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End-to-end learned image compression codecs have notably emerged in recent years. These codecs have demonstrated superiority over conventional methods, showcasing remarkable flexibility and adaptability across diverse data domains while supporting new distortion losses. Despite challenges such as computational complexity, learned image compression methods inherently align with learning-based data processing and analytic pipelines due to their well-suited internal representations. The concept of Video Coding for Machines has garnered significant attention from both academic researchers and industry practitioners. This concept reflects the growing need to integrate data compression with computer vision applications. In light of these developments, we present a comprehensive survey and review of lossy image compression methods. Additionally, we provide a concise overview of two prominent international standards, MPEG Video Coding for Machines and JPEG AI. These standards are designed to bridge the gap between data compression and computer vision, catering to practical industry use cases.

Glioblastoma (GBM) is a malignant brain tumor, commonly treated with temozolomide (TMZ). Upregulation of A disintegrin and metalloproteinases (ADAMs) is correlated to malignancy; however, whether ADAMs modulate TMZ sensitivity in GBM cells remains unclear. To explore the role of ADAMs in TMZ resistance, we analyzed changes in ADAM expression following TMZ treatment using RNA sequencing and noted that ADAM17 was markedly upregulated. Hence, we established TMZ-resistant cell lines to elucidate the role of ADAM17. Furthermore, we evaluated the impact of ADAM17 knockdown on TMZ sensitivity in vitro and in vivo. Moreover, we predicted microRNAs upstream of ADAM17 and transfected miRNA mimics into cells to verify their effects on TMZ sensitivity. Additionally, the clinical significance of ADAM17 and miRNAs in GBM was analyzed. ADAM17 was upregulated in GBM cells under serum starvation and TMZ treatment and was overexpressed in TMZ-resistant cells. In in vitro and in vivo models, ADAM17 knockdown conferred greater TMZ sensitivity. miR-145 overexpression suppressed ADAM17 and sensitized cells to TMZ. ADAM17 upregulation and miR-145 downregulation in clinical specimens are associated with disease progression and poor prognosis. Thus, miR-145 enhances TMZ sensitivity by inhibiting ADAM17. These findings offer insights into the development of therapeutic approaches to overcome TMZ resistance.

Klebsiella pneumoniae is an important human pathogen causing hospital-acquired and community-acquired infections. Systemic K. pneumoniae infections may be preceded by gastrointestinal colonization, but the basis of this bacterium’s interaction with the intestinal epithelium remains unclear. Here, we report that the K. pneumoniae Sap (sensitivity to antimicrobial peptides) transporter contributes to bacterial–host cell interactions and in vivo virulence. Gene deletion showed that sapA is required for the adherence of a K. pneumoniae blood isolate to intestinal epithelial, lung epithelial, urinary bladder epithelial, and liver cells. The ΔsapA mutant was deficient for translocation across intestinal epithelial monolayers, macrophage interactions, and induction of proinflammatory cytokines. In a mouse gastrointestinal infection model, ΔsapA yielded significantly decreased bacterial loads in liver, spleen and intestine, reduced liver abscess generation, and decreased mortality. These findings offer new insights into the pathogenic interaction of K. pneumoniae with the host gastrointestinal tract to cause systemic infection.

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor often treated with Temozolomide (TMZ). Research reveals that secretory substances and receptor-activated signaling may contribute to TMZ resistance in GBM cells. RNA-Seq and bioinformatics analyses reveal that TMZ treatment downregulates most genes, particularly those involved in cell structure and metabolism, while activating genes linked to secretory substances like cytokines, chemokines, and growth factors. Antibody array analysis identified a significant increase in TGF-α secretion after TMZ treatment, which also triggered its associated pathways. Moreover, the remarkable secretion of TGF-α also triggered the activation of its associated pathways. Notably, a marked increase in TGF-α expression was observed in TMZ-resistant cells. TGF-α knockdown restored TMZ sensitivity in a mouse xenograft model. Tissue analysis revealed significantly higher TGF-α levels in GBM, suggesting its potential as a drug resistance biomarker and target for new therapies.

Background Osteosarcoma is the most common primary malignant bone tumor in children and adolescents and has also been associated with a high degree of malignancy and enhanced metastatic capacity. Curcumin (CUR) is well known for its anti-osteosarcoma activity. However, both demethoxycurcumin (DMC), and bisdemethoxycurcumin (BDMC) are natural curcumin analogues/congeners from turmeric whose role in osteosarcoma development remains unknown. Methods To evaluate the growth inhibitory effects of CUR, DMC and BDMC on osteosarcoma (HOS and U2OS), breast (MDA-MB-231), and melanoma (A2058) cancer cells, we employed the MTT assay, annexin V-FITC /7-AAD staining, and clonogenic assay. Results CUR,DMC, and BDMC all decreased the viability of HOS, U2OS, MDA-MB-231, and A2058 cancer cells. Additionally, CUR,DMC, and BDMC induced the apoptosis of HOS cells through activation of Smad 2/3 or repression of Akt signaling pathway. Furthermore, the combination of CUR,DMC, and BDMC synergistically reduced cell viability, colony formation and increased apoptosis than either two or a single agent in HOS cells. Conclusions The combination of these three compounds could be used as a novel target for the treatment of osteosarcoma.

Nonalcoholic fatty liver disease (NAFLD) is common worldwide and closely associated with metabolic dysfunction. NAFLD leads to a higher risk of development of severe liver diseases, such as nonalcoholic steatohepatitis (NASH), liver cirrhosis, and hepatocellular carcinoma (HCC). To date, no pharmacotherapy targeting NAFLD has received general approval. Adlay is a plant that has been used as traditional herbal medicine in Asia and is a promising candidate to solve this global issue. We have established a mouse model of NAFLD by feeding a high-fat diet (HFD) for 10 weeks. Here, ethanolic or water extracts of adlay seed (ASE and ASW, respectively), mixed with HFD, were fed to the mice for 10 weeks. The ASE and ASW treatment ameliorated hyperglycemia and improved the glucose tolerance and insulin resistance in the HFD mice. Hyperlipidemia in HFD mice was prevented by the ASE and ASW diet. In addition, the ASE and ASW supplementation attenuated hepatic steatosis and inflammation, improved liver function, and caused no harm to the kidneys. Moreover, the mechanism of the effect of ASE and ASW on inhibiting hepatic lipogenesis and inducing fatty acid β-oxidation was certified by the simulated human fatty liver cell model. Our study showed the regulatory potential of the extracts of adlay seeds for alleviating NAFLD, as well as related liver and metabolic diseases.

Resveratrol has well-known anticancer properties; however, its oligomers, including α-viniferin, ε-viniferin, and kobophenol A, have not yet been well investigated. This is the first study examining the anti-epithelial-mesenchymal transition (EMT) effects of α-viniferin and ε-viniferin on A549, NCI-H460, NCI-H520, MCF-7, HOS, and U2OS cells. The results showed that α-viniferin and ε-viniferin significantly inhibited EMT, invasion and migration in TGF-β1- or IL-1β-induced non-small cell lung cancer. α-Viniferin and ε-viniferin also reversed TGF-β1-induced reactive oxygen species (ROS), MMP2, vimentin, Zeb1, Snail, p-SMAD2, p-SMAD3, and ABCG2 expression in A549 cells. Furthermore, ε-viniferin was found to significantly inhibit lung metastasis in A549 cell xenograft metastatic mouse models. In view of these findings, α-viniferin and ε-viniferin may play an important role in the prevention of EMT and cancer metastasis in lung cancer.

In the era of deepfakes and AI-generated content, digital image manipulation poses significant challenges to image authenticity, creating doubts about the credibility of images. Traditional image forensics techniques often struggle to detect sophisticated tampering, and passive detection approaches are reactive, verifying authenticity only after counterfeiting occurs. In this paper, we propose a novel full-resolution secure learned image codec (SLIC) designed to proactively prevent image manipulation by creating self-destructive artifacts upon re-compression. Once a sensitive image is encoded using SLIC, any subsequent re-compression or editing attempts will result in visually severe distortions, making the image’s tampering immediately evident. Because the content of an SLIC image is either original or visually damaged after tampering, images encoded with this secure codec hold greater credibility. SLIC leverages adversarial training to fine-tune a learned image codec that introduces out-of-distribution perturbations, ensuring that the first compressed image retains high quality while subsequent re-compressions degrade drastically. We analyze and compare the adversarial effects of various perceptual quality metrics combined with different learned codecs. Our experiments demonstrate that SLIC holds significant promise as a proactive defense strategy against image manipulation, offering a new approach to enhancing image credibility and authenticity in a media landscape increasingly dominated by AI-driven forgeries.

α-Viniferin, a natural stilbene compound found in plants and a polymer of resveratrol, had demonstrated potential anti-cancer and anti-inflammatory effects. However, the specific mechanisms underlying its anti-cancer activity were not yet fully understood and required further investigation. This study evaluated the effectiveness of α-viniferin and ε-viniferin using MTT assay. Results showed that α-viniferin was more effective than ε-viniferin in reducing the viability of NCI-H460 cells, a type of non-small cell lung cancer. Annexin V/7AAD assay results provided further evidence that the decrease in cell viability observed in response to α-viniferin treatment was due to the induction of apoptosis in NCI-H460 cells. The present findings indicated that treatment with α-viniferin could stimulate apoptosis in cells by cleaving caspase 3 and PARP. Moreover, the treatment reduced the expression of SIRT1, vimentin, and phosphorylated AKT, and also induced AIF nuclear translocation. Furthermore, this research provided additional evidence for the effectiveness of α-viniferin as an anti-tumor agent in nude mice with NCI-H460 cell xenografts. As demonstrated by the TUNEL assay results, α-viniferin promoted apoptosis in NCI-H460 cells in nude mice.

Background Serum albumin level is a crucial nutritional indicator for patients on dialysis. Approximately one-third of patients on hemodialysis (HD) have protein malnutrition. Therefore, the serum albumin level of patients on HD is strongly correlated with mortality. Methods In study, the data sets were obtained from the longitudinal electronic health records of the largest HD center in Taiwan from July 2011 to December 2015, included 1,567 new patients on HD who met the inclusion criteria. Multivariate logistic regression was performed to evaluate the association of clinical factors with low serum albumin, and the grasshopper optimization algorithm (GOA) was used for feature selection. The quantile g-computation method was used to calculate the weight ratio of each factor. Machine learning and deep learning (DL) methods were used to predict the low serum albumin. The area under the curve (AUC) and accuracy were calculated to determine the model performance. Results Age, gender, hypertension, hemoglobin, iron, ferritin, sodium, potassium, calcium, creatinine, alkaline phosphatase, and triglyceride levels were significantly associated with low serum albumin. The AUC and accuracy of the GOA quantile g-computation weight model combined with the Bi-LSTM method were 98% and 95%, respectively. Conclusion The GOA method was able to rapidly identify the optimal combination of factors associated with serum albumin in patients on HD, and the quantile g-computation with DL methods could determine the most effective GOA quantile g-computation weight prediction model. The serum albumin status of patients on HD can be predicted by the proposed model and accordingly provide patients with better a prognostic care and treatment.