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The prognostic value of dynamic body mass index (BMI) changes during hospitalization in surgical intensive care unit (ICU) patients admitted emergently remains unclear. This study aimed to investigate the association between in-hospital BMI change and 28-day mortality in this high-risk population. This retrospective cohort study utilized data from the eICU Collaborative Research Database (2014-2015). A total of 20,543 adult surgical ICU patients admitted via the emergency department (ED) were included. BMI change was calculated as discharge BMI minus admission BMI. Multivariable Cox regression, restricted cubic splines, and subgroup analyses were employed to evaluate the association between BMI change and mortality. The 28-day ICU mortality was 4.70%. BMI change exhibited a U-shaped, non-linear association with death: risk declined modestly as BMI rose toward the nadir of -1.75 kg/m , then increased sharply thereafter. Each additional kg/m above this threshold raised mortality by 9% (HR 1.09, 95% CI 1.05-1.12,  < 0.0001). Patients in the highest BMI-gain quartile faced a 52% higher risk than those in the lowest quartile (HR 1.52, 95% CI 1.27-1.82, p < 0.0001). Dynamic BMI change outperformed static BMI or weight measures (AUC 57.9). In-hospital BMI change is a significant predictor of 28-day mortality in surgical ICU patients admitted via the ED. A moderate reduction in BMI (-1.75 kg/m ) was associated with the lowest mortality risk. Dynamic BMI monitoring may enhance risk stratification and guide personalized fluid management in this population.

Homogenously dispersing single-walled carbon nanotubes (SWNTs) in solvents has been one critical step towards exploiting their exceptional properties in high-performance components. However, the solubility of SWNTs is severely limited by the inert tube surfaces and strong tube-tube van der Waals attractions. Starting with carbon nanotubides, i.e., negatively charged SWNTs reduced by alkali metals, we herein propose a sonication-free approach to prepare an aqueous dispersion of SWNTs. The approach combines the spontaneous dissolution of nanotubides in polar aprotic solvents with polyvinylpyrrolidone wrapping and dialysis in deionized H2O, which results in well-dispersed, neutralized SWNTs. The gelation of concentrated SWNT dispersion leads to the formation of hydrogels, which is subsequently transformed into SWNT aerogels through lyophilization. The prepared SWNT aerogels exhibit high-mass-sorption capacities for organic solvent absorption, paving the way towards harvesting the extraordinary properties of SWNTs.

In Taiwan, the aerial part of (Al) is used in the form of herbal tea or in a folk remedy primarily to mitigate inflammatory conditions in the lungs and liver. Due to the excellent health benefits of Al against inflammation, it has become increasingly crucial and in great demand during the COVID-19 pandemic. However, Al has been found to be adulterated with , , and/or because of similarities in appearance and vernacular names. This study aimed to develop a PCR-RFLP DNA molecular method for the authentication of Al. The restriction enzyme I was used according to the sequencing and alignment results of PCR products in the ITS2 regions of Al and its adulterants. Gel electrophoresis resulted in the clear separation of Al and its adulterants into two distinct categories. In conclusion, the PCR-RFLP authentication method developed herein provides an easy, rapid, and accurate method to distinguish Al from its adulterants to assure user health and safety.

Accumulating evidence has shown that patients with inflammatory bowel disease (IBD) have liver function abnormalities and are susceptible to liver diseases. However, the existence of a causal relationship between IBD and liver function or disease remains unclear. A two-sample Mendelian randomization (MR) analysis was performed using genetic associations from publicly available genome-wide association studies (GWAS). These associations encompass ulcerative colitis (UC), Crohn's disease (CD), liver function traits, and liver disease phenotypes. The liver function traits comprised hepatic biochemistries, percent liver fat, and liver iron content from the UK Biobank. Furthermore, the liver disease phenotypes included cholelithiasis, non-alcoholic fatty liver disease (NAFLD), primary sclerosing cholangitis (PSC), and primary biliary cholangitis (PBC) in cohorts of European ancestry. The primary estimation used the inverse-variance weighted method, with GWAS of C-reactive protein (CRP) in the UK Biobank serving as a positive control outcome. Genetically predicted UC is causally associated with decreased levels of albumin (ALB) and liver iron content, while genetically predicted CD is causally associated with increased levels of alkaline phosphatase (ALP). Moreover, genetically predicted UC or CD increases the risk of PSC, and CD increases the risk of PBC. Neither UC nor CD causally increases the risk of cholelithiasis and NAFLD. UC affects the levels of ALB and liver iron content, while CD affects the levels of ALP. Both UC and CD increase the risk of PSC, and CD increases the risk of PBC.

Aims To design a model to predict the early prognosis of patients with traumatic brain injury (TBI) based on parameters that can be quickly obtained in emergency conditions from medical history, physical examination, and supplementary examinations. Methods The medical records of TBI patients who were hospitalized in two medical institutions between June 2015 and June 2021 were collected and analyzed. Patients were divided into the training set, validation set, and testing set. The possible predictive indicators were screened after analyzing the data of patients in the training set. Then prediction models were found based on the possible predictive indicators in the training set. Data of patients in the validation set and the testing set was provided to validate the predictive values of the models. Results Age, Glasgow coma scale score, Apolipoprotein E genotype, damage area, serum C‐reactive protein, and interleukin‐8 (IL‐8) levels, and Marshall computed tomography score were found associated with early prognosis of TBI patients. The accuracy of the early prognosis prediction model (EPPM) was 80%, and the sensitivity and specificity of the EPPM were 78.8% and 80.8% in the training set. The accuracy of the EPPM was 79%, and the sensitivity and specificity of the EPPM were 66.7% and 86.2% in the validation set. The accuracy of the early EPPM was 69.1%, and the sensitivity and specificity of the EPPM were 67.9% and 77.8% in the testing set. Conclusion Prediction models integrating general information, clinical manifestations, and auxiliary examination results may provide a reliable and rapid method to evaluate and predict the early prognosis of TBI patients. By analyzing the admission information and examination results of patients with traumatic brain injury (TBI), the factors that may affect the early prognosis of patients with TBI were obtained. Then these factors are combined by mathematics to establish a prediction model to implement the effective prediction of early prognosis of patients with TBI. The results show that this idea is feasible.

Aim To establish an artery and venous sinus occlusion image score (AVOIS) which is compatible in both cerebral arteries and venous system diseases. Methods A total of 188 consecutive patients with the final diagnosis of anterior circulation infarct (ACI) and 56 consecutive patients with cerebral venous and sinus thrombosis (CVST) were retrospectively studied. The AVOIS was developed based on the severity of occlusive changes of main intracranial arteries and venous sinuses (present = 0, partial occlusion = 1, absent = 2), and divided into four groups (CVST group: 0, 1‐5, 6‐10, >10. ACI group: 0, 1‐5, 6‐10, >10) arbitrarily. A receiver operating characteristic (ROC) curve was applied to discover the sensitivity and specificity of AVOIS. The National Institutes of Health Stroke Scale (NIHSS), Clot Burden Score (CBS) were set as the reference. Logistic regression models were developed to adjust for baseline clinical variables and AVOIS. Length of hospital stay (LOS) was also evaluated using the Kaplan‐Meier estimator. Results For the CVST group, a positive correlation between AVOIS and NIHSS was discovered (Spearman's ρ = 0.54, p < 0.001). For the ACI group, ROC showed relatively high sensitivity (84.8%) and specificity (81.8%). Besides, the probability of time to discharge was significantly different among the AVOIS subgroups as well (p < 0.001). Conclusion The AVOIS can be used to evaluate the treatment of patients with acute stroke caused by cerebral venous sinus thrombosis and anterior circulation large vessel occlusion. It is a reliable and convenient method that may help prompt prognosis and guide the treatment of individual patients. A novel score system called the Artery and Venous Sinus Occlusion Image Score (AVOIS) was developed based on quantification analysis of the intracranial thrombus in both artery and venous sinus (Table 1). According to the CTA or MRA, anterior circulation and venous sinuses were allotted different scores (present = 0, partial occlusion = 1, absent = 2) by researchers. The total score on AVOIS in anterior circulation or venous sinus was accumulated to 14 points.

Anodic oxygen evolution reaction (OER) is recognized as kinetic bottleneck in water electrolysis. Transition metal sites with high valence states can accelerate the reaction kinetics to offer highly intrinsic activity, but suffer from thermodynamic formation barrier. Here, we show subtle engineering of highly oxidized Ni 4+ species in surface reconstructed (oxy)hydroxides on multicomponent FeCoCrNi alloy film through interatomically electronic interplay. Our spectroscopic investigations with theoretical studies uncover that Fe component enables the formation of Ni 4+ species, which is energetically favored by the multistep evolution of Ni 2+ →Ni 3+ →Ni 4+ . The dynamically constructed Ni 4+ species drives holes into oxygen ligands to facilitate intramolecular oxygen coupling, triggering lattice oxygen activation to form Fe-Ni dual-sites as ultimate catalytic center with highly intrinsic activity. As a result, the surface reconstructed FeCoCrNi OER catalyst delivers outstanding mass activity and turnover frequency of 3601 A g metal −1 and 0.483 s −1 at an overpotential of 300 mV in alkaline electrolyte, respectively. Electrocatalytic water oxidation is facilitated by high valence states, but these are challenging to achieve at low applied potentials. Here, authors report a multicomponent FeCoCrNi alloy with dynamically formed Ni 4+ species to offer high catalytic activity via lattice oxygen activation mechanism.

With the rapid development of artificial intelligence, machine learning is gradually becoming popular for predictions in all walks of life. In meteorology, it is gradually competing with traditional climate predictions dominated by physical models. This survey aims to consolidate the current understanding of Machine Learning (ML) applications in weather and climate prediction—a field of growing importance across multiple sectors, including agriculture and disaster management. Building upon an exhaustive review of more than 20 methods highlighted in existing literature, this survey pinpointed eight techniques that show particular promise for improving the accuracy of both short-term weather and medium-to-long-term climate forecasts. According to the survey, while ML demonstrates significant capabilities in short-term weather prediction, its application in medium-to-long-term climate forecasting remains limited, constrained by factors such as intricate climate variables and data limitations. Current literature tends to focus narrowly on either short-term weather or medium-to-long-term climate forecasting, often neglecting the relationship between the two, as well as general neglect of modeling structure and recent advances. By providing an integrated analysis of models spanning different time scales, this survey aims to bridge these gaps, thereby serving as a meaningful guide for future interdisciplinary research in this rapidly evolving field.

Photothermoelectric materials have important applications in many fields. Here, we joined a silver nanostructure film and a carbon nanotube film by van der Waals force to form a heterojunction, which shows excellent photothermal and photoelectric conversion properties. The local temperature difference and the output photovoltage increase rapidly when the heterojunction is irradiated by lasers with wavelengths ranging from ultraviolet to terahertz. The maximum temperature difference reaches 215.9 K, which is significantly higher than that of other photothermoelectric materials reported in the literature. The photothermal and photoelectric responsivity depend on the wavelength of lasers, which are 175~601 K W -1 and 9.35~40.4 mV W -1 , respectively. We demonstrate that light absorption of the carbon nanotube is enhanced by local surface plasmons, and the output photovoltage is dominated by Seebeck effect. The proposed heterostructure can be used as high-efficiency sensitive photothermal materials or as ultra-wideband fast-response photoelectric materials. Finding efficient photothermoelectric materials remains critical to the development of clean and renewable energy conversion technologies. Here, authors prepare a silver nanostructure film/carbon nanotube film heterojunction with excellent photothermal and photoelectric conversion performance.

Solar‐driven overall water splitting based on metal sulfide semiconductor photocatalysts remains as a challenge owing to the strong charge recombination and deficient catalytic active sites. Additionally, significant inhibition of back reactions, especially the oxidation of sulfide ions during the photocatalytic water oxidation catalysis, is an arduous task that requires an efficient photogenerated hole transfer dynamics. Here, a ternary dumbbell‐shaped catalyst based on RuO2/CdS/MoS2 with spatially separated catalytic sites is developed to achieve simultaneous production of hydrogen and oxygen under simulated solar‐light without any sacrificial agents. Particularly, MoS2 nanosheets anchored on the two ends of CdS nanowires are identified as a reduction cocatalyst to accelerate hydrogen evolution, while RuO2 nanoparticles as an oxidation cocatalyst are deposited onto the sidewalls of CdS nanowires to facilitate oxygen evolution kinetics. The density functional theory simulations and ultrafast spectroscopic results reveal that photogenerated electrons and holes directionally migrate to MoS2 and RuO2 catalytic sites, respectively, thus achieving efficient charge carrier separation. The design of ternary dumbbell structure guarantees metal sulfides against photocorrosion and thus extends their range in solar water splitting. The ternary dumbbell‐like RuO2/CdS/MoS2 photocatalyst with selective attachment of reduction and oxidation cocatalysts enables water splitting into H2 and O2. The critical aspect is the spatially separated distribution of MoS2 and RuO2 dual cocatalysts, which not only achieves photogenerated electron–hole pairs separation, but also protects CdS from photocorrosion by holes.