Cross Dataset Evaluation for IoT Network Intrusion Detection

With the advent of Internet of Things (IOT) technology, the need to ensure the security of an IOT network has become important. There are several intrusion detection systems (IDS) that are available for analyzing and predicting network anomalies and threats. However, it is challenging to evaluate them to realistically estimate their performance when deployed. A lot of research has been conducted where the training and testing is done using the same simulated dataset. However, realistically, a network on which an intrusion detection model is deployed will be very different from the network on which it was trained. The aim of this research is to perform a cross-dataset evaluation using different machine learning models for IDS. This helps ensure that a model that performs well when evaluated on one dataset will also perform well when deployed. Two publicly available simulation datasets., IOTID20 and Bot-IoT datasets created to capture IOT networks for different attacks such as DoS and Scanning were used for training and testing. Machine learning models applied to these datasets were evaluated within each dataset followed by cross -dataset evaluation. A significant difference was observed between the results obtained using the two datasets. Supervised machine learning models were built and evaluated for binary classification to classify between normal and anomaly attack instances as well as for multiclass classification to also categorize the type of attack on the IoT network

Prevalence of Bombay phenotype among Bangladeshi ‘O’ blood group population

Background: The Bombay blood group, a rare type often confused with ‘O’, poses a critical transfusion risk, requiring specific compatibility with Bombay (Oh) blood. With a lack of data in Bangladesh, this study aimed to establish a comprehensive database for the rare Bombay phenotype, crucial for transfusion safety. Objective was to determine the frequency prevalence of Bombay phenotype among ‘O’ blood group individuals. Methods: A cross-sectional study conducted at Bangabandhu Sheikh Mujib Medical University from January 2020 to June 2021 involved, aseptic collection of 3 ml venous blood sample, with forward and reverse blood grouping revealing a ‘O’ phenotype. Utilizing anti-H lectin resolved discrepancies and confirmed the absence of ‘H’ antigen in individuals with Bombay blood groups. Blood samples of Bombay phenotype individuals showed the following reactions: anti-A (-), anti-B (-), anti-AB (-), anti-H (-), A cells 4+, B cells 4+, O cells 4+. Results: Among 10,000 individuals with apparent blood group ‘O’, 99.97% were identified as ‘O’ blood type, while only 0.03% exhibited the rare Bombay blood group. ABO and Rh-D blood group frequencies varied over the study period, with B +ve at the highest (28.31%) and AB -ve at the lowest (0.21% to 0.23%). Overall, O +ve had the highest frequency (97.29%), and Bombay blood group was rare, with ‘O’ dominating at 99.97%. Conclusions: The study identified a 0.03% prevalence of the Bombay phenotype. Due to its potential confusion with ‘O’ blood group, transfusing ‘O’ blood to Bombay individuals carries a substantial risk of severe hemolytic reactions, including fatal consequences

Frequency of ABO and Rh-D blood groups in cervical cancer

There is much evidence that the ABO blood group system may play a role in the pathogenesis of the disease. The relationship between ABO and Rhesus blood groups and cancer risk has been demonstrated in many research works. However, concerning gynaecological malignancies, these findings are inconsistent. This study aimed to evaluate the frequency of ABO and Rh-D blood groups in patients with carcinoma cervix. This cross-sectional study was conducted in the Department of Transfusion Medicine, Department of Gynaecological Oncology and Department of Pathology of Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka. A total of 110 clinically suspected cervical cancer patients were included in this study. Pap smear tests was done in all cases and the patients were divided into case (Pap test positive) and control group (Pap test negative). A total of 55 patients were included in each group. Blood groups (ABO & Rh-D) of all the patients were recorded. A higher number of the patients in the cervical cancer group were multiparous than in the control group. Almost in two-thirds of the population, the age of marriage was <18 years in the cervical cancer group compared to 34.5% in the control group. More than one-third population had “O” blood group in the case group, while it was 31% in the control group. The almost equal number had Rh D+ve in the case and control (92.7% vs. 94.5%). The differences between the blood group and Rh D were not statistically significant between the two groups. Nearly half (40.0%) of the participants had used a hormonal contraceptive in the case and 61.8% in control. The differences in hormonal contraceptives use were statistically significant within the two groups. The distribution of “O” blood group and Rh D +ve cases was found to be higher in patients with cervical cancer than in non-cancer patients although the difference was not statistically significant. BSMMU J 2022; 15(2): 70-7

Identification of Phytoconstituents as Potent Inhibitors of Casein Kinase-1 Alpha Using Virtual Screening and Molecular Dynamics Simulations

Casein kinase-1 alpha (CK1&alpha;) is a multifunctional protein kinase that belongs to the serine/threonine kinases of the CK1&alpha; family. It is involved in various signaling pathways associated with chromosome segregation, cell metabolism, cell cycle progression, apoptosis, autophagy, etc. It has been known to involve in the progression of many diseases, including cancer, neurodegeneration, obesity, and behavioral disorders. The elevated expression of CK1&alpha; in diseased conditions facilitates its selective targeting for therapeutic management. Here, we have performed virtual screening of phytoconstituents from the IMPPAT database seeking potential inhibitors of CK1&alpha;. First, a cluster of compounds was retrieved based on physicochemical parameters following Lipinski&rsquo;s rules and PAINS filter. Further, high-affinity hits against CK1&alpha; were obtained based on their binding affinity score. Furthermore, the ADMET, PAINS, and PASS evaluation was carried out to select more potent hits. Finally, following the interaction analysis, we elucidated three phytoconstituents, Semiglabrinol, Curcusone_A, and Liriodenine, posturing considerable affinity and specificity towards the CK1&alpha; binding pocket. The result was further evaluated by molecular dynamics (MD) simulations, dynamical cross-correlation matrix (DCCM), and principal components analysis (PCA), which revealed that binding of the selected compounds, especially Semiglabrinol, stabilizes CK1&alpha; and leads to fewer conformational fluctuations. The MM-PBSA analysis suggested an appreciable binding affinity of all three compounds toward CK1&alpha;

MAP/Microtubule Affinity Regulating Kinase 4 Inhibitory Potential of Irisin: A New Therapeutic Strategy to Combat Cancer and Alzheimer’s Disease

Irisin is a clinically significant protein playing a valuable role in regulating various diseases. Irisin attenuates synaptic and memory dysfunction, highlighting its importance in Alzheimer’s disease. On the other hand, Microtubule Affinity Regulating Kinase 4 (MARK4) is associated with various cancer types, uncontrolled neuronal migrations, and disrupted microtubule dynamics. In addition, MARK4 has been explored as a potential drug target for cancer and Alzheimer’s disease therapy. Here, we studied the binding and subsequent inhibition of MARK4 by irisin. Irisin binds to MARK4 with an admirable affinity (K = 0.8 × 107 M−1), subsequently inhibiting its activity (IC50 = 2.71 µm). In vitro studies were further validated by docking and simulations. Molecular docking revealed several hydrogen bonds between irisin and MARK4, including critical residues, Lys38, Val40, and Ser134. Furthermore, the molecular dynamic simulation showed that the binding of irisin resulted in enhanced stability of MARK4. This study provides a rationale to use irisin as a therapeutic agent to treat MARK4-associated diseases

Bridging the climate information gap for adaptation: Mainstreaming climate services into higher education in Bangladesh

Bangladesh has proactively integrated climate change into national policies, and is renowned for constantly improving adaptation capacity. Yet, much of the focus has concentrated on long-term climate change scenarios and short-term weather forecasts. Additionally, most decision-makers (both policymakers and practitioners) lack the knowledge and skills to understand and use available climate information (past, present, short-, medium- and long-term future) that can support locally-led adaptation and reduce loss and damage. Bangladesh Meteorological Department (BMD) has been working with IRI and others to improve not only the range and quality of information products but also its communication modalities. International Centre for Climate Change and Development (ICCCAD), International Research Institute for Climate and Society (IRI), Bangladesh Meteorological Department (BMD), and International Maize and Wheat Improvement Center (CIMMYT) jointly created the Bangladesh Academy for Climate Services (BACS) to strengthen national climate services through training, academic engagement and stakeholder convening. This report describes the outcomes of an Adaptation Research Alliance (ARA) funded microgrant project aligned with the BACS goals of co-producing climate services content that can help bridge the climate services knowledge gap in Bangladesh through transdisciplinary collaboration. The project was a collaboration between several universities across the country to support a long-term vision where young people are trained in every climate-sensitive sector to make use of all information available to improve their resilience

Comparative analysis of web-based programs for single amino acid substitutions in proteins

Single amino-acid substitution in a protein affects its structure and function. These changes are the primary reasons for the advent of many complex diseases. Analyzing single point mutations in a protein is crucial to see their impact and to understand the disease mechanism. This has given many biophysical resources, including databases and web-based tools to explore the effects of mutations on the structure and function of human proteins. For a given mutation, each tool provides a score-based outcomes which indicates deleterious probability. In recent years, developments in existing programs and the introduction of new prediction algorithms have transformed the state-of-the-art protein mutation analysis. In this study, we have performed a systematic study of the most commonly used mutational analysis programs (10 sequence-based and 5 structure-based) to compare their prediction efficiency. We have carried out extensive mutational analyses using these tools for previously known pathogenic single point mutations of five different proteins. These analyses suggested that sequence-based tools, PolyPhen2, PROVEAN, and PMut, and structure-based web tool, mCSM have a better prediction accuracy. This study indicates that the employment of more than one program based on different approaches should significantly improve the prediction power of the available methods

Loss-to-follow-up and delay to treatment initiation in Pakistan's national tuberculosis control programme

BACKGROUND: Researchers and policy-makers have identified loss to follow-up as a major programmatic problem. Therefore, the objective of this study is to quantify TB related pre-treatment loss to follow up and treatment delay in private sector health care facilities in Pakistan. METHODS: This was a retrospective, descriptive cohort study using routinely collected programmatic data from TB referral, diagnosis and treatment registers. Data from 48 private healthcare facilities were collected using an online questionnaire prepared in ODK Collect, for the period October 2015 to March 2016. Data were analysed using SPSS. We calculated the: (1) number and proportion of patients who were lost to follow-up during the diagnostic period, (2) number and proportion of patients with pre-treatment loss to follow-up, and (3) the number of days between diagnosis and initiation of treatment. RESULTS: One thousand five hundred ninety-six persons with presumptive TB were referred to the laboratory. Of these, 96% (n = 1538) submitted an on-the-spot sputum sample. Of the 1538 people, 1462 (95%) people subsequently visited the laboratory to submit the early morning (i.e. the second) sample. Hence, loss to follow-up during the diagnostic process was 8% overall (n = 134). Of the 1462 people who submitted both sputum samples, 243 (17%) were diagnosed with sputum smear-positive pulmonary TB and 231 were registered for anti-TB treatment, hence, loss in the pre-treatment phase was 4.9% (n = 12). 152 persons with TB (66%) initiated TB treatment either on the day of TB diagnosis or the next day. A further 79 persons with TB (34%) commenced TB treatment within a mean time of 7 days (range 2 to 64 days). CONCLUSION: Concentrated efforts should be made by the National TB Control Programme to retain TB patients and innovative methods such as text reminders and behavior change communication may need to be used and tested

Impact of single amino acid substitutions in Parkinsonism-associated deglycase-PARK7 and their association with Parkinson’s disease

Parkinsonism-associated deglycase-PARK7/DJ-1 (PARK7) is a multifunctional protein having significant roles in inflammatory and immune disorders and cell protection against oxidative stress. Mutations in PARK7 may result in the onset and progression of a few neurodegenerative disorders such as Parkinson’s disease. This study has analyzed the non-synonymous single nucleotide polymorphisms (nsSNPs) resulting in single amino acid substitutions in PARK7 to explore its diseasecausing variants and their structural dysfunctions. Initially, we retrieved the mutational dataset of PARK7 from the Ensembl database and performed detailed analyses using sequence-based and structure-based approaches. The pathogenicity of the PARK7 was then performed to distinguish the destabilizing/deleterious variants. Aggregation propensity, noncovalent interactions, packing density, and solvent accessible surface area analyses were carried out on the selected pathogenic mutations. The SODA study suggested that mutations in PARK7 result in aggregation, inducing disordered helix and altering the strand propensity. The effect of mutations alters the number of hydrogen bonds and hydrophobic interactions in PARK7, as calculated from the Arpeggio server. The study indicated that the alteration in the hydrophobic contacts and frustration of the protein could alter the stability of the missense variants of the PARK7, which might result in disease progression. This study provides a detailed understanding of the destabilizing effects of single amino acid substitutions in PARK7