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This paper utilizes the digital economy, regional spatial distribution digital mining technology, establishes the indicator system, assigns values to the indicators, and applies the indicator system to evaluate the development of industrial structure upgrading and transformation of the regional economy. According to the research results of the basic structure and algorithm of the self-organized neural network model, combined with the classification layer smoothing algorithm, the regional spatial clustering model is constructed. Using the constructed model, the regional economic spatial dynamic data is mined, and the path of industrial transformation and upgrading in the regional spatial area is dynamically studied. Furthermore, using the CA algorithm, the evolution law of land use structure in the region is predicted, and the development of the regional economy is inferred. At the same time, through the spatial autocorrelation regional prediction model, the relevant regional spatial expansion prediction method is proposed, the three research hypotheses of this paper are made, and the constructed model is utilized to innovate the exploration of industrial transformation and upgrading paths from the spatial dimension. Using empirical research methods, descriptive statistics, and mediating effect heterogeneity analysis are carried out to analyze the factors that influence regional economic variables in place A. The empirical analysis shows that the fluctuation range interval of industrial structure is between [0.811,10.2805], which brings a large positive impact on the regional economy.2017 national digital economic growth rate changed from -0.17446 to 0.17143 to realize a positive growth rate, and at the same time, there is a heterogeneity in the development of the east-west and central regions of A. The hypotheses presented in this paper are all valid.

Cancer: vitamin A derivative prevents salivary gland tumors spreading Treatment of salivary gland tumors with a metabolite of vitamin A could help prevent rare cancer from spreading to the lungs. A team led by Xiao-hong Chen and Lu Kong from Capital Medical University in Beijing, China, performed extensive molecular profiling on primary and metastatic tumor cells taken from two patients with advanced salivary gland cancer. Even though these patients’ cancers did not harbor either of two common mutations that are hallmarks of the disease, both of which drive tumor proliferation and spread, the cells did show signs of altered gene expression and faulty molecular signaling consistent with these same mutational profiles. The abnormal signaling could be overcome by treatment with retinoic acid, a derivative of vitamin A that, when given to mouse models of cancer, reduced the development of lung metastases.

Abstract Salivary adenoid cystic carcinoma (SACC) with a unique MYB‐NFIB fusion has been considered an “immune‐cold” tumor, but the mechanisms behind this remain unclear. In this study, we analyzed the immune status of 29 SACC patients and found that most lung metastases exhibited an immunoinflammatory state, in contrast to the primary SACC tissues. Single‐cell sequencing data showed that anergic T‐cell types were low in primary inflammatory tissues, while inflammatory metastatic lung tissues had elevated levels of anergic CD8+ natural killer T (NKT)‐like cells and low levels of memory T cells. Primary exclusive tissues had high levels of myeloid‐derived suppressor cells (MDSCs) and low levels of activated CD8+ NKT‐like cells. These data support the fact that metastatic SACC cells might induce a stronger immune response in the lung. Additionally, an in vivo experiment showed that a minimally invasive SACC cell line with higher expression of human leukocyte antigens ‐B and ‐C induced NKT cell activation in mice and effectively attenuated the incidence of lung metastases caused by a highly invasive SACC cell line. This suggests that NKT therapy may be active in treating SACC lung metastasis. Conclusively, this study sheds light on the immune microenvironment of SACC and highlights the potential of NKT‐based therapy.

Testing drugs for anti-aging effects has historically been conducted in mouse life-span studies, but are costly and time consuming, and more importantly, difficult to recapitulate in humans. In addition, life-span studies in mice are not well suited to testing drug combinations that target multiple factors involved in aging. Additional paradigms for testing therapeutics aimed at slowing aging are needed. A new paradigm, designated as the Geropathology Grading Platform (GGP), is based on a standardized set of guidelines developed to detect the presence or absence of low-impact histopathological lesions and to determine the level of severity of high-impact lesions in organs from aged mice. The GGP generates a numerical score for each age-related lesion in an organ, summed for total lesions, and averaged over multiple mice to obtain a composite lesion score (CLS). Preliminary studies show that the platform generates CLSs that increase with the age of mice in an organ-dependent manner. The CLSs are sensitive enough to detect changes elicited by interventions that extend mouse life span, and thus help validate the GGP as a novel tool to measure biological aging. While currently optimized for mice, the GGP could be adapted to any preclinical animal model.

In order to assess the characteristics of polybrominated diphenyl ether (PBDEs) in the atmosphere of urban Jinan, eastern China, gas phase and PM2.5 were hereby sampled in July 2020. The concentration and composition characteristics of 11 PBDEs were obtained. The Human exposure was evaluated by the daily exposure calculation method. During the observation period, the average concentration of ∑11PBDEs in PM2.5 and gas phase was 214.8±31.3 pg/m3, that of low-PBDEs was 119.1±2.1 pg/m3, and that of BDE209 was 95.8±15.4 pg/m3. Among the 10 low-PBDEs, the highest single content was BDE99, followed by BDE47, accounting for 43%. PCA showed the main sources of PBDEs in the atmosphere of urban Jinan were Penta-BDEs and Deca-BDEs. The daily respiratory exposure of children were higher than that of adults, and the potential risk should be taken seriously.

The roles of lamin A/C in adipocyte differentiation and skeletal muscle lipid metabolism are associated with familial partial lipodystrophy of Dunnigan (FPLD). We confirmed that LMNA knockdown (KD) in mouse adipose-derived mesenchymal stem cells (AD-MSCs) prevented adipocyte maturation. Importantly, in in vitro experiments, we discovered a significant increase in phosphorylated lamin A/C levels at serine 22 or 392 sites (pLamin A/C-S22/392) accompanying increased lipid synthesis in a liver cell line (7701 cells) and two hepatocellular carcinoma (HCC) cell lines (HepG2 and MHCC97-H cells). Moreover, HCC cells did not survive after LMNA knockout (KO) or even KD. Evidently, the functions of lamin A/C differ between the liver and adipose tissue. To date, the mechanism of hepatocyte lipid metabolism mediated by nuclear lamin A/C remains unclear. Our in-depth study aimed to identify the molecular connection between lamin A/C and pLamin A/C, hepatic lipid metabolism and liver cancer. Gain- and loss-of-function experiments were performed to investigate functional changes and the related molecular pathways in 7701 cells. Adenosine 5’ monophosphate-activated protein kinase α (AMPKα) was activated when abnormalities in functional lamin A/C were observed following lamin A/C depletion or farnesyltransferase inhibitor (FTI) treatment. Active AMPKα directly phosphorylated acetyl-CoA-carboxylase 1 (ACC1) and subsequently inhibited lipid synthesis but induced glycolysis in both HCC cells and normal cells. According to the mass spectrometry analysis, lamin A/C potentially regulated AMPKα activation through its chaperone proteins, ATPase or ADP/ATP transporter 2. Lonafarnib (an FTI) combined with low-glucose conditions significantly decreased the proliferation of the two HCC cell lines more efficiently than lonafarnib alone by inhibiting glycolysis or the maturation of prelamin A.

Inflammation of adipose tissue induces metabolic derangements associated with obesity. Thus, determining ways to control or inhibit inflammation in adipose tissue is of clinical interest. The present study tested the hypothesis that in mouse adipose tissue, endogenous prostaglandin E2 (PGE2) negatively regulates inflammation via activation of prostaglandin E receptor 4 (EP4). PGE2 (5–500nM) attenuated lipopolysaccharide-induced mRNA and protein expression of chemokines, including interferon-γ-inducible protein 10 and macrophage-inflammatory protein-1α in mouse adipose tissue. A selective EP4 antagonist (L161,982) reversed, and two structurally different selective EP4 agonists [CAY10580 and CAY10598] mimicked these actions of PGE2. Adipose tissue derived from EP4-deficient mice did not display this response. These findings establish the involvement of EP4 receptors in this anti-inflammatory response. Experiments performed on adipose tissue from high-fat-fed mice demonstrated EP4-dependent attenuation of chemokine production during diet-induced obesity. The anti-inflammatory actions of EP4 became more important on a high-fat diet, in that EP4 activation suppressed a greater variety of chemokines. Furthermore, adipose tissue and systemic inflammation was enhanced in high-fat-fed EP4-deficient mice compared with wild-type littermates, and in high-fat-fed untreated C57BL/6 mice compared with mice treated with EP4 agonist. These findings provide in vivo evidence that PGE2-EP4 signaling limits inflammation. In conclusion, PGE2, via activation of EP4 receptors, functions as an endogenous anti-inflammatory mediator in mouse adipose tissue, and targeting EP4 may mitigate adipose tissue inflammation.