HIF-1α facilitates glioma proliferation and invasion by activating pyroptosis signaling axis.

BACKGROUND: HIF-1α is thought to be a novel regulator which contributes to carcinogenesis. However, the mechanism underlying the effect of HIF-1α in gliomas remains largely unknown. METHODS: In the research, we demonstrate that HIF-lα mRNA and protein levels are elevated in glioma cells. The colony formation assays, transwell assays, and wound-healing assays showed that overexpression of HIF-1α promoted proliferation and invasion of glioma cells. RESULTS: Overexpression of HIF-lα also increased the expression of inflammatory factors related to pyrolysis (TNF-α, IL-10, and IL-1ß) and protein related to pyrolysis signal pathway (NLRP3, ASC, caspase-1, GSDMD, and GSDME). CONCLUSIONS: Therefore, we speculate that HIF-1α promotes the proliferation and invasion of glial cells by regulating pyrolysis pathway. These results might provide a novel strategy and target for treatment of glioma.

Crucial role of SWL1 in chloroplast biogenesis and development in Arabidopsis thaliana.

KEY MESSAGE: The disruption of the SWL1 gene leads to a significant down regulation of chloroplast and secondary metabolites gene expression in Arabidopsis thaliana. And finally results in a dysfunction of chloroplast and plant growth. Although the development of the chloroplast has been a consistent focus of research, the corresponding regulatory mechanisms remain unidentified. In this study, the CRISPR/Cas9 system was used to mutate the SWL1 gene, resulting in albino cotyledons and variegated true leaf phenotype. Confocal microscopy and western blot of chloroplast protein fractions revealed that SWL1 localized in the chloroplast stroma. Electron microscopy indicated chloroplasts in the cotyledons of swl1 lack well-defined grana and internal membrane structures, and similar structures have been detected in the albino region of variegated true leaves. Transcriptome analysis revealed that down regulation of chloroplast and nuclear gene expression related to chloroplast, including light harvesting complexes, porphyrin, chlorophyll metabolism and carbon metabolism in the swl1 compared to wild-type plant. In addition, proteomic analysis combined with western blot analysis, showed that a significant decrease in chloroplast proteins of swl1. Furthermore, the expression of genes associated with secondary metabolites and growth hormones was also reduced, which may be attributed to SWL1 associated with absorption and fixation of inorganic carbon during chloroplast development. Together, the above findings provide valuable information to elucidate the exact function of SWL1 in chloroplast biogenesis and development.

Exposure to resorcinol bis (diphenyl phosphate) induces colonization of alien microorganisms with potential impacts on the gut microbiota and metabolic disruption in male zebrafish.

Organophosphate esters (OPEs) have been demonstrated to induce various forms of toxicity in aquatic organisms. However, a scarcity of evidence impedes the conclusive determination of whether OPEs manifest sex-dependent toxic effects. Here, we investigated the effects of tris (1-chloro-2-propyl) phosphate (TCPP) and resorcinol bis (diphenyl phosphate) (RDP) on the intestines of both female and male zebrafish. The results indicated that, in comparison to TCPP, RDP induced more pronounced intestinal microstructural damage and oxidative stress, particularly in male zebrafish. 16S rRNA sequencing and metabolomics revealed significant alterations in the species richness and oxidative stress-related metabolites in the intestinal microbiota of zebrafish under exposure to both TCPP and RDP, manifesting gender-specific effects. Based on differential species analysis, we defined invasive species and applied invasion theory to analyze the reasons for changes in the male fish intestinal community. Correlation analysis demonstrated that alien species may have potential effects on metabolism. Overall, this study reveals a pronounced gender-dependent impact on both the intestinal microbiota and metabolic disruptions of zebrafish due to OPEs exposure and offers a novel perspective on the influence of pollutants on intestinal microbial communities and metabolism.

Mechanism of apoptosis induced by the combined action of acrylamide and Elaidic acid through endoplasmic reticulum stress injury.

Thermal processing of food is likely to form acrylamide (AA) and elaidic acid (EA), which are both mainly metabolized by the liver. The two substances are associated with the pathogenesis of liver disease. In the current study, we investigated the toxic effects of the combined action of AA and EA on HSC-T6 cells, and the mechanism of apoptosis exacerbated by the co-exposure. The results showed a synergistic effect of AA and EA, which exacerbated the damage and oxidative stress (OS) in HSC-T6. Meanwhile, the expression of endoplasmic reticulum stress (ERS) proteins, such as GRP78 and CHOP, was increased, the ERS pathway was activated, and Ca2+ in cells was increased, which exacerbated mitochondrial damage, and opened IP3R-Grp75-VDAC1 channel. Both ERS and mitochondrial damage caused the process of cell apoptosis. Inhibition of ERS by 4-phenylbutyric acid (4-PBA) significantly reversed the synergistic effects on mitochondrial damage via ERS, suggesting that AA and EA exacerbated mitochondrial damage through ERS-mediated Ca2+ overload. AA and EA synergistically damaged the function of mitochondria through exacerbating ERS and led to cell apoptosis.

Autophagy-related protein 5 (ATG5) interacts with bone marrow stromal cell antigen 2 (BST2) to stimulate HBV replication through antagonizing the antiviral activity of BST2.

Hepatitis B virus (HBV) infection is a major global health burden with 820 000 deaths per year. In our previous study, we found that the knockdown of autophagy-related protein 5 (ATG5) significantly upregulated the interferon-stimulated genes (ISGs) expression to exert the anti-HCV effect. However, the regulation of ATG5 on HBV replication and its underlying mechanism remains unclear. In this study, we screened the altered expression of type I interferon (IFN-I) pathway genes using RT² Profiler™ PCR array following ATG5 knock-down and we found the bone marrow stromal cell antigen 2 (BST2) expression was significantly increased. We then verified the upregulation of BST2 by ATG5 knockdown using RT-qPCR and found that the knockdown of ATG5 activated the Janus kinase/signal transducer and activator of transcription (JAK-STAT) signaling pathway. ATG5 knockdown or BST2 overexpression decreased Hepatitis B core Antigen (HBcAg) protein, HBV DNA levels in cells and supernatants of HepAD38 and HBV-infected NTCP-HepG2. Knockdown of BST2 abrogated the anti-HBV effect of ATG5 knockdown. Furthermore, we found that ATG5 interacted with BST2, and further formed a ternary complex together with HBV-X (HBx). In conclusion, our finding indicates that ATG5 promotes HBV replication through decreasing BST2 expression and interacting with it directly to antagonize its antiviral function.

Association between amino acids and recent osteoporotic fracture: a matched incident case-control study.

Context: Osteoporotic fracture is a major public health issue globally. Human research on the association between amino acids (AAs) and fracture is still lacking. Objective: To examine the association between AAs and recent osteoporotic fractures. Methods: This age and sex matched incident case-control study identified 44 recent x-ray confirmed fracture cases in the Second Hospital of Jilin University and 88 community-based healthy controls aged 50+ years. Plasma AAs were measured by high performance liquid chromatography coupled with mass spectrometry. After adjusting for covariates (i.e., body mass index, milk intake >1 time/week, falls and physical activity), we conducted conditional logistical regression models to test the association between AAs and fracture. Results: Among cases there were 23 (52.3%) hip fractures and 21 (47.7%) non-hip fractures. Total, essential, and non-essential AAs were significantly lower in cases than in controls. In the multivariable conditional logistic regression models, after adjusting for covariates, each standard deviation increase in the total (odds ratio [OR]: 0.304; 95% confidence interval [CI]: 0.117-0.794), essential (OR: 0.408; 95% CI: 0.181-0.923) and non-essential AAs (OR: 0.290; 95%CI: 0.107-0.782) was negatively associated with recent fracture. These inverse associations were mainly found for hip fracture, rather than non-hip fractures. Among these AAs, lysine, alanine, arginine, glutamine, histidine and piperamide showed the significantly negative associations with fracture. Conclusion: There was a negative relationship between AAs and recent osteoporotic fracture; such relationship appeared to be more obvious for hip fracture.

Range-Intensity-Profile-Guided Gated Light Ranging and Imaging Based on a Convolutional Neural Network.

Three-dimensional (3D) range-gated imaging can obtain high spatial resolution intensity images as well as pixel-wise depth information. Several algorithms have been developed to recover depth from gated images such as the range-intensity correlation algorithm and deep-learning-based algorithm. The traditional range-intensity correlation algorithm requires specific range-intensity profiles, which are hard to generate, while the existing deep-learning-based algorithm requires large number of real-scene training data. In this work, we propose a method of range-intensity-profile-guided gated light ranging and imaging to recover depth from gated images based on a convolutional neural network. In this method, the range-intensity profile (RIP) of a given gated light ranging and imaging system is obtained to generate synthetic training data from Grand Theft Auto V for our range-intensity ratio and semantic network (RIRS-net). The RIRS-net is mainly trained on synthetic data and fine-tuned with RIP data. The network learns both semantic depth cues and range-intensity depth cues in the synthetic data, and learns accurate range-intensity depth cues in the RIP data. In the evaluation experiments on both a real-scene and synthetic test dataset, our method shows a better result compared to other algorithms.

A dual-signal ratiometric electrochemical aptasensor based on Thi/Au/ZIF-8 and catalytic hairpin assembly for ultra-sensitive detection of aflatoxin B1.

A dual-signal ratiometric electrochemical aptasensor has been developed  for AFB1 detection using thionine/Au/zeolitic imidazolate framework-8 (Thi/Au/ZIF-8) nanomaterials and catalytic hairpin assembly (CHA) reaction. Thi/Au/ZIF-8 combined with DNA hairpin 2 (H2) was used as a signal probe. [Fe(CN)6]3-/4- was served as another signal probe, and the IThi/Au/ZIF-8/I[Fe(CN)6]3-/4- ratio was for the first time utilized to quantify AFB1. AFB1-induced CHA was used to expand the ratio of electrical signals. In the presence of AFB1, H2/Thi/Au/ZIF-8 bound to the electrode via CHA, enhanced  the current signal of Thi/Au/ZIF-8. H2 contained the DNA phosphate backbone hindered [Fe(CN)6]3-/4- redox reaction and resulted in a lower [Fe(CN)6]3-/4- current signal. This aptasensor exhibited high specificity for AFB1, a linear range of 0.1 pg mL-1 to 100 ng mL-1, and a detection limit of 0.089 pg mL-1. It demonstrated favorable sensitivity, selectivity, stability, and repeatability. The aptasensor was suitable for detecting AFB1 in peanuts and black tea and holds potential for real sample applications.

Predicting maturity and identifying key factors in organic waste composting using machine learning models.

The measurement of germination index (GI) in composting is a time-consuming and laborious process. This study employed four machine learning (ML) models, namely Random Forest (RF), Artificial Neural Network (ANN), Support Vector Regression (SVR), and Decision Tree (DT), to predict GI based on key composting parameters. The prediction results showed that the coefficient of determination (R2) for RF (>0.9) and ANN (>0.9) was higher than SVR (<0.6) and DT (<0.8), suggesting that RF and ANN displayed superior predictive performance for GI. The SHapley additive exPlanations value result indicated that composting time, temperature, and pH were the important features contributing to GI. Composting time was found to have the most significant impact on GI. Overall, RF and ANN were suggested as effective tools for predicting GI in composting. This study offers the reliable approach of accurately predicting GI in composting processes, thereby enabling intelligent composting practices.

Trends and prescribing patterns of antimigraine medicines in nine major cities in China from 2018 to 2022: a retrospective prescription analysis.

BACKGROUND: The objective of this study was to investigate the trends and prescribing patterns of antimigraine medicines in China. METHODS: The prescription data of outpatients diagnosed with migraine between 2018 and 2022 were extracted from the Hospital Prescription Analysis Cooperative Project of China. The demographic characteristics of migraine patients, prescription trends, and corresponding expenditures on antimigraine medicines were analyzed. We also investigated prescribing patterns of combination therapy and medicine overuse. RESULTS: A total of 32,246 outpatients who were diagnosed with migraine at 103 hospitals were included in this study. There were no significant trend changes in total outpatient visits, migraine prescriptions, or corresponding expenditures during the study period. Of the patients who were prescribed therapeutic medicines, 70.23% received analgesics, and 26.41% received migraine-specific agents. Nonsteroidal anti-inflammatory drugs (NSAIDs; 28.03%), caffeine-containing agents (22.15%), and opioids (16.00%) were the most commonly prescribed analgesics, with corresponding cost proportions of 11.35%, 4.08%, and 19.61%, respectively. Oral triptans (26.12%) were the most commonly prescribed migraine-specific agents and accounted for 62.21% of the total therapeutic expenditures. The proportion of patients receiving analgesic prescriptions increased from 65.25% in 2018 to 75.68% in 2022, and the proportion of patients receiving concomitant triptans decreased from 29.54% in 2018 to 21.55% in 2022 (both P <  0.001). The most frequently prescribed preventive medication classes were calcium channel blockers (CCBs; 51.59%), followed by antidepressants (20.59%) and anticonvulsants (15.82%), which accounted for 21.90%, 34.18%, and 24.15%, respectively, of the total preventive expenditures. Flunarizine (51.41%) was the most commonly prescribed preventive drug. Flupentixol/melitracen (7.53%) was the most commonly prescribed antidepressant. The most commonly prescribed anticonvulsant was topiramate (9.33%), which increased from 6.26% to 12.75% (both P <  0.001). A total of 3.88% of the patients received combined therapy for acute migraine treatment, and 18.63% received combined therapy for prevention. The prescriptions for 69.21% of opioids, 38.53% of caffeine-containing agents, 26.61% of NSAIDs, 13.97% of acetaminophen, and 6.03% of triptans were considered written medicine overuse. CONCLUSIONS: Migraine treatment gradually converges toward evidence-based and guideline-recommended treatment. Attention should be given to opioid prescribing, weak evidence-based antidepressant use, and medication overuse in migraine treatment.

The security of IOT from the perspective of the observability of complex networks.

The Internet of Things (IOT) is based on the computer Internet, using RFID, wireless data communication and other technologies to construct a network covering everything in the world. It contains numerous entities such as sensors, processors, transmitters and actuators, meanwhile the interactions of which are complicated. These characteristics of IOT are consistent with those of the complex network. Motivated by this, this paper comprehends the security issue of IOT from the sight of the observability of complex network and regards the ability of reconstruction as a security threat to IOT network. We try to identify the minimum vertices whose data could reconstruct the whole data of network, in other words, we need to implement additional protective measures on these vertices to enhance the security of IOT network. By analyzing the topology of IOT network, an identification strategy is adopted and the corresponding algorithm is proposed to identify the minimum protection vertices.

A novel MARV glycoprotein-specific antibody with potentials of broad-spectrum neutralization to filovirus.

Marburg virus (MARV) is one of the filovirus species that cause deadly hemorrhagic fever in humans, with mortality rates up to 90%. Neutralizing antibodies represent ideal candidates to prevent or treat virus disease. However, no antibody has been approved for MARV treatment to date. In this study, we identified a novel human antibody named AF-03 that targeted MARV glycoprotein (GP). AF-03 possessed a high binding affinity to MARV GP and showed neutralizing and protective activities against the pseudotyped MARV in vitro and in vivo. Epitope identification, including molecular docking and experiment-based analysis of mutated species, revealed that AF-03 recognized the Niemann-Pick C1 (NPC1) binding domain within GP1. Interestingly, we found the neutralizing activity of AF-03 to pseudotyped Ebola viruses (EBOV, SUDV, and BDBV) harboring cleaved GP instead of full-length GP. Furthermore, NPC2-fused AF-03 exhibited neutralizing activity to several filovirus species and EBOV mutants via binding to CI-MPR. In conclusion, this work demonstrates that AF-03 represents a promising therapeutic cargo for filovirus-caused disease.

A Global Seawater Density Distribution Model Using a Convolutional Neural Network.

Seawater density is an important physical property in oceanography that affects the accuracy of calculations such as gravity fields and tidal potentials and the calibration of acoustic and optical oceanographic sensors. In related studies, constant density values are frequently used, which can introduce significant errors. Therefore, this study employs a basic convolutional neural network model to construct a comprehensive model showing the seawater density distribution across the globe. The model takes into account depth, latitude, longitude, and month as inputs. Numerous real seawater datasets were used to train the model, and it has been shown that the model has an absolute mean error and root mean square error of less than 1 kg/m3 in 99% of the test set samples. The model effectively demonstrates the influence of input parameters on the distribution of seawater density. In this paper, we present a newly developed global model for distributing seawater density which is both comprehensive and accurate, surpassing previous models. The utilization of the model presented in this paper for estimating seawater density can minimize errors in theoretical ocean models and serve as a foundation for designing and analyzing ocean exploration systems.

Genome variation and LTR-RT analyses of an ancient peach landrace reveal mechanism of blood-flesh fruit color formation and fruit maturity date advancement.

Peach (Prunus persica) landrace has typical regional characteristics, strong environmental adaptability, and contains many valuable genes that provide the foundation for breeding excellent varieties. Therefore, it is necessary to assemble the genomes of specific landraces to facilitate the localization and utilization of these genes. Here, we de novo assembled a high-quality genome from an ancient blood-fleshed Chinese landrace Tianjin ShuiMi (TJSM) that originated from the China North Plain. The assembled genome size was 243.5 Mb with a contig N50 of 23.7 Mb and a scaffold N50 of 28.6 Mb. Compared with the reported peach genomes, our assembled TJSM genome had the largest number of specific structural variants (SVs) and long terminal repeat-retrotransposons (LTR-RTs). Among the LTR-RTs with the potential to regulate their host genes, we identified a 6688 bp LTR-RT (named it blood TE) in the promoter of NAC transcription factor-encoding PpBL, a gene regulating peach blood-flesh formation. The blood TE was not only co-separated with the blood-flesh phenotype but also associated with fruit maturity date advancement and different intensities of blood-flesh color formation. Our findings provide new insights into the mechanism underlying the development of the blood-flesh color and determination of fruit maturity date and highlight the potential of the TJSM genome to mine more variations related to agronomic traits in peach fruit.

Superconductivity of cubic MB6 (M = Na, K, Rb, Cs).

Previous studies have shown that NaB6, KB6, and RbB6 adopting Pm3̄m are superconductors with a relatively high Tc under ambient conditions. In this paper, we conducted systematic structural and related properties research on CsB6 through a genetic evolution algorithm and total energy calculations based on density functional theory between 0 and 20 GPa. Our results reveal a cubic Pm3̄m CsB6, which is dynamically stable under the pressures we studied. We systematically calculated the formation enthalpies, electronic properties, and superconducting properties of Pm3̄m MB6 (M = Na, K, Rb, Cs). They all exhibit metallic features, and boron has high contributions to band structures, density of states, and electron-phonon coupling (EPC). The calculated results about the Helmholtz free energy difference of Pm3̄m CsB6 at 0, 10, and 20 GPa indicate that it is stable upon chemical decomposition (decomposition to simple substances Cs and B) from 0 to 400 K. The phonon density of states indicates that boron atoms occupy the high frequency area. The EPC results show that Pm3̄m CsB6 is a superconductor with Tc = 11.7 K at 0 GPa, close to NaB6 (13.1 K), KB6 (11.7 K), and RbB6 (11.3 K) at 0 GPa in our work, which indicates that boron atoms play an essential role in superconductivity: vibrations of B6 regular octagons lead to the high Tc of Pm3̄m MB6. Our work about Pm3̄m hexaborides provides a supplementary study on the borides of the group IA elements (without Fr and Li) and has an important guiding significance for the experimental synthesis of CsB6.

Unraveling EGFR-TKI resistance in lung cancer with high PD-L1 or TMB in EGFR-sensitive mutations.

BACKGROUND: Although EGFR-TKI resistance mechanisms in non-small cell lung cancer (NSCLC) have been extensively studied, certain patient subgroups remain with unclear mechanisms. This retrospective study analysed mutation data of NSCLC patients with EGFR-sensitive mutations and high programmed death-ligand 1 (PD-L1) expression or high TMB to identify primary resistance mechanisms. METHODS: Hybrid capture-based next-generation sequencing (NGS) was used to analyse mutations in 639 genes in tumor tissues and blood samples from 339 NSCLC patients. PD-L1 immunohistochemical staining was also performed on the same cell blocks. Molecular and pathway profiles were compared among patient subgroups. RESULTS: TMB was significantly higher in lung cancer patients with EGFR-sensitive mutations and high PD-L1 expression. Compared with the high-expression PD-L1 or high TMB and low-expression or TMB groups, the top 10 genes exhibited differences in both gene types and mutation rates. Pathway analysis revealed a significant mutations of the PI3K signaling pathway in the EGFR-sensitive mutation group with high PD-L1 expression (38% versus 12%, p < 0.001) and high TMB group (31% versus 13%, p < 0.05). Notably, PIK3CA and PTEN mutations emerged as the most important differentially mutated genes within the PI3K signaling pathway. CONCLUSIONS: Our findings reveal that the presence of PI3K signaling pathway mutations may be responsible for inducing primary resistance to EGFR-TKIs in NSCLC patients with EGFR-sensitive mutations along with high PD-L1 expression or high TMB. This finding is of great significance in guiding subsequent precision treatments in NSCLC.

Ultraflexible Monolithic Three-Dimensional Static Random Access Memory.

Flexible static random access memory (SRAM) plays an important role in flexible electronics and systems. However, achieving SRAM with a small footprint, high flexibility, and high thermal stability has always been a big challenge. In this work, an ultraflexible six-transistor SRAM with high integration density is realized based on a monolithic three-dimensional (M3D) design. In this design, vertical stacked n-type indium gallium zinc oxide thin film transistors and p-type carbon nanotube transistors share common gate and drain electrodes, respectively, saving interlayer vias used in traditional M3D designs. This compact architecture reduces the footprint of the SRAM cell from a six-transistor to a four-transistor area, saving 33% of the area, and significantly enables the SRAM to have the highest flexibility among the reported ones, withstanding a harsh deforming process (6000 cycles of bending at a radius of 500 µm) without performance degradation. Moreover, this design facilitates the thermal stability of the SRAM under high temperature (333 K). It also exhibits great static and dynamic performance, with the highest normalized hold noise margin of 73.6%, a maximum gain of 151.2, and a minimum static power consumption of 3.15 µW in hold operation among the reported flexible SRAMs. This demonstration provides possibilities for SRAMs to be used in advanced wearable system applications.

Understanding resistant-starch formation during drying high-amylose maize kernels.

Interests in using high-amylose maize (HAM) flour and starch for low glycemic index foods continue to grow. The objective of this work was to understand resistant-starch formation during drying the HAM kernels. Freshly harvested HAM kernels with 28.2 % initial moisture were subjected to sun drying (~30 °C) or hot-air drying at 50 °C, 70 °C, 90 °C, or 110 °C. The enzymatic digestibility of HAM flour decreased from 63.6 % to 41.1 % as the drying temperature increased from 30 °C to 110 °C. The swelling power, solubility, and overall viscosity of HAM flours milled from kernels dried at 110 °C decreased, whereas the peak and conclusion gelatinization temperatures, enthalpy change, and relative crystallinity increased compared to those of flours from kernels dried at 30 °C, 50 °C, 70 °C, and 90 °C. Light microscopic and scanning electron microscopic images showed that starch granule aggregation in HAM flour increased with increasing drying-temperatures. The aggregates remained after 16 h enzymatic hydrolysis of cooked HAM flours. These results suggested that the increase of enzymatic resistance of HAM flour resulted from the formation of high temperature-resistant ordered structures in starch granules and the starch aggregates less accessible to enzymatic hydrolysis.