Study on the interaction protein of transcription factor Smad3 based on TurboID proximity labeling technology.

TurboID is a highly efficient biotin-labelling enzyme, which can be used to explore a number of new intercalating proteins due to the very transient binding and catalytic functions of many proteins. TGF-ß/Smad3 signaling pathway is involved in many diseases, especially in diabetic nephropathy and inflammation. In this paper, a stably cell line transfected with Smad3 were constructed by using lentiviral infection. To further investigate the function of TGF-ß/Smad3, the protein labeling experiment was conducted to find the interacting protein with Smad3 gene. Label-free mass spectrometry analysis was performed to obtain 491 interacting proteins, and the interacting protein hnRNPM was selected for IP and immunofluorescence verification, and it was verified that the Smad3 gene had a certain promoting effect on the expression of hnRNPM gene, and then had an inhibitory effect on IL-6. It lays a foundation for further study of the function of Smad3 gene and its involved regulatory network.

Impacts of spatial symmetries on stimulated Brillouin scatterings in nanoscale silicon waveguides: a theoretical and numerical study considering material anisotropies.

Fully considering the mechanical and photoelastic anisotropies of monocrystalline silicon, the impacts of spatial symmetries on the stimulated Brillouin scatterings (SBSs) in nanoscale suspended silicon waveguides are studied theoretically and numerically based on group theory. First, starting from an assumption that the principal material coordinate system can be arbitrarily orientated in a waveguide with fixed geometry, the silicon waveguides are systematically classified into a number of point groups according to their spatial symmetry features. Thereafter, the symmetry characteristics of physical fields and SBS opto-mechanical coupling characteristics in the silicon waveguides belonging to different point groups are further examined, and the major new findings can be summarized as follows: The SBS opto-mechanical couplings in several kinds of silicon waveguides with certain nontrivial symmetry features exhibit relatively predictable behaviors in that the opto-mechanical coupling coefficients can be deterministically vanishing or nonvanishing under very few constraints, which can thus serve as general symmetry selection rules for SBSs in suspended silicon waveguides. The results obtained in the present study could be a useful theoretical reference for the design of novel SBS-active silicon photonic devices.

Metabolic-Related Gene Prognostic Index for Predicting Prognosis, Immunotherapy Response, and Candidate Drugs in Ovarian Cancer.

Ovarian cancer (OC) is a highly heterogeneous disease, with patients at different tumor staging having different survival times. Metabolic reprogramming is one of the key hallmarks of cancer; however, the significance of metabolism-related genes in the prognosis and therapy outcomes of OC is unclear. In this study, we used weighted gene coexpression network analysis and differential expression analysis to screen for metabolism-related genes associated with tumor staging. We constructed the metabolism-related gene prognostic index (MRGPI), which demonstrated a stable prognostic value across multiple clinical trial end points and multiple validation cohorts. The MRGPI population had its distinct molecular features, mutational characteristics, and immune phenotypes. In addition, we investigated the response to immunotherapy in MRGPI subgroups and found that patients with low MRGPI were prone to benefit from anti-PD-1 checkpoint blockade therapy and exhibited a delayed treatment effect. Meanwhile, we identified four candidate therapeutic drugs (ABT-737, crizotinib, panobinostat, and regorafenib) for patients with high MRGPI, and we evaluated the pharmacokinetics and safety of the candidate drugs. In summary, the MRGPI was a robust clinical feature that could predict patient prognosis, immunotherapy response, and candidate drugs, facilitating clinical decision making and therapeutic strategy of OC.

Association of socioeconomic status and poststroke cognitive function: A systematic review and meta-analysis.

BACKGROUND: Stroke survivors are at high risk of coping with cognitive problems after stroke. In recent decades, the relationship between socioeconomic status (SES) and health-related outcomes has been a topic of considerable interest. Learning more about the potential impact of SES on poststroke cognitive dysfunction is of great importance. OBJECTIVE: The purpose of this systematic review and meta-analysis was to summarize the association between SES and poststroke cognitive function by quantifying the effect sizes of the existing studies. METHOD: We searched studies from PubMed, Ovid, Embase, Cochrane, Scopus, and PsychINFO up to January 30th 2024 and the references of relevant reviews. Studies reporting the risk of poststroke cognitive dysfunction as assessed by categorized SES indicators were included. The Newcastle-Ottawa scale and the Agency for Healthcare Research and Quality were used to evaluate the study quality. Meta-analyses using fixed-effect models or random-effect models based on study heterogeneity were performed to estimate the influence of SES on cognitive function after stroke, followed by subgroup analyses stratified by study characteristics. RESULTS: Thirty-four studies were eligible for this systematic review and meta-analysis. Of which, 19 studies reported poststroke cognitive impairment (PSCI) as the outcome, 13 reported poststroke dementia (PSD), one reported both PSCI and PSD, and one reported vascular cognitive impairment no dementia. The findings showed that individuals with lower SES levels had a higher risk of combined poststroke cognitive dysfunction (odds ratio (OR) = 1.91, 95% confidence interval (CI) = 1.59-2.29), PSCI (OR = 2.09, 95% CI = 1.57-2.78), and PSD (OR = 1.95, 95% CI = 1.48-2.57). Subgroup analyses stratified by SES indicators demonstrated the protective effects of education and occupation against the diagnoses of combined poststroke cognitive dysfunction, PSCI, and PSD. CONCLUSIONS: Stroke survivors belonging to a low SES are at high risk of poststroke cognitive dysfunction. Our findings add evidence for public health strategies to reduce the risk of poststroke cognitive dysfunction by reducing SES inequalities.

Puerarin inhibits NHE1 activity by interfering with the p38 pathway and attenuates mitochondrial damage induced by myocardial calcium overload in heart failure rats.

Previous studies have shown that puerarin plays a key role in protecting humans and animals from cardiovascular diseases. The exact mechanism of the therapeutic effect of puerarin on various cardiovascular diseases (protective effect on cardiomyocytes) is still unclear. In the present study, we identify the role of puerarin in an animal model of experimental heart failure (HF) and explore its underlying mechanisms. The HF rat model is induced by intraperitoneal injection of adriamycin (ADR), and puerarin is administered intragastrically at low, medium, and high concentrations. We demonstrate that puerarin significantly improves myocardial fibrosis and inflammatory infiltration and, as a result, improves cardiac function in ADR-induced HF rats. Mechanistically, we find for the first time that puerarin inhibits overactivated Na +/H + exchange isoform 1 (NHE1) in HF, which may improve HF by decreasing Na + and Ca 2+ ion concentrations and attenuating mitochondrial damage caused by calcium overload; on the other hand, puerarin inhibits the activation of the p38 pathway in HF, reduces the expressions of TGF-ß and proinflammatory cytokines, and suppresses myocardial fibrosis. In conclusion, our results suggest that Puerarin is an effective drug against HF and may play a protective role in the myocardium by inhibiting the activation of p38 and its downstream NHE1.

Citronellal improves endothelial dysfunction by affecting the stability of the GCH1 protein.

Endothelial dysfunction (ED) serves as the pathological basis for various cardiovascular diseases. Guanosine triphosphate cyclopyrrolone 1 (GCH1) emerges as a pivotal protein in sustaining nitric oxide (NO) production within endothelial cells, yet it undergoes degradation under oxidative stress, contributing to endothelial cell dysfunction. Citronellal (CT), a monoterpenoid, has been shown to ameliorate endothelial dysfunction induced by in atherosclerosis rats. However, whether CT can inhibit the degradation of GCH1 protein is not clear. It has been reported that ubiquitination may play a crucial role in regulating GCH1 protein levels and activities. However, the specific E3 ligase for GCH1 and the molecular mechanism of GCH1 ubiquitination remain unclear. Using data-base exploration analysis, we find that the levels of the E3 ligase Smad-ubiquitination regulatory factor 2 (Smurf2) negatively correlate with those of GCH1 in vascular tissues and HUVECs. We observe that Smurf2 interacts with GCH1 and promotes its degradation via the proteasome pathway. Interestingly, ectopic Smurf2 expression not only decreases GCH1 levels but also reduces cell proliferation and reactive oxygen species (ROS) levels, mostly because of increased GCH1 accumulation. Furthermore, we identify BH 4/eNOS as downstream of GCH1. Taken together, our results indicate that CT can obviously improve vascular endothelial injury in Type 1 diabetes mellitus (T1DM) rats and reverse the expressions of GCH1 and Smurf2 proteins in aorta of T1DM rats. Smurf2 promotes ubiquitination and degradation of GCH1 through proteasome pathway in HUVECs. We conclude that the Smurf2-GCH1 interaction might represent a potential target for improving endothelial injury.

Advanced Mass Spectrometry-Based Biomarker Identification for Metabolomics of Diabetes Mellitus and Its Complications.

Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography-tandem mass spectrometry (GC-MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease.

A QTL GN1.1, encoding FT-L1, regulates grain number and yield by modulating polar auxin transport in rice.

Rice grain number is a crucial agronomic trait impacting yield. In this study, we characterized a quantitative trait locus (QTL), GRAIN NUMBER 1.1 (GN1.1), which encodes a Flowering Locus T-like1 (FT-L1) protein and acts as a negative regulator of grain number in rice. The elite allele GN1.1B, derived from the Oryza indica variety, BF3-104, exhibits a 14.6% increase in grain yield compared with the O. japonica variety, Nipponbare, based on plot yield tests. We demonstrated that GN1.1 interacted with and enhanced the stability of ADP-ribosylation factor (Arf)-GTPase-activating protein (Gap), OsZAC. Loss of function of OsZAC results in increased grain number. Based on our data, we propose that GN1.1B facilitates the elevation of auxin content in young rice panicles by affecting polar auxin transport (PAT) through interaction with OsZAC. Our study unveils the pivotal role of the GN1.1 locus in rice panicle development and presents a novel, promising allele for enhancing rice grain yield through genetic improvement.

SFC active reconfiguration based on user mobility and resource demand prediction in dynamic IoT-MEC networks.

To achieve secure, reliable, and scalable traffic delivery, request streams in mobile Internet of Things (IoT) networks supporting Multi-access Edge Computing (MEC) typically need to pass through a service function chain (SFC) consisting of an ordered series of Virtual Network Functions (VNFs), and then arrive at the target application in the MEC for processing. The high mobility of users and the real-time variability of network traffic in IoT-MEC networks lead to constant changes in the network state, which results in a mismatch between the performance requirements of the currently deployed SFCs and the allocated resources. Meanwhile, there are usually multiple instances of the same VNF in the network, and proactively reconfiguring the deployed SFCs based on the network state changes to ensure high quality of service in the network is a great challenge. In this paper, we study the SFC Reconfiguration Strategy (SFC-RS) based on user mobility and resource demand prediction in IoT MEC networks, aiming to minimize the end-to-end delay and reconfiguration cost of SFCs. First, we model SFC-RS as Integer Linear Programming (ILP). Then, a user trajectory prediction model based on codec movement with attention mechanism and a VNF resource demand prediction model based on the Long Short-Term Memory (LSTM) network are designed to accurately predict user trajectories and node computational and storage resources, respectively. Based on the prediction results, a Prediction-based SFV Active Reconfiguration (PSAR) algorithm is proposed to achieve seamless SFC migration and routing update before the user experience quality degrades, ensuring network consistency and high quality service. Simulation results show that PSAR provides 51.28%, 28.60%, 21.75%, and 16.80% performance improvement over the existing TSRFCM, DDQ, OSA, and DPSM algorithms in terms of end-to-end delay reduction, and 33.32%, 18.94%, 67.42%, and 60.61% performance optimization in terms of reconfiguration cost reduction.

Advances in two-photon absorption photodynamic therapy of glioma based on porphyrin-based metal-organicframework composites.

Gliomas of the brain are characterised by high aggressiveness, high postoperative recurrence rate, high morbidity and mortality, posing a great challenge to clinical treatment. Traditional treatments include surgery, radiotherapy and chemotherapy; they also have significant associated side effects, leading to difficulties in tumour resection and recurrence. Photodynamic therapy has been shown to be a promising new strategy to help treat malignant tumours of the brain. It irradiates the tumour site at a specific wavelength to activate a photosensitiser, which selectively accumulates at the tumour site, triggering a photochemical reaction that destroys the tumour cells. It has the advantages of being minimally invasive, highly targeted and with few adverse reactions, and is expected to be well used in anti-tumour therapy. However, the therapeutic effect of traditional PDT is limited by the weak tissue penetration ability of photosensitiser, hypoxia and immunosuppression in the tumour microenvironment. This paper reviews the current research status on the therapeutic principle of photodynamic therapy in glioma and the mechanism of tumour cell injury, and also analyses the advantages and disadvantages of the current application in glioma treatment, and clarifies the analysis of ideas to improve the tissue penetration ability of photosensitizers. It aims to provide a feasible direction for the improvement of photodynamic therapy for glioma and a reference for the clinical treatment of deep brain tumours.

Evaluating the use of unmanned aerial vehicles for spray applications in mountain Nanguo pear orchards.

BACKGROUND: Nanguo pear is a distinctive pear variety in northeast China, grown mainly in mountainous areas. Due to terrain limitations, ground-based pesticide application equipment is difficult to use. This limitation could be overcome by using unmanned aerial vehicles (UAVs) for pesticide application in Nanguo pear orchards. This study evaluated the spraying performance of two UAVs in the Nanguo pear orchards and compared them with a manually used backpack electric sprayer (BES). The study also analyzed the effect of canopy size on droplet deposition and ground loss, and evaluated two sampling methods, leaf sampling and telescopic rod sampling. RESULTS: Compared to BESs, droplet deposition is lower for UAVs, but the actual pesticide active ingredient deposition is not necessarily lower given the solution concentration. The droplet deposition varies among different UAVs due to structural differences. Under the same UAV operating parameters, droplet deposition on trees with smaller canopy sizes is typically greater than that on trees with larger canopy sizes, and the ground loss was also more severe. Although telescopic rod sampling is a quick and convenient method, it can only reflect the trend of droplet deposition, and the data error is greater compared with leaf sampling. CONCLUSION: UAVs can achieve better droplet deposition in mountainous Nanguo pear orchards and does almost no harm to the operators compared with the BES. However, canopy size needs to be considered to adjust the application volume rate. Telescopic rods can be used for qualitative analyses, but are not recommended for quantitative analyses. © 2024 Society of Chemical Industry.

Artificial antibody-antigen-directed immobilization of lipase for consecutive catalytic synthesis of ester: Benzyl acetate case study.

A strategy based on artificial antibody-antigen recognition was proposed for the specific directed immobilization of lipase. The artificial antibody was synthesized using catechol as a template, α-methacrylic acid as a functional monomer, and Fe3O4 as the matrix material. Lipase was modified with 3,4-dihydroxybenzaldehyde as an artificial antigen. The artificial antibody can specifically recognize catechol fragment in the enzyme structure to achieve the immobilization of lipase. The immobilization amount, yield, specific activity, and immobilized enzyme activity were 13.2 ± 0.2 mg/g, 78.9 ± 0.4 %, 7.9 ± 0.2 U/mgprotein, and 104.6 ± 1.7 U/gcarrier, respectively. Moreover, the immobilized lipase exhibited strong reusability and regeneration ability. Additionally, the immobilized lipase successfully catalyzed the synthesis of benzyl acetate and demonstrated robust continuous catalytic activity. These results fully demonstrate the feasibility of the proposed artificial antibody-antigen-directed immobilization of lipase.

Expressway traffic flow prediction based on MF-TAN and STSA.

Highly accurate traffic flow prediction is essential for effectively managing traffic congestion, providing real-time travel advice, and reducing travel costs. However, traditional traffic flow prediction models often fail to fully consider the correlation and periodicity among traffic state data and rely on static network topology graphs. To solve this problem, this paper proposes a expressway traffic flow prediction model based on multi-feature spatial-temporal adaptive periodic fused graph convolutional network (MFSTAPFGCN). First, we make fine preprocessing of the raw data to construct a complete and accurate dataset. Second, by deeply investigating the correlation properties among section speed, traffic flow, and section saturation rate, we incorporate these features into a multi-feature temporal attention mechanism in order to dynamically model the correlation of traffic flow in different time periods. Next, we adopt a spatial-temporal adaptive fusion graph convolutional network to capture the daily cycle similarity and potential spatial-temporal dependence of traffic flow data. Finally, the superiority of the proposed MFSTAPFGCN model over the traditional baseline model is verified through comparative experiments on real Electronic Toll Collection (ETC) gantry transaction data, and the effectiveness of each module is demonstrated through ablation experiments.

Prostate cancer with elevated free prostate-specific antigen density: A case report.

BACKGROUND: Prostate cancer is the second most common cancer among men worldwide, and prostate-specific antigen (PSA) is often used in clinical practice to screen for prostate cancer. Normal total PSA (tPSA) level initially excludes prostate cancer. Here, we report a case of prostate cancer with elevated free PSA density (fPSAD). CASE SUMMARY: A patient diagnosed with benign prostatic hyperplasia underwent prostatectomy, and the postoperative pathological results showed acinar adenocarcinoma of the prostate. The patient is currently undergoing endocrine chemotherapy. CONCLUSION: We provide a clinical reference for diagnosis and treatment of patients with normal tPSA but elevated fPSAD.

Ultrasoft and High-Adhesion Block Copolymers for Neuromorphic Computing.

The "von Neumann bottleneck" is a formidable challenge in conventional computing, driving exploration into artificial synapses. Organic semiconductor materials show promise but are hindered by issues such as poor adhesion and a high elastic modulus. Here, we combine polyisoindigo-bithiophene (PIID-2T) with grafted poly(dimethylsiloxane) (PDMS) to synthesize the triblock-conjugated polymer (PIID-2T-PDMS). The polymer exhibited substantial enhancements in adhesion (4.8-68.8 nN) and reductions in elastic modulus (1.6-0.58 GPa) while maintaining the electrical characteristics of PIID-2T. The three-terminal organic synaptic transistor (three-terminal p-type organic artificial synapse (TPOAS)), constructed using PIID-2T-PDMS, exhibits an unprecedented analog switching range of 276×, surpassing previous records, and a remarkable memory on-off ratio of 106. Moreover, the device displays outstanding operational stability, retaining 99.6% of its original current after 1600 write-read events in the air. Notably, TPOAS replicates key biological synaptic behaviors, including paired-pulse facilitation (PPF), short-term plasticity (STP), and long-term plasticity (LTP). Simulations using handwritten digital data sets reveal an impressive recognition accuracy of 91.7%. This study presents a polyisoindigo-bithiophene-based block copolymer that offers enhanced adhesion, reduced elastic modulus, and high-performance artificial synapses, paving the way for the next generation of neuromorphic computing systems.

Determination of the effective swath of a plant protection UAV adapted to mist nozzles in mountain Nangguo pear orchards.

Plant protection unmanned aerial vehicles (UAVs) have become popular in mountain orchards, but due to the differences in planting structures, the chances of heavy spraying, missed spraying and pesticide drift are increasing. To mitigate the adverse effects of these phenomena, it is necessary to clarify the effective deposition range of aerial spray droplets. This study proposed an effective spray swath determination method for the effective spraying range of mountainous orchards with UAVs equipped with a mist nozzle (bilateral 1% coverage). This approach focused on exploring the effects of flight height (unidirectional flight modes of 2, 3 and 4 m), spray nozzle atomization performance (reciprocating flight modes of 20, 30 and 40 µm) and flight route (treetop flying and inter-row flying) on the spraying range in a mountain setting. In addition, the study analysed the relationship between the droplet-size spectrum and the effective swath position. The results showed that it is feasible to use the bilateral 1% coverage evaluation method to determine the effective spray swath of a UAV adapted with a mist nozzle for aerial operation in a mountainous Nangguo Pear orchard. With the increase in UAV flight height (2-4 m), the effective unidirectional spray swath also increased, and with the increase in atomization level (20-40 µm), the effective reciprocating spray swath showed a decreasing trend. Moreover, the average effective swath width measured by the UAV for treetop flight was greater than that measured for inter-row flight. The study also found that the proportion of small droplets (droplet size less than 100 µm) below the UAV route was lower (approximately 50%) than along the sides of the route (approximately 80%), and the spray swath was not symmetrically distributed along the flight route but shifted laterally by approximately 3 to 4 m in the downhill direction.

SERS monitoring of methylene blue degradation by Au-Ag@Cu2O-rGO nanocomposite.

A combination of multiple materials effectively improves and enhances the performance of the materials. Thus, a gold-silver@cuprous oxide (Au-Ag@Cu2O)-reduced graphene oxide (rGO) structure was designed and fabricated. We decorated the Au nanoparticles (NPs) on the Ag@Cu2O-rGO composite surface by a redox reaction to form a Au-Ag@Cu2O-rGO structure with two noble metals attached to a Cu2O semiconductor. A comparable Au-Ag@Cu2O structure was also fabricated. After decorating Au NPs into the Ag@Cu2O-rGO composite, the Au-Ag@Cu2O composite structure was loosened, and the surface and interior of the Cu2O shell were decorated with Au and Ag NPs. Moreover, the addition of Au NPs resulted in a proper surface plasmon resonance effect and a significant broadening of the absorption range. The loose structure increased the adsorption of the probe molecules, which increased the surface-enhanced Raman scattering (SERS) intensity. In addition, the fabricated Au-Ag@Cu2O-rGO exhibited excellent catalytic reduction of methylene blue (MB) with sodium borohydride (NaBH4). Therefore, the SERS-based monitoring of the MB degradation was obviously improved.

Decoration of Ag nanoparticle on MXene sheets for SERS studies.

MXene sheets with the unique electrical and optical properties show the excellent potential for surface-enhanced Raman spectroscopy (SERS) applications. In this study, we chose Ti3C2Tx, a type of MXene, to decorate silver nanoparticles (Ag NPs) on the ultrathin two-dimensional (2D) MXene sheets. The designed Ag-MXene substrates with SERS activity showed high sensitivity, high stability, and reproducibility. The SERS signal was enhanced by the synergistic contribution of both charge-transfer (CT) and surface plasmon resonance (SPR) involving the Ag NPs and the MXene sheets. Due to the strong interaction between the probe molecules and Ag NPs which provided the nanoscale gap, the substrate exhibited remarkable SERS performance. A novel experimental strategy was developed to facilitate the controlled synthesis of noble metal NPs and MXene sheets and provide insights for further improving the practical applications of these materials in SERS detection.