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Protocol for evaluating the cost-effectiveness of Mongolia’s sugar-sweetened beverages tax using double machine learning
Elevated consumption of sugar-sweetened beverages (SSBs) has been associated with an increase in obesity, type 2 diabetes, and other non-communicable diseases (NCDs), a significant health and economic burden on Mongolia. To address this, the government has introduced a 20% SSB tax set to take effect in 2027. This study conducts a Cost-Effectiveness Analysis (CEA) using a Markov cohort model, incorporating Double Machine Learning (DML) to estimate price elasticity and assess policy-driven consumption changes while addressing potential confounding. The analysis integrates DML-estimated price elasticity and consumption shifts with disease transition probabilities, simulating outcomes for the 2023 Mongolian population, aged over 15 years old, over two time horizons of 20 years and a lifetime. The model estimates changes in obesity prevalence, healthcare costs, and disease burden, translating them into Disability-Adjusted Life Years (DALYs) averted, and Quality-Adjusted Life Years (QALYs) gained. Tax revenue projections and sensitivity analyses further assess the robustness of assumptions. By combining machine learning-based causal inference with economic modelling, this study provides policy-relevant evidence on the cost-effectiveness of SSB taxation, supporting data-driven decision-making for public health strategies in Mongolia, highlighting the tax’s potential to reduce the burden of NCDs and promote healthier behaviours.
Innovative data techniques for centrifugal pump optimization with machine learning and AI model
In modern centrifugal pump machines (CPM), a data acquisition system encompassing software- hardware interfacing is essential for parameter recording. The quality of recorded data plays a crucial role and directly influences the data transformation phase in machine learning (ML) and deep learning (DL) models. The Dewesoft FFT DAQ system is designed to extract the high-quality data from the CPM based on sensor fusion technology. The data recorded from DAQ system undergoes thorough in-depth analysis, processing & transformation before being incorporated into machine learning (ML) or artificial intelligence models. This paper emphasizes the importance of data cleaning, pre-processing, and applying appropriate methodologies to transform raw data into a valuable resource that can be utilized by ML and AI models. Key techniques include Exploratory Data Analysis (EDA), Data Visualization, and Feature Engineering (FE), which collectively enhance data interpretability. Following these transformations, hypothesis testing validates the data’s integrity, ensuring reliability for subsequent modeling. The validated data is employed to train machine learning classifiers and deep learning algorithms, targeting a 27.25% enhancement in operational efficiency based on F1 score. Additionally, it decreases model training time by 180 seconds, facilitating predictive maintenance of critical performance metrics and minimizing downtime. The assessment of model performance relies on Precision, Recall, and F1 score. This approach leverages recent advancements in data science to derive actionable insights from CPM data, facilitating more informed decision-making and optimization of pump operations.
Multiscale computational evaluation of Vitex trifolia phytochemicals as VEGFR2 inhibitors for targeted breast cancer therapy
Breast cancer (BC), the second most common cancer, is a genetically heterogeneous disease driven by angiogenesis, cell growth, metastasis, and oxidative stress. VEGFR2, a key angiogenesis regulator, presents a potential target for inhibiting the angiogenic process essential for tumor growth. The present study aimed to investigate the therapeutic potential of phytochemicals of Vitex trifolia to inhibit VEGFR2 for BC. The current study employed extensively in silico-based computational tools to assess the binding affinity and interactions through docking and validating through simulations, along with evaluating the molecular characteristics of the phytochemicals of Vitex trifolia. The docking results revealed that VT-6 (cynaroside) showed the highest docking score (−14.611 kcal/mol), followed by VT-10 (−13.641 kcal/mol) against the VEGFR2 protein. Significant stable interactions were formed by the key interacting residues of the binding pocket (GLU917, ASP1046, LYS868, CYS919, and GLU885), also highlighted through the SIFT analysis. Additionally, the density functional theory (DFT) analysis demonstrated balanced electrophilic and nucleophilic electronic distribution and reactivity for VT-6. The simulations further validated the stability of VT-6 within the binding cavity of VEGFR2, exhibiting flexibility within a range of <3Å and stable conformational changes. Moreover, the MM/GBSA calculations also signify that VT-6 exhibited stronger binding affinity with more negative free energies (−32.5 kcal/mol MM/PBSA, −34.7 kcal/mol MM/GBSA). Notably, principal component analysis (PCA) and free energy landscape (FEL) indicated that the VT-6 complex remained compact during 200 ns simulations. Conclusively, these findings underscore VT-6 as a potent VEGFR2 inhibitor against BC. However, optimizing the ADMET profile through structural modifications and nanocarrier delivery, along with in vivo and in vitro experimental validation, will enhance its therapeutic potential.
Fake news, misinformation, vaccine hesitancy and the role of community engagement in COVID-19 vaccine acceptance in Southern Ghana
Introduction The novel coronavirus (COVID-19) is characterised by loads of fake news and misinformation, which can influence vaccine acceptance. Implementing a harmonized public health strategy during an outbreak necessitates effective community engagement and communication, which facilitates public trust and decision-making. This study explored the role of community engagement in the acceptance of COVID-19 vaccine amid fake news and misinformation in two municipalities in Ghana. Method A case study design was employed using in-depth interviews with government officials from the Ghana Health Service, Municipal Assembly, Information Services Department and the National Commission on Civic Education and community gatekeepers. Additionally, focus group discussions were conducted with a cross-section of women, men and migrants’ community members to understand the role of community engagement in vaccine acceptance. Qualitative analysis software Nvivo 12 was used to support thematic coding and analysis. All ethical procedures and COVID-19 preventive protocols were observed. Results Study participants reported the sources of fake news and misinformation about the COVID-19 vaccines from interpersonal communication, the radio, and a popular anti-vaccine song. Some of the factors contributing to vaccine hesitancy were community members believed in the fake news and misinformation, low trust in the government and public institutions, and the lack of extensive education on COVID-19 vaccines. The Ghana Health Service was the most successful in engaging communities to promote vaccine acceptance amid fake news and misinformation. It leveraged on its existing community-based health planning and services (CHPS) programme, which engaged the communities frequently through routine programmes such as durbars, antenatal clinics, child welfare clinics, and other community programmes to carry out engagement. Conclusion Misinformation and fake news about COVID-19 vaccines were widespread in the study communities, with significant implications for vaccine hesitancy. The sources of misinformation ranged from social media platforms and radio broadcasts to personal interactions within communities. While government efforts at community engagement were noted, these efforts were often inadequate to counteract the deeply ingrained fears and misconceptions.
The oldest Pottery Neolithic (PN) culture of northeastern Iran: First absolute dating from eastern Mazandaran plains
In the past, establishing a clear chronology for the Epipalaeolithic and Neolithic periods in eastern Mazandaran proved challenging. A major obstacle had been the lack of radiocarbon dating. Previous dates provided by Coon and McBurney were not considered reliable, even after recalibrations. However, over the last fifteen years, new archaeological fieldwork and research have significantly enhanced our understanding of these periods. Recent excavations at the PN sites of Touq Tappeh and Tappeh Valiki have provided new information about the Epipalaeolithic and Neolithic chronology and dating. The sites yielded the oldest dating of the PN in northeastern Iran so far, making the PN of eastern Mazandaran start at least from the first half of the 7th millennium BC and lasted until the early 6th millennium BC (c. 6600–5800 BC). While Tappeh Valiki represents the oldest dates, the PN periods may have started in the region even earlier, given the presence of potteries from the lowest layers of the site. Analysis of the available material from these sites through dating indicates strong regional connections, while also showing inter-regional connections. The new dating from the old and new Epipalaeolithic and Neolithic sites of eastern Mazandaran suggests there is no gap between them, which is not surprising given the favorable environment during the early Holocene.
Short Lifetime Radical Metal Cluster Scintillator
Abstract Metal clusters, an emerging class of scintillator materials, have attracted much attention owing to their inherently high X‐ray absorption, mild synthesis conditions, low toxicity, strong luminescence, and large Stokes shift. However, the decay lifetime of metal clusters is usually on the order of microseconds, which is unfavorable for safety inspection, nondestructive testing, and medical imaging. Here, the open‐shell luminescent radical ligand was used to construct the first radical cluster scintillator Cu 2 I 2 (L) 4 . The spin‐allowed doublet emission of Cu 2 I 2 (L) 4 theoretically enabled 100% exciton utilization and exhibited a short radiation decay lifetime on the nanosecond scale. Cu 2 I 2 (L) 4 can be fabricated into a flexible scintillator screen for X‐ray imaging, achieving a high resolution of 30.7 LP mm −1 . More importantly, the Cu 2 I 2 (L) 4 scintillator screen has no residual images during X‐ray imaging. This work reports the first luminescent metal cluster with a radical ligand and presents a new strategy for constructing short lifetime X‐ray scintillators.
Effect of intranasal administration of Erigeron annuus and Carthamus tinctorius extracts in a rat model of olfactory dysfunction induced by 3-methylindole
There are many factors that can cause olfactory dysfunction, including upper respiratory tract viral infections, non-inflammatory respiratory diseases, trauma, and current treatments such as medications and surgery can have adverse effects and may not respond. Therefore, we aimed to develop a natural product-based adjunctive treatment strategy for olfactory dysfunction that is safe and has minimal adverse effects. We investigated the effects of extracts from Erigeron annuus and Carthamus tinctorius, which have demonstrated anti-apoptotic, neuroprotective, and anti-inflammatory activities, on 3-methylindole-induced olfactory dysfunction. A 3-methylindole-induced olfactory dysfunction model rat was established and olfactory dysfunction was treated with intranasal administration of Erigeron annus extract (EAE) and Carthamus tinctorius extract (CTE) or their combination. After 3 weeks, alterations in food-finding tests and OMP expression in olfactory bulb and olfactory epithelium were assessed. Comparing the food finding test, the EAE + CTE group had a significant decrease in food finding time compared to the vehicle group. IHC and Western blot analyses showed that OMP expression in the olfactory bulb was significantly increased in the EAE + CTE group compared to the vehicle group. Western blot analysis of olfactory epithelial tissue also showed a significant increase in OMP expression. Intranasal administration of EAE + CTE alleviated 3-methylindole-induced olfactory dysfunction.
Stitching competition with digital threads: Unveiling the drivers of competitive success in the apparel sector
This study explores and validates the dimensions of digital capabilities and competitive performance within the apparel industry, aiming to develop a robust, multidimensional measurement instrument. Employing a sequential QUAL→QUAN exploratory design, the research began with in-depth interviews with key industry experts to identify critical constructs. These insights informed the subsequent quantitative phase, in which exploratory factor analysis and confirmatory factor analysis were applied to confirm the factor structure and validate the instrument. The study identifies four key dimensions of competitive performance in the apparel supply chain: customer satisfaction, better utilisation of resources, collaboration to compete, and strategic advantage. Process and technical digitalisation emerged as essential components of digital capabilities, reflecting the dual role of digital infrastructure and operational integration in enhancing performance. Theoretically, this research contributes by introducing validated instruments grounded in the Resource-based view, the Dynamic capabilities view, and the Extended resource-based view, offering an empirical framework that links digital capabilities with competitive performance. Practically, the instrument provides apparel manufacturers with a diagnostic tool to assess digital maturity and strategically align digital initiatives with performance goals. These findings are particularly relevant for firms navigating rapid technological change and seeking sustained global apparel supply chain competitiveness.
High‐Pressure Synthesis of Ultra‐Incompressible Beryllium Tungsten Nitride Pernitride BeW <sub>10</sub> N <sub>14</sub> (N <sub>2</sub> )
Abstract For the activation of nitrogen and its reduction to ammonia, transition metals are crucial in biological as well as industrial processes. So far, only a few binary transition metal compounds with nitrogen dimer anions are known, whereas a ternary compound has remained undiscovered as yet. Here, we report on the synthesis and properties of the first ternary transition metal compound, namely, BeW 10 N 14 (N 2 ), which exhibits dinitrogen anions. It was synthesized in a high‐temperature high‐pressure approach from W 2 Be 4 N 5 . The crystal structure, elucidated with synchrotron radiation, unites WN 7 capped trigonal prisms with intriguing BeN 6 octahedra and (N 2 )‐anions. Elastic and electronic properties of the title compound were corroborated by DFT calculations, revealing simultaneous ultra‐incompressible and metallic behavior. The synthesis and investigation of the first ternary transition metal nitride with dinitrogen units opens the door to a new field of research on nitride and pernitride chemistry.
Hospital volume and outcomes of surgical repair in type A acute aortic dissection: A nationwide cohort study
Background Over the last decade, the number of patients treated with open repair for TAAAD in Taiwan has dramatically increased. This study aims to assess the hospital-volume relationship with surgical outcomes of type A acute aortic dissection (TAAAD) across hospitals in Taiwan. Methods Using the Taiwan National Health Insurance (NHI) Research Database (NHIRD), we include only the patients who underwent first open repair for TAAAD from 01/01/2005, to 31/12/2020, in Taiwan. A total of 8,059 patients in 77 hospitals were eligible for the analysis. Hospitals were categorized based on their 16-year cumulative volume of TAAAD open repair surgeries, and patients were grouped into quartiles accordingly. Results Ascending aortic replacement (55.7%) and partial/total arch replacement (38.8%) were the most common methods of open aortic repair. In-hospital mortality was 22% and decreased from 28% in 2005 to 20% in 2020. Greater volume (per 5 annual surgeries) was associated with lower risks of in-hospital mortality (odd ratio 0.90, 95% confidence interval [CI] 0.87–0.92) and mortality after discharge (hazard ratio 0.97, 95% CI 0.95–0.99). Conclusion Operative volume inversely correlates to in-hospital mortality and postoperative complications. The volume-outcome effect extends after discharge and reflects better long-term survival. Hospital referral to high-volume centers should be considered in patients needing complex open repair for TAAAD.
Effect of calcium dobesilate on macular microvasculature in patients with diabetic retinopathy
Purpose To investigate the impact of calcium dobesilate (CaD) on the macular microvasculature in patients with diabetic retinopathy (DR) using optical coherence tomography angiography. Methods In this retrospective study, patients with DR were divided into two groups: those treated with 1 g/day of CaD (Group 1) and those without CaD treatment (Group 2). Following the baseline, patients underwent two additional examinations at 3-month intervals for analysis. The vessel density of the superficial vascular complex (SVD) and deep vascular complex (DVD) were compared against prior assessments. Generalized linear mixed models analyzed factors associated with changes in SVD and DVD over time. Results A total of 81 eyes were included: 39 in Group 1 and 42 in Group 2. The mean SVD was 21.8 ± 5.7% at baseline, 23.5 ± 6.5% at 3 months, and 23.3 ± 6.1% at 6 months in Group 1, respectively (P = 0.034), with significant changes observed from baseline to 3 months (P = 0.021), but not from 3 to 6 months (P = 0.745). The mean DVD was 18.2 ± 3.4% at baseline, 20.0 ± 3.9% at 3 months, and 19.9 ± 4.1% at 6 months in Group 1, respectively (P = 0.008), showing a significant increase from baseline to 3 months (P = 0.007), but not from 3 to 6 months (P = 0.825). Group 2 showed no significant changes over time in either SVD (P = 0.175) or DVD (P = 0.156). In Group 1, multivariate analysis identified DR severity as significantly associated with changes in SVD (estimate = 5.07, P = 0.016). Conclusions The administration of CaD positively influences macular microcirculation in DR patients, demonstrating its effectiveness even in advanced stages of the disease.
Additive effect of diabetes mellitus on the prevalence and prognosis of sarcopenic obesity: Implications for all-cause mortality
Diabetes mellitus (DM) and sarcopenic obesity are common conditions associated with increased morbidity and mortality. DM, characterized by chronic hyperglycemia, is a recognized risk factor for cardiovascular disease and premature death. Sarcopenic obesity, characterized by reduced muscle mass and increased adiposity, contributes to physical frailty and metabolic dysfunction. This study investigated the effect of DM on mortality rates and causes of death among individuals with high adiposity and low muscle mass (HA-LM) by using data from the National Health and Nutrition Examination Survey (NHANES) linked to mortality records from 2011 to 2018. A total of 2366 patients with HA-LM patients were analyzed, including 194 (8.199%) with DM and 2172 (91.80%) without DM. During the study period, the mortality rate was 1.19% in the HA-LM without DM group and 5.15% in the HA-LM with DM group. Kaplan-Meier survival analysis demonstrated a significantly higher mortality rate in the HA-LM patients with DM group, supported by both crude (hazard ratio [HR]: 4.34, 95% confidence interval [CI]: 2.09–9.00, p < 0.001) and adjusted (HR: 2.88, 95% CI: 1.23–6.73, p < 0.01) models. Cause-specific analysis revealed that heart disease (40%) was the leading cause of mortality in the HA-LM with DM group, followed by other residual causes (30%). By contrast, other residual causes were predominant among those without DM (34.62%), followed by malignant neoplasms (19.23%). These findings underscore the synergistic effects of DM and sarcopenic obesity on the risk of mortality and emphasize the need for targeted interventions aimed at managing diabetes and preserving muscle mass. The study findings may inform interventions aimed at improving health outcomes and reducing mortality in this high-risk population.
Self‐Optimized Reconstruction of Metal–Organic Frameworks Introduces Cation Vacancies for Selective Electrosynthesis of Hydrogen Peroxide
Abstract The electrocatalytic synthesis of hydrogen peroxide (H 2 O 2 ) through the two‐electron oxygen reduction pathway represents a green production process that has gained increasing importance. Nevertheless, there is a dearth of efficacious catalysts to attain high activity under industrial current density. In this study, we present a strategy for cation vacancy generation through metal–organic frameworks self‐optimized reconfiguration for the efficient electrosynthesis of H 2 O 2 under industrial current densities in solid‐electrolyte cell. The ZIF‐ZC91@Co(OH) 2 ‐V Co electrocatalyst exhibits significant H 2 O 2 selectivity of 97.8%, and the H 2 O 2 productivity is up to 24.53 mol g catalyst −1 h −1 with a direct and continuous output of ∼3.36 wt% H 2 O 2 aqueous solutions under industrial current density (400 mA cm −2 ). Impressively, the ZIF‐ZC91@Co(OH) 2 ‐V Co possesses superb long‐term durability for over 220 h and can output H 2 O 2 aqueous solution with a concentration of ∼8.03 wt% in the pilot experiment. Theoretical calculations confirm that the introduction of modest cation vacancies optimizes the adsorption strength of *OOH intermediate and reduces both thermodynamic and kinetic barriers, thus balancing the selectivity of the two‐electron oxygen reduction. This work provides valuable insights into the rapid, eco‐friendly synthesis of H 2 O 2 and the rational design of highly active catalysts.
Unsustainable anthropogenic mortality threatens the long-term viability of lion populations in Mozambique
Anthropogenic mortality is a pervasive threat to global biodiversity. African lions (Panthera leo) are particularly vulnerable to these threats due to their wide-ranging behaviour and substantial energetic requirements, which typically conflict with human activities, often resulting in population declines and even extirpations. Mozambique supports the 7th largest lion population in Africa, which is recovering from decades of warfare, while ongoing conflicts and broad-scale socio-economic fragility continue to threaten these populations. Moreover, there are concerns that Mozambique represents a regional hotspot for targeted poaching of lions which fuels a transnational illegal wildlife trade. This study aimed to quantify the longitudinal impact of anthropogenic mortality on lion populations in Mozambique. Using national population estimates and monitoring records, we performed forward simulation population viability modelling incorporating detection-dependent population trends and varying scales of anthropogenic mortality. Between 2010–2023, 326 incidents of anthropogenic mortality involving 426 lions were recorded. Bushmeat bycatch and targeted poaching for body parts were the greatest proximate causes of lion mortality (i.e., 53% of incidents), increasing significantly over time and acting as cryptic suppressors of regional population recovery, followed by legal trophy hunting (i.e., 33%), and retaliatory killing (i.e., 13%). Our findings suggest that resilience to anthropogenic threats is largely a function of lion population size as well as resource and management capacity. For instance, projections suggest that the lion population in Niassa Special Reserve will likely remain stable despite comparatively high levels of anthropogenic mortality, although further escalation may precipitate decline. Conversely, the lion population in Limpopo National Park is projected to become extirpated by 2030 without the buffering effect of its neighbouring source population in Kruger National Park. These unsustainable levels of anthropogenic mortality threaten the long-term viability of lion populations in Mozambique, requiring urgent national-level action and public-private partnerships to support site security, monitoring, and policy enforcement.
Quantifying the influence of optical coherence tomography beam tilt in each retinal layer
Purpose Well-aligned microstructures within the retina – like retinal nerve fiber layer (RNFL) axons – differentially reflect light depending on its angle. Our goal was to quantify the influence of optical coherence tomography (OCT) beam tilt on reflectivity of each layer of the mouse retina. Methods We collected OCT images in a single plane capturing the optic nerve head, temporal retina, and nasal retina, while tilting the OCT beam at various angles. We converted signal intensities to estimated attenuation coefficients (eAC). The attenuation coefficient describes how quickly the remainder of an OCT beam’s light is absorbed or scattered at a given depth into the retina. A single-ellipse model based on prior literature was calculated at each retinal depth, describing the maximum eAC across all tilts (ellipse semi-major axis), the beam tilt eliciting that maximum eAC, and eAC’s dependence on beam tilt (semi-major versus semi-minor axes). Post hoc, the inner retina bore an unexpectedly complex relationship between beam tilt and eAC, which we explored with a two-ellipse model. Results eACs in the temporal and nasal retina were dissimilar at specific beam tilts, but this was near-completely explained by differences in microstructure alignment. Dependence on beam tilt was substantial over the photoreceptors, but non-zero in all retinal layers. Post-hoc, two-ellipse models implied that microstructures vitread to the external limiting membrane were well-aligned with the photoreceptor inner and outer segments, and a small fraction (≥0.3%) of that tissue is especially translucent. Conclusion We mapped microstructure alignment throughout the retina. Expected findings at the photoreceptor inner and outer segments are complemented by new evidence of unusually translucent microstructures spanning much of the retina, possibly representing Müller glia.
In vivo tracking of grape marc biomarkers, bioconversion, metabolic tracers, and microbiota modulation in swine fed a polyphenol-rich extract diet
This work evaluated the addition of the polyphenol-rich bioactive extract “e-Vitis”, derived from grape marc (the main by-product of the wine industry), into swine feed. This was performed with the aim of testing the in vivo bioavailability of functional compounds, mainly phenolics, through the digestive system and excreta, together with the detection of bioconversion products associated with gut microbiota improvements. Additionally, the palatability of e-Vitis feed was evaluated, as well as the absence of metabolites that could compromise its innocuity. Through a pilot trial, a global methodology for the extraction and direct analysis of polyphenols from samples of gastric contents, duodenum, jejunum, ileum, caecum, colon, faeces and urine of these animals was proposed for the first time. The extraction process of bioactive compounds from samples was carried out using the matrix solid-phase dispersion (MSPD) technique. High resolution QToF (quadrupole time-of-flight) mass spectrometry and metabolomics tools were employed to identify 112 biomarkers that clearly differentiated (p < 0.05) the two groups of pigs (with and without enriched feed). The results showed a bioamplifying effect of e-Vitis feed on bile acids in gastric contents, associated with reduced oxidative stress and enhanced liver protection. This was attributed to the capacity of grape marc polyphenols to encapsulate bile acids, facilitating their transport through the digestive system. Polyphenolic bioconversion pathways were also elucidated, detecting structures such as apigenin, davidigenin and isoliquiritigenin, metabolised from quercetins contained in e-Vitis feed. Likewise, several markers of gut microbiota metabolism, including hippuric acid, phenylacetic acid and phenylalanine, were identified in pigs fed e-Vitis, which were related to the intake of phenolic compounds. Therefore, this study provides a comprehensive methodology applied to various biological matrices (digestive system and excreta) to understand the metabolism of polyphenols and their value as bioindicators in the determination of effective doses of by-product addition in animal diets.
First-line toripalimab plus chemotherapy versus chemotherapy for advanced esophageal squamous cell carcinoma: A cost-effectiveness analysis
Objectives This study aims to evaluate the cost-effectiveness of toripalimab combined with chemotherapy versus chemotherapy alone as a first-line treatment for advanced esophageal squamous cell carcinoma (ESCC) from the perspective of U.S. healthcare payers. Methods A 10-year partitioned survival model was developed using survival data from the JUPITER-06 clinical trial (NCT03829969). Costs included only direct medical expenses, and health utility values were derived from published literature. One-way and probabilistic sensitivity analysis were performed to assess the robustness of the model. Results Toripalimab combined with chemotherapy incurred an incremental cost of $64,483.3 and achieved an incremental effectiveness of 0.53 quality-adjusted life-years (QALY) compared to chemotherapy alone, resulting in an incremental cost-effectiveness ratio (ICER) of $122,771.67 per QALY. This ICER is below the willingness-to-pay threshold in the United States ($150,000). The model results were sensitive to the cost of toripalimab and the utility values of both progression-free and progressed disease states. Conclusions The findings indicate that toripalimab combined with chemotherapy as a first-line treatment for advanced ESCC in the United States provides a cost-effective benefit in comparison to chemotherapy alone.
Student engagement assessment using multimodal deep learning
Student engagement assessment plays an important role in enhancing students’ positive performance and optimizing teaching methods. In this paper, a multimodal deep learning framework is proposed for student engagement assessment. Based on this framework, we propose a method for engagement assessment that utilizes data from three modalities: video, text, and logs. This method implements the extraction of engagement indicators, the fusion of asynchronous data, the use of deep learning models to evaluate engagement levels, and the use of gradient magnitude mapping to further distinguish subtle differences between engagement levels. In subsequent empirical studies, we explore the applicability of several popular deep CNN models in this method and validate the reliability of the engagement quantification results using statistical methods. The analysis results demonstrate that the framework, which combines multimodal asynchronous data fusion and deep learning models to assess engagement, is both effective and practical.
Microclimate effects and outdoor thermal comfort of green roof types in hot and dry climates: Modelling in the historic city of Yazd, Iran
In hot and arid climates, developing green roofs to improve the microclimate and thermal comfort faces challenges due to water scarcity and harsh climate conditions. To evaluate the effect of green roof types on microclimate parameters and thermal comfort, a simulation was conducted in Yazd, Iran, using the ENVI-met model. Three scenarios—intensive green roofs, extensive green roofs, and roofs without vegetation—were simulated using meteorological data from 7:00 am to 6:00 PM during the hottest period of the year. Desert-adapted plant species were included in two green roof types. The model outputs indicated that, compared to extensive green roofs and roofs without vegetation, intensive green roofs resulted in lower air temperature, mean radiant temperature, and longwave radiation. They also led to higher wind speed and relative humidity, contributing to more desirable thermal comfort. Extensive green roofs and roofs without vegetation generally showed no significant differences in the measured microclimatic parameters or thermal comfort index. As suggested by the findings of this study, intensive green roofs demonstrated superior performance in enhancing thermal comfort compared to extensive green roofs. However, during the hottest period of the year and within the measured hours, all three scenarios were classified as ‘very hot’ (PMV = 5.03) and ‘hot’ (PMV = 3.2), experiencing strong to extreme heat stress, respectively. The measured hours and distance from the roofs affected the microclimatic parameters and thermal comfort, with the intensive green roof showing the most favorable thermal comfort condition (PMV = 0.18) during 7:00–9:00 am, perceived as comfortable with no thermal stress. However, the microclimatic improvements and thermal comfort enhancements resulting from the simulated green roofs in the surrounding environment) were not significant. Considering the outcomes alongside the severe climatic conditions prevalent in the city of Yazd, characterized by high temperatures, intense radiation during the summer, and extreme water scarcity, the proposition for the construction and development of green roofs in this region is not advisable. Although green roofs aim to ameliorate the microclimate and improve thermal comfort during hot periods, their effectiveness under such harsh conditions remains limited.
Tandem Biocatalysis to Generate Hydrogen Sulfide and Promote Endogenous Antioxidant Response
Abstract Promoting cellular protective responses during oxidative stress conditions through the generation of antioxidant persulfide (RS‐SH) and hydrogen sulfide (H 2 S) has tremendous therapeutic potential. Here, we report a bioinspired glycoconjugate, a candidate for tandem biocatalysis and generates persulfide/ H 2 S in response to oxidative stress. The glycoconjugate is cleaved by β‐galactosidase, an enzyme that is expressed during oxidative stress; the product of this reaction is a substrate for 3‐mercaptopyruvate sulfurtransferase (3‐MST), an enzyme that is involved in persulfide/ H 2 S biosynthesis. The catalytic systems are orthogonal to one another, and the glycoconjugate is efficiently cleaved by these enzymes to generate the potent antioxidant glutathione persulfide as well as H 2 S. We demonstrate the efficacy of this conjugate in mitigating inflammation in the brain in an animal model. Together, using rationally designed substrates and fully catalytic steps, we leverage tandem biocatalysis to direct the generation of persulfide/ H 2 S, and promote cells’ own antioxidant response.