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Genomic dissection of genetic effects on desirable traits and the subsequent use of genomic selection hold great promise for accelerating the rate of genetic improvement of forest tree species. In this study, a total of 661 offspring trees from 66 open-pollinated families of Japanese larch (Larix kaempferi (Lam.) Carrière) were sampled at a test site. The contributions of additive and non-additive effects (dominance, imprinting and epistasis) were evaluated for nine valuable traits related to growth, wood physical and chemical properties, and competitive ability using three pedigree-based and four Genomics-based Best Linear Unbiased Predictions (GBLUP) models and used to determine the genetic model. The predictive ability (PA) of two genomic prediction methods, GBLUP and Reproducing Kernel Hilbert Spaces (RKHS), was compared. The traits could be classified into two types based on different quantitative genetic architectures: for type I, including wood chemical properties and Pilodyn penetration, additive effect is the main source of variation (38.20-67.46%); for type II, including growth, competitive ability and acoustic velocity, epistasis plays a significant role (50.76-91.26%). Dominance and imprinting showed low to moderate contributions (< 36.26%). GBLUP was more suitable for traits of type I (PAs = 0.37-0.39 vs. 0.14-0.25), and RKHS was more suitable for traits of type II (PAs = 0.23-0.37 vs. 0.07-0.23). Non-additive effects make no meaningful contribution to the enhancement of PA of GBLUP method for all traits. These findings enhance our current understanding of the architecture of quantitative traits and lay the foundation for the development of genomic selection strategies in Japanese larch.
Subject(s)
Larix , Larix/genetics , Genotype , Japan , Genome , Genomics/methods , Phenotype , Models, Genetic , Polymorphism, Single NucleotideABSTRACT
Gels show great promise for applications in wearable electronics, biomedical devices, and energy storage systems due to their exceptional stretchability and adjustable electrical conductivity. However, the challenge lies in integrating multiple functions like elasticity, instantaneous self-healing, and a wide operating temperature range into a single gel. To address this issue, a hybrid hydrogen bonding strategy to construct gel with these desirable properties is proposed. The intricate network of hybrid strong weak hydrogen bonds within the polymer matrix enables these ionohydrogel to exhibit remarkable instantaneous self-healing, stretching up to five times their original length within seconds. Leveraging these properties, the incorporation of ionic liquids, water, and zinc salts into hybrid hydrogen bond crosslinked network enables conductivity and redox reaction, making it a versatile ionic skin for real-time monitoring of human movements and respiratory. Moreover, the ionohydrogel can be used as electrolyte in the assembly of a zinc-ion battery, ensuring a reliable power supply for wearable electronics, even in extreme conditions (-20 °C and extreme deformations). This ionohydrogel electrolyte simplifies the diverse structural requirements of gels to meet the needs of various electronic applications, offering a new approach for multi-functional electronics.
ABSTRACT
The room temperature metal-free cascade electrophilic addition/cyclization/oxidation reactions of (3-phenoxyprop-1-yn-1-yl)benzenes to divergently synthesize various brominated benzopyran derivatives (3-bromo-2H-chromenes, 3-bromo-2H-chromen-2-ols and 3-bromo coumarins) by tuning the amount of Br2 and H2O have been developed. The method exhibited high selectivity, mild reaction conditions, broad substrate scope, high efficiency, and the applicability for derivatization of the brominated products. The importance of the strategies provides a great advantage for selective synthesis of brominated benzopyran derivatives.
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BACKGROUND: The existing staging system cannot meet the needs of accurate survival prediction. Accurate survival prediction for locally advanced cervical cancer (LACC) patients who have undergone concurrent radiochemotherapy (CCRT) can improve their treatment management. Thus, this present study aimed to develop and validate radiomics models based on pretreatment 18Fluorine-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-computed tomography (CT) images to accurately predict the prognosis in patients. METHODS: The data from 190 consecutive patients with LACC who underwent pretreatment 18F-FDG PET-CT and CCRT at two cancer hospitals were retrospectively analyzed; 176 patients from the same hospital were randomly divided into training (n = 117) and internal validation (n = 50) cohorts. Clinical features were selected from the training cohort using univariate and multivariate Cox proportional hazards models; radiomic features were extracted from PET and CT images and filtered using least absolute shrinkage and selection operator and Cox proportional hazard regression. Three prediction models and a nomogram were then constructed using the previously selected clinical, CT and PET radiomics features. The external validation cohort that was used to validate the models included 23 patients with LACC from another cancer hospital. The predictive performance of the constructed models was evaluated using receiver operator characteristic curves, Kaplan Meier curves, and a nomogram. RESULTS: In total, one clinical, one PET radiomics, and three CT radiomics features were significantly associated with progression-free survival in the training cohort. Across all three cohorts, the combined model displayed better efficacy and clinical utility than any of these parameters alone in predicting 3-year progression-free survival (area under curve: 0.661, 0.718, and 0.775; C-index: 0.698, 0.724, and 0.705, respectively) and 5-year progression-free survival (area under curve: 0.661, 0.711, and 0.767; C-index, 0.698, 0.722, and 0.676, respectively). On subsequent construction of a nomogram, the calibration curve demonstrated good agreement between actually observed and nomogram-predicted values. CONCLUSIONS: In this study, a clinico-radiomics prediction model was developed and successfully validated using an independent external validation cohort. The nomogram incorporating radiomics and clinical features could be a useful clinical tool for the early and accurate assessment of long-term prognosis in patients with LACC patients who undergo concurrent chemoradiotherapy.
Subject(s)
Nomograms , Uterine Cervical Neoplasms , Female , Humans , Fluorodeoxyglucose F18 , Positron Emission Tomography Computed Tomography , Progression-Free Survival , Radiomics , Retrospective Studies , Uterine Cervical Neoplasms/diagnostic imaging , Uterine Cervical Neoplasms/therapyABSTRACT
The La(OTf)3-catalyzed [3+2] cycloaddition reactions for the synthesis of benzo[d]oxazoles/benzofurans via quinones and 1,2-di-tert-butyl-3-(cyanimino)diaziridine (1,3-di-tert-butyl-2-cyanoguanidine)/vinyl azides have been explored. A series of 5-hydroxybenzofuran-4-carboxylic acid derivatives and 5-hydroxybenzo[d]oxazole-4-carboxylic acid derivatives were conveniently obtained with high yields and good stereoselectivities, which could be used for further transformations to valuable compounds.
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Microwave irradiation (MW) and ionic liquids (ILs) are two of the most promising relatively greener synthetic approaches to preparing value-added chemicals. Herein, a series of 2-acylbenzothiazole derivatives were synthesized for the first time from commercially available α-bromoacetophenones and disulfane-diyl-dianilines through the cooperation of ionic liquids and microwave irradiation under metal- and extra-additives-free conditions. A plausible mechanism involving the successive IL-induced enolation has been proposed.
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PURPOSE: Despite the increasing preference for minimally invasive surgery for colorectal cancer (CRC), the incidence of prolonged postoperative ileus (PPOI) remains high. Thus, this study aimed to identify risk factors for PPOI in patients with CRC who underwent minimally invasive surgery (MICRS) and to develop a practical nomogram for predicting individual PPOI risk. METHODS: A consecutive series of 2368 patients who underwent MICRS between 2013 and 2023 at two tertiary academic centers were retrospectively studied. Using the data from 1895 patients in the training cohort, a multivariable logistic regression model was employed to select significant variables for the construction of a best-fit nomogram. The nomogram was internally and externally validated. RESULTS: PPOI occurred in 9.5% of patients. Six independent risk factors were identified to construct a nomogram: advanced age (OR 1.055, P = 0.002), male sex (OR 2.914, P = 0.011), age-adjusted Charlson comorbidity index ≥ 6 (OR 2.643, P = 0.025), preoperative sarcopenia (OR 0.857, P = 0.02), preoperative prognostic nutritional index (OR 2.206, P = 0.047), and intraoperative fluid overload (OR 2.227, P = 0.045). The AUCs of the model for predicting PPOI in the training and external validation cohorts were 0.887 and 0.838, respectively. The calibration curves demonstrated excellent consistency between the nomogram-predicted and observed probabilities in both cohorts. Individuals with a total nomogram score of < 197 or ≥ 197 were considered to be at low or high risk for PPOI, respectively. CONCLUSIONS: The integrated nomogram we developed could provide personalized risk prediction of PPOI after MICRS. This quantification enables surgeons to implement personalized prevention strategies, thereby improving patient outcomes.
Subject(s)
Colorectal Neoplasms , Ileus , Minimally Invasive Surgical Procedures , Nomograms , Postoperative Complications , Humans , Male , Female , Risk Factors , Ileus/etiology , Ileus/epidemiology , Middle Aged , Colorectal Neoplasms/surgery , Aged , Minimally Invasive Surgical Procedures/adverse effects , Postoperative Complications/etiology , Risk Assessment , Precision Medicine , Retrospective StudiesABSTRACT
Understanding the extent of heritability of a plant-associated microbiome (phytobiome) is critically important for exploitation of phytobiomes in agriculture. Two crosses were made between pairs of cotton cultivars (Z2 and J11, L1 and Z49) with differential resistance to Verticillium wilt. F2 plants were grown in a field, together with the four parents to study the heritability of cotton rhizosphere microbiome. Amplicon sequencing was used to profile bacterial and fungal communities in the rhizosphere. F2 offspring plants of both crosses had higher average alpha diversity indices than the two parents; parents differed significantly from F2 offspring in Bray-Curtis beta diversity indices as well. Two types of data were used to study the heritability of rhizosphere microbiome: principal components (PCs) and individual top microbial operational taxonomic units (OTUs). For the L1 × Z49 cross, the variance among the F2 progeny genotypes (namely, genetic variance, VT) was significantly greater than the random variability (VE) for 12 and 34 out of top 100 fungal and bacterial PCs, respectively. For the Z2 × J11 cross, the corresponding values were 10 and 20 PCs. For 29 fungal OTUs and 10 bacterial OTUs out of the most abundant 100 OTUs, genetic variance (VT) was significantly greater than VE for the L1 × Z49 cross; the corresponding values for the Z2 × J11 cross were 24 and one. The estimated heritability was mostly in the range of 40% to 60%. These results suggested the existence of genetic control of polygenic nature for specific components of rhizosphere microbiome in cotton. KEY POINTS: ⢠F2 offspring cotton plants differed significantly from parents in rhizosphere microbial diversity. ⢠Specific rhizosphere components are likely to be genetically controlled by plants. ⢠Common PCs and specific microbial groups are significant genetic components between the two crosses.
Subject(s)
Bacteria , Fungi , Gossypium , Microbiota , Rhizosphere , Soil Microbiology , Gossypium/microbiology , Gossypium/genetics , Microbiota/genetics , Fungi/genetics , Fungi/classification , Fungi/isolation & purification , Bacteria/genetics , Bacteria/classification , Bacteria/isolation & purification , Plant Diseases/microbiology , Plant Roots/microbiology , Plant Roots/genetics , Genetic Variation , Verticillium/genetics , GenotypeABSTRACT
The time-dependent quantum transportation through a metal/polymer/metal system is theoretically investigated on the basis of a Su-Schrieffer-Heeger model combined with the hierarchical equations of motion formalism. Using a non-adiabatic dynamical method, the evolution of the electron subspace and lattice atoms with time can be obtained. It is found that the calculated transient currents vary with time and reach stable values after a response time under the bias voltages. However, the stable current as the system reaches its dynamical steady state exhibits a discrepancy between two sweep directions of the bias voltage, which results in pronounced electrical hysteresis loops in the current-voltage curve. By analyzing the evolution of instantaneous energy eigenstates, the occupation number of the instantaneous eigenstates, and the lattice of the polymer, we show that the formation of excitons and the delay of their annihilation are responsible for the hysteretic current-voltage characteristics, where electron-phonon interactions play the key factor. Furthermore, the hysteresis width and amplitude can also be modulated by the strength of the electron-phonon coupling, level-width broadening function, and temperature. We hope these results about past condition-dependent switching performance at a sweep voltage can provide further insight into some of the basic issues of interest in hysteresis processes in conducting polymers.
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BACKGROUND: Cancer screening is a pivotal method for reducing mortality from disease, but the screening coverage is still lower than expected. Telehealth interventions demonstrated significant benefits in cancer care, yet there is currently no consensus on their impact on facilitating cancer screening or on the most effective remote technology. DESIGN: A network meta-analysis was conducted to detect the impact of telehealth interventions on cancer screening and to identify the most effective teletechnologies. METHODS: Six English databases were searched from inception until July 2023 to yield relevant randomized controlled trials (RCTs). Two individual authors completed the literature selection, data extraction, and methodological evaluations using the Cochrane Risk of Bias tool. Traditional pairwise analysis and network meta-analysis were performed to identify the overall effects and compare different teletechnologies. RESULTS: Thirty-four eligible RCTs involving 131,644 participants were enrolled. Overall, telehealth interventions showed statistically significant effects on the improvement of cancer screening. Subgroup analyses revealed that telehealth interventions were most effective for breast and cervical cancer screening, and rural populations also experienced benefits, but there was no improvement in screening for older adults. The network meta-analysis indicated that mobile applications, video plus telephone, and text message plus telephone were associated with more obvious improvements in screening than other teletechnologies. CONCLUSION: Our study identified that telehealth interventions were effective for the completion of cancer screening and clarified the exact impact of telehealth on different cancer types, ages, and rural populations. Mobile applications, video plus telephone, and text message plus telephone are the three forms of teletechnologies most likely to improve cancer screening. More well-designed RCTs involving direct comparisons of different teletechnologies are needed in the future. CLINICAL RELEVANCE: Telehealth interventions should be encouraged to facilitate cancer screening, and the selection of the optimal teletechnology based on the characteristics of the population is also necessary.
Subject(s)
Early Detection of Cancer , Network Meta-Analysis , Randomized Controlled Trials as Topic , Telemedicine , Humans , Early Detection of Cancer/methods , Early Detection of Cancer/statistics & numerical data , Mass Screening/statistics & numerical data , Mass Screening/methods , Neoplasms/diagnosisABSTRACT
As an important class of detoxifying enzymes, glutathione S-transferases (GSTs) are pivotal in decreasing insecticide toxicity to insects. Periplaneta americana GSTd1 (PaGSTd1) has been verified as a key enzyme in detoxifying pyrethroid insecticides, but its detoxification capability against a broader spectrum of insecticides has never been investigated. It is revealed that PaGSTd1 expression showed a rapid and significant increase upon exposure to various insecticides (organophosphates, neonicotinoids, and fipronil). Subsequent in vitro metabolic assays indicated that organophosphates, particularly chlorpyrifos-methyl, can be effectively metabolized by PaGSTd1. Further knockdown of PaGSTd1 via RNA interference significantly heightened the susceptibility of P. americana to chlorpyrifos-methyl, underscoring the enzyme's key role in detoxifying chlorpyrifos-methyl. Additionally, this study confirmed that PaGSTd1 cannot mitigate insecticide toxicity through countering oxidative stress. Collectively, these findings elucidate the involvement of PaGSTd1 in the detoxification processes for organophosphates, offering a comprehensive insight into the metabolic mechanisms mediated by GSTs in P. americana. This research provides a foundational understanding for managing GSTs-mediated metabolic resistance in this species, which is crucial for effective pest control strategies.
Subject(s)
Glutathione Transferase , Insecticides , Periplaneta , Periplaneta/drug effects , Periplaneta/metabolism , Animals , Insecticides/toxicity , Insecticides/pharmacology , Glutathione Transferase/metabolism , Glutathione Transferase/genetics , Organophosphates/toxicity , Organophosphates/metabolism , Insect Proteins/metabolism , Insect Proteins/genetics , Inactivation, Metabolic , Chlorpyrifos/toxicity , Chlorpyrifos/analogs & derivatives , Oxidative Stress/drug effectsABSTRACT
AIMS AND OBJECTIVES: To assess the effectiveness of different nonpharmacological treatments for severe radiation-induced oral mucositis in patients with head and neck cancer. BACKGROUND: Radiation-induced oral mucositis is highly prevalent in patients with head and neck cancer. Current medications for radiation-induced oral mucositis are limited in effectiveness and susceptible to side effects, and while there is an increasing adoption of nonpharmacological interventions, the optimal one remains unclear. DESIGN: Systematic review and network meta-analysis based on the PRISMA-NMA guidelines. METHODS: Six databases were searched. Two authors independently performed the literature screening, data extraction and methodological quality assessment of the included studies. Traditional pairwise meta-analysis was performed by R Studio. A network meta-analysis was then conducted to assess the effects of nonpharmacological interventions for severe radiation-induced oral mucositis in patients with head and neck cancer. RESULTS: Fifty-two studies involving seven types of nonpharmacological interventions were enrolled. The network meta-analysis indicated that natural plant-based therapies might be the most effective, health education interventions might be the second most effective, and honey might be the third most effective interventions for reducing the incidence of severe radiation-induced oral mucositis. For reducing the incidence of severe oral mucositis-related pain, the pairwise meta-analysis showed that only natural plant-based therapies and health education interventions were effective. CONCLUSIONS: Nonpharmacological interventions are effective in the management of severe radiation-induced oral mucositis among patients with head and neck cancer. RELEVANCE TO CLINICAL PRACTICE: Nonpharmacological interventions are a category of safe and effective adjunctive therapies that should be encouraged in clinical practice. TRIAL REGISTRATION DETAILS: CRD42023400745.
Subject(s)
Head and Neck Neoplasms , Radiation Injuries , Stomatitis , Humans , Head and Neck Neoplasms/radiotherapy , Network Meta-Analysis , Radiation Injuries/therapy , Radiation Injuries/etiology , Randomized Controlled Trials as Topic , Stomatitis/etiologyABSTRACT
Noninvasive differentiation between the squamous cell carcinoma (SCC) and adenocarcinoma (ADC) subtypes of non-small cell lung cancer (NSCLC) could benefit patients who are unsuitable for invasive diagnostic procedures. Therefore, this study evaluates the predictive performance of a PET/CT-based radiomics model. It aims to distinguish between the histological subtypes of lung adenocarcinoma and squamous cell carcinoma, employing four different machine learning techniques. A total of 255 Non-Small Cell Lung Cancer (NSCLC) patients were retrospectively analyzed and randomly divided into the training (n = 177) and validation (n = 78) sets, respectively. Radiomics features were extracted, and the Least Absolute Shrinkage and Selection Operator (LASSO) method was employed for feature selection. Subsequently, models were constructed using four distinct machine learning techniques, with the top-performing algorithm determined by evaluating metrics such as accuracy, sensitivity, specificity, and the area under the curve (AUC). The efficacy of the various models was appraised and compared using the DeLong test. A nomogram was developed based on the model with the best predictive efficiency and clinical utility, and it was validated using calibration curves. Results indicated that the logistic regression classifier had better predictive power in the validation cohort of the radiomic model. The combined model (AUC 0.870) exhibited superior predictive power compared to the clinical model (AUC 0.848) and the radiomics model (AUC 0.774). In this study, we discovered that the combined model, refined by the logistic regression classifier, exhibited the most effective performance in classifying the histological subtypes of NSCLC.
Subject(s)
Adenocarcinoma , Carcinoma, Non-Small-Cell Lung , Carcinoma, Squamous Cell , Lung Neoplasms , Humans , Adenocarcinoma/diagnostic imaging , Carcinoma, Non-Small-Cell Lung/diagnostic imaging , Carcinoma, Squamous Cell/diagnostic imaging , Epithelial Cells , Fluorodeoxyglucose F18 , Lung , Lung Neoplasms/diagnostic imaging , Machine Learning , Positron Emission Tomography Computed Tomography , Radiomics , Retrospective StudiesABSTRACT
Pyrethroids are ubiquitously present in environmental media and threaten both the ecosystem and human health. To explore effective ways to remove pyrethroids from the environment, an odorant binding protein (OBP) with affinity for various pyrethroids was investigated. Initially, the target OBP, Spodoptera littoralis pheromone binding protein 1 (SlitPBP1), underwent redesign to enhance its affinity for pyrethroids. The modified SlitPBP1E97ND106E demonstrated a substantially increased affinity for deltamethrin (DeltaM), with a dissociation constant of 0.77 ± 0.17 µM. The affinity of SlitPBP1E97ND106E for other pyrethroids also increased to varying extents. Consequently, SlitPBP1E97ND106E displayed a markedly enhanced capability to adsorb and remove pyrethroids. When exposed to free SlitPBP1E97ND106E in solution, the reduction in DeltaM surged from 16.78 ± 0.32% to 97.51 ± 0.56%. SlitPBP1E97ND106E was immobilized by coupling the protein to Ni2+-NTA agarose resin. Liquid chromatography results attested to the superior efficacy of immobilized SlitPBP1E97ND106E in removing pyrethroids, especially DeltaM. No significant differences in pyrethroid removal were detected across various water samples. Our findings introduce a potent tool for pyrethroid removal. A wider range of OBPs can similarly be optimized and applied to remove organic pollutants, including but not limited to pesticides.
Subject(s)
Environmental Pollutants , Insecticides , Pesticides , Pyrethrins , Humans , Pyrethrins/analysis , Ecosystem , Odorants , Pesticides/analysis , Environmental Pollutants/analysis , Insecticides/chemistryABSTRACT
The physical characteristics of classrooms can significantly impact the physical and mental health as well as the learning performance of college students. This study investigates the effects of classroom size and ceiling height on learning performance using virtual reality technology. Four classroom settings were created: two small classrooms (40.5 m2) with ceiling heights of 3.0 m and 3.9 m, and two large classrooms (62.1 m2) with ceiling heights of 3.9 m and 4.8 m. 34 students participated in task tests while their subjective evaluations and physiological data were recorded. Results showed higher subjective ratings in larger classrooms with the same ceiling height. Classroom size did not significantly affect task test scores. However, there is a significant difference in Task test scores for ceilings of different heights with the same size classroom. The task test improved by 17.3% in the Big and High Room (BHR) and by 20.1% in the Small and Low Room (SLR). Physiological data revealed significant effects of ceiling height, with HRV-nLF/nHF and EEG-ß power increasing by 26.5% and 53.9% in BHR, and by 10.7% and 22.8% in SLR, respectively. This study concludes that classroom size and ceiling height plays a crucial role in learning performance and provides insights for classroom design. It also establishes a framework for future research on the interplay between heart rate variability, EEG, and learning performance.
Subject(s)
Learning , Students , Virtual Reality , Humans , Male , Female , Young Adult , Learning/physiology , Universities , AdultABSTRACT
Sti1/Hop, a stress-induced co-chaperone protein, serves as a crucial link between Hsp70 and Hsp90 during cellular stress responses. Despite its importance in stress defense mechanisms, the biological role of Sti1 in Verticillium dahliae, a destructive fungal pathogen, remains largely unexplored. This study focused on identifying and characterizing Sti1 homologues in V. dahliae by comparing them to those found in Saccharomyces cerevisiae. The results indicated that the VdSti1-deficient mutant displayed increased sensitivity to drugs targeting the ergosterol synthesis pathway, leading to a notable inhibition of ergosterol biosynthesis. Moreover, the mutant exhibited reduced production of microsclerotia and melanin, accompanied by decreased expression of microsclerotia and melanin-related genes VDH1, Vayg1, and VaflM. Additionally, the mutant's conidia showed more severe damage under heat shock conditions and displayed growth defects under various stressors such as temperature, SDS, and CR stress, as well as increased sensitivity to H2O2, while osmotic stress did not impact its growth. Importantly, the VdSti1-deficient mutant demonstrated significantly diminished pathogenicity compared to the wild-type strain. This study sheds light on the functional conservation and divergence of Sti1 homologues in fungal biology and underscores the critical role of VdSti1 in microsclerotia development, stress response, and pathogenicity of V. dahliae.
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There is currently a lack of effective olfaction-based techniques to control diamondback moth (DBM) larvae. Identifying behaviorally active odorants for DBM larvae and exploring their recognition mechanisms can provide insights into olfaction-based larval control strategies. Through the two-choice assay, (E,E)-2,6-farnesol (farnesol) was identified as a compound exhibiting significant attractant activity toward DBM larvae, achieving an attraction index of 0.48 ± 0.13. PxylGOBP1 and PxylGOBP2, highly expressed in the antennae of DBM larvae, both showed high affinity toward farnesol. RNAi technology was used to knock down PxylGOBP1 and PxylGOBP2, revealing that the attraction of DBM larvae to farnesol nearly vanished following the knockdown of PxylGOBP2, indicating its critical role in recognizing farnesol. Further investigation into the PxylGOBP2-farnesol interaction revealed the importance of residues like Thr9, Trp37, and Phe118 in PxylGOBP2's binding to farnesol. This research is significant for unveiling the olfactory mechanisms of DBM larvae and developing larval behavior regulation techniques.
Subject(s)
Farnesol , Moths , Animals , Larva/genetics , Farnesol/pharmacology , Farnesol/metabolism , Odorants , Moths/metabolism , SmellABSTRACT
Sirtuins are pivotal in orchestrating numerous cellular pathways, critically influencing cell metabolism, DNA repair, aging processes, and oxidative stress. In recent years, the involvement of sirtuins in tumor biology has garnered substantial attention, with a growing body of evidence underscoring their regulatory roles in various aberrant cellular processes within tumor environments. This article delves into the sirtuin family and its biological functions, shedding light on their dual roles-either as promoters or inhibitors-in various cancers including oral, breast, hepatocellular, lung, and gastric cancers. It further explores potential anti-tumor agents targeting sirtuins, unraveling the complex interplay between sirtuins, miRNAs, and chemotherapeutic drugs. The dual roles of sirtuins in cancer biology reflect the complexity of targeting these enzymes but also highlight the immense therapeutic potential. These advancements hold significant promise for enhancing clinical outcomes, marking a pivotal step forward in the ongoing battle against cancer.
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Background: Lung squamous cell carcinoma (LUSC) ranks among the carcinomas with the highest incidence and dismal survival rates, suffering from a lack of effective therapeutic strategies. Consequently, biomarkers facilitating early diagnosis of LUSC could significantly enhance patient survival. This study aims to identify novel biomarkers for LUSC. Methods: Utilizing the TCGA, GTEx, and CGGA databases, we focused on the gene encoding Family with Sequence Similarity 20, Member A (FAM20A) across various cancers. We then corroborated these bioinformatic predictions with clinical samples. A range of analytical tools, including Kaplan-Meier, MethSurv database, Wilcoxon rank-sum, Kruskal-Wallis tests, Gene Set Enrichment Analysis, and TIMER database, were employed to assess the diagnostic and prognostic value of FAM20A in LUSC. These tools also helped evaluate immune cell infiltration, immune checkpoint genes, DNA repair-related genes, DNA methylation, and tumor-related pathways. Results: FAM20A expression was found to be significantly reduced in LUSC, correlating with lower survival rates. It exhibited a negative correlation with key proteins in DNA repair signaling pathways, potentially contributing to LUSC's radiotherapy resistance. Additionally, FAM20A showed a positive correlation with immune checkpoints like CTLA-4, indicating potential heightened sensitivity to immunotherapies targeting these checkpoints. Conclusion: FAM20A emerges as a promising diagnostic and prognostic biomarker for LUSC, offering potential clinical applications.