A Transpiration-Driven Electrokinetic Power Generator with a Salt Pathway for Extended Service Life in Saltwater.

To ensure prolonged functionality of transpiration-driven electrokinetic power generators (TEPGs) in saltwater environments, it is imperative to mitigate salt accumulation. This study presents a salt pathway transpiration-driven electrokinetic power generator (SPTEPG), incorporating MXene, graphene oxide (GO), and carbon nanotubes (CNTs) as active materials, along with cellulose nanofibers (CNF) and poly(vinyl alcohol) (PVA) as aqueous binders and nonwoven fabrics. This unique combination confers exceptional hydrophilicity and enhances the energy generation performance. When tested with deionized water, the SPTEPG achieved a maximum voltage of 0.6 V and a current of 4.2 µA. In simulated seawater conditions, the presence of conductive ions in the solution boosted these values to 0.64 V and 42 µA. The incorporation of the salt pathway mechanism facilitates the return of excess salt deposits to the bulk solution, thus extending the SPTEPG's service life in saltwater environments. This research offers a straightforward yet effective strategy for designing transpiration-driven power generators suitable for saline water applications.

A Mood Semantic Awareness Model for Emotional Interactive Robots.

The rapid development of natural language processing technology and improvements in computer performance in recent years have resulted in the wide-scale development and adoption of human-machine dialogue systems. In this study, the Icc_dialogue model is proposed to enhance the semantic awareness of moods for emotional interactive robots. Equipped with a voice interaction module, emotion calculation is conducted based on model responses, and rules for calculating users' degree of interest are formulated. By evaluating the degree of interest, the system can determine whether it should transition to a new topic to maintain the user's interest. This model can also address issues such as overly purposeful responses and rigid emotional expressions in generated replies. Simultaneously, this study explores topic continuation after answering a question, the construction of dialogue rounds, keyword counting, and the creation of a target text similarity matrix for each text in the dialogue dataset. The matrix is normalized, weights are assigned, and the final text score is calculated. In the text with the highest score, the content of dialogue continuation is determined by calculating a subsequent sentence with the highest similarity. This resolves the issue in which the conversational bot fails to continue dialogue on a topic after answering a question, instead waiting for the user to voluntarily provide more information, resulting in topic interruption. As described in the experimental section, both automatic and manual evaluations were conducted to validate the significant improvement in the mood semantic awareness model's performance in terms of dialogue quality and user experience.

A Lightweight Image Super-Resolution Reconstruction Algorithm Based on the Residual Feature Distillation Mechanism.

In recent years, the development of image super-resolution (SR) has explored the capabilities of convolutional neural networks (CNNs). The current research tends to use deeper CNNs to improve performance. However, blindly increasing the depth of the network does not effectively enhance its performance. Moreover, as the network depth increases, more issues arise during the training process, requiring additional training techniques. In this paper, we propose a lightweight image super-resolution reconstruction algorithm (SISR-RFDM) based on the residual feature distillation mechanism (RFDM). Building upon residual blocks, we introduce spatial attention (SA) modules to provide more informative cues for recovering high-frequency details such as image edges and textures. Additionally, the output of each residual block is utilized as hierarchical features for global feature fusion (GFF), enhancing inter-layer information flow and feature reuse. Finally, all these features are fed into the reconstruction module to restore high-quality images. Experimental results demonstrate that our proposed algorithm outperforms other comparative algorithms in terms of both subjective visual effects and objective evaluation quality. The peak signal-to-noise ratio (PSNR) is improved by 0.23 dB, and the structural similarity index (SSIM) reaches 0.9607.

Selective Cleavage of Cß-O-4 Bond for Lignin Depolymerization via Paired-Electrolysis in an Undivided Cell.

The cleavage of C-O bonds is one of the most promising strategies for lignin-to-chemicals conversion, which has attracted considerable attention in recent years. However, current catalytic system capable of selectively breaking C-O bonds in lignin often requires a precious metal catalyst and/or harsh conditions such as high-pressure H2 and elevated temperatures. Herein, we report a novel protocol of paired electrolysis to effectively cleave the Cß-O-4 bond of lignin model compounds and real lignin at room temperature and ambient pressure. For the first time, "cathodic hydrogenolysis of Cß-O-4 linkage" and "anodic C-H/N-H cross-coupling reaction" are paired in an undivided cell, thus the cleavage of C-O bonds and the synthesis of valuable triarylamine derivatives could be simultaneously achieved in an energy-effective manner. This protocol features mild reaction conditions, high atom economy, remarkable yield with excellent chemoselectivity, and feasibility for large-scale synthesis. Mechanistic studies indicate that indirect H* (chemical absorbed hydrogen) reduction instead of direct electron transfer might be the pathway for the cathodic hydrogenolysis of Cß-O-4 linkage.

Multiomics Sequencing and AlphaFold2 Analysis of the Stereoselective Behavior of Mefentrifluconazole for Bioactivity Improvement and Risk Reduction.

As the first isopropanol chiral triazole fungicide, mefentrifluconazole has broad prospects for application. In this study, the stereoselective stability, bioactivity, fate, and biotoxicity were systematically investigated. Our results indicated that the stability of mefentrifluconazole enantiomers differed between environmental media, and they were stable in water and sediment in the dark. The bactericidal activity of R-mefentrifluconazole against the four target pathogens was 4.6-43 times higher than that of S-mefentrifluconazole. In the water-sediment system, S-mefentrifluconazole dissipated faster than R-mefentrifluconazole in water; however, its accumulation capacity was higher than that of R-mefentrifluconazole in sediment and zebrafish. S-Mefentrifluconazole induced more differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) in zebrafish than did R-mefentrifluconazole. Multiomics sequencing results showed that S-mefentrifluconazole enhanced the antioxidant, detoxification, immune, and metabolic functions of zebrafish by interacting with related proteins. Based on AlphaFold2 modeling and molecular docking, mefentrifluconazole enantiomers had different binding modes with key target proteins in pathogens and zebrafish, which may be the main reason for the stereoselective differences in bioactivity and biotoxicity. Based on its excellent bioactivity and low biotoxicity, the R-enantiomer can be developed to improve the bioactivity and reduce the risk of mefentrifluconazole.

Vision Transformers (ViT) for Blanket-Penetrating Sleep Posture Recognition Using a Triple Ultra-Wideband (UWB) Radar System.

Sleep posture has a crucial impact on the incidence and severity of obstructive sleep apnea (OSA). Therefore, the surveillance and recognition of sleep postures could facilitate the assessment of OSA. The existing contact-based systems might interfere with sleeping, while camera-based systems introduce privacy concerns. Radar-based systems might overcome these challenges, especially when individuals are covered with blankets. The aim of this research is to develop a nonobstructive multiple ultra-wideband radar sleep posture recognition system based on machine learning models. We evaluated three single-radar configurations (top, side, and head), three dual-radar configurations (top + side, top + head, and side + head), and one tri-radar configuration (top + side + head), in addition to machine learning models, including CNN-based networks (ResNet50, DenseNet121, and EfficientNetV2) and vision transformer-based networks (traditional vision transformer and Swin Transformer V2). Thirty participants (n = 30) were invited to perform four recumbent postures (supine, left side-lying, right side-lying, and prone). Data from eighteen participants were randomly chosen for model training, another six participants' data (n = 6) for model validation, and the remaining six participants' data (n = 6) for model testing. The Swin Transformer with side and head radar configuration achieved the highest prediction accuracy (0.808). Future research may consider the application of the synthetic aperture radar technique.

[Protective effect of Liujing Toutong Tablets on rats with permanent cerebral ischemia via NF-κB signaling pathway].

This study investigated the neuroprotective effects and underlying mechanism of Liujing Toutong Tablets(LJTT) on a rat model of permanent middle cerebral artery occlusion(pMCAO). The pMCAO model was established using the suture method. Eighty-four male SPF-grade SD rats were randomly divided into a sham operation group, a model group, a nimodipine group(0.020 g·kg~(-1)), and high-, medium-, and low-dose LJTT groups(2.8, 1.4, and 0.7 g·kg~(-1)). The Longa score, adhesive removal test and laser speckle contrast imaging technique were used to evaluate the degree of neurological functional impairment and changes in local cerebral blood flow. The survival and mortality of rats in each group were recorded daily. After seven days of continuous administration following the model induction, the rats in each group were euthanized, and brain tissue and blood samples were collected for corresponding parameter measurements. Nissl staining was used to examine pathological changes in brain tissue neurons. The levels of tumor necrosis factor-alpha(TNF-α), interleukin-6(IL-6), IL-1ß, vascular endothelial growth factor(VEGF), calcitonin gene-related peptide(CGRP), beta-endorphin(ß-EP), and endogenous nitric oxide(NO) in rat serum were measured using specific assay kits. The entropy weight method was used to analyze the weights of various indicators. The protein expression levels of nuclear factor kappa-B(NF-κB), inhibitor kappaB alpha(IκBα), phosphorylated IκBα(p-IκBα), and phosphorylated inhibitor of NF-κB kinase alpha(p-IKKα) in brain tissue were determined using Western blot. Immunohistochemistry was used to detect the protein expression of chemokine-like factor 1(CKLF1) and C-C chemokine receptor 5(CCR5) in rat brain tissue. Compared with the sham operation group, the model group showed significantly higher neurological functional impairment scores, prolonged adhesive removal time, decreased cerebral blood flow, increased neuronal damage, reduced survival rate, significantly increased levels of TNF-α, IL-1ß, IL-6, CGRP, and NO in serum, significantly decreased levels of VEGF and ß-EP, significantly increased expression levels of NF-κB p65, p-IκBα/IκBα, and p-IKKα in rat brain tissue, and significantly upregulated protein expression of CKLF1 and CCR5. Compared with the model group, the high-dose LJTT group significantly improved the neurological functional score of pMCAO rats after oral administration for 7 days. LJTT at all doses significantly reduced adhesive removal time and restored cerebral blood flow. The high-and medium-dose LJTT groups significantly improved neuronal damage. The LJTT groups at all doses showed reduced levels of TNF-α, IL-1ß, IL-6, CGRP, and NO in rat serum, increased VEGF and ß-EP levels, and significantly decreased expression levels of NF-κB p65, p-IκBα/IκBα, p-IKKα, and CCR5 protein in rat brain tissue. The entropy weight analysis revealed that CGRP and ß-EP were significantly affected during the model induction, and LJTT exhibited a strong effect in reducing the release of inflammatory factors such as TNF-α and IL-1ß. LJTT may exert a neuroprotective effect on rats with permanent cerebral ischemia by reducing neuroinflammatory damage, and its mechanism may be related to the inhibition of the NF-κB signaling pathway and the regulation of the CKLF1/CCR5 axis. Additionally, LJTT may exert certain analgesic effects by reducing CGRP and NO levels and increasing ß-EP levels.

The potential role of FNDC5/irisin in various liver diseases: awakening the sleeping beauties.

Fibronectin type III domain-containing protein 5 (FNDC5) is a transmembrane protein and the precursor of irisin, which serves as a systemic exerkine/myokine with multiple origins. Since its discovery in 2012, this hormone-like polypeptide has rapidly evolved to a component significantly involved in a gamut of metabolic dysregulations and various liver diseases. After a decade of extensive investigation on FNDC5/irisin, we are still surrounded by lots of open questions regarding its diagnostic and therapeutic values. In this review, we first concentrated on the structure-function relationship of FNDC5/irisin. Next, we comprehensively summarised the current knowledge and research findings regarding pathogenic roles/therapeutic applications of FNDC5/irisin in the context of non-alcoholic fatty liver disease, fibrosis, liver injury due to multiple detrimental insults, hepatic malignancy and intrahepatic cholestasis of pregnancy. Moreover, the prominent molecules involved in the underlying mechanisms and signalling pathways were highlighted. As a result, emerging evidence reveals FNDC5/irisin may act as a proxy for diagnosing liver disease pathology, a sensitive biomarker for assessing damage severity, a predisposing factor for surveilling illness progression and a treatment option with protective/preventive impact, all of which are highly dependent on disease grading and contextually pathological features.

Synthesis and antitumor activity of benzophenone compound.

Seven benzophenone compounds were synthesized in one or two steps, then their antitumor activity was evaluated. The total yields ranged from 9% to 44%. Compounds 3c-5c exhibited obvious antitumor activity. Among them, compounds 3c and 4c exhibited excellent and broad-spectrum antitumor activity. Compound 3c exhibited much stronger inhibitory activities against fourteen cancer cells than cisplatin. In particular, compound 3c exhibited stronger cytotoxicity against hepatocarcinoma SMMC-7721 cells than Taxol, with a half maximal inhibitory concentration (IC50) of approximately 0.111 µM. These results demonstrated that compounds 3c, 4c and 5c were very promising antitumor leads for further structural modification.

Estimation of moisture migration in rammed earth based on entropy theory.

In the field of cultural relic protection, the migration of moisture will cause a series of adverse effects, such as disruption and crater eruption. Assessment of water migration status is the key to early warning and prevention of these problems. In an attempt for a solution, the whole process of moisture migration in rammed earth is studied by using the moisture migration initiation criterion based on entropy. We analyzed and compared the entropy change law of the infrared radiation temperature in the two main migration stages, and we made a judgment on whether the moisture state is in the steady equilibrium or in the process of dynamic migration. The results show that the moisture migration status can be identified quickly and in real time by using the moisture migration initiation criterion based on entropy. The results of this study provide a new method for judging the state of moisture migration in geotechnical engineering, especially in the field of cultural relic protection, which has very important practical significance.

Syntheses of xanthone derivatives and their bioactivity investigation.

Sixteen substituted 1-hydroxy-3-methylxanthones were synthesized in one step. The yields ranged from 33 to 76%. Then, the antitumor, antioxidant, anti-tyrosinase, anti-pancreatic lipase, and antifungal activities of compounds 1-16 were evaluated. Compounds 10-12 and 14 inhibited tyrosinase and pancreatic lipase activity to a certain extent, respectively. Compound 16 exhibited obvious cytotoxicity against fifteen cancer cells, moderate antioxidant activity, and moderate inhibitory activity against Candida albicans. In particular, compound 16 exhibited strong inhibitory activity against A-549 and A549/Taxol cells. These results demonstrated that compounds 10-12, 14, and 16 are promising leads for further structural modification.[Formula: see text].

Reciprocal transrepression between FOXF2 and FOXQ1 controls basal-like breast cancer aggressiveness.

FOXF2 and FOXQ1, forkhead box transcription factor superfamily members, are encoded by neighboring genes located on human chromosome 6p25.3 and play opposite roles in epithelial-mesenchymal transition (EMT) and metastasis in basal-like breast cancer (BLBC). However, the relationship between FOXF2 and FOXQ1 in cancer remains unknown. Here, we found mutual transcriptional repression between FOXF2 and FOXQ1, and the reciprocal negative feedback loop controlled EMT, aggressiveness, and chemoresistance in BLBC cells. We further demonstrated that FOXF2 recruited nuclear receptor corepressor 1 and histone deacetylase 3 to the FOXQ1 promoter to inhibit its transcription in BLBC cells, but FOXQ1 did not exert such an effect on FOXF2. Our findings reveal novel mechanisms underlying the determination of BLBC aggressiveness and the transrepressive function of FOXF2 in a basal-like cell subtype-specific manner. Therefore, blocking the vicious cycle of the abnormal reciprocal feedback loop between FOXF2 and FOXQ1 to induce cell differentiation and restore tissue homeostasis is a promising strategy for the treatment of aggressive BLBC.-Kang, L.-J., Yu, Z.-H., Cai, J., He, R., Lu, J.-T., Hou, C., Wang, Q.-S., Li, X.-Q., Zhang, R., Feng, Y.-M. Reciprocal transrepression between FOXF2 and FOXQ1 controls basal-like breast cancer aggressiveness.

Scoparone as a therapeutic drug in liver diseases: Pharmacology, pharmacokinetics and molecular mechanisms of action.

Scoparone is an active and efficious ingredient of herbal medicine Artemisia capillaris Thunb, which has been used clinically in traditional Chinese medicine formula (e.g. Yin-Chen-Hao decoction) for the treatment of hepatic dysfunction, cholestasis and jaundice for over thousand years. More recently, scoparone has received increasing attention due to its multiple properties. In this comprehensive review, we provide the first summary of the pharmacological effects and pharmacokinetic characteristics of scoparone, and discuss future research prospects. The results implicated that scoparone possesses a wide spectrum of pharmacological activities, including anti-inflammatory, antioxidant, anti-apoptotic, anti-fibrotic and hypolipidemic properties. Pharmacokinetic studies have addressed that isoscopoletin and scopoletin are major primary metabolites of scoparone. Moreover, hepatic dysfunction might promote bioavailability of scoparone due to limited intrinsic clearance. On the other hand, the bioavailability of multi-component including scoparone in certain TCM formula can also be enhanced by applying this formula at a high dose on account of their interacted effects. In view of good pharmacological actions, scoparone is anticipated to be a potential drug candidate for various liver diseases, such as acute liver injury, fulminant hepatitis, alcohol-induced hepatotoxicity, non-alcoholic fatty liver disease and fibrosis. However, further studies are warranted to clarify its molecular mechanisms and targets, elucidate its toxicity, and identify its interplay with other active ingredients of classical TCM formula in clinical settings.

Large population-based study using the SEER database: is endoscopic resection appropriate for early gastric cancer patients in the United States?

AIM: To investigate whether endoscopic treatment is applicable to American patients and explores the predictors of lymph node metastasis (LNM) in early gastric cancer (EGC). METHODS: Patients with EGC confined to either mucosa (T1a, n = 1799) and submucosa (T1b, n = 1689) were identified from the Surveillance, Epidemiology, and End Result database. Multivariate logistic regression, Kaplan-Meier method, and univariate/multivariate Cox regression were used to assess the correlation between invasion depth and LNM or prognosis. A nomogram for predicting LNM was constructed and internally validated. RESULTS: EGC limited to T1a exhibited a 2.4% incidence of LNM, which increased to 11.1% when the depth invaded T1b.LNM was present at 1.4%, 5.2%, and 5.0% for sizes ≤2, 2-5, and >5cm of low-grade T1a EGC, respectively, (p = .019) and at 4.8%, 12.4%, and 28.6% of T1b EGC, respectively (p < .001).The multivariate logistic model revealed that older age, T1b invasion, larger tumor size, and high-grade lesions were associated with a higher risk of LNM. Moreover, the T1a EGC patients had better cancer-specific survival (OS) and overall survival(CSS) compared with the T1b EGC patients (5-year OS: 77.2% versus 67.4%, p < .001; 5-year CSS: 90.6% versus 81.4%, p < .001). The discrimination of the prediction model was 0.745. CONCLUSIONS: Endoscopic treatment may only be suitable for patients in the US population who have low-grade T1a lesions of less than 2 cm in size. Patients with T1a lesions of greater than 2 cm in size, lesions with high-grade, and all T1b lesions may benefit from radical surgical resection with lymphadenectomy.

PP2Acα positively regulates the termination of liver regeneration in mice through the AKT/GSK3ß/Cyclin D1 pathway.

BACKGROUND & AIMS: Liver injury triggers a highly organized and ordered liver regeneration (LR) process. Once regeneration is complete, a stop signal ensures that the regenerated liver is an appropriate functional size. The inhibitors and stop signals that regulate LR are unknown, and only limited information is available about these mechanisms. METHODS: A 70% partial hepatectomy (PH) was performed in hepatocyte-specific PP2Acα-deleted (PP2Acα(-/-)) and control (PP2Acα(+/+)) mice. LR was estimated by liver weight, serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels and cell proliferation, and the related cellular signals were analyzed. RESULTS: We found that the catalytic subunit of PP2A was markedly upregulated during the late stage of LR. PP2Acα(-/-) mice showed prolonged LR termination, an increased liver size compared to the original mass and lower levels of serum ALT and AST compared with control mice. In these mice, cyclin D1 protein levels, but not mRNA levels, were increased. Mechanistically, AKT activated by the loss of PP2Acα inhibited glycogen synthase kinase 3ß (GSK3ß) activity, which led to the accumulation of cyclin D1 protein and accelerated hepatocyte proliferation at the termination stage. Treatment with the PI3K inhibitor wortmannin at the termination stage was sufficient to inhibit cyclin D1 accumulation and hepatocyte proliferation. CONCLUSIONS: PP2Acα plays an essential role in the proper termination of LR via the AKT/GSK3ß/Cyclin D1 pathway. Our findings enrich the understanding of the molecular mechanism that controls the termination of LR and provides a potential therapeutic target for treating liver injury.

Enhancing Breast Cancer Diagnosis: A Nomogram Model Integrating AI Ultrasound and Clinical Factors.

PURPOSE: A novel nomogram incorporating artificial intelligence (AI) and clinical features for enhanced ultrasound prediction of benign and malignant breast masses. MATERIALS AND METHODS: This study analyzed 340 breast masses identified through ultrasound in 308 patients. The masses were divided into training (n = 260) and validation (n = 80) groups. The AI-based analysis employed the Samsung Ultrasound AI system (S-detect). Univariate and multivariate analyses were conducted to construct nomograms using logistic regression. The AI-Nomogram was based solely on AI results, while the ClinAI- Nomogram incorporated additional clinical factors. Both nomograms underwent internal validation with 1000 bootstrap resamples and external validation using the independent validation group. Performance was evaluated by analyzing the area under the receiver operating characteristic (ROC) curve (AUC) and calibration curves. RESULTS: The ClinAI-Nomogram, which incorporates patient age, AI-based mass size, and AI-based diagnosis, outperformed an existing AI-Nomogram in differentiating benign from malignant breast masses. The ClinAI-Nomogram surpassed the AI-Nomogram in predicting malignancy with significantly higher AUC scores in both training (0.873, 95% CI: 0.830-0.917 vs. 0.792, 95% CI: 0.748-0.836; p = 0.016) and validation phases (0.847, 95% CI: 0.763-0.932 vs. 0.770, 95% CI: 0.709-0.833; p < 0.001). Calibration curves further revealed excellent agreement between the ClinAI-Nomogram's predicted probabilities and actual observed risks of malignancy. CONCLUSION: The ClinAI- Nomogram, combining AI alongside clinical data, significantly enhanced the differentiation of benign and malignant breast masses in clinical AI-facilitated ultrasound examinations.

Constructing Kinematic Confidence Regions With Double Quaternions.

A spatial displacement as an element of SE ( 3 ) can be approximated by a 4D rotation, which is an element of SO ( 4 ) . In this way, the problem of constructing confidence regions of uncertain spatial displacements may be studied as that of constructing confidence ellipsoids in SO ( 4 ) . In this light, a double-quaternion formulation of kinematic confidence regions is presented that approximately preserve the geometry of SE ( 3 ) . Examples are provided to demonstrate the efficacy of this approach in comparison with the dual-quaternion formulation.

On the Computation of Mean and Variance of Spatial Displacements.

This paper studies the problem of computing an average (or mean) displacement from a set of given spatial displacements using three types of parametric representations: Euler angles and translation vectors, unit quaternions and translation vectors, and dual quaternions. It is shown that the use of Euclidean norm in the space of unit quaternions reduces the problem to that of computing the mean for each quaternion component separately and independently. While the resulting algorithm is simple, a change in the sign of a unit quaternion could lead to an incorrect result. A novel kinematic measure based on dual quaternions is introduced to capture the separation between two spatial displacements. This kinematic measure is used to define the variance of a set of displacements, which is then used to formulate a constrained least squares minimization problem. It is shown that the problem decomposes into that of finding the optimal translation vector and the optimal unit quaternion. The former is simply the centroid of the set of translation vectors and the latter is obtained as the eigenvector corresponding to the least eigenvalue of a 4 × 4 positive definite symmetric matrix. In addition, it is found that the weight factor used in combining rotations and translations in the formulation does not play a role in the final outcome. Examples are provided to show the comparisons of these methods.

On the Construction of Confidence Regions for Uncertain Planar Displacements.

This paper studies the statistical concept of confidence region for a set of uncertain planar displacements with a certain level of confidence or probabilities. Three different representations of planar displacements are compared in this context and it is shown that the most commonly used representation based on the coordinates of the moving frame is the least effective. The other two methods, namely the exponential coordinates and planar quaternions, are equally effective in capturing the group structure of SE(2). However, the former relies on the exponential map to parameterize an element of SE(2), while the latter uses a quadratic map, which is often more advantageous computationally. This paper focus on the use of planar quaternions to develop a method for computing the confidence region for a given set of uncertain planar displacements. Principal component analysis (PCA) is another tool used in our study to capture the dominant direction of movements. To demonstrate the effectiveness of our approach, we compare it to an existing method called rotational and translational confidence limit (RTCL). Our examples show that the planar quaternion formulation leads to a swept volume that is more compact and more effective than the RTCL method, especially in cases when off-axis rotation is present.