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Objective: To investigate the stability of Acorus tatarinowii and Atractylodes lancea essential oils (ATaAL-EO) under a hot environment at 60 °C, and to analyze the differences in component, quantity, and quality changes, as well as variations in the main components, under different treatment methods of crude oil, β-cyclodextrin inclusion of ATaAL-EO, and Pickering emulsion, to improve the stability and quality of ATaAL-EO. Methods: The stability of the ATaAL-EO group, the β-cyclodextrin inclusion ATaAL-EO group, and the Pickering emulsion group were investigated under a 60 °C heat environment. Volatile oil retention rate and peroxide value were collected and measured. The volatile oil components of each group were determined by GC-MS, and t-tests were used to screen for differential components. PCA plots for each group were constructed using the OmicShare online platform. Line plots were generated using the Rmisc and reshape2 packages. Upset Venn diagrams under different hot environments were created using the OmicShare online platform to identify quantitative and qualitative changing components and heat map stack plots for newly generated compounds and connected line plots for disappearing compounds were produced for each group. Boxplots for the main component compounds under different hot environments were generated using the reshape2 and ggplot2 packages. Results: In a hot environment of 60 °C, the β-cyclodextrin inclusion ATaAL-EO and Pickering emulsion group with 1, 3, and 8 h of placement showed higher retention and lower oxidation degree compared to the stability of the ATaAL-EO group. GC-MS analysis results showed that the stability of volatile components in the Pickering emulsion group and β-cyclodextrin inclusion ATaAL-EO group was significantly improved compared to the crude oil group. Conclusion: β-cyclodextrin inclusion complexes with ATaAL-EO, as well as Pickering emulsions, can significantly enhance the stability and quality of ATaAL-EO. Pickering emulsions have more advantages.

Summary: Background: Liver cirrhosis (LC) is the highest risk factor for hepatocellular carcinoma (HCC) development worldwide. The efficacy of the guideline-recommended surveillance methods for patients with LC remains unpromising. Methods: A total of 4367 LCs not previously known to have HCC and 510 HCCs from 16 hospitals across 11 provinces of China were recruited in this multi-center, large-scale, cross-sectional study. Participants were divided into Stage Ⅰ cohort (510 HCCs and 2074 LCs) and Stage Ⅱ cohort (2293 LCs) according to their enrollment time and underwent Tri-phasic CT/enhanced MRI, US, AFP, and cell-free DNA (cfDNA). A screening model called PreCar Score was established based on five features of cfDNA using Stage Ⅰ cohort. Surveillance performance of PreCar Score alone or in combination with US/AFP was evaluated in Stage Ⅱ cohort. Findings: PreCar Score showed a significantly higher sensitivity for the detection of early/very early HCC (Barcelona stage A/0) in contrast to US (sensitivity of 51.32% [95% CI: 39.66%–62.84%] at 95.53% [95% CI: 94.62%–96.38%] specificity for PreCar Score; sensitivity of 23.68% [95% CI: 14.99%–35.07%] at 99.37% [95% CI: 98.91%–99.64%] specificity for US) (P

Background: There is currently no consensus regarding the optimal perioperative antiplatelet strategy for carotid artery surgery. This multicentre study aimed to analyse the association between preoperative aspirin monotherapy following postoperative dual antiplatelet therapy (DAPT) and the risk for stroke and death after carotid endarterectomy (CEA). Methods: This cohort study included 821 patients with carotid artery stenosis who underwent CEA. Primary outcomes included any stroke or death up to the one-month postoperative follow-up. Multilevel multivariate regression analyses and descriptive statistics were performed. Results: Patients were predominantly male (53 %), with a mean age of 66.2 years. The primary outcome occurred in 1.6 % of patients. Univariate and multivariate analyses revealed that patients with chronic obstructive pulmonary disease (COPD) exhibited a high risk for stroke or death (P = 0.011). The occurrence of any local complications in the neck was accompanied by an increase in diastolic blood pressure (DBP) (P = 0.007). Patients with a high systolic blood pressure (SBP) (P = 0.002) experienced a longer operative duration. The length of hospital stay was longer in the patients with COPD (P = 0.020), minor stroke (P = 0.011), and major stroke (P = 0.001). A positive linear correlation was found between SBP and operative duration in the overall population (β 0.4 [95 % confidence interval (CI) 0.1–0.7]; P = 0.002). The resultant curve for DBP and any local complications in the neck exhibited a two-stage change and one breakpoint in the entire population (k = 68 mmHg,

Objective: This study was designed to delve into the complexities involved in diagnosing of benign and malignant bone tumors and to assess the potential of AI technologies like ChatGPT in improving diagnostic accuracy and efficiency. The study also explores the few-shot learning as a method to optimize ChatGPT's performance in specialized medical domains such as benign and malignant bone tumors diagnosis. Methods: A total of 1366 benign and malignant bone tumors-related imaging reports were collected and diagnosed by 25 experienced physicians. The gold standard of diagnosis was established by combining clinical, imaging and pathological principles.These reports were then input into the ChatGPT model which underwent a few-shot learning method to generate diagnostic results. The diagnostic results of the physicians and the AI model were compared to evaluate the performance of ChatGPT. An experiment was conducted to assess the influence of different radiologist's reporting styles on the model's diagnostic performance. Furthermore, in-depth analysis of misdiagnosed cases was carried out, categorizing diagnostic errors and exploring possible causes. Results: The diagnostic results generated by ChatGPT showed an accuracy of 0.73, sensitivity of 0.95, and specificity of 0.58. After few-shot learning, ChatGPT demonstrated significant improvement, achieving an accuracy of 0.87, sensitivity of 0.99, and specificity of 0.73, bringing it much closer to the level of physician diagnostics. In an experiment analyzing the influence of the radiologist's reporting style, the model demonstrated higher sensitivity when interpreting reports written by high-level radiologists. In 56 benign cases, ChatGPT misdiagnosed them as malignant. Among these, 35 benign lesions- fibrous dysplasia and osteofibrous dysplasia- were incorrectly identified as metastatic tumors or osteosarcomas; 8 cases of myositis ossificans were wrongly diagnosed as extraosseous osteosarcoma. 7 cases of giant cell tumor of bone at the end of long bone were misdiagnosed as osteosarcoma by intermediate doctors. Chondroblastoma was misdiagnosed as malignant tumor in 6 cases −2 osteosarcoma and 4 chondrosarcoma-In this study, 23 osteosarcoma cases were misdiagnosed by ChatGPT as osteomyelitis; Chondrosarcoma was misdiagnosed as fibrous dysplasia or aneurysmal bone cyst in 8 cases. Four cases of spinal chordoma were misdiagnosed as spinal tuberculosis. Conclusion: Our findings highlight the potential of ChatGPT in the diagnosis of benign and malignant bone tumors, offering advantages like enhanced efficiency and a reduction in missed diagnoses. However, the necessity of collaborative interactions between physicians and ChatGPT in practical settings was underscored. With an examination into AI's capacity in benign and malignant bone tumors diagnosis, this study lays the groundwork for future AI advancements in medicine. Additionally, the benefits of few-shot learning in fine-tuning ChatGPT applications in specialized fields were also demonstrated.

Long-range multi-purpose cluster munitions with reconnaissance, identification, strike and evaluation functions are widely used, and a large number of unexploded submunitions will be generated on the surface, which will greatly hinder the battlefield maneuver, deployment and depth attack. Due to its special visual characteristics, surface unexploded submunitions use imaging technology and deep learning technology for long-distance, large-area, non-contact rapid and accurate detection and recognition. This paper introduces the common methods of unexploded submunition detection and their advantages and disadvantages, summarizes the imaging characteristics of unexploded submunitions under different imaging technology conditions and their identification and positioning methods, analyzes the signifi-cant advantages of deep learning in the field of unexploded submunition detection and recognition. Then, a UAV-borne rapid detection, identification and positioning method based on deep learning for surface unexploded submunitions is proposed.

Snow algal blooms have a remarkable climatic or environmental effect through influencing the snow–albedo feedback, accelerating the melting of surface snow, and amplifying global warming. Snow algal blooms occurred frequently on King George Island, Antarctic, during the recent six austral summers (December to next February) through 2017–2022. Based on an assessment of satellite images, this study found that the range and amount of snow algal blooms in the summers of 2018, 2020, 2021 and 2022 are relatively larger than in the summers of 2017 and 2019. Whether meteorological conditions have shaped the year-to-year variation of algal bloom intensities is analyzed through observational composite. The results suggest that during the strong bloom summers there exist prevailing northerly or northwesterly wind anomalies which advect warm and humid airmass from the southern ocean into the island, increasing surface air temperature and humidity; the warmer and more humid surface favors melting of snow and an increase of low cloud cover, subsequently enhancing the atmospheric downward long-wave radiation and amplifying surface warmth; the increased low cloud cover reflects more ultraviolet rays back to space and weakens the short-wave radiation reaching the surface. All these factors together favor to a stronger bloom. In comparison, during 2017 and 2019 there exist weak southerly wind anomalies which induce the northward advection of cold and dry air from the Antarctic Continent and favor the cooler surface. Consequently, it is unfavorable for the snow algal bloom. Based on these results, a snow algal bloom potential index (API) integrating the meteorological conditions is constructed, and its future trend is projected based on the EC-Earth3 run attending the CMIP6 under SSP245 and SSP585. A significant increasing trend is projected especially under SSP585. Thus snow algal bloom on King George Island will become more frequent and stronger in future. This implies a potential accelerate melting of ice shelf over Antarctic Peninsula.

Abstract Soft fluidic robots have attracted a lot of attention and have broad application prospects. However, poor fluidic power source and easy to damage have been hindering their development, while the lack of intelligent self-protection also brings inconvenience to their applications. Here, we design diversified self-protection soft fluidic robots that integrate soft electrohydrodynamic pumps, actuators, healing electrofluids, and E-skins. We develop high-performance soft electrohydrodynamic pumps, enabling high-speed actuation and large deformation of untethered soft fluidic robots. A healing electrofluid that can form a self-healed film with excellent stretchability and strong adhesion is synthesized, which can achieve rapid and large-areas-damage self-healing of soft materials. We propose multi-functional E-skins to endow robots intelligence, making robots realize a series of self-protection behaviors. Moreover, our robots allow their functionality to be enhanced by the combination of electrodes or actuators. This design strategy enables soft fluidic robots to achieve their high-speed actuation and intelligent self-protection, opening a door for soft robots with physical intelligence.

Objective Posterior wall (PW) fractures were sometimes associated in both‐column acetabular fractures. How to evaluate pre‐operatively the necessity for the performance of the posterior approach was an issue to be solved. In order to solve this issue, the computer‐assisted virtual surgery technique was used to evaluate if the involved PW in both‐column acetabular fractures (BACF) should be managed through posterior approach and verify the feasibility of this method. Methods Data of a consecutive cohort of 72 patients with both‐acetabular fractures from January 2012 to January 2020 was collected for retrospective study, of which 44 patients had concomitant acetabular PW fractures, and patients without PW fractures were labeled as the BCAF group. Computer‐assisted virtual surgery technique was performed pre‐operatively to evaluate the necessity for performance of posterior approach in 44 patients, and posterior approach was required if more than 3 mm of displacement was still present in the reduced 3D model. The 23 patients without treatment through posterior approach were labeled as the BCAF‐PW− group, and the 21 patients with treatment through posterior approach were labeled as the BCAF‐PW+ group. Operation‐related and post‐operative parameters were recorded. The quality of reduction and functional outcomes were assessed by the Matta scoring system and modified Merle d'Aubigné and Postel scoring system. The measurement data were analyzed using the t‐test of independent samples and rank‐sum test of ranked data between every two groups. Also, the one‐way analysis of variance (ANOVA) was used to analyze data between the three groups. Results Comparing operation‐related and post‐operative parameters in the three groups, some PW fractures in both‐column acetabular fractures could be ignored, and which could be evaluated pre‐operatively for necessity of an additional posterior approach. Operative time (271.2 ± 32.8 mins) and intra‐operative blood loss (1176.7 ± 211.1 mL) were significantly higher in the BCAF‐PW+ group. The excellent/good of reduction (25/28 of the BCAF group, 21/23 of the BCAF‐PW− group, 19/21 of the BCAF‐PW+ group) and functional outcomes (24/28 of the BCAF group, 18/23 of the BCAF‐PW− group, 18/21 of the BCAF‐PW+ group) of three groups were similar. The incidence of complications, such as deep vein thrombosis (4/28 of the BCAF group >3/23 of the BCAF‐PW− group >1/21 of the BCAF‐PW+ group) and injury of lateral femoral cutaneous nerve (3/23 of the BCAF‐PW− group >2/28 of the BCAF group >0/21 of the BCAF‐PW+ group), was no significant difference. Conclusion The partial both‐column acetabular fractures with PW involvement could be managed through a single anterior approach without another posterior approach by evaluation of computer‐assisted virtual surgery technique.

Reliable and economical energy storage technologies are urgently required to ensure sustainable energy supply. Hydrogen (H2) is an energy carrier that can be produced environment-friendly by renewable power to split water (H2O) via electrochemical cells. By this way, electric energy is stored as chemical energy of H2, and the storage can be large-scale and economical. Among the electrochemical technologies for H2O electrolysis, solid oxide electrolysis cells (SOECs) operated at temperatures above 500 ℃ have the benefits of high energy conversion efficiency and economic feasibility. In addition to the H2O electrolysis, SOECs can also be employed for CO2 electrolysis and H2O–CO2 co-electrolysis to produce value-added chemicals of great economic and environmental significance. However, the SOEC technology is not yet fully ready for commercial deployment because of material limitations of the key components, such as electrolytes, air electrodes, and fuel electrodes. As is well known, the reactions in SOEC are, in principle, inverse to the reactions in solid oxide fuel cells (SOFCs). Component materials of SOECs are currently adopted from SOFC materials. However, their performance stability issues are evident, and need to be overcome by materials development in line with the unique requirements of the SOEC materials. Key topics discussed in this review include SOEC critical materials and their optimization, material degradation and its safeguards, future research directions, and commercialization challenges, from both traditional oxygen ion (O2−)-conducting SOEC (O-SOEC) and proton (H+)-conducting SOEC (H-SOEC) perspectives. It is worth to believe that H2O or/and CO2 electrolysis by SOECs provides a viable solution for future energy storage and conversion.

Abstract Background There are many studies indicating that alterations in the abundance of certain gut microbiota are associated with colorectal cancer (CRC). However, a causal relationship has not been identified due to confounding factors such as lifestyle, environmental, and possible reverse causal associations between the two. Furthermore, certain host gene mutations can also contribute to the development of CRC. However, the association between genes and gut microbes in patients with CRC has not been extensively studied. Methods We conducted a two-sample Mendelian randomization (MR) study to reveal the causal relationship between gut microbiota and CRC. We obtained SNPs associated with gut microbiome abundance as instrumental variables (IVs) from a large-scale, multi-ethnic GWAS study, and extracted CRC-related datasets from an East Asian Population genetic consortia GWAS (AGWAS) study and FinnGen consortium, respectively. We analyzed a total of 166 bacterial features at four taxonomic levels, including order, family, genus, and species. The inverse-variance-weighted (IVW), weighted median, MR-Egger, and simple median methods were applied to the MR analysis, and the robustness of the results were tested using a series of sensitivity analyses. We extracted IVs of gut microbiota with direct causal association with CRC for SNP annotation to identify the genes in which these genetic variants were located to reveal the possible host gene-microbiome associations in CRC patients. Results The findings from our MR analysis based on CRC-associated GWAS datasets from AGWAS revealed causal relationships between 6 bacterial taxa and CRC at a locus-wide significance level (P

Abstract Urothelial bladder cancer (UBC) is one of the most prevalent malignancies worldwide, with striking tumor heterogeneity. Elucidating the molecular mechanisms that can be exploited for the treatment of aggressive UBC is a particularly relevant goal. Protein ubiquitination is a critical post-translational modification (PTM) that mediates the degradation of target protein via the proteasome. However, the roles of aberrant protein ubiquitination in UBC development and the underlying mechanisms by which it drives tumor progression remain unclear. In this study, taking advantage of clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein (Cas) 9 technology, we identified the ubiquitin E3 ligase ANAPC11, a critical subunit of the anaphase-promoting complex/cyclosome (APC/C), as a potential oncogenic molecule in UBC cells. Our clinical analysis showed that elevated expression of ANAPC11 was significantly correlated with high T stage, positive lymph node (LN) metastasis, and poor outcomes in UBC patients. By employing a series of in vitro experiments, we demonstrated that ANAPC11 enhanced the proliferation and invasiveness of UBC cells, while knockout of ANAPC11 inhibited the growth and LN metastasis of UBC cells in vivo. By conducting immunoprecipitation coupled with mass spectrometry, we confirmed that ANAPC11 increased the ubiquitination level of the Forkhead transcription factor FOXO3. The resulting decrease in FOXO3 protein stability led to the downregulation of the cell cycle regulator p21 and decreased expression of GULP1, a downstream effector of androgen receptor signaling. Taken together, these findings indicated that ANAPC11 plays an oncogenic role in UBC by modulating FOXO3 protein degradation. The ANAPC11–FOXO3 regulatory axis might serve as a novel therapeutic target for UBC.

Robotic manipulators play a pivotal role in modern intelligent manufacturing and unmanned production systems, often tasked with executing specific paths accurately. However, the input of the robotic manipulators is trajectory which is a path with time information. The resulting core technology is trajectory planning methods which are broadly classified into two categories: maximum velocity curve (MVC) methods and multiphase direct collocation (MPDC) methods. This paper concentrates on addressing challenges associated with the latter methods. In MPDC methods, the solving efficiency and accuracy are greatly influenced by the number of discretization nodes. When dealing with systems with complex dynamics, such as robotic manipulators, striking a balance between solving time and path discretization errors becomes crucial. We use a mesh refinement (MR) algorithm to find a suitable number of nodes under the premise of ensuring the path discretization error. So, the actual device can effectively implement the planned solutions. Nonetheless, the conventional application of the MR algorithm requires solving the original problem in each iteration; these processes are extremely time-consuming and may fail to solve when dealing with a complex dynamic system. As a result, we propose a sequential optimal trajectory planning scheme to solve the problem efficiently by dividing the original optimal control (OC) problem into two stages: path planning (PP) and trajectory planning (TP). In the PP stage, we employ a DC method based on arc length and an MR algorithm to identify key nodes along the specified path. This aims to minimize the approximation error introduced during discretization. In the TP stage, the identified key nodes serve as boundary conditions for an MPDC method based on time. This facilitates the generation of an optimal trajectory that maximizes motion performance, considering constant velocity in Cartesian space and dynamic constraints while keeping the path discretization error. Simulation and experiment are conducted with a six-axis robotic manipulator, ROCR6, and show significant potential for a wide range of applications in robotics.