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Background Breast cancer is rapidly increasing worldwide. Pakistan has a high incidence rate of one in every nine women. The lack of awareness is the major reason for delayed diagnosis, thus resulting in high mortality. This study aimed to assess the impact of pharmacist-led breast cancer education at community pharmacies on promoting breast cancer awareness. Methodology A longitudinal pre-post intervention study was conducted on 319 participants using a self-designed questionnaire. During the pre-intervention phase, data were collected from participants at various community pharmacies employing questionnaire administration. The provision of a breast cancer educational session followed the session. After three months, the participants were contacted via telephone, and the questionnaires were filled in again during the post-intervention phase. Data was analyzed using SPSS version 25. Results The pre-post phase data evaluation reported improved breast cancer awareness among the study participants, with a significant increase ( p  = 0.000) in awareness of breast cancer symptoms, risk factors, and diagnostic techniques. There was a statistical increase in breast self-examination practice during the post-intervention phase (2.5% to 93.8%). Knowledge about clinical breast examination improved from 8.5% (pre-intervention phase) to 84.4% (post-intervention phase). Additionally, understanding mammography as a vital screening technique improved significantly, with approximately 34.7% of eligible women having undergone mammography in the post-intervention phase. Conclusion A notable improvement in breast cancer awareness and self-examination was observed through pharmacist-led education. Leveraging pharmacist-led services in community pharmacies could effectively contribute to breast cancer control efforts. Utilizing pharmacists nationwide could facilitate the implementation of comprehensive strategies to elevate public breast cancer awareness nationally.

This study, while detailing the processes of securitisation and de-securitisation of a non-traditional security issue, deliberates on the water scarcity in Pakistan. It addresses the question that whether the problem of not giving importance to water scarcity lies with the ‘intent’ or ‘capacity’ of the actors – the elite. Or the securitisation is done by the actors ‘only’ to achieve their political objectives? This qualitative embedded case study deals with the rhetoric about the construction of the Diamer Basha Dam in order to address the water scarcity around the 2018 elections. The study finds that the securitisation of non-tradition security issues translates the elite's (securitising actors) political rhetoric (speech acts) into policy. The same elite de-securitises the issues after realising their political goals by removing the ‘speech acts’ from the equation.

This review article explores the transformative impact of next-generation technologies on patient care and rehabilitation. The advent of next-generation tools has revolutionized the fields of patient care and rehabilitation, providing modern solutions to improve scientific outcomes and affected person studies. Powered through improvements in artificial intelligence, robotics, and smart devices, these improvements are reshaping healthcare with the aid of improving therapeutic approaches and personalizing treatments. In the world of rehabilitation, robotic devices and assistive technology are supplying essential help for people with mobility impairments, promoting more independence and healing. Additionally, wearable technology and real-time tracking systems permit continuous fitness information monitoring, taking into consideration early analysis and extra effective, tailored interventions. In clinical settings, these modern-day innovations have automated diagnostics, enabled remote patient-monitoring, and brought virtual rehabilitation systems that expand the reach of clinical experts. This comprehensive review delves into the evolution, cutting-edge programs, and destiny potential of that equipment by examining their capability to deliver progressed care even while addressing growing needs for efficient healthcare solutions. Furthermore, this review explores the challenges related to their adoption, including ethical considerations, accessibility barriers, and the need for refined regulatory standards to ensure their safe and widespread use.

Breast cancer (BC) significantly contributes to cancer-related mortality in women, underscoring the criticality of early detection for optimal patient outcomes. Mammography is a key tool for identifying and diagnosing breast abnormalities; however, accurately distinguishing malignant mass lesions remains challenging. To address this issue, we propose a novel deep learning approach for BC screening utilizing mammography images. Our proposed model comprises three distinct stages: data collection from established benchmark sources, image segmentation employing an Atrous Convolution-based Attentive and Adaptive Trans-Res-UNet (ACA-ATRUNet) architecture, and BC identification via an Atrous Convolution-based Attentive and Adaptive Multi-scale DenseNet (ACA-AMDN) model. The hyperparameters within the ACA-ATRUNet and ACA-AMDN models are optimized using the Modified Mussel Length-based Eurasian Oystercatcher Optimization (MML-EOO) algorithm. The performance is evaluated using a variety of metrics, and a comparative analysis against conventional methods is presented. Our experimental results reveal that the proposed BC detection framework attains superior precision rates in early disease detection, demonstrating its potential to enhance mammography-based screening methodologies.

In recent years, microwave imaging (MWI) has emerged as a non-ionizing and cost-effective modality in healthcare, specifically within medical imaging. Concurrently, advances in artificial intelligence (AI) have significantly augmented the capabilities of medical imaging tools. This paper explores the intersection of these two domains, focusing on the integration of AI algorithms into MWI techniques to elevate accuracy and overall performance. Within the scope of existing literature, representative prior works are compared concerning the application of AI in both the “MWI for Healthcare Applications\" and “Artificial Intelligence Assistance In MWI\" sections. This comparative analysis sheds light on the diverse approaches employed to enhance the synergy between AI and MWI. While highlighting the state-of-the-art technology in MWI and its historical context, this paper delves into the historical taxonomy of AI-assisted MWI, elucidating the evolution of intelligent systems within this domain. Moreover, it critically examines prominent works, providing a nuanced understanding of the advancements and challenges encountered. Addressing the limitations and challenges inherent in developing AI-assisted MWI systems like Generalization to different conditions, Generalization to different conditions, etc the paper offers a brief synopsis of these obstacles, emphasizing the importance of overcoming them for robust and reliable results in actual clinical environments. Finally, the paper not only underscores the current advancements but also anticipates future innovations and developments in utilizing AI for MWI applications in healthcare.

The ongoing COVID-19 pandemic is caused by SARs-CoV-2. The virus is transmitted from person to person through droplet infections i.e. when infected person is in close contact with another person. In January 2020, first report of detection of SARS-CoV-2 in faeces, has made it clear that human wastewater might contain this virus. This may illustrate the probability of environmentally facilitated transmission, mainly the sewage, however, environmental conditions that could facilitate faecal oral transmission is not yet clear. We used existing Pakistan polio environment surveillance network to investigate presence of SARs-CoV-2 using three commercially available kits and E-Gene detection published assay for surety and confirmatory of positivity. A Two-phase separation method is used for sample clarification and concentration. An additional high-speed centrifugation (14000Xg for 30 min) step was introduced, prior RNA extraction, to increase viral RNA yield resulting a decrease in Cq value. A total of 78 wastewater samples collected from 38 districts across Pakistan, 74 wastewater samples from existing polio environment surveillance sites, 3 from drains of COVID-19 infected areas and 1 from COVID 19 quarantine center drainage, were tested for presence of SARs-CoV-2. 21 wastewater samples (27%) from 13 districts turned to be positive on RT-qPCR. SARs-COV-2 RNA positive samples from areas with COVID 19 patients and quarantine center strengthen the findings and use of wastewater surveillance in future. Furthermore, sequence data of partial ORF 1a generated from COVID 19 patient quarantine center drainage sample also reinforce our findings that SARs-CoV-2 can be detected in wastewater. This study finding indicates that SARs-CoV-2 detection through wastewater surveillance has an epidemiologic potential that can be used as supplementary system to monitor viral tracking and circulation in cities with lower COVID-19 testing capacity or heavily populated areas where door-to-door tracing may not be possible. However, attention is needed on virus concentration and detection assay to increase the sensitivity. Development of highly sensitive assay will be an indicator for virus monitoring and to provide early warning signs.

The global spread of SARS-CoV-2 was significantly impacted by the emergence of Variants of Concern (VOC), with Pakistan experiencing similar trends to other countries. To gain a comprehensive understanding of the genomic epidemiology of SARS-CoV-2 strains circulating during Pakistan’s third and fourth pandemic waves, we conducted the largest single sequencing effort in the country to date. Using the GridION platform (Oxford Nanopore Technologies), we performed whole genome sequencing on 1052 confirmed COVID-19 patient samples collected from multiple cities across Pakistan between March and October 2021. Our analysis revealed a clear temporal shift in variant dominance. The Alpha variant (B.1.1.7 lineage) predominated in the first half of 2021, while the Delta variant (B.1.617.2) became most prevalent in the latter half. This transition reflects global trends and provides crucial insights into the timing and dynamics of this shift within Pakistan. Mutational analysis revealed that the most frequent nucleotide mutations in Pakistani SARS-CoV-2 samples were A23403G (associated with the D614G mutation in the spike protein), C3037T, C14408T, and C241T, potentially contributing to increased disease transmission and evasion of host immune responses. The rapid evolution and spread of these circulating variants highlight the possibility of novel variants emerging with enhanced mutational fitness. The AY.108 lineage, which has been reported at relatively low frequencies globally including in Europe and North America, with Pakistan accounting for approximately 34% of global cases, suggesting potential regional evolution or specific introduction events. Our findings underscore the dynamic nature of SARS-CoV-2 and emphasize the critical importance of ongoing, large-scale genomic surveillance in Pakistan. This study demonstrates the feasibility and utility of using nanopore sequencing for comprehensive viral monitoring in Pakistan’s public health context. While we utilized the higher-throughput GridION platform for centralized processing, the Oxford Nanopore technology still provided distinct advantages through its simplified library preparation protocol, flexible run capacities, and reduced computational requirements for base-calling compared to traditional high-throughput sequencers. These benefits enabled efficient processing of our large sample batches collected from distributed sites across the country, demonstrating a scalable approach for genomic surveillance that balances throughput needs with resource availability. This could inform future public health strategies, including vaccine updates and targeted interventions. Continued monitoring and adaptive strategies are essential to keep pace with the evolving viral ecology and to enhance preparedness for future outbreaks.

Since the emergence of COVID-19 pandemic in China in late 2019, scientists are striving hard to explore non-toxic, viable anti-SARS-CoV-2 compounds or medicines. We determined In vitro anti-SARS-CoV-2 activity of oral formulations (syrup and capsule)of an Iodine-complex (Renessans). First, cell cytotoxicity of Renessans on the Vero cells was determined using MTT assay. Afterwards, the antiviral activity of Renessans was determined using viral inhibition assays and TCID50. For this, nontoxic concentrations of the Renessans were used. The results showed that Renessans is nontoxic to the cells up to 50 µg/mL. At 1.5 µg/mL concentration, SARS-CoV-2 production was significantly reduced to 101.43 TCID50 and 101.58 TCID50 for the syrup and capsule, respectively, as compare to virus infected control cells 106.08 TCID50 and we found the dose dependent inhibition of virus replication in the presence of Renessans. Renessans inhibited SARS-CoV-2 with an EC50 value of 0.425 µg/mL and 0.505 µg/mL for syrup and capsule, respectively. Furthermore, there was no virus detected at concentration of 50 µg/mL of Renessans. This study indicates that Renessans, containing iodine, have potential activity against SARS-CoV-2 which needs to be further investigated in human clinical trials.