Tag: pubmed

J Dent Educ. 2024 Nov 15. doi: 10.1002/jdd.13785. Online ahead of print.

ABSTRACT

PURPOSE: To compare the educational outcomes of remote instruction (RI) in impression-taking using smart glasses with those of face-to-face instruction (FI) and paper-based self-learning (SL) and analyze the educational effects, aiming to develop a remote clinical training strategy.

METHODS: Participants were recruited from among the dental residents who were trained in the first-year clinical program at the university hospital in 2023. The participants were divided into three groups as the original skill level was equal, and the groups were assigned RI, FI, printed guidance, and SL. All the participants took impressions of the jaw models attached to the mannequin using alginate impression material. Next, assigned instructions were provided. Then again, the trainees took impressions of the jaw models. The pre- and postinstruction impressions of each participant were evaluated, and the change in the impression score was statistically analyzed.

RESULTS: The pre- and postinstruction scores of the trainees in the RI and FI groups showed a significant increase (p < 0.05), whereas no significant difference was observed in the score changes in the SL group. In the intergroup comparisons, the score changes of the RI and FI groups were greater than those of the SL group, although no significant difference was found between the score changes of the RI and FI groups (p < 0.05).

CONCLUSION: RI in impression-taking using smart glasses has a greater educational effectiveness than paper-based SL. It has also been suggested that RI can have educational efficacy similar to FI.

PMID:39548350 | DOI:10.1002/jdd.13785

Sci Rep. 2024 Nov 15;14(1):28176. doi: 10.1038/s41598-024-79999-4.

ABSTRACT

Low fertility is not conducive to healthy population development. The total fertility rate (TFR) is influenced by the education expansion (measured by the proportion of non-student women, NSP), marriage delay (measured by the proportion of married women, MP), and marital fertility rate (MFR). This study decomposes the TFR change into the changes in NSP, MP, and MFR using China’s census and 1% population sample survey data. During 1990-2020, the changes in NSP, MP, and MFR contributed – 22%, – 90%, and 12%, respectively, to the changes in TFR. The continuous decline in NSP reduced the TFR, and the intensity continued to increase over time. As the primary negative driving force, the rapid decline in MP also consistently reduced the TFR. The marital fertility rate had a downward effect on the TFR before 2000 and an upward effect after 2000. The effects of NSP, MP, and MFR on the TFR varied with the birth order, age and region (among cities, towns, and villages). In summary, China’s TFR has considerably changed in combination with changes in NSP, MP, and MFR. Without effective measures, China’s TFR may further decline into the lowest-low fertility trap.

PMID:39548321 | DOI:10.1038/s41598-024-79999-4

Sci Rep. 2024 Nov 15;14(1):28178. doi: 10.1038/s41598-024-79921-y.

ABSTRACT

Colorectal cancer in Brazil is among the main public health concern. The burden of disease can be related to unhealthy lifestyle behavior and inequality in access to health services. The aim of this study was to identify the main factors associated with colorectal cancer mortality in Brazil. This is an ecological study that had the Brazilian Federal Units as the primary units of analysis. Colorectal cancer mortality data (ICD C18-C21) were obtained from Brazilian national mortality system to the year 2020. Prevalence of overweight, food consumption (fiber, whole grains and red meat), physical inactivity, smoke, alcohol consumption, the median of household income, years of study, rates of cancer treatment units and oncologist by Brazilian Federal Units were considered as factor associated to the colorectal cancer mortality. Quasipoisson Generalized Linear Models were used to associate CRC mortality and variables related to dietary intake, risk behavior, and access to health services. In 2020, there were 21,501 deaths by colorectal cancer (51% among women). Prevalence of overweight (men: IRR 1.03; CI: 1.01-1.04; women IRR 1.05; CI 1.02-1.08) and the density of oncologist (men: IRR 1.02; CI: 1.01-1.03; women IRR 1.02; CI 1.01-1.03) were the main factors associated with colorectal cancer mortality. Sociodemographic and food consumption characteristics were not statistically associated with CRC. Prevalence of overweight was the strongest factor associated with mortality from colorectal cancer in Brazil in 2020. Therefore, current public policies to reduce overweight and obesity should be prioritized and strengthened in Brazil.

PMID:39548314 | DOI:10.1038/s41598-024-79921-y

Sci Rep. 2024 Nov 15;14(1):28230. doi: 10.1038/s41598-024-79727-y.

ABSTRACT

This research explores the design of an infrared (IR) photodetector using mercury cadmium telluride (Hg_1-xCd_xTe). It proposes two- and three-dimensional homojunction models based on p⁺-Hg_0.7783Cd_0.2217Te/n^–-Hg_0.7783Cd_0.2217Te, focusing on applications in the long-wavelength infrared range. The photodetector’s performance is analyzed using Silvaco ATLAS TCAD software and compared with analytical calculations based on drift-diffusion, tunneling, and Chu’s approximation techniques. Optimized for operation at 10.6 μm wavelength under liquid nitrogen temperature, the proposed photodetector demonstrates promising optoelectronic characteristics including the dark current density of 0.20 mA/cm², photocurrent density of 4.98 A/cm², and photocurrent density-to-dark current density ratio of 2.46 × 10⁴, a 3-dB cut-off frequency of 104 GHz, a rise time of 0.8 ps, quantum efficiency of 58.30 %, peak photocurrent responsivity of 4.98 A/W, specific detectivity of 3.96 × 10¹¹ cmHz^1/2/W, and noise equivalent power of 2.52 × 10^-16 W/Hz^1/2 indicating its potential for low-noise, high-frequency and fast-switching applications. The study also incorporates machine learning regression models to validate simulation results and provide a predictive framework for performance optimization, evaluating these models using various statistical metrics. This comprehensive approach demonstrates the synergy between advanced materials science and computational techniques in developing next-generation optoelectronic devices. By combining theoretical modeling, simulation, and machine learning, the research highlights the potential to accelerate progress in IR detection technology and enhance device performance and efficiency. This multidisciplinary methodology could serve as a model for future studies in optoelectronics, illustrating how advanced materials and computational methods can be utilized to enhance device capabilities.

PMID:39548271 | DOI:10.1038/s41598-024-79727-y

J Perinatol. 2024 Nov 15. doi: 10.1038/s41372-024-02161-5. Online ahead of print.

ABSTRACT

OBJECTIVES: Characterize the relationship between infant outcomes and prenatal homelessness, food insecurity and unemployment.

STUDY DESIGN: California live births between 22- and 44-weeks’ gestation comprised 6,089,327 pregnancies (2007-2020). Data were collected from linked Vital Statistics and hospital discharge records. Prenatal homelessness, food insecurity, and unemployment were classified as health-related social needs (HRSN) using International Classification of Disease codes in delivery records. Risk ratios for preterm birth, low birthweight, small for gestational age, neonatal intensive care unit admission, emergency department admission, rehospitalization, and death were estimated using log-linear Poisson regression adjusted for birthing person race, payer, and education.

RESULTS: 65.7 per 100,000 births had HRSN. These infants had a higher risk of preterm birth (aRR 2.7), low birthweight (aRR 2.7), SGA (aRR 1.5), NICU admission (aRR 3.5), and death (aRR 3.0).

CONCLUSIONS: HRSN increase the risk of infant morbidity and mortality but remain underreported in administrative records, making definitive conclusions difficult.

PMID:39548269 | DOI:10.1038/s41372-024-02161-5

Sci Rep. 2024 Nov 15;14(1):28185. doi: 10.1038/s41598-024-79571-0.

ABSTRACT

Acute hydrocephalus is a severe complication that may occur early after an intracerebral hemorrhage (ICH). However, clinical factors predicting the occurrence of acute hydrocephalus have rarely been studied. This study aimed to establish a nomogram model to predict early acute hydrocephalus after ICH. We retrospectively analyzed the data of 930 patients with ICH who were treated at our hospital between January 2017 and May 2024. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to screen for risk factors for acute hydrocephalus, and stepwise logistic regression analysis was used to construct the prediction model, which was visualized using a nomogram. Data were randomly divided into training (n = 652) and test (n = 278) sets at a 7:3 ratio. A total of 930 patients were included, of whom 123 (13.2%) developed acute hydrocephalus within 6 h of being diagnosed with ICH. Univariate analysis revealed that 11 indicators were associated with acute hydrocephalus. In the training set, LASSO and stepwise logistic regression analyses identified four independent risk factors that were used to establish a prediction model. These were the modified Graeb score, age, infratentorial hemorrhage > 15 mL, and thalamic hemorrhage > 15 mL. A graphical nomogram was then developed. The area under the receiver operating characteristic (ROC) curve was 0.974 (95% confidence interval 0.961-0.987). In the Hosmer-Lemeshow test, the p-value was 0.887. The mean absolute error of the calibration plot was 0.012. The decision curve analysis (DCA) validated the fitness and clinical application value of this nomogram. Internal validation showed the test set was in good accordance with the training set. The nomogram prediction model showed good accuracy and could be used to predict the risk of early acute hydrocephalus after ICH, thereby aiding neurologist in making rapid clinical decisions.

PMID:39548258 | DOI:10.1038/s41598-024-79571-0

Sci Rep. 2024 Nov 15;14(1):28245. doi: 10.1038/s41598-024-79486-w.

ABSTRACT

Acute-on-chronic liver failure (ACLF) is a syndrome characterized by the acute decompensation of chronic liver disease, resulting in organ failure and high short-term mortality. The progression of ACLF is dynamic and reversible in a considerable proportion of patients during hospitalization. Early detection and accurate assessment of ACLF are essential; however, ideal methods for this purpose are still lacking. Therefore, this study aimed to develop a new score for predicting the onset of ACLF in patients with various chronic liver diseases.A total of 6,188 patients with various chronic liver diseases were included in the study. Clinical and laboratory data were collected, and the occurrence of ACLF within 28 days was recorded. The Lasso-Cox regression method was employed to develop prediction models for the onset of ACLF at 7, 14, and 28 days. Among 5,221 patients without ACLF, 477 progressed to ACLF within 28 days. Seven predictors were identified as significantly associated with the occurrence of ACLF at 7, 14, and 28 days. A new scoring system was developed as follows: [NEUT ≥ 7, 10⁹/L; 1 or 0] × 0.49 + [PLT < 100, 10⁹/L; 1 or 0] × 0.44 + [TBIL ≥ 35, µmol/L; 1 or 0] × 0.05 + [HDL-C < 0.5, mmol/L; 1 or 0] × 1.04 – Ln[Hb, g/L] × 0.89 + [BUN > 7, mmol/L; 1 or 0] × 0.51 + Ln[INR] × 0.87 + 3.40. This new score demonstrated superior discrimination, with the C-indexes of 0.958, 0.944, and 0.938 at 7, 14, and 28 days, respectively, outperforming those of four other scores (CLIF-C-ACLF-Ds, MELD, MELD-Na, and CLIF-C-ADs score; all P < 0.001). Additionally, the new score improved in predictive accuracy, time-dependent receiver operating characteristics, probability density function evaluations, and calibration curves, making it highly predictive for the onset of ACLF at all time points. The optimal cut-off value of 9.6 effectively distinguished between high- and low-risk patients for ACLF onset. These findings were further validated in a separate cohort of patients. A new progressive score, based on seven predictors, has been developed to accurately forecast the occurrence of ACLF within 7, 14, and 28 days in patients with various chronic liver diseases. This tool may be utilized to identify high-risk patients, tailor follow-up management, and guide the escalation of care, prognostication, and transplant evaluation.

PMID:39548240 | DOI:10.1038/s41598-024-79486-w

Sci Rep. 2024 Nov 15;14(1):28107. doi: 10.1038/s41598-024-79477-x.

ABSTRACT

In this study, polymer composite nanofibers and thin membranes were synthesized using Carbon Nanotubes (CNTs) and Zinc Oxide (ZnO) as fillers in a Polyvinyl Alcohol (PVA) matrix, aiming to evaluate their electrical and mechanical properties. The composite nanofibers and thin membranes were prepared by incorporating different weight ratios of CNTs and ZnO into the PVA matrix using electrospinning and solution casting techniques, respectively. Solutions were prepared by mixing specific weight ratios of PVA, ZnO, and CNTs, followed by magnetic stirring and ultrasonication for homogenization. Electrospinning was performed at 20 kV with a syringe-to-collector distance of 14.5 cm at flow rate of 2.4 ml/hr. The composites were characterized using FTIR spectroscopy and Scanning Electron Microscopy (SEM). The PVA/5%ZnO/0.5%CNT composite exhibited the highest dielectric constant of 10.3 at high frequencies, while PVA/5%CNT showed the highest capacitance of 31.1 pF at 2 MHz. The maximum AC conductivity of 2.72 × 10^{– 7}S/m was also observed for the PVA/5%ZnO/0.5%CNT composite. Mechanical testing revealed significant improvements in Young’s modulus, stress yield, and load yield, with PVA/5%CNT achieving a Young’s modulus of 387.12 MPa and a stress yield of 6.92 MPa. The addition of ZnO and CNT fillers resulted in enhanced electrical and mechanical properties, making these composites suitable for applications in microelectronic devices and packaging materials.

PMID:39548235 | DOI:10.1038/s41598-024-79477-x

Eye (Lond). 2024 Nov 15. doi: 10.1038/s41433-024-03454-x. Online ahead of print.

ABSTRACT

This systematic review and network meta-analysis (NMA) focuses on comparing monovision and bilateral multifocal lenses (bMFIOL) implantation methods in treating presbyopia, a common age-related condition often seen in post-cataract surgery patients. This review focuses on evaluating the efficacy, user satisfaction and limitations of these two approaches through direct or indirect comparison. A comprehensive search was conducted in Medline, Embase, and Cochrane library, considering studies up to 15 July 2022, with direct or indirect comparisons between any monovision and bMFIOL implantation with bilateral cataract surgery. The study protocol has been published in the International Prospective Register of Systematic Reviews (PROSPERO, CRD42022340257). Thirty-two studies (3082 patients) were included in the NMA for the primary outcome, complete post-operative spectacle independence. NMA showed monovision to be inferior to bMFIOLs, as bMFIOL was more likely to provide complete spectacle independence (RR = 2.06, 95% CI = 1.34 to 3.15, p = 0.002) compared to monovision. Monovision resulted in less glare compared to bMFIOL (RR = 0.343, 95% CI = 0.181 to 0.651, p = 0.001). There was no statistically significant difference between monovision and bMFIOL for binocular unadjusted distance visual acuity (MD = 70.01, 95% CI = -19.88 to 4.60, p = 0.437) and binocular unadjusted near visual acuity (MD = 5.46, 95% CI = -5.24 to 10.94, p = 0.191). When compared to monovision, bMFIOL provided greater complete spectacle independence at the expense of greater glare. This study was limited by data heterogeneity, and further studies with standardized reporting would be useful.

PMID:39548216 | DOI:10.1038/s41433-024-03454-x

Sci Rep. 2024 Nov 15;14(1):28154. doi: 10.1038/s41598-024-78924-z.

ABSTRACT

The rapid changes in the shipping fleet during the last decades has increased the ship-induced loads and, thus, their impact on infrastructures, margin protections and ecosystems. Primary waves have been pointed out as the cause of those impacts, with heights that can exceed 2 m and periods around 2 minutes. Consequently, extensive literature can be found on their estimation mainly from a deterministic perspective with methods based on datasets limited to one location, making difficult their generalization. These studies propose either computationally expensive numerical models or empirical equations which often underestimate the extreme primary waves, hindering their use for design purposes. Moreover, a framework to allow the design of infrastructure under ship-wave attack based on probabilistic concepts such as return periods is still missing. In this study, a probabilistic model based on bivariate copulas is proposed to model the joint distribution of the primary wave height, the peak of the total energy flux, the ship length, the ship width, the relative velocity of the ship and the blockage factor. This model, a vine-copula, is developed and validated for four different deployments along the Savannah river (USA), with different locations and times. To do so, the model is quantified using part of the data in one deployment and validated using the rest of the data from this deployment and data of the other three. The vine-copula is validated from both a predictive performance point of view and with respect to the statistical properties. We prove that the probabilistic dependence of the data is preserved spatially and temporally in the Savannah river.

PMID:39548207 | DOI:10.1038/s41598-024-78924-z