Environmental footprints of the data center service sector in Sweden.

The global data center (DC) sector has expanded rapidly during the last decades, due to the rising demand for digital services. In the Nordic region, Sweden has emerged as a global hub, attracting leading technology companies like Amazon, Facebook, Microsoft, and Google. Server halls of DCs are energy intensive buildings, which puts pressure on local water resources and contributes to global greenhouse gas emissions. This study aims to, firstly, quantify the environmental impact of DCs, based on energy usage, water consumption, and greenhouse gas (GHG) emissions. Secondly, it develops a planning tool by employing a multi-criteria approach to optimally locate new DCs and to assess the site suitability of existing ones in Sweden. Data of various performance indicators (geographical data on renewable energy accessibility, free cooling conditions, excess heat receivers, and resilience to water shortages) of DCs was collected through different means, e.g., questionnaire surveys, permit applications, company websites, and other open online data repositories. ArcGIS Pro was employed for spatial analysis, and 68 DCs with a site suitability index (SSI) ≤ 45 % were identified as less ideally located. The principal findings are centered on Sweden, and thereby primarily benefit stakeholders engaged in decision-making for evaluating existing or strategic planning of new DCs by incorporating a comprehensive environmental perspective. Given the rapidly changing climate, strategically siting DCs will become crucial for minimizing the sector's environmental impact.

Effective Surgical Site Infection Prevention Strategies for Diabetic Patients Undergoing Surgery: A Systematic Review.

Surgical site infections (SSIs) pose a significant clinical challenge, with heightened risks and severe consequences for diabetic patients undergoing surgical procedures. This systematic review aims to synthesize the current evidence on effective prevention strategies for mitigating SSI risk in this vulnerable population. From inception to March 2024, we comprehensively searched multiple electronic databases (PubMed, Medline, Embase, Cochrane Library, CINAHL) to identify relevant studies evaluating SSI prevention strategies in diabetic surgical patients. Our search strategy followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, utilizing a combination of keywords and Medical Subject Headings (MeSH) terms related to diabetes, surgical site infections, prevention strategies, and surgical procedures. Inclusion criteria focused on peer-reviewed clinical trials, randomized controlled trials, and meta-analyses published in English. The search yielded three studies meeting the eligibility criteria, subject to data extraction and qualitative synthesis. Key findings highlighted the efficacy of interventions such as optimized perioperative glycemic control, timely prophylactic antibiotic administration, and meticulous preoperative skin antisepsis in reducing SSI rates among diabetic surgical patients. The potential for personalized prevention approaches based on individual patient factors, such as diabetes type and surgical complexity, was explored. This systematic review underscores the importance of a multifaceted, evidence-based approach to SSI prevention in diabetic surgical patients, integrating strategies like glycemic control, antibiotic prophylaxis, and preoperative skin antisepsis. Furthermore, our findings suggest the potential benefits of personalized care pathways tailored to individual patient characteristics. Implementing these interventions requires interdisciplinary collaboration, adaptation to diverse healthcare settings, and patient engagement through culturally sensitive education initiatives. This comprehensive analysis informs clinical practice, fosters patient safety, and contributes to the global efforts to enhance surgical outcomes for this high-risk population.

Hypoglycemic, anti-inflammatory, and neuroprotective potentials of crude methanolic extract from Acacia nilotica L. - results of an in vitro study.

Acacia nilotica L., also known as babul, belonging to the Fabaceae family and the Acacia genus, is typically used for ornamental purposes and also as a medicinal plant found in tropical and subtropical areas. This plant is a rich source of bioactive compounds. The current study aimed to elucidate the hypoglycemic, anti-inflammatory, and neuroprotective potential of A. nilotica's crude methanolic extract. The results of the in vitro antidiabetic assay revealed that methanolic extract of A. nilotica inhibited the enzyme α-glucosidase (IC50: 33 µg mL-1) and α-amylase (IC50: 17 µg mL-1) in a dose-dependent manner. While in the anticholinesterase enzyme inhibitory assay, maximum inhibition was shown by the extract against acetylcholinesterase (AChE) (637.01 µg mL-1) and butyrylcholinesterase (BChE) (491.98 µg mL-1), with the highest percent inhibition of 67.54% and 71.50% at 1000 µg mL-1, respectively. This inhibitory potential was lower as compared to the standard drug Galantamine that exhibited 82.43 and 89.50% inhibition at the same concentration, respectively. Moreover, the methanolic extract of A. nilotica also significantly inhibited the activities of cyclooxygenase 2 (COX-2) and 5-lipoxygenase (5-LOX) in a concentration-dependent manner. The percent inhibitory activity of 5-LOX and COX-2 ranged from 42.47% to 71.53% and 43.48% to 75.22%, respectively. Furthermore, in silico, in vivo, and clinical investigations must be planned to validate the above-stated bioactivities of A. nilotica.

Long-term Risk of Stroke After New-Onset Atrial Fibrillation in Sepsis Survivors: A 2-Year Follow-Up Study.

BACKGROUND: Cardiovascular complications such as new-onset atrial fibrillation (NOAF) are common in sepsis and are known to increase the risk of in-hospital mortality and stroke. However, only a handful of studies have evaluated the long-term risk of stroke after NOAF in sepsis survivors. As part of our efforts to address this issue, we conducted the first-ever follow-up study in a developing country evaluating the long-term risk of stroke for sepsis survivors following NOAF. Methods: This retrospective study evaluated all adult patients admitted at the Aga Khan University Hospital between July 2019 and December 2019 with the diagnosis of sepsis. Data was collected from medical records of the included patients. Outcome measures included in-hospital mortality and ischemic stroke within 2 years. Results: Seven hundred thirty patients were included in the study; 415 (57%) were males and 315 (43%) females; mean age was 59.4 ± 18 years. 59 (8%) patients developed NOAF. The risk of stroke within 2 years in sepsis survivors was 3.5%. Six out of 30 (20%) patients in the atrial fibrillation (AF) group developed stroke, whereas 11 out of 448 (2%) patients in the non-AF group developed stroke. NOAF was associated with an increased risk of ischemic stroke within 2 years (OR = 6.6; 95% CI, 2.3-12.8; P = <.001). Conclusion: We conclude that AF occurred frequently in sepsis patients and was also associated with a 6-fold increase in the risk of ischemic stroke within 2 years. Reliable interventions for identifying high-risk patients for ischemic stroke are still poorly characterized, and this study may serve as a basis for more extensive multicenter studies to identify patients at high risk for ischemic stroke in the aftermath of septic AF and develop precise interventions for preventing it.

Significance of serum ferritin and De Ritis ratio in non-alcoholic fatty liver disease as diagnostic markers.

Objectives: To ascertain the significance of serum ferritin and De Ritis ratio as diagnostic markers in patients of nonalcoholic fatty liver disease with and without type 2 diabetes mellitus. METHODS: The comparative cross-sectional study was conducted from February to October 2022 at the Radiology Department of Combined Military Hospital, Rawalpindi, Pakistan, and comprised individuals aged 30-65 who were divided into 3 groups. Healthy controls formed group I, non-alcoholic fatty liver disease patients without type 2 diabetes mellitus formed group II and non-alcoholic fatty liver disease patients with type 2 diabetes mellitus were in group III. Blood 5ml was withdrawn and assessed for alkaline phosphatase, aspartate transaminase, alanine transaminase and ferritin. De Ritis ratio was calculated and subjected to intergroup comparison. Data was analysed using SPSS 22. RESULTS: Of the 210 subjects, 110(52.4%) were males and 100(47.6%) were females, with 70(33.3%) in each of the three groups. Group I had 38(54.3%) females and 32(45.7%) males with mean age 37.50±4.513. In group II, there were 27(38.6%) females and 43(61.4%) males with mean age 45.86±9.646, while in group III there were 35(50%) females and 35(50%) males with mean age 54.01±9.243 years. Serum ferritin levels were significantly increased in patient groups II and III compared to control group I (p<0.05). De Ritis ratio was markedly raised in groups II and III compared to group I (p<0.05). Ferritin was significantly correlated to age, weight, height, fasting blood glucose, haemoglobin, alkaline phosphatase, aspartate aminotransferase, alanine transaminase and bilirubin (p<0.05). De Ritis ratio had a significant correlation with body mass index and fasting blood glucose (p<0.05). CONCLUSIONS: Serum ferritin and De Ritis ratio were found to be useful diagnostic indicators for non-alcoholic fatty liver disease, highlighting their importance in improving disease screening.

A comprehensive exploration of artificial intelligence in orthopaedics within lower-middle-income countries: a narrative review.

Integrating Artificial Intelligence (AI) in orthopaedic within lower-middle-income countries (LMICs) promises landmark improvement in patient care. Delving into specific use cases-fracture detection, spine imaging, bone tumour classification, and joint surgery optimisation-the review illuminates the areas where AI can significantly enhance orthopaedic practices. AI could play a pivotal role in improving diagnoses, enabling early detection, and ultimately enhancing patient outcomes- crucial in regions with constrained healthcare services. Challenges to the integration of AI include financial constraints, shortage of skilled professionals, data limitations, and cultural and ethical considerations. Emphasising AI's collaborative role, it can act as a complementary tool working in tandem with physicians, aiming to address gaps in healthcare access and education. We need continued research and a conscientious approach, envisioning AI as a catalyst for equitable, efficient, and accessible orthopaedic healthcare for patients in LMICs.

Anti-Diabetic, Anti-Cholinesterase, and Anti-Inflammatory Potential of Plant Derived Extracts and Column Semi-Purified Fractions of Ficus benghalensis.

BACKGROUND: The present study aimed to investigate the in-vitro anti-diabetic, anti-cholinesterase, and anti-inflammatory potential of extracts from different parts of Ficus benghalensis, including leaves, stem, and roots, as well as isolated column fractions (F-B-1 C, F-B-2 C, F-B-3 C, and F-B-4 C). METHODS: The extracts and subsequent fractions were evaluated for their inhibitory activity against key enzymes involved in diabetes [α-glucosidase and α-amylase], neurodegenerative diseases [acetylcholinesterase and butyrylcholinesterase], and inflammation (cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX)). RESULTS: The results showed that F. benghalensis leaf extract exhibited the highest α-glucosidase inhibitory activity (73.84%) and α-amylase inhibitory activity (76.29%) at 1000 µg/mL. The stem extract (65.50%) and F-B-2 C fraction (69.67%) also demonstrated significant α-glucosidase inhibitory activity. In terms of anti-cholinesterase activity, the extracts of roots, leaves, and stem showed promising inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), with half maximal inhibitory concentration (IC50) values ranging from 50.50 to 474.83 µg/mL. The derived fractions (F-B-1 C, F-B-2 C, F-B-3 C, and F-B-4 C) also exhibited notable inhibition of AChE and BChE, with IC50 values from 91.85 to 337.94 µg/mL. Moreover, the F-B-3 C fraction demonstrated the highest COX-2 inhibitory potential (85.72%), followed by F-B-1 C (83.13%), the stem extract (80.85%), and the leaves extract (79.00%). The F-B-1 C fraction showed the highest 5-LOX inhibitory activity (87.63%), while the root extract exhibited the lowest inhibition (73.39%). CONCLUSIONS: The results demonstrated promising bioactivity, suggesting the potential of F. benghalensis as a source of natural compounds with therapeutic applications. Further studies are required to identify and isolate the active components responsible for these effects and to evaluate their in-vivo efficacy and safety.

Strengthening neurosurgical training programs in Sub-saharan Africa: a medical student's perspective.

This article provides a nuanced exploration of the state and exigencies of neurosurgical training in sub-Saharan Africa (SSA), viewed through the discerning lens of a medical student. The region has a pronounced scarcity of neurosurgical services, further compounded by sociocultural intricacies and infrastructural inadequacies, resulting in elevated mortality and morbidity rates. The insufficiency of neurosurgeons, facilities, and training centers, particularly in remote areas, exacerbates this predicament. The imperative to fortify neurosurgical training programs is underscored, necessitating a multifaceted approach inclusive of international collaborations and innovative strategies. The challenges impeding neurosurgical training program implementation range from constrained infrastructure to faculty shortages and financial constraints. Recommendations encompass infrastructural investments, faculty development initiatives, and augmented community engagement. An exploration of neurosurgical training programs across diverse African regions reveals commendable strides and imminent deficits, warranting heightened international collaboration. Furthermore, technological innovations, including virtual reality, robotics, and artificial intelligence, are posited as transformative conduits for augmenting neurosurgical training in SSA. The article concludes with a sagacious compendium of recommendations, encompassing standardized curricula, mentorship paradigms, and stringent evaluation mechanisms, all combining efficaciously fortifying neurosurgical insight in SSA and producing transformative improvements in healthcare outcomes.

CAPTURE: Comprehensive anti-cancer peptide predictor with a unique amino acid sequence encoder.

Anticancer peptides (ACPs) key properties including bioactivity, high efficacy, low toxicity, and lack of drug resistance make them ideal candidates for cancer therapies. To deeply explore the potential of ACPs and accelerate development of cancer therapies, although 53 Artificial Intelligence supported computational predictors have been developed for ACPs and non ACPs classification but only one predictor has been developed for ACPs functional types annotations. Moreover, these predictors extract amino acids distribution patterns to transform peptides sequences into statistical vectors that are further fed to classifiers for discriminating peptides sequences and annotating peptides functional classes. Overall, these predictors remain fail in extracting diverse types of amino acids distribution patterns from peptide sequences. The paper in hand presents a unique CARE encoder that transforms peptides sequences into statistical vectors by extracting 4 different types of distribution patterns including correlation, distribution, composition, and transition. Across public benchmark dataset, proposed encoder potential is explored under two different evaluation settings namely; intrinsic and extrinsic. Extrinsic evaluation indicates that 12 different machine learning classifiers achieve superior performance with the proposed encoder as compared to 55 existing encoders. Furthermore, an intrinsic evaluation reveals that, unlike existing encoders, the proposed encoder generates more discriminative clusters for ACPs and non-ACPs classes. Across 8 public benchmark ACPs and non-ACPs classification datasets, proposed encoder and Adaboost classifier based CAPTURE predictor outperforms existing predictors with an average accuracy, recall and MCC score of 1%, 4%, and 2% respectively. In generalizeability evaluation case study, across 7 benchmark anti-microbial peptides classification datasets, CAPTURE surpasses existing predictors by an average AU-ROC of 2%. CAPTURE predictive pipeline along with label powerset method outperforms state-of-the-art ACPs functional types predictor by 5%, 5%, 5%, 6%, and 3% in terms of average accuracy, subset accuracy, precision, recall, and F1 respectively. CAPTURE web application is available at https://sds_genetic_analysis.opendfki.de/CAPTURE.

Prevalence, predictors, and consequences of workplace violence among female healthcare workers in tertiary care hospitals: A cross-sectional study in Pakistan.

OBJECTIVE: To determine the prevalence, predictors and perpetrators of violence, and its impact on the mental health of female healthcare workers. METHODS: The cross-sectional study was conducted from June to October 2022 at three tertiary care hospitals after approval from the ethics review board of Rawalpindi Medical University, Rawalpindi, Pakistan, and comprised female healthcare workers, including doctors, nurses and paramedical staff. Data was collected regarding workplace violence using a structured questionnaire adopted from literature. The incidence of verbal, physical and sexual violence in the preceding 12 months was noted, and predictors were analysed. Data was analysed using SPSS 25. RESULTS: Of the 140 subjects with an age range of 16-60 years, verbal violence was experienced by 102(72.9%) and physical violence by 26(18.6%), while verbal and physical forms of sexual violence were reported by 33(23.6%) and 13(9.3%), respectively. Those in the Medicine department had significantly lower odds of experiencing verbal violence compared to those from the Surgery department (adjusted odds ratio=0.223; 95% confidence interval: 0.078-0.036; p=0.005). Those in the Emergency department had significantly greater odds of experiencing physical violence compared to those in Surgery (adjusted odds ratio=8.716; 95% confidence interval: 1.693-44.87; p=0.01). Violence had a significant detrimental impact on the mental health of female healthcare workers (p<0.05). CONCLUSIONS: Violence was found to be prevalent in the healthcare sector, specifically in stressful and critical-care departments, like Emergency and Surgery.

The Potential of Fecal and Urinary Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: A Systematic Review.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer often diagnosed at advanced stages, highlighting the urgent need for early detection strategies. This systematic review explores the potential of fecal and urinary biomarkers for early PDAC detection. A comprehensive search identified eight relevant studies investigating various biomarkers, including proteins, metabolites, microbial profiles, DNA mutations, and non-coding RNAs. Promising findings suggest that urinary biomarkers related to metabolic alterations, inflammatory processes, fecal microbiome profiles, and fecal miRNAs hold diagnostic potential even at early stages of PDAC. Combining biomarkers into panels may enhance diagnostic accuracy. Challenges such as validation in larger cohorts, standardization of protocols, and regulatory approval must be addressed for clinical translation. Despite these hurdles, non-invasive urinary and fecal biomarkers represent a promising avenue for improving PDAC outcomes through early detection.

Language-adaptive artificial intelligence: assessing CHATGPT'S answer to frequently asked questions on total hip arthroplasty questions.

ChatGPT is reported to be an acceptable tool to answer a majority of frequently asked patient questions. ChatGPT also converses in other languages including Urdu, which offers immense potential for the education of Pakistani patients. Therefore, this study evaluated ChatGPT's Urdu answers to the ten most frequently asked questions on Total Hip Arthroplasty, which were then rated by an expert. Out of 10 answers in English, 9 (90%) were satisfactory requiring minimal clarification and 1 (10%) was satisfactory requiring moderate clarification. In both Roman and Nastaliq script Urdu, 1 (10%) answer was satisfactory requiring moderate clarification, while 9 (90%) were unsatisfactory requiring substantial clarification. In conclusion, as opposed to ChatGPT English responses, Urdu responses were much less rigorous, generic, and lacked scientific rigor. We have a long way to go before Pakistani patients with limited English language skills could benefit from AI chatbots like ChatGPT.

Early detection of deep-seated smouldering fires in wood waste storage using ERT.

Incidents of waste and biofuel fires are common at all stages of the waste recycling chain and have grave implications for business, employees, firefighters, society, and environment. An early detection of waste and biofuel fires in the smouldering stage could save precious lives, resources, and our environment. Existing fire detection methodologies e.g. handheld temperature sensors, IR cameras, gas sensors, and video and satellite-based monitoring techniques have inherent limitations to efficiently detect smouldering fires. An attempt was made to explore the potential of electrical resistivity tomography (ERT) as an alternate tool to address the problem. In the experiments an externally powered resistive wire was employed to initiate the smouldering fire inside the test material (wood pellets, wood shavings, wood fines). Time series of ERT that followed the initiation and development of smouldering were recorded using an automated monitoring instrument setup. The actual geometry of the experimental sample container and electrode setup was integrated in the 3D finite element method (FEM) model grid to perform inverse numerical modelling (inversion) and to develop resistivity tomographic images. The study shows a sharp increase in ratio of resistivity (R/Ro ≥ 50 %) in the test material in the region of smouldering hotspot and demonstrates the potential use of ERT technique for the detection of smouldering hotspots in silos and pile storage of organic material such as wood-based fuels, wood waste, coal, municipal solid waste (MSW), recyclables etc. More research is however required for enabling the use of this technique at the practical scale for different storage conditions.

Pattern and Management of Missile Injury to the Oral and Maxillofacial Region: A 12-Year Experience During Boko Haram Insurgency in Maiduguri, North-Eastern Nigeria.

Introduction: Missile injury is a global public health problem, which occurs in both military and civilian settings. Boko Haram insurgency in North-Eastern Nigeria is one of the major violence the country experienced that resulted in many civilian casualties. This study was aimed at exploring the various patterns of the missile injuries to the maxillofacial region during Boko Haram insurgency. Methods: In this retrospective cross-sectional study, relevant information was retrieved from patient records including sociodemographic, causes of missile injuries, site of injuries, pattern of presentation, treatment, and the complications, and analysed using SPSS version 23. Result: A total of 526 patients with various maxillofacial injuries were seen during this 12-year study period, with age ranging from 4 to 65 years, the peak incidence in the age group 31-40 years, 89.5% were males, 92.9% of the injuries were allegedly inflicted by insurgents and comprised of 61.0% gunshot injuries, 24.5% bomb blast, and machete cuts 7.4%. Most of the injuries occurred in the lower third of the face, 39.8%, and mandible was the commonest fractured facial bone. Conclusion: Facial injuries commonly are associated with devastating consequences to survivors and, hence, may require long time monitoring and psychosocial rehabilitations.

Esophageal leiomyoma within an epinephric diverticulum.

Epinephric diverticula are distal esophageal pouches protruding from the epithelial lining of the esophagus while esophageal leiomyomas are benign smooth muscle lesions that constitute a significant percentage of all gastrointestinal leiomyomas. Epinephric diverticula and esophageal leiomyomas are common individually but their co-existence is rare. Moreover, they present asymptomatically but can occasionally present with complains of dysphagia and weight loss. In this paper, we present a 58-year-old Asian man with three months history of indigestion and progressive weight loss. Preoperatively, CT Scan with IV Contrast showed a large soft tissue mass appearing on the right distal esophageal wall, with its lumen communicating with the esophageal lumen, likely representing an epinephric diverticulum. Biopsy and immunohistochemistry stains confirmed the diagnosis of smooth muscle neoplasm, likely a leiomyoma. Later, the patient underwent a two-stage esophagectomy. The postoperative biopsy was consistent with the initial one: therefore, supporting the diagnosis of a leiomyoma. Postoperatively, the recovery remained uneventful.

Real-Time Seamless Multi-Projector Displays on Deformable Surfaces.

Prior works on multi-projector displays have focused primarily on static rigid objects, some focusing on dynamic rigid objects. However, works on projection based displays on deformable dynamic objects have focused only on small scale single projector displays. Tracking a deformable dynamic surface and updating projections precisely in real time on it is a significantly challenging task, even for a single projector system. In this paper, we present the first end-to-end solution for achieving a real-time, seamless display on deformable surfaces using mutliple unsychronized projectors without requiring any prior knowledge of the surface or device parameters. The system first accurately calibrates multiple RGB-D cameras and projectors using the deformable display surface itself, and then using those calibrated devices, tracks the continuous changes in the surface shape. Based on the deformation and projector calibration, the system warps and blends the image content in real-time to create a seamless display on a surface that continuously changes shape. Using multiple projectors and RGB-D cameras, we provide the much desired aspect of scale to the displays on deformable surfaces. Most prior dynamic multi-projector systems assume rigid objects and depend critically on the constancy of surface normals and non-existence of local shape deformations. These assumptions break in deformable surfaces making prior techniques inapplicable. Point-based correspondences become inadequate for calibration, exacerbated with no synchronization between the projectors. A few works address non-rigid objects with several restrictions like targeting semi-deformable surfaces (e.g. human face), or using single coaxial (optically aligned) projector-camera pairs, or temporally synchronized cameras. We break loose from such restrictions and handle multiple projector systems for dynamic deformable fabric-like objects using temporally unsynchronized devices. We devise novel methods using ray and plane-based constraints imposed by the pinhole camera model to address these issues and design new blending methods dependent on 3D distances suitable for deformable surfaces. Finally, unlike all prior work with rigid dynamic surfaces that use a single RGB-D camera, we devise a method that involve all RGB-D cameras for tracking since the surface is not seen completely by a single camera. These methods enable a seamless display at scale in the presence of continuous movements and deformations. This work has tremendous applications on mobile and expeditionary systems where environmentals (e.g. wind, vibrations, suction) cannot be avoided. One can create large displays on tent walls in remote, austere military or emergency operations in minutes to support large scale command and control, mission rehearsal or training operations. It can be used to create displays on mobile and inflatable objects for tradeshows/events and touring edutainment applications.

Ligand based-design of potential schistosomiasis inhibitors through QSAR, homology modeling, molecular dynamics, pharmacokinetics, and DFT studies.

Objectives: Schistosomiasis, a neglected tropical disease, is a leading cause of mortality in affected geographic areas. Currently, because no vaccine for schistosomiasis is available, control measures rely on widespread administration of the drug praziquantel (PZQ). The mass administration of PZQ has prompted concerns regarding the emergence of drug resistance. Therefore, new therapeutic targets and potential compounds are necessary to combat schistosomiasis. Methods: Twenty-four potent derivatives of PZQ were optimized via density functional theory (DFT) at the B3LYP/6-31G∗ level. Quantitative structureactivity relationship (QSAR) models were generated and statistically validated, and a lead candidate was selected to develop therapeutic options with improved efficacy against schistosomiasis. The biological and binding energies of the designed compounds were evaluated. In addition, molecular dynamics; drug-likeness; absorption, distribution, metabolism, excretion, and toxicity (ADMET); and DFT studies were performed on the newly designed compounds. Results: Five QSAR models were generated, among which model 1 had favorable validation parameters (R2train: 0.957, R2adj: 0.941, LOF: 0.101, Q2cv: 0.906, and R2test: 0.783) and was chosen to identify a lead candidate. Other statistical parameters for the chosen model included variance inflation factor values ranging from 1.242 to 1.678, and a Y-scrambling coefficient (cRp2) of 0.747. Five new compounds were designed with improved predicted activity (ranging from 5.081 to 7.022) surpassing those of both the lead compound and PZQ (predicted pEC50 of 5.545). Molecular dynamics simulation revealed high binding affinity of the proposed compounds toward the target receptor. ADMET and drug-likeness assessments indicated adherence to Lipinski's rule of five criteria, thereby suggesting pharmacological and oral safety. In addition, DFT analysis indicated resistance to electronic alteration during chemical reactions. Conclusion: The proposed compounds exhibited potential drug characteristics, thus indicating their suitability for further investigation to enhance schistosomiasis treatment options.

Optimizing immunization services: A Data Envelopment Analysis (DEA) of child immunization facilities in Pakistan.

INTRODUCTION: Child immunization, though cost-beneficial, experiences varying costs influenced by individual facility-level factors. A real-time solution is to optimize resources and enhance vaccination services through proper method to measure immunization facility efficiency using existing data. Additionally, examine the impact of COVID-19 on facility efficiency, with the primary goal of comprehensively assessing child immunization facility efficiency in Pakistan. METHODS: Utilizing survey data collected in four rounds from May 2018 to December 2020, the research focuses on doses administered and stock records for the preceding six months in each phase. In the initial stage, Data Envelopment Analysis (DEA) is utilized to compute facility efficiency, employing two models with varied outputs while maintaining consistent inputs. Model 1 assesses doses administered, encompassing three outputs (pentavalent vaccine 1, 2, and 3). Meanwhile, Model 2, focuses on stock used featuring a single output (total doses used). The inputs considered in both models include stock availability, staff members, cold chain equipment, vaccine carriers, and vaccine sessions. The second stage involves the application of two competing regression specifications (Tobit and Simar-Wilson) to explore the impact of the COVID-19 pandemic and external factors on the efficiency of these facilities. RESULTS: In 12 districts across Punjab and Sindh, we assess 466 facilities in Model 1 and 455 in Model 2. Model 1 shows 59% efficiency, and Model 2 shows 70%, indicating excess stock. Stock of vaccines need to be reduced by from 36% to 43%. In the stage, COVID-19 period reduced efficiency in Model 1 by 10%, however, insignificant in Model 2. CONCLUSIONS: The proposed methodology, utilizing DEA, emerges as a valuable tool for immunization facilities seeking to improve resource utilization and overall efficiency. Model 1, focusing on doses administered indicates facilities low efficiency at average 59% and proves more pertinent for efficiency analysis as it directly correlates with the number of children vaccinated. The prevalent issue of overstocking across all facilities significantly impacts efficiency. This study underscores the critical importance of optimizing resources through the redistribution of excess stock with low efficiency.