Tag: pubmed

Sci Rep. 2024 Nov 26;14(1):29261. doi: 10.1038/s41598-024-80849-6.

ABSTRACT

The dynamic and multimodal nature of photovoltaic (PV) systems makes it challenging to examine all solar photovoltaic characteristics. Consequently, this study recommends a recently developed optimization method called the marine predator algorithm (MPA) for developing reliable PV models. In the traditional MPA, the two main search processes are Lévy flight (LF) and Brownian walk (BW), and the switch across them is unpredictable. This is while the transition between these two mechanisms is naturally continuous and dynamic. To rectify the limitation mentioned above, this research paper presents an innovative, dynamic shift function that effectively modulates the interplay that exists between the BW and LF procedures. By enhancing the changeover pattern between the primary phases of MPA, the suggested dynamic walk substantially boosts the performance of MPA. The dynamic Lévy-Brownian MPA (DLBMPA) is also made to be resilient in dealing with the parameterization limitations of PV Modeling approaches by using a constraint handling technique. The performance of DLBMPA is tested using ten popular optimization methods. Employing the DLBMPA achieved an average RMSE of 9.7 × 10^{– 4} in the parameter estimation across a number of multiple PV models, including the SDM, DDM, and TDM, where out of the ten optimization algorithms experimented, this was statistically significant (p < 0.05) better. In terms of averaged computation time, DLBMPA was 13 ms and still showed high accuracy in dealing with different irradiance and temperature levels. These improvements allow for MBPA to be credited as having a high efficiency when estimating the PV parameters since its speed of convergence and accuracy level surpass the previous techniques used.

PMID:39587262 | DOI:10.1038/s41598-024-80849-6

Nat Cancer. 2024 Nov 25. doi: 10.1038/s43018-024-00863-5. Online ahead of print.

ABSTRACT

Refractoriness to initial chemotherapy and relapse after remission are the main obstacles to curing T cell acute lymphoblastic leukemia (T-ALL). While tumor heterogeneity has been implicated in treatment failure, the cellular and genetic factors contributing to resistance and relapse remain unknown. Here we linked tumor subpopulations with clinical outcome, created an atlas of healthy pediatric hematopoiesis and applied single-cell multiomic analysis to a diverse cohort of 40 T-ALL cases. We identified a bone marrow progenitor (BMP)-like leukemia subpopulation associated with treatment failure and poor overall survival. The single-cell-derived molecular signature of BMP-like blasts predicted poor outcome across multiple subtypes of T-ALL and revealed that NOTCH1 mutations additively drive T-ALL blasts away from the BMP-like state. Through in silico and in vitro drug screenings, we identified a therapeutic vulnerability of BMP-like blasts to apoptosis-inducing agents including venetoclax. Collectively, our study establishes multiomic signatures for rapid risk stratification and targeted treatment of high-risk T-ALL.

PMID:39587259 | DOI:10.1038/s43018-024-00863-5

Sci Rep. 2024 Nov 25;14(1):29229. doi: 10.1038/s41598-024-80650-5.

ABSTRACT

A novel, optimized, polysaccharide and biochar-based, compostable hydrogel horticultural growing substrate for use in hydroponics and vertical farming was created based upon empirical methods and statistical design of experiments. A 15-run D-optimal mixture design of experiments was completed that increased the 14-day plant growing ability of a five-component hydrogel nearly ten-fold from 4.3695 g to 41.2623 g per 100 plants. The data were analyzed using a standard least squares method with an effect screening emphasis, and a model was created that maximized the signal to noise ratio. There was a good correlation between the measured and predicted values of the model, with an r-squared value of 0.90. The predictions of efficacy and compostability were confirmed with subsequent experiments that showed the hydrogel was composted in less than 84 days and that the plant growth predicted by the model differed from the experimental growth by 0.65%. The resulting optimized formulation had a high fertilizer content for a growth medium. We therefore suggest that an empirical approach to formulation research can produce superior outcomes with a statistically designed study.

PMID:39587252 | DOI:10.1038/s41598-024-80650-5

Nat Ecol Evol. 2024 Nov 25. doi: 10.1038/s41559-024-02594-3. Online ahead of print.

ABSTRACT

A pressing question resulting from global warming is how climate change will affect infectious diseases. Answering this question requires research into the effects of weather on the population dynamics of transmission and infection; elucidating these effects, however, has proved difficult due to the challenges of assessing causality from the predominantly observational data available in epidemiological research. Here we show how concepts from causal inference-the sub-field of statistics aiming at inferring causality from data-can guide that research. Through a series of case studies, we illustrate how such concepts can help assess study design and strategically choose a study’s location, evaluate and reduce the risk of bias, and interpret the multifaceted effects of meteorological variables on transmission. More broadly, we argue that interdisciplinary approaches based on explicit causal frameworks are crucial for reliably estimating the effect of weather and accurately predicting the consequences of climate change.

PMID:39587221 | DOI:10.1038/s41559-024-02594-3

Sci Rep. 2024 Nov 25;14(1):29205. doi: 10.1038/s41598-024-80554-4.

ABSTRACT

Insecticide based paint formulations have been available since years, however the concept of using such paint products at household level did not get attention due to various reasons. The advancement in insecticidal paint technology has steered toward the development and evaluation of such formulations for use against arthropod vectors. The improved insecticidal paint formulations may contain two or more active agents, hence could display different type of activity against the target vectors. In the present study, optimum concentrations of deltamethrin (1%), chlorpyriphos (0.5%) and pyriproxyfen (0.075%) were used as active ingredients (AIs) to develop flame retardant slow-release insecticides paint (FRSRIP) formulation. The developed formulation was tested for physico-chemical properties, toxicity and efficacy against two important mosquito vectors. The formulation was glossy, smooth, uniform and scratch proof. Furthermore, the formulation was flame retardant and conformed to class-A according to the guidelines. Acute oral, dermal and inhalation toxicity suggested that the formulation is safe for use in human dwellings. The formulation was evaluated against Ae. aegypti and An. stephensi mosquitoes in laboratory upto four years. It was found that KDT₅₀ after 24 months (T24) was 14.8 ± 0.8 min and 17.1 ± 1.0 min, while after 48 month (T48) was 21.3 ± 2.0 min and 22.4 ± 1.4 min in both Ae. aegypti and An. stephensi respectively. KDT₅₀ was found varying during the different time intervals (T6 to T48) in both Ae. aegypti (p = 0.01) and An. stephensi (p = 0.0003). Furthermore the corrected mortality (CM) also found statistically declined during the period of evaluation (T6 to T48) in both the test species (F ≥ 42. 4; p ≤ 0.0001). Ae. aegypti mosquitoes that survived FRSRIP exposure exhibited overall decline in total eggs laid, eggs hatched, pupae formed and adult emerged at different time intervals upto T21. Behavioural experiments showed that both the tested species elicited negative response to the test formulation. The concentrations of all the three active agents were estimated by HPLC after different time intervals, however only deltamethrin (0.24%) was found after T48. The developed formulation was stable, safe and effective against mosquito vectors for a considerably longer time. In the pretext of continuous toll of vector borne diseases and trans-boundary expansion of mosquito vectors into new geographical areas, the idea of using insecticidal paint could be a game changer.

PMID:39587220 | DOI:10.1038/s41598-024-80554-4

Commun Med (Lond). 2024 Nov 25;4(1):247. doi: 10.1038/s43856-024-00680-y.

ABSTRACT

BACKGROUND: The advantage of intensified myeloablative conditioning (MAC) over standard MAC has not been determined in haematopoietic stem cell transplantation (HSCT) for adult acute lymphoblastic leukemia (ALL) patients.

METHODS: To evaluate heterogeneous effects of intensified MAC among individuals, we analyzed the registry database of adult ALL patients between 2000 and 2021. After propensity score matching, we applied a machine-learning Bayesian causal forest algorithm to develop a prediction model of individualized treatment effect (ITE) of intensified MAC on reduction in overall mortality at 1 year after HSCT.

RESULTS: Among 2440 propensity score-matched patients, our model shows heterogeneity in the association between intensified MAC and 1-year overall mortality. Individuals in the high-benefit group (n = 1220), defined as those with ITEs greater than the median, are more likely to be younger, male, and to have higher refined Disease Risk Index (rDRI), T-cell phenotype, and grafts from related donors than those in the low-benefit group (n = 1220). The high-benefit approach (applying intensified MAC to individuals in the high-benefit group) shows the largest reduction in overall mortality at 1 year (risk difference [95% confidence interval], +5.94 percentage points [0.88 to 10.51], p = 0.011). In contrast, the high-risk approach (targeting patients with high or very high rDRI) does not achieve statistical significance (risk difference [95% confidence interval], +3.85 percentage points [-1.11 to 7.90], p = 0.063).

CONCLUSIONS: These findings suggest that the high-benefit approach, targeting patients expected to benefit from intensified MAC, has the capacity to maximize HSCT effectiveness using intensified MAC.

PMID:39587218 | DOI:10.1038/s43856-024-00680-y

Sci Rep. 2024 Nov 26;14(1):29272. doi: 10.1038/s41598-024-80488-x.

ABSTRACT

To meet the challenges of increasing food production demand globally, extracting insights regarding the persistent agriculture-related problems on a nationwide scale is the need of the hour. Policymakers now have limited possibilities for acquiring a comprehensive knowledge of the difficulties that farmers face on a national level. In this direction, the presented work proposes a new artificial intelligence-based pipeline to gain insights at country level regarding the farmers’ demand for assistance in India. The presented study uses the data from the Kisan Call Centres, a nationwide network of farmer’s helplines, including 28.6 million call-log records, made available by the Ministry of Agriculture & Farmers’ Welfare, Government of India. Additionally, the extracted insights are presented in the form of “Topic-wise Problems’ Trend Clusters” (TPTC), which can be used by policymakers in both the government and private sectors to aid decision-making. The article also introduces a pipeline for designing forecasting models to estimate the monthly frequency of farmer inquiries (in terms of the number of query calls). The seven statistical forecasting models were examined in the study with the TBATP1 (Trigonometric seasonal components with Box-Cox transformation incorporating ARIMA errors and Trend including the Seasonal components) model attaining the lowest error rates in terms of Root Mean Square Error (0.034) and Mean Absolute Error (0.107). The study also explores numerous applications of the derived insights in the real world as well as the future scope of the presented work.

PMID:39587214 | DOI:10.1038/s41598-024-80488-x

Sci Rep. 2024 Nov 25;14(1):29143. doi: 10.1038/s41598-024-80109-7.

ABSTRACT

OBJECTIVES: Investigate the relationship between bone mineral density (BMD) at various body sites and dental caries.

MATERIALS AND METHODS: Based on the National Health and Nutrition Examination Survey (NHANES) database from 2011 to 2016, the correlation between BMD at various body sites and the DMFS index among 7044 adults aged 20-59 years was analyzed. Multiple linear regression, restricted cubic splines (RCS), piecewise linear regression, logistic regression, weighted quantile sum regression (WQS) and mediation effects analysis were integrated to explore the relationship between BMD and dental caries.

RESULTS: Under the linear assumption, except for arm BMD, the BMDs of all other sites are negatively correlated with the DMFS index of dental caries. RCS analysis indicates a U-shaped relationship between head BMD and the DMFS index (p for nonlinear < 0.0001). WQS analysis indicates that mixed BMD is significantly negatively correlated with the DMFS index for dental caries (estimate, – 0.023; 95% CI, – 0.025 ~ – 0.020), and head BMD has the most significant impact on the DMFS index (weight = 91.4%). Simple mediation analysis of the effect of dental caries on BMD levels mediated by inflammation levels showed negative results, suggesting that dental caries may not influence BMD through inflammation levels.

CONCLUSION: Monitoring BMD should be combined with appropriate oral healthcare and caries management strategies to effectively address these interconnected health issues, and particular attention should be paid to the monitoring of head BMD.

PMID:39587203 | DOI:10.1038/s41598-024-80109-7

Sci Rep. 2024 Nov 25;14(1):29155. doi: 10.1038/s41598-024-80790-8.

ABSTRACT

To examine the relationship between age at diagnosis of type 2 diabetes (T2DM) with cardiovascular and all-cause mortality in the U.S. population. Data was used from NHANES 1999 ~ 2018, which were screened to include a total of 8,654 participants with a diagnosis of diabetes for the study. We estimated the association between age at diagnosis and cardiovascular and all-cause mortality using weighted multivariate Cox regression analyses. Subgroup analyses and sensitivity analyses were performed to ensure the robustness of the data analysis. The number of participants diagnosed with diabetes at ages < 40, between 40 and 59, and > 60 are 1,492, 3,970, and 3,192, respectively, with median ages of 44.04, 57.59, and 72.24. Among patients diagnosed with T2DM, the relative risk of all-cause mortality increased with younger age at diagnosis: compared to patients with late-onset diabetes (age at type 2 diabetes diagnosis ≥ 60), the hazard ratio for all-cause mortality was 2.72 (95% CI 1.83-4.05) in those with early-onset diabetes (age at type 2 diabetes diagnosis < 40). Similarly, the risk of cardiovascular disease death was observed to be a higher relative risk with younger age at diagnosis. Exposure-effect analysis indicated that younger age at diagnosis is associated with higher risk of all-cause mortality. Subgroup analysis found that the association between age at diagnosis and cardiovascular and all-cause mortality was stronger in the current smokers and hypertensive population. The results of this study suggest that younger age at diagnosis of T2DM is associated with higher risk of death in patients. Younger patients diagnosed with T2DM had a higher risk of cardiovascular and all-cause mortality. These findings strengthen the understanding of the risk of death from T2DM and emphasize the importance of early prevention of diabetes.

PMID:39587196 | DOI:10.1038/s41598-024-80790-8

Sci Rep. 2024 Nov 25;14(1):29154. doi: 10.1038/s41598-024-80499-8.

ABSTRACT

Three-dimensional (3D) marker-based motion capture is the current gold standard to assess and monitor pathological gait in a clinical setting. However, 3D markerless motion capture based on pose estimation is advancing into the field of gait analysis. This study aims at evaluating the lower-body 3D gait kinematics and kinetics from synchronously recorded Theia3D markerless and CAST marker-based systems. Twelve healthy individuals and 34 clinical patients aged 8-61 years walked at self-selected speed over a 13 m long walkway. Similarity between models was statistically analysed using inter-trial variability, root mean square error, Pearson’s correlation coefficient and Statistical Parametric Mapping. Inter-trial variability was on average higher for clinical patients in both models. Overall, the markerless system demonstrated similar gait patterns although hip and knee rotations were non-comparable. Pelvic anterior tilt was significantly underestimated. Significant differences especially in peak values at specific phases of the gait cycle were observed across all planes for all joints (more so for clinical patients than healthy subjects) as well as in the sagittal powers of the hip, knee and ankle. Theia3D markerless system offers great potential in gait analysis. This study brings awareness to potential clinical users and researchers where they can have confidence, as well as areas where caution should be exercised.

PMID:39587194 | DOI:10.1038/s41598-024-80499-8