Comparative assessment of the capability of machine learning-based radiomic models for predicting omental metastasis in locally advanced gastric cancer.

The study aims to investigate the predictive capability of machine learning algorithms for omental metastasis in locally advanced gastric cancer (LAGC) and to compare the performance metrics of various machine learning predictive models. A retrospective collection of 478 pathologically confirmed LAGC patients was undertaken, encompassing both clinical features and arterial phase computed tomography images. Radiomic features were extracted using 3D Slicer software. Clinical and radiomic features were further filtered through lasso regression. Selected clinical and radiomic features were used to construct omental metastasis predictive models using support vector machine (SVM), decision tree (DT), random forest (RF), K-nearest neighbors (KNN), and logistic regression (LR). The models' performance metrics included accuracy, area under the curve (AUC) of the receiver operating characteristic curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In the training cohort, the RF predictive model surpassed LR, SVM, DT, and KNN in terms of accuracy, AUC, sensitivity, specificity, PPV, and NPV. Compared to the other four predictive models, the RF model significantly improved PPV. In the test cohort, all five machine learning predictive models exhibited lower PPVs. The DT model demonstrated the most significant variation in performance metrics relative to the other models, with a sensitivity of 0.231 and specificity of 0.990. The LR-based predictive model had the lowest PPV at 0.210, compared to the other four models. In the external validation cohort, the performance metrics of the predictive models were generally consistent with those in the test cohort. The LR-based model for predicting omental metastasis exhibited a lower PPV. Among the machine learning algorithms, the RF predictive model demonstrated higher accuracy and improved PPV relative to LR, SVM, KNN, and DT models.

A highly stable full-polymer electrochemical deionization system: dopant engineering & mechanism study.

Electrochemical deionization (ECDI) has emerged as a promising technology for water treatment, with faradaic ECDI systems garnering significant attention due to their enhanced performance potential. This study focuses on the development of a highly stable and efficient, full-polymer (polypyrrole, PPy) ECDI system based on two key strategies. Firstly, dopant engineering, involving the design of dopants with a high charge/molecular weight (MW) ratio and structural complexity, facilitating their effective integration into the polymer backbone. This ensures sustained contribution of strong negative charges, enhancing system performance, while the bulky dopant structure promotes stability during extended operation cycles. Secondly, operating the system with well-balanced charges between deionization and concentration processes significantly reduces irreversible reactions on the polymer, thereby mitigating dopant leakage. Implementing these strategies, the PPy(PSS)//PPy(ClO4) (PSS: polystyrene sulfonate) system achieves a high salt removal capacity (SRC) of 48 mg g-1, an ultra-low energy consumption (EC) of 0.167 kW h kgNaCl-1, and remarkable stability, with 96% SRC retention after 104 cycles of operation. Additionally, this study provides a detailed degradation mechanism based on pre- and post-cycling analyses, offering valuable insights for the construction of highly stable ECDI systems with superior performance in water treatment applications.

Integrated metagenomic and metabolomic analysis reveals distinctive stage-specific gut-microbiome-derived metabolites in intracranial aneurysms.

OBJECTIVE: Our study aimed to explore the influence of gut microbiota and their metabolites on intracranial aneurysms (IA) progression and pinpoint-related metabolic biomarkers derived from the gut microbiome. DESIGN: We recruited 358 patients with unruptured IA (UIA) and 161 with ruptured IA (RIA) from two distinct geographical regions for conducting an integrated analysis of plasma metabolomics and faecal metagenomics. Machine learning algorithms were employed to develop a classifier model, subsequently validated in an independent cohort. Mouse models of IA were established to verify the potential role of the specific metabolite identified. RESULTS: Distinct shifts in taxonomic and functional profiles of gut microbiota and their related metabolites were observed in different IA stages. Notably, tryptophan metabolites, particularly indoxyl sulfate (IS), were significantly higher in plasma of RIA. Meanwhile, upregulated tryptophanase expression and indole-producing microbiota were observed in gut microbiome of RIA. A model harnessing gut-microbiome-derived tryptophan metabolites demonstrated remarkable efficacy in distinguishing RIA from UIA patients in the validation cohort (AUC=0.97). Gut microbiota depletion by antibiotics decreased plasma IS concentration, reduced IA formation and rupture in mice, and downregulated matrix metalloproteinase-9 expression in aneurysmal walls with elastin degradation reduction. Supplement of IS reversed the effect of gut microbiota depletion. CONCLUSION: Our investigation highlights the potential of gut-microbiome-derived tryptophan metabolites as biomarkers for distinguishing RIA from UIA patients. The findings suggest a novel pathogenic role for gut-microbiome-derived IS in elastin degradation in the IA wall leading to the rupture of IA.

A single session of sensorimotor rhythm neurofeedback enhances long-game performance in professional golfers.

Enhanced Sensorimotor Rhythm activity has been linked to increased automation in motor execution. Although existing research demonstrates the positive effects of SMR neurofeedback training on improving golf putting performance, its influence on golf long-game performance remains unexplored. This study sought to address this gap by involving seventeen professional female golfers (Age =24.63 ± 3.24 years, Handicap＝2.06 ± 1.18) in a crossover-designed experiment incorporating both NFT and a no-training control condition. During the study, participants executed 40 150-yard swings while receiving continuous SMR neurofeedback. Pre- and post-testing included visual analog scales to assess psychological processes associated with SMR activities, including attention engagement, conscious motor control, and physical relaxation levels. The results revealed that a single session of NFT effectively heightened SMR power irrespective of T1 (p = .02) or T2 (p = .03), which was observed with improved swing accuracy compared to the control conditions, particularly in "To Pin" (p = .04, the absolute distance to the hole after the ball comes to a stop). Subjective assessments further indicated that SMR NFT contributed to a sense of ease and tranquility during motor preparation for the golf swing (attention engagement: p = .01, conscious motor control: p = .033, physical relaxation: p = .013), and which offered valuable insights into the potential mechanisms underlying the impact of SMR NFT on long-game performance. Additionally, in such practical applications professional athletes can utilize our single-session neurofeedback protocol to train efficiently and cost-effectively before competitions, thereby enhancing their opportunity to achieve a higher rank.

High Performance Indium-Tin-Oxide Schottky Diodes for Terahertz Band Operation.

Schottky diode, capable of ultrahigh frequency operation, plays a critical role in modern communication systems. To develop cost-effective and widely applicable high-speed diodes, researchers have delved into thin-film semiconductors. However, a performance gap persists between thin-film diodes and conventional bulk semiconductor-based ones. Featuring high mobility and low permittivity, indium-tin-oxide has emerged to bridge this gap. Nevertheless, due to its high carrier concentration, indium-tin-oxide has predominantly been utilized as electrode rather than semiconductor. In this study, a remarkable quantum confinement induced dedoping phenomenon was discovered during the aggressive indium-tin-oxide thickness downscaling. By leveraging such a feature to change indium-tin-oxide from metal-like into semiconductor-like, in conjunction with a novel heterogeneous lateral design facilitated by an innovative digital etch, we demonstrated an indium-tin-oxide Schottky diode with a cutoff frequency reaching terahertz band. By pushing the boundaries of thin-film Schottky diodes, our research offers a potential enabler for future fifth-generation/sixth-generation networks, empowering diverse applications.

Black rice diet alleviates colorectal cancer development through modulating tryptophan metabolism and activating AHR pathway.

Consumption of dietary fiber and anthocyanin has been linked to a lower incidence of colorectal cancer (CRC). This study scrutinizes the potential antitumorigenic attributes of a black rice diet (BRD), abundantly rich in dietary fiber and anthocyanin. Our results demonstrate notable antitumorigenic effects in mice on BRD, indicated by a reduction in both the size and number of intestinal tumors and a consequent extension in life span, compared to control diet-fed counterparts. Furthermore, fecal transplants from BRD-fed mice to germ-free mice led to a decrease in colonic cell proliferation, coupled with maintained integrity of the intestinal barrier. The BRD was associated with significant shifts in gut microbiota composition, specifically an augmentation in probiotic strains Bacteroides uniformis and Lactobacillus. Noteworthy changes in gut metabolites were also documented, including the upregulation of indole-3-lactic acid and indole. These metabolites have been identified to stimulate the intestinal aryl hydrocarbon receptor pathway, inhibiting CRC cell proliferation and colorectal tumorigenesis. In summary, these findings propose that a BRD may modulate the progression of intestinal tumors by fostering protective gut microbiota and metabolite profiles. The study accentuates the potential health advantages of whole-grain foods, emphasizing the potential utility of black rice in promoting health.

Comparative effectiveness and tolerability of calcitonin gene-related peptide (CGRP) monoclonal antibodies and onabotulinumtoxinA in chronic migraine: A multicenter, real-world study in Taiwan.

OBJECTIVE: To compare the real-world effectiveness and tolerability of calcitonin gene-related peptide (CGRP) monoclonal antibodies (mAbs) and onabotulinumtoxinA in chronic migraine (CM) patients. METHODS: This multicenter study involved retrospective analysis of prospectively collected data of CM patients treated with CGRP mAbs or onabotulinumtoxinA, including difficult-to-treat (DTT) patients (i.e., ≥3 preventive failures). Treatment outcomes were determined at 6 months based on prospective headache diaries and Migraine Disability Assessment (MIDAS). RESULTS: The study included 316 (55 M/261F, mean age 44.4 ± 13.5 years) and 333 (61 M/272F, mean age 47.9 ± 13.4 years) CM patients treated with CGRP mAbs or onabotulinbumtoxinA, respectively. At 6 months, CGRP mAb treatment was associated with a greater decrease in monthly migraine days (MMDs) (-13.0 vs. -8.7 days/month, p < 0.001) and a higher ≥50% responder rate (RR) (74.7% vs. 50.7%, p < 0.001) compared with onabotulinumtoxinA injections. The findings were consistent in DTT patients (-13.0 vs. -9.1 MMDs, p < 0.001; ≥50% RR: 73.9% vs. 50.3%, p < 0.001) or those with medication-overuse headache (MOH) (-13.3 vs. -9.0 MMDs, p < 0.001; ≥50% RR: 79.0% vs. 51.6%, p < 0.001). Besides, patients receiving CGRP mAbs had greater improvement (-42.2 vs. -11.8, p < 0.001) and a higher ≥50% RR (62.0% vs. 40.0%, p = 0.001) in MIDAS scores and a lower rate of adverse events (AEs) (6.0% vs. 21.0%, p < 0.001). However, none of the patients discontinued treatment due to AEs. CONCLUSIONS: In this multicenter, real-world study, CGRP mAbs were more effective than onabotulinumtoxinA in CM patients, even in DTT or MOH patients. All of these injectables were well tolerated. Further prospective studies are needed to verify these findings.

Photochemistry of plateau lake-derived dissolved organic matter: Reactive species generation and effects on 17ß-estradiol photodegradation.

Naturally strong ultraviolet irradiation at high altitudes causes photobleaching of plateau lake DOM (P-DOM) and affects its photochemical activity. However, the photoreactivity of P-DOM has remained unclear under natural photobleaching condition. Here, six P-DOM samples isolated from plateau lakes in Yunnan Province, China as well as two reference DOM as comparisons were used to explore the photogeneration of reactive species (RS) and their effects on 17ß-estradiol photodegradation. Compared with SRHA/SRFA, P-DOM has lower aromaticity, average molecular weight, and electron-donating capacity. The quantum yields of triplet state P-DOM (3P-DOM*), 1O2, and ∙OH produced in P-DOM solutions were greatly higher than those of reference DOM. The RS quantum yields had positive linear correlations with E2/E3 and SR, whereas were negatively linear correlated with SUVA25. Radical quenching experiments showed that 3P-DOM* was the prominent RS for 17ß-estradiol photodegradation, and its contribution exceeded 70% for each of P-DOM. 3P-DOM*-mediated photodegradation was mainly attributed to the electron-transfer reactions with an average second-order rate constant of 4.62 × 109 M-1s-1, indicating the strong photoreactivity towards 17ß-estradiol. These findings demonstrate that P-DOM is an efficient photosensitizer for RS production, among which 3P-DOM* may play an important role in enhanced photodegradation for organic micropollutants in plateau lake enriched with DOM.

Deciphering DED assembly mechanisms in FADD-procaspase-8-cFLIP complexes regulating apoptosis.

Fas-associated protein with death domain (FADD), procaspase-8, and cellular FLICE-inhibitory proteins (cFLIP) assemble through death-effector domains (DEDs), directing death receptor signaling towards cell survival or apoptosis. Understanding their three-dimensional regulatory mechanism has been limited by the absence of atomic coordinates for their ternary DED complex. By employing X-ray crystallography and cryogenic electron microscopy (cryo-EM), we present the atomic coordinates of human FADD-procaspase-8-cFLIP complexes, revealing structural insights into these critical interactions. These structures illustrate how FADD and cFLIP orchestrate the assembly of caspase-8-containing complexes and offer mechanistic explanations for their role in promoting or inhibiting apoptotic and necroptotic signaling. A helical procaspase-8-cFLIP hetero-double layer in the complex appears to promote limited caspase-8 activation for cell survival. Our structure-guided mutagenesis supports the role of the triple-FADD complex in caspase-8 activation and in regulating receptor-interacting protein kinase 1 (RIPK1). These results propose a unified mechanism for DED assembly and procaspase-8 activation in the regulation of apoptotic and necroptotic signaling across various cellular pathways involved in development, innate immunity, and disease.

Study of individual domains contributing to MALT1 dimerization in BCL10-independent and dependent assembly.

The CARMA-BCL10-MALT1 (CBM) signalosome functions as a pivotal supramolecular module, integrating diverse receptor-induced signaling pathways to regulate BCL10-dependent NF-kB activation in innate and adaptive immunity. Conversely, the API2-MALT1 fusion protein in t(11; 18)(q21; q21) MALT lymphoma constitutively induces BCL10-independent NF-kB activation. MALT1 dimer formation is indispensable for the requisite proteolytic activity and is critical for NF-kB activation regulation in both scenarios. However, the molecular assembly of MALT1 individual domains in CBM activation remains elusive. Here we report the crystal structure of the MALT1 death domain (DD) at a resolution of 2.1 Å, incorporating reconstructed residues in previously disordered loops 1 and 2. Additionally, we observe a conformational regulation element (CRE) regulating stem-helix formation in NLRPs pyrin (PYD) within the MALT1 DD structure. The structure reveals a stem-helix-mediated dimer further corroborated in solution. To elucidate how the BCL10 filament facilitates MALT1 dimerization, we reconstitute a BCL10-CARD-MALT1-DD-IG1-IG2 complex model. We propose a N+7 rule for BCL10-dependent MALT1 dimerization via the IG1-IG2 domain and for MALT1-dependent cleavage in trans. Biochemical data further indicates concentration-dependent dimerization of the MALT1 IG1-IG2 domain, facilitating MALT1 dimerization in BCL10-independent manner. Our findings provide a structural and biochemical foundation for understanding MALT1 dimeric mechanisms, shedding light on potential BCL10-independent MALT1 dimer formation and high-order BCL10-MALT1 assembly.

Modulating Nanoparticle Structure by Metal-Metal Oxide Interfacial Interaction in a CeO2-Supported Bimetallic System: The Ni-Cu Case.

Structure-optimized bimetallic and multicomponent catalysts often outperform single-component catalysts, inspiring a detailed investigation of metal-metal and metal-support interactions in the system. We investigated the geometric and electronic structures of ceria-supported Ni-Cu particles prepared using different metal deposition sequences employing a combination of X-ray photoelectron spectroscopy, resonant photoemission spectroscopy, and infrared reflection absorption spectroscopy. The bimetallic model catalyst structure was altered by a distinct surface evolution process determined by the metal deposition sequence. The postdeposited Cu stays on the surface of Ni predeposited CeO2 and forms only a limited Ni-Cu alloy in the Cu-contacted Ni region. However, when Ni is deposited on the Cu predeposited CeO2 surface, Ni can migrate through the Cu layer to the Cu-ceria interface and form an extended Ni-Cu alloy to the whole deposited metal layer on the ceria surface. The dynamic metal diffusion in the CeO2-supported Ni-Cu system indicates that metal-support interactions can be used to achieve the rational design of a bimetallic composition distribution during catalyst preparation.

Comparing fine motor performance among young children with autism spectrum disorder, intellectual disability, attention-deficit/hyperactivity disorder, and specific developmental disorder of motor function.

Objective: The acquisition of fine motor skills is considered to be a crucial developmental milestone throughout early childhood. This study aimed to investigate the fine motor performance of young children with different disability diagnoses. Methods: We enrolled a sample of 1,897 young children under the age of 6 years who were at risk of developmental delays and were identified by a transdisciplinary team. A series of standardized developmental assessments included the Bayley Scales of Infant Development-Third Edition, Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition, Peabody Developmental Motor Scale-Second Edition, and Movement Assessment Battery for Children-Second Edition were used. Retrospective chart reviews were conducted on all children to identify specific developmental disorders. The number of autism spectrum disorder (ASD), intellectual disability (ID), attention-deficit/hyperactivity disorder (ADHD), comorbidity, motor dysfunction, and unspecified developmental delays (DD) were 363 (19.1%), 223 (11.8%), 234 (12.3%), 285 (15.0%), 128 (6.7%), and 590 (31.1%), respectively. Results: Young children with ID, comorbidity, and motor dysfunction demonstrated significant difficulty in performing manual dexterity and visual motor integration tasks and scored significantly lower in these areas than children with ASD, ADHD, and unspecified DD. In addition, fine motor performance was associated with cognitive ability in children with different disability diagnoses, indicating that young children showed better fine motor performance when they demonstrated better cognitive ability. Conclusion: Our findings support that differences in fine motor performance differ by disability type. Close links between fine motor performance and cognitive ability in children under the age of 6 years were seen in all disability types.

Fibrate and the risk of cardiovascular disease among moderate chronic kidney disease patients with primary hypertriglyceridemia.

Introduction: Hypertriglyceridemia is the most prevalent dyslipidemia in patients with chronic kidney disease (CKD). However, research about fibrate treatment in CKD patients is limited, and assessing its benefits becomes challenging due to the frequent concurrent use of statins. Thus, this study is aimed to investigate the role of fibrate in CKD stage 3 patients with hypertriglyceridemia who did not receive other lipid-lowering agents. Methods: This study enrolled patients newly diagnosed CKD3 with LDL-C<100mg/dL and had never received statin or other lipid-lowering agents from Chang Gung Research Database. The participants were categorized into 2 groups based on the use of fibrate: fibrate group and non-fibrate group (triglyceride >200mg/dL but not receiving fibrate treatment). The inverse probability of treatment weighting was performed to balance baseline characteristics. Results: Compared with the non-fibrate group (n=2020), the fibrate group (n=705) exhibited significantly lower risks of major adverse cardiac and cerebrovascular events (MACCEs) (10.4% vs. 12.8%, hazard ratios [HRs]: 0.69, 95% confidence interval [CI]: 0.50 to 0.95), AMI (2.3% vs. 3.9%, HR: 0.52, 95% CI: 0.37 to 0.73), and ischemic stroke (6.3% vs. 8.0%, HR: 0.67, 95% CI: 0.52 to 0.85). The risk of all-cause mortality (5.1% vs. 4.5%, HR: 1.09, 95% CI: 0.67 to 1.79) and death from CV (2.8% vs. 2.3%, HR: 1.07, 95% CI: 0.29 to 2.33) did not significantly differ between the 2 groups. Conclusion: This study suggests that, in moderate CKD patients with hypertriglyceridemia but LDL-C < 100mg/dL who did not take other lipid-lowering agents, fibrates may be beneficial in reducing cardiovascular events.

Torsional Strain Enabled Ring-Opening Polymerization towards Axially Chiral Semiaromatic Polyesters with Chemical Recyclability.

The development of new chemically recyclable polymers via monomer design would provide a transformative strategy to address the energy crisis and plastic pollution problem. Biaryl-fused cyclic esters were targeted to generate axially chiral polymers, which would impart new material performance. To overcome the non-polymerizability of the biaryl-fused monomer DBO, a cyclic ester Me-DBO installed with dimethyl substitution was prepared to enable its polymerizability via enhancing torsional strain. Impressively, Me-DBO readily went through well-controlled ring-opening polymerization, producing polymer P(Me-DBO) with high glass transition temperature (Tg >100 °C). Intriguingly, mixing these complementary enantiopure polymers containing axial chirality promoted a transformation from amorphous to crystalline material, affording a semicrystalline stereocomplex with a melting transition temperature more than 300 °C. P(Me-DBO) were capable of depolymerizing back to Me-DBO in high efficiency, highlighting an excellent recyclability.

MRI predictors of long-term outcomes of neonatal hypoxic ischaemic encephalopathy: a primer for radiologists.

This review aims to serve as a foundational resource for general radiologists, enhancing their understanding of the role of Magnetic Resonance Imaging (MRI) in early prognostication for newborns diagnosed with hypoxic ischaemic encephalopathy (HIE). The article explores the application of MRI as a predictive instrument for determining long-term outcomes in newborns affected by HIE. With HIE constituting a leading cause of neonatal mortality and severe long-term neurodevelopmental impairments, early identification of prognostic indicators is crucial for timely intervention and optimal clinical management. We examine current literature and recent advancements to provide an in-depth overview of MRI predictors, encompassing brain injury patterns, injury scoring systems, spectroscopy, and diffusion imaging. The potential of these MRI biomarkers in predicting long-term neurodevelopmental outcomes and the probability of epilepsy is also discussed.

Influence of surface nanostructure-induced innermost ion structuring on capacitance of carbon/ionic liquid double layers.

Ionic liquids have drawn great interest as electrolytes for energy storage applications in which they form characteristic electrical double layers at electrode interfaces. For ionic liquids at carbon electrode interfaces, their double layers are subject to nanoscale structuring of the electrode surface, involving altered ion structure and interactions that significantly influence the double layer capacitance. In this regard, we investigate the modulation of ionic liquid double layers by electrode surface roughness and the resulting effects on the ion structure, interaction, and capacitance. We performed fixed voltage molecular dynamics simulations to compute the differential capacitance profiles for the ionic liquids [BMIm+][TFSI-] and [BMIm+][FSI-] at model carbon electrode interfaces with the surface channel width at subnanometer and nanometer scales. We find that both [BMIm+][TFSI-] and [BMIm+][FSI-] exhibit enhanced differential capacitance for the electrode surface with a subnanometer channel width relative to the flat graphene surface, but the most pronounced enhancements for these two ionic liquids unexpectedly appear at different applied potential regimes. For [BMIm+][TFSI-], the nanostructured electrode shows significant enhancement of capacitance at high positive potential. For [BMIm+][FSI-], on the other hand, this enhancement is small at positive polarization but noticeable at low negative potential. We demonstrate that differences in these capacitance trends is due to differences in ion correlation that arise from a steric constraint of nanostructured electrode surface on the voltage-mediated restructuring of ions closest to the electrode interface. For example, the TFSI- and FSI- anions tend to structure with their charged and nonpolar groups in contact with the positive electrode surface when the constraint on these close-contact anions is relaxed. This anion structuring largely retains the cation association near the nanostructured electrode, resulting in only a slight increase in capacitance at positive polarization. Our simulations highlight the sensitive dependence of the innermost ion structure on the electrode surface nanostructure and applied voltage and the resulting influence on ion correlation and capacitance of ionic liquid double layers.

A Single Set of Well-Designed Aptamer Probes for Reliable On-site Qualitative and Ultra-Sensitive Quantitative Detection.

Aptamer-based probes are pivotal components in various sensing strategies, owing to their exceptional specificity and versatile programmable structure. Nevertheless, numerous aptamer-based probes usually offer only a single function, limiting their capacity to meet the diverse requirements of multi-faceted sensing systems. Here, we introduced supersandwich DNA probes (SSW-DNA), designed and modified on the outer surface of nanochannels with hydrophobic inner walls, enabling dual functionality: qualitative detection for on-site analysis and quantitative detection for precise analysis. The fragmented DNAs resulting from the target recognition, are subsequently identified through lateral flow assays, enabling robust on-site qualitative detection of microcystin-LR with an impressively low limit of detection (LOD) at 0.01 µg/L. Meanwhile, the nanochannels enable highly sensitive quantification of microcystin-LR through the current analysis, achieving an exceptionally low LOD at 2.5×10-7  µg/L, with a broad dynamic range spanning from 1×10-6 to 1×102  µg/L. Furthermore, the process of target recognition introduces just a single potential error propagation, which reduces the overall risk of errors during the entire qualitative and quantitative detection process. This sensing strategy broadens the scope of applications for aptamer-based composite probes, holding promising implications across diverse fields, such as medical diagnosis, food safety, and environmental protection.

Synergistic anti-tumor effect of dual drug co-assembled nanoparticles based on ursolic acid and sorafenib.

Both ursolic acid (UA) and sorafenib (Sora) have been generally utilized in cancer treatment, and the combination of the two has also shown a good anti-tumor effect. However, single-agent therapy for Hepatocellular carcinoma (HCC) has the disadvantages of multi-drug resistance, poor water solubility and low bioavailability, and the application of traditional nanocarrier materials is limited due to their low drug loading and low carrier-related toxicity. Therefore, we prepared US NPs with different proportions of UA and Sora by solvent exchange method for achieving synergistic HCC therapy. US NPs had suitable particle size, good dispersibility and storage stability, which synergistically inhibited the proliferation of HepG2 cells, SMMC7721 cells and H22 cells. In addition, we also proved that US NPs were able to suppress the migration of HepG2 cells and SMMC7721 cells and reduce the adhesion ability and colony formation ability of these cells. According to the results, US NPs could degrade the membrane potential of mitochondrial, participate in cell apoptosis, and synergistically induce autophagy. Collectively, the carrier-free US NPs provide new strategies for HCC treatment and new ideas for the development of novel nano-drug delivery systems containing UA and Sora.

Predicting the therapeutic response to valproic acid in childhood absence epilepsy through electroencephalogram analysis using machine learning.

Childhood absence epilepsy (CAE) is a common type of idiopathic generalized epilepsy, manifesting as daily multiple absence seizures. Although seizures in most patients can be adequately controlled with first-line antiseizure medication (ASM), approximately 25 % of patients respond poorly to first-line ASM. In addition, an accurate method for predicting first-line medication responsiveness is lacking. We used the quantitative electroencephalogram (QEEG) features of patients with CAE along with machine learning to predict the therapeutic effects of valproic acid in this population. We enrolled 25 patients with CAE from multiple medical centers. Twelve patients who required additional medication for seizure control or who were shifted to another ASM and 13 patients who achieved seizure freedom with valproic acid within 6 months served as the nonresponder and responder groups. Using machine learning, we analyzed the interictal background EEG data without epileptiform discharge before ASM. The following features were analyzed: EEG frequency bands, Hjorth parameters, detrended fluctuation analysis, Higuchi fractal dimension, Lempel-Ziv complexity (LZC), Petrosian fractal dimension, and sample entropy (SE). We applied leave-one-out cross-validation with support vector machine, K-nearest neighbor (KNN), random forest, decision tree, Ada boost, and extreme gradient boosting, and we tested the performance of these models. The responders had significantly higher alpha band power and lower delta band power than the nonresponders. The Hjorth mobility, LZC, and SE values in the temporal, parietal, and occipital lobes were higher in the responders than in the nonresponders. Hjorth complexity was higher in the nonresponders than in the responders in almost all the brain regions, except for the leads FP1 and FP2. Using KNN classification with theta band power in the temporal lobe yielded optimal performance, with sensitivity of 92.31 %, specificity of 76.92 %, accuracy of 84.62 %, and area under the curve of 88.46 %.We used various EEG features along with machine learning to accurately predict whether patients with CAE would respond to valproic acid. Our method could provide valuable assistance for pediatric neurologists in selecting suitable ASM.

Comparative study on chemical composition, functional properties of dietary fibers prepared from four China cereal brans.

Comparison of chemical composition and functional properties of insoluble and soluble dietary fiber (IDF, SDF) obtained from four China cereal brans was investigated. With findings, IDFs and SDFs for rice bran (RB), wheat bran (WB), highland barely bran (HBB) and tartary buckwheat bran (TBB) contained several monosaccharides such as arabinose, galactose, glucose, xylose, and galacturonic acid. The RBIDF was shrinking and formed a rugged microscopic structure, while the structure of WBIDF was dense and flat. HBBIDF and TBBIDF showed fold and flake structure. The glucose adsorption capacity of the HBBIDF was highest among all samples, which was 3.2 mmol/g. TBBIDF exhibited the highest value of cholesterol adsorption capacity (10.5 mg/g) at pH 7.0 and maximum binding capacity (BCmax, 365.2 µmol/g) for cadmium at pH 7.0 among all samples, respectively. As a result, HBBIDF and TBBIDF are potential fiber-rich ingredients in functional foods.