboratory confirmed COVID-19 cases among children in North India.

Background: The role of children in transmitting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is difficult to ascertain and the consequences remain unclear. This is necessary for public health or infection control purposes. The objective of this study was to describe the epidemiological, month-wise trends and clinical characteristics of coronavirus disease 2019 (COVID-19) infection among children in a tertiary care hospital. Materials and Methods: A cross-sectional study was performed on all pediatric samples of suspected cases of SARS-CoV-2 infection. The samples were received from the adjoining districts and our Institution in the Department of Microbiology from June to November 2020. Cases were then confirmed by real-time reverse transcriptase-polymerase chain reaction. Results: Of the total 62,030 pediatric samples tested, 847 (1.3%) were SARS-CoV-2 positive. The majority of positive cases were between the ages of 11-15 years. The median age of confirmed patients was 14 years. The male to female ratio was 1.5:1. Infants represented 1.6% of the positive cases. About 62.1% of all positive cases were asymptomatic. Childhood cases increased from June 2020 and peaked in September 2020 before declining. Conclusion: Children of all ages appeared susceptible to COVID-19 and accounted for a very small proportion of confirmed cases. Mostly, children were found to be asymptomatic. Young children can be important transmitters of SARS-CoV-2 infection in the general population. This population can be important for targeting immunization efforts throughout a rapidly evolving situation. Our findings provide further evidence of the distribution of infection in children and the transmission of SARS-CoV-2.

Current Status and Potential of Biofortification to Enhance Crop Nutritional Quality: An Overview

Around 2 billion people are suffering from chronic malnutrition or “hidden hunger”, which is the result of many diseases and disorders, including cognitive degeneration, stunting growth, and mortality. Thus, biofortification of staple food crops enriched with micronutrients is a more sustainable option for providing nutritional supplements and managing malnutrition in a society. Since 2001, when the concept of biofortification came to light, different research activities have been carried out, like the development of target populations, breeding or genetic engineering, and the release of biofortified cultivars, in addition to conducting nutritional efficacy trials and delivery plan development. Although, being a cost-effective intervention, it still faces many challenges, like easy accessibility of biofortified cultivars, stakeholders’ acceptance, and the availability of biofortified germplasm in the public domain, which varies from region to region. Hence, this review is focused on the recent potential, efforts made to crop biofortification, impacts analysis on human health, cost-effectiveness, and future perspectives to further strengthen biofortification programs. Through regular interventions of sustainable techniques and methodologies, biofortification holds huge potential to solve the malnutrition problem through regular interventions of nutrient-enriched staple food options for billions of people globally.

Double zero tillage and foliar phosphorus fertilization coupled with microbial inoculants enhance maize productivity and quality in a maize-wheat rotation.

Maize is an important industrial crop where yield and quality enhancement both assume greater importance. Clean production technologies like conservation agriculture and integrated nutrient management hold the key to enhance productivity and quality besides improving soil health and environment. Hence, maize productivity and quality were assessed under a maize-wheat cropping system (MWCS) using four crop-establishment and tillage management practices [FBCT-FBCT (Flat bed-conventional tillage both in maize and wheat); RBCT-RBZT (Raised bed-CT in maize and raised bed-zero tillage in wheat); FBZT-FBZT (FBZT both in maize and wheat); PRBZT-PRBZT (Permanent raised bed-ZT both in maize and wheat], and five P-fertilization practices [P100 (100% soil applied-P); P50 + 2FSP (50% soil applied-P + 2 foliar-sprays of P through 2% DAP both in maize and wheat); P50 + PSB + AM-fungi; P50 + PSB + AMF + 2FSP; and P0 (100% NK with no-P)] in split-plot design replicated-thrice. Double zero-tilled PRBZT-PRBZT system significantly enhanced the maize grain, starch, protein and oil yield by 13.1-19% over conventional FBCT-FBCT. P50 + PSB + AMF + 2FSP, integrating soil applied-P, microbial-inoculants and foliar-P, had significantly higher grain, starch, protein and oil yield by 12.5-17.2% over P100 besides saving 34.7% fertilizer-P both in maize and on cropping-system basis. P50 + PSB + AMF + 2FSP again had significantly higher starch, lysine and tryptophan content by 4.6-10.4% over P100 due to sustained and synchronized P-bioavailability. Higher amylose content (24.1%) was observed in grains under P50 + PSB + AMF + 2FSP, a beneficial trait due to its lower glycemic-index highly required for diabetic patients, where current COVID-19 pandemic further necessitated the use of such dietary ingredients. Double zero-tilled PRBZT-PRBZT reported greater MUFA (oleic acid, 37.1%), MUFA: PUFA ratio and P/S index with 6.9% higher P/S index in corn-oil (an oil quality parameter highly required for heart-health) over RBCT-RBCT. MUFA, MUFA: PUFA ratio and P/S index were also higher under P50 + PSB + AMF + 2FSP; avowing the obvious role of foliar-P and microbial-inoculants in influencing maize fatty acid composition. Overall, double zero-tilled PRBZT-PRBZT with crop residue retention at 6 t/ha per year along with P50 + PSB + AMF + 2FSP while saving 34.7% fertilizer-P in MWCS, may prove beneficial in enhancing maize productivity and quality so as to reinforce the food and nutritional security besides boosting food, corn-oil and starch industry in south-Asia and collateral arid agro-ecologies across the globe.

An exploratory study to assess stakeholder's perception for new online teaching-learning environment during covid-19

Certain events bring unprecedented changes for the way things take place in our life. Spread of COVID-19 has brought a paradigm shift in a similar manner to the way we learn things and has dramatically altered the teaching learning process. Like any other tool, online learning was considered to be a supporting hand for augmenting the teaching learning experience by making the learning process more interactive and participative. COVID-19 has made online teaching as the sole mode for teaching learning for students and teachers. Without any doubt, when we run out of options only then we can ascertain the true facets of something. It can also be applied to evaluate the effectiveness of online teaching over traditional teaching. The present study is an endeavor to assess the stakeholder's perception for this new teaching learning environment which has emerged during this unprecedented situation. Respondents were selected using stratified judgment sampling method. 120 respondents from Delhi NCR were interviewed using structured questionnaire. Statistical tools like factor analysis, cross tabulation, t-test and discriminant analysis were used for data analysis. Factor analysis led to formation of dimensions namely awareness related to online teaching learning process, perception for decisions taken by higher education bodies, impact of pandemic on economic conditions and subsequent attendance and effectiveness of online classes. Further two-group discriminant analysis was applied to find out association among predictors and effectiveness of online learning. It was observed that awareness related to online teaching learning process, perception for decisions taken by administration, impact of pandemic on economic conditions, attendance, socio-economic background were prominent factors which significantly affect the respondent's perception for effectiveness of online classes._

Synergistic Effects of Multiple Factors Involved in COVID-19-dependent Muscle Loss.

The COVID-19 pandemic caused by the novel SARS-CoV-2 coronavirus is an ongoing pandemic causing severe health crisis worldwide. Recovered COVID-19 patients go through several long-term side effects such as fatigue, headaches, dizziness, weight loss, and muscle loss among others. Our study sought to determine the molecular mechanisms behind muscle loss in COVID-19 patients. We hypothesized that multiple factors such as cytokine storm and therapeutic drugs (glucocorticoid and antiviral drugs) might be involved in muscle loss. Using the Gene Expression Omnibus database, we identified several studies that performed RNA sequencing on skeletal muscles with the treatment of cytokine, glucocorticoid, and antiviral drugs. Our study identified cytokines, such as IL-1b, and IL-6, associated with altered regulation of several genes involved in the myogenic processes, including Ttn, Cxxc5, Malat1, and Foxo1. We also observed that glucocorticoid altered the expression of Foxo1, Lcn2, Slc39a14, and Cdkn1a. Finally, we found out that the antiviral (RNA-dependent RNA polymerase inhibitor) drug regulates the expression of some of the muscle-related genes (Txnip, Ccnd1, Hdac9, and Fbxo32). Based on our findings, we hypothesize that the cytokine storm, glucocorticoids, and antiviral drugs might be synergistically involved in COVID-19-dependent muscle loss.

Telemedicine trends in orthopaedics and trauma during the COVID-19 pandemic: A bibliometric analysis and review.

OBJECTIVES: In the wake of recent widespread interest in telemedicine during the COVID-19 era, many orthopaedic surgeons may be unfamiliar with clinical examination skills, patients' safety, data security, and implementation-related concerns in telemedicine. We present a bibliometric analysis and review of the telemedicine-related publications concerning orthopaedics care during the COVID-19 pandemic. Such analysis can help orthopaedic surgeons become acquainted with the recent developments in telemedicine and its usage in regular orthopaedics practice. METHODS: We systematically searched the database of Thomson Reuters Web of Science for telemedicine-related articles in orthopaedics published during the COVID-19 pandemic. The selected articles were analysed for their source journals, corresponding authors, investigating institutions, countries of the corresponding authors, number of citations, study types, levels of evidence, and a qualitative review. RESULTS: Fifty-nine articles meeting the inclusion criteria were published in 28 journals. Three hundred forty-two authors contributed to these research papers. The United States (US) contributed the most number of articles to the telemedicine-related orthopaedics research during the COVID-19 era. All articles combined had a total of 383 citations and 66.1% were related to the Economic and Decision-making Analyses of telemedicine implementation. By and large, level IV evidence was predominant in our review. CONCLUSION: Telemedicine can satisfactorily cover a major proportion of patients' visits to outpatient departments, thus limiting hospitals' physical workload. Telemedicine has a potential future role in emergency orthopaedics and inpatient care through virtual aids. The issues related to patient privacy, data security, medicolegal, and reimbursement-related aspects need to be addressed through precise national or regional guidelines. Lastly, the orthopaedic physical examination is a weak link in telemedicine and needs to be strengthened.