Eco-friendly, pH-sensitive curcumin-loaded sodium alginate/hydroxyapatite/quaternary ammonium chitosan microspheres with enhanced antibacterial and antioxidant activities for fruit preservation.

The development of intelligent responsive reactive packaging materials with natural polymers shows excellent potential in food preservation. In this study, eco-friendly, pH-sensitive sodium alginate (SA)/hydroxyapatite (HA)/quaternary ammonium chitosan (HACC) composite microspheres loading curcumin (CUR) with excellent antibacterial and antioxidant activities were successfully synthesized. Scanning electron microscopy (SEM) and nitrogen adsorption/desorption tests indicated that the doping of HA substantially increased the specific surface area and pore volume of the microspheres. The loading experiments showed that the efficiency of the microspheres was significantly increased by 49.47 % and 55.10 %, respectively, when HA and HACC were incorporated into the SA network. The release test results suggested that the release rate of SA/HA/HACC microspheres loading CUR (SA/HA/HACC@CUR) increased as the pH decreased, demonstrating notable pH-responsive release characteristics. DPPH free radical scavenging experiments demonstrated that the SA/HA/HACC@CUR had excellent and long-lasting antioxidant capacity. The antibacterial experiments revealed that the SA/HA/HACC@CUR had excellent antibacterial properties, with inhibition rates of 88.73 % and 92.52 % against E. coli and S. aureus, respectively. Making coatings out of microspheres could effectively slow down the rotting and deterioration of cherry tomatoes during storage, suggesting that microspheres with intelligent responses have a broad application prospect in fruit preservation.

Biomimetic Hydrodynamic Sensor with Whisker Array Architecture and Multidirectional Perception Ability.

The rapid development of ocean exploration and underwater robot technology has put forward new requirements for underwater sensing methods, which can be used for hydrodynamic characteristics perception, underwater target tracking, and even underwater cluster communication. Here, inspired by the specialized undulated surface structure of the seal whisker and its ability to suppress vortex-induced vibration, a multidirectional hydrodynamic sensor based on biomimetic whisker array structure and magnetic 3D self-decoupling theory is introduced. The magnetic-based sensing method enables wireless connectivity between the magnetic functional structures and electronics, simplifying device design and endowing complete watertightness. The 3D self-decoupling capability enables the sensor, like a seal or other organisms, to perceive arbitrary whisker motions caused by the action of water flow without complex calibration and additional sensing units. The whisker sensor is capable of detecting a variety of hydrodynamic information, including the velocity (RMSE < 0.061 m s-1) and direction of the steady flow field, the frequency (error < 0.05 Hz) of the dynamic vortex wake, and the orientation (error < 7°) of the vortex wake source, demonstrating its extensive potential for underwater environmental perception and communication, especially in deep sea conditions.

Two-Dimensional Exciton Oriented Diffusion via Periodic Potentials.

Excitonic devices operate based on excitons, which can be excited by photons as well as emitting photons and serve as a medium for photon-carrier conversion. Excitonic devices are expected to combine the advantages of both the high response rate of photonic devices and the high integration of electronic devices simultaneously. However, because of the neutral feature, exciton transport is generally achieved via diffusion rather than using electric fields, and the efficient control of exciton flux directionality has always been difficult. In this work, a precisely designed one-dimensional periodic nanostructure (1DPS) is used to introduce periodic strain field along with resonant mode to the WS2 monolayer, achieving exciton oriented diffusion with a 7.6-fold exciton diffusion coefficient enhancement relative to that of intrinsic, while enhancing the excitonic emission intensity by a factor of 10 and reducing exciton saturation threshold power by 2 orders of magnitude. Based on the analysis of the density functional theory (DFT) and the finite-element method (FEM), we attribute the anisotropy of exciton diffusion to exciton funneling induced by periodic potentials, which do not require excessive potential height difference for an efficient oriented diffusion. As a result of resonant emission, the exciton diffusion is dragged into the nonlinear regime owing to the high exciton density close to saturation, which improves the exciton diffusion coefficient and diffusion anisotropy more appreciably.

Bistable soft jumper capable of fast response and high takeoff velocity.

In contrast with jumping robots made from rigid materials, soft jumpers composed of compliant and elastically deformable materials exhibit superior impact resistance and mechanically robust functionality. However, recent efforts to create stimuli-responsive jumpers from soft materials were limited in their response speed, takeoff velocity, and travel distance. Here, we report a magnetic-driven, ultrafast bistable soft jumper that exhibits good jumping capability (jumping more than 108 body heights with a takeoff velocity of more than 2 meters per second) and fast response time (less than 15 milliseconds) compared with previous soft jumping robots. The snap-through transitions between bistable states form a repeatable loop that harnesses the ultrafast release of stored elastic energy. On the basis of the dynamic analysis, the multimodal locomotion of the bistable soft jumper can be realized: the interwell mode of jumping and the intrawell mode of hopping. These modes are controlled by adjusting the duration and strength of the magnetic field, which endows the bistable soft jumper with robust locomotion capabilities. In addition, it is capable of jumping omnidirectionally with tunable heights and distances. To demonstrate its capability in complex environments, a realistic pipeline with amphibious terrain was established. The jumper successfully finished a simulative task of cleansing water through a pipeline. The design principle and actuating mechanism of the bistable soft jumper can be further extended for other flexible systems.

Antiferromagnetic phase transition in a 3D fermionic Hubbard model.

The fermionic Hubbard model (FHM)1 describes a wide range of physical phenomena resulting from strong electron-electron correlations, including conjectured mechanisms for unconventional superconductivity. Resolving its low-temperature physics is, however, challenging theoretically or numerically. Ultracold fermions in optical lattices2,3 provide a clean and well-controlled platform offering a path to simulate the FHM. Doping the antiferromagnetic ground state of a FHM simulator at half-filling is expected to yield various exotic phases, including stripe order4, pseudogap5, and d-wave superfluid6, offering valuable insights into high-temperature superconductivity7-9. Although the observation of antiferromagnetic correlations over short10 and extended distances11 has been obtained, the antiferromagnetic phase has yet to be realized as it requires sufficiently low temperatures in a large and uniform quantum simulator. Here we report the observation of the antiferromagnetic phase transition in a three-dimensional fermionic Hubbard system comprising lithium-6 atoms in a uniform optical lattice with approximately 800,000 sites. When the interaction strength, temperature and doping concentration are finely tuned to approach their respective critical values, a sharp increase in the spin structure factor is observed. These observations can be well described by a power-law divergence, with a critical exponent of 1.396 from the Heisenberg universality class12. At half-filling and with optimal interaction strength, the measured spin structure factor reaches 123(8), signifying the establishment of an antiferromagnetic phase. Our results provide opportunities for exploring the low-temperature phase diagram of the FHM.

Ganoderma lucidum spores-derived particulate ß-glucan treatment improves antitumor response by regulating myeloid-derived suppressor cells in triple-negative breast cancer.

Granular ß-1,3-glucan extracted from the wall of Ganoderma lucidum spores, named GPG, is a bioregulator. In this study, we investigated the structural, thermal, and other physical properties of GPG. We determined whether GPG ameliorated immunosuppression caused by Gemcitabine (GEM) chemotherapy. Triple-negative breast cancer mice with GPG combined with GEM treatment had reduced tumor burdens. In addition, GEM treatment alone altered the tumor microenvironment(TME), including a reduction in antitumor T cells and a rise in myeloid-derived suppressor cells (MDSC) and regulatory T cells (Tregs). However, combined GPG treatment reversed the tumor immunosuppressive microenvironment induced by GEM. GPG inhibited bone marrow (BM)-derived MDSC differentiation and reversed MDSC expansion induced by conditioned medium (CM) in GEM-treated E0771 cells through a Dectin-1 pathway. In addition, GPG downgraded PD-L1 and IDO1 expression on MDSC while boosting MHC-II, CD86, TNF-α, and IL-6 expression. In conclusion, this study demonstrated that GPG could alleviate the adverse effects induced by GEM chemotherapy by regulating TME.

A network pharmacology-based method to explore the therapeutic effect of honokiol on diabetes with comorbid depression in mice.

The effective treatment of diabetes with comorbid depression is a big challenge so far. Honokiol, a bioactive compound from the dietary supplement Magnolia officinalis extract, possesses multiple health benefits. The present study aims to propose a network pharmacology-based method to elucidate potential targets of honokiol in treating diabetes with comorbid depression and related mechanisms. The antidepressant-like efficacy of honokiol was evaluated in high-fat diet (HFD) induced diabetic mice using animal behavior testing, immuno-staining and western blotting assay. Through network pharmacology analysis, retinoid X receptor alpha (RXRα) and vitamin D receptor (VDR) were identified as potential targets related to diabetes and depression. The stable binding conformation between honokiol and RXR/VDR was determined by molecular docking simulation. Moreover, hononkiol effectively alleviated depression-like behaviors in HFD diabetic mice, presented anti-diabetic and anti-neuroinflammatory functions, and protected the hippocampal neuroplasticity. Importantly, honokiol could activate RXR/VDR heterodimer in vivo. The beneficial effects of honokiol on HFD mice were significantly suppressed by UVI3003 (a RXR antagonist), while enhanced by calcitriol (a VDR agonist). Additionally, the disruption of autophagy in the hippocampus of HFD mice was ameliorated by honokiol, which was attenuated by UVI3003 but strengthened by calcitriol. Taken together, the data provide new evidence that honokiol exerts the antidepressant-like effect in HFD diabetic mice via activating RXR/VDR heterodimer to restore the balance of autophagy. Our findings indicate that the RXR/VDR-mediated signaling might be a potential target for treating diabetes with comorbid depression.

Time to benefit of colchicine in patients with cardiovascular disease: A pooled analysis of randomized controlled trials.

Background: Low-dose colchicine has been shown to lower major adverse cardiovascular events (MACE) among those with cardiovascular disease (CVD). It remains unclear how long a CVD patient needs to live to potentially benefit from colchicine. Our study aimed to determine the time to benefit (TTB) of colchicine in individuals with CVD. Methods: Literature searches were performed in PubMed for the cardiovascular outcome trial of colchicine in patients with CVD until October 12, 2023. The primary outcome measured was MACE. Reconstructed individual participant data (IPD) and the stratified Cox proportional hazards model were used to calculate the hazard ratio (HR) and 95 % confidence interval (CI) to estimate the efficacy of colchicine, and Weibull survival curves were fitted to estimate TTB for specific absolute risk reduction (ARR) thresholds (0.002, 0.005, and 0.01). Results: Four trials randomizing 11,594 adults aged between 59.8 and 66.5 years were included (follow-up duration: 12-28.6 months). Compared with placebo, colchicine reduced the risk of MACE (HR 0.68, 95 % CI: 0.60 to 0.78) but had no impact on cardiovascular and all-cause mortality. A TTB of 11.0 months (95 % CI: 0.59 to 21.3) was estimated to be needed to prevent 1 MACE in 100-colchicine-treated patients. The TTB for acute coronary syndrome was similar compared to stable coronary artery disease (10.7 vs. 11.2 months for ARR = 0.010). Conclusions: By using reconstructed IPD, this pooled analysis demonstrated that colchicine was associated with reduced nonfatal MACE, and the TTB was approximately 11.0 months to prevent 1 MACE per 100 patients.

Cluster-Triggered Self-Luminescence, Rapid Self-Healing, and Adaptive Reprogramming Liquid Crystal Elastomers Enabled by Dynamic Imine Bond.

The integration of advanced functions and diverse practical applications calls for multifunctional liquid crystal elastomers (LCEs); however, the structure-intrinsic luminescence and excellent mechanical properties of LCEs have not yet been explored. In this study, clusteroluminescence (CL)-based LCEs (CL-LCEs) are successfully fabricated without depending on large conjugated structures, thereby avoiding redundant organic synthesis and aggregation-caused quenching. The experimental and theoretical results reveal that secondary amine (-NH-) and imine (-C = N-) groups play vital roles in determining the presence of fluorescence in CL-LCEs. Based on the above observation, the strategy universalization and a molecular library for constructing CL-LCEs are further demonstrated. Meanwhile, the dynamic bond of imine bonds endows the CL-LCE system with rapid self-healing under mild conditions (70 °C in 10 min), excellent stretchability, and adaptive programmable characteristics. Furthermore, the self-luminescent performance enables visual detection of the self-healing process. Finally, CL-based information storage and anticounterfeiting are successfully realized and their applications in fiber actuators and fluorescent textiles are demonstrated. The distinctive luminescence and dynamic chemistry presented in this work has significant implications in elucidating the mechanism of CL and providing new strategies for the rational design of novel multifunctional LCE materials.

Interactive model for predicting the oncological outcome of patients with early-stage huge hepatocellular carcinoma after hepatectomy: a multicenter population-based study.

An interactive model for predicting the oncological outcome of patients with early-stage huge hepatocellular carcinoma (ES-HHCC) after hepatectomy is still lacking. This study was aimed at exploring the independent risk parameters and developing an interactive model for predicting the cancer-specific survival (CSS) of ES-HHCC. Data from patients with ES-HHCC who underwent hepatectomy were collected. The dimensionality of the clinical features was reduced by least absolute shrinkage and selection operator regression and further screened as predictors of CSS by Cox regression. Then, an interactive prediction model was developed and validated. Among the 514 screened patients, 311 and 203 of them were assigned into the training and validation cohort, respectively. Six independent variables, including alpha-fetoprotein, cirrhosis, microvascular invasion, satellite, tumor morphology, and tumor diameter, were identified and incorporated into the prediction model for CSS. The model achieved C-indices of 0.724 and 0.711 in the training and validation cohorts, respectively. Calibration curves showed general consistency in both cohorts. Compared with single predictor, the model had a better performance and greater benefit according to the time-independent receiver operating characteristic curve and decision curve analysis (P < 0.05). The calculator owned satisfactory accuracy and flexible operability for predicting the CSS of ES-HHCC, which could serve as a practical tool to stratify patients with different risks, and guide decision-making.

Genome-wide analysis of LOG family genes in castor and RcLOG5 enhances drought, salt, and cold stress tolerance in Arabidopsis thaliana.

The gene encoding the specific phosphohydrolase LONELY GUY (LOG) plays an important role in the activation of cytokinin and the stress response in plant cells. However, the role of LOG genes in castor bean (Ricinus communis) has not been reported. In this study, we identified a total of nine members of the LOG gene family in the castor bean genome and investigated the upregulated expression of the RcLOG5 gene using transcriptome data analysis. We found that the RcLOG5 gene exhibited tissue-specific expression and was activated by polyethylene glycol, NaCl, low temperature, and abscisic acid stress. The subcellular localization results showed that the RcLOG5 gene is mainly located in the cytoplasm. Based on phenotypic and physiological indicators, namely root length, peroxidase activity, and malondialdehyde content, overexpression of the RcLOG5 gene not only improved the drought resistance, salt tolerance, and cold tolerance of transgenic Arabidopsis, but also shortened the dormancy period of the transgenic plants. Transcriptomic sequencing revealed that the overexpression of the RcLOG5 gene led to the enrichment of differentially expressed genes in the glutathione metabolism pathway in transgenic Arabidopsis. Moreover, the overexpression plants had higher levels of glutathione and a higher GSH/GSSG ratio under stress compared to the wild type. Therefore, we inferred that the RcLOG5 gene may be responsible for regulating cell membrane homeostasis by reducing the accumulation of reactive oxygen species through the glutathione pathway. Overall, the overexpression of the RcLOG5 gene positively regulated the stress resistance of transgenic Arabidopsis. This study provides valuable gene resources for breeding stress-tolerant castor bean varieties.

The potential role of the triglyceride-glucose index in left ventricular systolic function and in-hospital outcomes for patients with acute myocardial infarction.

BACKGROUND: A limited number of small-sample cohort studies have investigated the association between the triglyceride-glucose index and in-hospital prognosis. Moreover, the translational potential role of left ventricular systolic function - measured by left ventricular ejection fraction - combined with the triglyceride-glucose index in prioritizing patients with acute myocardial infarction at high risk of in-hospital major adverse cardiovascular events remains unknown. AIM: To explore the potential role of the triglyceride-glucose index in left ventricular systolic function and in-hospital major adverse cardiovascular events in patients with acute myocardial infarction. METHODS: The Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome project (CCC-ACS) was analysed for this study. RESULTS: We included 43,796 patients with acute myocardial infarction. Patients with a higher triglyceride-glucose index showed an increased risk of major adverse cardiovascular events (adjusted odds ratio 1.46, 95% confidence interval 1.31-1.63). Interaction analyses revealed that left ventricular ejection fraction modified the relationship between the triglyceride-glucose index and major adverse cardiovascular events. Furthermore, patients with acute myocardial infarction were categorized by the triglyceride-glucose index and left ventricular ejection fraction; the low left ventricular ejection fraction/high triglyceride-glucose index group showed the highest risk of major adverse cardiovascular events (adjusted odds ratio 2.14, 95% confidence interval 1.58-2.89). CONCLUSIONS: In a comprehensive nationwide acute myocardial infarction registry conducted in China, a higher triglyceride-glucose index was found to be associated with in-hospital major adverse cardiovascular events, and this was particularly evident among patients with a lower left ventricular ejection fraction. Moreover, the triglyceride-glucose index combined with left ventricular ejection fraction was helpful for risk stratification of patients with acute myocardial infarction.

Green Starch-Based Hydrogels with Excellent Injectability, Self-Healing, Adhesion, Photothermal Effect, and Antibacterial Activity for Promoting Wound Healing.

Hydrogel materials have proven valuable in wound healing, but improving the safety of these hydrogels is still challenging. Therefore, designing multifunctional natural polymeric-based hydrogels with excellent mechanical properties to replace toxic or potentially risky, refractory chemical polymer-based hydrogels such as polyacrylamide and polyethylene glycol is of particular significance. Here, a green starch-based hydrogel (Starch@Ca/CGC hydrogel) with injectability, self-healing, and instant adhesion was constructed by coordination interaction, electrostatic interaction, and intramolecular and intermolecular hydrogen bonds. Therein, natural bioactive small molecules gallic acid (GA) and carvacrol (CA) were coordinated with metal ions by the ultrasonic-triggered self-assembly and ionic cross-linking codriven strategy to prepare Cu-gallic acid-carvacrol nanospheres (CGC NPs), which conferred the hydrogel with near-infrared light (NIR)-controlled CA release and photothermal synergistic sterilization properties, as well as antioxidant and anti-infection capabilities. More importantly, the multifunctional hydrogel platforms could completely cover an irregular wound shape to prevent secondary injury and significantly accelerate wound healing under NIR with more skin appendages like hair follicles and blood vessels appearing. Therefore, it is expected that this starch-based hydrogel could serve as a competitive multifunctional dressing in the biomedical field, including bacteria-derived wound infection and other tissue repair.

Split-Type Magnetic Soft Tactile Sensor with 3D Force Decoupling.

Tactile sensory organs for sensing 3D force, such as human skin and fish lateral lines, are indispensable for organisms. With their sensory properties enhanced by layered structures, typical sensory organs can achieve excellent perception as well as protection under frequent mechanical contact. Here, inspired by these layered structures, a split-type magnetic soft tactile sensor with wireless 3D force sensing and a high accuracy (1.33%) fabricated by developing a centripetal magnetization arrangement and theoretical decoupling model is introduced. The 3D force decoupling capability enables it to achieve a perception close to that of human skin in multiple dimensions without complex calibration. Benefiting from the 3D force decoupling capability and split design with a long effective distance (>20 mm), several sensors are assembled in air and water to achieve delicate robotic operation and water flow-based navigation with an offset <1.03%, illustrating the extensive potential of magnetic tactile sensors in flexible electronics, human-machine interactions, and bionic robots.

Response inhibition impairment related to altered frontal-striatal functional connectivity in insomnia disorder: A pilot and non-clinical study.

BACKGROUND: It is not clear whether and how insomnia disorder (ID) impairs response inhibition ability. Fronto-striatal functional connectivity (FC) plays a critical role in response inhibition and is found be abnormal in patients with ID. In this study, we examined whether insomnia symptoms impair response inhibition in a large non-clinical sample and whether impaired response inhibition is related to abnormal fronto-striatal FC. METHODS: One hundred and fifteen young ID patients and 160 age and sex-matched healthy controls (HC) underwent resting-state functional magnetic response imaging scans and performed the stop-signal task (SST). Performance of SST, Gray Matter Volumes (GMVs), and connections of brain regions related to fronto-striatal circuits was compared between groups. Further examined the association between response inhibition impairment and fronto-striatal FC. RESULTS: The behavioral results showed that patients with ID had significantly longer stop-signal reaction time (SSRT) compared with the HC, reflecting the impaired response inhibition among IDs. Brain imaging results showed IDs had decreased GMVs of the Right Superior Frontal (SFG) and left Supplementary Motor area (SMA). Seed-based FC results showed that compared to HC, the ID showed decreased FC between left SMA and left Paracentral lobule, left SMA and right SMA, and right SFG and right Orbital Middle Frontal gyrus, and increased FC between right SFG and right putamen. Meanwhile, the FC between right SFG and putamen was positively correlated with SSRT in IDs. CONCLUSIONS: The current study found significantly impaired response inhibition among ID and this impairment may be related to abnormal fronto-striatal FC in ID.

Arecoline-Induced Hepatotoxicity in Rats: Screening of Abnormal Metabolic Markers and Potential Mechanisms.

Arecoline is a pyridine alkaloid derived from areca nut in the Arecaceae family. It has extensive medicinal activity, such as analgesic, anti-inflammatory, and anti-allergic. However, the toxicity of Arecoline limits its application. Most current studies on its toxicity mainly focus on immunotoxicity, carcinogenesis, and cancer promotion. However, there are few systematic studies on its hepatotoxicity and mechanisms. Therefore, this research explored the mechanism of hepatotoxicity induced by Arecoline in rats and analyzed endogenous metabolite changes in rat plasma by combining network toxicology with metabolomics. The differential metabolites after Arecoline exposure, such as D-Lysine, N4-Acetylaminobutanal, and L-Arginine, were obtained by metabolomics study, and these differential metabolites were involved in the regulation of lipid metabolism, amino acid metabolism, and vitamin metabolism. Based on the strategy of network toxicology, Arecoline can affect the HIF-1 signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, and other concerning pathways by regulating critical targets, such as ALB, CASP3, EGFR, and MMP9. Integration of metabolomics and network toxicology results were further analyzed, and it was concluded that Arecoline may induce hepatotoxicity by mediating oxidative stress, inflammatory response, energy and lipid metabolism, and cell apoptosis.

An AI Dietitian for Type 2 Diabetes Mellitus Management Based on Large Language and Image Recognition Models: Preclinical Concept Validation Study.

BACKGROUND: Nutritional management for patients with diabetes in China is a significant challenge due to the low supply of registered clinical dietitians. To address this, an artificial intelligence (AI)-based nutritionist program that uses advanced language and image recognition models was created. This program can identify ingredients from images of a patient's meal and offer nutritional guidance and dietary recommendations. OBJECTIVE: The primary objective of this study is to evaluate the competence of the models that support this program. METHODS: The potential of an AI nutritionist program for patients with type 2 diabetes mellitus (T2DM) was evaluated through a multistep process. First, a survey was conducted among patients with T2DM and endocrinologists to identify knowledge gaps in dietary practices. ChatGPT and GPT 4.0 were then tested through the Chinese Registered Dietitian Examination to assess their proficiency in providing evidence-based dietary advice. ChatGPT's responses to common questions about medical nutrition therapy were compared with expert responses by professional dietitians to evaluate its proficiency. The model's food recommendations were scrutinized for consistency with expert advice. A deep learning-based image recognition model was developed for food identification at the ingredient level, and its performance was compared with existing models. Finally, a user-friendly app was developed, integrating the capabilities of language and image recognition models to potentially improve care for patients with T2DM. RESULTS: Most patients (182/206, 88.4%) demanded more immediate and comprehensive nutritional management and education. Both ChatGPT and GPT 4.0 passed the Chinese Registered Dietitian examination. ChatGPT's food recommendations were mainly in line with best practices, except for certain foods like root vegetables and dry beans. Professional dietitians' reviews of ChatGPT's responses to common questions were largely positive, with 162 out of 168 providing favorable reviews. The multilabel image recognition model evaluation showed that the Dino V2 model achieved an average F1 score of 0.825, indicating high accuracy in recognizing ingredients. CONCLUSIONS: The model evaluations were promising. The AI-based nutritionist program is now ready for a supervised pilot study.

Destriping of Remote Sensing Images by an Optimized Variational Model.

Satellite sensors often capture remote sensing images that contain various types of stripe noise. The presence of these stripes significantly reduces the quality of the remote images and severely affects their subsequent applications in other fields. Despite the existence of many stripe noise removal methods in the research, they often result in the loss of fine details during the destriping process, and some methods even generate artifacts. In this paper, we proposed a new unidirectional variational model to remove horizontal stripe noise. The proposed model fully considered the directional characteristics and structural sparsity of the stripe noise, as well as the prior features of the underlying image, to design different sparse constraints, and the ℓp quasinorm was introduced in these constraints to better describe these sparse characteristics, thus achieving a more excellent destriping effect. Moreover, we employed the fast alternating direction method of multipliers (ADMM) to solve the proposed non-convex model. This significantly improved the efficiency and robustness of the proposed method. The qualitative and quantitative results from simulated and real data experiments confirm that our method outperforms existing destriping approaches in terms of stripe noise removal and preservation of image details.

Patterns of Circulating Microbiota during the Acute Phase Following ST-Segment Elevation Myocardial Infarction Predict Long-Term Cardiovascular Events.

Limited information exists regarding whether circulating microbiota could predict long-term clinical outcomes following ST-segment elevation myocardial infarction (STEMI). A total of 244 consecutive patients with STEMI were followed for 2.8 years, and 64 first major adverse cardiovascular events (MACEs) were recorded. Both microbiota abundance [Corynebacterium tuberculostearicum (HR, 1.28; 95% CI, 1.03-1.58) and Staphylococcus aureus (S. aureus) (HR, 1.16; 95% CI, 1.02-1.33) ] and microbiota clusters (Cluster 2 versus Cluster 1: HR, 1.84; 95% CI, 1.04-3.27) could independently predict MACE. Furthermore, a model based on established independent predictors alone was significantly improved by the addition of different microbiota patterns. In addition, CD14++CD16+ monocytes (Mon2) had a significant mediation effect on the microbiota patterns → MACE association. The present study demonstrated that the abundance and clusters of circulating microbiota are associated with future adverse cardiovascular events independent of traditional risk factors, which were partially mediated by an increase in Mon2.

Subtypes of insomnia revealed by the heterogeneity of neuroanatomical patterns: A structural MRI study.

The current conflicting neuroimaging findings of insomnia disorder (ID) may be attributed to heterogeneity in ID. The present study aims to clarify the high heterogeneity in ID and examine the objective neurobiological subtypes of ID by using a novel machine learning method based on gray matter volumes (GMVs). We recruited 56 patients with ID and 73 healthy controls (HCs). The T1-weighted anatomical images were obtained for each participant. We investigated whether the ID has higher interindividual heterogeneity in GMVs. Then, we used a heterogeneous machine learning algorithm by discriminative analysis (HYDRA) to identify subtypes of ID with features of brain regional GMVs. We found that patients with ID have higher interindividual variability than HCs. HYDRA identified two distinct and reliable neuroanatomical subtypes of ID. Two subtypes showed significantly different aberrance in GMVs compared with HCs. Specifically, subtype 1 exhibited widespread decreased GMVs in some brain regions, including the right inferior temporal gyrus, left superior temporal gyrus, left precuneus, right middle cingulate, and right supplementary motor area. Subtype 2 only demonstrated increased GMVs in the right superior temporal gyrus. Additionally, the GMVs of altered brain regions in subtype 1 were significantly correlated with daytime functioning, but in subtype 2, they were significantly correlated with sleep disturbance. These results explain conflicting neuroimaging findings and propose a potential objective neurobiological classification contributing to ID's precise clinical diagnosis and treatment.