Association Between Preoperative Sleep Disturbance and Postoperative Delirium in Elderly: A Retrospective Cohort Study.

Purpose: Postoperative sleep disturbance, characterized by diminished postoperative sleep quality, is a risk factor for postoperative delirium (POD); however, the association between pre-existing sleep disturbance and POD remains unclear. This study aimed to evaluate the association between preoperative sleep disturbance and POD in elderly patients after non-cardiac surgery. Patients and methods: This retrospective cohort study was conducted at a single center and enrolled 489 elderly patients who underwent surgery between May 1, 2020, and March 31, 2021. Patients were divided into the sleep disorder (SD) and non-sleep disorder (NSD) groups according to the occurrence of one or more symptoms of insomnia within one month or sleep- Numerical Rating Scale (NRS)≥6 before surgery. The primary outcome was the incidence of POD. Propensity score matching analysis was performed between the two groups. Multiple logistic regression analysis was performed to identify the risk factors for POD. Results: In both the unmatched cohort (16.0% vs 6.7%, P=0.003) and the matched cohort (17.0% vs 6.2%, P=0.023), the incidence of POD was higher in the SD group than in the NSD group. In addition, the postoperative sleep quality and the VAS score at postoperative 24 h were significantly lower in the SD group than in the NSD group. Multivariate logistic regression analysis indicated that age (Odds Ratio, 1.13 [95% CI: 1.04-1.23], P=0.003) and preoperative sleep disturbance (Odds Ratio, 3.03 [95% CI: 1.09-9.52], P=0.034) were independent risk factors for the development of POD. Conclusion: The incidence of POD was higher in patients with pre-existing sleep disturbance than those without it. Whether improving sleep quality for preoperative sleep disturbance may help prevent POD remains to be determined.

[Tibiotalocalcaneal arthrodesis for end-stage ankle and hindfoot arthropathy: Short- and mid-term clinical outcomes].

OBJECTIVE: To analyze the clinical data of patients with end-stage ankle and hindfoot arthropathy who underwent tibiotalocalcaneal (TTC) arthrodesis by the same surgeon, explore the short- and mid-term clinical results, complications and functional improvement, and discuss the clinical prognosis and precautions of TTC arthrodesis. METHODS: Retrospective analysis was made on the clinical data of 40 patients who underwent TTC arthrodesis by the same surgeon from March 2011 to December 2020. In this study, 23 males and 17 females were included, with an average age of (49.1±16.0) years. All the patients underwent unilateral surgery. The clinical characteristics, imaging manifestations, main diagnosis and specific surgical techniques of the patients were recorded. The clinical outcomes were evaluated by comparison of the American Orthopaedic Foot and Ankle Society (AOFAS) ankle-hindfoot score and visual analogue scale (VAS) between pre-operation and at the last follow-up. The fusion healing time, symptom improvement (significant improvement, certain improvement, no improvement or deterioration) and postoperative complications were also recorded. RESULTS: The median follow-up time was 38.0 (26.3, 58.8) months. The preoperative VAS score was 6.0 (4.0, 7.0), and the AOFAS score was 33.0 (25.3, 47.3). At the last follow-up, the median VAS score was 0 (0, 3.0), and the AOFAS score was 80.0 (59.0, 84.0). All the significantly improved compared with their preoperative corresponding values (P < 0.05). There was no wound necrosis or infection in the patients. One patient suffered from subtalar joint nonunion, which was syphilitic Charcot arthropathy. The median bony healing time of other patients was 15.0 (12.0, 20.0) weeks. Among the included patients, there were 25 cases with significant improvement in symptom compared with that preoperative, 8 cases with certain improvement, 4 cases with no improvement, and 3 cases with worse symptoms than that before operation. CONCLUSION: TTC arthrodesis is a reliable method for the treatment of the end-stage ankle and hindfoot arthropathy. The function of most patients was improved postoperatively, with little impact on daily life. The causes of poor prognosis included toe stiffness, stress concentration in adjacent knee joints, nonunion and pain of unknown causes.

Human telomere length is chromosome end-specific and conserved across individuals.

Short telomeres cause age-related disease and long telomeres predispose to cancer; however, the mechanisms regulating telomere length are unclear. We developed a nanopore-based method, Telomere Profiling, to determine telomere length at nearly single nucleotide resolution. Mapping telomere reads to chromosome ends showed chromosome end-specific length distributions that could differ by more than six kilobases. Telomere lengths in 147 individuals showed certain chromosome ends were consistently longer or shorter. The same rank order was found in newborn cord blood, suggesting that telomere length is determined at birth and chromosome end-specific telomere length differences are maintained as telomeres shorten with age. Telomere Profiling makes precision investigation of telomere length widely accessible for laboratory, clinical, and drug discovery efforts and will allow deeper insights into telomere biology.

Interaction between HTR2A rs3125 and negative life events in suicide attempts among patients with major depressive disorder: a cross-sectional study.

BACKGROUND: Both genetic and environmental factors play crucial roles in the development of major depressive disorder (MDD) and suicide attempts (SA). However, the interaction between both items remains unknown. This study aims to explore the interactions between the genetic variants of the serotonin 2 A receptor (HTR2A) and the nitric oxide synthase 1 (NOS1) and environmental factors in patients who experience MDD and SA. METHODS: A total of 334 patients with MDD and a history of SA (MDD-SA) were recruited alongside 518 patients with MDD with no history of SA (MDD-NSA), and 716 healthy controls (HC). The demographic data and clinical characteristics were collected. Sequenom mass spectrometry was used to detect eight tag-single nucleotide polymorphisms (tagSNPs) in HTR2A (rs1328683, rs17068986, and rs3125) and NOS1 (rs1123425, rs2682826, rs3741476, rs527590, and rs7959232). Generalized multifactor dimensionality reduction (GMDR) was used to analyze the gene-environment interactions. RESULTS: Four tagSNPs (rs17068986, rs3125, rs527590, and rs7959232) exhibited significant differences between the three groups. However, these differences were not significant between the MDD-SA and MDD-NSA groups after Bonferroni correction. A logistic regression analysis revealed that negative life events (OR = 1.495, 95%CI: 1.071-2.087, P = 0.018), self-guilt (OR = 2.263, 95%CI: 1.515-3.379, P < 0.001), and negative cognition (OR = 2.252, 95%CI: 1.264-4.013, P = 0.006) were all independently associated with SA in patients with MDD. Furthermore, GMDR analysis indicated a significant interaction between HTR2A rs3125 and negative life events. Negative life events in conjunction with the HTR2A rs3125 CG + GG genotype were associated with a higher SA risk in patients with MDD when compared to the absence of negative life events in conjunction with the CC genotype (OR = 2.547, 95% CI: 1.264-5.131, P = 0.009). CONCLUSION: Several risk factors and a potential interaction between HTR2A rs3125 and negative life events were identified in patients with SA and MDD. The observed interaction likely modulates the risk of MDD and SA, shedding light on the pathogenesis of SA in patients with MDD.

Blockade of the deubiquitinating enzyme USP48 degrades oncogenic HMGA2 and inhibits colorectal cancer invasion and metastasis.

HMGA2, a pivotal transcription factor, functions as a versatile regulator implicated in the progression of diverse aggressive malignancies. In this study, mass spectrometry was employed to identify ubiquitin-specific proteases that potentially interact with HMGA2, and USP48 was identified as a deubiquitinating enzyme of HMGA2. The enforced expression of USP48 significantly increased HMGA2 protein levels by inhibiting its degradation, while the deprivation of USP48 promoted HMGA2 degradation, thereby suppressing tumor invasion and metastasis. We discovered that USP48 undergoes SUMOylation at lysine 258, which enhances its binding affinity to HMGA2. Through subsequent phenotypic screening of small molecules, we identified DUB-IN-2 as a remarkably potent pharmacological inhibitor of USP48. Interestingly, the small-molecule inhibitor targeting USP48 induces destabilization of HMGA2. Clinically, upregulation of USP48 or HMGA2 in cancerous tissues is indicative of poor prognosis for patients with colorectal cancer (CRC). Collectively, our study not only elucidates the regulatory mechanism of DUBs involved in HMGA2 stability and validates USP48 as a potential therapeutic target for CRC, but also identifies DUB-IN-2 as a potent inhibitor of USP48 and a promising candidate for CRC treatment.

Evaluation of sweat-based biomarkers using wearable biosensors for monitoring stress and fatigue: a systematic review.

Objectives. This systematic review aims to report the evaluation of wearable biosensors for the real-time measurement of stress and fatigue using sweat biomarkers. Methods. A thorough search of the literature was carried out in databases such as PubMed, Web of Science and IEEE. A three-step approach for selecting research articles was developed and implemented. Results. Based on a systematic search, a total of 17 articles were included in this review. Lactate, cortisol, glucose and electrolytes were identified as sweat biomarkers. Sweat-based biomarkers are frequently monitored in real time using potentiometric and amperometric biosensors. Wearable biosensors such as an epidermal patch or a sweatband have been widely validated in scientific literature. Conclusions. Sweat is an important biofluid for monitoring general health, including stress and fatigue. It is becoming increasingly common to use biosensors that can measure a wide range of sweat biomarkers to detect fatigue during high-intensity work. Even though wearable biosensors have been validated for monitoring various sweat biomarkers, such biomarkers can only be used to assess stress and fatigue indirectly. In general, this study may serve as a driving force for academics and practitioners to broaden the use of wearable biosensors for the real-time assessment of stress and fatigue.

In vivo EPID-based daily treatment error identification for volumetric-modulated arc therapy in head and neck cancers with a hierarchical convolutional neural network: a feasibility study.

We proposed a deep learning approach to classify various error types in daily VMAT treatment of head and neck cancer patients based on EPID dosimetry, which could provide additional information to support clinical decisions for adaptive planning. 146 arcs from 42 head and neck patients were analyzed. Anatomical changes and setup errors were simulated in 17,820 EPID images of 99 arcs obtained from 30 patients using in-house software for model training, validation, and testing. Subsequently, 141 clinical EPID images from 47 arcs belonging to the remaining 12 patients were utilized for clinical testing. The hierarchical convolutional neural network (HCNN) model was trained to classify error types and magnitudes using EPID dose difference maps. Gamma analysis with 3%/2 mm (dose difference/distance to agreement) criteria was also performed. The F1 score, a combination of precision and recall, was utilized to evaluate the performance of the HCNN model and gamma analysis. The adaptive fractioned doses were calculated to verify the HCNN classification results. For error type identification, the overall F1 score of the HCNN model was 0.99 and 0.91 for primary type and subtype identification, respectively. For error magnitude identification, the overall F1 score in the simulation dataset was 0.96 and 0.70 for the HCNN model and gamma analysis, respectively; while the overall F1 score in the clinical dataset was 0.79 and 0.20 for the HCNN model and gamma analysis, respectively. The HCNN model-based EPID dosimetry can identify changes in patient transmission doses and distinguish the treatment error category, which could potentially provide information for head and neck cancer treatment adaption.

Genome assembly in the telomere-to-telomere era.

Genome sequences largely determine the biology and encode the history of an organism, and de novo assembly - the process of reconstructing the genome sequence of an organism from sequencing reads - has been a central problem in bioinformatics for four decades. Until recently, genomes were typically assembled into fragments of a few megabases at best, but now technological advances in long-read sequencing enable the near-complete assembly of each chromosome - also known as telomere-to-telomere assembly - for many organisms. Here, we review recent progress on assembly algorithms and protocols, with a focus on how to derive near-telomere-to-telomere assemblies. We also discuss the additional developments that will be required to resolve remaining assembly gaps and to assemble non-diploid genomes.

3D Printable Modular Soft Elastomers from Physically Cross-linked Homogeneous Associative Polymers.

Three-dimensional (3D) printing of elastomers enables the fabrication of many technologically important structures and devices. However, there remains a critical need for the development of reprocessable, solvent-free, soft elastomers that can be printed without the need for post-treatment. Herein, we report modular soft elastomers suitable for direct ink writing (DIW) printing by physically cross-linking associative polymers with a high fraction of reversible bonds. We designed and synthesized linear-associative-linear (LAL) triblock copolymers; the middle block is an associative polymer carrying amide groups that form double hydrogen bonding, and the end blocks aggregate to hard glassy domains that effectively act as physical cross-links. The amide groups do not aggregate to nanoscale clusters and only slow down polymer dynamics without changing the shape of the linear viscoelastic spectra; this enables molecular control over energy dissipation by varying the fraction of the associative groups. Increasing the volume fraction of the end linear blocks increases the network stiffness by more than 100 times without significantly compromising the extensibility. We created elastomers with Young's moduli ranging from 8 kPa to 8 MPa while maintaining the tensile breaking strain around 150%. Using a high-temperature DIW printing platform, we transformed our elastomers to complex, highly deformable 3D structures without involving any solvent or post-print processing. Our elastomers represent the softest melt reprocessable materials for DIW printing. The developed LAL polymers synergize emerging homogeneous associative polymers with a high fraction of reversible bonds and classical block copolymer self-assembly to form a dual-cross-linked network, providing a versatile platform for the modular design and development of soft melt reprocessable elastomeric materials for practical applications.

Evaluating and improving the representation of bacterial contents in long-read metagenome assemblies.

BACKGROUND: In the metagenomic assembly of a microbial community, abundant species are often thought to assemble well given their deeper sequencing coverage. This conjuncture is rarely tested or evaluated in practice. We often do not know how many abundant species are missing and do not have an approach to recover them. RESULTS: Here, we propose k-mer based and 16S RNA based methods to measure the completeness of metagenome assembly. We show that even with PacBio high-fidelity (HiFi) reads, abundant species are often not assembled, as high strain diversity may lead to fragmented contigs. We develop a novel reference-free algorithm to recover abundant metagenome-assembled genomes (MAGs) by identifying circular assembly subgraphs. Complemented with a reference-free genome binning heuristics based on dimension reduction, the proposed method rescues many abundant species that would be missing with existing methods and produces competitive results compared to those state-of-the-art binners in terms of total number of near-complete genome bins. CONCLUSIONS: Our work emphasizes the importance of metagenome completeness, which has often been overlooked. Our algorithm generates more circular MAGs and moves a step closer to the complete representation of microbial communities.

A comprehensive study to estimate income and price elasticities of household electricity consumption using Auto-metrics.

This study focuses on understanding family electricity consumption behaviors in response to income and price changes from 1994 to 2022 across 12 prominent European countries. We employ a unique econometric approach, Auto-selection Models, to analyze the nuances of energy demand elasticity. Our methodology includes the use of saturation techniques, which are highly effective in identifying anomalies and discontinuities in the data, ensuring the reliability of our results. The Auto-metrics method streamlines the model selection process and enhances the accuracy of elasticity predictions. We use Error Correction Models (ECMs) for each country to examine the long-term equilibrium relationships among key variables such as energy consumption, household income, electricity prices, and weather patterns, taking into account any observed anomalies and significant structural changes. The findings reveal varying levels of income and price elasticity across the countries, reflecting their unique economic and climatic conditions. The study's results hold significant implications for policymaking. By recognizing and adapting to the varied characteristics of electricity demand elasticity, energy policies can be more accurately tailored at both the national and European Union levels.

Analysis of the limited M. tuberculosis accessory genome reveals potential pitfalls of pan-genome analysis approaches.

Pan-genome analysis is a fundamental tool in the study of bacterial genome evolution. Benchmarking the accuracy of pan-genome analysis methods is challenging, because it can be significantly influenced by both the methodology used to compare genomes, as well as differences in the accuracy and representativeness of the genomes analyzed. In this work, we curated a collection of 151 Mycobacterium tuberculosis (Mtb) isolates to evaluate sources of variability in pan-genome analysis. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. We characterized the effect of the panqc adjustment on both pan-genome analysis of Mtb and E. coli genomes, and highlight how different levels of genomic diversity are prone to unique biases. Overall, this study illustrates the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.

A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma.

Background: Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an indicator for predicting the prognosis and response to immunotherapy in lung adenocarcinoma (LUAD). Methods: We downloaded the tumor mutation profiles and RNA-seq expression database of LUAD from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were extracted based on the cumulative number of mutations. Cox regression analyses were used to identify the prognostic lncRNA signature, and the prognostic value of the five selected lncRNAs was validated by using survival analysis and the receiver operating characteristic (ROC) curve. We used qPCR to validate the expression of five selected lncRNAs between human lung epithelial and human lung adenocarcinoma cell lines. The ImmuCellAI, immunophenoscore (IPS) scores and Tumor Immune Dysfunction and Exclusion (TIDE) analyses were used to predict the response to immunotherapy for this mutation related lncRNA signature. Results: A total of 162 lncRNAs were detected among the differentially expressed lncRNAs between the Tumor mutational burden (TMB)-high group and the TMB-low group. Then, five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as tumor mutation-related candidates for constructing the prognostic prediction model. Kaplan‒Meier curves showed that the overall survival of the low-risk group was significantly better than that of the high-risk group, and the results of the GSE50081 set were consistent. The expression levels of PD1, PD-L1 and CTLA4 in the low-risk group were higher than those in the high-risk group. The IPS scores and TIDE scores of patients in the low-risk group were significantly higher than those in the high-risk group. Conclusion: Our findings demonstrated that the five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as candidates for constructing the tumor mutation-related model which may serve as an indicator of tumor mutation levels and have important implications for predicting the response to immunotherapy in LUAD.

Sirtuin 3 Mediated by Spinal cMyc-Enhancer of Zeste Homology 2 Pathway Plays an Important Role in Human Immunodeficiency Virus-Related Neuropathic Pain Model.

BACKGROUND: Clinical data demonstrate that chronic use of opioid analgesics increases neuropathic pain in people living with human immunodeficiency virus (HIV). Therefore, it is important to elucidate the molecular mechanisms of HIV-related chronic pain. In this study, we investigated the role of the transcription factor cMyc, epigenetic writer enhancer of zeste homology 2 (EZH2), and sirtuin 3 (Sirt3) pathway in HIV glycoprotein gp120 with morphine (gp120M)-induced neuropathic pain in rats. METHODS: Neuropathic pain was induced by intrathecal administration of recombinant gp120 with morphine. Mechanical withdrawal threshold was measured using von Frey filaments, and thermal latency using the hotplate test. Spinal expression of cMyc, EZH2, and Sirt3 were measured using Western blots. Antinociceptive effects of intrathecal administration of antisense oligodeoxynucleotide against cMyc, a selective inhibitor of EZH2, or recombinant Sirt3 were tested. RESULTS: In the spinal dorsal horn, gp120M upregulated expression of cMyc (ratio of gp120M versus control, 1.68 ± 0.08 vs 1.00 ± 0.14, P = .0132) and EZH2 (ratio of gp120M versus control, 1.76 ± 0.05 vs 1.00 ± 0.16, P = .006), and downregulated Sirt3 (ratio of control versus gp120M, 1.00 ± 0.13 vs 0.43 ± 0.10, P = .0069) compared to control. Treatment with intrathecal antisense oligodeoxynucleotide against cMyc, GSK126 (EZH2 selective inhibitor), or recombinant Sirt3 reduced mechanical allodynia and thermal hyperalgesia in this gp120M pain model. Knockdown of cMyc reduced spinal EZH2 expression in gp120M treated rats. Chromatin immunoprecipitation (ChIP) assay showed that enrichment of cMyc binding to the ezh2 gene promoter region was increased in the gp120M-treated rat spinal dorsal horn, and that intrathecal administration of antisense ODN against cMyc (AS-cMyc) reversed the increased enrichment of cMyc. Enrichment of trimethylation of histone 3 on lysine residue 27 (H3K27me3; an epigenetic mark associated with the downregulation of gene expression) binding to the sirt3 gene promoter region was upregulated in the gp120M-treated rat spinal dorsal horn; that intrathecal GSK126 reversed the increased enrichment of H3K27me3 in the sirt3 gene promoter. Luciferase reporter assay demonstrated that cMyc mediated ezh2 gene transcription at the ezh2 gene promoter region, and that H3K27me3 silenced sirt3 gene transcription at the gene promoter region. CONCLUSION: These results demonstrated that spinal Sirt3 decrease in gp120M-induced neuropathic pain was mediated by cMyc-EZH2/H3K27me3 activity in an epigenetic manner. This study provided new insight into the mechanisms of neuropathic pain in HIV patients with chronic opioids.

FishSNP: a high quality cross-species SNP database of fishes.

The progress of aquaculture heavily depends on the efficient utilization of diverse genetic resources to enhance production efficiency and maximize profitability. Single nucleotide polymorphisms (SNPs) have been widely used in the study of aquaculture genomics, genetics, and breeding research since they are the most prevalent molecular markers on the genome. Currently, a large number of SNP markers from cultured fish species are scattered in individual studies, making querying complicated and data reuse problematic. We compiled relevant SNP data from literature and public databases to create a fish SNP database, FishSNP ( http://bioinfo.ihb.ac.cn/fishsnp ), and also used a unified analysis pipeline to process raw data that the author of the literature did not perform SNP calling on to obtain SNPs with high reliability. This database presently contains 45,690,243 (45 million) nonredundant SNP data for 13 fish species, with 30,288,958 (30 million) of those being high-quality SNPs. The main function of FishSNP is to search, browse, annotate and download SNPs, which provide researchers various and comprehensive associated information.

Suppression of A-to-I RNA-editing enzyme ADAR1 sensitizes hepatocellular carcinoma cells to oxidative stress through regulating Keap1/Nrf2 pathway.

BACKGROUND: A-to-I RNA editing is an abundant post-transcriptional modification event in hepatocellular carcinoma (HCC). Evidence suggests that adenosine deaminases acting on RNA 1 (ADAR1) correlates to oxidative stress that is a crucial factor of HCC pathogenesis. The present study investigated the effect of ADAR1 on survival and oxidative stress of HCC, and underlying mechanisms. METHODS: ADAR1 expression was measured in fifty HCC and normal tissues via real-time quantitative PCR, and immunohistochemistry. For stable knockdown or overexpression of ADAR1, adeno-associated virus vectors carrying sh-ADAR1 or ADAR1 overexpression were transfected into HepG2 and SMMC-7721 cells. Transfected cells were exposed to oxidative stress agonist tBHP or sorafenib Bay 43-9006. Cell proliferation, apoptosis, and oxidative stress were measured, and tumor xenograft experiment was implemented. RESULTS: ADAR1 was up-regulated in HCC and correlated to unfavorable clinical outcomes. ADAR1 deficiency attenuated proliferation of HCC cells and tumor growth and enhanced apoptosis. Moreover, its loss facilitated intracellular ROS accumulation, and elevated Keap1 and lowered Nrf2 expression. Intracellular GSH content and SOD activity were decreased and MDA content was increased in the absence of ADAR1. The opposite results were observed when ADAR1 was overexpressed. The effects of tBHP and Bay 43-9006 on survival, apoptosis, intracellular ROS accumulation, and Keap1/Nrf2 pathway were further exacerbated by simultaneous inhibition of ADAR1. CONCLUSIONS: The current study unveils that ADAR1 is required for survival and oxidative stress of HCC cells, and targeting ADAR1 may sensitize HCC cells to oxidative stress via modulating Keap1/Nrf2 pathway.

Investigation of Flame Structures of Double-Base Propellant and Modified Double-Base Propellant Containing Nitramine Using OH-PLIF and Kinetic Simulation.

The combustion behavior of various propellant samples, including double-base propellants, pressed nitramine powders, and modified double-base propellants containing nitramine, was examined using OH-PLIF technology. The combustion process took place within a combustion chamber, and images capturing the flame at the moment of stable combustion were selected for further analysis. The distribution and production rate of OH radicals in both the double-base propellant and the nitramine-modified double-base propellant were simulated using Chemkin-17.0 software. The outcomes from both the experimental and simulation studies revealed that the concentration of OH radicals increased with a higher content of NG in the double-base propellant. In the modified double-base propellant containing RDX, the OH radical concentration decreased as the RDX content increased, with these tendencies of change aligning closely with the simulation results.

First Evidence of the Bioaccumulation and Trophic Transfer of Tire Additives and Their Transformation Products in an Estuarine Food Web.

The discovery of the significant lethal impacts of the tire additive transformation product N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6PPD-Q) on coho salmon has garnered global attention. However, the bioaccumulation and trophic transfer of tire additives and their transformation products (TATPs) within food webs remain obscure. This study first characterized the levels and compositions of 15 TATPs in the Pearl River Estuary, estimated their bioaccumulation and trophic transfer potential in 21 estuarine species, and identified priority contaminants. Our observations indicated that TATPs were prevalent in the estuarine environment. Eight, six, seven, and 10 TATPs were first quantified in the shrimp, sea cucumber, snail, and fish samples, with total mean levels of 45, 56, 64, and 67 ng/g (wet weight), respectively. N,N'-Diphenyl-p-phenylenediamine (DPPD) and N,N'-bis(2-methylphenyl)-1,4-benzenediamine (DTPD) exhibited high bioaccumulation. Significant biodilution was only identified for benzothiazole, while DPPD and DTPD displayed biomagnification trends based on Monte Carlo simulations. The mechanisms of bioaccumulation and trophodynamics of TATPs could be explained by their chemical hydrophobicity, molecular mass, and metabolic rates. Based on a multicriteria scoring technique, DPPD, DTPD, and 6PPD-Q were characterized as priority contaminants. This work emphasizes the importance of biomonitoring, particularly for specific hydrophobic tire additives.

Re-investigation of in vitro activity of acetohydroxyacid synthase I holoenzyme from Escherichia coli.

Acetohydroxyacid synthase (AHAS) is one of the key enzymes of the biosynthesis of branched-chain amino acids, it is also an effective target for the screening of herbicides and antibiotics. In this study we present a method for preparing Escherichia coli AHAS I holoenzyme (EcAHAS I) with exceptional stability, which provides a solid ground for us to re-investigate the in vitro catalytic properties of the protein. The results show EcAHAS I synthesized in this way exhibits similar function to Bacillus subtilis acetolactate synthase in its catalysis with pyruvate and 2-ketobutyrate (2-KB) as dual-substrate, producing four 2-hydroxy-3-ketoacids including (S)-2-acetolactate, (S)-2-aceto-2-hydroxybutyrate, (S)-2-propionyllactate, and (S)-2-propionyl-2-hydroxybutyrate. Quantification of the reaction indicates that the two substrates almost totally consume, and compound (S)-2-aceto-2- hydroxybutyrate forms in the highest yield among the four major products. Moreover, the protein also condenses two molecules of 2-KB to furnish (S)-2-propionyl-2-hydroxybutyrate. Further exploration manifests that EcAHAS I ligates pyruvate/2-KB and nitrosobenzene to generate two arylhydroxamic acids N-hydroxy-N-phenylacetamide and N-hydroxy-N-phenyl- propionamide. These findings enhance our comprehension of the catalytic characteristics of EcAHAS I. Furthermore, the application of this enzyme as a catalyst in construction of C-N bonds displays promising potential.

A Siamese ResNeXt network for predicting carotid intimal thickness of patients with T2DM from fundus images.

Objective: To develop and validate an artificial intelligence diagnostic model based on fundus images for predicting Carotid Intima-Media Thickness (CIMT) in individuals with Type 2 Diabetes Mellitus (T2DM). Methods: In total, 1236 patients with T2DM who had both retinal fundus images and CIMT ultrasound records within a single hospital stay were enrolled. Data were divided into normal and thickened groups and sent to eight deep learning models: convolutional neural networks of the eight models were all based on ResNet or ResNeXt. Their encoder and decoder modes are different, including the standard mode, the Parallel learning mode, and the Siamese mode. Except for the six unimodal networks, two multimodal networks based on ResNeXt under the Parallel learning mode or the Siamese mode were embedded with ages. Performance of eight models were compared via the confusion matrix, precision, recall, specificity, F1 value, and ROC curve, and recall was regarded as the main indicator. Besides, Grad-CAM was used to visualize the decisions made by Siamese ResNeXt network, which is the best performance. Results: Performance of various models demonstrated the following points: 1) the RexNeXt showed a notable improvement over the ResNet; 2) the structural Siamese networks, which extracted features parallelly and independently, exhibited slight performance enhancements compared to the traditional networks. Notably, the Siamese networks resulted in significant improvements; 3) the performance of classification declined if the age factor was embedded in the network. Taken together, the Siamese ResNeXt unimodal model performed best for its superior efficacy and robustness. This model achieved a recall rate of 88.0% and an AUC value of 90.88% in the validation subset. Additionally, heatmaps calculated by the Grad-CAM algorithm presented concentrated and orderly mappings around the optic disc vascular area in normal CIMT groups and dispersed, irregular patterns in thickened CIMT groups. Conclusion: We provided a Siamese ResNeXt neural network for predicting the carotid intimal thickness of patients with T2DM from fundus images and confirmed the correlation between fundus microvascular lesions and CIMT.