The combination of temozolomide and perifosine synergistically inhibit glioblastoma by impeding DNA repair and inducing apoptosis.

Temozolomide (TMZ) is widely utilized as the primary chemotherapeutic intervention for glioblastoma. However, the clinical use of TMZ is limited by its various side effects and resistance to chemotherapy. The present study revealed the synergistic inhibition of glioblastoma through the combined administration of TMZ and perifosine. This combination therapy markedly diminished BRCA1 expression, resulting in the suppression of DNA repair mechanisms. Furthermore, the combination of TMZ and perifosine elicited caspase-dependent apoptosis, decreasing glioblastoma cell viability and proliferation. The observed synergistic effect of this combination therapy on glioblastoma was validated in vivo, as evidenced by the substantial reduction in glioblastoma xenograft growth following combined treatment with TMZ and perifosine. In recurrent glioma patients, higher BRCA1 expression is associated with worse prognosis, especially the ones that received TMZ-treated. These findings underscore the potent antitumor activity of the AKT inhibitor perifosine when combined with TMZ and suggest that this approach is a promising strategy for clinical glioblastoma treatment.

The development of the biological soil crust regulates the fungal distribution and the stability of fungal networks.

The heterogeneous composition of fungi plays an indispensable role in the foundation of the multifunctionalities of ecosystems within drylands. The precise mechanisms that govern fluctuations in soil fungal assemblages in dryland ecosystems remain incompletely elucidated. In this study, biological soil crusts (biocrusts) at different successional stages in the Gurbantunggut Desert were used as substrates to examine the characteristics and driving factors that influence fungal abundance and community dynamics during biocrust development using qPCR and high-throughput sequencing of the ITS2 region. The findings showed that the physicochemical properties changed significantly with the development of biocrusts. In particular, total nitrogen increased 4.8 times, along with notable increases in ammonium, total phosphorus (2.1 times) and soil organic carbon (6.5 times). Initially, there was a rise in fungal abundance, which was subsequently followed by a decline as the biocrust developed, with the highest abundance detected in lichen crust (2.66 × 107 copies/g soil) and the lowest in bare sand (7.98 × 106 copies/g soil). Ascomycetes and Basidiomycetes emerged as dominant phyla, collectively forming 85% of the fungal community. As the biocrust developed, noticeable alterations occurred in fungal community compositions, resulting from changes in the relative proportions of Dothideomycetes, Lecanoromycetes and unclassified ascomycetes. Nitrogen, phosphorus, organic carbon content, and pH of biocrusts were identified as direct or indirect regulators of fungal abundance and community structure. The complexity of fungal networks increased as biocrusts developed as revealed by network analysis, but reduced in the stability of fungal communities within algal and lichen crusts. Keystone species within the fungal community also underwent changes as biocrust developed. These results suggested that shifts in interspecies relationships among fungi could further contribute to the variation in fungal communities during the development of biocrusts.

Crystal structure of a tetrameric RNA G-quadruplex formed by hexanucleotide repeat expansions of C9orf72 in ALS/FTD.

The abnormal GGGGCC hexanucleotide repeat expansions (HREs) in C9orf72 cause the fatal neurodegenerative diseases including amyotrophic lateral sclerosis and frontotemporal dementia. The transcribed RNA HREs, short for r(G4C2)n, can form toxic RNA foci which sequestrate RNA binding proteins and impair RNA processing, ultimately leading to neurodegeneration. Here, we determined the crystal structure of r(G4C2)2, which folds into a parallel tetrameric G-quadruplex composed of two four-layer dimeric G-quadruplex via 5'-to-5' stacking in coordination with a K+ ion. Notably, the two C bases locate at 3'- end stack on the outer G-tetrad with the assistance of two additional K+ ions. The high-resolution structure reported here lays a foundation in understanding the mechanism of neurological toxicity of RNA HREs. Furthermore, the atomic details provide a structural basis for the development of potential therapeutic agents against the fatal neurodegenerative diseases ALS/FTD.

Consistent community assembly but contingent species pool effects drive ß-diversity patterns of multiple microbial groups in desert biocrust systems.

One of the key goals of ecology is to understand how communities are assembled. The species co-existence theory suggests that community ß-diversity is influenced by species pool and community assembly processes, such as environmental filtering, dispersal events, ecological drift and biotic interactions. However, it remains unclear whether there are similar ß-diversity patterns among different soil microbial groups and whether all these mechanisms play significant roles in mediating ß-diversity patterns. By conducting a broad survey across Chinese deserts, we aimed to address these questions by investing biological soil crusts (biocrusts). Through amplicon-sequencing, we acquired ß-diversity data for multiple microbial groups, that is, soil total bacteria, diazotrophs, phoD-harbouring taxa, and fungi. Our results have shown varying distance decay rates of ß-diversity across microbial groups, with soil total bacteria showing a weaker distance-decay relationship than other groups. The impact of the species pool on community ß-diversity varied across microbial groups, with soil total bacteria and diazotrophs being significantly influenced. While the contributions of specific assembly processes to community ß-diversity patterns varied among different microbial groups, significant effects of local community assembly processes on ß-diversity patterns were consistently observed across all groups. Homogenous selection and dispersal limitation emerged as crucial processes for all groups. Precipitation and soil C:P were the key factors mediating ß-diversity for all groups. This study has substantially advanced our understanding of how the communities of multiple microbial groups are structured in desert biocrust systems.

Advances in Nanodynamic Therapy for Cancer Treatment.

Nanodynamic therapy (NDT) exerts its anti-tumor effect by activating nanosensitizers to generate large amounts of reactive oxygen species (ROS) in tumor cells. NDT enhances tumor-specific targeting and selectivity by leveraging the tumor microenvironment (TME) and mechanisms that boost anti-tumor immune responses. It also minimizes damage to surrounding healthy tissues and enhances cytotoxicity in tumor cells, showing promise in cancer treatment, with significant potential. This review covers the research progress in five major nanodynamic therapies: photodynamic therapy (PDT), electrodynamic therapy (EDT), sonodynamic therapy (SDT), radiodynamic therapy (RDT), and chemodynamic therapy (CDT), emphasizing the significant role of advanced nanotechnology in the development of NDT for anti-tumor purposes. The mechanisms, effects, and challenges faced by these NDTs are discussed, along with their respective solutions for enhancing anti-tumor efficacy, such as pH response, oxygen delivery, and combined immunotherapy. Finally, this review briefly addresses challenges in the clinical translation of NDT.

Freestanding Serpentine Silicon Strips with Ultrahigh Stretchability over 300% for Wearable Electronics.

Well-functionalized electronic materials, such as silicon, in a stretchable format are desirable for high-performance wearable electronics. However, obtaining Si materials that meet the required stretchability of over 100% for wearable applications remains a significant challenge. Herein, a rational design strategy is proposed to achieve freestanding serpentine Si strips (FS-Si strips) with ultrahigh stretchability, fulfilling wearable requirements. The self-supporting feature makes the strips get rid of excessive constraints from substrates and enables them to deform with the minimum strain energy. Micrometer-scale thicknesses enhance robustness, and large diameter-to-width ratios effectively reduce strain concentration. Consequently, the FS-Si strips with the optimum design could withstand 300% stretch, bending, and torsion without fracturing, even under rough manual operation. They also exhibit excellent stability and durability over 50,000 cycles of 100% stretching cycles. For wearable applications, the FS-Si strips can maintain conformal contact with the skin and have a maximum stretchability of 120%. Moreover, they are electrically insensitive to large deformations, which ensure signal stability during their daily use. Combined with mature processing techniques and the excellent semiconductor properties of Si, FS-Si strips are promising core stretchable electronic materials for wearable electronics.

Surface Modification of Silicon Nanowires with Siloxane Molecules for High-Performance Hydrovoltaic Devices.

Hydrovoltaic devices (HDs) based on silicon nanowires (SiNWs) have attracted significant attention due to their potential of high output power and good compatibility with Si-based photovoltaic devices for integrated power systems. However, it remains a major challenge to further improve the output performance of SiNW HDs for practical applications. Here, a new strategy to modify the surface of SiNWs with siloxane molecules is proposed to improve the output performance of the SiNW HDs. After modification, both the open-circuit voltage (Voc) and short-circuit current density (Jsc) of n-type SiNW HDs can be improved by approximately 30%, while the output power density can be greatly increased by over 200%. With siloxane modification, Si-OH groups on the surface of typical SiNWs are replaced by Si-O-Si chemical bonds that have a weaker electron-withdrawing capability. More free electrons in n-type SiNWs are liberated from surface bound states and participate in directed flow induced by water evaporation, thereby improving the output performance of HDs. The improved performance is significant for system integration applications as it reduces the number of required devices. Three siloxane-modified SiNW HDs in series are able to drive a 2 V light-emitting diode (LED), whereas four unmodified devices in series are initially needed for the same task. This work provides a simple yet effective strategy for surface modification to improve the output performance of SiNW HDs. Further research into the effect of different surface modifications on the performance of SiNW HDs will greatly promote their performance enhancement and practical applications.

Modulating the density of silicon nanowire arrays for high-performance hydrovoltaic devices.

Hydrovoltaic devices (HDs) based on silicon nanowire (SiNW) arrays have received intensive attention due to their simple preparation, mature processing technology, and high output power. Investigating the impact of structure parameters of SiNWs on the performance of HDs can guide the optimization of the devices, but related research is still not sufficient. This work studies the effect of the SiNW density on the performance of HDs. SiNW arrays with different densities were prepared by controlling the react time of Si wafers in the seed solution (tseed) in metal-assisted chemical etching. Density of SiNW array gradually decreases with the increase oftseed. HDs were fabricated based on SiNW arrays with different densities. The research results indicate that the open-circuit voltage gradually decreases with increasingtseed, while the short-circuit current first increases and then decreases with increasingtseed. Overall, SiNW devices withtseedof 20 s and 60 s have the best output performance. The difference in output performance of HDs based on SiNWs with different densities is attributed to the difference in the gap sizes between SiNWs, specific surface area of SiNWs, and the number of SiNWs in parallel. This work gives the corresponding relationship between the preparation conditions of SiNWs, array density, and output performance of hydrovoltaic devices. Density parameters of SiNW arrays with optimized output performance and corresponding preparation conditions are revealed. The relevant results have important reference value for understanding the mechanism of HDs and designing structural parameters of SiNWs for high-performance hydrovoltaic devices.

Exploring the cuproptosis-related molecular clusters in the peripheral blood of patients with amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a progressive and lethal neurodegenerative disease. Several studies have suggested the involvement of cuproptosis in its pathogenesis. In this research, we intend to explore the cuproptosis-related molecular clusters in ALS and develop a novel cuproptosis-related genes prediction model. METHODS: The peripheral blood gene expression data was downloaded from the Gene Expression Omnibus (GEO) online database. Based on the GSE112681 dataset, we investigated the critical cuproptosis-related genes (CuRGs) and pathological clustering of ALS. The immune microenvironment features of the peripheral blood in ALS patients were also examined using the CIBERSORT algorithm. Cluster-specific hub genes were determined by the WGCNA. The most accurate prediction model was selected by comparing the performance of four machine learning techniques. ROC curves and two independent datasets were applied to validate the prediction accuracy. The available compounds targeting these hub genes were filtered to investigate their efficacy in treating ALS. RESULTS: We successfully determined four critical cuproptosis-related genes and two pathological clusters with various immune profiles and biological characteristics in ALS. Functional analysis showed that genes in Cluster1 were primarily enriched in pathways closely associated with immunity. The Support Vector Machine (SVM) model exhibited the best discrimination properties with a large area under the curve (AUC = 0.862). Five hub prediction genes (BAP1, SMG1, BCLAF1, DHX15, EIF4G2) were selected to establish a nomogram model, suggesting significant risk prediction potential for ALS. The accuracy of this model in predicting ALS incidence was also demonstrated through calibration curves, nomograms, and decision curve analysis. Finally, three drugs targeting BAP1 were determined through drug-gene interactions. CONCLUSION: This study elucidated the complex associations between cuproptosis and ALS and constructed a satisfactory predictive model to explore the pathological characteristics of different clusters in ALS patients.

Corrigendum: Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma.

[This corrects the article DOI: 10.3389/fmed.2022.939776.].

Array density effect on the optical and photoelectric properties of silicon nanowire arrays via Ag-assisted chemical etching.

Ag-assisted chemical etching (AgACE) is a low-cost method to produce silicon nanowires (SiNWs) for photoelectric applications. Structure parameters of SiNWs have great impact on their optical and photoelectric properties, which are worth studying for fabricating high-performance devices. However, array density of SiNWs via AgACE, as an important structural parameter, has not been sufficiently investigated. Here, array density effect on the optical and photoelectric properties of SiNWs is experimentally investigated. SiNW arrays with different densities (silicon occupation ratio of 7%-34.5%) were prepared through controlling the reaction time of silicon wafers in the seed solution (tseed). The SiNW array with atseedof 90 s shows optimum light absorption over 98% in the wavelength range of 300-1000 nm, though all the samples have light absorption over 95% due to the light trapping effect of nanowire array structure. In addition, the SiNW array with atseedof 90 s exhibits the best photoelectric property. SiNW arrays with shortertseedand higher density suffer more surface recombination, harming the photoelectric property. In SiNW arrays with longertseedthan 90 s and lower density, some SiNWs topple down and break, which has an adverse effect on transport and collection of carriers. These results indicate that the array density of SiNWs via AgACE has obvious effect on their photoelectric property. SiNW arrays via AgACE with atseedof 90 s are ideal for photoelectric devices. This work is potential to guide SiNW fabrication for photoelectric applications.

Sitravatinib is a potential EGFR inhibitor and induce a new death phenotype in Glioblastoma.

Glioblastoma (GBM) is a highly lethal neurological tumor that presents significant challenge for clinicians due to its heterogeneity and high mortality rate. Despite extensive research, there is currently no effective drug treatment available for GBM. Research evidence has consistently demonstrated that the epidermal growth factor receptor (EGFR) promotes tumor progression and is associated with poor prognosis in several types of cancer. In glioma, EGFR abnormal amplification is reported in approximately 40% of GBM patients, with overexpression observed in 60% of cases, and deletion or mutation in 24% to 67% of patients. In our study, Sitravatinib, a potential EGFR inhibitor, was identified through molecular docking screening based on protein structure. The targeting of EGFR and the tumor inhibitory effect of Sitravatinib on glioma were verified through cellular and in vivo experiments, respectively. Our study also revealed that Sitravatinib effectively inhibited GBM invasive and induced DNA damage and cellular senescence. Furthermore, we observed a novel cell death phenotype induced by Sitravatinib, which differed from previously reported programmed death patterns such as apoptosis, pyroptosis, ferroptosis, and necrosis.

Strain effect on the field-effect sensing property of Si wires.

Silicon-based field effect transistor (FET) sensors with high sensitivity are emerging as powerful sensors for detecting chemical/biological species. Strain engineering has been demonstrated as an effective means to improve the performance of Si-based devices. However, the strain effect on the field-effect sensing property of silicon materials has not been studied yet. Here, we investigate the strain effect on the field-effect sensing property of silicon wires by taking humidity sensing as an example. The humidity sensitivity of FET sensors based on silicon wires increases with increasing tensile strain but decreases with increasing compressive strain. The sensitivity is very responsive to strain with an enhancement factor of 67 for tensile strain. Theoretical analysis shows that the sensitivity variation under different strains is mainly attributed to the change in adsorption energy between silicon wires and water molecules. This work indicates that strain engineering can be an effective route to modulate the field-effect sensing property of Si wires for constructing highly sensitive Si-based FET sensors.

The CDK inhibitor AT7519 inhibits human glioblastoma cell growth by inducing apoptosis, pyroptosis and cell cycle arrest.

Glioblastoma multiforme (GBM) is the most lethal primary brain tumor with a poor median survival of less than 15 months. However, clinical strategies and effective therapies are limited. Here, we found that the second-generation small molecule multi-CDK inhibitor AT7519 is a potential drug for GBM treatment according to high-throughput screening via the Approved Drug Library and Clinical Compound Library (2718 compounds). We found that AT7519 significantly inhibited the cell viability and proliferation of U87MG, U251, and patient-derived primary GBM cells in a dose-dependent manner. Furthermore, AT7519 also inhibited the phosphorylation of CDK1/2 and arrested the cell cycle at the G1-S and G2-M phases. More importantly, AT7519 induced intrinsic apoptosis and pyroptosis via caspase-3-mediated cleavage of gasdermin E (GSDME). In the glioblastoma intracranial and subcutaneous xenograft assays, tumor volume was significantly reduced after treatment with AT7519. In summary, AT7519 induces cell death through multiple pathways and inhibits glioblastoma growth, indicating that AT7519 is a potential chemical available for GBM treatment.

Ultrasound deep brain stimulation decelerates telomere shortening in Alzheimer's disease and aging mice.

Telomere length is a reliable biomarker for health and longevity prediction in both humans and animals. The common neuromodulation techniques, including deep brain stimulation (DBS) and optogenetics, have excellent spatial resolution and depth penetration but require implementation of electrodes or optical fibers. Therefore, it is important to develop methods for noninvasive modulation of telomere length. Herein, we reported on a new method for decelerating telomere shortening using noninvasive ultrasound deep brain stimulation (UDBS). Firstly, we found that UDBS could activate the telomerase-associated proteins in normal mice. Then, in the Alzheimer's disease mice, UDBS was observed to decelerate telomere shortening of the cortex and myocardial tissue and to effectively improve spatial learning and memory abilities. Similarly, UDBS was found to significantly slow down telomere shortening of the cortex and peripheral blood, and improve motor and cognitive functions in aging mice. Finally, transcriptome analysis revealed that UDBS upregulated the neuroactive ligand-receptor interaction pathway. Overall, the present findings established the critical role of UDBS in delaying telomere shortening and indicated that ultrasound modulation of telomere length may constitute an effective therapeutic strategy for aging and aging-related diseases.

Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma.

Recent studies have found that the protein encoded by the FDX1 gene is involved in mediating Cuproptosis as a regulator of protein lipoylation and related to immune response process of tumors. However, the specific biological function of FDX1 in glioma is currently unclear. To explore the potential function of FDX1, this study explored the correlation between the expression of FDX1 in cancers and survival prognosis by analyzing the public databases of GEPIA and Cbioportal. Immune infiltration was analyzed by the TIMER2.0 database in tumors. The possible biological processes and functions of FDX1-related in glioma were annotated through gene enrichment. Relationship between Cuproptosis and autophagy was explored through gene co-expression studies. Summary and conclusions of this study: (1) FDX1 is highly expressed in gliomas and associated with poor prognosis in low-grade gliomas (LGG). (2) Gene annotation indicates that FDX1 is mainly involved in the tumor protein lipoylation and cell death. (3) FDX1 expression is positively correlated with the infiltration of immune cells. (4) LIPT2 and NNAT, two other genes involved in lipoylation, may be unidentified marker gene for Cuproptosis. And the Cuproptosis genes related to FDX1 were positively correlated with the expression of autophagy marker genes Atg5, Atg12, and BECN-1. This evidence suggests that there may be some interaction between FDX1 mediated Cuproptosis and autophagy. In summary, FDX1 may serve as a potential immunotherapy target and prognostic marker for Glioma.

Rationally designed nanoarray catalysts for boosted photothermal CO2 hydrogenation.

It is of emerging interest to convert CO2 and green H2 into solar fuels with great efficiency through photothermal CO2 hydrogenation. However, designing photothermal catalysts with improved sunlight harvesting ability, intrinsic catalytic activity, and thermal management to prevent heat dissipation still remains rather challenging. Herein, we report a facile structural engineering strategy for preparing efficient nanoarray-based photothermal catalysts with strong light absorption ability, high metal dispersity, and effective thermal management. Optimizing the 120 µm-SiNCs@Co catalyst allowed it to reach a record high Co-based photothermal CO2 conversion rate of 1780 mmol gCo-1 h-1. This study provides insight into the structural engineering of photothermal catalysts for enhanced catalytic performance and lays a foundation for efficient photothermal CO2 catalysis.

APOE interacts with ACE2 inhibiting SARS-CoV-2 cellular entry and inflammation in COVID-19 patients.

Apolipoprotein E (APOE) plays a pivotal role in lipid including cholesterol metabolism. The APOE ε4 (APOE4) allele is a major genetic risk factor for Alzheimer's and cardiovascular diseases. Although APOE has recently been associated with increased susceptibility to infections of several viruses, whether and how APOE and its isoforms affect SARS-CoV-2 infection remains unclear. Here, we show that serum concentrations of APOE correlate inversely with levels of cytokine/chemokine in 73 COVID-19 patients. Utilizing multiple protein interaction assays, we demonstrate that APOE3 and APOE4 interact with the SARS-CoV-2 receptor ACE2; and APOE/ACE2 interactions require zinc metallopeptidase domain of ACE2, a key docking site for SARS-CoV-2 Spike protein. In addition, immuno-imaging assays using confocal, super-resolution, and transmission electron microscopies reveal that both APOE3 and APOE4 reduce ACE2/Spike-mediated viral entry into cells. Interestingly, while having a comparable binding affinity to ACE2, APOE4 inhibits viral entry to a lesser extent compared to APOE3, which is likely due to APOE4's more compact structure and smaller spatial obstacle to compete against Spike binding to ACE2. Furthermore, APOE ε4 carriers clinically correlate with increased SARS-CoV-2 infection and elevated serum inflammatory factors in 142 COVID-19 patients assessed. Our study suggests a regulatory mechanism underlying SARS-CoV-2 infection through APOE interactions with ACE2, which may explain in part increased COVID-19 infection and disease severity in APOE ε4 carriers.

Identification of serum metabolites enhancing inflammatory responses in COVID-19.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is characterized by a strong production of inflammatory cytokines such as TNF and IL-6, which underlie the severity of the disease. However, the molecular mechanisms responsible for such a strong immune response remains unclear. Here, utilizing targeted tandem mass spectrometry to analyze serum metabolome and lipidome in COVID-19 patients at different temporal stages, we identified that 611 metabolites (of 1,039) were significantly altered in COVID-19 patients. Among them, two metabolites, agmatine and putrescine, were prominently elevated in the serum of patients; and 2-quinolinecarboxylate was changed in a biphasic manner, elevated during early COVID-19 infection but levelled off. When tested in mouse embryonic fibroblasts (MEFs) and macrophages, these 3 metabolites were found to activate the NF-κB pathway that plays a pivotal role in governing cytokine production. Importantly, these metabolites were each able to cause strong increase of TNF and IL-6 levels when administered to wildtype mice, but not in the mice lacking NF-κB. Intriguingly, these metabolites have little effects on the activation of interferon regulatory factors (IRFs) for the production of type I interferons (IFNs) for antiviral defenses. These data suggest that circulating metabolites resulting from COVID-19 infection may act as effectors to elicit the peculiar systemic inflammatory responses, exhibiting severely strong proinflammatory cytokine production with limited induction of the interferons. Our study may provide a rationale for development of drugs to alleviate inflammation in COVID-19 patients.

Merbromin is a mixed-type inhibitor of 3-chyomotrypsin like protease of SARS-CoV-2.

3-chyomotrypsin like protease (3CLpro) has been considered as a promising target for developing anti-SARS-CoV-2 drugs. Herein, about 6000 compounds were analyzed by high-throughput screening using enzyme activity model, and Merbromin, an antibacterial agent, was identified as a potent inhibitor of 3CLpro. Merbromin strongly inhibited the proteolytic activity of 3CLpro but not the other three proteases Proteinase K, Trypsin and Papain. Michaelis-Menten kinetic analysis showed that Merbromin was a mixed-type inhibitor of 3CLpro, due to its ability of increasing the KM and decreasing the Kcat of 3CLpro. The binding assays and molecular docking suggested that 3CLpro possessed two binding sites for Merbromin. Consistently, Merbromin showed a weak binding to the other three proteases. Together, these findings demonstrated that Merbromin is a selective inhibitor of 3CLpro and provided a scaffold to design effective inhibitors of SARS-CoV-2.