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Upper limb (UL) motor dysfunctions impact residual movement in hands/shoulders and limit participation in play, sports, and leisure activities. Clinical and laboratory assessments of UL movement can be time-intensive, subjective, and/or require specialized equipment and may not optimally capture a child's motor abilities. The restrictions to in-person research experienced during the COVID-19 pandemic have inspired investigators to design inclusive at-home studies with child participants and their families. Relying on the ubiquity of mobile devices, mobile health (mHealth) applications offer solutions for various clinical and research problems. This scoping review article aimed to aggregate and synthesize existing research that used health technology and mHealth approaches to evaluate and assess the hand function and UL movement in children with UL motor impairment. A scoping review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) model was conducted in March 2023 yielding 25 articles (0.32% of 7891 studies). Assessment characteristics included game or task-based tests (13/25, 52%), primarily for neurological disorders (e.g., autism spectrum disorder [ASD], dystonia, dysgraphia) or children with cerebral palsy (CP). Although several mHealth studies were conducted in the clinical environment (10/25, 40%), studies conducted at home or in nonclinical settings (15/25, 60%) reported acceptable and highly satisfactory to the patients as minimizing the potential risks in participation. Moreover, the remaining barriers to clinical translation included object manipulation on a touch screen, offline data analysis, real-world usability, and age-appropriate application design for the wider population. However, the results emphasize the exploration of mHealth over traditional approaches, enabling user-centered study design, family-oriented methods, and large-scale sampling in future research.

Standardizing clinical laboratory test results is critical for conducting clinical data science research and analysis. However, standardized data processing tools and guidelines are inadequate. In this paper, a novel approach for standardizing categorical test results based on supervised machine learning and the Jaro-Winkler similarity algorithm is proposed. A supervised machine learning model is used in this approach for scalable categorization of the test results into predefined groups or clusters, while Jaro-Winkler similarity is used to map text terms into standard clinical terms within these corresponding groups. The proposed method is applied to 75062 test results from two private hospitals in Bangladesh. The Support Vector Classification algorithm with a linear kernel has a classification accuracy of 98%, which is better than the Random Forest algorithm when categorizing test results. The experiment results show that Jaro-Winkler similarity achieves a remarkable 99.93% success rate in the test result standardization for the majority of groups with manual validation. The proposed method outperforms previous studies that concentrated on standardizing test results using rule-based classifiers on a smaller number of groups and distance similarities such as Cosine similarity or Levenshtein distance. Furthermore, when applied to the publicly available MIMIC-III dataset, our approach also performs excellently. All these findings show that the proposed standardization technique can be very beneficial for clinical big data research, particularly for national clinical research data hubs in low- and middle-income countries., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

Green synthesis is a promising and cost-effective technique to synthesize nanoparticles from plant extract. The present study shows the green synthesis of zirconium nanoparticles using the extract of ginger, garlic, and zirconium nitride. The obtained nanoparticles were studied for potential dental implant applications. The synthesized nanoparticles were characterized by Fourier Transform Infrared Spectroscopy (FTIR), Field Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-Ray Spectroscopy (EDX), X-Ray diffraction analysis (XRD), and antibacterial analysis. FTIR analysis confirmed the presence of various organic compounds in the synthesized nanoparticles. The synthesized nanoparticles were spherical, triangular, and irregular, with varying sizes confirmed by FESEM analysis. The nanoparticles synthesized from the combination of garlic and ginger, and zirconium exhibited potent antibacterial activity against S. aureus . Anti-biofilm, anti-microbial activity, biointegration formation, and cell mechanism survival are also mentioned. Thus, the synthesized nanoparticles can be a good candidate for a dental implant because of their excellent antimicrobial properties., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)

Protecting personal health records is becoming increasingly important as more people use Mobile Health applications (mHealth apps) to improve their health outcomes. These mHealth apps enable consumers to monitor their health-related problems, store, manage, and share health records, medical conditions, treatment, and medication. With the increase of mHealth apps accessibility and usability, it is crucial to create, receive, maintain or transmit protected health information (PHI) on behalf of a covered entity or another business associate. The Health Insurance Portability and Accountability Act (HIPAA) provides guidelines to the app developers so that the apps must be compliant with required and addressable Technical Safeguards. However, most mobile app developers, including mHealth apps are not aware of HIPAA security and privacy regulations. Therefore, a research opportunity has emerged to develop an analytical framework to assist the developer to maintain a secure and HIPAA-compliant source code and raise awareness among consumers about the privacy and security of sensitive and personal health information. We proposed an Android source code analysis framework that evaluates twelve HIPAA Technical Safeguards to check whether a mHealth application is HIPAA compliant or not. The implemented meta-analysis and data-flow analysis algorithms efficiently identify the risk and safety features of mHealth apps that violate HIPAA regulations. Furthermore, we addressed API level checking for secure data communication mandated by recent CMS guidelines between third-party mobile health apps and EHR systems. Experimentally, a web-based tool has been developed for evaluating the efficacy of analysis techniques and algorithms. We have investigated 200 top popular Medical and Health & Fitness category Android apps collected from Google Play Store. We identified from the comparative analysis of the HIPAA rules assessment results that authorization to access sensitive resources, data encryption-decryption, and data transmission security is the most vulnerable features of the investigated apps. We provided recommendations to app developers about the most common mistake made at the time of app development and how to avoid these mistakes to implement secure and HIPAA-compliant apps. The proposed framework enables us to develop an IDE plugin for mHealth app developers and a web-based interface for mHealth app consumers.

Environmental degradation can be predicted and managed in a sustainable manner by the perodic analysis of the Land Use/Land Cover (LULC) change pattern, which not only helps to revitalize the environment but also helps to improve future land-use policies. With the Rohingya influx in 2017, the Kutupalong Mega Camp area in Bangladesh is at a severe risk of environmental degradation as the area is experiencing remarkable LULC change. The aim of this research is to illustrate the LULC change in the Kutupalong Mega Camp before and after the refugee influx, as well as its impact on the surrounding environment because of this change. The spatial and temporal variation of the LULC is analyzed from the classified multi-temporal Landsat images for years-2015, 2018, and 2021. The study reveals gradual decrease in forest cover of the area, which is replaced by the increasing human settlements. The study found an inverse relation between the refugee influx and the vegetation cover, where a positive relation to the bare land and settlement exists. The area experienced about ten times increase in human settlements during 2015-2021, which resulted deforestation of surrounding forest cover. Between 2015 to 2021, 74 % of forest cover of the studied area has been cleaned up for newer settlements, with an increase of wetland to meet the needs of increasing refugee population which has made the scenario worse. We also noticed an increase of Land Surface Temperature (LST) within a short period, where the average temperature increase rate is 0.06% during 2015-2018 and 0.01% during 2018-2021. The ecosystem, wild-habitat, and the thermal environment has been disturbed to a great extent due to this drastic change of forest cover mostly by the increasing anthropogenic activities in this area. The study represents the present scenario in comparison to its natural setting just a few years ago, and may serve as a guidance for the concerned authorities and international humanitarian organizations to develop a sustainable, comprehensive, and environment-friendly land management plan in order to protect the surrounding forest-ecology as well as the humanitarian works., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors.)

Bangladesh remains cholera endemic with biannual seasonal peaks causing epidemics. At least 300,000 severe cases and over 4,500 deaths occur each year. The available oral cholera vaccineshave not yet been adopted for cholera control in Bangladesh due to insufficient number of doses available for endemic control. With a public private partnership, icddr,b initiated a collaboration between vaccine manufacturers in Bangladesh and abroad. A locally manufactured Oral Cholera Vaccine (OCV) named Cholvax became available for testing in Bangladesh. We evaluated the safety and immunogenicity of this locally produced Cholvax (Incepta Vaccine Ltd) inexpensive OCV comparatively to Shanchol (Shantha Biotechnics-Sanofi Pasteur) which is licensed in several countries. We conducted a randomized non-inferiority clinical trial of bivalent, killed oral whole-cell cholera vaccine Cholvax vs. Shanchol in the cholera-endemic area of Mirpur, Dhaka, among three different age cohorts (1-5, 6-17 and 18-45 years) between April 2016 and April 2017. Two vaccine doses were given at 14 days apart to 2,052 healthy participants. No vaccine-related serious adverse events were reported. There were no significant differences in the frequency of solicited (7.31% vs. 6.73%) and unsolicited (1.46% vs. 1.07%) adverse events reported between the Cholvax and Shanchol groups. Vibriocidal antibody responses among the overall population for O1 Ogawa (81% vs. 77%) and O1 Inaba (83% vs. 84%) serotypes showed that Cholvax was non-inferior to Shanchol, with the non-inferiority margin of -10%. For O1 Inaba, GMT was 462.60 (Test group), 450.84 (Comparator group) with GMR 1.02(95% CI: 0.92, 1.13). For O1 Ogawa, GMT was 419.64 (Test group), 387.22 (Comparator group) with GMR 1.12 (95% CI: 1.02, 1.23). Cholvax was safe and non-inferior to Shanchol in terms of immunogenicity in the different age groups. These results support public use of Cholvax to contribute for reduction of the cholera burden in Bangladesh. ClinicalTrials.gov number: NCT027425581., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The study was done to find out the causes that changes the fasting serum glucose level in postmenopausal women. This was descriptive type of cross sectional study carried out over a period of one year from July 2014 to June 2015 in the department of physiology, Mymensingh Medical College, Mymensingh. Women of reproductive age (25-45 years) and clinically diagnosed 100 menopausal women (45-70 years) were included for this study. Convenience type of sampling technique was used for selecting the study subjects. Measurement of fasting serum glucose was done by GOD-PAP method. Data were expressed as mean±SD and statistical significance of difference among the groups were calculated by unpaired student's 't' test. The mean±SD of serum glucose in menopausal women were significant at 1% level of probability than women of reproductive age. This study revealed that postmenopausal women showed higher levels of fasting serum glucose level. Fasting blood sugar level between the study & control group were 7.69±2.37 and 4.59±0.73 and the difference was statistically significant.

Merkel cell carcinoma (MCC) is the most aggressive skin cancer. Recently, it was demonstrated that human Merkel cell polyomavirus (MCV) is clonally integrated in 80% of MCC tumors. Genetic studies of MCV have shown that T antigen protein is responsible for replication of genome and play a foremost role in viral infection. Therefore, T antigen protein may be used as suitable target for disease diagnosis. Viral activity can be restrained through RNA interference (RNAi) technology, an influential method for post transcriptional gene silencing in a sequence specific manner. In current study four effective siRNA molecules for silencing of MCV were rationally designed and validated using computational methods, which may lead to knockdown the activity of virus. Thus, this approach may provide an insight for the chemical synthesis of antiviral RNA molecule for the treatment of MCC at genome level.