Spatial Data Infrastructure (SDI) frameworks provide a foundation for the integration and sharing of geospatial data, essential for public health decision-

Of the approximately 40 million people living with human immunodeficiency virus (HIV) globally as of 2022, a clinically significant subset harbours multidrug-resistant (MDR) HIV-1, leaving them with few viable antiretroviral options. Ibalizumab (Trogarzo), a recombinant humanised IgG4 monoclonal antibody, received FDA approval in March 2018 as the first monoclonal antibody for HIV-1 therapy and the first agent of a novel mechanistic class approved in over a decade. This review critically appraises ibalizumab across its discovery, mechanism of action, pharmacology, clinical trial evidence, safety profile, special populations, and access considerations. A narrative review of peer-reviewed literature was conducted using PubMed and Embase, supplemented by data from ClinicalTrials.gov, FDA and European Medicines Agency (EMA) regulatory documents, and relevant conference proceedings published up to March 2026. Ibalizumab binds domain 2 (D2) of the extracellular CD4 receptor, sterically blocking post-attachment conformational changes required for co-receptor engagement without impairing MHC class II immune signalling. In the pivotal Phase III TMB-301 trial, 83% of heavily treatment-experienced adults achieved a clinically meaningful viral load reduction at week 24, while extended-access studies demonstrated durable virological suppression and sustained immunological recovery. The drug is generally well tolerated, with diarrhoea, headache, and nausea being the most frequently reported adverse events. Resistance develops rapidly when ibalizumab is used as monotherapy, underscoring the necessity of combining it with an optimised background antiretroviral regimen. Ibalizumab represents a genuine therapeutic advance for patients with MDR HIV-1 who have exhausted conventional regimens. Its unique mechanism, established efficacy, and favourable safety profile make it an indispensable salvage therapy component. Key barriers to broader uptake include intravenous administration, biweekly clinic attendance, high cost, and limited availability in resource-constrained settings. Long-acting formulations and bispecific antibody strategies offer promise for expanding its clinical reach.

Antimicrobial resistance (AMR) is a major global health threat that erodes the effectiveness of antibiotics and increases morbidity, mortality, and healthcare costs. Updated forecasts project that bacterial AMR could directly cause approximately 39 million deaths between 2025 and 2050, with annual deaths rising from 1.14 million in 2021 to an estimated 1.91 million in 2050; earlier economic modelling placed the cumulative cost of unchecked resistance at up to 100 trillion United States dollars. These figures underscore the need for sustainable alternatives to conventional antibiotics. This review synthesizes current evidence on non-antibiotic strategies, including bacteriophages, antimicrobial peptides, CRISPR-based antimicrobials, microbiome modulation, host-directed therapies, nanotechnology, and artificial-intelligence-driven drug discovery. We searched more than one hundred peer-reviewed studies, clinical trial reports, primary epidemiological analyses, and international policy and regulatory documents to evaluate therapeutic mechanisms, clinical progress, and implementation barriers, with particular attention to which strategies suit personalized, patient-specific application and which are more amenable to standardized mass production. Bacteriophages and antimicrobial peptides show potent broad-spectrum activity with reduced resistance selection pressure, CRISPR-based approaches enable precise pathogen targeting, and microbiome therapies restore colonization resistance. Clinical translation, however, is hindered by inconsistent regulatory frameworks, limited manufacturing scalability, incomplete safety profiles, and constrained funding in low-resource settings. Mitigating the AMR crisis will require a coordinated, multidisciplinary response grounded in the One Health paradigm, emphasizing antimicrobial stewardship, equitable global access to emerging therapeutics, and sustained investment in translational research.

Cyberbullying is persistent deliberate harm, inflicted within a power imbalance between victim and perpetrator, with the hostility conveyed through electronic media. It is a serious global public health issue, exacerbated by advancing technologies and the expanding digital environment. This study determined the prevalence, pattern and self-reported health effects of cyberbullying among university students of Ekiti State University, Ado-Ekiti, Nigeria. A cross-sectional study was conducted among 384 university students of Ekiti State University, Ado-Ekiti, using an adapted, pretested, semi-structured, interviewer-administered questionnaire to collect the data. Multistage sampling methods was used to select the participants. All data collected were analyzed using Statistical package for social science software version 25. Data were summarised using descriptive statistics, and 95% confidence intervals (CI) were calculated for prevalence estimates. In the preceding three months, 9.6% (95% CI 7.1-13.0) of respondents had perpetrated and 28.9% (95% CI 24.6-33.6) had experienced cyberbullying. The commonest forms among perpetrators (n=37) and victims (n=111) were hurtful or insulting remarks (59.5% and 64.9%) and exclusion from an online group (51.4% and 61.3%); relationship-related abuse or sexual solicitation was reported by 52.3% of victims but only 10.8% of perpetrators. Perpetrators most often used chat platforms such as WhatsApp and Snapchat (73.0%) and phone calls (43.2%), whereas victims most often reported text messages and chat platforms (46.8% each). Among victims, the most frequently reported symptoms were feeling tense, anxious or nervous (38.7%), feeling sad (36.9%) and little appetite (33.3%); stomach ache (18.0%) was least reported. In conclusion, almost three in ten undergraduates reported being cyberbullied, and about one in ten reported perpetrating cyberbullying, in the preceding three months. Hurtful remarks and online exclusion predominated, mostly through chat platforms, text messages and phone calls. Victims commonly reported tension or anxiety, sadness and loss of appetite, although causality cannot be inferred from this cross-sectional design. Campus-based awareness and health promotion programmes, institutional reporting policies and counselling support targeted at these forms and media are recommended.

Electrocardiogram (ECG) arrhythmia classification remains critical for automated cardiac diagnosis, yet feature extraction methods are frequently adopted without systematic comparative evaluation. This study presents a controlled comparative analysis of four signal processing techniques—Mel-Frequency Cepstral Coefficients (MFCC), Discrete Wavelet Transform (DWT), Hilbert–Huang Transform (HHT), and Synchrosqueezing Wavelet Transform (SSWT)—for ECG feature extraction. Using the MIT-BIH Arrhythmia Database with ANSI/AAMI EC57:1998 standard mapping, we trained Cascade Forest classifiers on each feature set under identical preprocessing and SMOTE-based class balancing conditions to ensure a fair comparison. DWT features achieved superior performance (accuracy: 98.79%, macro-F1: 92.93%, precision: 94.39%) compared to MFCC (88.30% macro-F1), SSWT (84.54% macro-F1), and HHT (83.59% macro-F1), particularly for clinically challenging minority arrhythmia classes. However, DWT’s performance advantage incurred substantial computational cost (10,050 s), while MFCC provided competitive results with a 62% lower computational burden. These findings provide evidence-based guidance for feature extraction method selection in interpretable ECG classification systems, demonstrating critical performance-efficiency trade-offs relevant to clinical deployment contexts.