A new mouse-fixation device for IOP measurement in awake mice.

Glaucoma is an irreversible blinding eye disease. The mechanisms underlying glaucoma are complex. Up to now, no successful remedy has been found to completely cure the condition. High intraocular pressure (IOP) is an established risk factor for glaucoma and the only known modifiable factor for glaucoma treatment. Mice have been widely used to study glaucoma pathogenesis. IOP measurement is an important tool for monitoring the potential development of glaucomatous phenotypes in glaucoma mouse models. Currently, there are two methods of IOP measurement in mice: invasive and non-invasive. As the invasive method can cause corneal damage and inflammation, and most of the noninvasive method involves the use of anesthetics. In the course of our research, we designed a mouse fixation device to facilitate non-invasive measurements of mouse IOPs. Using this device, mouse IOPs can be accurately measured in awake mice. This device will help researchers to accurately assess mouse IOP without the use of anesthetics.

Riveting technique in percutaneous balloon compression for trigeminal neuralgia remedy.

BACKGROUND: The percutaneous balloon compression (PBC) is a safe and simple treatment for trigeminal neuralgia. It works by compressing the Gasserian ganglion to block pain signals from the trigeminal nerve. To ensure effectiveness, it is important to focus the compression on the lower part of the balloon. OBJECTIVE: To validate the efficacy of a riveting technique, specifically pulling an inflated balloon, in order to apply enhanced compression on the ganglion. METHODS: To compare this novel technique with the conventional approach, a retrospective investigation was conducted on consecutive PBCs performed in our department between 2019 and 2022. For postoperative outcome assessment, efficacy was defined as achieving a VAS score of 0 or an improvement exceeding 5 points. Postoperative numbness was graded as none, mild, or severe based on its impact on daily life and tolerance level. RESULTS: Excluding cases with missed follow-up, a total of 179 participants were included in the study, and their follow-up period ranged up to 40 months. Postoperatively, symptomatic remission was achieved by 98.1% (52/53) of patients in the riveting technique group compared to 87.3% (110/126) in the conventional group (P<0.05). At the last follow-up period, with recurrence observed over time, the long-term efficacy of riveting and conventional groups were 94.3% and 74.6%, respectively (P<0.05). The majority of cases in both groups experienced ipsilateral facial numbness immediately following PBC, which appeared to diminish after 3 months in both groups without significant difference between them (P>0.05).

Influence of boundary layer jets on the vertical distribution of ozone in Guangdong, China.

The planetary boundary layer (PBL) characteristics during ozone (O3) episodes in China have been extensively studied; however, knowledge of the impact of boundary layer jets (BLJs) on O3 vertical distribution is limited. This study conducted a field campaign from 1 to 8 December 2020 to examine the vertical structure of the O3 concentration and wind velocity within the boundary layer at two sites (Foshan: FS, Maoming: MM) in Guangdong. Utilising lidar observations and the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), distinct spatial distribution patterns of O3 over FS and MM influenced by BLJs were identified. The BLJs at both locations exhibited pronounced diurnal variations with a nocturnal maximum exceeding 11 m/s at a height of approximately 500 m. The nocturnal enhancement of BLJs resulted from inertial oscillations coupled with diurnal thermal forcing over sloping terrain. A stronger BLJ at FS induced an evident uplift of O3 and the prevailing northeasterly wind facilitated the transport of O3 in the nocturnal residual layer from FS to MM. After sunrise, surface heating and the development of the PBL caused the air mass with elevated O3 levels in the residual layer to descend to ground level. At MM, calm surface winds, a weaker BLJ at 500 m height, and strong downdrafts collectively contributed to a significant increase in surface O3 concentration in subsequent days. These findings contribute to our understanding of the interactions between BLJs and variations in surface air pollutant concentrations, thereby providing important insights for future regional emissions control measures.

Top-Down Induced Crystallization Orientation toward Highly Efficient p-i-n Perovskite Solar Cells.

Crystallization orientation plays a crucial role in determining the performance and stability of perovskite solar cells (PVSCs), whereas effective strategies for realizing oriented perovskite crystallization is still lacking. Herein, a facile and efficient top-down strategy is reported to manipulate the crystallization orientation via treating perovskite wet film with propylamine chloride (PACl) before annealing. The PA+ ions tend to be adsorbed on the (001) facet of the perovskite surface, resulting in the reduced cleavage energy to induce (001) orientation-dominated growth of perovskite film and then reduce the temperature of phase transition, meanwhile, the penetrating Cl ions further regulate the crystallization process. As-prepared (001)-dominant perovskite films exhibit the ameliorative film homogeneity in terms of vertical and horizontal scale, leading to alleviated lattice mismatch and lowered defect density. The resultant PVSC devices deliver a champion power conversion efficiency (PCE) of 25.07% with enhanced stability, and the unencapsulated PVSC device maintains 95% of its initial PCE after 1000 h of operation at the maximum power point under simulated AM 1.5G illumination.

Body Composition and Clinical Outcomes in Esophageal Cancer Patients Treated with Immune Checkpoint Inhibitors.

BACKGROUND: Obesity is associated with increased mortality in various cancers, but the relationship between obesity and clinical outcomes in unresectable or recurrent esophageal cancer who receive immune checkpoint inhibitors (ICIs) remains unknown. This study investigated the association between body composition and clinical outcomes in patients with unresectable or recurrent esophageal cancer who received ICIs. METHODS: Utilizing an unbiased database of 111 unresectable or recurrent esophageal cancers, we evaluated the relationships between body composition (body mass index, waist circumference, psoas major muscle volume, and subcutaneous and visceral fat areas) at the initiation of ICI treatment and clinical outcomes including the disease control rate and progression-free survival (PFS). RESULTS: Waist circumference was significantly associated with the disease control rate at the first assessment (P = 0.0008). A high waist circumference was significantly associated with favorable PFS in patients treated with nivolumab. In an univariable model, for 5-cm increase of waist circumference in the outcome category of PFS, univariable hazard ratio (HR) was 0.73 (95% confidence interval [CI], 0.61-0.87; P = 0.0002). A multivariable model controlling for potential confounders yielded a similar finding (multivariable HR, 0.56; 95% CI, 0.33-0.94; P = 0.027). We observed the similar finding in esophageal cancer patients treated with pembrolizumab+CDDP+5-FU (P = 0.048). In addition, waist circumference was significantly associated with the prognostic nutritional index (P = 0.0073). CONCLUSIONS: A high waist circumference was associated with favorable clinical outcomes in ICI-treated patients with unresectable or recurrent esophageal cancer, providing a platform for further investigations on the relationships among body composition, nutrition, and the immune status.

Automatedly identify dryland threatened species at large scale by using deep learning.

Dryland biodiversity is decreasing at an alarming rate. Advanced intelligent tools are urgently needed to rapidly, automatedly, and precisely detect dryland threatened species on a large scale for biological conservation. Here, we explored the performance of three deep convolutional neural networks (Deeplabv3+, Unet, and Pspnet models) on the intelligent recognition of rare species based on high-resolution (0.3 m) satellite images taken by an unmanned aerial vehicle (UAV). We focused on a threatened species, Populus euphratica, in the Tarim River Basin (China), where there has been a severe population decline in the 1970s and restoration has been carried out since 2000. The testing results showed that Unet outperforms Deeplabv3+ and Pspnet when the training samples are lower, while Deeplabv3+ performs best as the dataset increases. Overall, when training samples are 80, Deeplabv3+ had the best overall performance for Populus euphratica identification, with mean pixel accuracy (MPA) between 87.31 % and 90.2 %, which, on average is 3.74 % and 11.29 % higher than Unet and Pspnet, respectively. Deeplabv3+ can accurately detect the boundaries of Populus euphratica even in areas of dense vegetation, with lower identification uncertainty for each pixel than other models. This study developed a UAV imagery-based identification framework using deep learning with high resolution in large-scale regions. This approach can accurately capture the variation in dryland threatened species, especially those in inaccessible areas, thereby fostering rapid and efficient conservation actions.

Learning Diverse Tone Styles for Image Retouching.

Image retouching, aiming to regenerate the visually pleasing renditions of given images, is a subjective task where the users are with different aesthetic sensations. Most existing methods adopt a deterministic model to learn the retouching style from a specific expert, making it less flexible to meet diverse subjective preferences. Besides, the intrinsic diversity of an expert due to the targeted processing of different images is also deficiently described. To circumvent such issues, we propose to learn diverse image retouching with normalizing flow-based architectures. Unlike current flow-based methods which directly generate the output image, we argue that learning in a one-dimensional style space could 1) disentangle the retouching styles from the image content, 2) lead to a stable style presentation form, and 3) avoid the spatial disharmony effects. For obtaining meaningful image tone style representations, a joint-training pipeline is delicately designed, which is composed of a style encoder, a conditional RetouchNet, and the image tone style normalizing flow (TSFlow) module. In particular, the style encoder predicts the target style representation of an input image, which serves as the conditional information in the RetouchNet for retouching, while the TSFlow maps the style representation vector into a Gaussian distribution in the forward pass. After training, the TSFlow can generate diverse image tone style vectors by sampling from the Gaussian distribution. Extensive experiments on MIT-Adobe FiveK and PPR10K datasets show that our proposed method performs favorably against state-of-the-art methods and is effective in generating diverse results to satisfy different human aesthetic preferences. Source codeterministic and pre-trained models are publicly available at https://github.com/SSRHeart/TSFlow.

Personalized Machine Learning-Coupled Nanopillar Triboelectric Pulse Sensor for Cuffless Blood Pressure Continuous Monitoring.

A wearable system that can continuously track the fluctuation of blood pressure (BP) based on pulse signals is highly desirable for the treatments of cardiovascular diseases, yet the sensitivity, reliability, and accuracy remain challenging. Since the correlations of pulse waveforms to BP are highly individualized due to the diversity of the patients' physiological characteristics, wearable sensors based on universal designs and algorithms often fail to derive BP accurately when applied on individual patients. Herein, a wearable triboelectric pulse sensor based on a biomimetic nanopillar layer was developed and coupled with Personalized Machine Learning (ML) to provide accurate and continuous monitoring of BP. Flexible conductive nanopillars as the triboelectric layer were fabricated through soft lithography replication of a cicada wing, which could effectively enhance the sensor's output performance to detect weak signal characteristics of pulse waveform for BP derivation. The sensors were coupled with a personalized Partial Least-Squares Regression (PLSR) ML to derive unknown BP based on individual pulse characteristics with reasonable accuracy, avoiding the issue of individual variability that was encountered by General PLSR ML or formula algorithms. The cuffless and intelligent design endow this ML-sensor as a highly promising platform for the care and treatments of hypertensive patients.

A novel web-based calculator to predict 30-day all-cause in-hospital mortality for 7,202 elderly patients with heart failure in ICUs: a multicenter retrospective cohort study in the United States.

Background and aims: Heart failure (HF) is a significant cause of in-hospital mortality, especially for the elderly admitted to intensive care units (ICUs). This study aimed to develop a web-based calculator to predict 30-day in-hospital mortality for elderly patients with HF in the ICU and found a relationship between risk factors and the predicted probability of death. Methods and results: Data (N = 4450) from the MIMIC-III/IV database were used for model training and internal testing. Data (N = 2,752) from the eICU-CRD database were used for external validation. The Brier score and area under the curve (AUC) were employed for the assessment of the proposed nomogram. Restrictive cubic splines (RCSs) found the cutoff values of variables. The smooth curve showed the relationship between the variables and the predicted probability of death. A total of 7,202 elderly patients with HF were included in the study, of which 1,212 died. Multivariate logistic regression analysis showed that 30-day mortality of HF patients in ICU was significantly associated with heart rate (HR), 24-h urine output (24h UOP), serum calcium, blood urea nitrogen (BUN), NT-proBNP, SpO2, systolic blood pressure (SBP), and temperature (P < 0.01). The AUC and Brier score of the nomogram were 0.71 (0.67, 0.75) and 0.12 (0.11, 0.15) in the testing set and 0.73 (0.70, 0.75), 0.13 (0.12, 0.15), 0.65 (0.62, 0.68), and 0.13 (0.12, 0.13) in the external validation set, respectively. The RCS plot showed that the cutoff values of variables were HR of 96 bmp, 24h UOP of 1.2 L, serum calcium of 8.7 mg/dL, BUN of 30 mg/dL, NT-pro-BNP of 5121 pg/mL, SpO2 of 93%, SBP of 137 mmHg, and a temperature of 36.4°C. Conclusion: Decreased temperature, decreased SpO2, decreased 24h UOP, increased NT-proBNP, increased serum BUN, increased or decreased SBP, fast HR, and increased or decreased serum calcium increase the predicted probability of death. The web-based nomogram developed in this study showed good performance in predicting 30-day in-hospital mortality for elderly HF patients in the ICU.

LESO: A ten-year ensemble of satellite-derived intercontinental hourly surface ozone concentrations.

This study presents a novel ensemble of surface ozone (O3) generated by the LEarning Surface Ozone (LESO) framework. The aim of this study is to investigate the spatial and temporal variation of surface O3. The LESO ensemble provides unique and accurate hourly (daily/monthly/yearly as needed) O3 surface concentrations on a fine spatial resolution of 0.1◦ × 0.1◦ across China, Europe, and the United States over a period of 10 years (2012-2021). The LESO ensemble was generated by establishing the relationship between surface O3 and satellite-derived O3 total columns together with high-resolution meteorological reanalysis data. This breakthrough overcomes the challenge of retrieving O3 in the lower atmosphere from satellite signals. A comprehensive validation indicated that the LESO datasets explained approximately 80% of the hourly variability of O3, with a root mean squared error of 19.63 µg/m3. The datasets convincingly captured the diurnal cycles, weekend effects, seasonality, and interannual variability, which can be valuable for research and applications related to atmospheric and climate sciences.

Lumbar Endoscopic Unilateral Laminotomy With Bilateral Decompression Surgery in Severe Lumbar Stenosis Under Electrophysiological Monitoring-Focused on Full-Visualized Trephine/Osteotome.

OBJECTIVE: Although endoscopic drill has the advantages in manipulation and hemostasis, whose low efficiency and blurred vision reduce the efficacy of lumbar endoscopic unilateral laminotomy with bilateral decompression (LE-ULBD). The present study was designed to evaluate the safety and efficacy of full-visualized trephine/osteotome in the LE-ULBD surgery for severe lumbar stenosis. METHODS: Fifty-seven severe lumbar stenosis patients who underwent LE-ULBD between January 2020 to January 2023 were enrolled, who were divided into drill and visualized trephine groups. The medical records including demographics, operative duration, intraoperative electrophysiological findings, postoperative hospital stay or hospital stay, postoperative outcomes and complications were retrospectively reviewed and analyzed. RESULTS: A total of 57 patients included 15 in drill and 42 in trephine group were enrolled in the study. There was significant difference in the pre- and postoperative visual analogue scale and Oswestry Disability Index scores in both groups (p < 0.05). The mean operative duration in the trephine group (101.05 ± 12.18 minutes) was shorter than that in the drill group (134.67 ± 9.68 minutes) (p < 0.05). There was no statistical difference between the 2 groups in electrophysiological monitoring, posthospital stays, postoperative outcomes and complications. Abnormal free-electromyography (EMG) were recorded in 2 (13.3%) and 5 patients (11.9%) in the drill and trephine group. Intraoperative somatosensory evoked potential changes occurred in 3 (20%) and 3 patients (7.1%) in the drill and trephine group and all patients recovered immediately when surgery ended. No serious complications and recurrence occurred in all the patients. CONCLUSION: Full-visualized trephine/osteotome has been approved to be convenient, safe and efficient in our study, which combined with translaminar inside-out technique and EMG monitoring especially free-EMG may offer a new choice in LE-ULBD surgery for lumbar stenosis patients.

Characteristics of secondary inorganic aerosols and contributions to PM2.5 pollution based on machine learning approach in Shandong Province.

Primary emissions of particulate matter and gaseous pollutants, such as SO2 and NOx have decreased in China following the implementation of a series of policies by the Chinese government to address air pollution. However, controlling secondary inorganic aerosol pollution requires attention. This study examined the characteristics of the secondary conversion of nitrate (NO3-) and sulfate (SO42-) in three coastal cities of Shandong Province, namely Binzhou (BZ), Dongying (DY), and Weifang (WF), and an inland city, Jinan (JN), during December 2021. Furthermore, the Shapley Additive Explanation (SHAP), an interpretable attribution technique, was adopted to accurately calculate the contributions of secondary formations to PM2.5. The nitrogen oxidation rate exhibited a significant dependence on the concentration of O3. High humidity facilitates sulfur oxidation. Compared to BZ, DY, and WF, the secondary conversion of NO3- and SO42- was more intense in JN. The light-gradient boosting model outperformed the random forest and extreme-gradient boosting models, achieving a mean R2 value of 0.92. PM2.5 pollution events in BZ, DY, and WF were primarily attributable to biomass burning, whereas pollution in Jinan was contributed by the secondary formation of NO3- and vehicle emissions. Machine learning and the SHAP interpretable attribution technique offer a precise analysis of the causes of air pollution, showing high potential for addressing environmental concerns.

Surface Modification Functionalized Carbon Dots.

Carbon dots (CDs) smaller than 10 nm constitute a new type of fluorescent carbon-based nanomaterial. They have attracted much attention owing to their unique structures and excellent photoelectric properties. Primitive CDs usually comprise carbon and oxygen and are synthesized in one step from various natural products or synthetic organic compounds, usually via microwave or hydrothermal methods. However, the uniformity of surface functional groups often make CDs lack the diversity of active sites required for specific applications. Therefore, the functionalization of CDs by specific groups is a powerful strategy for improving their photophysical and photochemical properties. This paper reviews surface modification strategies to overcome these shortcomings. Functionalizing CDs using covalent or non-covalent modification can give them unique properties and broaden their applicability.

Highly Efficient Perovskite/Organic Tandem Solar Cells Enabled by Mixed-Cation Surface Modulation.

Perovskite/organic tandem solar cells (POTSCs) are gaining attention due to their easy fabrication, potential to surpass the S-Q limit, and superior flexibility. However, the low power conversion efficiencies (PCEs) of wide bandgap (Eg) perovskite solar cells (PVSCs) have hindered their development. This work presents a novel and effective mixed-cation passivation strategy (CE) to passivate various types of traps in wide-Eg perovskite. The complementary effect of 4-trifluoro phenethylammonium (CF3 -PEA+ , denoted as CA+ ) and ethylenediammonium (EDA2+ , denoted as EA2+ ) reduces both electron/hole defect densities and non-radiative recombination rate, resulting in a record open-circuit voltage (Voc ) of wide-Eg PVSCs (1.35 V) and a high fill factor (FF) of 83.29%. These improvements lead to a record PCE of 24.47% when applied to fabricated POTSCs, the highest PCE to date. Furthermore, unencapsulated POTSCs exhibit excellent photo and thermal stability, retaining over 90% of their initial PCE after maximum power point (MPP) tracking or exposure to 60 °C for 500 h. These findings imply that the synergic effect of surface passivators is a promising strategy to achieve high-efficiency and stable wide-Eg PVSCs and corresponding POTSCs.

A deep registration method for accurate quantification of joint space narrowing progression in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that leads to progressive articular destruction and severe disability. Joint space narrowing (JSN) has been regarded as an important indicator for RA progression and has received significant attention. Radiology plays a crucial role in the diagnosis and monitoring of RA through the assessment of joint space. A new framework for monitoring joint space by quantifying joint space narrowing (JSN) progression through image registration in radiographic images has emerged as a promising research direction. This framework offers the advantage of high accuracy; however, challenges still exist in reducing mismatches and improving reliability. In this work, we utilize a deep intra-subject rigid registration network to automatically quantify JSN progression in the early stages of RA. In our experiments, the mean-square error of the Euclidean distance between the moving and fixed images was 0.0031, the standard deviation was 0.0661 mm and the mismatching rate was 0.48%. Our method achieves sub-pixel level accuracy, surpassing manual measurements significantly. The proposed method is robust to noise, rotation and scaling of joints. Moreover, it provides misalignment visualization, which can assist radiologists and rheumatologists in assessing the reliability of quantification, exhibiting potential for future clinical applications. As a result, we are optimistic that our proposed method will make a significant contribution to the automatic quantification of JSN progression in RA. Code is available at https://github.com/pokeblow/Deep-Registration-QJSN-Finger.git.

Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain.

Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.

The Value of a Headless Pear Shape in Percutaneous Balloon Compression for Trigeminal Neuralgia.

BACKGROUND AND OBJECTIVES: Percutaneous balloon compression (PBC) has been regarded as a simple and effective remedy for trigeminal neuralgia. This study aims to retrospectively analyze the correlation between intraoperative balloon shapes and postoperative outcomes. METHOD: Those consecutive PBC cases performed in our department between 2019 and 2022 were reviewed. According to the intraoperative balloon figures, they were cataloged as headless pear, slim pear, bottle gourd, and winter melon groups. The degree of pain or numbness was quantified using the visual analog scale. Those pain-free or pain score <3 and satisfied by the patient were called effective, and those numb score >3 were taken into account of numbness incidence. RESULTS: Except for missing cases, 160 were finally recruited in this study with a mean follow-up for 23.6 ± 12.8 months. Postoperatively, the pain score plunged from 8.8 ± 1.0 to 0.8 ± 2.0 immediately, which rose slightly over time and maintained at 2.4 ± 3.1. The maximal pain score drop occurred in the headless pear group ( P < .001) and the minimal in the winter melon group ( P < .001). The early efficacy of PBC was 100%, 84.1%, 91.4%, and 50.0%, respectively. However, the long-term efficacy was 88.2%, 75.0%, 82.1% and 25.0%. The ipsilateral numbness occurred in most of the cases immediately after PBC with a score of 3.5 ± 2.3, which decreased significantly within 3 months to 2.3 ± 2.0 and turned to 1.7 ± 1.8 finally ( P < .05). The highest and lowest numb score appeared in bottle gourd and winter melon groups, respectively ( P < .05). CONCLUSION: A headless pear shape emerged in lateral fluoroscopy as the balloon was fully inflated indicates that the entire Meckel cave is suffused, and hence, the anterior semilunar ganglion has been solidly compressed, which may lead to a successful outcome.

Development of a prediction model for the risk of 30-day unplanned readmission in older patients with heart failure: A multicenter retrospective study.

BACKGROUND AND AIM: Heart failure (HF) imposes significant global health costs due to its high incidence, readmission, and mortality rate. Accurate assessment of readmission risk and precise interventions have become important measures to improve health for patients with HF. Therefore, this study aimed to develop a machine learning (ML) model to predict 30-day unplanned readmissions in older patients with HF. METHODS AND RESULTS: This study collected data on hospitalized older patients with HF from the medical data platform of Chongqing Medical University from January 1, 2012, to December 31, 2021. A total of 5 candidate algorithms were selected from 15 ML algorithms with excellent performance, which was evaluated by area under the operating characteristic curve (AUC) and accuracy. Then, the 5 candidate algorithms were hyperparameter tuned by 5-fold cross-validation grid search, and performance was evaluated by AUC, accuracy, sensitivity, specificity, and recall. Finally, an optimal ML model was constructed, and the predictive results were explained using the SHapley Additive exPlanations (SHAP) framework. A total of 14,843 older patients with HF were consecutively enrolled. CatBoost model was selected as the best prediction model, and AUC was 0.732, with 0.712 accuracy, 0.619 sensitivity, and 0.722 specificity. NT.proBNP, length of stay (LOS), triglycerides, blood phosphorus, blood potassium, and lactate dehydrogenase had the greatest effect on 30-day unplanned readmission in older patients with HF, according to SHAP results. CONCLUSIONS: The study developed a CatBoost model to predict the risk of unplanned 30-day special-cause readmission in older patients with HF, which showed more significant performance compared with the traditional logistic regression model.

Acute effects of different exercise forms on executive function and the mechanism of cerebral hemodynamics in hospitalized T2DM patients: a within-subject study.

Objective: This study aimed to investigate the acute effects of aerobic exercise (AE), resistance exercise (RE), and integrated concurrent exercise (ICE; i.e., AE plus RE) on executive function among hospitalized type 2 diabetes mellitus (T2DM) inpatients, and the mechanism of cerebral hemodynamics. Methods: A within-subject design was applied in 30 hospitalized patients with T2DM aged between 45 and 70 years in the Jiangsu Geriatric Hospital, China. The participants were asked to take AE, RE, and ICE for 3 days at 48-h intervals. Three executive function (EF) tests, namely, Stroop, More-odd shifting, and 2-back tests, were applied at baseline and after each exercise. The functional near-infrared spectroscopy brain function imaging system was used to collect cerebral hemodynamic data. The one-way repeated measurement ANOVA was used to explore training effects on each test indicator. Results: Compared with the baseline data, the EF indicators have been improved after both ICE and RE (p < 0.05). Compared with the AE group, the ICE and RE groups have demonstrated significant improvements in inhibition (ICE: MD = - 162.92 ms; RE: MD = -106.86 ms) and conversion functions (ICE: MD = -111.79 ms; RE: MD = -86.95 ms). Based on the cerebral hemodynamic data, the beta values of brain activation in executive function related brain regions increased after three kinds of exercise, the EF improvements after the ICE showed synchronous activation of blood flow in the dorsolateral prefrontal cortex (DLPFC), the frontal polar (FPA) and orbitofrontal cortex (OFC), the improvement of inhibitory function after RE displayed synchronous activation of DLPFC and FPA, and AE mainly activates DLPFC. The HbO2 concentration in the pars triangularis Broca's area increased significantly after AE, but the EF did not improve significantly. Conclusion: The ICE is preferred for the improvements of executive function in T2DM patients, while AE is more conducive to the improvements of refresh function. Moreover, a synergistic mechanism exists between cognitive function and blood flow activation in specific brain regions.

Vertically molybdenum disulfide nanosheets on carbon cloth using CVD by controlling growth atmosphere for electrocatalysis.

Molybdenum disulfide (MoS2) has been deemed as one of the promising noble-metal-free electrocatalysts for hydrogen evolution reaction (HER), but it suffers from the inert basal plane and low electronic conductivity. Regulating the morphology of MoS2during the synthesis on conductive substrates is a synergistic strategy for enhancing the HER performance. In this work, vertical MoS2nanosheets were fabricated on carbon cloth (CC) using an atmospheric pressure chemical vapor deposition method. The growth process could be effectively tuned through introducing hydrogen gas during vapor deposition process, resulting in nanosheets with increased edge density. The mechanism for edge-enriching through controlling the growth atmosphere is systematically studied. The as-prepared MoS2exhibits excellent HER activity due to the combination of optimized microstructures and coupling with CC. Our findings provide new insights to design advanced MoS2-based electrocatalysts for HER.