Cross-site validation of lung cancer diagnosis by electronic nose with deep learning: a multicenter prospective study.

BACKGROUND: Although electronic nose (eNose) has been intensively investigated for diagnosing lung cancer, cross-site validation remains a major obstacle to be overcome and no studies have yet been performed. METHODS: Patients with lung cancer, as well as healthy control and diseased control groups, were prospectively recruited from two referral centers between 2019 and 2022. Deep learning models for detecting lung cancer with eNose breathprint were developed using training cohort from one site and then tested on cohort from the other site. Semi-Supervised Domain-Generalized (Semi-DG) Augmentation (SDA) and Noise-Shift Augmentation (NSA) methods with or without fine-tuning was applied to improve performance. RESULTS: In this study, 231 participants were enrolled, comprising a training/validation cohort of 168 individuals (90 with lung cancer, 16 healthy controls, and 62 diseased controls) and a test cohort of 63 individuals (28 with lung cancer, 10 healthy controls, and 25 diseased controls). The model has satisfactory results in the validation cohort from the same hospital while directly applying the trained model to the test cohort yielded suboptimal results (AUC, 0.61, 95% CI: 0.47─0.76). The performance improved after applying data augmentation methods in the training cohort (SDA, AUC: 0.89 [0.81─0.97]; NSA, AUC:0.90 [0.89─1.00]). Additionally, after applying fine-tuning methods, the performance further improved (SDA plus fine-tuning, AUC:0.95 [0.89─1.00]; NSA plus fine-tuning, AUC:0.95 [0.90─1.00]). CONCLUSION: Our study revealed that deep learning models developed for eNose breathprint can achieve cross-site validation with data augmentation and fine-tuning. Accordingly, eNose breathprints emerge as a convenient, non-invasive, and potentially generalizable solution for lung cancer detection. CLINICAL TRIAL REGISTRATION: This study is not a clinical trial and was therefore not registered.

Effects of sulfamonomethoxine and trimethoprim co-exposures at different environmentally relevant concentrations on microalgal growth and nutrient assimilation.

In aquaculture around the world, sulfamonomethoxine (SMM), a long-acting antibiotic that harms microalgae, is widely employed in combination with trimethoprim (TMP), a synergist. However, their combined toxicity to microalgae under long-term exposures at environmentally relevant concentrations remains poorly understood. Therefore, we studied the effects of SMM single-exposures and co-exposures (SMM:TMP=5:1) at concentrations of 5 µg/L and 500 µg/L on Chlorella pyrenoidosa within one aquacultural drainage cycle (15 days). Photosynthetic activity and N assimilating enzyme activities were employed to evaluate microalgal nutrient assimilation. Oxidative stress and flow cytometry analysis for microalgal proliferation and death jointly revealed mechanisms of inhibition and subsequent self-adaptation. Results showed that exposures at 5 µg/L significantly inhibited microalgal nutrient assimilation and induced oxidative stress on day 7, with a recovery to levels comparable to the control by day 15. This self-adaptation and over 95 % removal of antibiotics jointly contributed to promoting microalgal growth and proliferation while reducing membrane-damaged cells. Under 500 µg/L SMM single-exposure, microalgae self-adapted to interferences on nutrient assimilation, maintaining unaffected growth and proliferation. However, over 60 % of SMM remained, leading to sustained oxidative stress and apoptosis. Remarkably, under 500 µg/L SMM-TMP co-exposure, the synergistic toxicity of SMM and TMP significantly impaired microalgal nutrient assimilation, reducing the degradation efficiency of SMM to about 20 %. Consequently, microalgal growth and proliferation were markedly inhibited, with rates of 9.15 % and 17.7 %, respectively, and a 1.36-fold increase in the proportion of cells with damaged membranes was observed. Sustained and severe oxidative stress was identified as the primary cause of these adverse effects. These findings shed light on the potential impacts of antibiotic mixtures at environmental concentrations on microalgae, facilitating responsible evaluation of the ecological risks of antibiotics in aquaculture ponds.

regionalpcs : improved discovery of DNA methylation associations with complex traits.

We have developed the regional principal components (rPCs) method, a novel approach for summarizing gene-level methylation. rPCs address the challenge of deciphering complex epigenetic mechanisms in diseases like Alzheimer's disease (AD). In contrast to traditional averaging, rPCs leverage principal components analysis to capture complex methylation patterns across gene regions. Our method demonstrated a 54% improvement in sensitivity over averaging in simulations, offering a robust framework for identifying subtle epigenetic variations. Applying rPCs to the AD brain methylation data in ROSMAP, combined with cell type deconvolution, we uncovered 838 differentially methylated genes associated with neuritic plaque burden-significantly outperforming conventional methods. Integrating methylation quantitative trait loci (meQTL) with genome-wide association studies (GWAS) identified 17 genes with potential causal roles in AD, including MS4A4A and PI-CALM . Our approach is available in the Bioconductor package regionalpcs , opening avenues for research and facilitating a deeper understanding of the epigenetic landscape in complex diseases.

An Anthropomorphic Diagnosis System of Pulmonary Nodules using Weak Annotation-Based Deep Learning.

Purpose: To develop an anthropomorphic diagnosis system of pulmonary nodules (PN) based on Deep learning (DL) that is trained by weak annotation data and has comparable performance to full-annotation based diagnosis systems. Methods: The proposed system uses deep learning (DL) models to classify PNs (benign vs. malignant) with weak annotations, which eliminates the need for time-consuming and labor-intensive manual annotations of PNs. Moreover, the PN classification networks, augmented with handcrafted shape features acquired through the ball-scale transform technique, demonstrate capability to differentiate PNs with diverse labels, including pure ground-glass opacities, part-solid nodules, and solid nodules. Results: The experiments were conducted on two lung CT datasets: (1) public LIDC-IDRI dataset with 1,018 subjects, (2) In-house dataset with 2740 subjects. Through 5-fold cross-validation on two datasets, the system achieved the following results: (1) an Area Under Curve (AUC) of 0.938 for PN localization and an AUC of 0.912 for PN differential diagnosis on the LIDC-IDRI dataset of 814 testing cases, (2) an AUC of 0.943 for PN localization and an AUC of 0.815 for PN differential diagnosis on the in-house dataset of 822 testing cases. These results demonstrate comparable performance to full annotation-based diagnosis systems. Conclusions: Our system can efficiently localize and differentially diagnose PNs even in resource-limited environments with good robustness across different grade and morphology sub-groups in the presence of deviations due to the size, shape, and texture of the nodule, indicating its potential for future clinical translation. Summary: An anthropomorphic diagnosis system of pulmonary nodules (PN) based on deep learning and weak annotation was found to achieve comparable performance to full-annotation dataset-based diagnosis systems, significantly reducing the time and the cost associated with the annotation. Key Points: A fully automatic system for the diagnosis of PN in CT scans using a suitable deep learning model and weak annotations was developed to achieve comparable performance (AUC = 0.938 for PN localization, AUC = 0.912 for PN differential diagnosis) with the full-annotation based deep learning models, reducing around 30%∼80% of annotation time for the experts.The integration of the hand-crafted feature acquired from human experts (natural intelligence) into the deep learning networks and the fusion of the classification results of multi-scale networks can efficiently improve the PN classification performance across different diameters and sub-groups of the nodule.

Osr2 functions as a biomechanical checkpoint to aggravate CD8+ T cell exhaustion in tumor.

Alterations in extracellular matrix (ECM) architecture and stiffness represent hallmarks of cancer. Whether the biomechanical property of ECM impacts the functionality of tumor-reactive CD8+ T cells remains largely unknown. Here, we reveal that the transcription factor (TF) Osr2 integrates biomechanical signaling and facilitates the terminal exhaustion of tumor-reactive CD8+ T cells. Osr2 expression is selectively induced in the terminally exhausted tumor-specific CD8+ T cell subset by coupled T cell receptor (TCR) signaling and biomechanical stress mediated by the Piezo1/calcium/CREB axis. Consistently, depletion of Osr2 alleviates the exhaustion of tumor-specific CD8+ T cells or CAR-T cells, whereas forced Osr2 expression aggravates their exhaustion in solid tumor models. Mechanistically, Osr2 recruits HDAC3 to rewire the epigenetic program for suppressing cytotoxic gene expression and promoting CD8+ T cell exhaustion. Thus, our results unravel Osr2 functions as a biomechanical checkpoint to exacerbate CD8+ T cell exhaustion and could be targeted to potentiate cancer immunotherapy.

D3S-001, a KRAS G12C inhibitor with rapid target engagement kinetics, overcomes nucleotide cycling and demonstrates robust preclinical and clinical activities.

First-generation KRAS G12C inhibitors, such as sotorasib and adagrasib, are limited by the depth and duration of clinical responses. One potential explanation for their modest clinical activity is the dynamic "cycling" of KRAS between its GDP- and GTP-bound states, raising controversy about whether targeting the GDP-bound form can fully block this oncogenic driver. We herein report D3S-001, a next generation GDP-bound G12C inhibitor with faster target engagement (TE) kinetics, depletes cellular active KRAS G12C at nanomolar concentrations. In the presence of growth factors, such as EGF and HGF, the ability of sotorasib and adagrasib to inhibit KRAS was compromised whereas the TE kinetics of D3S-001 was nearly unaffected, a unique feature differentiating D3S-001 from other GDP-bound G12C inhibitors. Furthermore, the high covalent potency and cellular TE efficiency of D3S-001 contributed to robust anti-tumor activity preclinically and translated into promising clinical activity in an ongoing phase 1 trial (NCT05410145).

MRI findings in 1 case of primary gallbladder lymphoma.

We describe a case of gallbladder extra-nodal marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue (MALT-ML). MALT-ML is rare, and its clinical manifestations are lack of specificity. A few cases have been reported, and no characteristic imaging features have been described. We discussed the challenges of MRI in diagnosing MALT-ML of gallbladder, especially in differentiating it from gallbladder cancer. We found a "comb-like" sign in the inner wall of gallbladder on T2WI, which may be helpful in diagnosing gallbladder MALT-ML.

The Association of Malnutrition and Health-Related Factors among 474,467 Older Community-Dwellers: A Population-Based Data Mining Study in Guangzhou, China.

BACKGROUND: This study aimed to examine the prevalence and associated factors of malnutrition in older community-dwellers and explore the interaction between associated factors. METHODS: A total of 474,467 older community-dwellers aged 65 or above were selected in Guangzhou, China. We used a two-step methodology to detect the associated factors of malnutrition and constructed logistic regression models to explore the influencing factors and interactive effects on three patterns of malnutrition. RESULTS: The prevalence of malnutrition was 22.28%. Older adults with both hypertension and diabetes (RERI = 0.13), both meat or fish diet and hypertension (RERI = 0.79), and both meat or fish diet and diabetes (RERI = 0.81) had positive additive interaction effects on the risk of obesity, whereas those on a vegetarian diet with hypertension (RERI = -0.25) or diabetes (RERI = -0.19) had negative additive interaction effects. Moreover, the interactions of physical activity with a meat or fish diet (RERI = -0.84) or dyslipidemia (RERI = -0.09) could lower the risk of obesity. CONCLUSIONS: Malnutrition was influenced by different health factors, and there were interactions between these influencing factors. Pertinent dietary instruction should be given according to different nutritional status indexes and the prevalence of metabolic diseases to avoid the occurrences of malnutrition among older adults.

Rapid visual detection of Giardia duodenalis in faecal samples using an RPA-CRISPR/Cas12a system.

Giardiasis is a common intestinal infection caused by Giardia duodenalis, which is a major economic and health burden for humans and livestock. Currently, a convenient and effective detection method is urgently needed. CRISPR/Cas12a-based diagnostic methods have been widely used for nucleic acid-based detection of pathogens due to their high efficiency and sensitivity. In this study, a technique combining CRISPR/Cas12a and RPA was established that allows the detection of G. duodenalis in faecal samples by the naked eye with high sensitivity (10-1 copies/µL) and specificity (no cross-reactivity with nine common pathogens). In clinical evaluations, the RPA-CRISPR/Cas12a-based detection assay detected Giardia positivity in 2% (1/50) of human faecal samples and 47% (33/70) of cattle faecal samples, respectively, which was consistent with the results of nested PCR. Our study demonstrated that the RPA-CRISPR/Cas12a technique for G. duodenalis is stable, efficient, sensitive, specific and has low equipment requirements. This technique offers new opportunities for on-site detection in remote and poor areas.

Dexamethasone promotes renal fibrosis by upregulating ILT4 expression in myeloid-derived suppressor cells.

Studies have shown that adoptive transfer of myeloid-derived suppressor cells (MDSCs) can alleviate various inflammatory diseases, including glomerulonephritis, but the long-term effects of the transferred MDSCs are still unclear. In addition, although glucocorticoids exert immunosuppressive effects on inflammatory diseases by inducing the expansion of MDSCs, the impact of glucocorticoids on the immunosuppressive function of MDSCs and their molecular mechanisms are unclear. In this study, we found that adoptive transfer of MDSCs to doxorubicin-induced focal segmental glomerulosclerosis (FSGS) mice for eight consecutive weeks led to an increase in serum creatinine and proteinuria and aggravation of renal interstitial fibrosis. Similarly, 8 weeks of high-dose dexamethasone administration exacerbated renal interstitial injury and interstitial fibrosis in doxorubicin-induced mice, manifested as an increase in serum creatinine and proteinuria, collagen deposition and α-SMA expression. On this basis, we found that dexamethasone could enhance MDSC expression and secretion of the fibrosis-related cytokines TGF-ß and IL-10. Mechanistically, we revealed that dexamethasone promotes the expression of immunoglobulin-like transcription factor 4 (ILT4), which enhances the T-cell inhibitory function of MDSCs and promotes the activation of STAT6, thereby strengthening the expression and secretion of TGF-ß and IL-10. Knocking down ILT4 alleviated renal fibrosis caused by adoptive transfer of MDSCs. Therefore, our findings demonstrate that the role and mechanism of dexamethasone mediate the expression and secretion of TGF-ß and IL-10 in MDSCs by promoting the expression of ILT4, thereby leading to renal fibrosis.

Recombinant bivalent subunit vaccine combining truncated VP4 from P[7] and P[23] induces protective immunity against prevalent porcine rotaviruses.

Porcine rotaviruses (PoRVs) cause severe economic losses in the swine industry. P[7] and P[23] are the predominant genotypes circulating on farms, but no vaccine is yet available. Here, we developed a bivalent subunit PoRV vaccine using truncated versions (VP4*) of the VP4 proteins from P[7] and P[23]. The vaccination of mice with the bivalent subunit vaccine elicited more robust neutralizing antibodies (NAbs) and cellular immune responses than its components, even at high doses. The bivalent subunit vaccine and inactivated bivalent vaccine prepared from strains PoRVs G9P[7] and G9P[23] were used to examine their protective efficacy in sows and suckling piglets after passive immunization. The immunized sows showed significantly elevated NAbs in the serum and colostrum, and the suckling piglets acquired high levels of sIgA antibodies from the colostrum. Challenging subunit-vaccinated or inactivated-vaccinated piglets with homologous virulent strains did not induce diarrhea, except in one or two piglets, which had mild diarrhea. Immunization with the bivalent subunit vaccine and inactivated vaccine also alleviated the microscopic lesions in the intestinal tissues caused by the challenge with the corresponding homologous virulent strain. However, all the piglets in the challenged group displayed mild to watery diarrhea and high levels of viral shedding, whereas the feces and intestines of the piglets in the bivalent subunit vaccine and inactivated vaccine groups had lower viral loads. In summary, our data show for the first time that a bivalent subunit vaccine combining VP4*P[7] and VP4*P[23] effectively protects piglets against the diarrhea caused by homologous virulent strains.IMPORTANCEPoRVs are the main causes of diarrhea in piglets worldwide. The multisegmented genome of PoRVs allows the reassortment of VP4 and VP7 genes from different RV species and strains. The P[7] and P[23] are the predominant genotypes circulating in pig farms, but no vaccine is available at present in China. Subunit vaccines, as nonreplicating vaccines, are an option to cope with variable genotypes. Here, we have developed a bivalent subunit candidate vaccine based on a truncated VP4 protein, which induced robust humoral and cellular immune responses and protected piglets against challenge with homologous PoRV. It also appears to be safe. These data show that the truncated VP4-protein-based subunit vaccine is a promising candidate for the prevention of PoRV diarrhea.

Microalgae enhanced co-metabolism of sulfamethoxazole using aquacultural feedstuff components: Co-metabolic pathways and enzymatic mechanisms.

The application of antibiotics in freshwater aquaculture leads to increased contamination of aquatic environments. However, limited information is available on the co-metabolic biodegradation of antibiotics by microalgae in aquaculture. Feedstuffs provide multiple organic substrates for microalgae-mediated co-metabolism. Herein, we investigated the co-metabolism of sulfamethoxazole (SMX) by Chlorella pyrenoidosa when adding main components of feedstuff (glucose and lysine). Results showed that lysine had an approximately 1.5-fold stronger enhancement on microalgae-mediated co-metabolism of SMX than glucose, with the highest removal rate (68.77% ± 0.50%) observed in the 9-mM-Lys co-metabolic system. Furthermore, we incorporated reactive sites predicted by density functional theory calculations, 14 co-metabolites identified by mass spectrometry, and the roles of 18 significantly activated enzymes to reveal the catalytic reaction mechanisms underlying the microalgae-mediated co-metabolism of SMX. In lysine- and glucose-treated groups, five similar co-metabolic pathways were proposed, including bond breaking on the nucleophilic sulfur atom, ring cleavage and hydroxylation at multiple free radical reaction sites, together with acylation and glutamyl conjugation on electrophilic nitrogen atoms. Cytochrome P450, serine hydrolase, and peroxidase play crucial roles in catalyzing hydroxylation, bond breaking, and ring cleavage of SMX. These findings provide theoretical support for better utilization of microalgae-driven co-metabolism to reduce sulfonamide antibiotic residues in aquaculture.

Exploring aryl hydrocarbon receptor expression and distribution in the tumor microenvironment, with a focus on immune cells, in various solid cancer types.

Introduction: Aryl hydrocarbon receptor (AhR) is a transcription factor that performs various functions upon ligand activation. Several studies have explored the role of AhR expression in tumor progression and immune surveillance. Nevertheless, investigations on the distribution of AhR expression, specifically in cancer or immune cells in the tumor microenvironment (TME), remain limited. Examining the AhR expression and distribution in the TME is crucial for gaining insights into the mechanism of action of AhR-targeting anticancer agents and their potential as biomarkers. Methods: Here, we used multiplexed immunohistochemistry (mIHC) and image cytometry to investigate the AhR expression and distribution in 513 patient samples, of which 292 are patients with one of five solid cancer types. Additionally, we analyzed the nuclear and cytosolic distribution of AhR expression. Results: Our findings reveal that AhR expression was primarily localized in cancer cells, followed by stromal T cells and macrophages. Furthermore, we observed a positive correlation between the nuclear and cytosolic expression of AhR, indicating that the expression of AhR as a biomarker is independent of its localization. Interestingly, the expression patterns of AhR were categorized into three clusters based on the cancer type, with high AhR expression levels being found in regulatory T cells (Tregs) in non-small cell lung cancer (NSCLC). Discussion: These findings are anticipated to serve as pivotal evidence for the design of clinical trials and the analysis of the anticancer mechanisms of AhR-targeting therapies.

3D Artificial Skin Platform for Investigating Pregnancy-Related Skin Pigmentation.

In this study, we created a 3D Artificial Skin Platform that can be used for the treatment of pigmentation by artificially realizing the skin of pregnant women. For the stable realization of 3D artificial skin, a bilayer hydrogel composed of collagen type I and fibrin was designed and applied to the study to reduce the tension-induced contraction of collagen type I, the extracellular matrix (ECM) of artificial skin, by dynamic culture. Oxygen concentration and 17ß-Estradiol (E2) concentration, which are highly related to melanin production, were selected as parameters of the pregnancy environment and applied to cell culture. Oxygen concentration, which is locally reduced in the first trimester (2.5-3%), and E2, which is upregulated in the third trimester, were applied to the cell culture process. We analyzed whether the 3D artificial skin implemented in the 3D Artificial Skin Platform could better represent the tendency of melanin expression in pregnant women than cells cultured under the same conditions in 2D. The expression levels of melanin and melanin-related genes in the 2D cell culture did not show a significant trend that was similar to the melanin expression trend in pregnant women. However, the 3D artificial skin platform showed a significant trend towards a 2-6-fold increase in melanin expression in response to low oxygen concentrations (2.5%) and E2 concentrations (17 ng/mL), which was similar to the trend in pregnant women in vivo. These results suggest that 3D artificial skin cultured on the Artificial Skin Platform has the potential to be used as a substitute for human pregnant skin in various research fields related to the treatment of pigmentation.

Taste-Active Peptides from Triple-Enzymatically Hydrolyzed Straw Mushroom Proteins Enhance Salty Taste: An Elucidation of Their Effect on the T1R1/T1R3 Taste Receptor via Molecular Docking.

The objective of our study was to analyze and identify enzymatic peptides from straw mushrooms that can enhance salty taste with the aim of developing saltiness enhancement peptides to reduce salt intake and promote dietary health. We isolated taste-related peptides from the straw mushroom extract using ultrafiltration and identified them using UPLC-Q-TOF-MS/MS. The study found that the ultrafiltration fraction (500-2000 Da) of straw mushroom peptides had a saltiness enhancement effect, as revealed via subsequent E-tongue and sensory analyses. The ultrafiltration fractions (500-2000 Da) were found to contain 220 peptides, which were identified through UPLC-Q-TOF-MS/MS analysis. The interaction of these peptides with the T1R1/T1R3 receptor was also assessed. The investigation highlighted the significant involvement of Asp223, Gln243, Leu232, Asp251, and Pro254 in binding peptides from triple-enzymatically hydrolyzed straw mushrooms to T1R1/T1R3. Based on the binding energy and active site analysis, three peptides were selected for synthesis: DFNALPFK (-9.2 kcal/mol), YNEDNGIVK (-8.8 kcal/mol), and VPGGQEIKDR (-8.9 kcal/mol). Importantly, 3.2 mmol of VPGGQEIKDR increased the saltiness level of a 0.05% NaCl solution to that of a 0.15% NaCl solution. Additionally, the addition of 0.8 mmol of YNEDNGIVK to a 0.05% NaCl solution resulted in the same level of saltiness as a 0.1% NaCl solution.

Application of Multimodal Transformer Model in Intelligent Agricultural Disease Detection and Question-Answering Systems.

In this study, an innovative approach based on multimodal data and the transformer model was proposed to address challenges in agricultural disease detection and question-answering systems. This method effectively integrates image, text, and sensor data, utilizing deep learning technologies to profoundly analyze and process complex agriculture-related issues. The study achieved technical breakthroughs and provides new perspectives and tools for the development of intelligent agriculture. In the task of agricultural disease detection, the proposed method demonstrated outstanding performance, achieving a precision, recall, and accuracy of 0.95, 0.92, and 0.94, respectively, significantly outperforming the other conventional deep learning models. These results indicate the method's effectiveness in identifying and accurately classifying various agricultural diseases, particularly excelling in handling subtle features and complex data. In the task of generating descriptive text from agricultural images, the method also exhibited impressive performance, with a precision, recall, and accuracy of 0.92, 0.88, and 0.91, respectively. This demonstrates that the method can not only deeply understand the content of agricultural images but also generate accurate and rich descriptive texts. The object detection experiment further validated the effectiveness of our approach, where the method achieved a precision, recall, and accuracy of 0.96, 0.91, and 0.94. This achievement highlights the method's capability for accurately locating and identifying agricultural targets, especially in complex environments. Overall, the approach in this study not only demonstrated exceptional performance in multiple tasks such as agricultural disease detection, image captioning, and object detection but also showcased the immense potential of multimodal data and deep learning technologies in the application of intelligent agriculture.

Effects of Rosa multiflora root extract on adipogenesis and lipogenesis in 3T3-L1 adipocytes and SD rat models.

BACKGROUND/OBJECTIVES: Obesity is a major cause of metabolic disorders; to prevent obesity, research is ongoing to develop natural and safe ingredients with few adverse effects. In this study, we determined the anti-obesity effects of Rosa multiflora root extract (KWFD-H01) in 3T3-L1 adipocytes and Sprague-Dawley (SD) rats. MATERIALS/METHODS: The anti-obesity effects of KWFD-H01in 3T3-L1 adipocytes and SD rats were examined using various assays, including Oil Red O staining, gene expression analyses, protein expression analyses, and blood biochemical analyses. RESULTS: KWFD-H01 reduced intracellular lipid accumulation and inhibited the mRNA expression of peroxisome proliferator-activated receptor γ (PPARγ), cytidine-cytidine-adenosine-adenosine-thymidine (CCAAT)/enhancer binding proteins (C/EBPα), sterol regulatory element-binding transcription factor 1 (SREBP-1c), acetyl-CoA carboxylase (ACC), and fatty acid synthase (FAS) in 3T3-L1 cells. KWFD-H01 also reduced body weight, weight gain, and the levels of triglycerides, total and LDL-cholesterol, glucose, and leptin, while increasing high-density lipoprotein-cholesterol and adiponectin in SD rats. PPARγ, C/EBPα, SREBP-1c, ACC, and FAS protein expression was inhibited in the epididymal fat of SD rats. CONCLUSION: Overall, these results confirm the anti-obesity effects of KWFD-H01 in 3T3-L1 adipocytes and SD rats, indicating their potential as baseline data for developing functional health foods or pharmaceuticals to control obesity.

Ethylene/Polar Monomer Copolymerization by [N, P] Ti Complexes: Polar Copolymers with Ultrahigh-Molecular Weight.

A series of novel titanium complexes (2a-2e) bearing [N, P] aniline-chlorodiphenylphosphine ligands (1a-1e) featuring CH3 and F substituents have been synthesized and characterized. Surprisingly, in the presence of polar additive, the complexes (2a-2e) all displayed high catalytic activities (up to 1.04 × 106 gPolymer (mol·Ti)-1·h-1 and produced copolymer with the ultrahigh molecular weight up to 1.37 × 106 g/mol. The catalytic activities are significantly enhanced by introducing electron-withdrawing group (F) into the aniline aromatic ring. Especially, the increase in activity based on different complexes followed the order of 2e > 2d > 2c > 2b > 2a. Simultaneously, density functional theory (DFT) calculations have been performed to probe the polymerization mechanism as well as the electronic and steric effects of various substituents on the catalyst backbone. DFT computation revealed that the polymerization behaviors could be adjusted by the electronic effect of ligand substituents; however, it has little to do with the steric hindrance of the substituents. Furthermore, theoretical calculation results keep well in accordance with experimental measurement results. The article provided an appealing design method that the employment of fluorine atom as electron-withdrawing to be studied is the promotive effect of transition-metal coordination polymerization.

Enrichment and MALDI-TOF MS Analysis of Phosphoinositides in Brain Tissue.

Triazolium cyclodextrin click cluster (+CCC) is an ideal scaffold to specifically bind phosphoinositides (PIPs) via multivalent electrostatic interaction. A new enrichment material, triazolium cyclodextrin click cluster-magnetic agarose bead conjugate (+CCC-MAB), was synthesized and applied to the PIP enrichment of brain tissue. The enriched sample was analyzed using MALDI-TOF MS in negative ion mode without any derivatization. The PIP extract of brain tissue is known to contain abundant lipid interferences. By employing magnetic pull-down separation using +CCC-MAB, we effectively removed the weak-binding interferences in the PIP extract, thereby improving the signal-to-noise ratio (S/N) of the PIPs. Our +CCC-MAB-based PIP enrichment enabled us to analyze 16 PIP species in brain tissue. Six species with high S/N were assigned by MS/MS, while the remaining 10 species with low S/N were characterized by an empirical selection guide based on the biological relevance of PIPs. We conclude that +CCC-MAB-based PIP enrichment is a promising MALDI sample preparation method for specific PIP analysis in brain tissue.

Unveiling the anticancer effects of SGLT-2i: mechanisms and therapeutic potential.

Cancer and diabetes are significant diseases that pose a threat to human health. Their interconnection is complex, particularly when they coexist, often necessitating multiple therapeutic approaches to attain remission. Sodium-glucose cotransporter protein two inhibitors (SGLT-2i) emerged as a treatment for hyperglycemia, but subsequently exhibited noteworthy extra-glycemic properties, such as being registered for the treatment of heart failure and chronic kidney disease, especially with co-existing albuminuria, prompting its assessment as a potential treatment for various non-metabolic diseases. Considering its overall tolerability and established use in diabetes management, SGLT-2i may be a promising candidate for cancer therapy and as a supplementary component to conventional treatments. This narrative review aimed to examine the potential roles and mechanisms of SGLT-2i in the management of diverse types of cancer. Future investigations should focus on elucidating the antitumor efficacy of individual SGLT-2i in different cancer types and exploring the underlying mechanisms. Additionally, clinical trials to evaluate the safety and feasibility of incorporating SGLT-2i into the treatment regimen of specific cancer patients and determining appropriate dosage combinations with established antitumor agents would be of significant interest.