Deep Learning-Assisted Spectrum-Structure Correlation: State-of-the-Art and Perspectives.

Spectrum-structure correlation is playing an increasingly crucial role in spectral analysis and has undergone significant development in recent decades. With the advancement of spectrometers, the high-throughput detection triggers the explosive growth of spectral data, and the research extension from small molecules to biomolecules accompanies massive chemical space. Facing the evolving landscape of spectrum-structure correlation, conventional chemometrics becomes ill-equipped, and deep learning assisted chemometrics rapidly emerges as a flourishing approach with superior ability of extracting latent features and making precise predictions. In this review, the molecular and spectral representations and fundamental knowledge of deep learning are first introduced. We then summarize the development of how deep learning assist to establish the correlation between spectrum and molecular structure in the recent 5 years, by empowering spectral prediction (i.e., forward structure-spectrum correlation) and further enabling library matching and de novo molecular generation (i.e., inverse spectrum-structure correlation). Finally, we highlight the most important open issues persisted with corresponding potential solutions. With the fast development of deep learning, it is expected to see ultimate solution of establishing spectrum-structure correlation soon, which would trigger substantial development of various disciplines.

Untargeted LC-MS metabolomics reveals the metabolic responses in the Eriocheir sinensis gills exposed to salinity and alkalinity stress.

In recent years, saline-alkaline aquaculture development has become an important measure for China to expand its fishery development space to ensure food safety. Previous studies have verified that salinity and alkalinity positively influence the quality of Chinese mitten crabs (Eriocheir sinensis). However, the regulatory mechanism of E. sinensis endures saline-alkaline stress which remains obscure. This study investigated the metabolic changes in puberty-molting E. sinensis gills exposed to freshwater (FW), sodium chloride salinity of 5 ppt (SW), and carbonate alkalinity 10.00 mmol/L (AW) for 50 days using untargeted liquid chromatography-mass spectrometry metabolomics (LC-MS). A total of 5802 (positive-ion mode) and 6520 (negative-ion mode) peaks were extracted by LC-MS, respectively. A total of 188 (50 upregulated and 138 downregulated), 141 (94 upregulated and 47 downregulated), and 130 (87 upregulated and 43 downregulated) significantly regulated metabolites (SRMs) were observed in the FW-SW, FW-AW, and SW-AW treatments, respectively, wherein 42 generic SRMs were also found by Venn diagram analysis. Seven of the top 10 SRMs with the highest (variable importance in projection) VIP values were similarly identified in FW-SW and SW-AW. Integrated analysis of key metabolic pathways revealed glycerophospholipid, choline in cancer, phenylalanine, and butanoate metabolism. Overall, significant differences were observed in the metabolites and key metabolic pathways of E. sinensis gill exposed to salinity and alkalinity stress. These results will be helpful in understanding the environmental adaptability of aquatic crustaceans to saline-alkaline water.

Signal2signal: Pushing the Spatiotemporal Resolution to the Limit by Single Chemical Hyperspectral Imaging.

There is growing interest in developing a high-performance self-supervised denoising algorithm for real-time chemical hyperspectral imaging. With a good understanding of the working function of the zero-shot Noise2Noise-based denoising algorithm, we developed a self-supervised Signal2Signal (S2S) algorithm for real-time denoising with a single chemical hyperspectral image. Owing to the accurate distinction and capture of the weak signal from the random fluctuating noise, S2S displays excellent denoising performance, even for the hyperspectral image with a spectral signal-to-noise ratio (SNR) as low as 1.12. Under this condition, both the image clarity and the spatial resolution could be significantly improved and present an almost identical pattern with a spectral SNR of 7.87. The feasibility of real-time denoising during imaging was well demonstrated, and S2S was applied to monitor the photoinduced exfoliation of transition metal dichalcogenide, which is hard to accomplish by confocal Raman spectroscopy. In general, the real-time denoising capability of S2S offers an easy way toward in situ/in vivo/operando research with much improved spatial and temporal resolution. S2S is open-source at https://github.com/3331822w/Signal2signal and will be accessible online at https://ramancloud.xmu.edu.cn/tutorial.

High Expression Level of TRIP6 is Correlated with Poor Prognosis in Colorectal Cancer and Promotes Tumor Cell Proliferation and Migration.

Globally, colorectal cancer (CRC) is one of the leading causes of health problems. More reliable molecular biomarkers for early diagnosis in CRC patients are needed. A crucial role for thyroid hormone receptor interacting protein 6 (TRIP6) is played in tumorigenesis and tumor growth. Our study aims to determine the diagnostic and prognostic roles of TRIP6 at CRC. TRIP6 gene expression levels were analyzed in this study from public databases. The relationship between TRIP6 expression and clinicopathological characteristics was explored by logistic regression analysis. Based on Kaplan-Meier (K-M) survival curves and receiver operating characteristic curves (ROC) analysis, the prognostic and diagnostic values of TRIP6 were determined. Protein-protein interaction (PPI) networks analysis were performed using the STRING database. A Spearman's correlation analysis applied for examining the correlation between TRIP6 expression, immune cell infiltration, and immune checkpoint genes. Moreover, colony formation assay and transwell assay were used to investigate the functions of TRIP6. TRIP6 was highly expressed in CRC cancer tissues and cells. K-M survival analysis indicated that a high expression of TRIP6 was associated with poor prognosis. TRIP6 expression was obviously associated with immune cell infiltration and immune checkpoint gene expression. For validation, the results of collected clinical CRC samples show that TRIP6 levels in CRC tumor tissue were higher than those of paired adjacent colorectal tissues. Additionally, in vitro experiments suggested that TRIP6 knockdown suppressed proliferation and migration in CRC cell line RKO. TRIP6 overexpression promoted the proliferation and migration of normal colon cell line NCM460. High TRIP6 expression is associated with poor prognosis in colorectal cancer and promotes tumor cell proliferation and migration which may be a potential diagnostic and prognostic biomarker and a promising therapeutic target for CRC, providing new insights into its role in CRC.

Decomposed FDG PET-based phenotypic heterogeneity predicting clinical prognosis and decision-making in temporal lobe epilepsy patients.

OBJECTIVE: This study utilized a data-driven Bayesian model to automatically identify distinct latent disease factors represented by overlapping glucose metabolism patterns from 18F-Fluorodeoxyglucose PET (18F-FDG PET) to analyze heterogeneity among patients with TLE. METHODS: We employed unsupervised machine learning to estimate latent disease factors from 18F-FDG PET scans, representing whole-brain glucose metabolism patterns in seventy patients with TLE. We estimated the extent to which multiple distinct factors were expressed within each participant and analyzed their relevance to epilepsy burden, including seizure onset, duration, and frequency. Additionally, we established a predictive model for clinical prognosis and decision-making. RESULTS: We identified three latent disease factors: hypometabolism in the unilateral temporal lobe and hippocampus (factor 1), hypometabolism in bilateral prefrontal lobes (factor 2), and hypometabolism in bilateral temporal lobes (factor 3), variably co-expressed within each patient. Factor 3 demonstrated the strongest negative correlation with the age of onset and duration (r = - 0.33, - 0.38 respectively, P < 0.05). The supervised classifier, trained on latent disease factors for predicting patient-specific antiepileptic drug (AED) responses, achieved an area under the curve (AUC) of 0.655. For post-surgical seizure outcomes, the AUC was 0.857, and for clinical decision-making, it was 0.965. CONCLUSIONS: Decomposing 18F-FDG PET-based phenotypic heterogeneity facilitates individual-level predictions relevant to disease monitoring and personalized therapeutic strategies.

Optimization of Bear Oil Extraction Process and Hair Growth Activity.

According to ancient Chinese books, bear grease has the effects of strengthening muscles and bones, which is beneficial for weakness, but there is relatively little research on it. Thus, the extraction of it is beneficial for compensating for research in this area. In this study, a uniform experimental design method was used to optimize the extraction process of bear grease by enzymatic hydrolysis extraction, and the extraction rate can reach 81.89% under optimized extraction conditions. Furthermore, the components of bear grease obtained by this study were analyzed by GC-MS, and the results showed that ursolic oil was rich in unsaturated fatty acids (67.51%), which was higher than that of the traditional method (66.92%). The composition of bear grease extracted by the enzymatic method was also better than that extracted by the traditional method. In addition, bear grease obtained in this study had the obvious activity of promoting hair growth. The length, weight, and number of hair follicles in the depilation area of mice in the high-dose group were significantly different from those in the blank group (p < 0.01). This study optimized the extraction process of bear grease and conducted a preliminary analysis of its fatty acid composition, which is expected to provide some reference for the development of the medicinal value of bear grease.

The impact of smoking and alcohol consumption on rosacea: a multivariable Mendelian randomization study.

Backgrounds: Observational studies have shown that cigarette smoking is inversely associated with risk of rosacea, However, it remains uncertain whether this association is causal or it is a result of reverse causation, and whether this association is affected by drinking behaviors. Methods: This study utilized the summary-level data from the largest genome-wide association study (GWAS) for smoking, alcohol consumption, and rosacea. The objective was to investigate the effect of genetically predicted exposures to smoking and alcohol consumption on the risk of developing rosacea. Two-sample bidirectional Mendelian randomization (MR) was applied, accompanied by sensitive analyses to validate the robustness of findings. Furthermore, multivariable MR was conducted to evaluate the direct impact of smoking on rosacea. Results: A decreased risk of rosacea was observed in individuals with genetically predicted lifetime smoking [odds ratio (OR)MR - IVW = 0.53; 95% confidence interval (CI), 0.318-0.897; P = 0.017], and number of cigarettes per day (ORMR - IVW = 0.55; 95% CI, 0.358-0.845; P = 0.006). However, no significant associations were found between initiation of regular smoking, smoking cessation, smoking initiation, alcohol consumption and rosacea. Reverse MR analysis did not show any associations between genetic liability toward rosacea and smoking or alcohol drinking. Importantly, the effect of lifetime smoking and the number of cigarettes per day on rosacea remained significant even after adjusting for alcohol consumption in multivariable MR analysis. Conclusion: Smoking was causally related to a lower risk of rosacea, while alcohol consumption does not appear to be associated with risk of rosacea.

Revealing the Denoising Principle of Zero-Shot N2N-Based Algorithm from 1D Spectrum to 2D Image.

Denoising is a necessary step in image analysis to extract weak signals, especially those hardly identified by the naked eye. Unlike the data-driven deep-learning denoising algorithms relying on a clean image as the reference, Noise2Noise (N2N) was able to denoise the noise image, providing sufficiently noise images with the same subject but randomly distributed noise. Further, by introducing data augmentation to create a big data set and regularization to prevent model overfitting, zero-shot N2N-based denoising was proposed in which only a single noisy image was needed. Although various N2N-based denoising algorithms have been developed with high performance, their complicated black box operation prevented the lightweight. Therefore, to reveal the working function of the zero-shot N2N-based algorithm, we proposed a lightweight Peak2Peak algorithm (P2P) and qualitatively and quantitatively analyzed its denoising behavior on the 1D spectrum and 2D image. We found that the high-performance denoising originates from the trade-off balance between the loss function and regularization in the denoising module, where regularization is the switch of denoising. Meanwhile, the signal extraction is mainly from the self-supervised characteristic learning in the data augmentation module. Further, the lightweight P2P improved the denoising speed by at least ten times but with little performance loss, compared with that of the current N2N-based algorithms. In general, the visualization of P2P provides a reference for revealing the working function of zero-shot N2N-based algorithms, which would pave the way for the application of these algorithms toward real-time (in situ, in vivo, and operando) research improving both temporal and spatial resolutions. The P2P is open-source at https://github.com/3331822w/Peak2Peakand will be accessible online access at https://ramancloud.xmu.edu.cn/tutorial.

Ginger polysaccharide alleviates the effects of acute exposure to carbonate in crucian carp (Carassius auratus) by regulating immunity, intestinal microbiota, and intestinal metabolism.

Alkaline stress poses a significant challenge to the healthy growth of fish. Ginger polysaccharide (GP) is one of the main active substances in ginger and has pharmacological effects, such as anti-oxidation and immune regulation. However, the physiological regulatory mechanism of GP addition to diet on alkalinity stress in crucian carp remains unclear. This study aimed to investigate the potential protective effects of dietary GP on antioxidant capacity, gene expression levels, intestinal microbiome, and metabolomics of crucian carp exposed to carbonate (NaHCO3). The CK group (no GP supplementation) and COG group (NaHCO3 stress and no GP supplementation) were set up. The GPCS group (NaHCO3 stress and 0.4% GP supplementation) was stressed for seven days. Based on these data, GP significantly increased the activities of total antioxidant capacity (T-AOC), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-PX), acid phosphatase (ACP), and alkaline phosphatase (AKP) in carp under alkalinity stress (p < 0.05) and decreased the activity of malon dialdehyde (MDA) (p < 0.05). GP restored the activity of GSH-PX, ACP, and AKP to CK levels. The expression levels of tumor necrosis factor ß (TGF-ß), tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), and interleukin 8 (IL-8) genes were decreased, and the expression levels of determination factor kappa-B (NF-κB) and interleukin 10 (IL-10) genes were increased (p < 0.05). Based on 16 S rRNA high-throughput sequencing, GP improved the changes in the intestinal microbial diversity and structural composition of crucian carp caused by NaHCO3 exposure. In particular, GP increased the relative abundance of Proteobacteria and Bacteroidetes and decreased the relative abundance of Actinobacteria. The metabolic response of GP to NaHCO3 exposed crucian carp guts was studied using LC/MS. Compared to the COG group, the GPCS group had 64 different metabolites and enriched 10 metabolic pathways, including lipid metabolism, nucleotide metabolism, and carbohydrate metabolism. The addition of GP to feed can promote galactose metabolism and provide an energy supply to crucian carp, thus alleviating the damage induced by alkalinity stress. In conclusion, GP can mitigate the effects of NaHCO3 alkalinity stress by regulating immune function, intestinal flora, and intestinal metabolism in crucian carp. These findings provide a novel idea for studying the mechanism of salt-alkali tolerance in crucian carp by adding GP to feed.

A therapeutic hepatitis B mRNA vaccine with strong immunogenicity and persistent virological suppression.

Here we report on the development and comprehensive evaluations of an mRNA vaccine for chronic hepatitis B (CHB) treatment. In two different HBV carrier mouse models generated by viral vector-mediated HBV transfection (pAAV-HBV1.2 and rAAV8-HBV1.3), this vaccine demonstrates sufficient and persistent virological suppression, and robust immunogenicity in terms of induction of strong innate immune activation, high-level virus-specific antibodies, memory B cells and T cells. mRNA platform therefore holds prospects for therapeutic vaccine development to combat CHB.

Patch-Based Convolutional Encoder: A Deep Learning Algorithm for Spectral Classification Balancing the Local and Global Information.

Molecular vibrational spectroscopies, including infrared absorption and Raman scattering, provide molecular fingerprint information and are powerful tools for qualitative and quantitative analysis. They benefit from the recent development of deep-learning-based algorithms to improve the spectral, spatial, and temporal resolutions. Although a variety of deep-learning-based algorithms, including those to simultaneously extract the global and local spectral features, have been developed for spectral classification, the classification accuracy is still far from satisfactory when the difference becomes very subtle. Here, we developed a lightweight algorithm named patch-based convolutional encoder (PACE), which effectively improved the accuracy of spectral classification by extracting spectral features while balancing local and global information. The local information was captured well by segmenting the spectrum into patches with an appropriate patch size. The global information was extracted by constructing the correlation between different patches with depthwise separable convolutions. In the five open-source spectral data sets, PACE achieved a state-of-the-art performance. The more difficult the classification, the better the performance of PACE, compared with that of residual neural network (ResNet), vision transformer (ViT), and other commonly used deep learning algorithms. PACE helped improve the accuracy to 92.1% in Raman identification of pathogen-derived extracellular vesicles at different physiological states, which is much better than those of ResNet (85.1%) and ViT (86.0%). In general, the precise recognition and extraction of subtle differences offered by PACE are expected to facilitate vibrational spectroscopy to be a powerful tool toward revealing the relevant chemical reaction mechanisms in surface science or realizing the early diagnosis in life science.

Plant invasion and naturalization are influenced by genome size, ecology and economic use globally.

Human factors and plant characteristics are important drivers of plant invasions, which threaten ecosystem integrity, biodiversity and human well-being. However, while previous studies often examined a limited number of factors or focused on a specific invasion stage (e.g., naturalization) for specific regions, a multi-factor and multi-stage analysis at the global scale is lacking. Here, we employ a multi-level framework to investigate the interplay between plant characteristics (genome size, Grime's adaptive CSR-strategies and native range size) and economic use and how these factors collectively affect plant naturalization and invasion success worldwide. While our findings derived from structural equation models highlight the substantial contribution of human assistance in both the naturalization and spread of invasive plants, we also uncovered the pivotal role of species' adaptive strategies among the factors studied, and the significantly varying influence of these factors across invasion stages. We further revealed that the effects of genome size on plant invasions were partially mediated by species adaptive strategies and native range size. Our study provides insights into the complex and dynamic process of plant invasions and identifies its key drivers worldwide.

The Biochemical Composition and Quality of Adult Chinese Mitten Crab Eriocheir sinensis Reared in Carbonate-Alkalinity Water.

Saline-alkaline aquaculture has become an important breakthrough in expanding the space available for aquaculture in China. However, the biochemical composition and quality of Eriocheir sinensis reared in carbonate alkalinity water are still unclear. Therefore, this study investigated the edible yield, coloration, and nutritional and flavor quality of Eriocheir sinensis. A significantly lower gonadosomatic index (GSI), meat yield (MY), and total edible yield (TEY) were detected in intensive pond (IP) samples than those in semi-intensive reed wetland (SIWR) (p < 0.05). Six color parameters in the hepatopancreas (p < 0.05) differed between IP and SIRW. The contents of crude protein and fat in the female hepatopancreas of IP were significantly higher than those in SIRW (p < 0.05). The concentrations of total monounsaturated fatty acids (∑MUFA), total essential fatty acids (∑EFA), and hypocholesterolaemic/hypercholesterolaemic ratio (h/H) in the female edible tissues checked were higher in IP than those in SIRW, with significant differences including ∑MUFA in the hepatopancreas and ovary, ∑EFA in the muscle, and h/H in the ovary (p < 0.05). Higher total free amino acid (∑FAA) contents of muscle were detected in SIRW than that in IP samples. Significantly higher K, Ca, Mg, Fe, and Zn contents in the ovary were detected in SIRW samples compared to IP (p < 0.05). Overall, Eriocheir sinensis reared in carbonate-alkalinity water is an important source of nutrients.

Selection and Validation of Reference Genes for Gene Expression in Bactericera gobica Loginova under Different Insecticide Stresses.

Insecticide resistance has long been a problem in crop pest control. Bactericera gobica is a major pest on the well-known medicinal plants Lycium barbarum L. Investigating insecticide resistance mechanisms of B. gobica will help to identify pesticide reduction strategies to control the pest. Gene expression normalization by RT-qPCR requires the selection and validation of appropriate reference genes (RGs). Here, 15 candidate RGs were selected from transcriptome data of B. gobica. Their expression stability was evaluated with five algorithms (Delta Ct, GeNorm, Normfinder, BestKeeper and RefFinder) for sample types differing in response to five insecticide stresses and in four other experimental conditions. Our results indicated that the RGs RPL10 + RPS15 for Imidacloprid and Abamectin; RPL10 + AK for Thiamethoxam; RPL32 + RPL10 for λ-cyhalothrin; RPL10 + RPL8 for Matrine; and EF2 + RPL32 under different insecticide stresses were the most suitable RGs for RT-qPCR normalization. EF1α + RPL8, EF1α + ß-actin, ß-actin + EF2 and ß-actin + RPS15 were the optimal combination of RGs under odor stimulation, temperature, developmental stages and both sexes, respectively. Overall, EF2 and RPL8 were the two most stable RGs in all conditions, while α-TUB and RPL32 were the least stable RGs. The corresponding suitable RGs and one unstable RG were used to normalize a target cytochrome P450 CYP6a1 gene between adult and nymph stages and under imidacloprid stress. The results of CYP6a1 expression were consistent with transcriptome data. This study is the first research on the most stable RG selection in B. gobica nymphs exposed to different insecticides, which will contribute to further research on insecticide resistance mechanisms in B. gobica.

Amphibian-derived peptide RL-RF10 ameliorates paraquat-induced pulmonary fibrosis injury.

Pulmonary fibrosis is the result of dysfunctional repair after lung tissue injury, characterized by fibroblast proliferation and massive extracellular matrix aggregation. Once fibrotic lesions develop, effective treatment is difficult, with few drugs currently available. Here, we identified a short cyclic decapeptide RL-RF10 derived from frog skin secretions as a potential novel lead molecule for the amelioration of pulmonary fibrosis. In vivo experiments indicated that RL-RF10 treatment ameliorated lung histopathological damage and fibrogenesis after paraquat (PQ) induction in a concentration-dependent manner. On day 7, bronchoalveolar lavage fluid assays performed on mice showed that RL-RF10 exerted anti-inflammatory effects by decreasing the expression of inflammation-related factors, including transforming growth factor-ß1 (TGF-ß1) and tumor necrosis factor-α, in lung tissue. In addition, RL-RF10 down-regulated the levels of collagen I, collagen III, and vimentin, while increasing the expression of E-cadherin to inhibit epithelial-mesenchymal transition. Further research demonstrated that the SMAD2/3 signaling pathway, which is strongly linked to TGF-ß1, played a critical function in enhancing the pulmonary fibrosis relief achieved by RL-RF10. Both in vivo and in vitro assays showed that RL-RF10 treatment led to a significant reduction in the phosphorylation levels of SMAD2 and SMAD3 following PQ induction. Overall, we investigated the protective effects and underlying mechanisms of the RL-RF10 peptide against pulmonary fibrosis and demonstrated its potential as a novel therapeutic drug candidate for the treatment of pulmonary fibrotic diseases.

Identification of Fasudil as a collaborator to promote the anti-tumor effect of lenvatinib in hepatocellular carcinoma by inhibiting GLI2-mediated hedgehog signaling pathway.

Lenvatinib is a frontline tyrosine kinase inhibitor for patients with advanced hepatocellular carcinoma (HCC). However, just 25% of patients benefit from the treatment, and acquired resistance always develops. To date, there are neither effective medications to combat lenvatinib resistance nor accurate markers that might predict how well a patient would respond to the lenvatinib treatment. Thus, novel strategies to recognize and deal with lenvatinib resistance are desperately needed. In the current study, a robust Lenvatinib Resistance index (LRi) model to predict lenvatinib response status in HCC was first established. Subsequently, five candidate drugs (Mercaptopurine, AACOCF3, NU1025, Fasudil, and Exisulind) that were capable of reversing lenvatinib resistance signature were initially selected by performing the connectivity map (CMap) analysis, and fasudil finally stood out by conducting a series of cellular functional assays in vitro and xenograft mouse model. Transcriptomics revealed that the co-administration of lenvatinib and fasudil overcame lenvatinib resistance by remodeling the hedgehog signaling pathway. Mechanistically, the feedback activation of EGFR by lenvatinib led to the activation of the GLI2-ABCC1 pathway, which supported the HCC cell's survival and proliferation. Notably, co-administration of lenvatinib and fasudil significantly inhibited IHH, the upstream switch of the hedgehog pathway, to counteract GLI2 activation and finally enhance the effectiveness of lenvatinib. These findings elucidated a novel EGFR-mediated mechanism of lenvatinib resistance and provided a practical approach to overcoming drug resistance in HCC through meaningful drug repurposing strategies.

Enhanced gene transfection and induction of apoptosis in melanoma cells by branched poly(ß-amino ester)s with uniformly distributed branching units.

Melanoma, one of the most devastating forms of skin cancer, currently lacks effective clinical treatments. Delivery of functional genes to modulate specific protein expression to induce melanoma cell apoptosis could be a promising therapeutic approach. However, transfecting melanoma cells using non-viral methods, particularly with cationic polymers, presents significant challenges. In this study, we synthesized three branched poly(ß-amino ester)s (HPAEs) with evenly distributed branching units but varying space lengths through a two-step "oligomer combination" strategy. The unique topological structure enables HPAEs to condense DNA to form nano-sized polyplexes with favorable physiochemical properties. Notably, HPAEs, especially HPAE-2 with intermediate branching unit space length, demonstrated significantly higher gene transfection efficiency than the leading commercial gene transfection reagent, jetPRIME, in human melanoma cells. Furthermore, HPAE-2 efficiently delivered the Bax-encoding plasmid into melanoma cells, leading to a pronounced pro-apoptotic effect without causing noticeable cytotoxicity. This study establishes a potent non-viral platform for gene transfection of melanoma cells by harnessing the distribution of branching units, paving the way for potential clinical applications of gene therapy in melanoma treatment.

HSP90a promotes the resistance to oxaliplatin in HCC through regulating IDH1-induced cell competition.

Though burgeoning research manifests that cell competition, an essential selection and quality control mechanism for maintaining tissue or organ growth and homeostasis in multicellular organisms, is closely related to tumorigenesis and development, the mechanism of cell competition associated with tumor drug resistance remains elusive. In the study, we uncovered that oxaliplatin-resistant hepatocellular carcinoma (HCC) cells exhibit a pronounced competitive advantage against their sensitive counterparts, which is related to lipid takeover of resistant cells from sensitive cells. Of note, such lipid takeover is dependent on the existence of isocitrate dehydrogenase 1 (IDH1) in resistant HCC cells. Mechanistically, IDH1 activity is regulated by heat shock protein 90 alpha (HSP90α) through binding with each other, which orchestrates the expressions of lipid metabolic enzymes and lipid accumulation in resistant HCC cells. Our results suggest that HCC cell competition-driven chemoresistance can be regulated by HSP90α/IDH1-mediated lipid metabolism, which may serve as a promising target for overcoming drug resistance in HCC.

Post-endoscopic submucosal dissection phlegmonous enteritis: A case report and literature review.

Background: This study presents the initial case of phlegmonous enteritis following endoscopic submucosal dissection (ESD), a rare and potentially fatal complication. Additionally, a comprehensive review of relevant literature is provided. Case report: A 66-year-old female patient, diagnosed with Hashimoto's thyroiditis and thrombocytopenia, underwent ESD to address a laterally spreading tumor located in the ascending colon. After the procedure, the patient manifested abdominal pain and a high fever, was diagnosed with peritonitis, necessitating an emergency exploratory laparotomy and right hemicolectomy. Subsequent histological examination indicated a significant presence of neutrophil infiltration across all layers of the intestines. The ascites culture yielded the growth of Escherichia coli. Literature review: A search was conducted in the PubMed database to identify case reports conforming to the definition of phlegmonous enteritis proposed by Rokitansky et al. We retrieved about 30 studies regarding phlegmonous enteritis from 1951 to 2022, with around 39 cases. Among these, only 28 patients had comprehensive medical data available. Subsequently, an examination of the literature was undertaken to explore the pathogenesis, prevention, and treatment of phlegmonous enteritis. Conclusion: The possibility of phlegmonous enteritis should be taken into consideration in cases of unexplained acute abdomen, particularly in patients with compromised immunity, in order to provide active surgical and antibiotic interventions.