A tree-based corpus annotated with Cyber-Syndrome, symptoms, and acupoints.

Prolonged and over-excessive interaction with cyberspace poses a threat to people's health and leads to the occurrence of Cyber-Syndrome, which covers not only physiological but also psychological disorders. This paper aims to create a tree-shaped gold-standard corpus that annotates the Cyber-Syndrome, clinical manifestations, and acupoints that can alleviate their symptoms or signs, designating this corpus as CS-A. In the CS-A corpus, this paper defines six entities and relations subject to annotation. There are 448 texts to annotate in total manually. After three rounds of updating the annotation guidelines, the inter-annotator agreement (IAA) improved significantly, resulting in a higher IAA score of 86.05%. The purpose of constructing CS-A corpus is to increase the popularity of Cyber-Syndrome and draw attention to its subtle impact on people's health. Meanwhile, annotated corpus promotes the development of natural language processing technology. Some model experiments can be implemented based on this corpus, such as optimizing and improving models for discontinuous entity recognition, nested entity recognition, etc. The CS-A corpus has been uploaded to figshare.

Innovative computational tools provide new insights into the polyploid wheat genome.

Bread wheat (Triticum aestivum) is an important crop and serves as a significant source of protein and calories for humans, worldwide. Nevertheless, its large and allopolyploid genome poses constraints on genetic improvement. The complex reticulate evolutionary history and the intricacy of genomic resources make the deciphering of the functional genome considerably more challenging. Recently, we have developed a comprehensive list of versatile computational tools with the integration of statistical models for dissecting the polyploid wheat genome. Here, we summarize the methodological innovations and applications of these tools and databases. A series of step-by-step examples illustrates how these tools can be utilized for dissecting wheat germplasm resources and unveiling functional genes associated with important agronomic traits. Furthermore, we outline future perspectives on new advanced tools and databases, taking into consideration the unique features of bread wheat, to accelerate genomic-assisted wheat breeding.

Preparation of 3D flexible SERS substrates by mixing gold nanorods in hydrogels for the detection of malachite green and crystal violet.

A simple and cost-effective fabrication method of gold nanorods (AuNRs) nanoparticles hybridized with polyvinyl alcohol hydrogel (AuNR/PVA) for SERS substrate is described. The AuNR/PVA achieves the control of inter-particle nanogap by modulating the density of gold nanorods, and inter-particle nanogap by the spatial deformation of the hydrogel, and the reduction of the gap between the AuNRs deposited on hydrogel makes the SERS enhancement. In addition, the AuNR/PVA substrate maintains high SERS activity after more than 100 cycles of bending and storage in air for 30 days, and the substrate possesses high sensitivity and high reproducibility. Combining a flexible and transparent surface-enhanced Raman spectroscopy (SERS) substrate for in situ detection with a small portable Raman can be applied to scenarios such as environmental detection and hazardous materials detection. The substrate showed excellent SERS activity against malachite green (MG) and crystal violet (CV) with limits of detection of 1.18 × 10-13 M and 7.17 × 10-12 M, respectively. The usability of the proposed SERS substrate was demonstrated by detecting the above contaminants in aquatic water. This work not only utilizes a cost-effective method for mass production but also provides a reliable and convenient platform for the preparation of other noble metal flexible substrates.

Glucagon-like peptide-1 analogs: Miracle drugs are blooming?

Glucagon-like peptide-1 (GLP-1), secreted by L cells in the small intestine, assumes a central role in managing type 2 diabetes mellitus (T2DM) and obesity. Its influence on insulin secretion and gastric emptying positions it as a therapeutic linchpin. However, the limited applicability of native GLP-1 stems from its short half-life, primarily due to glomerular filtration and the inactivating effect of dipeptidyl peptidase-IV (DPP-IV). To address this, various structural modification strategies have been developed to extend GLP-1's half-life. Despite the commendable efficacy displayed by current GLP-1 receptor agonists, inherent limitations persist. A paradigm shift emerges with the advent of unimolecular multi-agonists, such as the recently introduced tirzepatide, wherein GLP-1 is ingeniously combined with other gastrointestinal hormones. This novel approach has captured the spotlight within the diabetes and obesity research community. This review summarizes the physiological functions of GLP-1, systematically explores diverse structural modifications, delves into the realm of unimolecular multi-agonists, and provides a nuanced portrayal of the developmental prospects that lie ahead for GLP-1 analogs.

Prognostic factors in surgically treated tongue squamous cell carcinoma in stage T1-2N0-1M0: A retrospective analysis.

PURPOSE: The study aimed to retrospectively identify the prognostic factors of surgically treated primary tongue squamous cell carcinoma (TSCC) cases and assess the benefits of surgical neck lymph node dissection (LND) in early-stage cancer. METHODS: Patients with primary TSCC with pT1-2N0-1M0 stage without distant metastasis who were treated with surgery during 2014-2016 at Xiangya Hospital, Central South University were included. Univariate and multivariate Cox models were constructed to explore prognostic factors of overall survival (OS), disease-free survival (DFS), and local recurrence-free survival (LRFS). Sub-group analysis was used to assess the effect of adjuvant therapy and the prognostic value of LND for the early-stage patients. RESULTS: In total, 440 patients met the inclusion criteria. During the follow-up period, the 5-year OS, DFS, were 84.4% and 70.0%, respectively. Univariate analysis showed that TNM stage, lymphovascular invasion (LVI), and/or perineural invasion (PNI), pathological differentiation, etc. were significant predictors of OS and DFS. Multivariate analysis showed that TNM stage and the degree of pathological differentiation were independent prognostic factors for all outcomes. Besides, the number of cervical LND could independently predict both DFS and LRFS while LVI/PNI were associated with DFS. And high-quality neck LND (≥30) significantly improved DFS and LRFS for patients of pT1cN0M0 or stage I as compared to those without LND. CONCLUSIONS: TNM stage and pathological differentiation were crucial prognostic factors for postoperative patients with TSCC. Notably, high-quality cervical LND was beneficial for the improvement of DFS and LRFS for patients of pT1cN0M0 or stage I.

Machine Learning Models for Predicting Early Neurological Deterioration and Risk Classification of Acute Ischemic Stroke.

This study aimed to create machine learning models for predicting early neurological deterioration and risk classification in acute ischemic stroke (AIS) before intravenous thrombolysis (IVT). The study included 704 AIS patients categorized into END and non-END groups. The least absolute shrinkage and selection operator (LASSO) regression was employed to select the best predictors from clinical indicators, leading to the creation of Model 1. Univariate and multivariate logistic regression analyses identified independent predictive factors for END from inflammatory cell ratios. These factors were combined with clinical indicators, forming Model 2. Receiver operating characteristic (ROC) curves assessed the models' predictive performance. Key variables for Model 1 included the NIHSS score, systolic blood pressure, and lymphocyte percentage. Neutrophil-to-Lymphocyte ratio, Platelet-to-Neutrophil ratio, and Platelet-to-Lymphocyte ratio independently predicted END. Model 1 exhibited moderate predictive ability (AUC 0.721 in training, AUC 0.635 in test). Model 2, which integrated clinical indicators and inflammatory cell ratios, demonstrated strong performance in both training (AUC 0.862) and test (AUC 0.816). Machine learning models, combining clinical indicators and inflammatory cell ratios before IVT, accurately predict END and associated risk in AIS.

[Establishment and evaluation of a predictive model for early neurological deterioration after intravenous thrombolysis in acute ischemic stroke based on machine learning].

OBJECTIVE: To establish a machine learning model to predict the risk of early neurological deterioration (END) based on the clinical and laboratory data of patients with acute ischemic stroke (AIS) before intravenous thrombolysis. METHODS: The clinical data of AIS patients who received intravenous thrombolytic with recombinant tissue plasminogen activator (rt-PA) at the Stroke Center of the First Hospital of Qinhuangdao City from January 2019 to July 2022 were retrospectively analyzed. Patients were divided into END group and non-END group according to whether END appeared after intravenous thrombolytic. Clinical data of patients at admission were collected, including demographic characteristics, clinical evaluation, comorbidification, drug use history, laboratory tests, etc. Univariate and multivariate Logistic regression analysis were performed to screen out the independent predictors of the END of AIS patients after intravenous thrombolytic. The study subjects were randomly divided into a training set and a test set in a 7 : 3 ratio. Four machine learning prediction models, including Logistic regression (LR), K-nearest neighbor (KNN), support vector machine (SVM) and random forest (RF), were established based on independent predictors. The receiver operator characteristic curve (ROC curve) was used to evaluate the predictive ability of each model in END. RESULTS: A total of 704 patients were enrolled, of whom 99 were identified as END and 605 as non-END. Univariate and multivariate Logistic regression analysis was used to screen out the National Institutes of Health stroke scale [NIHSS, odds ratio (OR) = 1.049, 95% confidence interval (95%CI) was 1.015-1.082, P = 0.004], systolic blood pressure (OR = 1.013, 95%CI was 1.004-1.022, P = 0.004), lymphocyte percentage (LYM%, OR = 0.903, 95%CI was 0.853-0.953, P < 0.001), platelet to lymphocyte ratio (PLR, OR = 1.007, 95%CI was 1.002-1.014, P = 0.013) were the independent predictors of END in AIS patients after intravenous thrombolysis. The area under the curve (AUC) of LR, KNN, SVM, and RF machine learning models in the test dataset were 0.789 (95%CI was 0.675-0.902), 0.797 (95%CI was 0.685-0.910), 0.851 (95%CI was 0.751-0.952) and 0.809 (95%CI was 0.699-0.919), respectively. The RF model had the highest sensitivity (95.7%). The accuracy (0.736), specificity (72.0%) and AUC of SVM model were the highest, and its overall prediction ability was better than the other three models. CONCLUSIONS: Machine learning models have a potential role in early predicting the risk of END after intravenous thrombolysis in AIS patients, and can provide help in clinical decision-making for intravenous thrombolysis.

Preparation of SERS base membrane with cellulose compound dopamine and determination of hypochlorite.

Flexible silver substrates were made by in situ reduction of silver nanoparticles in bacterial cellulose membranes using the unique advantage of dopamine. Subsequently, we modified the substrate with 4-mercaptophenol (4-MP), a molecule capable of specifically recognizing ClO-, and its corresponding SERS signal changes with the concentration of hypochlorite, thus allowing the quantitative detection of ClO- content. The method showed a negative linear correlation (R2 = 0.9567) with the SERS intensity at 1077 cm-1 over the concentration range 0.5-100 µM, and the detection limit was 0.15 µM. The RSD of the SERS intensity at 1077 cm-1 under five batches was 4.2%, which proved the good reproducibility of P-BCM-Ag NP-MP. Finally, the P-BCM-Ag NPs were used for the detection of hypochlorite in cell contents, artificial urine, and clinical serum samples, utilizing spike experiments in all three environments. The recoveries were in the range 90-110% indicating the accuracy of the method for the detection of hypochlorite and validating the promising application of this assay for practical detection in intricate biological samples.

Research Progress of SERS Sensors Based on Hydrogen Peroxide and Related Substances.

Hydrogen peroxide (H2O2) has an important role in living organisms, and its detection is of great importance in medical, chemical, and food safety applications. This review provides a comparison of different types of Surface-enhanced Raman scattering (SERS) sensors for H2O2 and related substances with respect to their detection limits, which are of interest due to high sensitivity compared to conventional sensors. According to the latest research report, this review focuses on the sensing mechanism of different sensors and summarizes the linear range, detection limits, and cellular applications of new SERS sensors, and discusses the limitations in vivo and future prospects of SERS technology for the detection of H2O2.

Hyperbranched Polymer Dots with Strong Absorption and High Fluorescence Quantum Yield for In Vivo NIR-II Imaging.

In order to improve the fluorescence quantum yield (QY) of NIR-II-emitting nanoparticles, D-A-D fluorophores are typically linked to intramolecular rotatable units to reduce aggregation-induced quenching. However, incorporating such units often leads to a twisted molecular backbone, which affects the coupling within the D-A-D unit and, as a result, lowers the absorption. Here, we overcome this limitation by cross-linking the NIR-II fluorophores to form a 2D polymer network, which simultaneously achieves a high QY by well-controlled fluorophore separation and strong absorption by restricting intramolecular distortion. Using the strategy, we developed polymer dots with the highest NIR-II single-particle brightness among reported D-A-D-based nanoparticles and applied them for imaging of hindlimb vasculatures and tumors as well as fluorescence-guided tumor resection. The high brightness of the polymer dots offered exceptional image quality and excellent surgical results, showing a promising performance for these applications.

Design of off-axis aspheric four-mirror non-axial mechanical zoom optical system with large relative aperture.

A large relative aperture is essential to improve the spatial resolution of zoom systems. To overcome the limitations of the existing off-axis reflective mechanical zoom system with a low zoom rate and a small relative aperture, this paper proposes a non-axis movement method for increasing the degrees of freedom. On the basis of nodal aberration theory, passive eccentricity is changed into active eccentricity to achieve wave aberration balance in the multiple structures of the zoom imaging system. An off-axis aspherical four-mirror non-axial mechanical zoom optical system is designed and fabricated. The prototype has been successfully processed and assembled with the help of computer-aided alignment technology. The prototype's F-number is 4 and zoom ratio is 4.57:1. Experimental results verify the feasibility of the proposed method.

Thermosensitive SUMOylation of TaHsfA1 defines a dynamic ON/OFF molecular switch for the heat stress response in wheat.

Dissecting genetic components in crop plants associated with heat stress (HS) sensing and adaptation will facilitate the design of modern crop varieties with improved thermotolerance. However, the molecular mechanisms underlying the ON/OFF switch controlling HS responses (HSRs) in wheat (Triticum aestivum) remain largely unknown. In this study, we focused on the molecular action of TaHsfA1, a class A heat shock transcription factor, in sensing dynamically changing HS signals and regulating HSRs. We show that the TaHsfA1 protein is modified by small ubiquitin-related modifier (SUMO) and that this modification is essential for the full transcriptional activation activity of TaHsfA1 in triggering downstream gene expression. During sustained heat exposure, the SUMOylation of TaHsfA1 is suppressed, which partially reduces TaHsfA1 protein activity, thereby reducing the intensity of downstream HSRs. In addition, we demonstrate that TaHsfA1 interacts with the histone acetyltransferase TaHAG1 in a thermosensitive manner. Together, our findings emphasize the importance of TaHsfA1 in thermotolerance in wheat. In addition, they define a highly dynamic SUMOylation-dependent "ON/OFF" molecular switch that senses temperature signals and contributes to thermotolerance in crops.

The RNA-binding protein LRPPRC promotes resistance to CDK4/6 inhibition in lung cancer.

Kinase inhibitors against Cyclin Dependent Kinase 4 and 6 (CDK4/6i) are promising cancer therapeutic drugs. However, their effects are limited by primary or acquired resistance in virtually all tumor types. Here, we demonstrate that Leucine Rich Pentatricopeptide Repeat Containing (LRPPRC) controls CDK4/6i response in lung cancer by forming a feedback loop with CDK6. LRPPRC binds to CDK6-mRNA, increasing the stability and expression of CDK6. CDK6 and its downstream E2F Transcription Factor 1 (E2F1), bind to the LRPPRC promoter and elevate LRPPRC transcription. The activation of the LRPPRC-CDK6 loop facilitates cell cycle G1/S transition, oxidative phosphorylation, and cancer stem cell generation. Gossypol acetate (GAA), a gynecological medicine that has been repurposed as a degrader of LRPPRC, enhances the CDK4/6i sensitivity in vitro and in vivo. Our study reveals a mechanism responsible for CDK4/6i resistance and provides an enlightening approach to investigating the combinations of CDK4/6 and LRPPRC inhibitors in cancer therapy.

Optimized Charge Storage in Aza-Based Covalent Organic Frameworks by Tuning Electrolyte Proton Activity.

Proton activity in electrolytes plays a crucial role in deciding the electrochemical performance of aqueous batteries. On the one hand, it can influence the capacity and rate performance of host materials because of the high redox activity of protons. On the other hand, it can also cause a severe hydrogen evolution reaction (HER) when the protons are aggregated near the electrode/electrolyte interface. The HER dramatically limits the potential window and the cycling stability of the electrodes. Therefore, it is critical to clarify the impact of electrolyte proton activity on the battery macro-electrochemical performance. In this work, using an aza-based covalent organic framework (COF) as a representative host material, we studied the effect of electrolyte proton activity on the potential window, storage capacity, rate performance, and cycle stability in various electrolytes. A tradeoff relationship between proton redox reactions and the HER in the COF host is revealed by utilizing various in situ and ex situ characterizations. Moreover, the origin of proton activity in near-neutral electrolytes is discussed in detail and is confirmed to be related to the hydrated water molecules in the first solvation shell. A detailed analysis of the charge storage process in the COFs is presented. These understandings can be of importance for utilizing the electrolyte proton activity to build high-energy aqueous batteries.

A novel "on-off" SERS nanoprobe based on sulfonated cellulose nanofiber-Ag composite for selective determination of NADH in human serum.

A novel S-CNF-based nanocomposite was created using sulfonated cellulose nanofiber (S-CNF) to enable the detection of NADH in serum by surface-enhanced Raman spectroscopy (SERS). The numerous hydroxyl and sulfonic acid groups on the S-CNF surface absorbed silver ions and converted them to silver seeds, which formed the load fulcrum. After adding a reducing agent, silver nanoparticles (Ag NPs) were firmly adhered to the S-CNF surface to form stable 1D "hot spots." The S-CNF-Ag NP substrate demonstrated outstanding SERS performance, including good uniformity with an RSD of 6.88% and an enhancement factor (EF) of 1.23 × 107. Owing to the anionic charge repulsion effect, the S-CNF-Ag NP substrate still maintains remarkable dispersion stability after 12 months of preservation. Finally, S-CNF-Ag NPs' surface was modified with 4-mercaptophenol (4-MP), a special redox Raman signal molecule, to detect reduced nicotinamide adenine dinucleotide (NADH). The results showed that the detection limit (LOD) of NADH was 0.75 µM; a good linear relationship (R2 = 0.993) was established in the concentration range 10-6 - 10-2 M. The SERS nanoprobe enabled rapid detection of NADH in human serum without any complicated sample pretreatment and provides a new potential to detect biomarkers.

Mitochondrial Protease Targeting Chimeras for Mitochondrial Matrix Protein Degradation.

Targeted protein degradation (TPD) is an emerging technique for protein regulation. Currently, all TPD developed in eukaryotic cells relies on either ubiquitin-proteasome or lysosomal systems, thus are powerless against target proteins in membrane organelles lacking proteasomes and lysosomes, such as mitochondria. Here, we developed a mitochondrial protease targeting chimera (MtPTAC) to address this issue. MtPTAC is a bifunctional small molecule that can bind to mitochondrial caseinolytic protease P (ClpP) at one end and target protein at the other. Mechanistically, MtPTAC activates the hydrolase activity of ClpP while simultaneously bringing target proteins into proximity with ClpP. Taking mitochondrial RNA polymerase (POLRMT) as a model protein, we have demonstrated the powerful proteolytic ability and antitumor application prospects of MtPTAC, both in vivo and in vitro. This is the first modularly designed TPD that can specifically hydrolyze target proteins inside mitochondria.

A novel method for the component identification of human blood products: Mass spectrometric analysis of human fibrinogen digested after SDS-PAGE in-gel digestion.

Human fibrinogen, as a blood product of special origin, is relatively simple to prepare and purify. Therefore, completely isolating and removing the relevant impurity proteins is difficult. Further, which impurity protein components are present is not clear. In this study, human fibrinogen products from seven enterprises were collected from the market, and the presence of impurity proteins was confirmed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Subsequently, the major 12 impurity proteins were identified and screened by in-gel enzymolysis mass spectrometry, and 7 major impurity proteins with different peptide coverage were identified by enzyme-linked immunosorbent assay, in agreement with the mass spectrometry results. The seven major impurity proteins included fibronectin, plasminogen, F-XIII, F-VIII, complement factor H, cystatin-A, and α-2-macroglobulin. The final test results were in the range of undetectable to 50.94 µg/mL, with correspondingly low levels of impurity proteins between different companies and a manageable risk. Moreover, we found that these impurity proteins existed in the form of polymers, which might also be an important cause of adverse reactions. This study established a protein identification technique applicable to fibrinogen products, which provided new ideas for studying the protein composition of blood products. In addition, it provided a new means of testing for companies to monitor the flow of proteomic fractions and improve the purification yield and product quality. It laid the foundation for reducing the risk of clinical adverse reactions.

Reducing brassinosteroid signalling enhances grain yield in semi-dwarf wheat.

Modern green revolution varieties of wheat (Triticum aestivum L.) confer semi-dwarf and lodging-resistant plant architecture owing to the Reduced height-B1b (Rht-B1b) and Rht-D1b alleles1. However, both Rht-B1b and Rht-D1b are gain-of-function mutant alleles encoding gibberellin signalling repressors that stably repress plant growth and negatively affect nitrogen-use efficiency and grain filling2-5. Therefore, the green revolution varieties of wheat harbouring Rht-B1b or Rht-D1b usually produce smaller grain and require higher nitrogen fertilizer inputs to maintain their grain yields. Here we describe a strategy to design semi-dwarf wheat varieties without the need for Rht-B1b or Rht-D1b alleles. We discovered that absence of Rht-B1 and ZnF-B (encoding a RING-type E3 ligase) through a natural deletion of a haploblock of about 500 kilobases shaped semi-dwarf plants with more compact plant architecture and substantially improved grain yield (up to 15.2%) in field trials. Further genetic analysis confirmed that the deletion of ZnF-B induced the semi-dwarf trait in the absence of the Rht-B1b and Rht-D1b alleles through attenuating brassinosteroid (BR) perception. ZnF acts as a BR signalling activator to facilitate proteasomal destruction of the BR signalling repressor BRI1 kinase inhibitor 1 (TaBKI1), and loss of ZnF stabilizes TaBKI1 to block BR signalling transduction. Our findings not only identified a pivotal BR signalling modulator but also provided a creative strategy to design high-yield semi-dwarf wheat varieties by manipulating the BR signal pathway to sustain wheat production.

RuCu Nanosheets with Ultrahigh Nanozyme Activity for Chemodynamic Therapy.

Nanoenzymes have been widely explored for chemodynamic therapy (CDT) in cancer treatment. However, poor catalytic efficiency of nanoenzymes, especially in the tumor microenvironment with insufficient H2 O2 and mild acidity, limits the effect of CDT. Herein, a new ultrathin RuCu nanosheet (NS) based nanoenzyme which has a large specific surface area and abundant channels and defects is developed. The RuCu NSs show superb catalytic efficiency for the oxidation of peroxidase substrate H2 O2 at a wide range of pH and their catalytic efficiency (kcat /Km = 177.2 m-1  s-1 ) is about 14.9 times higher than that of the single-atom catalyst FeN3 P. Besides being an efficient nanozyme as peroxidase, the RuCu NSs possess other two enzyme activities, not only disproportionating superoxide anion to produce H2 O2 but also consuming glutathione to keep a high concentration of H2 O2 in the tumor microenvironment for Fenton reaction. With these advantages, the RuCu NSs exhibit good performance to kill cancer cells and inhibit tumor growth in mice, demonstrating a promising potential as new CDT reagent.

Transcriptomic analysis of the effect of deferoxamine exposure on the growth, photosynthetic activity and iron transfer of Microcystis aeruginosa.

Deferoxamine (DFB) is a trihydroxamic acid siderophore that chelates with iron (Fe) to form iron-siderophore complexes. The existence of siderophores in nature changes the form of iron and affects the absorption and utilization of iron by organisms. However, the relationship between siderophores and the growth of Cyanobacteria is largely unknown. In this study, the cellular and transcriptomic responses to the addition of DFB were investigated. A high concentration of DFB (12 mg/L) significantly inhibited the growth of Cyanobacteria cells, reduced photosynthetic activity, and induced the production of peroxidase, with the highest inhibition rate of algal growth of 74.82%. These indexes were also affected for the low (3 mg/L) and medium concentration (6 mg/L) groups, but this difference is closely related to the growth stage of Cyanobacteria cells. This may be due to competition between the cell-associated iron-binding part/system and the extracellular Fe (Ⅲ)-DFB ligand. Transcriptome results showed that most of the genes involved in iron uptake and transport were down-regulated, and only the fur gene encoding the iron uptake regulator protein was significantly up-regulated. Most genes related to photosynthesis, glycolysis, and fatty acid metabolism were also down-regulated, while the obvious up-regulation of a few genes may be a complex regulation in response to the down-regulation of most genes. These findings will provide important insights into the effects of siderophores on iron bioavailability in algae.