搜索结果：Cheaper

Accurate nodal staging in intermediate- to high-risk prostate cancer (PCa) is crucial for treatment decisions. While extended pelvic lymph node dissection (ePLND) is the standard, it is invasive and has a low diagnostic yield. A 2019 analysis suggested that non-invasive imaging such as PSMA-PET/CT and ferumoxtran-enhanced macrophage-MRI (m-MRI) is cost-effective, but at the possible expense of a small QALY loss compared to ePLND, based on limited evidence. Recent Phase 3 trials have provided new data, prompting a reevaluation. Therefore, the aim of this article is to update a model with recent trial data to assess the cost-effectiveness of m-MRI and PSMA-PET/CT versus ePLND in Germany. We adapted a Markov model to simulate lifetime outcomes for men with intermediate- to high-risk PCa from a German insurer's perspective, with costs updated to 2025 level. Diagnostic accuracy data were derived from recent multicenter trials. Costs and QALYs were calculated using a 3% discount rate. Sensitivity analyses tested uncertainties. A practical interactive online-tool is provided for clinical decision-making and research purposes, which can incorporate various input data (https://macrophage-mri.app). Both imaging options were dominant over ePLND (€37,855; 18.11 QALYs). PSMA-PET/CT was €7,869 cheaper and gained 0.800 QALYs; m-MRI was €9,985 cheaper and gained 0.990 QALYs. m-MRI was superior, saving €2,116 and gaining 0.19 QALYs over PSMA-PET/CT. The probabilistic analysis showed that m-MRI was optimal over 95% of the time at an €80,000/QALY threshold; the probability of PSMA-PET/CT being optimal was less than 5%. An imaging-first approach outperforms routine ePLND, with m-MRI as a cost-effective option. PSMA-PET/CT's low sensitivity limits its usefulness, though it is still cheaper than ePLND. These results support including m-MRI in guidelines for initial staging.

Agriculture dominates United Kingdom ammonia emissions, from livestock manure exposed to the atmosphere via livestock housing, storage, land and grazing. Ammonia significantly contributes to the formation of PM2.5 (particles with diameter of 2.5 μm or less) concentrations in Europe which are associated with adverse human health outcomes. Ammonia emissions contribute to nitrogen deposition, whereby reactive compounds of nitrogen are deposited into the biosphere, potentially resulting in biodiversity loss. Recent research has not found sufficient evidence for effectiveness of interventions to reduce ammonia emissions and little evidence on the cost-effectiveness of interventions. The current study aimed to address this knowledge gap. The study aimed to assess effectiveness and cost-effectiveness of two agricultural interventions to mitigate ammonia emissions - improved housing for farmed animals and improved manure application. Emission measurements were made at five farms (dairy, pig, poultry). Information on uptake of mitigation measures, barriers and enablers for implementation were determined through an online survey and focus groups with farmers, supplemented by stakeholder interviews. Chemical transport and dispersion modelling estimated population exposures to air pollution at local and national levels under three scenarios (low, medium, high intervention uptake). A health impact assessment estimated health effects associated with the scenarios, and data on self-reported health issues were collected via an online survey of rural residents. Economic evaluation methods estimated cost-benefits of the scenarios and impact on ecosystems. Farmers favour mitigation measures which are cheaper, and build on existing practices, such as amending diet or extending the grazing season. However, these are less effective in decreasing ammonia emissions. Scenarios based on realistic current, and future, uptake levels of measures showed little impact on air quality, partly due to the ammonia-rich United Kingdom atmosphere minimising conversion of ammonia emissions to particulate matter. Consequently, minimal impact of mitigation measures was evident on health outcomes and costs. There was no evidence that self-reported health symptoms from rural residents were related to living near a farm, type of farm or seasonality of farm activities, consistent with results of local dispersion modelling which estimated that most emissions from animal housing dispersed within 1 km. Impacts of COVID-19 and the United Kingdom's withdrawal from the European Union on the agricultural industry affected the recruitment and availability of farms and farmers, resulting in fewer field measurements than planned. A lower response to the farmers' survey was mitigated by the quality of data provided by participants and the successful series of focus groups. The study highlights the need for enhanced communication with the farming community to encourage implementation of more effective mitigation measures, such as air scrubbers, or those relating to slurry storage, currently perceived to be too expensive and complex. Greater clarity on benefits is essential so that farmers understand not only what they need to do but also how and why. Further investigation of the health impacts of ammonia emission should focus on those exposed on the farm, or resident nearby animal houses. Further modelling development of key atmospheric processes is also indicated to minimise uncertainties associated with the regional modelling. This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme as award number NIHR129449. Air pollution damages lung and heart health, contributing to premature death and hospital admissions. These health effects are associated with exposure to very small particles, including from reactions of ammonia emitted from farming, the main United Kingdom producer of ammonia, principally from animal manure in livestock housing, fertilisation of fields and animal grazing. Recently, other United Kingdom sources of particles have decreased, but ammonia levels have not. This study aimed to assess the effectiveness of improved cattle housing and manure storage and application, at reducing emissions of gases and particles. We measured ammonia emissions from five farms and used surveys, focus groups and interviews with farmers and stakeholders to understand views on ammonia reduction measures. Computer models were used to estimate the impact of emissions reduction on exposure and related health issues of people near farms and the wider United Kingdom population. We calculated savings in National Health Service costs. We also surveyed people living near farms about their health. The study found that the measures that farmers were currently prepared to consider implementing reduced ammonia emissions by up to 13%, but the overall reduction in air pollution particles was limited (around 1%). Improvements in health and cost-savings were also small, and surveys of rural residents did not show health problems were related to farming. The study also showed that emissions from farms almost entirely dispersed into the background air within 1 km. Farmers were interested in reducing their environmental impact and favoured cheaper interventions building on existing practices, which also tended to be less effective in reducing ammonia emissions. Barriers to using these interventions were costs and lack of knowledge. To reduce ammonia emissions, future policies should address the barriers and clearly communicate benefits to the environment and to farmers. It would be useful to study more effective farming interventions to reduce air pollution.

Copaiba oil-resin (CO), extracted from trunks of various copaiba species, has several therapeutic and cosmetic properties and is a valuable non-timber forest product that contributes to preservation of the Amazon rainforest. Unfortunately, adulteration of this oil-resin with cheaper vegetable oils such as soybean oil (SO) has been common. In this paper, a method for the fast screening of SO in CO using time-domain NMR (TD NMR) relaxometry was developed and validated. CPMG relaxation measurements were performed by two analysts using two TD NMR instruments from different manufacturers. Strict temperature control, a low number of echoes, and a long echo time were required for adequate repeatability. The first derivative of CPMG decays and the percentage of SO in CO were modeled with partial least squares regression (PLSR). The first derivative of CPMG signal was found to minimize contributions of longer T2 components and to emphasize those of shorter T2 components, associated with more viscous components of the CO/SO mixture. As a result, the first derivative increased sensitivity of the method to the SO content. Results obtained with 1 latent variable showed an R²CV > 0.98, RMSECV between 2.9% and 4.7% SO, and LOQ values ranging from 29.3% to 48.3% SO, with an average close to 36% SO, lower than the adulteration level normally above 50%, but unable to monitor low-level contamination. The precision was assessed by repeatability (RMSEP 2.6 ± 0.5% SO) and intermediate precision (RMSEP 4.2 ± 1.0% SO). The results agreed with those obtained using established infrared and NMR spectroscopic methods. Therefore, this method shows potential for rapid and non-destructive screening of gross adulteration of CO with SO, as observed in Brazilian markets.

In May 2023, Ghana implemented a 20% ad valorem tax on bottled water and sweet beverages (SBs), replacing a 17.5% tax; sachet water remained untaxed. The effect on low-income consumers' purchasing decisions and consumption patterns remains poorly understood. We aimed to explore factors influencing water and SB purchasing behaviours among low-income households in four peri-urban Accra communities. This study employed a convergent parallel mixed-methods design. Four focus group discussions (n = 36) and a cross-sectional survey (n = 43) were conducted among purposively sampled household primary shoppers in early 2025 across Oyarifa, Teiman, Kweiman, and Danfa. Data were analysed thematically and descriptively. Of 43 participants, 67% were female and 65% had junior high school education. Water insecurity was common (60%), and sachet water was the main drinking source (77%). SB purchasing was driven by taste and convenience, while sachet water choices were linked to perceived safety, price, and availability. Tax awareness was moderate (56%); many perceived bottled water taxation as unfair and reported intentions to switch to cheaper local alternatives. Limited tax awareness and perceived inequities suggest the need for policy refinements to better align fiscal measures with public health objectives.

Most clinically relevant data are in unstructured clinical notes, which are verbose and imprecise, making structured data extraction a costly bottleneck for screening patients for studies or maintaining health care registries. This challenge is particularly pronounced in interstitial lung disease (ILD) and requires significant human effort to interpret notes and determine classification to create an ILD registry. Large language models (LLMs) have the potential to significantly reduce this cost and effort. We aim to compare the performance of various LLMs for structured data extraction from unstructured ILD clinic notes. Our primary aim was to evaluate LLM extraction of binary structured data (yes/no answers) from clinical notes regarding key ILD clinical questions. A secondary analysis evaluated select LLMs for the extraction of multiclass data to determine ILD classification. We used 12 different LLMs to extract binary answers to 10 ILD clinical questions from the most recent clinic notes of 100 ILD clinic patients. We additionally used 2 LLMs (gpt-oss-20b and gpt-oss-120b) to extract multiclass data regarding ILD classification. Prompts were created with the assistance of ChatGPT (OpenAI) and refined with an iterative approach by testing on a prompt engineering cohort of 10 ILD clinic patient notes. Ground truth was established by consensus among 3 ILD physicians. LLM performance was evaluated using accuracy, precision, recall, and F1-scores. LLMs processed each interface call of a clinical note-prompt combination in 1-2 seconds, with estimated costs ranging from less than US $0.001 to US $0.11 (or approximately US $0.05 to US $10.50 per clinical note accounting for 10 runs and 10 binary prompts) depending on the model. Out of the 12 LLMs assessed, 7 models (Claude 3.5 Sonnet [Anthropic], GPT-4o, gpt-oss-20b, gpt-oss-120b, o1, o1-mini, and o3-mini [OpenAI]) performed at human-level accuracy, similar to that of the 3 ILD clinicians (96.2%). A total of 5 LLMs performed significantly worse than humans (Holm-adjusted P≤.003 for all). gpt-oss-120b, o1, and o3-mini models achieved the highest F1-scores of all the evaluated LLMs. There was no significant difference in model accuracy among the top tier models (Claude 3.5 Sonnet, gpt-oss-20b, gpt-oss-120b, o1, o1-mini, and o3-mini), though GPT-4o achieved significantly lower accuracy than o1 (Bonferroni-adjusted P=.04). Multiclass data extraction using gpt-oss-120b and gpt-oss-20b demonstrated lower accuracy when compared to its corresponding binary data extraction (91.1% and 88.0%, respectively). There was no significant difference in accuracy between gpt-oss-120b and gpt-oss-20b for multiclass extraction. Multiple LLMs consistently achieved human-level accuracy in extracting structured binary data from ILD clinical notes, while being orders of magnitude faster and cheaper. Multiclass data extraction was possible but associated with a lower accuracy. LLMs are promising tools that can be used for clinical data extraction to improve clinical research efficiency.

Rapidly changing Asian food environments characterized by increased availability of cheaper, energy-dense, and low-nutrient products, are negatively impacting nutritional and health outcomes. This paper introduces SHAPE Asia, a collaborative learning network of food environment interest-holders across Indonesia, Malaysia, Thailand, the Philippines, and Sri Lanka. These countries face significant regulatory challenges. Unregulated food marketing and retail practices promote unhealthy products resulting in adverse health impacts. Policymaking is hampered by insufficient political will, industry interference, and government sensitivity to perceived economic impacts of regulation compounded by inadequate public awareness and limited prioritization of sustained behavior change. Balancing economic and public health interests requires multifaceted, multisectoral approaches to ensure commitment toward healthier food environments. SHAPE Asia generates regionally-specific knowledge through shared learning to support double-duty food policy actions. It engages policymakers, academics, government agencies, international organizations, media, and civic organizations to ensure inclusive and equitable food environment transformation. It facilitates peer learning and South-South and North-South capacity building supporting healthy food environment advocacy. It translates research into action by strengthening coordinated efforts to develop feasible, effective, and sustainable policy options while building interest-holder support and generating policy-relevant evidence. SHAPE Asia is part of a global cohort of multi-actor coalitions influencing policies and transforming food systems across Central and South America, South Asia, and Southeast Asia. These coalitions combine collaborative learning networks and communities of practice to support production, consumption, and access to healthy diets, particularly for vulnerable populations, while emphasizing sustainable, gender-equitable, and inclusive systems contributing to the health of people and ecosystems. Added knowledge: This paper provides the first comprehensive documentation of how South-South and North-South collaborative learning networks can generate regionally-specific, actionable knowledge to support double-duty food policy development while building multi-sectoral interest-holder capacity for sustainable food environment transformation.Global health impact for policy and action: SHAPE Asia offers a replicable model for coordinating multi-actor coalitions to translate research into feasible policy options that balance economic and public health interests, with potential application to other regions experiencing rapid nutrition transitions and weak regulatory frameworks for unhealthy food environments.

The purpose of this research is to develop a fast, environmentally friendly, precise, sensitive, and specific high-performance liquid chromatography (HPLC) method for the simultaneous determination of sildenafil and sodium benzoate in bulk raw materials and in the legally marketed reference drug (Revatio powder for oral suspension). The optimized mobile phase flow rate was 1 mL/min, with the mobile phase consisting of 600 mL of 0.2% v:v phosphoric acid aqueous solution and 400 mL of ethyl alcohol. The range of linearity used for sildenafil and sodium benzoate was 3.5-280 µg/mL (sildenafil) and 0.35-28 µg/mL (sodium benzoate), respectively. The wavelength used to analyze the samples was 230 nm; the sample size was 10 µL; and the analysis time was less than 4.5 min. The ultimate scores are as follows: 0.63 for the Analytical Greenness Metric for Sample Preparation (AGREEprep), 72.22 for the Analytical Green Star Area (AGSA), 80 for the Blue Applicability Grade Index (BAGI), 72 for the Click Analytical Chemistry Index (CACI), 88 for the Carbon Footprint Reduction Index (CaFRI), 89 for the Analytical Ecoscale (AES), and 78 for the Modified Green Analytical Procedure Index (MoGAPI), and an (A) letter score of 75.3% indicates the whiteness level using the Multi-color Assessment (MA) Tool, and all imply the high sustainability, greenness, whiteness, and economic wisdom of the current method. All validation characteristics have followed the International Council for Harmonisation (ICH) and United States Food and Drug Administration (US FDA) validation guidelines. Compared to complicated systems such as Ultra-performance Liquid Chromatography-tandem Mass Spectrophotometry (UPLC-MS), it has benefits including shorter retention times, less reagent usage, simultaneous analysis, and cheaper prices.

The equations of classical mechanics can be used to model the time evolution of countless physical systems, from the astrophysical to the atomic scale. Accurate numerical integration requires small time steps, which limits the computational efficiency-especially in cases such as molecular dynamics that span wildly different timescales. Using machine-learning (ML) algorithms to predict trajectories allows one to greatly extend the integration time step, at the cost of introducing artifacts such as lack of energy conservation and loss of equipartition between different degrees of freedom of a system. We propose learning data-driven structure-preserving (symplectic and time-reversible) maps to generate long-time-step classical dynamics and show that this method is equivalent to learning the mechanical action of the system of interest. These models can be learned based on short reference trajectories and be transferred across thermodynamic conditions and chemical composition. We show that an action-derived ML integrator eliminates the pathological behavior of non-structure-preserving ML predictors and that the method can be applied iteratively, serving as a correction to computationally cheaper direct predictors.

Recent increases in food prices in Egypt have raised concerns about their impact on dietary patterns and household food security (FS), particularly among economically vulnerable groups, forcing families to reduce dietary diversity and nutrient intake. This may indirectly contribute to an increased risk of malnutrition and chronic diseases. To identify changes in food consumption behavior (food choices and dietary patterns) among Egyptian households following food inflation and determine the levels and predictors of food insecurity (FI). An online cross-sectional survey of 723 Egyptian households from June to December 2024. Data was collected using a pretested structured questionnaire targeting household heads. The tool assessed sociodemographic characteristics, food consumption changes, and FS status. Most participants reported increased food expenditure (58.2%) with dietary shift toward cheaper carbohydrate-rich staple foods (55.2%). Reduced consumption of animal protein and dairy products was also observed. Overall, 64.6% of households experienced FI: 15.8% mild, 27.5% moderate, and 20.3% severe levels. Significant predictors of FI included female respondents (OR&#x2009;=&#x2009;2.425, P&#xa0;<&#x2009;.001), maternal unemployment [odds ratio (OR)&#x2009;=&#x2009;1.597, P&#xa0;=&#x2009;.018], low household income (OR&#x2009;=&#x2009;1.774, P&#xa0;=&#x2009;.001), maternal financial responsibility (OR&#x2009;=&#x2009;3.432, P&#xa0;<&#x2009;.001), the presence of a family member with chronic disease (OR&#x2009;=&#x2009;1.748, P&#xa0;=&#x2009;.002), and a current smoking father (OR&#x2009;=&#x2009;1.711, P&#xa0;=&#x2009;.004). Increased food prices lead to changes in food consumption patterns with shifts toward less nutritionally valuable foods and deprive most households of FS. Therefore, there is an urgent need for national nutrition health education programs to help households optimize the use of limited household budgets to achieve a balanced diet.

Access and adherence to cardiac rehabilitation (CR) remain suboptimal, particularly in rural and remote settings. This study evaluated the implementation of person-centred, evidence-based CR delivery model tailored to improve access and completion. The implementation framework utilised was the Model for Large-Scale Knowledge Translation. The Country Heart Attack Prevention (CHAP) project introduced evidence-based flexible CR including, face-to-face, telehealth, telephone, web-based and primary care options. A matched prospective cohort compared CR attendance, completion (primary outcomes), cardiovascular (CV) readmissions, mortality, and emergency department (ED) visits between CHAP rural services and standard metropolitan face-to-face CR. CR attendance was comparable between groups (24.2% vs 23.8%; odds ratio [OR] 1.15; 95% confidence interval [CI] 0.89-1.47; p=0.16), but completion rates were significantly higher in the CHAP Project (77.1% vs 57.5%; OR 1.69; 95% CI 1.30-2.18; p<0.001). Patient satisfaction was also greater (85.9% vs 77.1%; p<0.001). Median waiting times were similar (38 vs 36 days; p=0.008). Alternative delivery models were equivalent to traditional face-to-face modes for CV readmissions (hazard ratio [HR] 1.19; 95% CI 0.96-1.49; p=0.17), CV mortality (HR 1.70; 95% CI 0.92-3.16; p=0.09), and ED visits (HR 1.06; 95% CI 0.94-1.21; p=0.33). CR completion through CHAP was cheaper and more effective (costs: $6,542 vs $8,689; completions: 77.1% vs 57.5%). The CHAP model had over 50% probability of being cost-effective in improving CR completion. Uptake of the CHAP model would result in a cost reduction ranging from $2 million (m) at 20% uptake to $10m if all patients referred attended and completed CR. The CHAP Project significantly improved program completion and achieved satisfaction without compromising clinical outcomes and showed important levels of economic benefit. Broader implementation of person-centred models of CR, across all geographic areas to enhance uptake and impact of CR in underserved populations is recommended.

Wasted tea of Salvia officinalis (WTSO) and the acorn cupule of Quercus coccifera (ACQC) were used as highly efficient biosorbents in the experiments. The aim is to convert waste materials into novel treatment materials which will be economically cheaper sources compared with conventional activated carbon. The powdered form of these materials, without any thermal or chemical pretreatment, was applied to wastewater containing Blue X GRL (BXGRL) and Red Violet 3R (RV3R) textile dyes. Various parameters affecting the separation such as pH, amount of biosorbent, contact time, dye concentration, and temperature were investigated. High removal efficiencies (up to 99%) and biosorption capacities could be readily obtained by these novel biosorbents for the studied toxic dyes. The most convenient pH and adsorbent dosage were found to be 8 and 0.1&#xa0;g/100 mL, respectively. The values obtained from WTSO material with RV3R dye were fitted to Freundlich isotherm model, while the results from other material-dye sets were fitted to Langmuir model at 25&#xa0;&#xb0;C. The data from both ACQC and WTSO biosorbents were very well conformed to pseudo-second order reaction kinetic model with a R2 value of 99% when compared with pseudo first order and Elovich models. The rate limiting step was found to be chemisorption according to the results of pseudo second order and intraparticle diffusion models. In adsorption studies using high concentrations, it was observed that the dye removal efficiency increased with temperature. The highest biosorption capacities for BXGRL were obtained as 344.83&#xa0;mg/g with WTSO and 222.22&#xa0;mg/g for ACQC at 25&#xa0;&#xb0;C according to the Langmuir isotherm model. The biosorption capacities of WTSO and ACQC were 147.06 and 106.38&#xa0;mg/g, respectively, for RV3R dye at 25&#xa0;&#xb0;C as a result of Langmuir model.

By studying and analysing a great number of textile metal threads from different time periods in Croatia, from archaeological sites to preserved specimens from various museum collections, change can be seen through the centuries. Metal threads decorate textiles not only for aesthetic purposes, but also to display wealth, assert authority, and command respect. Primarily, such decorated clothing was worn for liturgical purposes, ceremonial folk customs, or to mark high military ranks. Through the characteristics of these threads, one can see the change in the customs and lives of the people who used them in different ways and for different purposes. The shine and luxury that the first gold metal threads have can be achieved with lower quality threads like silver, copper, and their alloys. As the quality of metal textile threads decreased, they became cheaper and more applicable in everyday life. The use of metal textile threads on clothing increased, and through the century, they became a clothing part for all people, not just the privileged. Analyses of metal threads were performed with scanning electron microscopy with an energy-dispersive X-ray detector (SEM-EDX) due to its sensitivity and suitability for the observation of metal threads from various textiles. The type of textile cores from the combined textile metal threads was determined through a laboratory optical microscope. Differences have been observed between archaeological and historical textile metal threads in terms of physical properties, as well as textile and metal composition. Archaeological samples are combined textile metal threads that have a metal component of gilded silver and a textile component of silk. While more recent historical samples have different types of metal threads, from individual threads of lamellae and wires to combined textile metal threads. Most samples have cotton as a textile component, while copper, alone or in alloys, predominates in the metal threads.

Childhood malnutrition remains a significant challenge in sub-Saharan Africa, particularly in regions where cassava is a staple. Despite its prevalence, cassava is an inadequate complementary food for children aged 6-59&#x2009;months due to its low protein content, persistent cyanogenic glucosides, and high-viscosity, low-nutrient density. This study aimed to develop and optimize an instant cassava-soybean composite porridge using extrusion cooking. Using a mixture design to evaluate nine formulations against WHO nutrient recommendations, a 70:30 cassava-to-soybean ratio was identified as optimal. A central composite design involving 21 experimental runs further optimized extrusion conditions by varying barrel temperature (BT) (60&#xb0;C-150&#xb0;C) and feed moisture (16%-30%). The ideal extrusion parameters were determined to be a 145.6&#xb0;C (BT) and 19.7% feed moisture. The resulting flour contained 12.04% protein with 70.9% digestibility, 8.42% moisture, and a viscosity of 1086.63&#x2009;cP. Notably, extrusion significantly reduced cyanogenic glucosides, enhancing product safety. Sensory evaluation by a semi-trained panel of 30 adults using a 9-point hedonic scale indicated high consumer appeal, with overall acceptability and texture scores of 7.3 and 7.4, respectively (&#x1d45d;&#x2009;<&#x2009;0.05). Cost analysis showed the final product is 56%-65% cheaper than commercial alternatives like Cerelac. In summary, this optimized porridge complies with WHO guidelines for complementary foods, offering a feasible, safe, and economical nutritional solution for cassava-consuming communities.

Ethiopia's unregulated private antibiotic economy spans private hospitals, clinics, pharmacies, drug shops and informal vendors. It drives resistance through three forces: intergenerational self-medication (reservoir habit), a satisfaction imperative linking sales to customer retention, and a corner drugstore calculus prioritising immediate access over cheaper but slow public care. Non-prescribed dispensing becomes the norm and selects resistant bacteria. We propose a six-pillar framework: tiered accreditation, point-of-service education, supply chain engagement, mystery client support, technology enabled consultation and operational research. This stewardship without walls is an urgent priority for Ethiopia and similar settings.

Pulmonary infections in elderly patients cause high morbidity and mortality. Conventional culture has low sensitivity and slow turnaround, delaying targeted therapy. Metagenomic next-generation sequencing (mNGS) is an emerging technology, but its diagnostic performance and cost-effectiveness are unclear. This study therefore aims to evaluate its diagnostic performance compared to conventional culture in older adults with pulmonary infections and to assess its cost-effectiveness. From March 2020 to March 2023, 522 patients (aged 55-69&#xa0;years) diagnosed with pulmonary infections were enrolled at Peking University Shenzhen Hospital. Of these, 168 patients underwent simultaneous mNGS and conventional culture testing using bronchoalveolar lavage fluid (BALF) samples, while the remaining 354 patients received culture testing alone. Pathogen detection results were compared to assess the diagnostic performance of mNGS versus traditional culture methods. Additionally, cost-effectiveness analyses of the two diagnostic strategies-as well as the impact of mNGS testing timing post-admission-were conducted in the overall cohort and across stratified subgroups. Among the 168 patients who underwent both tests, mNGS identified a greater diversity and abundance of microorganisms than culture (overall detection: 89.88% vs. 26.79%; pathogen detection: 67.86% vs. 18.45%, p&#x2009;<&#x2009;0.001). mNGS testing yielded a net economic benefit of 1202.70 CNY per patient overall and 3831.15 CNY among pathogen-positive cases. Delaying mNGS testing tended to be associated with increased hospitalization length of stay (LOS) and costs, with the most pronounced difference observed around 6&#xa0;days after admission (p&#x2009;<&#x2009;0.001). Early mNGS testing (within 6&#xa0;days of admission) provided a net benefit of 6346.00 CNY. BALF-based mNGS showed higher positivity rates and a broader pathogen detection spectrum compared to conventional culture methods in this study. Early implementation of mNGS shows strong potential to guide the treatment of pulmonary infections and reduce healthcare costs for elderly and aging patients. Diagnosing pulmonary infections in elderly patients is challenging because traditional &#x201c;culture&#x201d; methods often fail to find the specific germ. In this study, we analyzed bronchoalveolar lavage fluid samples from 522 patients aged 55&#x2013;69, we compared a newer DNA-based testing technology called metagenomic next-generation sequencing (mNGS), a method that can simultaneously detect all genetic material in samples and identify virtually any pathogen capable of causing infection, with traditional culture methods. We then compared the results of the two methods and calculated total hospital costs&#x2014;including testing, length of stay, and other related expenses. Our findings highlight three key advantages. First, mNGS detected a much wider variety of pathogens than culture methods. Second, despite the higher upfront cost of the sequencing test, using mNGS was actually cheaper overall than relying on culture, saving an average of 1202.70 CNY per patient by guiding better treatment. Third, timing is critical: performing mNGS early (within 6&#xa0;days of admission) saved significantly more money compared to delayed testing. These results suggest that using mNGS early is not only clinically superior but also reduces the financial burden on patients and hospitals.

Human-induced environmental change increases unpredictability, disrupting habitats and social structures in ways that many animals are poorly adapted to. This may also reduce the reliability of information faster as contingencies shift. While independently acquired information is often more accurate, increased unpredictability may make recency the key to reliability, increasing the value of social information, which is cheaper and faster to update. Unpredictability might thus shift the balance between the values of these types of information, increasing reliance on more recent social information. Thus, independent of information quality, the predictability of background conditions may affect how animals make decisions. To test whether living in an unstable environment changes the inherent value of information, zebrafish (Danio rerio) were housed for 3&#x2005;mo under either highly unpredictable Dynamic (water temperature, feeding times, habitat complexity, group size and membership fluctuated) or Stable conditions. Across 6 behavioral assays, Dynamic condition fish showed more information-seeking, greater attention to social stimuli, more sensitivity to social cues, and were less coordinated but swam closer together in shoals. When personal and social information conflicted, they were also more likely to prioritize recent social information over previously learned personal information. Together, these results indicate that long-term housing in an unpredictable environment diminishes the value of information faster, raises the value of social information to allow for faster updating, shifts decision-making strategies independent of the quality of information itself, and disrupts coordinated schooling in zebrafish. This sensitivity may fundamentally alter how animal collectives navigate an increasingly unpredictable world.

Using six laser tubes with various diameters, lengths, and volumes of the active zone, an investigation on an ultraviolet gold vapor laser is undertaken. We achieve a maximal average output power of 1.07&#xa0;W at 312.2&#xa0;nm wavelength. We also obtain a specific average laser power of 56.3 mW.cm-&#x2009;3, which is more than 6 times higher than the value described so far. Polarized high-beam-quality laser radiation is generated for the first time through an unstable cavity equipped with a Glan prism. In addition, the sum frequency mixing of the fundamental 312.2-nm and 627.8-nm output yields laser oscillation at a new spectral 208.5-nm line. This laser source constitutes a cheaper alternative of excimer and other UV lasers for materials surface modification and photochemistry applications.

We introduce SCRIVENER (sequential conjugation and recombination for in vivo elongation of nucleotides with low errors), an in vivo DNA assembly platform that streamlines and scales DNA engineering. SCRIVENER combines bacterial conjugation, in vivo DNA cutting, and homologous recombination to stitch DNA blocks together by mating E. coli in large arrays or pools. This approach is simpler, cheaper, and higher throughput than methods requiring DNA to be moved in and out of cells. We performed over 5,000 assemblies with 2 to 19 blocks (240 bp-12 kb) and assembled constructs up to 81 kb with high fidelity. Most errors are deletions between long repeats, but SCRIVENER minimizes their impact by enabling high-replication assembly and sequence verification at a nominal additional cost per replicate. The platform enables combinatorial library construction and DNA block reuse without PCR and is therefore a powerful tool to accelerate DNA design-build-test-learn cycles. A record of this paper's transparent peer review process is included in the supplemental information.

There's a saying in the management world, popularized by NASA administrator Daniel Goldin in the 1990s, that the goal of technological improvements is to make products faster, better, and cheaper. Although this strategy had some success in the aerospace industry, the zealots of artificial intelligence (AI) have been making the same argument regarding how it will transform work, claiming that so little human effort will be required that humanity will enter an era of radical abundance, free from disease, drudgery, and danger, among other benefits, leaving society with more time for creative pursuits. But history tells a different story. When machines began to increase productivity during the second industrial revolution, American engineer Frederick Winslow Taylor's The Principles of Scientific Management encouraged corporations to use surveillance to get employees to work harder and longer, an approach that exhausted and discouraged workers and led to the transfer of knowledge and any decision-making from workers to management, while enriching the profits for only those at the top. Yet, it remains foundational to the American economic enterprise. Indeed, scientific publishing is starting to experience some Taylorism with the insertion of AI. Rigorous human checking of AI-generated research papers is creating bottlenecks as publishers strive to maintain the integrity of the scientific record. The challenge is requiring even more human effort, making the whole endeavor slower and more expensive.