The Functional Characterization of MaGS2 and Its Role as a Negative Regulator of Ciboria shiraiana.

Glutamine synthetase (GS) is a key enzyme involved in nitrogen metabolism. GS can be divided into cytosolic and plastidic subtypes and has been reported to respond to various biotic and abiotic stresses. However, little research has been reported on the function of GS in mulberry. In this study, the full length of MaGS2 was cloned, resulting in 1302 bp encoding 433 amino acid residues. MaGS2 carried the typical GS2 motifs and clustered with plastidic-subtype GSs in the phylogenetic analysis. MaGS2 localized in chloroplasts, demonstrating that MaGS2 is a plastidic GS. The expression profile showed that MaGS2 is highly expressed in sclerotiniose pathogen-infected fruit and sclerotiniose-resistant fruit, demonstrating that MaGS2 is associated with the response to sclerotiniose in mulberry. Furthermore, the overexpression of MaGS2 in tobacco decreased the resistance against Ciboria shiraiana, and the knockdown of MaGS2 in mulberry by VIGS increased the resistance against C. shiraiana, demonstrating the role of MaGS2 as a negative regulator of mulberry resistance to C. shiraiana infection.

Prognostic implication and immunotherapy response prediction of a novel ubiquitination-related gene signature in liver cancer.

HCC, also known as hepatocellular carcinoma, is a frequently occurring form of cancer with an unfavorable prognosis. This research constructed a prognostic signature related to ubiquitination and investigated its correlation with the response to immunotherapy in HCC. The Molecular Signatures Database provided a compilation of genes associated with ubiquitination. A gene signature related to ubiquitination was obtained through Cox regression using the Least Absolute Shrinkage and Selection Operator method. The genetic factors CPY26B1, MCM10, SPINK4, and TRIM54 notably impacted the outcomes of HCC. The patients were divided into two groups: one group had a high risk of poor survival while the other had a low risk but a greater chance of controlling HCC progression. Both univariate and multivariate analyses using Cox regression found the risk score to be an independent predictor of HCC prognosis. Gene set enrichment analysis (GSEA) indicated enrichment in cell cycle and cancer-related microRNAs in high-risk groups. The tumor microenvironment (TME), response to immunotherapy, and effectiveness of chemotherapy medications positively correlated with the risk score. In the high-risk group, erlotinib showed higher IC50 values compared to the low-risk group which exhibited higher IC50 values for VX-11e, AKT inhibitor VIII, AT-7519, BMS345541, Bortezomib, CP466722, FMK, and JNK-9L. The results of RT-qPCR revealed that the expression of four UEGs was higher in tumor tissue as compared to normal tissue. Based on the genes that were expressed differently and associated with ubiquitination-related tumor categorization, we have developed a pattern of four genes and a strong nomogram that can predict the prognosis of HCC, which could be useful in identifying and managing HCC.

Advanced Materials for NH3 Capture: Interaction Sites and Transport Pathways.

Ammonia (NH3) is a carbon-free, hydrogen-rich chemical related to global food safety, clean energy, and environmental protection. As an essential technology for meeting the requirements raised by such issues, NH3 capture has been intensively explored by researchers in both fundamental and applied fields. The four typical methods used are (1) solvent absorption by ionic liquids and their derivatives, (2) adsorption by porous solids, (3) ab-adsorption by porous liquids, and (4) membrane separation. Rooted in the development of advanced materials for NH3 capture, we conducted a coherent review of the design of different materials, mainly in the past 5 years, their interactions with NH3 molecules and construction of transport pathways, as well as the structure-property relationship, with specific examples discussed. Finally, the challenges in current research and future worthwhile directions for NH3 capture materials are proposed.

Adjustments in energy metabolism of brown adipose tissue in heat-acclimated Kunming mice.

The thermogenic capacity of brown adipose tissue (BAT) in rodents decreases with prolonged heat exposure. However, the underlying mechanisms are not well understood. In this study, Kunming mice were acclimated at 23 ± 1 °C and 33 ± 1 °C for four weeks each to examine the body heat balance and BAT alterations. Results showed that heat-acclimated Kunming mice exhibited reduced body mass and elevated body temperature. Additionally, they displayed lower resting metabolic rates, diminished non-shivering thermogenesis, and reduced BAT thermogenic function. Metabolically, there was a significant reduction in several key metabolites involved in energy metabolism in BAT, including thiamine pyrophosphate, citric acid, cis-Aconitate, isocitric acid, oxoglutaric acid, succinate, fumarate, L-Malic acid, oxaloacetate, flavin mononucleotide, nicotinamide adenine dinucleotide, and adenosine 5'-triphosphate. These findings suggest that BAT adapts to heat acclimation by regulating pathways related to pyruvate oxidation, tricarboxylic acid cycle, and oxidative phosphorylation, which may help maintain thermal homeostasis in Kunming mice.

Porous Hydrogels for Immunomodulatory Applications.

Cancer immunotherapy relies on the insight that the immune system can be used to defend against malignant cells. The aim of cancer immunotherapy is to utilize, modulate, activate, and train the immune system to amplify antitumor T-cell immunity. In parallel, the immune system response to damaged tissue is also crucial in determining the success or failure of an implant. Due to their extracellular matrix mimetics and tunable chemical or physical performance, hydrogels are promising platforms for building immunomodulatory microenvironments for realizing cancer therapy and tissue regeneration. However, submicron or nanosized pore structures within hydrogels are not favorable for modulating immune cell function, such as cell invasion, migration, and immunophenotype. In contrast, hydrogels with a porous structure not only allow for nutrient transportation and metabolite discharge but also offer more space for realizing cell function. In this review, the design strategies and influencing factors of porous hydrogels for cancer therapy and tissue regeneration are first discussed. Second, the immunomodulatory effects and therapeutic outcomes of different porous hydrogels for cancer immunotherapy and tissue regeneration are highlighted. Beyond that, this review highlights the effects of pore size on immune function and potential signal transduction. Finally, the remaining challenges and perspectives of immunomodulatory porous hydrogels are discussed.

Effective capping of dissolved sulfide generated in Ulva prolifera-rich marine sediments by iron-rich red soil.

Bloom-induced macroalgal enrichment on the seafloor can substantially facilitate dissolved sulfide (DS) production through sulfate reduction. The reaction of DS with sedimentary reactive iron (Fe) is the main mechanism of DS consumption, which however usually could not effectively prevent DS accumulation caused by pulsed macroalgal enrichment. Here we used incubations to investigate the performance of Fe-rich red soil for buffering of DS produced from macroalgae (Ulva prolifera)-enriched sediment. Based on our results, a combination of red soil additions (6.8 kg/m2) before and immediately after pulsed macroalgal deposition (455 g/m2) can effectively cap DS within the red soil layer. The effective DS buffering is mainly due to ample Fe-oxide surface sites available for reaction with DS. Only a small loss (4 %) of buffering capacity after 18-d incubation suggests that the red soil is capable of prolonged DS buffering in macroalgae-enriched sediments.

Characterization of a predictive signature for tumor microenvironment and immunotherapy response in hepatocellular carcinoma involving neutrophil extracellular traps.

Neutrophil extracellular traps (NETs) and other factors play a significant role in impacting the prognosis of patients with Hepatocellular carcinoma (HCC). Nevertheless, further research is warranted to fully elucidate the prognostic implications of NETs in patients with HCC. We employed a hierarchical clustering technique to examine the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) data and identified subtypes associated with NETs. Subsequently, we utilized LASSO regression analysis to identify a distinct gene expression pattern within these subtypes. The strength of this signature was further validated through analysis of TCGA-LIHC and International Cancer Genome Consortium-Liver Cancer (ICGC-LIRI-JP) data. Our findings resulted in the construction of a six-gene signature related to NETs, which can predict survival outcomes in HCC patients. To enhance the predictive accuracy of our tool, we developed a nomogram that integrates the NETs signature with clinicopathological characteristics. We validated the significance of NETs in HCC patients using qRT-PCR and immunohistochemistry assays, along with in vitro experiments targeting high-risk genes. Furthermore, our exploration of the immune microenvironment uncovered augmented immune-specific metrics within the low-risk cohort, implying potential disparities in immune-related attributes between the high-risk and low-risk contingents. In summary, the NETs signature we discovered serves as a valuable biomarker and provides guidance for personalized therapy in HCC patients.

Synthesis and biological evaluation of novel benzothiazole derivatives as potential anticancer and antiinflammatory agents.

Introduction: Cancer, a significant global health concern, necessitates innovative treatments. The pivotal role of chronic inflammation in cancer development underscores the urgency for novel therapeutic strategies. Benzothiazole derivatives exhibit promise due to their distinctive structures and broad spectrum of biological effects. This study aims to explore new anti-tumor small molecule drugs that simultaneously anti-inflammatory and anticancer based on the advantages of benzothiazole frameworks. Methods: The compounds were characterized by nuclear magnetic resonance (NMR), liquid chromatograph-mass spectrometer (LC-MS) and high performance liquid chromatography (HPLC) for structure as well as purity and other related physicochemical properties. The effects of the compounds on the proliferation of human epidermoid carcinoma cell line (A431) and human non-small cell lung cancer cell lines (A549, H1299) were evaluated by MTT method. The effect of compounds on the expression levels of inflammatory factors IL-6 and TNF-α in mouse monocyte macrophages (RAW264.7) was assessed using enzyme-linked immunosorbent assay (ELISA). The effect of compounds on apoptosis and cell cycle of A431 and A549 cells was evaluated by flow cytometry. The effect of compounds on A431 and A549 cell migration was evaluated by scratch wound healing assay. The effect of compounds on protein expression levels in A431 and A549 cells was assessed by Western Blot assay. The physicochemical parameters, pharmacokinetic properties, toxicity and drug similarity of the active compound were predicted using Swiss ADME and admetSAR web servers. Results: Twenty-five novel benzothiazole compounds were designed and synthesized, with their structures confirmed through spectrogram verification. The active compound 6-chloro-N-(4-nitrobenzyl) benzo[d] thiazol-2-amine (compound B7) was screened through a series of bioactivity assessments, which significantly inhibited the proliferation of A431, A549 and H1299 cancer cells, decreased the activity of IL-6 and TNF-α, and hindered cell migration. In addition, at concentrations of 1, 2, and 4 µM, B7 exhibited apoptosis-promoting and cell cycle-arresting effects similar to those of the lead compound 7-chloro-N-(2, 6-dichlorophenyl) benzo[d] thiazole-2-amine (compound 4i). Western blot analysis confirmed that B7 inhibited both AKT and ERK signaling pathways in A431 and A549 cells. The prediction results of ADMET indicated that B7 had good drug properties. Discussion: This study has innovatively developed a series of benzothiazole derivatives, with a focus on compound B7 due to its notable dual anticancer and anti-inflammatory activities. B7 stands out for its ability to significantly reduce cancer cell proliferation in A431, A549, and H1299 cell lines and lower the levels of inflammatory cytokines IL-6 and TNF-α. These results position B7B7 as a promising candidate for dual-action cancer therapy. The study's mechanistic exploration, highlighting B7's simultaneous inhibition of the AKT and ERK pathways, offers a novel strategy for addressing both the survival mechanisms of tumor cells and the inflammatory milieu facilitating cancer progression.

Pan-cancer Multi-omics Analysis Reveals HMGN1 as a Potential Prognostic and Immune Infiltration-associated Biomarker.

BACKGROUND: The High Mobility Group Nucleosomal Binding Domain 1 Gene (HMGN1) is crucial for epigenetic regulation. However, the specific function of HMGN1 in cancer development is unclear. METHODS: Raw data on HMGN1 expression were procured from Genotype-Tissue Expression (GTEx), the University of Alabama- Birmingham CANcer data analysis Portal (UALCAN), and The Cancer Genome Atlas (TCGA). Thereafter, the pan-cancer analysis was implemented to understand the HMGN1 expression patterns, prognostic value, and immunological features. Furthermore, the Gene Set Enrichment Analysis (GSEA) was executed via R language. In addition, the relationship between HMGN1 and the sensitivity of antitumor drugs was also determined. Finally, real-time PCR (RT-PCR) experiments were carried out. RESULTS: Pan-cancer analysis revealed that HMGN1 was upregulated in several solid tumors and was associated with pathological staging and poor prognosis. In addition, HMGN1 was found to be involved in regulating the tumor microenvironment. The GSEA enrichment analysis indicated that HMGN1 assisted in the regulation of oncogenic processes, especially metabolic and immune pathways. Furthermore, HMGN1 expression was linked to microsatellite instability (MSI) and tumor mutational burden (TMB) across diverse tumor types. RT-PCR assays indicated that HMGN1 was overexpressed in the gastric and breast cancer cell lines and tissues. CONCLUSION: This study highlighted the potential of HMGN1 as a biomarker for pan- - cancer analysis.

Investigating the impact of inflammatory response-related genes on renal fibrosis diagnosis: a machine learning-based study with experimental validation.

Renal fibrosis plays a crucial role in the progression of renal diseases, yet the lack of effective diagnostic markers poses challenges in scientific and clinical practices. In this study, we employed machine learning techniques to identify potential biomarkers for renal fibrosis. Utilizing two datasets from the GEO database, we applied LASSO, SVM-RFE and RF algorithms to screen for differentially expressed genes related to inflammatory responses between the renal fibrosis group and the control group. As a result, we identified four genes (CCL5, IFITM1, RIPK2, and TNFAIP6) as promising diagnostic indicators for renal fibrosis. These genes were further validated through in vivo experiments and immunohistochemistry, demonstrating their utility as reliable markers for assessing renal fibrosis. Additionally, we conducted a comprehensive analysis to explore the relationship between these candidate biomarkers, immunity, and drug sensitivity. Integrating these findings, we developed a nomogram with a high discriminative ability, achieving a concordance index of 0.933, enabling the prediction of disease risk in patients with renal fibrosis. Overall, our study presents a predictive model for renal fibrosis and highlights the significance of four potential biomarkers, facilitating clinical diagnosis and personalized treatment. This finding presents valuable insights for advancing precision medicine approaches in the management of renal fibrosis.Communicated by Ramaswamy H. Sarma.

Global economic structure transition boosts PM2.5-related human health impact in Belt and Road Initiative.

The Belt and Road Initiative (BRI) is an open platform for international cooperation proposed by China to promote common global development and prosperity. The BRI can promote the optimal allocation of resources and promote in-depth cooperation in international trade. Meanwhile, it can establish a green supply chain cooperation network to help BRI countries achieve green transformation. BRI has made a notable contribution to the rapid growth of cross-border trade. However, it has also brought environmental impacts. Given that little attention has been paid to the trade-embodied particulate matter 2.5 related human health impacts (PM2.5-HHI) throughout the BRI, this study accounts for and traces the embodied PM2.5-HHI flows between the BRI countries and non-Belt and Road Initiative (non-BRI) countries. Moreover, this study also uncovers the critical socioeconomic drivers of PM2.5-HHI changes in BRI countries during 1990-2015, based on the multi-regional input-output based structural decomposition analysis (MRIO-SDA). Results show that, firstly, BRI countries had significantly increased their economic added value by exporting products to the non-BRI countries. They also have brought PM2.5-HHI to themselves. Secondly, the final demand of BRI countries was the largest potential driving force of PM2.5-HHI of BRI countries. Thirdly, the emission intensity change of BRI is the key socioeconomic factor for reducing PM2.5-HHI. While per capita final demand level change of BRI and production structure change of non-BRI are the key socioeconomic factors for increasing PM2.5-HHI. The study's findings on the one hand can help reduce the PM2.5-HHI and impacts of environmental pollution of BRI countries from a global perspective by providing scientific support. On the other hand, they can help provide relevant policy recommendations for the green transformation of BRI and the construction of green BRI.

Protective effect and mechanism of nanoantimicrobial peptide ND-C14 against Streptococcus pneumoniae infection.

BACKGROUND: Streptococcus pneumoniae (S. pneumoniae) is a common pathogen that causes bacterial pneumonia. However, with increasing bacterial resistance, there is an urgent need to develop new drugs to treat S. pneumoniae infections. Nanodefensin with a 14-carbon saturated fatty acid (ND-C14) is a novel nanoantimicrobial peptide designed by modifying myristic acid at the C-terminus of human α-defensin 5 (HD5) via an amide bond. However, it is unclear whether ND-C14 is effective against lung infections caused by S. pneumoniae. METHODS: In vitro, three groups were established, including the control group, and the HD5 and ND-C14 treatment groups. A virtual colony-count assay was used to evaluate the antibacterial activity of HD5 and ND-C14 against S. pneumoniae. The morphological changes of S. pneumoniae treated with HD5 or ND-C14 were observed by scanning electron microscopy. In vivo, mice were divided into sham, vehicle, and ND-C14 treatment groups. Mice in the sham group were treated with 25 µL of phosphate-buffered saline (PBS). Mice in the vehicle and ND-C14 treatment groups were treated with intratracheal instillation of 25 µL of bacterial suspension with 2×108 CFU/mL (total bacterial count: 5×106 CFU), and then the mice were given 25 µL PBS or intratracheally injected with 25 µL of ND-C14 (including 20 µg or 50 µg), respectively. Survival rates were evaluated in the vehicle and ND-C14 treatment groups. Bacterial burden in the blood and bronchoalveolar lavage fluid were counted. The lung histology of the mice was assessed. A propidium iodide uptake assay was used to clarify the destructive effect of ND-C14 against S. pneumoniae. RESULTS: Compared with HD5, ND-C14 had a better bactericidal effect against S. pneumoniae because of its stronger ability to destroy the membrane structure of S. pneumoniae in vitro. In vivo, ND-C14 significantly delayed the death time and improved the survival rate of mice infected with S. pneumoniae. ND-C14 reduced bacterial burden and lung tissue injury. Moreover, ND-C14 had a membrane permeation effect on S. pneumoniae, and its destructive ability increased with increasing ND-C14 concentration. CONCLUSION: The ND-C14 may improve bactericidal effects on S. pneumoniae both in vitro and in vivo.

Improving Mechanical Properties of Co-Cr-Fe-Ni High Entropy Alloy via C and Mo Microalloying.

The as-cast [Co40Cr25(FeNi)35-yMoy]100-xCx (x = 0, 0.5, y = 3, 4, 5 at.%) HEAs (high-entropy alloys) were prepared by a vacuum arc melting furnace and were then hot rolled. The effect of C and Mo elements on the microstructure evolution and mechanical properties of HEAs was systematically analyzed. The results showed that when no C atoms were added, the HEAs consisted of FCC + HCP dual-phase structure. In addition, as the Mo content increased, the grain size of the alloy increased from 17 µm to 47 µm. However, only the FCC phase appeared after adding 0.5 at.% carbon in Mo microalloyed HEAs, and the grain size of the Mo4C0.5 HEA decreased significantly. Due to the Mo atom content exceeding the solid solution limit, the carbides of Mo combined with the C element appeared in the Mo5C0.5 HEA. The strength of C and Mo microalloyed HEAs significantly increased compared to HEAs with no C added. However, the Mo4C0.5 HEA exhibited excellent comprehensive mechanical properties, which was superior to a majority of reported HEAs and conventional metal alloys. Its yield strength, tensile strength, and elongation were 757 MPa, 1186 MPa, and 69%, respectively. The strengthening mechanism was a combination of fine grain strengthening, TWIP effect, and solid solution strengthening.

Functional characterization of MaEXPA11 and its roles in response to biotic and abiotic stresses in mulberry.

Mulberry is a traditional economic tree with various values in sericulture, ecology, food industry and medicine. Expansins (EXPs) are known as cell wall expansion related proteins and have been characterized to involve in plant development and responses to diverse stresses. In present study, twenty EXP and expansin-like (EXL) genes were identified in mulberry. RNA-seq results indicated that three EXP and EXL genes showed up-regulated expression level under sclerotiniose pathogen infection in three independent RNA-seq datasets. The most significant upregulated EXPA11 was selected as key EXP involving in response to sclerotiniose pathogen infection in mulberry. Furthermore, a comprehensive functional analysis was performed to reveal subcellular location, tissue expression profile of MaEXPA11 in mulberry. Down-regulation of MaEXPA11 using virus induced gene silence (VIGS) was performed to explore the function of MaEXPA11 in Morus alba. Results showed that MaEXPA11 can positively regulate mulberry resistance to Ciboria shiraiana infection and negatively regulate mulberry resistance to cold or drought stress.

Polyurea-magnetic hierarchical porous composites for profiling of anionic metabolites.

Combining powerful adsorption capacity, simple preparation, rapid separation as well as superior stability and recyclability, a polyurea-magnetic hierarchical porous composite has been prepared. It demonstrates efficient physisorption for anionic metabolites in less than one minute and is promising for application to the analysis of a broad range of anionic metabolites in complex matrices.

New strategies to address world food security and elimination of malnutrition: future role of coarse cereals in human health.

As we face increasing challenges of world food security and malnutrition, coarse cereals are coming into favor as an important supplement to human staple foods due to their high nutritional value. In addition, their functional components, such as flavonoids and polyphenols, make them an important food source for healthy diets. However, we lack a systematic understanding of the importance of coarse cereals for world food security and nutritional goals. This review summarizes the worldwide cultivation and distribution of coarse cereals, indicating that the global area for coarse cereal cultivation is steadily increasing. This paper also focuses on the special adaptive mechanisms of coarse cereals to drought and discusses the strategies to improve coarse cereal crop yields from the perspective of agricultural production systems. The future possibilities, challenges, and opportunities for coarse cereal production are summarized in the face of food security challenges, and new ideas for world coarse cereal production are suggested.

Predictive accuracy of machine learning for radiation-induced temporal lobe injury in nasopharyngeal carcinoma patients: a systematic review and meta-analysis.

Background: Radiotherapy is a common treatment for nasopharyngeal carcinoma (NPC) but can cause radiation-induced temporal lobe injury (RTLI), resulting in irreversible damage. Predicting RTLI at the early stage may help with that issue by personalized adjustment of radiation dose based on the predicted risk. Machine learning (ML) models have recently been used to predict RTLI but their predictive accuracy remains unclear because the reported concordance index (C-index) varied widely from around 0.31 to 0.97. Therefore, a meta-analysis was needed. Methods: The PubMed, Web of Science, Embase, and Cochrane Library databases were searched from inception to November 2022. Studies that fully develop one or more ML risk models of RTLI after radiotherapy for NPC were included. The Prediction model Risk Of Bias Assessment Tool (PROBAST) was used to assess the risk of bias in the included research. The primary outcome of this review was the C-index, specificity (Spe), and sensitivity (Sen). Results: The meta-analysis included 14 studies with 15,573 NPC patients reporting a total of 72 prediction models. Overall, 94.44% of models were found to have a high risk of bias. Radiomics was included in 57 models, dosimetric predictors in 28, and clinical data in 27. The pooled C-index for ML models predicting RTLI was 0.77 [95% confidence interval (CI): 0.75-0.79] in the training set and 0.78 (95% CI: 0.75-0.81) in the validation set. The pooled Sen was 0.75 (95% CI: 0.69-0.80) in the training set and 0.70 (95% CI: 0.66-0.73) in the validation set and the pooled Spe was 0.78 (95% CI: 0.73-0.82) in the training set and 0.79 (95% CI: 0.75-0.82) in the validation set. Models with radiomics and clinical data achieved the most excellent discriminative performance, with a pooled C-index of 0.895. Conclusions: ML models can accurately predict RTLI at an early stage, allowing for timely interventions to prevent further damage. The kind of ML methods and the selection of predictors may influence the predictive accuracy.

Novel immune checkpoint-related gene model to predict prognosis and treatment responsiveness in low-grade gliomas.

Recently, studies have shown that immune checkpoint-related genes (ICGs) are instrumental in maintaining immune homeostasis and can be regarded as potential therapeutic targets. However, the prognostic applications of ICGs require further elucidation in low-grade glioma (LGG) cases. In the present study, a unique prognostic gene signature in LGG has been identified and validated as well based on ICGs as a means of facilitating clinical decision-making. The RNA-seq data as well as corresponding clinical data of LGG samples have been retrieved utilizing the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. ICG-defined non-negative matrix factorization (NMF) clustering was performed to categorize patients with LGG into two molecular subtypes with different prognoses, clinical traits, and immune microenvironments. In the TCGA database, a signature integrating 8 genes has been developed utilizing the LASSO Cox method and validated in the GEO database. The signature developed is superior to other well-recognized signatures in terms of predicting the survival probability of patients with LGG. This 8-gene signature was then subsequently applied to categorize patients into high- and low-risk groups, and differences between them in terms of gene alteration frequency were observed. There were remarkable variations in IDH1 (91% and 64%) across low-as well as high-risk groups. Additionally, various analyses like function enrichment, tumor immune microenvironment, and chemotherapy drug sensitivity revealed significant variations across high- and low-risk populations. Overall, this 8-gene signature may function as a useful tool for prognosis and immunotherapy outcome predictions among LGG patients.

Construction and validation of a signature for T cell-positive regulators related to tumor microenvironment and heterogeneity of gastric cancer.

Background: Positive regulators of T cell function play a vital role in the proliferation and differentiation of T cells. However, their functions in gastric cancer have not been explored so far. Methods: The TCGA-STAD dataset was utilized to perform consensus clustering in order to identify subtypes related to T cell-positive regulators. The prognostic differentially expressed genes of these subtypes were identified using the least absolute shrinkage and selection operator (LASSO) regression analysis. To validate the robustness of the identified signature, verification analyses were conducted across the TCGA-train, TCGA-test, and GEO datasets. Additionally, a nomogram was constructed to enhance the clinical efficacy of this predictive tool. Transwell migration, colony formation, and T cell co-culture assays were used to confirm the function of the signature gene in gastric cancer and its influence on T cell activation. Results: Two distinct clusters of gastric cancer, related to T cell-positive regulation, were discovered through the analysis of gene expression. These clusters exhibited notable disparities in terms of survival rates (P = 0.028), immune cell infiltration (P< 0.05), and response to immunotherapy (P< 0.05). Furthermore, a 14-gene signature was developed to classify gastric cancer into low- and high-risk groups, revealing significant differences in survival rates, tumor microenvironment, tumor mutation burden, and drug sensitivity (P< 0.05). Lastly, a comprehensive nomogram model was constructed, incorporating risk factors and various clinical characteristics, to provide an optimal predictive tool. Additionally, an assessment was conducted on the purported molecular functionalities of low- and high-risk gastric cancers. Suppression of DNAAF3 has been observed to diminish the migratory and proliferative capabilities of gastric cancer, as well as attenuate the activation of T cells induced by gastric cancer within the tumor microenvironment. Conclusion: We identified an ideal prognostic signature based on the positive regulators of T cell function in this study.

Characterizing Excited States of a Copper-Based Molecular Qubit Candidate with Correlated Electronic Structure Methods.

Molecular spins have a variety of potential advantages as qubits for quantum computation, such as tunability and well-understood design pathways through organometallic synthesis. Organometallic and heavy-metal-based molecular spin qubits can also exhibit rich electronic structures due to ligand field interactions and electron correlation. These features make consistent and reliable modeling of these species a considerable challenge for contemporary electronic structure techniques. Here, we elucidate the electronic structure of a Cu(II) complex analogous to a recently proposed room-temperature molecular spin qubit. Using active space methods to describe the electron correlation, we show the nuanced interaction between the metal d orbitals and ligand σ and π orbitals makes these systems challenging to model, both in terms of the delocalized spin density and the excited state ordering. We show that predicting the correct spin delocalization requires special consideration of the Cu d orbitals and that the excited state spectrum for the Cu(III) complex also requires the explicit inclusion of the π orbitals in the active space. These interactions are rather common in molecular spin qubit motifs and may play an important role in spin-decoherence processes. Our results may lend insight into future studies of the orbital interactions and electron delocalization of similar complexes.