Ultrathin Oxide Films by Atomic Layer Deposition on Graphene

In this paper, a method is presented to create and characterize mechanically robust, free standing, ultrathin, oxide films with controlled, nanometer-scale thickness using Atomic Layer Deposition (ALD) on graphene. Aluminum oxide films were deposited onto suspended graphene membranes using ALD. Subsequent etching of the graphene left pure aluminum oxide films only a few atoms in thickness. A pressurized blister test was used to determine that these ultrathin films have a Young's modulus of 154 \pm 13 GPa. This Young's modulus is comparable to much thicker alumina ALD films. This behavior indicates that these ultrathin two-dimensional films have excellent mechanical integrity. The films are also impermeable to standard gases suggesting they are pinhole-free. These continuous ultrathin films are expected to enable new applications in fields such as thin film coatings, membranes and flexible electronics.Comment: Nano Letters (just accepted

Analysis of ocean internal waves imaged by multichannel reflection seismics, using ensemble empirical mode decomposition

Research on ocean internal waves using seismic oceanography is a frontier issue both for marine geophysicists and physical oceanographers. Images of the ocean water layer obtained by conventional processing of multichannel seismic reflection data can show the overall patterns of internal waves. However, in order to extract more information from the seismic data, new tools need to be developed. Here, we use the ensemble empirical mode decomposition (EEMD) method to decompose vertical displacement data from seismic sections and apply this method to a seismic section from the northeastern South China Sea, where clear internal waves are observed. Compared with the conventional empirical mode decomposition method, EEMD has greatly reduced the scale mixing problems induced in the decomposition results. The results obtained show that the internal waves in this area are composed of different characteristic wavelengths at different depths. The depth range of 200–1050 m contains internal waves with a wavelength of 1.25 km that are very well coupled in the vertical direction. The internal waves with a wavelength of 3 km, in the depth range of 200–600 m, are also well coupled, but in an oblique direction; this suggests that the propagation speed of internal waves of this scale changes with depth in this area. Finally, the internal waves with a wavelength of 6.5 km, observed in the depth range of 200–800 m, are separated into two parts with a phase difference of about 90◦, by a clear interface at a depth of 650 m; this allows us to infer an oblique propagation of wave energy of this scale.publishe

Enhancing nutritional management in peritoneal dialysis patients through a generative pre-trained transformers-based recipe generation tool: a pilot study

BackgroundPatients undergoing peritoneal dialysis (PD) often face nutritional deficiencies due to inadequate intake, nutrient loss, insufficient dialysis, and a state of micro-inflammatory. Traditional nutritional management methods have not fully met personalized needs. Therefore, this study aimed to develop and evaluate an application for generating recipes based on Generative Pre-trained Transformers to improve the nutritional status of these patients.MethodsThis self-controlled prospective study included 35 patients undergoing PD from January to February 2024. The study was divided into two phases: the initial phase involved conventional dietary education under PD management, followed by a second phase where a new GPT-based dietary guidance tool was introduced. Patients adhered to the diets recommended by the tool. Nutritional intervention effects were assessed by comparing serum prealbumin, albumin, and phosphate levels before and after the intervention.ResultsAfter the intervention, the mean prealbumin levels significantly improved from 289.04 ± 74.60 mg/L to 326.72 ± 78.89 mg/L (p = 0.001). Although there was no statistical significance, the serum albumin levels in patients increased from 34.70 ± 5.94 g/L to 35.66 ± 5.14 g/L (p = 0.153). Serum phosphate levels remained stable and within safe limits (p = 0.241).ConclusionThe AI-based recipe generation application significantly improved serum prealbumin levels in PD patients without causing adverse changes in phosphate levels, confirming its efficacy and safety in nutritional management for these patients. This study highlights the potential and practical value of AI technology in nutritional management for patients with chronic disease, providing important evidence for future clinical applications

Prescribed-time adaptive stabilization of high-order stochastic nonlinear systems with unmodeled dynamics and time-varying powers

In this paper, the control problem of prescribed-time adaptive neural stabilization for a class of non-strict feedback stochastic high-order nonlinear systems with dynamic uncertainty and unknown time-varying powers is discussed. The parameter separation technique, dynamic surface control technique, and dynamic signals were used to eradicate the influences of unknown time-varying powers together with state and input unmodeled dynamics, and to mitigate the computational intricacy of the backstepping. In a non-strict feedback framework, the radial basis function neural networks (RBFNNs) and Young's inequality were deployed to reconstruct the continuous unknown nonlinear functions. Finally, by establishing a new criterion of stochastic prescribed-time stability and introducing a proper bounded control gain function, an adaptive neural prescribed-time state-feedback controller was designed, ensuring that all signals of the closed-loop system were semi-global practical prescribed-time stable in probability. A numerical example and a practical example successfully validated the productivity and superiority of the control scheme

Interaction of influenza virus NS1 protein with growth arrest-specific protein 8

NS1 protein is the only non-structural protein encoded by the influenza A virus, and it contributes significantly to disease pathogenesis by modulating many virus and host cell processes. A two-hybrid screen for proteins that interact with NS1 from influenza A yielded growth arrest-specific protein 8. Gas8 associated with NS1 in vitro and in vivo. Deletion analysis revealed that the N-terminal 260 amino acids of Gas8 were able to interact with NS1, and neither the RNA-binding domain nor the effector domain of NS1 was sufficient for the NS1 interaction. We also found that actin, myosin, and drebrin interact with Gas8. NS1 and β-actin proteins could be co-immunoprecipitated from extracts of transfected cells. Furthermore, actin and Gas8 co-localized at the plasma membrane. These results are discussed in relation to the possible functions of Gas8 protein and their relevance in influenza virus release

Evaluation of the competence of an artificial intelligence-assisted colonoscopy system in clinical practice: A post hoc analysis

BackgroundArtificial intelligence-assisted colonoscopy (AIAC) has been proposed and validated in recent years, but the effectiveness of clinic application remains unclear since it was only validated in some clinical trials rather than normal conditions. In addition, previous clinical trials were mostly concerned with colorectal polyp identification, while fewer studies are focusing on adenoma identification and polyps size measurement. In this study, we validated the effectiveness of AIAC in the clinical environment and further investigated its capacity for adenoma identification and polyps size measurement.MethodsThe information of 174 continued patients who went for coloscopy in Chongqing Rongchang District People’s hospital with detected colon polyps was retrospectively collected, and their coloscopy images were divided into three validation datasets, polyps dataset, polyps/adenomas dataset (all containing narrow band image, NBI images), and polyp size measurement dataset (images with biopsy forceps and polyps) to assess the competence of the artificial intelligence system, and compare its diagnostic ability with endoscopists with different experiences.ResultsA total of 174 patients were included, and the sensitivity of the colorectal polyp recognition model was 99.40%, the accuracy of the colorectal adenoma diagnostic model was 93.06%, which was higher than that of endoscopists, and the mean absolute error of the polyp size measurement model was 0.62 mm and the mean relative error was 10.89%, which was lower than that of endoscopists.ConclusionArtificial intelligence-assisted model demonstrated higher competence compared with endoscopists and stable diagnosis ability in clinical use

The mutual interactions among Helicobacter pylori, chronic gastritis, and the gut microbiota: a population-based study in Jinjiang, Fujian

ObjectivesHelicobacter pylori (H. pylori) is a type of bacteria that infects the stomach lining, and it is a major cause of chronic gastritis (CG). H. pylori infection can influence the composition of the gastric microbiota. Additionally, alterations in the gut microbiome have been associated with various health conditions, including gastrointestinal disorders. The dysbiosis in gut microbiota of human is associated with the decreased secretion of gastric acid. Chronic atrophic gastritis (CAG) and H. pylori infection are also causes of reduced gastric acid secretion. However, the specific details of how H. pylori infection and CG, especially for CAG, influence the gut microbiome can vary and are still an area of ongoing investigation. The incidence of CAG and infection rate of H. pylori has obvious regional characteristics, and Fujian Province in China is a high incidence area of CAG as well as H. pylori infection. We aimed to characterize the microbial changes and find potential diagnostic markers associated with infection of H. pylori as well as CG of subjects in Jinjiang City, Fujian Province, China.ParticipantsEnrollment involved sequencing the 16S rRNA gene in fecal samples from 176 cases, adhering to stringent inclusion and exclusion criteria. For our study, we included healthy volunteers (Normal), individuals with chronic non-atrophic gastritis (CNAG), and those with CAG from Fujian, China. The aim was to assess gut microbiome dysbiosis based on various histopathological features. QIIME and LEfSe analyses were performed. There were 176 cases, comprising 126 individuals who tested negative for H. pylori and 50 who tested positive defined by C14 urea breath tests and histopathological findings in biopsies obtained through endoscopy. CAG was also staged by applying OLGIM system.ResultsWhen merging the outcomes from 16S rRNA gene sequencing results, there were no notable variations in alpha diversity among the following groups: Normal, CNAG, and CAG; OLGIM I and OLGIM II; and H. pylori positive [Hp (+)] and H. pylori negative [Hp (–)] groups. Beta diversity among different groups show significant separation through the NMDS diagrams. LEfSe analyses confirmed 2, 3, and 6 bacterial species were in abundance in the Normal, CNAG, and CAG groups; 26 and 2 species in the OLGIM I and OLGIM II group; 22 significant phylotypes were identified in Hp (+) and Hp (–) group, 21 and 1, respectively; 9 bacterial species exhibited significant differences between individuals with CG who were Hp (+) and those who were Hp (–).ConclusionThe study uncovered notable distinctions in the characteristics of gut microbiota among the following groups: Normal, CNAG, and CAG; OLGIM I and OLGIM II; and Hp (+) and Hp (–) groups. Through the analysis of H. pylori infection in CNAG and CAG groups, we found the gut microbiota characteristics of different group show significant difference because of H. pylori infection. Several bacterial genera could potentially serve as diagnostic markers for H. pylori infection and the progression of CG