ISI Foundation

Abstract Biological and behavioral differences between genders influence infectious disease dynamics. Yet, most epidemiological models overlook these aspects in favor of age stratification alone. Here, we systematically evaluate the impact of incorporating gender-specific features into an age-structured epidemic compartmental model, calibrated to COVID-19 mortality data from the second wave in Italy (Autumn 2020–Winter 2021). We develop eight model versions representing different combinations of three data-driven features: gender-stratified contact matrices derived from CoMix data, gender-specific infection fatality ratios (IFR), and gender-dependent transmission rates linked to behavioral differences. We calibrate these models against aggregated mortality data and evaluate their performance on data disaggregated by gender, age, and both. Our results demonstrate that models incorporating gender-stratified contact patterns significantly outperform those relying solely on age, improving the accuracy of the fit even when analyzing age-disaggregated data alone. Furthermore, the inclusion of gender-specific IFR is essential for reproducing the empirically higher mortality rates observed in males. While phenomenological behavioral adjustments improve the fit for specific subgroups, such as older males, we observe trade-offs where maximizing performance for one demographic group occasionally reduces accuracy for another. Overall, our findings highlight that integrating gender data—particularly regarding contact patterns—is a critical step toward increasing the realism and precision of epidemiological models, even when outcome data is not fully disaggregated. Author summary Due to a combination of behavioral and biological factors, such as the adoption of protective measures and immune responses, infectious diseases affect men and women differently. However, the mathematical models used to understand and predict epidemics often overlook these aspects, focusing primarily on age. Here, we investigate whether explicitly including gender-specific data improves the accuracy of epidemic simulations. Using data from the second wave of the COVID-19 pandemic in Italy, we develop and compare several models that incorporated gender differences in social interaction patterns, biological risk of death, and protective behaviors. We find that men and women exhibit distinct social mixing patterns, and including this information is the most important factor for accurately reproducing the overall number of deaths. Additionally, accounting for the higher biological risk faced by males is essential for capturing gender-specific mortality trends. We also observe that because men had higher mortality rates, the models naturally prioritized fitting male data, sometimes at the expense of accuracy for females. Our work demonstrates that gender-agnostic models may miss crucial details. We conclude that incorporating gender-specific data is vital for creating more realistic models and designing inclusive public health policies that protect all demographic groups effectively.

Introduction: This study details the phased development and implementation of an Artificial Intelligence (AI)-driven nursing summary system designed to reduce nurses’ documentation workload. Methods: Over a 1-year development period beginning in December 2023, we constructed a system that automatically generates nursing care summaries from patient records to support care continuity. The system utilized large language models with prompt tuning techniques and a subjective, objective, assessment, plan (SOAP) format integration. Results: Through three iterations informed by clinical feedback, the system reduced the median summary creation time from 16 to 10 minutes (p < 0.001), representing an approximate 40% reduction. When validating the AI-generated nursing summaries, total scores for the five evaluation items in Versions 0.2 and 0.3 showed no significant difference. Discussion: This system produces comprehensive summaries that consider both nursing care plans and changes in patient condition, simultaneously improving efficiency and enhancing documentation quality. This study demonstrates the importance of iterative development and expert knowledge integration in implementing AI in clinical practice, offering valuable insights for advancing digital healthcare transformation. Conclusion: This study achieved an approximate 40% reduction in nursing record creation time and produced clinically acceptable summary documents through the phased development and implementation of an AI-driven nursing summary system. Keywords: patient discharge summaries, artificial intelligence, nursing, large language models, electronic health records

Background Digital participatory surveillance (DPS) may provide information on non-medically attended influenza-like illnesses (ILI). Combining DPS with laboratory testing allows pathogen identification. We assessed the feasibility of DPS and home-based swabbing in South Africa. Methods We enrolled a cohort of individuals aged ≥18 years who completed weekly respiratory symptoms questionnaires from March–October 2022. We calculated the percent of weekly DPS-reports consistent with ILI and COVID-19 syndromes and compared with weekly private respiratory consultations. Symptomatic participants in 3 provinces were offered self-administered nasal swabbing for influenza and SARS-CoV-2 detection by polymerase chain reaction (PCR). We assessed six feasibility indicators: recruitment capability, representativeness, reliability, accuracy, acceptability, and usefulness. Results Recruitment capability: 26% (249/954) of participants who accessed the platform enrolled and 92% (81/88) of participants eligible for self-swabbing were enrolled. Acceptability: 84% (210/249) of participants remained enrolled until the end of follow-up, 15% (32/249) completed the acceptability questionnaire with 100% (32/32) indicating willingness to participate in future studies, whereas 16% (39/210) withdrew from the study. Representativeness: 50% (125/249) were aged 18-39 years and 50% were older than 40 years (124/249), 71% (178/249) were female and 79% (196/249) had a tertiary qualification. Reliability: median weekly participation was 23% (interquartile range (IQR): 19%-29%) and 38% (80/210) submitted >1 weekly symptoms questionnaire. Accuracy: 2% (31/1440) and 25% (359/1440) of weekly questionnaires met ILI and COVID-19 case definitions, respectively. Influenza and SARS-CoV-2 were detected in 7% (6/81) and 32% (26/81) of tested samples, respectively. There was low correlation with respiratory consultations (0.08, 95% CI -0.27–0.43) for ILI and (0.36, 95% CI 0.11–0.62) COVID19. Usefulness: symptoms were reported in 32% (459/1440) of reports and 11% (49/459) sought medical care. Conclusion The study was feasible, however, the low enrolment numbers limit power. Linkage to self-swabbing was successful and demonstrates the potential for pathogen confirmation.

Abstract Access to cohort data is critical for reproducing studies, validating hypotheses in new settings and testing new approaches with past data in light of new findings. Nevertheless, previously collected data are often inaccessible due to confidentiality and privacy standards. In recent years, thanks to the development of AI, the field of synthetic data generation has emerged as a possible solution to facilitate cohort data sharing. However, synthetic data generation faces a tradeoff between statistical fidelity and information disclosure, which becomes even more restrictive for high dimensionality data.Here we assess the feasibility of employing state-of-the-art data synthesization and anonymization techniques to generate high-fidelity and privacy preserving synthetic datasets capable of meaningfully reproducing study results, thus benchmarking the potential of synthetic cohort data for public sharing.We design a protocol relying on four public packages, seven privacy metrics and five synthesization algorithms. We employ data collected within the framework of the Verdi project (Influweb) and publicly available hospitalisation cohort datasets (MIMIC-III) to assess privacy levels preserved by multiple data synthetization algorithms in three different studies. We employ multiple privacy metrics to ensure that statistical fidelity in our datasets do not come at the cost of information disclosure. Finally, we qualitatively compare the similarity of results reproduced with the synthetic datasets, noting that determinants of health-related behavior and in-hospital mortality remain largely unchanged with respect to estimates performed on the original data.Our findings show that synthetic data generation is a promising technique for public data sharing and study reproducibility. However, its broad application for new exploratory studies on complex or rare patterns may introduce limitations and biases, as fidelity of previously unobserved statistical relationships is not guaranteed.

The fall armyworm (Spodoptera frugiperda) is a major pest of several crops leading to significant yield losses. Developing effective and eco-friendly pest management strategies against fall armyworm (FAW) is crucial for sustainable agriculture. This study investigates the synthesis and evaluation of the insecticidal activity of silver nanoparticles based on an aqueous extract of Moringa oleifera leaves (MOL-AgNPs) against FAW. The synthesized MOL-AgNPs were characterized and confirmed using UV-Vis spectroscopy, Energy Dispersive X-ray Spectroscopy (EDX), Fourier Transform Infrared (FTIR), and Scanning Electron Microscopy (SEM) imaging. Four concentrations (200, 300, 400, and 500 ppm) of MOL-AgNPs and a deionized water as blank control were tested against larval mortality of the last three larval instars of FAW by food dipping method. Results showed different concentrations of MOL-AgNPs exhibited significantly higher larvicidal activity (p&lt;0.05). In the 4th instar, 67.5%, 82.5%, and 95% larval mortality were observed in MOL-AgNPs at 500 ppm after 24, 48, and 72 h of the larval exposure, respectively. Similarly in the 5th instar larvae, 72.5% (24 h), 83.75% (48 h), and 90% (72 h) mortality was observed after larval exposures to maximum concentration (500 ppm) of MOL-AgNPs. The 6th instar larvae showed 52.5% (24 h), 57.5% (48 h), and 85% (72 h) percentage mortality at 500 ppm. The MOL-AgNPs demonstrated high larvicidal activity which increased with the increase in concentrations of MOL-AgNPs and duration of exposure. The concentration levels with increased duration of exposure resulted in higher larval mortalities in all three larval instars. However, a more pronounced impact of larvicidal activity was observed on the 4th and 5th instars as compared to the 6th instar. The mortality rates recorded for both the concentration of the nanoparticles and the duration of exposure highlighted the potential of MOL-AgNPs as an eco-friendly and effective pest management strategy.

Abstract Background Transorbital neuroendoscopic (TONES) approaches have been described for resection of spheno-orbital, cavernous sinus, and Gasserian ganglion lesions. Lesions involving the petrous apex and cerebello-pontine angle (CPA) offer a formidable challenge via standard TONES approaches. This cadaveric study examined the surgical field-of-view and anatomic constraints provided by a novel extended transorbital neuroendoscopic (eTONES) approach and compared these to previously described TONES approaches and the traditional subtemporal anterior petrosectomy.Methods The eTONES approach includes single-piece removal of the superior and lateral orbital rims. This in turn offers expanded surgical trajectory to middle fossa skull base, anterior petrous ridge, and ventro-lateral posterior fossa, while reducing globe retraction. Four cadaveric heads underwent eTONES approach on one side and traditional subtemporal anterior petrosectomy on the contralateral side. Petrosectomy volume, location, and posterior fossa field-of-view were compared between the two approaches.Results Mean volume of petrous bone removed in the standard eTONES was 0.84 ± 0.38 ml. In comparison, the mean volume of petrous bone removed in the subtemporal approach was 0.72 ± 0.15 ml. On a single specimen, a superior eTONES variation was performed, tailored to provide access to the petrous apex and petroclival region, and 0.07ml of petrous bone was removed. Standard eTONES offered a straight on ventral-to-dorsal view of the internal acoustic canal and CPA contents. Conversely, traditional subtemporal approach, provided an unobstructed view of the medial CPA and petroclival region, with a lateral-to-medial viewing angle. Superior eTONES variation ‘bridges-the-gap’ between standard eTONES and subtemporal approaches in terms of petroclival and petrous apex exposure.Conclusion eTONES provides a straight on, minimally invasive endoscopic surgical approach that is comparable to the traditional subtemporal approach and may complement other surgical approaches for lesions involving the cavernous sinus, petroclival region, petrous ridge, and CPA. The describ1ed approach has yet to be examined in a clinical setting.

BackgroundHereditary hemochromatosis (HH) is an autosomal recessive disorder that leads to iron overload and multiorgan failure.ObjectivesThe aim of this systematic review was to provide up-to-date evidence of all the current data on the costs and cost effectiveness of screening and treatment for HH.MethodsWe searched PubMed, Cochrane Library, National Health Service Economic Evaluation Database (NHSEED), Cost-Effectiveness Analysis Registry (CEA Registry), Health Technology Assessment Database (HTAD), Centre for Reviews and Dissemination (CRD), and Econlit until April 2023 with no date restrictions. Articles that reported cost-utility, cost-description, cost-minimization, cost-effectiveness, or cost-benefit analyses for any kind of management (drugs, screening, etc.) were included in the study. Patients with HH, their siblings, or individuals suspected of having HH were included in the study. All screening and treatment strategies were included. Two authors assessed the quality of evidence related to screening (either phenotype or genotype screening) and treatment (phlebotomy and electrophoresis). Narrative synthesis was used to analyse the similarities and differences between the respective studies.ResultsThirty-nine papers were included in this study. The majority of the studies reported both the cost of phenotype screening, including transferrin saturation (TS), serum ferritin, and liver biopsy, and the cost of genotype screening (HFE screening, C282Y mutation). Few studies reported the cost for phlebotomy and erythrocytapheresis treatment. Data revealed that either phenotype or genotype screening were cost effective compared with no screening. Treatment studies concluded that erythrocytapheresis might be a cost-effective therapy compared with phlebotomy.ConclusionsEconomic studies on either the screening, or treatment strategy for HH patients should be performed in more countries. We suggest that cost-effectiveness studies on the role of deferasirox in HH should be carried out as an alternative therapy to phlebotomy.

Trachyspermum ammi is a frequently utilized traditional medicinal plant renowned for its pharmacological attributes, particularly in the realm of treating infectious diseases. This current study aims to comprehensively assess the in vitro properties of freshly prepared nanosuspensions derived from Trachyspermum ammi extracts, with a focus on their cost-effective potential in various areas, including antioxidant, antibacterial, cytotoxic, and antidiabetic activities. Biochemical characterization of T. ammi nanosuspensions by high-performance liquid chromatography (HPLC) and Fourier-transform infrared spectroscopy (FTIR) analyses. HPLC analysis revealed the presence of kaempferol and sinapic acid in various amounts at 11.5 ppm and 12.3 ppm, respectively. FTIR analysis of T. ammi powder revealed the presence of alcohols and amines. The assessment of antioxidant activity was conducted using a DPPH scavenging assay, indicating that the nanosuspensions exhibited their highest free radical scavenging activity, reaching 14.9%. Nanosuspensions showed 3.75 ± 3.529.5% biofilm inhibition activity against Escherichia coli. The antidiabetic activity was accessed through antiglycation and α- amylase inhibition assays, while nanosuspension showed the maximum inhibition activity at 25.35 ± 0.912133% and 34.6 ± 1.3675%. Hemolytic activity was also evaluated, and T. ammi nanosuspension showed 22.73 ± 1.539% hemolysis. This nanotechnology approach has established a foundation to produce plant-based nanosuspensions, offering a promising avenue for the biopharmaceutical production of herbal nanomedicines. These nanosuspensions have the potential to enhance bioavailability and can serve as a viable alternative to synthetic formulations.