Role of reactive oxygen species in myelodysplastic syndromes.

Reactive oxygen species (ROS) serve as typical metabolic byproducts of aerobic life and play a pivotal role in redox reactions and signal transduction pathways. Contingent upon their concentration, ROS production not only initiates or stimulates tumorigenesis but also causes oxidative stress (OS) and triggers cellular apoptosis. Mounting literature supports the view that ROS are closely interwoven with the pathogenesis of a cluster of diseases, particularly those involving cell proliferation and differentiation, such as myelodysplastic syndromes (MDS) and chronic/acute myeloid leukemia (CML/AML). OS caused by excessive ROS at physiological levels is likely to affect the functions of hematopoietic stem cells, such as cell growth and self-renewal, which may contribute to defective hematopoiesis. We review herein the eminent role of ROS in the hematological niche and their profound influence on the progress of MDS. We also highlight that targeting ROS is a practical and reliable tactic for MDS therapy.

Microbial Dysbiosis Linked to Metabolic Dysfunction-Associated Fatty Liver Disease in Asians: Prevotella copri Promotes Lipopolysaccharide Biosynthesis and Network Instability in the Prevotella Enterotype.

Metabolic dysfunction-associated fatty liver disease (MAFLD), formerly known as non-alcoholic fatty liver disease (NAFLD), is characterized by hepatic fat accumulation by metabolic dysfunction. The rising prevalence of MAFLD, especially among Asians, may be associated with changes in gut microbiota. We investigated gut microbiota characteristics and potential mechanisms leading to MAFLD development according to enterotypes. Case-control studies examining the gut microbiota composition between MAFLD and non-MAFLD participants were searched in public databases until July 2023. Gut microbiota was categorized into two enterotypes by principal component analysis. According to the enterotypes, LEfSe, ALDEx2, XGBoost, and DCiPatho were utilized to identify differential abundances and pathogenic microbes in the gut between the MAFLD and non-MAFLD groups. We analyzed microbial community networks with the SprCC module and predicted microbial functions. In the Prevotella enterotype (ET-P), 98.6% of Asians and 65.1% of Caucasians were associated with MAFLD (p = 0.049). MAFLD incidence was correlated with enterotype, age, obesity, and ethnicity (p < 0.05). Asian MAFLD patients exhibited decreased Firmicutes and Akkermansia muciniphila and increased Bacteroidetes and P. copri. The pathogenicity scores were 0.006 for A. muciniphila and 0.868 for P. copri. The Asian MAFLD group showed decreased stability and complexity in the gut microbiota network. Metagenome function analysis revealed higher fructose metabolism and lipopolysaccharide (LPS) biosynthesis and lower animal proteins and α-linolenic acid metabolism in Asians with MAFLD compared with the non-MAFLD group. LPS biosynthesis was positively correlated with P. copri (p < 0.05). In conclusion, P. copri emerged as a potential microbial biomarker for MAFLD. These findings enhance our understanding of the pathological mechanisms of MAFLD mediated through the gut microbiota, providing insights for future interventions.

Advances in Nanoplatforms for Immunotherapy Applications Targeting the Tumor Microenvironment.

Cancer immunotherapy is a treatment method that activates or enhances the autoimmune response of the body to fight tumor growth and metastasis, has fewer toxic side effects and a longer-lasting efficacy than radiotherapy and chemotherapy, and has become an important means for the clinical treatment of cancer. However, clinical results from immunotherapy have shown that most patients lack responsiveness to immunotherapy and cannot benefit from this treatment strategy. The tumor microenvironment (TME) plays a critical role in the response to immunotherapy. The TME typically prevents effective lymphocyte activation, reducing their infiltration, and inhibiting the infiltration of effector T cells. According to the characteristic differences between the TME and normal tissues, various nanoplatforms with TME targeting and regulation properties have been developed for more precise regulation of the TME and have the ability to codeliver a variety of active pharmaceutical ingredients, thereby reducing systemic toxicity and improving the therapeutic effect of antitumor. In addition, the precise structural design of the nanoplatform can integrate specific functional motifs, such as surface-targeted ligands, degradable backbones, and TME stimulus-responsive components, into nanomedicines, thereby reshaping the tumor microenvironment, improving the body's immunosuppressive state, and enhancing the permeability of drugs in tumor tissues, in order to achieve controlled and stimulus-triggered release of load cargo. In this review, the physiological characteristics of the TME and the latest research regarding the application of TME-regulated nanoplatforms in improving antitumor immunotherapy will be described. Furthermore, the existing problems and further applications perspectives of TME-regulated platforms for cancer immunotherapy will also be discussed.

Glucose Fluctuation Inhibits Nrf2 Signaling Pathway in Hippocampal Tissues and Exacerbates Cognitive Impairment in Streptozotocin-Induced Diabetic Rats.

Background: This research investigated whether glucose fluctuation (GF) can exacerbate cognitive impairment in streptozotocin-induced diabetic rats and explored the related mechanism. Methods: After 4 weeks of feeding with diets containing high fats plus sugar, the rat model of diabetes mellitus (DM) was established by intraperitoneal injection of streptozotocin (STZ). Then, GF was triggered by means of alternating satiety and starvation for 24 h. The weight, blood glucose level, and water intake of the rats were recorded. The Morris water maze (MWM) test was carried out to appraise the cognitive function at the end of week 12. Moreover, the morphological structure of hippocampal neurons was viewed through HE and Nissl staining, and transmission electron microscopy (TEM) was performed for ultrastructure observation. The protein expression levels of Nrf2, HO-1, NQO-1, Bax, Bcl-2, and Caspase-3 in the hippocampal tissues of rats were measured via Western blotting, and the mRNA expressions of Nrf2, HO-1, and NQO-1 were examined using qRT-PCR. Finally, Western blotting and immunohistochemistry were conducted to detect BDNF levels. Results: It was manifested that GF not only aggravated the impairment of spatial memory in rats with STZ-induced type 2 DM but also stimulated the loss, shrinkage, and apoptosis of hippocampal neurons. Regarding the expressions in murine hippocampal tissues, GF depressed Nrf2, HO-1, NQO-1, Bcl-2, and BDNF but boosted Caspase-3 and Bax. Conclusions: GF aggravates cognitive impairment by inhibiting the Nrf2 signaling pathway and inducing oxidative stress and apoptosis in the hippocampal tissues.

Definition of follicular helper T cell and cytokines expression in synovial fluid of rheumatoid arthritis.

OBJECTIVE: This study aimed to assess the role of synovial fluid (SF) CD4+T, CD19+B, follicular helper cells (Tfh), and cytokines in the pathogenesis of rheumatoid arthritis (RA). METHODS: This study enrolled 16 patients with RA and 8 patients with osteoarthritis (OA). The frequencies of the SF CD4+ T, CD19+ B, Tfh cells, and Tfh subsets were assessed using flow cytometry. The medical condition in patients with RA was evaluated using The Disease Activity Score 28 (DAS28), the Clinical Disease Activity Index (CDAI), and the Simplified Disease Activity Index (SDAI). Levels of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), anti-cyclic citrullinated peptide (anti-CCP), and rheumatoid factor (RF) were measured. The cytokines IL-4, IL-13, IL-21, and BLyS were measured by ELISA test. RESULTS: The percentages of SF CD4+T, CD19+B, and PD-1+CXCR5+ Tfh in RA patients were higher than those in OA patients. And the Tfh2 was the main subset among Tfh subsets. In addition, levels of IL-21 and BLyS were higher in patients with RA compared to patients with OA. Furthermore, the treatment of TNF-α inhibitors may be associated with decreased levels of SF Tfh. CONCLUSIONS: Elevated SF Tfh, B cell, and cytokines expression profiles were observed in RA patients. Tfh2 was the major subset of the Tfh, and IL-21 and BLyS were significantly enhanced. Additionally, TNF-α inhibitors reduced Tfh in SF. Therefore, Tfh, B, and Tfh2 cells could play a significant role in the progression of RA. Key Points •Tfh cells in the synovial fluid are significantly higher in RA patients and are dominated by the Tfh2 subpopulation. •Synovial fluid Tfh cells decrease in RA patients after anti-TNF-α treatment.

Towards disentangling the classification of freshwater fish trypanosomes.

Currently, new species of freshwater fish trypanosomes, which are economically important parasites, are being described based on subjectively selected features, i.e., their cell morphology and the host species. We have performed detailed phylogenetic and haplotype diversity analyses of all 18S rRNA genes available for freshwater fish trypanosomes, including the newly obtained sequences of Trypanosoma carassii and Trypanosoma danilewskyi. Based on a sequence similarity of 99.5%, we divide these trypanosomes into 15 operational taxonomic units, and propose three nominal scenarios for distinguishing T. carassii and other aquatic trypanosomes. We find evidences for the existence of a low number of freshwater fish trypanosomes, with T. carassii having the widest geographic and host ranges. Our analyses support the existence of an umbrella complex composed of T. carassii and two sister species. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-023-00191-0.

Study of Changes in the Ulan Buh Desert under the Dual Impacts of Desert Farmland Development and Climate Change.

Desert farmland provides food for desert areas, but water is the main limiting factor of this region, thus desert farmland has an extremely fragile ecological environment. This study investigated the temporal and spatial variations of vegetation NDVI (Normalized Difference Vegetation Index) in the Ulan Buh Desert, China, from 1990 to 2022, using long-term Landsat satellite data obtained from the Google Earth Engine platform and local statistical data. The results showed that from 1990 to 2022, the NDVI exhibited relatively small fluctuations and a steady increase. Furthermore, the study analyzed the impact of climate factors, namely precipitation and temperature, on NDVI, and collected the groundwater lever changes under irrigation and farmland development. The results demonstrated a positive correlation between NDVI and both precipitation and temperature from 1990 to 2006. The study area experienced an overall trend of increasing humidity. Specifically, from 1990 to 2006, significant positive correlations with precipitation and temperature were observed in 4.4% and 5.5% of the region, respectively. From 2007 to 2022, significant positive correlations were observed in 5.4% and 72.8% of the region for precipitation and temperature, respectively. These findings suggest that temperature has become increasingly influential on vegetation NDVI, while the impact of precipitation remains relatively stable. Moreover, the study assessed the impact of human activities on vegetation NDVI. The results revealed that from 1990 to 2006, human activities contributed to 43.1% of the promotion of local vegetation NDVI, which increased to 90.9% from 2007 to 2022. This study provides valuable insights into the dynamics of vegetation in the Ulan Buh Desert and its response to climatic changes and human activities. The findings highlight the significance of climate conditions and human interventions in shaping the vegetation dynamics in the region, offering essential information for ecological restoration and conservation efforts.

Relationship between acute glucose variability and cognitive decline in type 2 diabetes: A systematic review and meta-analysis.

BACKGROUND: Cognitive decline is one of the most widespread chronic complications of diabetes, which occurs in more than half of the patients with type 2 diabetes (T2DM). Emerging evidences have suggested that glucose variability (GV) is associated with the pathogenesis of diabetic complications. However, the influence of acute GV on cognitive dysfunction in T2DM is still controversial. The aim of the study was to evaluate the association between acute GV and cognitive defect in T2DM, and provide a most recent and comprehensive summary of the evidences in this research field. METHODS: PubMed, Cochrane library, EMBASE, Web of science, Sinomed, China National Knowledge Infrastructure (CNKI), and Wanfang were searched for articles that reported on the association between acute GV and cognitive impairment in T2DM. RESULTS: 9 eligible studies were included, with a total of 1263 patients with T2DM involved. Results showed that summary Fisher's z value was -0.23 [95%CI (-0.39, -0.06)], suggesting statistical significance (P = 0.006). Summary r value was -0.22 [95%CI (-0.37, -0.06)]. A lower cognitive performance was found in the subjects with greater glucose variation, which has statistical significance. Mean amplitude of glycemic excursions (MAGE) was associated with a higher risk of poor functional outcomes. Fisher's z value was -0.35 [95%CI (-0.43, -0.25)], indicating statistical significance (P = 0.011). Sensitivity analyses by omitting individual studies showed stability of the results. CONCLUSIONS: Overall, higher acute GV is associated with an increased risk of cognitive impairment in patients with T2DM. Further studies should be required to determine whether targeted intervention of reducing acute GV could prevent cognitive decline.

Enantioselective Alkynylation of Pyrazole-4,5-diones with Terminal Alkynes Catalyzed by Copper/PyBisulidine.

A copper/PyBisulidine-catalyzed enantioselective alkynylation of electrophilic pyrazole-4,5-dione with terminal alkynes has been developed. Chiral tertiary propargylic alcohols bearing the pyrazolone motif were prepared with yields (up to 99%) and enantioselectivities (up to 99% ee). The prominent feature of this protocol includes its mild reaction conditions and good stereoselectivities. The nonlinear effect study showed that the catalytically active specie was a monomeric catalyst and that the excess copper activated the alkynes through the π-system.

The potential of targeting cuproptosis in the treatment of kidney renal clear cell carcinoma.

Renal cell carcinoma (RCC) is one of the top ten malignancies and tumor-related causes of death worldwide. The most common histologic subtype is kidney renal clear cell carcinoma (KIRC), accounting for approximately 75% of all RCC cases. Early resection is considered the basic treatment for patients with KIRC. However, approximately 30% of these patients experience recurrence post-operation. Cuproptosis, an autonomous mechanism for controlling cell death, encompasses various molecular mechanisms and multiple cellular metabolic pathways. These pathways mainly include copper metabolic signaling pathways, mitochondrial metabolism signaling pathways, and lipoic acid pathway signaling pathways. Recent evidence shows that cuproptosis is identified as a key cell death modality that plays a meaningful role in tumor progression. However, there is no published systematic review that summarizes the correlation between cuproptosis and KIRC, despite the fact that investigations on cuproptosis and the pathogenesis of KIRC have increased in past years. Researchers have discovered that exogenous copper infusion accelerates the dysfunction of mitochondrial dysfunction and suppresses KIRC cells by inducing cuproptosis. The levels of tricarboxylic acid cycle proteins, lipoic acid protein, copper, and ferredoxin 1 (FDX1) were dysregulated in KIRC cells, and the prognosis of patients with high FDX1 expression is better than that of patients with low expression. Cuproptosis played an indispensable role in the regulation of tumor microenvironment features, tumor progression, and long-term prognosis of KIRC. In this review, we summarized the systemic and cellular metabolic processes of copper and the copper-related signaling pathways, highlighting the potential targets related to cuproptosis for KIRC treatment.

The role and mechanism of myeloperoxidase in dermatomyositis.

OBJECTIVE: Dermatomyositis (DM) is the best known subtype of idiopathic inflammatory myopathies. The hallmarks of DM muscle pathology including microangiopathy, inflammatory infiltration, and perifascicular atrophy. Recent findings have revealed pathogenetic effects of myeloperoxidase (MPO) by causing oxidative damage and regulating abnormal immunity in multiple disease conditions. In this study, we aimed to explore the role of MPO in the pathogenesis of DM. METHODS: The peripheral blood mononuclear cell (PBMC) mRNA expression and DNA methylation of MPO were verified using real-time qPCR and bisulfite pyrosequencing, respectively. Plasma MPO levels were measured with enzyme-linked immunosorbent assay, and their relationships with clinical characteristics were analyzed. The expression and distribution of MPO in muscle were tested by immunofluorescence. Purified human native MPO protein was used to stimulate human dermal microvascular endothelial cells (HDMECs) and skeletal muscle myotubes. The cell viability, tube forming capacity, permeability, adhesion molecule expressions in HDMECs, and atrophy and programmed cell death pathways in myotubes were then observed. RESULTS: MPO gene methylation was decreased, while mRNA expression and plasma levels were increased in DM. Plasma MPO of DM patients was positively correlated with serum creatine kinase (CK). MPO mainly distributed around endomysia capillaries and perifascicular atrophy in DM muscle biopsies, and was co-localized with CD4+, CD8+ T cells and CD19+ B cells. MPO not only could influence the cell viability, tube forming capacity, permeability and expression of adhesion molecules (including ICAM 1, VCAM 1 and E-selectin) of HDMECs, but also could cause atrophy of myotubes. CONCLUSIONS: Our study disclosed, for the first time, that MPO plays an important role in promoting inflammatory infiltration and inducing muscle damage in DM patients. MPO may be a potential biomarker for DM muscle involvement and MPO targeted drugs may be promising in DM treatment.

High-Precision Tomato Disease Detection Using NanoSegmenter Based on Transformer and Lightweighting.

With the rapid development of artificial intelligence and deep learning technologies, their applications in the field of agriculture, particularly in plant disease detection, have become increasingly extensive. This study focuses on the high-precision detection of tomato diseases, which is of paramount importance for agricultural economic benefits and food safety. To achieve this aim, a tomato disease image dataset was first constructed, and a NanoSegmenter model based on the Transformer structure was proposed. Additionally, lightweight technologies, such as the inverted bottleneck technique, quantization, and sparse attention mechanism, were introduced to optimize the model's performance and computational efficiency. The experimental results demonstrated excellent performance of the model in tomato disease detection tasks, achieving a precision of 0.98, a recall of 0.97, and an mIoU of 0.95, while the computational efficiency reached an inference speed of 37 FPS. In summary, this study provides an effective solution for high-precision detection of tomato diseases and offers insights and references for future research.

High diastereo- and enantioselective Michael addition of 3-acetoxy-2-oxindoles with nitroalkenes catalyzed by nickel/PyBisulidine.

A Ni/PyBisulidine catalyzed asymmetric Michael addition of 3-acyloxy-2-oxindoles to nitroalkenes has been developed. Various quaternary substituted 3-acyloxy-2-oxindoles were obtained with excellent yields and diastereo- and enantioselectivities in a low-toxic green solvent, ethyl acetate, with a low catalyst loading (1 mol%). The reaction process is air and moisture tolerant. The substrate scope was also extended to α,ß-disubstituted nitroalkenes and 3-hydroxy-2-oxindoles, and good results were obtained.

Emerging roles of ferroptosis-related miRNAs in tumor metastasis.

Ferroptosis, a novel mode of cell death dependent on iron and reactive oxygen species, has been extensively explored during malignant tumors metastasis. Ferroptosis can interact with multiple components of the tumor microenvironment to regulate metastasis. These interactions generally include the following aspects: (1) Epithelial-mesenchymal transformation, which can help cancer cells increase their sensitivity to ferroptosis while they have multiple mechanisms to fight against it; (2) Disorder of iron metabolism in cancer stem cells which maintains their stem characteristics; (3) Polarization of M0 macrophages to M2. (4) The paradoxical effects of iron metabolism and CD8 + T cells induced by ferroptosis (5) Regulation of angiogenesis. In addition, ferroptosis can be regulated by miRNAs through the reprogramming of various intracellular metabolism processes, including the regulation of the glutathione- glutathione peroxidase 4 pathway, glutamic acid/cystine transport, iron metabolism, lipid metabolism, and oxidative stress. Therefore, there are many potential interactions between ferroptosis-related miRNAs and tumor metastasis, including interaction with cancer cells and immune cells, regulating cytokines, and angiogenesis. This review focuses on the role of ferroptosis-related miRNA in tumor metastasis, aiming to help readers understand their relationship and provide a new perspective on the potential treatment strategies of malignant tumors.

A High-Precision Plant Disease Detection Method Based on a Dynamic Pruning Gate Friendly to Low-Computing Platforms.

Timely and accurate detection of plant diseases is a crucial research topic. A dynamic-pruning-based method for automatic detection of plant diseases in low-computing situations is proposed. The main contributions of this research work include the following: (1) the collection of datasets for four crops with a total of 12 diseases over a three-year history; (2) the proposition of a re-parameterization method to improve the boosting accuracy of convolutional neural networks; (3) the introduction of a dynamic pruning gate to dynamically control the network structure, enabling operation on hardware platforms with widely varying computational power; (4) the implementation of the theoretical model based on this paper and the development of the associated application. Experimental results demonstrate that the model can run on various computing platforms, including high-performance GPU platforms and low-power mobile terminal platforms, with an inference speed of 58 FPS, outperforming other mainstream models. In terms of model accuracy, subclasses with a low detection accuracy are enhanced through data augmentation and validated by ablation experiments. The model ultimately achieves an accuracy of 0.94.

Generalization Analysis of Pairwise Learning for Ranking With Deep Neural Networks.

Pairwise learning is widely employed in ranking, similarity and metric learning, area under the ROC curve (AUC) maximization, and many other learning tasks involving sample pairs. Pairwise learning with deep neural networks was considered for ranking, but enough theoretical understanding about this topic is lacking. In this letter, we apply symmetric deep neural networks to pairwise learning for ranking with a hinge loss ϕh and carry out generalization analysis for this algorithm. A key step in our analysis is to characterize a function that minimizes the risk. This motivates us to first find the minimizer of ϕh-risk and then design our two-part deep neural networks with shared weights, which induces the antisymmetric property of the networks. We present convergence rates of the approximation error in terms of function smoothness and a noise condition and give an excess generalization error bound by means of properties of the hypothesis space generated by deep neural networks. Our analysis is based on tools from U-statistics and approximation theory.

The efficacy and safety of Chinese herbal medicine in the treatment of painful diabetic neuropathy: A systematic review and meta-analysis.

Objective: The objective of this systematic review and meta-analysis is to assess the effectiveness and security of Chinese herbal medicine (CHM) in the therapy of painful diabetic neuropathy (PDN). Methods: We searched databases for randomized controlled trials (RCTs) of CHM in the treatment of PDN. Outcome indicators included nerve conduction velocity, clinical efficiency, pain score, TCM syndrome score, and adverse events. Stata 16.0 was used to carry out the Meta-analysis. Results: A total of 21 RCTs with 1,737 participants were included. This meta-analysis found that using CHM as adjuvant treatment or as monotherapy for PDN can improve SCV of median nerve [mean difference (MD) = 3.56, 95% Confidence interval (CI) (2.19, 4.92) ], MCV of median nerve [ MD = 3.82, 95% CI (2.51, 5.12) ], SCV of common peroneal nerve [ MD = 4.16, 95% CI (1.62, 6.70) ], MCV of common peroneal nerve [ MD = 4.37, 95% CI (1.82, 6.93) ], SCV of gastrocnemius nerve [ MD = 4.95, 95% CI (3.52, 6.37) ], SCV of tibial nerve [ MD = 3.17, 95% CI (-2.64, 8.99) ], MCV of tibial nerve [MD = 6.30, 95%CI (5.00, 7.60)] and clinical effective rate [ odds ratio (OR) = 4.00, 95% CI (2.89, 5.52) ] and reduce pain score [standardized mean difference (SMD) = -2.23, 95% CI (-3.04, -1.41) ], TCM syndrome score [ MD = -4.70, 95% CI (-6.61, -2.80) ]. In addition, compared to the control group, adverse events of Chinese medicine intervention occurred less. Conclusion: CHM as adjuvant therapy or single treatment has a good curative effect and is safe for patients with PDN, which is worthy of clinical promotion and use, however; higher quality clinical studies are still needed to prove. Systematic Review Registration: https://www.crd.york.ac.uk/, identifier CRD42022327967.

A High Performance Wheat Disease Detection Based on Position Information.

Protecting wheat yield is a top priority in agricultural production, and one of the important measures to preserve yield is the control of wheat diseases. With the maturity of computer vision technology, more possibilities have been provided to achieve plant disease detection. In this study, we propose the position attention block, which can effectively extract the position information from the feature map and construct the attention map to improve the feature extraction ability of the model for the region of interest. For training, we use transfer learning to improve the training speed of the model. In the experiment, ResNet built on positional attention blocks achieves 96.4% accuracy, which is much higher compared to other comparable models. Afterward, we optimized the undesirable detection class and validated its generalization performance on an open-source dataset.

Interaction of environmental factors with the polygenic risk scores of thinness-related genes in preventing obesity risk in middle-aged adults: The KoGES.

BACKGROUND: Some persons are genetically resistant to obesity, but only a few studies have evaluated thinness genes for preventing obesity. We aimed to investigate the association of polygenic variants with being underweight and their interaction with the lifestyles of middle-aged and elderly persons and identify potential new genetic approaches for managing body weight. METHODS: In total, 58,701 participants aged 40-77 years were recruited from urban hospitals in Korea. Underweight (case) was defined as body mass index (BMI) < 18.5 kg m2 (n = 991) and normal weight (control, n = 21,921) was defined as 18.5 ≤ BMI < 23 kg m2 . A genome-wide association study was run to identify thinness-related single nucleotide polymorphisms (SNPs) after adjustment for compound factors using Gplink. The generalised multifactor dimensionality reduction program was used to identify the genetic variants with SNP-SNP interactions. The polygenic risk score (PRS) was calculated by summing up the number of risk alleles in each SNP and classifying them into low-, medium- and high-PRS. RESULTS: The best model included the ANK2_rs7656666, CAST_rs28042, SLC1A3_rs928431867, CHST12_rs2906173, ALOX5_rs1051713, RGS6_rs17180754, ST8SIA5_rs79491311 and DCC_rs35721894 alleles. The participants with high-PRS had a lower BMI (p < 0.0001) than those with low-PRS and were 3.834 (2.58-5.70) times more likely to be underweight after multivariate adjustment (p < 0.001). The selected SNPs were correlated with each other and highly expressed in brain-related genes. The genes with minor alleles of CAST_rs28042 and CHST12_rs2906173 exhibited a higher expression frequency in brain-related tissues. PRS had significant interactions with protein, sodium, indigestible carbohydrates, calcium intake and exercise (p < 0.05), influencing the underweight state. People with a high-PRS were more underweight than those with low-PRS under high protein, sodium, high calcium, low indigestible carbohydrate intake and low exercise by 3.75, 3.88, 7.05, 3.18 and 3.80 times, respectively (p < 0.0001). CONCLUSIONS: In conclusion, adults having a high-PRS were significantly correlated with being underweight, especially in combination with a particular nutritional status. These results show the potential for thinness genes to be applied to personalised nutrition for preventing obesity through targeted gene therapy.

Autophagy-related prognostic signature characterizes tumor microenvironment and predicts response to ferroptosis in gastric cancer.

Background: Gastric cancer (GC) is an important disease and the fifth most common malignancy worldwide. Autophagy is an important process for the turnover of intracellular substances. Autophagy-related genes (ARGs) are crucial in cancer. Accumulating evidence indicates the clinicopathological significance of the tumor microenvironment (TME) in predicting prognosis and treatment efficacy. Methods: Clinical and gene expression data of GC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. A total of 22 genes with differences in expression and prognosis were screened from 232 ARGs. Three autophagy patterns were identified using an unsupervised clustering algorithm and scored using principal component analysis to predict the value of autophagy in the prognosis of GC patients. Finally, the relationship between autophagy and ferroptosis was validated in gastric cancer cells. Results: The expression of ARGs showed obvious heterogeneity in GC patients. Three autophagy patterns were identified and used to predict the overall survival of GC patients. These three patterns were well-matched with the immunophenotype. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses showed that the biological functions of the three autophagy patterns were different. A scoring system was then set up to quantify the autophagy model and further evaluate the response of the patients to the immunotherapy. Patients with high autophagy scores had a more severe tumor mutation burden and better prognosis. High autophagy scores were accompanied by high microsatellite instability. Patients with high autophagy scores had significantly higher PD-L1 expression and increased survival. The experimental results confirmed that the expression of ferroptosis genes was positively correlated with the expression of autophagy genes in different autophagy clusters, and inhibition of autophagy dramatically reversed the decrease in ferroptotic cell death and lipid accumulation. Conclusions: Autophagy patterns are involved in TME diversity and complexity. Autophagy score can be used as an independent prognostic biomarker in GC patients and to predict the effect of immunotherapy and ferroptosis-based therapy. This might benefit individualized treatment for GC.