Category: Nevin Manimala

Nat Commun. 2024 Feb 15;15(1):1404. doi: 10.1038/s41467-024-45674-5.

ABSTRACT

Multiple emulsions are usually stabilized by amphiphilic molecules that combine the chemical characteristics of the different phases in contact. When one phase is a liquid crystal (LC), the choice of stabilizer also determines its configuration, but conventional wisdom assumes that the orientational order of the LC has no impact on the stabilizer. Here we show that, for the case of amphiphilic polymer stabilizers, this impact can be considerable. The mode of interaction between stabilizer and LC changes if the latter is heated close to its isotropic state, initiating a feedback loop that reverberates on the LC in form of a complete structural rearrangement. We utilize this phenomenon to dynamically tune the configuration of cholesteric LC shells from one with radial helix and spherically symmetric Bragg diffraction to a focal conic domain configuration with highly complex optics. Moreover, we template photonic microparticles from the LC shells by photopolymerizing them into solids, retaining any selected LC-derived structure. Our study places LC emulsions in a new light, calling for a reevaluation of the behavior of stabilizer molecules in contact with long-range ordered phases, while also enabling highly interesting photonic elements with application opportunities across vast fields.

PMID:38360960 | DOI:10.1038/s41467-024-45674-5

Insights Imaging. 2024 Feb 16;15(1):49. doi: 10.1186/s13244-024-01613-y.

ABSTRACT

OBJECTIVE: To evaluate the added benefit of diffusion-weighted imaging (DWI) over clinical parameters in predicting kidney allograft function decline.

METHODS: Data from 97 patients with DWI of the kidney allograft were retrospectively analyzed. The DWI signals were analyzed with both the mono-exponential and bi-exponential models, yielding total apparent diffusion coefficient (ADC_T), true diffusion (D), pseudo-diffusion (D*), and perfusion fraction (fp). Three predictive models were constructed: Model 1 with clinical parameters, Model 2 with DWI parameters, and Model 3 with both clinical and DWI parameters. The predictive capability of each model was compared by calculating the area under the receiver-operating characteristic curve (AUROC).

RESULTS: Forty-five patients experienced kidney allograft function decline during a median follow-up of 98 months. The AUROC for Model 1 gradually decreased with follow-up time > 40 months, whereas Model 2 and Model 3 maintained relatively stable AUROCs. The AUROCs of Model 1 and Model 2 were not statistically significant. Multivariable analysis showed that the Model 3 included cortical D (HR = 3.93, p = 0.001) and cortical fp (HR = 2.85, p = 0.006), in addition to baseline estimated glomerular filtration rate (eGFR) and proteinuria. The AUROCs for Model 3 were significantly higher than those for Model 1 at 60-month (0.91 vs 0.86, p = 0.02) and 84-month (0.90 vs 0.83, p = 0.007) follow-up.

CONCLUSIONS: DWI parameters were comparable to clinical parameters in predicting kidney allograft function decline. Integrating cortical D and fp into the clinical model with baseline eGFR and proteinuria may add prognostic value for long-term allograft function decline.

CRITICAL RELEVANCE STATEMENT: Our findings suggested that cortical D and fp derived from IVIM-DWI increased the performance to predict long-term kidney allograft function decline. This preliminary study provided basis for the utility of multi-b DWI for managing patients with a kidney transplant.

KEY POINTS: • Both clinical and multi-b DWI parameters could predict kidney allograft function decline. • The ability to predict kidney allograft function decline was similar between DWI and clinical parameters. • Cortical D and fp derived from IVIM-DWI increased the performance to predict long-term kidney allograft function decline.

PMID:38360950 | DOI:10.1186/s13244-024-01613-y

Sci Rep. 2024 Feb 15;14(1):3845. doi: 10.1038/s41598-024-54502-1.

ABSTRACT

To assess the image quality parameters of dual-energy computed tomography angiography (DECTA) 40-, and 60 keV virtual monoenergetic images (VMIs) combined with deep learning-based image reconstruction model (DLM) and iterative reconstructions (IR). CT scans of 28 post EVAR patients were enrolled. The 60 s delayed phase of DECTA was evaluated. Objective [noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR)] and subjective (overall image quality and endoleak conspicuity – 3 blinded readers assessment) image quality analyses were performed. The following reconstructions were evaluated: VMI 40, 60 keV VMI; IR VMI 40, 60 keV; DLM VMI 40, 60 keV. The noise level of the DLM VMI images was approximately 50% lower than that of VMI reconstruction. The highest CNR and SNR values were measured in VMI DLM images. The mean CNR in endoleak in 40 keV was accounted for as 1.83 ± 1.2; 2.07 ± 2.02; 3.6 ± 3.26 in VMI, VMI IR, and VMI DLM, respectively. The DLM algorithm significantly reduced noise and increased lesion conspicuity, resulting in higher objective and subjective image quality compared to other reconstruction techniques. The application of DLM algorithms to low-energy VMIs significantly enhances the diagnostic value of DECTA in evaluating endoleaks. DLM reconstructions surpass traditional VMIs and IR in terms of image quality.

PMID:38360941 | DOI:10.1038/s41598-024-54502-1

Sci Rep. 2024 Feb 15;14(1):3848. doi: 10.1038/s41598-024-53053-9.

ABSTRACT

In the Americas, the fall armyworm (Spodoptera frugiperda) exists in two genetically distinct strains, the corn (C) and rice (R) strains. Despite their names, these strains are not associated with host plant preferences but have been shown to vary in pheromone composition and male responses. Recently, S. frugiperda was detected in Africa as an invasive species, but knowledge about variation in strain types, pheromone composition and inter-strain mating of populations of the pest in the continent has not been fully examined. Therefore, this study aimed to investigate variations, if any in the pheromone composition of female moths, male moth responses, and mating between C and R mitotypes of S. frugiperda populations in Kenya, as well as their geographic distribution. Strains (mitotypes) of S. frugiperda were identified using mitochondrial DNA (mtDNA) markers, and their pheromonal composition determined by coupled gas chromatography-mass spectrometric (GC-MS) analysis. Male moth responses to these compounds were evaluated using GC-electroantennographic detection (EAD), electroantennogram (EAG), and wind tunnel assays. Oviposition assays were used to determine whether R and C mitotype moths could mate and produce eggs. The results showed that both the R and C mitotypes were present, and there were no statistically significant differences in their distribution across all sampled locations. Five pheromone compounds including (Z)-7-dodecenyl acetate (Z7-12:OAc), (Z)-7-tetradecenyl acetate (Z7-14:OAc), (Z)-9-tetradecenyl acetate (Z9-14:OAc), (Z)-11-tetradecenyl acetate (Z11-14:OAc) and (Z)-11-hexadecenyl acetate (Z11-16:OAc), were detected in the pheromone glands of female moths of both mitotypes, with Z9-14:OAc being the most abundant. The relative percentage composition of Z9-14:OAc was similar in both mitotypes. However, the R mitotype had a 2.7 times higher relative percentage composition of Z7-12:OAc compared to the C mitotype moth, while the C mitotype moth had a 2.4 times higher relative percentage composition of Z11-16:OAc than the R mitotype moth. Male moths of both mitotypes exhibited similar responses to the pheromone compounds, showing the strongest responses to Z9-14:OAc and Z7-12:OAc in electrophysiological and behavioural assays. There was mating between R and C mitotypes with egg production comparable to mating within the same mitotype. Our results revealed that differences between the two S. frugiperda mitotypes are characterized by female moth pheromone composition rather than male moth responses to the pheromones, and that this does not prevent hybridisation between the mitotypes, which may have implications for their management.

PMID:38360933 | DOI:10.1038/s41598-024-53053-9

Sci Rep. 2024 Feb 15;14(1):3807. doi: 10.1038/s41598-024-52796-9.

ABSTRACT

Dengue fever, a prevalent and rapidly spreading arboviral disease, poses substantial public health and economic challenges in tropical and sub-tropical regions worldwide. Predicting infectious disease outbreaks on a countrywide scale is complex due to spatiotemporal variations in dengue incidence across administrative areas. To address this, we propose a machine learning ensemble model for forecasting the dengue incidence rate (DIR) in Brazil, with a focus on the population under 19 years old. The model integrates spatial and temporal information, providing one-month-ahead DIR estimates at the state level. Comparative analyses with a dummy model and ablation studies demonstrate the ensemble model’s qualitative and quantitative efficacy across the 27 Brazilian Federal Units. Furthermore, we showcase the transferability of this approach to Peru, another Latin American country with differing epidemiological characteristics. This timely forecast system can aid local governments in implementing targeted control measures. The study advances climate services for health by identifying factors triggering dengue outbreaks in Brazil and Peru, emphasizing collaborative efforts with intergovernmental organizations and public health institutions. The innovation lies not only in the algorithms themselves but in their application to a domain marked by data scarcity and operational scalability challenges. We bridge the gap by integrating well-curated ground data with advanced analytical methods, addressing a significant deficiency in current practices. The successful transfer of the model to Peru and its consistent performance during the 2019 outbreak in Brazil showcase its scalability and practical application. While acknowledging limitations in handling extreme values, especially in regions with low DIR, our approach excels where accurate predictions are critical. The study not only contributes to advancing DIR forecasting but also represents a paradigm shift in integrating advanced analytics into public health operational frameworks. This work, driven by a collaborative spirit involving intergovernmental organizations and public health institutions, sets a precedent for interdisciplinary collaboration in addressing global health challenges. It not only enhances our understanding of factors triggering dengue outbreaks but also serves as a template for the effective implementation of advanced analytical methods in public health.

PMID:38360915 | DOI:10.1038/s41598-024-52796-9

Evid Based Dent. 2024 Feb 15. doi: 10.1038/s41432-024-00985-w. Online ahead of print.

ABSTRACT

BACKGROUND: This systematic review investigates the association between peri-implantitis, an infectious/inflammatory disease sharing clinical and radiographic characteristics with periodontitis, and systemic inflammation.

DATA SOURCES: This study, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, systematically reviewed available evidence up to February 9, 2023. Searches were carried out across eight electronic databases (Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, Web of Science, Dentistry & Oral Sciences Source, Scopus, LILACS, and China Online), ClinicalTrials.gov, WHO International Clinical Trials Registry Platform (ICTRP), and gray literature.

STUDY SELECTION: The review encompasses human studies, including randomised controlled trials, non-randomised intervention studies, cohort studies, case-control, and cross-sectional studies, yielded 27 full-text articles, with 11 clinical studies meeting inclusion criteria, and 9 articles included in the meta-analysis.

DATA EXTRACTION AND SYNTHESIS: Two independent reviewers carried out data extraction using the PECOS /PICOS tool (Patients, Exposure, Comparison, Outcomes, Study designs). The evaluation of the quality and risk of bias in observational studies, randomised controlled trials, and non-randomised studies of interventions was conducted utilising the Newcastle-Ottawa Scale (NOS), the revised Cochrane tool (RoB 2), and the ROBINS-I tool, respectively. Qualitative and quantitative analyses, including weighted mean differences (WMDs) and standard mean differences (SMD), were conducted using Stata/MP 17.0. Heterogeneity was assessed with the Q-statistic method. Pooled estimates, addressing potential inter-study heterogeneity, were calculated with random effects models. Significance criteria were set at p < 0.05. Publication bias was examined via funnel plot and Egger’s test. Sensitivity analyses were predefined. Meta-analyses adhered to GRADE approach for inflammatory biomarkers/outcomes evaluation.

RESULTS: Patients with peri-implantitis exhibited elevated levels of serum C-reactive protein (CRP) (standard mean difference (SMD): 4.68, 98.7% CI: 2.12 to 7.25), interleukin-6 (IL-6) (weighted mean difference (WMD): 6.27 pg/mL, 0% CI: 5.01 to 7.54), and white blood cell counts (WMD: 1.16 * 103/mL, 0% CI: 0.61 to 1.70) compared to those without peri-implantitis.

CONCLUSIONS: The findings underscore a significant link between peri-implantitis and heightened systemic inflammation, emphasising the need for further research to elucidate the precise nature of this association.

PMID:38360889 | DOI:10.1038/s41432-024-00985-w

J Eat Disord. 2024 Feb 15;12(1):27. doi: 10.1186/s40337-024-00977-2.

ABSTRACT

BACKGROUND: Previous research has demonstrated that early weight gain in family-based treatment (FBT) is predictive of remission for adolescents with anorexia nervosa (AN). However, no published data has addressed if early weight gain is also predictive of reaching weight restoration (i.e., 95% EBW) in patients with avoidant/restrictive food intake disorder (ARFID). Furthermore, no studies have evaluated the performance of the statistical models used to predict weight restoration at the end of treatment. This study sought to examine whether early weight gain in ARFID is predictive of weight restoration at 20 weeks using ROC analysis. Additionally, this study assessed how accurately the model classified patients and what types of misclassifications occurred.

METHODS: Participants (n = 130, 57.7% cisgender female 70.0% white) received virtual outpatient FBT. Receiver operating characteristics (ROC) were used to predict successful weight restoration at end of treatment, using early weight gain as the predictor. Twenty weeks was considered as the end of treatment, to align with the definition of end of treatment in FBT clinical trials. ROC analyses demonstrated that gaining at least 6.2 pounds by week 5 of treatment was the strongest predictor of achieving 95% EBW at 20 weeks (AUC = 0.72 [0.63, 0.81]). ROC analyses misclassified 35% of patients; the most common misclassification was predicting that a patient would not achieve 95% EBW when they actually did (61.6%). A logistical regression model, which included the patients’ %EBW at admission in addition to early weight gain as a predictor, outperformed the ROC analyses (AUC = 0.90 [0.85, 0.95]) and provided additional context by showing the probability that a patient would succeed.

CONCLUSION: Taken together, research demonstrates that early weight gain is a useful predictor of 95% EBW at 20 weeks of treatment for patients with ARFID who require weight restoration. Furthermore, results suggest that statistical models need to take into account additional information, such as %EBW at admission, along with early weight gain in order to more accurately predict which patients will reach weight restoration at week 20.

PMID:38360833 | DOI:10.1186/s40337-024-00977-2

BMC Psychol. 2024 Feb 15;12(1):78. doi: 10.1186/s40359-024-01564-5.

ABSTRACT

INTRODUCTION: Researchers have shown various variables’ role in forming personality disorders (PD). This study aimed to assess the role of early maladaptive schema (EMS), attachment style (AS), and parenting style (PS) in discriminating between personality disorders and normal individuals.

METHODS: In this study, 78 personality disorder patients and 360 healthy volunteers aged 18-84 were selected using convenience sampling. They completed the Schema Questionnaire-Short Form (SQ-SF), Revised Adult Attachment Scale (RAAS), and Baumrind’s Parenting Styles Questionnaire (PSI). Data were analyzed using discriminant analysis with IBM SPSS 25.

RESULTS: The results showed higher mean scores in all early maladaptive schema domains, insecure attachment styles, and authoritarian parenting in the personality disorder group than in the normal group. Also, discriminant analyses revealed that the function was statistically significant and could distinguish between the two groups and a compound of essential variables, disconnection, impaired autonomy, and secure attachment, respectively, discriminating two groups. Given that all components were able to distinguish between the two groups.

CONCLUSION: Therefore, intervention based on these factors early in life may help reduce the characteristics of personality disorders. Also, considering the role of these factors, treatment protocols can be prepared.

PMID:38360823 | DOI:10.1186/s40359-024-01564-5

Sci Data. 2024 Feb 15;11(1):210. doi: 10.1038/s41597-024-03015-7.

ABSTRACT

Exosomes play a crucial role in intercellular communication and can be used as biomarkers for diagnostic and therapeutic clinical applications. However, systematic studies in cancer-associated exosomal nucleic acids remain a big challenge. Here, we developed ExMdb, a comprehensive database of exosomal nucleic acid biomarkers and disease-gene associations curated from published literature and high-throughput datasets. We performed a comprehensive curation of exosome properties including 4,586 experimentally supported gene-disease associations, 13,768 diagnostic and therapeutic biomarkers, and 312,049 nucleic acid subcellular locations. To characterize expression variation of exosomal molecules and identify causal factors of complex diseases, we have also collected 164 high-throughput datasets, including bulk and single-cell RNA sequencing (scRNA-seq) data. Based on these datasets, we performed various bioinformatics and statistical analyses to support our conclusions and advance our knowledge of exosome biology. Collectively, our dataset will serve as an essential resource for investigating the regulatory mechanisms of complex diseases and improving the development of diagnostic and therapeutic biomarkers.

PMID:38360815 | DOI:10.1038/s41597-024-03015-7

J Health Popul Nutr. 2024 Feb 15;43(1):27. doi: 10.1186/s41043-024-00523-5.

ABSTRACT

INTRODUCTION: Food security and nutrition have been severely impacted during the COVID-19 pandemic, particularly in low- and middle-income countries (LMICs). We aimed to quantify the impacts of the pandemic on food security and diet diversity within Chilanga District in Zambia and identify target areas for high-impact social protection and safety net programs.

METHODS: We conducted a cross-sectional study in Chilanga district immediately after the Omicron variant surge in February 2022. Diet quality and food security were assessed based on a household diet questionnaire and a Minimum Dietary Diversity-Women (MDD-W) score was calculated. A paired t-test was used to determine whether there was a statistically significant change in the MDD-W score and McNemar test was used to investigate the change in food security between the pre- and peri-COVID-19 period.

RESULTS: Compared to the pre-COVID-19 period, there were increases in food prices across the board in the peri-COVID-19 period and decreased consumption of key food categories including legumes, dairy and vitamin A rich foods. Despite high rates of food insecurity, only 6.6% of surveyed households received any cash or in-kind assistance from a government agency, non-profit, or other organization in the post-COVID-19 period.

CONCLUSION: The COVID-19 pandemic had significant impacts on food security and dietary diversity in Chilanga district. This is particularly relevant in the low-income communities that we surveyed, which had pre-existing challenges with food security. Additional resources must be invested in Chilanga District and similarly affected areas to address this gap in access to food and promote national equity. Trial Registration N/A.

PMID:38360811 | DOI:10.1186/s41043-024-00523-5