Immune response regulation by transduced mesenchymal stem cells with decorin gene on bleomycin-induced lung injury, fibrosis, and inflammation.

BACKGROUND: Pulmonary fibrosis is a pathological hallmark of lung injury. It is an aggressive disease that replaces normal lung parenchyma by fibrotic tissue. The transforming growth factor-beta-mothers against decapentaplegic homolog 3 (TGF-ß1-Smad3) signaling pathway plays a key role in regulating lung fibrosis. Decorin (DCN), a small leucine-rich proteoglycan, has a modulatory effect on the immune system by reversibly binding with TGF-ß and reducing its bioavailability. Mesenchymal stem cell (MSC) therapy is a new strategy that has an immune-modulatory capacity. OBJECTIVE: The aim of this study was to introduce a new therapeutic approach to harness remodeling in injured lung. MATERIAL AND METHODS: Bone marrow MSCs were isolated and transduced by decorin gene. Lung injury was induced by bleomycin and mice were treated with MSCs, MSCs-decorin, and decorin. Then, oxidative stress biomarkers, remodeling biomarkers, bronchoalveolar lavage cells, and histopathology study were conducted. RESULTS: Reduced catalase and superoxide dismutase increased due to treatments. Elevated malondialdehyde, hydroxyproline, TGF-ß levels, and polymorphonuclear cells count decreased in the treated groups. Additionally, the histopathology of lung tissues showed controlled inflammation and fibrosis. CONCLUSION: Transfected decorin gene to MSCs and used cell therapy could control remodeling and bleomycin-induced lung injury.

The LOB domain protein, a novel transcription factor with multiple functions: A review.

The LATERAL ORGAN BOUNDARIES DOMAIN (LBD) protein, named for its LATERAL ORGAN BOUNDARIES (LOB) domain, is a member of a class of specific transcription factors commonly found in plants and is absent from all other groups of organisms. LBD TFs have been systematically identified in about 35 plant species and are involved in regulating various aspects of plant growth and development. However, research on the signaling network and regulatory functions of LBD TFs is insufficient, and only a few members have been studied. Moreover, a comprehensive review of these existing studies is lacking. In this review, the structure, regulatory mechanism and function of LBD TFs in recent years were reviewed in order to better understand the role of LBD TFs in plant growth and development, and to provide a new perspective for the follow-up study of LBD TFs.

Analysis of the roles of MAD proteins in the wing dimorphism of Nilaparvata lugens.

Wing dimorphism in Nilaparvata lugens is controlled by the insulin-like growth factor 1 (IGF-1) signaling - Forkhead transcription factors (IIS-FoxO) pathway. However, the role of this signal in the wing development program remains largely unclear. Here, we identified 2 R-SMAD proteins, NlMAD1 and NlMAD2, in the brown planthopper (BPH) transcriptome, derived from the intrinsic transforming growth factor-ß pathway of insect wing development. Both proteins share high sequence similarity and conserved domains. Phylogenetic analysis placed them in the R-SMAD group and revealed related insect orthologs. The expression of Nlmad1 was elevated in the late instar stages of the macropterous BPH strain. Nlmad1 knockdown in nymphs results in malformed wings and reduced wing size in adults, which affects the forewing membrane. By contrast, Nlmad2 expression was relatively consistent across BPH strains and different developmental stages. Nlmad2 knockdown had a milder effect on wing morphology and mainly affected forewing veins and cuticle thickness in the brachypterous strain. NlMAD1 functions downstream of the IIS-FoxO pathway by mediating the FoxO-regulated vestigial transcription and wing morph switching. Inhibiting Nlmad1 partially reversed the long-winged phenotype caused by NlFoxO knockdown. These findings indicate that NlMAD1 and NlMAD2 play distinct roles in regulating wing development and morph differentiation in BPH. Generally, NlMAD1 is a key mediator of the IIS-FoxO pathway in wing morph switching.

FDX1 as a novel biomarker and treatment target for stomach adenocarcinoma.

BACKGROUND: Stomach adenocarcinoma (STAD) is one of the main reasons for cancer-related deaths worldwide. This investigation aimed to define the connection between STAD and Cuproptosis-related genes (CRGs). Cuproptosis is a newly identified form of mitochondrial cell death triggered by copper. AIM: To explore the identification of potential biomarkers for STAD disease based on cuproptosis. METHODS: A predictive model using Gene Ontology (GO), Least Absolute Shrinkage and Selection Operator (LASSO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Variation Analysis (GSVA), and Gene Set Enrichment Analysis analyzed gene interconnections, focusing on 3 copper-related genes and their expression in The Cancer Genome Atlas-STAD. Networks for mRNA-miRNA and mRNA-transcription factor interactions were constructed. The prognostic significance of CRG scores was evaluated using time-receiver operating characteristic, Kaplan-Meier curves, and COX regression analysis. Validation was conducted with datasets GSE26942, GSE54129, and GSE66229. Expression of copper-related differentially expressed genes was also analyzed in various human tissues and gastric cancer subpopulations using the human protein atlas. RESULTS: Three significant genes (FDX1, LIAS, MTF1) were identified and selected via LASSO analysis to predict and classify individuals with STAD into high and low CRG score subgroups. These genes were down-regulated in both risk categories. GO and KEGG analyses highlighted their involvement mainly in the electron transport chain. After validating their differential expression, FDX1 emerged as the most accurate diagnostic marker for gastric cancer. Additionally, the RCircos package localized FDX1 on chromosome 11. CONCLUSION: Our study revealed that FDX1 could be a potential biomarker and treatment target for gastric malignancy, providing new ideas for further scientific research.

From CaBaM2F12 to K2BaM2F12 (M = Zr, Hf): Heterovalent Cation-Substitution-Induced Symmetry Break and Nonlinear-Optical Activity.

Designing short-wavelength nonlinear-optical (NLO) crystals is of vital importance for laser applications. Here, the combination of alkaline-earth metals, d0 transition metals, and F atom has generated two new and isostructural fluorides, CaBaZr2F12 (CBZF) and CaBaHf2F12 (CBHF), which adopt centrosymmetric space group I4/mmm. Taking CBZF and CBHF as the parents, two new fluorides, K2BaZr2F12 (KBZF) and K2BaHf2F12 (KBHF), with an Imm2 polar structure were obtained via a heterovalent cation substitution strategy. All four compounds feature ZrF8-dodecahedra-built {[Zr2F12]4-}∞ chains and show short ultraviolet cutoff edges (<200 nm). KBZF and KBHF show phase-matchable behavior with moderate second-harmonic-generation responses [0.6 and 0.35 × KH2PO4 (KDP)] under 1064 nm laser radiation. This work enriches fluorides as promising short-wavelength NLO materials.

Multi-omics insights into the function and evolution of sodium benzoate biodegradation pathway in Benzoatithermus flavus gen. nov., sp. nov. from hot spring.

Biodegradation stands as an eco-friendly and effective approach for organic contaminant remediation. However, research on microorganisms degrading sodium benzoate contaminants in extreme environments remains limited. In this study, we report to display the isolation of a novel hot spring enriched cultures with sodium benzoate (400 mg/L) as the sole carbon source. The results revealed that the phylum Pseudomonadota was the potential sodium benzoate degrader and a novel genus within the family Geminicoccaceae of this phylum. The isolated strain was named Benzoatithermus flavus SYSU G07066T and was isolated from HNT-2 hot spring samples. Genomic analysis revealed that SYSU G07066T carried benABC genes and physiological experiments indicated the ability to utilize sodium benzoate as a sole carbon source for growth, which was further confirmed by transcriptomic data with expression of benABC. Phylogenetic analysis suggested that Horizontal Gene Transfer (HGT) plays a significant role in acquiring sodium benzoate degradation capability among prokaryotes, and SYSU G07066T might have acquired benABC genes through HGT from the family Acetobacteraceae. The discovery of the first microorganism with sodium benzoate degradation function from a hot spring enhances our understanding of the diverse functions within the family Geminicoccaceae. This study unearths the first novel genus capable of efficiently degrading sodium benzoate and its evolution history at high temperatures, holding promising industrial applications, and provides a new perspective for further exploring the application potential of hot spring "microbial dark matter".

KBa3M2F14Cl (M = Zr, Hf): novel short-wavelength mixed metal halides with the largest second-harmonic generation responses contributed by mixed functional moieties.

The development of short-wavelength nonlinear optical (NLO) materials is indispensable and urgently required for further applications. Halides have been disregarded as potential NLO materials with deep-ultraviolet (DUV) cutoff edges due to their weak second-harmonic generation (SHG) response and poor birefringence. Here, two novel and isostructural halides, KBa3M2F14Cl (M = Zr (KBZFC), Hf (KBHFC)), possess structures that are formed by isolated MF7 monocapped triangular prisms and dissociative K+, Ba2+, and Cl- ions. Compared with reported metal halides that are transparent to the DUV region, KBZFC and KBHFC possess the strongest SHG responses (approximately 1, 0.9 × KH2PO4), which are contributed by the synergistic effect of MF7 (M = Zr, Hf) groups, Ba2+ cations, and Cl- ions. The zero-dimensional structures favour sufficient birefringences (0.12, 0.10 @ 1064 nm) for phase-matchable (PM) behaviours. The discovery of KBZFC and KBHFC showcases the potential of NLO mixed metal halides transparent to the DUV region.

Hallmarks of cancer resistance.

This review explores the hallmarks of cancer resistance, including drug efflux mediated by ATP-binding cassette (ABC) transporters, metabolic reprogramming characterized by the Warburg effect, and the dynamic interplay between cancer cells and mitochondria. The role of cancer stem cells (CSCs) in treatment resistance and the regulatory influence of non-coding RNAs, such as long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs), are studied. The chapter emphasizes future directions, encompassing advancements in immunotherapy, strategies to counter adaptive resistance, integration of artificial intelligence for predictive modeling, and the identification of biomarkers for personalized treatment. The comprehensive exploration of these hallmarks provides a foundation for innovative therapeutic approaches, aiming to navigate the complex landscape of cancer resistance and enhance patient outcomes.

Cellular Aging and Senescence in Cancer: A Holistic Review of Cellular Fate Determinants.

This comprehensive review navigates the complex relationship between cellular aging, senescence, and cancer, unraveling the determinants of cellular fate. Beginning with an overview of cellular aging's significance in cancer, the review explores processes, changes, and molecular pathways influencing senescence. The review explores senescence as a dual mechanism in cancer, acting as a suppressor and contributor, focusing on its impact on therapy response. This review highlights opportunities for cancer therapies that target cellular senescence. The review further examines the senescence-associated secretory phenotype and strategies to modulate cellular aging to influence tumor behavior. Additionally, the review highlights the mechanisms of senescence escape in aging and cancer cells, emphasizing their impact on cancer prognosis and resistance to therapy. The article addresses current advances, unexplored aspects, and future perspectives in understanding cellular aging and senescence in cancer.

Noninvasive prediction of lymph node metastasis in pancreatic cancer using an ultrasound-based clinicoradiomics machine learning model.

OBJECTIVES: This study was designed to explore and validate the value of different machine learning models based on ultrasound image-omics features in the preoperative diagnosis of lymph node metastasis in pancreatic cancer (PC). METHODS: This research involved 189 individuals diagnosed with PC confirmed by surgical pathology (training cohort: n = 151; test cohort: n = 38), including 50 cases of lymph node metastasis. Image-omics features were extracted from ultrasound images. After dimensionality reduction and screening, eight machine learning algorithms, including logistic regression (LR), support vector machine (SVM), K-nearest neighbors (KNN), random forest (RF), extra trees (ET), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and multilayer perceptron (MLP), were used to establish image-omics models to predict lymph node metastasis in PC. The best omics prediction model was selected through ROC curve analysis. Machine learning models were used to analyze clinical features and determine variables to establish a clinical model. A combined model was constructed by combining ultrasound image-omics and clinical features. Decision curve analysis (DCA) and a nomogram were used to evaluate the clinical application value of the model. RESULTS: A total of 1561 image-omics features were extracted from ultrasound images. 15 valuable image-omics features were determined by regularization, dimension reduction, and algorithm selection. In the image-omics model, the LR model showed higher prediction efficiency and robustness, with an area under the ROC curve (AUC) of 0.773 in the training set and an AUC of 0.850 in the test set. The clinical model constructed by the boundary of lesions in ultrasound images and the clinical feature CA199 (AUC = 0.875). The combined model had the best prediction performance, with an AUC of 0.872 in the training set and 0.918 in the test set. The combined model showed better clinical benefit according to DCA, and the nomogram score provided clinical prediction solutions. CONCLUSION: The combined model established with clinical features has good diagnostic ability and can be used to predict lymph node metastasis in patients with PC. It is expected to provide an effective noninvasive method for clinical decision-making, thereby improving the diagnosis and treatment of PC.

The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers.

BACKGROUND: This study investigated whether the Combat compensation method can remove the variability of radiomic features extracted from different scanners, while also examining its impact on the subsequent predictive performance of machine learning models. MATERIALS AND METHODS: 135 CT images of Credence Cartridge Radiomic phantoms were collected and screened from three scanners manufactured by Siemens, Philips, and GE. 100 radiomic features were extracted and 20 radiomic features were screened according to the Lasso regression method. The radiomic features extracted from the rubber and resin-filled regions in the cartridges were labeled into different categories for evaluating the performance of the machine learning model. Radiomics features were divided into three groups based on the different scanner manufacturers. The radiomic features were randomly divided into training and test sets with a ratio of 8:2. Five machine learning models (lasso, logistic regression, random forest, support vector machine, neural network) were employed to evaluate the impact of Combat on radiomic features. The variability among radiomic features were assessed using analysis of variance (ANOVA) and principal component analysis (PCA). Accuracy, precision, recall, and area under the receiver curve (AUC) were used as evaluation metrics for model classification. RESULTS: The principal component and ANOVA analysis results show that the variability of different scanner manufacturers in radiomic features was removed (P˃0.05). After harmonization with the Combat algorithm, the distributions of radiomic features were aligned in terms of location and scale. The performance of machine learning models for classification improved, with the Random Forest model showing the most significant enhancement. The AUC value increased from 0.88 to 0.92. CONCLUSIONS: The Combat algorithm has reduced variability in radiomic features from different scanners. In the phantom CT dataset, it appears that the machine learning model's classification performance may have improved after Combat harmonization. However, further investigation and validation are required to fully comprehend Combat's impact on radiomic features in medical imaging.

Targeting PI3K/AKT/mTOR signaling to overcome drug resistance in cancer.

This review comprehensively explores the challenge of drug resistance in cancer by focusing on the pivotal PI3K/AKT/mTOR pathway, elucidating its role in oncogenesis and resistance mechanisms across various cancer types. It meticulously examines the diverse mechanisms underlying resistance, including genetic mutations, feedback loops, and microenvironmental factors, while also discussing the associated resistance patterns. Evaluating current therapeutic strategies targeting this pathway, the article highlights the hurdles encountered in drug development and clinical trials. Innovative approaches to overcome resistance, such as combination therapies and precision medicine, are critically analyzed, alongside discussions on emerging therapies like immunotherapy and molecularly targeted agents. Overall, this comprehensive review not only sheds light on the complexities of resistance in cancer but also provides a roadmap for advancing cancer treatment.

Salvianolic acid B protects against UVB-induced skin aging via activation of NRF2.

BACKGROUND: Prolonged exposure to sun radiation may result in harmful skin photoaging. Therefore, discovering novel anti-photoaging treatment modalities is critical. An active component isolated from Salvia miltiorrhiza (SM), Salvianolic acid B (Sal-B), is a robust antioxidant and anti-inflammatory agent. This investigation aimed to discover the therapeutic impact and pathways of salvianolic acid B for UVB-induced skin photoaging, an area that remains unexplored. METHODS: We conducted in vitro experiments on human dermal fibroblasts (HDFs) exposed to UVB radiation, assessing cellular senescence, superoxide dismutase (SOD) activity, cell viability, proliferation, migration, levels of reactive oxygen species (ROS), and mitochondrial health. The potential mechanism of Sal-B was analyzed using RNA sequencing, with further validation through Western blotting, PCR, and nuclear factor erythroid 2-related factor 2 (NRF2) silencing methods. In vivo, a model of skin photoaging induced by UVB in nude mice was employed. The collagen fiber levels were assessed utilizing hematoxylin and eosin (H&E), Masson, and Sirus red staining. Additionally, NRF2 and related gene and protein expression levels were identified utilizing PCR and Western blotting. RESULTS: Sal-B was found to significantly counteract photoaging in UVB-exposed skin fibroblasts, reducing aging-related decline in fibroblast proliferation and an increase in apoptosis. It was observed that Sal-B aids in protecting mitochondria from excessive ROS production by promoting NRF2 nuclear translocation. NRF2 knockdown experiments established its necessity for Sal-B's anti-photoaging effects. The in vivo studies also verified Sal-B's anti-photoaging efficacy, surpassing that of tretinoin (Retino-A). These outcomes offer novel insights into the contribution of Sal-B in developing clinical treatment modalities for UVB-induced photodamage in skin fibroblasts. CONCLUSION: In this investigation, we identified the Sal-B protective impact on the senescence of dermal fibroblasts and skin photoaging induced by radiation of UVB. The outcomes suggest Sal-B as a potential modulator of the NRF2 signaling pathway.

HgBr2: an easily growing wide-spectrum birefringent crystal.

Birefringent materials are of great significance to the development of modern optical technology; however, research on halide birefringent crystals with a wide transparent range remains limited. In this work, mercuric bromide (HgBr2) has been investigated for the first time as a promising birefringent material with a wide transparent window spanning from ultraviolet (UV) to far-infrared (far-IR) spectral regions (0.34-22.9 µm). HgBr2 has an exceptionally large birefringence (Δn, 0.235 @ 546 nm), which is 19.6 times that of commercial MgF2. The ordered linear motif [Br-Hg-Br] with high polarizability anisotropy within the molecule is the inherent source of excellent birefringence, making it an efficient building block for birefringent materials. In addition, HgBr2 can be easily grown under mild conditions and remain stable in air for prolonged periods. Studying the birefringent properties of HgBr2 crystals would provide new ideas for future exploration of wide-spectrum birefringent materials.

The role of USP7-YY1 interaction in promoting colorectal cancer growth and metastasis.

Colorectal cancer (CRC) remains a significant global health issue with high incidence and mortality. Yin Yang 1 (YY1) is a powerful transcription factor that acts dual roles in gene activation and repression. High expression level of YY1 has been reported in CRC, indicating the existence of stable factors of YY1 in CRC cells. We aimed to identify the key molecules and underlying mechanisms responsible for stabilizing YY1 expression in CRC. Mass spectrometry analysis was utilized to identify USP7 as a potential molecule that interacted with YY1. Mechanically, USP7 stabilizes YY1 expression at the protein level by interfering its K63 linkage ubiquitination. YY1 exerts its oncogenic function through transcriptionally activating TRIAP1 but suppressing LC3B. In addition, at the pathological level, there is a positive correlation between the expression of YY1 and the budding of CRC. This study has revealed the intricate interplay between YY1 and USP7 in CRC, suggesting that they could serve as novel therapeutic targets or predictive biomarkers for CRC patients.

Pentanary Oxythiogermanates Ba3MGe3O2S8 (M = Ca, Zn) Featuring [Ge3O2S8]8- Trimers and {[MGe3O2S8]6-}∞ Chains: Structural Chemistry and Physical Properties.

Oxychalcogenides are increasingly attracting wide attention because they contain multiple anions that may combine the advantages of oxides and chalcogenides. In this work, two new pentanary oxythiogermanates, Ba3MGe3O2S8 [M = Ca (1), Zn (2)], were synthesized by a high-temperature solid-state reaction. They crystallize in the orthorhombic space group Pnma, and their structures contain isolated [Ge3O2S8]8- units constructed by one [GeO2S2] and two [GeOS3] tetrahedra that link with M2+ ions to build the {[MGe3O2S8]6-}∞ chain, representing a new type of oxythiogermanate. Notably, a [ZnS5] square pyramid exists in 2. Their structural chemistry and relationship with relevant structures are analyzed. 1 and 2 exhibit wide band gaps of 3.93 and 2.63 eV, birefringences of 0.100 and 0.089 at 2100 nm, respectively, and also obvious photocurrent responses. This work may be extended to a family of AE3MIIMIV3O2Q8 (AE = alkali-earth metal; MII = Ca, Zn, Cd, Hg; MIV = Si, Ge, Sn; Q = S, Se), and further systematic survey on them can be performed to enrich the study of multifunctional oxychalcogenides.

Water masses influence the variation of microbial communities in the Yangtze River Estuary and its adjacent waters.

The Yangtze River estuary (YRE) are strongly influenced by the Kuroshio and terrigenous input from rivers, leading to the formation of distinct water masses, however, there remains a limited understanding of the full extent of this influence. Here the variation of water masses and bacterial communities of 58 seawater samples from the YRE and its adjacent waters were investigated. Our findings suggested that there were 5 water masses in the studied area: Black stream (BS), coastal water in the East China Sea (CW), nearshore mixed water (NM), mixed water in the middle and deep layers of the East China Sea (MM), and deep water blocks in the middle of the East China Sea (DM). The CW mass harbors the highest alpha diversity across all layers, whereas the NM mass exhibits higher diversity in the surface layer but lower in the middle layers. Proteobacteria was the most abundant taxa in all water masses, apart from that, in the surface layer masses, Cyanobacterium, Bacteroidota, and Actinobacteriota were the highest proportion in CW, while Bacteroidota and Actinobacteriota were the highest proportion in NM and BS; in the middle layer, Bacteroidota and Actinobacteriota were dominant phylum in CW and BS masses, but Cyanobacterium was main phylum in NM mass; in the bottom layer, Bacteroidota and Actinobacteriota were the dominant phylum in CW, while Marininimicrobia was the dominated phylum in DM and MM masses. Network analysis suggests water masses have obvious influence on community topological characteristics, moreover, community assembly across masses also differ greatly. Taken together, these results emphasized the significant impact of water masses on the bacterial composition, topological characteristics and assembly process, which may provide a theoretical foundation for predicting alterations in microbial communities within estuarine ecosystems under the influence of water masses.