Spectroscopic evidence of spin-state excitation in d-electron correlated semiconductor FeSb2.

Iron antimonide (FeSb2) has been investigated for decades due to its puzzling electronic properties. It undergoes the temperature-controlled transition from an insulator to an ill-defined metal, with a cross-over from diamagnetism to paramagnetism. Extensive efforts have been made to uncover the underlying mechanism, but a consensus has yet to be reached. While macroscopic transport and magnetic measurements can be explained by different theoretical proposals, the essential spectroscopic evidence required to distinguish the physical origin is missing. In this paper, through the use of X-ray absorption spectroscopy and atomic multiplet simulations, we have observed the mixed spin states of 3d 6 configuration in FeSb2. Furthermore, we reveal that the enhancement of the conductivity, whether induced by temperature or doping, is characterized by populating the high-spin state from the low-spin state. Our work constitutes vital spectroscopic evidence that the electrical/magnetical transition in FeSb2 is directly associated with the spin-state excitation.

Brain structural and functional signatures of multi-generational family history of suicidal behaviors in preadolescent children.

Parent-child transmission of suicidal behaviors has been extensively studied, but the investigation of a three-generation family suicide risk paradigm remains limited. In this study, we aimed to explore the behavioral and brain signatures of multi-generational family history of suicidal behaviors (FHoS) in preadolescents, utilizing a longitudinal design and the dataset from Adolescent Brain and Cognitive DevelopmentSM Study (ABCD Study®), which comprised 4 years of data and includes a total of 9,653 preadolescents. Our findings revealed that multi-generational FHoS was significantly associated with an increased risk of problematic behaviors and suicidal behaviors (suicide ideation and suicide attempt) in offspring. Interestingly, the problematic behaviors were further identified as a mediator in the multi-generational transmission of suicidal behaviors. Additionally, we observed alterations in brain structure within superior temporal gyrus (STG), precentral/postcentral cortex, posterior parietal cortex (PPC), cingulate cortex (CC), and planum temporale (PT), as well as disrupted functional connectivity of default mode network (DMN), ventral attention network (VAN), dorsal attention network (DAN), fronto-parietal network (FPN), and cingulo-opercular network (CON) among preadolescents with FHoS. These results provide compelling longitudinal evidence at the population level, highlighting the associations between multi-generational FHoS and maladaptive behavioral and neurodevelopmental outcomes in offspring. These findings underscore the need for early preventive measures aimed at mitigating the familial transmission of suicide risk and reducing the global burden of deaths among children and adolescents.

Kynurenine in IDO1high cancer cell-derived extracellular vesicles promotes angiogenesis by inducing endothelial mitophagy in ovarian cancer.

BACKGROUND: Mitophagy, a prominent cellular homeostasis process, has been implicated in modulating endothelial cell function. Emerging evidence suggests that extracellular vesicles (EVs) participate in intercellular communication, which could modulate tumor angiogenesis, a hallmark of ovarian cancer (OC) progression. However, the underlying mechanisms through how EVs regulate endothelial mitophagy associated with tumor angiogenesis during OC development remain obscure. METHODS: The effect of cancer cell-derived EVs on endothelial mitophagy and its correlation with tumor angiogenesis and OC development were explored by in vitro and in vivo experiments. Multi-omics integration analysis was employed to identify potential regulatory mechanisms of cancer cell-derived EVs on endothelial mitophagy, which is involved in tumor angiogenesis associated with OC development. These insights were then further corroborated through additional experiments. An orthotopic OC mouse model was constructed to assess the antiangiogenic and therapeutic potential of the Indoleamine 2,3 dioxygenase-1 (IDO1) inhibitor. RESULTS: Cancer cell-derived EVs promoted tumor angiogenesis via the activation of endothelial mitophagy, contributing to the growth and metastasis of OC. The aberrantly high expression of IDO1 mediated abnormal tryptophan metabolism in cancer cells and promoted the secretion of L-kynurenine (L-kyn)-enriched EVs, with associated high levels of L-kyn in EVs isolated from both the tumor tissues and patient plasma in OC. EVs derived from IDO1high ovarian cancer cells elevated nicotinamide adenine dinucleotide (NAD +) levels in endothelial cells via delivering L-kyn. Besides, IDO1high ovarian cancer cell-derived EVs upregulated sirt3 expression in endothelial cells by increasing acetylation modification. These findings are crucial for promoting endothelial mitophagy correlated with tumor angiogenesis. Notably, both endothelial mitophagy and tumor angiogenesis could be suppressed by the IDO1 inhibitor in the orthotopic OC mouse model. CONCLUSIONS: Together, our findings unveil a mechanism of mitophagy in OC angiogenesis and indicate the clinical relevance of EV enriched L-kyn as a potential biomarker for tumorigenesis and progression. Additionally, IDO1 inhibitors might become an alternative option for OC adjuvant therapy.

Fourteen-Day Tegoprazan-Amoxicillin Dual Therapy as the First-Line Treatment of Helicobacter pylori Infection (SHARE2301): A Multicenter, Noninferiority, Randomized Clinical Trial.

BACKGROUND: Potassium-competitive acid blockers have demonstrated enormous potential in the eradication treatment of Helicobacter pylori infection, with tegoprazan being one of the representatives. The available data on the safety and efficacy of tegoprazan in dual therapy are limited. MATERIALS AND METHODS: The multicenter, noninferiority, randomized-controlled trial was conducted from May 2023 to March 2024. Treatment-naive subjects were randomly assigned (1:1) to enter either the tegoprazan-amoxicillin (TA) group (tegoprazan 50 mg twice daily and amoxicillin 750 mg four times daily) or the esomeprazole-amoxicillin (EA) group (esomeprazole 20 mg and amoxicillin 750 mg all four times daily), with a duration for 14 days. The primary outcome was eradication rate as determined by 13C-urea breath test, including per-protocol (PP) analysis and intention-to-treat (ITT) analysis. Secondary outcomes were adverse events and compliance. RESULTS: A total of 368 individuals were included in the randomization. The eradication rates in the EA group and the TA group were 84.2% and 85.8%, respectively, according to an ITT analysis (p = 0.77), and 88.5% and 88.2%, respectively, according to PP analysis (p = 1.00). The eradication rates for the TA group were not inferior to those of the EA group in both PP (p = 0.0023) and ITT analyses (p = 0.0009). There were no significant statistical differences in the incidence of adverse events and compliance between the two groups. The multivariate logistic regression analysis revealed that poor compliance increased the risk of eradication failure (p < 0.001). CONCLUSIONS: Dual therapy containing tegoprazan is safe and effective to be considered as a clinical first-line treatment option, but further optimization involving antimicrobial susceptibility testing and adjustments in dosage and frequency is warranted. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT05870683.

Analysis of the Brucella melitensis epidemic in Xinjiang: genotyping, polymorphism, antibiotic resistance and tracing.

Brucella spp. are facultative intracellular pathogens that cause zoonosis- brucellosis worldwide. There has been a trend of the re-emergence of brucellosis worldwide in recent years. The epidemic situation of brucellosis is serious in Xinjiang. To analyze the epidemic situation of Brucella spp. in Xinjiang among humans and animals, this study identified 144 Brucella isolates from Xinjiang using classical identification and 16 S rRNA sequencing. MLVA, drug resistance testing, and wgSNP detection were also performed. At the same time, analysis was conducted based on the published data of Brucella isolates worldwide. The results showed that the dominant species was B. melitensis biovar 3, which belonged to GT42 (MLVA-8 typing) and the East Mediterranean lineage. The correlation among isolates was high both in humans or animals. The isolates in Xinjiang exhibited higher polymorphism compared to other locations in China, with polymorphism increasing each year since 2010. No amikacin/kanamycin-resistant strains were detected, but six rifampicin-intermediate isolates were identified without rpoB gene variation. The NJ tree of the wgSNP results indicated that there were three main complexes of the B. melitensis epidemic in Xinjiang. Based on the results of this study, the prevention and control of brucellosis in Xinjiang should focus on B. melitensis, particularly strains belonging to B. melitensis bv.3 GT42 (MLVA-8 typing) and East Mediterranean lineage. Additionally, the rifampicin- and trimethoprim-sulfamethoxazole- resistance of isolates in Xinjiang should be closely monitored to avoid compromising the therapeutic efficacy and causing greater losses. These results provide essential data for the prevention and control of brucellosis in Xinjiang and China. Although the isolates from Xinjiang have significant characteristics among Chinese isolates and can reflect the epidemiological situation of brucellosis in China to some extent, this study cannot represent the characteristics of isolates from other regions.

Environmental cadmium exposure perturbs systemic iron homeostasis via hemolysis and inflammation, leading to hepatic ferroptosis in common carp (Cyprinus carpio L.).

Cadmium (Cd) pollution is considered a pressing challenge to eco-environment and public health worldwide. Although it has been well-documented that Cd exhibits various adverse effects on aquatic animals, it is still largely unknown whether and how Cd at environmentally relevant concentrations affects iron metabolism. Here, we studied the effects of environmental Cd exposure (5 and 50 µg/L) on iron homeostasis and possible mechanisms in common carp. The data revealed that Cd elevated serum iron, transferrin saturation and iron deposition in livers and spleens, leading to the disruption of systemic iron homeostasis. Mechanistic investigations substantiated that Cd drove hemolysis by compromising the osmotic fragility and inducing defective morphology of erythrocytes. Cd concurrently exacerbated hepatic inflammatory responses, resulting in the activation of IL6-Stat3 signaling and subsequent hepcidin transcription. Notably, Cd elicited ferroptosis through increased iron burden and oxidative stress in livers. Taken together, our findings provide evidence and mechanistic insight that environmental Cd exposure could undermine iron homeostasis via erythrotoxicity and hepatotoxicity. Further investigation and ecological risk assessment of Cd and other pollutants on metabolism-related effects is warranted, especially under the realistic exposure scenarios.

The immune landscape and prognostic analysis of CXCL8 immune-related genes in cervical squamous cell carcinoma.

Cervical squamous cell carcinoma (CESC), one of the most common malignancies in women, imposes a significant burden on women's health worldwide. Despite extensive research, the molecular and pathogenic mechanisms of cervical squamous cell carcinoma and CESC remain unclear. This study aimed to explore the immune-related genes, immune microenvironment infiltration, and prognosis of CESC, providing a theoretical basis for guiding clinical treatment. Initially, by mining four gene sets and immune-related gene sets from public databases, 14 immune-related genes associated with CESC were identified. Through univariate and multivariate COX regression analyses, as well as lasso regression analysis, four CESC-independent prognostic genes were identified, and a prognostic model was constructed, dividing them into high and low-risk groups. The correlation between these genes and immune cells and immune functions were explored through ssGSEA enrichment analysis, revealing a close association between the high-risk group and processes such as angiogenesis and epithelial-mesenchymal transition. Furthermore, using public databases and qRT-PCR experiments, significant differences in CXCL8 expression between normal cervical cells and cervical cancer cells were discovered. Subsequently, a CXCL8 knockdown plasmid was constructed, and the efficiency of CXCL8 knockdown was validated in two CESC cell lines, MEG-01 and HCE-1. Through CCK-8, scratch, and Transwell assays, it was confirmed that CXCL8 knockdown could inhibit the proliferation, invasion, and migration abilities of CESC cells. Targeting CXCL8 holds promise for personalized therapy for CESC, providing a strong theoretical basis for achieving clinical translation.

Screening of active components in Astragalus mongholicus Bunge and Panax notoginseng formula for anti-fibrosis in CKD: nobiletin inhibits Lgals1/PI3K/AKT signaling to improve renal fibrosis.

The Astragalus mongholicus Bunge and Panax notoginseng formula (A&P) has been clinically shown to effectively slow down the progression of chronic kidney disease (CKD) and has demonstrated significant anti-fibrosis effects in experimental CKD model. However, the specific active ingredients and underlying mechanism are still unclear. The active ingredients of A&P were analyzed by Ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-HR-MS). A mouse model of CKD was constructed by 5/6 nephrectomy. Renal function was assessed by creatinine and urea nitrogen. Real-time PCR and Western Blot were performed to detect the mRNA and protein changes in kidney and cells. An in vitro fibrotic cell model was constructed by TGF-ß induction in TCMK-1 cells. The results showed that thirteen active ingredients of A&P were identified by UPLC-HR-MS, nine of which were identified by analysis with standards, among which the relative percentage of NOB was high. We found that NOB treatment significantly improved renal function, pathological damage and reduced the expression level of fibrotic factors in CKD mice. The results also demonstrated that Lgals1 was overexpressed in the interstitial kidney of CKD mice, and NOB treatment significantly reduced its expression level, while inhibiting PI3K and AKT phosphorylation. Interestingly, overexpression of Lgals1 significantly increased fibrosis in TCMK1 cells and upregulated the activity of PI3K and AKT, which were strongly inhibited by NOB treatment. NOB is one of the main active components of A&P. The molecular mechanism by which NOB ameliorates renal fibrosis in CKD may be through the inhibition of Lgals1/PI3K/AKT signaling pathway.

Physiological, Transcriptome, and Metabolome Analyses Reveal the Tolerance to Cu Toxicity in Red Macroalgae Gracilariopsis lemaneiformis.

Heavy metal copper (Cu) will inevitably impact the marine macroalgae Gracilariopsis lemaneiformis (G. lemaneiformis), which is a culture of economic importance along China's coastline. In this study, the detoxification mechanism of Cu stress on G. lemaneiformis was revealed by assessing physiological indicators in conjunction with transcriptome and metabolome analyses at 1 d after Cu stress. Our findings revealed that 25 µM Cu stimulated ROS synthesis and led to the enzymatic oxidation of arachidonic acid residues. This process subsequently impeded G. lemaneiformis growth by suppressing photosynthesis, nitrogen metabolism, protein synthesis, etc. The entry of Cu ions into the algae was facilitated by ZIPs and IRT transporters, presenting as Cu2+. Furthermore, there was an up-regulation of Cu efflux transporters HMA5 and ABC family transporters to achieve compartmentation to mitigate the toxicity. The results revealed that G. lemaneiformis elevated the antioxidant enzyme superoxide dismutase and ascorbate-glutathione cycle to maintain ROS homeostasis. Additionally, metabolites such as flavonoids, 3-O-methylgallic acid, 3-hydroxy-4-keto-gama-carotene, and eicosapentaenoic acid were up-regulated compared with the control, indicating that they might play roles in response to Cu stress. In summary, this study offers a comprehensive insight into the detoxification mechanisms driving the responses of G. lemaneiformis to Cu exposure.

Optimizing lower limb rehabilitation: the intersection of machine learning and rehabilitative robotics.

Lower limb rehabilitation is essential for recovery post-injury, stroke, or surgery, improving functional mobility and quality of life. Traditional therapy, dependent on therapists' expertise, faces challenges that are addressed by rehabilitation robotics. In the domain of lower limb rehabilitation, machine learning is progressively manifesting its capabilities in high personalization and data-driven approaches, gradually transforming methods of optimizing treatment protocols and predicting rehabilitation outcomes. However, this evolution faces obstacles, including model interpretability, economic hurdles, and regulatory constraints. This review explores the synergy between machine learning and robotic-assisted lower limb rehabilitation, summarizing scientific literature and highlighting various models, data, and domains. Challenges are critically addressed, and future directions proposed for more effective clinical integration. Emphasis is placed on upcoming applications such as Virtual Reality and the potential of deep learning in refining rehabilitation training. This examination aims to provide insights into the evolving landscape, spotlighting the potential of machine learning in rehabilitation robotics and encouraging balanced exploration of current challenges and future opportunities.

Ethnopharmacological study on Adenosma buchneroides Bonati inhibiting inflammation via the regulation of TLR4/MyD88/NF-κB signaling pathway.

Adenosma buchneroides Bonati, also known as fleagrass, is an important medicinal plant used by the Akha (Hani) people of China for treating inflammation-related skin swelling, acne, and diarrhoea, among other conditions. In this study, we aimed to evaluate the anti-inflammatory activities and explore the molecular mechanisms of fleagrass on treating skin swelling and acne. The results demonstrated that fleagrass inhibited the enzymatic activities of 5-LOX and COX-2 in vitro, and decreased the release of NO, IL-6, TNF-α, and IL-10 in the LPS-induced RAW264.7 macrophages. The levels of proteins associated with the nuclear factor-kappa B (NF-κB) pathway were examined by western blotting and immunofluorescence, demonstrating that fleagrass downregulated the expression of TLR4, MyD88, NF-κB/p65, and iNOS and blocked the nuclear translocation of NF-κB/p65. Furthermore, fleagrass exhibited acute anti-inflammatory activity in paw oedema models. The results confirm that fleagrass exhibits remarkable anti-inflammatory activity and can be used in alleviating inflammation, suggesting that fleagrass has the potential to be a novel anti-inflammatory agent.

A scoping review of utilization of the verbal fluency task in Chinese and Japanese clinical settings with near-infrared spectroscopy.

This review targets the application of the Verbal Fluency Task (VFT) in conjunction with functional near-infrared spectroscopy (fNIRS) for diagnosing psychiatric disorders, specifically in the contexts of China and Japan. These two countries are at the forefront of integrating fNIRS with VFT in clinical psychiatry, often employing this combination as a complementary tool alongside traditional psychiatric examinations. Our study aims to synthesize research findings on the hemodynamic responses elicited by VFT task in clinical settings of the two countries, analyzing variations in task design (phonological versus semantic), stimulus modality (auditory versus visual), and the impact of language typology. The focus on China and Japan is crucial, as it provides insights into the unique applications and adaptations of VFT in these linguistically and culturally distinct environments. By exploring these specific cases, our review underscores the importance of tailoring VFT to fit the linguistic and cultural context, thereby enhancing its validity and utility in cross-cultural psychiatric assessments.

Unveiling the pathogenesis and therapeutic approaches for diabetic nephropathy: insights from panvascular diseases.

Diabetic nephropathy (DN) represents a significant microvascular complication in diabetes, entailing intricate molecular pathways and mechanisms associated with cardiorenal vascular diseases. Prolonged hyperglycemia induces renal endothelial dysfunction and damage via metabolic abnormalities, inflammation, and oxidative stress, thereby compromising hemodynamics. Concurrently, fibrotic and sclerotic alterations exacerbate glomerular and tubular injuries. At a macro level, reciprocal communication between the renal microvasculature and systemic circulation establishes a pernicious cycle propelling disease progression. The current management approach emphasizes rigorous control of glycemic levels and blood pressure, with renin-angiotensin system blockade conferring renoprotection. Novel antidiabetic agents exhibit renoprotective effects, potentially mediated through endothelial modulation. Nonetheless, emerging therapies present novel avenues for enhancing patient outcomes and alleviating the disease burden. A precision-based approach, coupled with a comprehensive strategy addressing global vascular risk, will be pivotal in mitigating the cardiorenal burden associated with diabetes.

Significance of Aneuploidy in Predicting Prognosis and Treatment Response of Uveal Melanoma.

AIMS: This study aimed to improve personalized treatment strategies and predict survival outcomes for patients with uveal melanoma (UM). BACKGROUND: Copy number aberrations (CNAs) have been considered as a main feature of metastatic UM. OBJECTIVE: This study was designed to explore the feasibility of using copy number variation (CNV) in UM classification, prognosis stratification and treatment response. METHODS: The CNV data in the TCGA-UVM cohort were used to classify the samples. The differentially expressed genes (DEGs) between subtypes were screened by the "Limma" package. The module and hub genes related to aneuploidy score were identified by performing weighted gene co-expression network analysis (WGCNA) on the DEGs. Univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to train the hub genes for developing a prognosis model for UM. Finally, the expression levels of the screened prognostic key genes were verified in UM cells, and the cell migration and invasion abilities were detected using real-time quantitative PCR (qRT-PCR) and transwell assay. RESULTS: The UM samples were divided into 3 CNV subtypes, which differed significantly in overall survival (OS) and disease-specific survival (DSS). C1 had the shortest OS and DSS and the highest level of immune infiltration. A total of 2036 DEGs were obtained from the three subtypes. Eighty hub genes with the closest correlation with aneuploidy scores were selected by WGCNA. Univariate Cox and LASSO regression-based analyses finally determined eight genes as the key prognostic genes, including HES6, RNASEH2C, NQO1, NUDT14, TTYH3, GJC1, FKBP10, and MRPL24. A prognostic model was developed using the eight genes, demonstrating a strong prediction power. Differences in the response to immunotherapy among patients in different risk groups were significant. We found that high-risk patients were more sensitive to two drugs (Palbociclib_ 1054 and Ribociclib_1632), while low-risk patients were more sensitive to AZD1208_1449, ERK_2440_1713, Mirin_1048, and Selumetinib_1736. CONCLUSION: UM in this study was divided into three CNV subtypes, and a model based on eight aneuploidy score-related genes was established to evaluate the prognosis and drug treatment efficacy of UM patients. The current results may have the potential to help the clinical decision-making process for UM management.

FAFS-UNet: Redesigning skip connections in UNet with feature aggregation and feature selection.

In recent years, the encoder-decoder U-shaped network architecture has become a mainstream structure for medical image segmentation. Its biggest advantage lies in the incorporation of shallow features into deeper layers of the network through skip connections. However, according to our research, there are still some limitations in the skip connection part of the network: (1) The information from the encoder stage is not completely and effectively supplemented to the decoder stage; (2) The decoder receives the supplemented feature information from the encoder indiscriminately, which sometimes leads to the poor performance of the model. Therefore, to effectively address these limitations, we have redesigned the skip connections in UNet using a feature aggregation and feature selection approach. We firstly design the FA module to aggregate all encoder features and perform local multi-scale information extraction to obtain the complete multi-scale aggregated features. Further, we design the FS module to actively perform specific selection of these aggregated features through the decoder, thus effectively guiding the semantic recovery of the decoder. Finally, we conduct experiments on several medical image datasets, and the results show that our method has higher segmentation accuracy compared with other methods.

Four alkaloids from Portulaca oleracea L. and their anti-inflammatory.

Four alkaloids were isolated from Portulaca oleracea L., including two new compounds, 2-(4-amino-6-hydroxy-1,6-dihydropyrimidin-5-yl)-5-(hydroxymethyl)tetrahydrofuran-3,4-diol, named Olerapyrimidine (1) and (2 R,3S,4S,5R,6S)-2-(hydroxymethyl)-6-((6-hydroxypyridin-3-yl)oxy)tetrahydro-2H-pyran-3,4,5-triol, named Olerapyridine (2), and two known compounds including 1H-imidazole (3) and (5S, 6 R, 7S, 8 R)-5-amino-(2Z,4Z)-1,2,3-trihydroxybuta-2,4-dienyloxy-pentane-6,7,8,9-tetraol (4) from P. oleracea for the first time. Their structures were determined by spectroscopic methods, including UHPLC-ESI-Q-TOF/MS, 1D and 2D NMR spectra. Both Olerapyrimidine and Olerapyridine at 20 µM could inhibit the inflammatory factors, IL-1ß and TNF-α in the RAW 264.7 cells induced by LPS.

Medical image segmentation network based on multi-scale frequency domain filter.

With the development of deep learning, medical image segmentation in computer-aided diagnosis has become a research hotspot. Recently, UNet and its variants have become the most powerful medical image segmentation methods. However, these methods suffer from (1) insufficient sensing field and insufficient depth; (2) computational nonlinearity and redundancy of channel features; and (3) ignoring the interrelationships among feature channels. These problems lead to poor network segmentation performance and weak generalization ability. Therefore, first of all, we propose an effective replacement scheme of UNet base block, Double residual depthwise atrous convolution (DRDAC) block, to effectively improve the deficiency of receptive field and depth. Secondly, a new linear module, the Multi-scale frequency domain filter (MFDF), is designed to capture global information from the frequency domain. The high order multi-scale relationship is extracted by combining the depthwise atrous separable convolution with the frequency domain filter. Finally, a channel attention called Axial selection channel attention (ASCA) is redesigned to enhance the network's ability to model feature channel interrelationships. Further, we design a novel frequency domain medical image segmentation baseline method FDFUNet based on the above modules. We conduct extensive experiments on five publicly available medical image datasets and demonstrate that the present method has stronger segmentation performance as well as generalization ability compared to other state-of-the-art baseline methods.

Self-assembly of sophorolipid and eugenol into stable nanoemulsions for synergetic antibacterial properties through alerting membrane integrity.

Exploring the natural, safe, and effective antimicrobial is one of the preferable ways to control foodborne bacteria. In this work, novel oil-in-water nanoemulsions were formulated with sophorolipids and eugenol without any co-surfactant using a self-assembling strategy. These nanoemulsions showed high stability with sizes less than 200 nm when exposure to low concentrations of salt ions, various pH values (5.0, 7.0, 10.0), storage temperature and time. The synergistic antibacterial effects against both Gram-negative Escherichia coli and Gram-positive Bacillus cereus were determined with a minimum inhibitory concentration (MIC) value of 0.5 mg/mL and 0.125 mg/mL, respectively. Further microscopy (SEM, TEM, LCSM) examination and ATP/Na+-K+-ATPase assay results showed that the morphological changes, intensive cell membrane permeability, leakage of ATP, and decreased Na+-K+-ATPase contributed to the antibacterial effects. Moreover, the bonding mechanism between nanoemulsions and cell membranes were further evaluated by FTIR and ITC using a DPPC vesicle model, which demonstrated that the nanoemulsions adsorbed on the surface of bilayer, interacted with the hydrophobic chains of DPPC membrane mainly through the hydrophobic interaction, and altered the structural integrity of the lipid bilayer. These results not only provide a facile green strategy for fabricating stable nanoemulsions, but also highlight a new perspective for stabilizing essential oils for their widely application in food industry.

FCSU-Net: A novel full-scale Cross-dimension Self-attention U-Net with collaborative fusion of multi-scale feature for medical image segmentation.

Recently, ViT and CNNs based on encoder-decoder architecture have become the dominant model in the field of medical image segmentation. However, there are some deficiencies for each of them: (1) It is difficult for CNNs to capture the interaction between two locations with consideration of the longer distance. (2) ViT cannot acquire the interaction of local context information and carries high computational complexity. To optimize the above deficiencies, we propose a new network for medical image segmentation, which is called FCSU-Net. FCSU-Net uses the proposed collaborative fusion of multi-scale feature block that enables the network to obtain more abundant and more accurate features. In addition, FCSU-Net fuses full-scale feature information through the FFF (Full-scale Feature Fusion) structure instead of simple skip connections, and establishes long-range dependencies on multiple dimensions through the CS (Cross-dimension Self-attention) mechanism. Meantime, every dimension is complementary to each other. Also, CS mechanism has the advantage of convolutions capturing local contextual weights. Finally, FCSU-Net is validated on several datasets, and the results show that FCSU-Net not only has a relatively small number of parameters, but also has a leading segmentation performance.

EPolar-UNet: An edge-attending polar UNet for automatic medical image segmentation with small datasets.

BACKGROUND: Medical image segmentation is one of the most key steps in computer-aided clinical diagnosis, geometric characterization, measurement, image registration, and so forth. Convolutional neural networks especially UNet and its variants have been successfully used in many medical image segmentation tasks. However, the results are limited by the deficiency in extracting high resolution edge information because of the design of the skip connections in UNet and the need for large available datasets. PURPOSE: In this paper, we proposed an edge-attending polar UNet (EPolar-UNet), which was trained on the polar coordinate system instead of classic Cartesian coordinate system with an edge-attending construction in skip connection path. METHODS: EPolar-UNet extracted the location information from an eight-stacked hourglass network as the pole for polar transformation and extracted the boundary cues from an edge-attending UNet, which consisted of a deconvolution layer and a subtraction operation. RESULTS: We evaluated the performance of EPolar-UNet across three imaging modalities for different segmentation tasks: CVC-ClinicDB dataset for polyp, ISIC-2018 dataset for skin lesion, and our private ultrasound dataset for liver tumor segmentation. Our proposed model outperformed state-of-the-art models on all three datasets and needed only 30%-60% of training data compared with the benchmark UNet model to achieve similar performances for medical image segmentation tasks. CONCLUSIONS: We proposed an end-to-end EPolar-UNet for automatic medical image segmentation and showed good performance on small datasets, which was critical in the field of medical image segmentation.