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Effective and safe hemodialysis is essential for patients with acute kidney injury and chronic renal failures. However, the development of effective anticoagulant agents with safe antidotes for use during hemodialysis has proven challenging. Here, we describe DNA origami-based assemblies that enable the inhibition of thrombin activity and thrombus formation. Two different thrombin-binding aptamers decorated DNA origami initiates protein recognition and inhibition, exhibiting enhanced anticoagulation in human plasma, fresh whole blood and a murine model. In a dialyzer-containing extracorporeal circuit that mimicked clinical hemodialysis, the origami-based aptamer nanoarray effectively prevented thrombosis formation. Oligonucleotides containing sequences complementary to the thrombin-binding aptamers can efficiently neutralize the anticoagulant effects. The nanoarray is safe and immunologically inert in healthy mice, eliciting no detectable changes in liver and kidney functions or serum cytokine concentration. This DNA origami-based nanoagent represents a promising anticoagulant platform for the hemodialysis treatment of renal diseases. Safe haemodialysis is essential for patients with acute kidney injury and renal failure. Here the authors present a DNA origami-based approach with high affinity and specificity to thrombin, inhibiting coagulation.

Septic cardiomyopathy (SCM) is a prevalent and severe complication associated with sepsis. This study explores the effects of sevoflurane and pentobarbital on lipopolysaccharide (LPS) -induced SCM and elucidates underlying mechanisms. The SCM model was established using an intraperitoneal injection of 10 mg/kg LPS. Pentobarbital and sevoflurane were administered thirty minutes post-model establishment. Following the echocardiographic assessment, mice were euthanized 24 h after the modeling, and cardiac samples were collected. Gene sequencing and western blot were utilized to identify potential hub genes and signaling pathways. Sevoflurane markedly reduced LPS-induced myocardial injury and cardiac dysfunction compared to the pentobarbital intervention. Transcriptome sequencing revealed that numerous genes exhibited differential expression following intervention with sevoflurane and pentobarbital, with predominant enrichment in the signaling pathways, such as the extracellular region and matrix, tumor necrosis factor (TNF), and p53 signaling. Sevoflurane significantly induced TATA-box binding protein-associated factor, RNA polymerase I subunit D (TAF1D) expression and attenuated cardiomyocyte death, oxidative stress, and the secretion of IL-6 and TNF-α compared to the pentobarbital group ( p  < 0.05). Furthermore, oe-TAF1D significantly exacerbated cardiomyocyte death, oxidative stress, and inflammatory responses, which were alleviated with si-TAF1D ( p  < 0.05). Sevoflurane mitigates sepsis-induced cell death, oxidative stress, and inflammatory responses by up-regulating TAF1D, consequently diminishing cardiac injury and preserving cardiac function.

The present paper studied the effects of calcination temperatures (200–800 °C) on the appearance, mineral composition, and active SiO2 content in attapulgite and investigated the effects of attapulgite before and after calcination on the chemically bonded water content, the degree of reaction of cement paste, and the mechanical properties such as the flexural strength, compressive strength, and splitting-tensile strength of cement mortar. The results indicate that the calcination temperature changes the mineral composition of attapulgite, thereby affecting the hydration activity of cement-based materials. The attapulgite calcined at 500 °C (AT500) has the best enhancement on the hydration activity of cement-based materials. The calcination at 500 °C is most beneficial to the dissolution of SiO2, and the content of SiO2 reaches 20.96%. The contents of chemically bonded water in the samples incorporated with calcined attapulgite reduced and that of the samples incorporated with AT500 at 28 d is the same as that of the control group. The reaction degree of AT500 is 78.61% at 28 days. Calcined attapulgite clay can reduce the energy consumption of the cement industry and promote the sustainable development of attapulgite clay.

The human microbiome plays a crucial role in maintaining health, with advances in high‐throughput sequencing technology and reduced sequencing costs triggering a surge in microbiome research. Microbiome studies generally incorporate five key phases: design, sampling, sequencing, analysis, and reporting, with sequencing strategy being a crucial step offering numerous options. Present mainstream sequencing strategies include Amplicon sequencing, Metagenomic Next‐Generation Sequencing (mNGS), and Targeted Next‐Generation Sequencing (tNGS). Two innovative technologies recently emerged, namely MobiMicrobe high‐throughput microbial single‐cell genome sequencing technology and 2bRAD‐M simplified metagenomic sequencing technology, compensate for the limitations of mainstream technologies, each boasting unique core strengths. This paper reviews the basic principles and processes of these three mainstream and two novel microbiological technologies, aiding readers in understanding the benefits and drawbacks of different technologies, thereby guiding the selection of the most suitable method for their research endeavours. Current prevailing sequencing methodologies encompass Amplicon sequencing, Metagenomic Next‐Generation Sequencing (mNGS), and Targeted Next‐Generation Sequencing (tNGS). Recently introduced innovative platforms, MobiMicrobe high‐throughput microbial single‐cell genome sequencing technology and 2bRAD‐M simplified metagenomic sequencing technology, serve to ameliorate the constraints inherent to established techniques, each offering distinct core advantages. This manuscript delineates the foundational principles and operational protocols of both the mainstream and emergent microbiological sequencing technologies, The objective is to elucidate the merits and limitations of each approach, thereby providing informed guidance for researchers in selecting the most pertinent sequencing methodology for their scientific inquiries.

Binding kinetic properties of protein–ligand complexes are crucial factors affecting the drug potency. Nevertheless, the current in silico techniques are insufficient in providing accurate and robust predictions for binding kinetic properties. To this end, this work develops a variety of binding kinetic models for predicting a critical binding kinetic property, dissociation rate constant, using eight machine learning (ML) methods (Bayesian Neural Network (BNN), partial least squares regression, Bayesian ridge, Gaussian process regression, principal component regression, random forest, support vector machine, extreme gradient boosting) and the descriptors of the van der Waals/electrostatic interaction energies. These eight models are applied to two case studies involving the HSP90 and RIP1 kinase inhibitors. Both regression results of two case studies indicate that the BNN model has the state‐of‐the‐art prediction accuracy (HSP90: Rtest2=0.947${R}_{\\text{test}}^{2}=0.947$ , MAEtest = 0.184, rtest = 0.976, RMSEtest = 0.220; RIP1 kinase: Rtest2=0.745${R}_{\\text{test}}^{2}=0.745$ , MAEtest = 0.188, rtest = 0.961, RMSEtest = 0.290) in comparison with other seven ML models. This paper develops a variety of binding kinetic models for predicting dissociation rate constants using eight machine learning methods, which are tested by two case studies involving the HSP90 and RIP1 kinase inhibitors. Both regression results of the two case studies indicate that the Bayesian neural network model has the state‐of‐the‐art prediction accuracy in comparison with the other seven machine learning algorithms.

Glutamate plays a crucial role in the treatment of depression by interacting with the metabotropic glutamate receptor subtype 5 (mGluR5), whose negative allosteric modulators (NAMs) are thus promising antidepressants. At present, to explore the structural features of 106 newly synthesized aryl benzamide series molecules as mGluR5 NAMs, a set of ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses were firstly carried out applying comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. In addition, receptor-based analysis, namely molecular docking and molecular dynamics (MD) simulations, were performed to further elucidate the binding modes of mGluR5 NAMs. As a result, the optimal CoMSIA model obtained shows that cross-validated correlation coefficient Q2 = 0.70, non-cross-validated correlation coefficient R2ncv = 0.89, predicted correlation coefficient R2pre = 0.87. Moreover, we found that aryl benzamide series molecules bind as mGluR5 NAMs at Site 1, which consists of amino acids Pro655, Tyr659, Ile625, Ile651, Ile944, Ser658, Ser654, Ser969, Ser965, Ala970, Ala973, Trp945, Phe948, Pro903, Asn907, Val966, Leu904, and Met962. This site is the same as that of other types of NAMs; mGluR5 NAMs are stabilized in the “linear” and “arc” configurations mainly through the H-bonds interactions, π–π stacking interaction with Trp945, and hydrophobic contacts. We hope that the models and information obtained will help understand the interaction mechanism of NAMs and design and optimize NAMs as new types of antidepressants.

In high-voltage switchgear, partial discharge (PD) detection using six-degree-of-freedom (6-DOF) manipulators presents challenges. However, these involve inverse kinematics (IK) solution redundancy and the lack of synergistic optimization between end-effector positioning accuracy and energy consumption. To address these issues, a dual-layer adaptive optimization model integrating multiple algorithms is proposed. In the first layer, a spatio-temporal correlation particle memory-based particle swarm optimization BP neural network (STPSO-BP) is employed. It replaces traditional IK, while long short-term memory (LSTM) predicts particle movement trends, and trajectory similarity penalties constrain search trajectories. Thereby, positioning accuracy and adaptability are enhanced. In the second layer, a chaotic mapping-based simulated annealing (CM-SA) algorithm is utilized. Chaotic joint angle constraints, dynamic weight adjustment, and dynamic temperature regulation are incorporated. This approach achieves collaborative optimization of energy consumption and positioning error, utilizing cubic spline interpolation to smooth the joint trajectory. Specifically, the positioning error decreases by 68.9% compared with the traditional BP neural network algorithm. Energy consumption is reduced by 60.18% in contrast to the pre-optimization state. Overall, the model achieves significant optimization. An innovative solution for synergistic accuracy–energy control in 6-DOF manipulators for PD detection is offered.

Rectovaginal fistula (RVF) is a severe gynecological complication that can arise from obstetric trauma, surgical injury, infection, or physical trauma. RVF resulting from childhood sexual assault accompanied by extensive perineal injury is uncommon in clinical practice, and its management is particularly complex, as it requires not only meticulous anatomical reconstruction but also sustained attention to long-term psychological sequelae. This report presents the case of a patient with RVF secondary to childhood sexual assault. The patient underwent two unsuccessful repair attempts and subsequently developed a complex RVF associated with an old grade IV perineal laceration. At presentation, she reported intermittent passage of fecal material through the vagina. Physical examination showed a complete loss of the perineal body and central tendon, along with the absence of the rectovaginal septum. Pelvic magnetic resonance imaging revealed an incomplete posterior vaginal wall measuring 3.4 cm, extending from the lower vaginal segment to the vaginal introitus, consistent with RVF. Definitive anatomical reconstruction was achieved through close intraoperative collaboration among gynecology, colorectal surgery, and anesthesiology. Comprehensive perioperative psychological evaluation and psychiatric support alleviated trauma-related distress, improved treatment adherence, and facilitated postoperative recovery. Specialized nursing care optimized perioperative management and supported functional rehabilitation. Within this multidisciplinary team (MDT) framework, a successful single-stage surgical repair was accomplished. This case highlights the value of an individualized, MDT-based approach that integrates surgical reconstruction with psychological intervention in the management of complex RVF. Despite previous failed repairs and delayed intervention, a coordinated single-stage MDT strategy resulted in a favorable outcome. We further analyze the potential causes of previous surgical failure, identify key determinants of successful repair, and provide practical insights to guide the management of similar complex cases in clinical practice.

Here, we report on using chemical vapor deposition to generate three kinds of gallium sulfide nanosheets, with thicknesses of approximately 10, 40, and 170 nm. Next, we performed Raman imaging analysis on these nanosheets to evaluate their properties. The 10 nm GaS nanosheets exhibited a nearly equal distribution of Raman imaging intensity, whereas the 40 and 170 nm GaS nanosheets exhibited an inclination toward the edges with higher Raman intensity. When the polarization of the laser was changed, the intensity of Raman imaging of the 10 nm thick GaS nanosheets remained consistent when illuminated with a 532 nm laser. Notably, a greater Raman intensity was discernible at the edges of the 40 and 170 nm GaS nanosheets. Three distinct GaS nanosheet devices with different film thicknesses were fabricated, and their photocurrents were recorded. The devices were exposed to light of 455 nm wavelength. The GaS nanosheet devices with film thicknesses of 40 and 170 nm exhibited a positive photoresponse even though the photocurrents were fairly low. In contrast, the GaS nanosheet device with a film thickness of 10 nm had a considerable current without light, even though it had a weak reaction to light. This study reveals the different spatial patterns of Raman imaging with GaS thickness, the wavelength of excitation light, and polarization. Remarkably, the I-V diagram revealed a higher dark-field current of 800 nA in the device with a GaS nanosheet thickness of approximately 10 nm, when using a voltage of 1.5 V and a laser of 445 nm wavelength. These findings are comparable with those theretical pretictions in the existing literature. In conclusion, the observation above could serve as a catalyst for future exploration into photocatalysis, electrochemical hydrogen production through water splitting, energy storage, nonlinear optics, gas sensing, and ultraviolet selective photodetectors of GaS nanosheet-based photodetectors.

Bi2Te3 has been extensively used because of its excellent thermoelectric properties at room temperature. Here, 230–420 nm of Bi2Te3 hexagonal nanosheets has been successfully synthesized via a “green” method by using ethylene glycol solution and applying polyvinyl pyrrolidone (PVP) as a surfactant. In addition, factors influencing morphological evolution are discussed in detail in this study. Among these parameters, the reaction temperature, molar mass of NaOH, different surfactants, and reaction duration are considered as the most essential. The results show that the existence of PVP is vital to the formation of a plate-like morphology. The reaction temperature and alkaline surroundings played essential roles in the formation of Bi2Te3 single crystals. By spark plasma sintering, the Bi2Te3 hexagonal nanosheets were hot pressed into solid-state samples. We also studied the transport properties of solid-state samples. The electrical conductivity σ was 18.5 × 103 Sm−1 to 28.69 × 103 Sm−1, and the Seebeck coefficient S was −90.4 to −113.3 µVK−1 over a temperature range of 300–550 K. In conclusion, the observation above could serve as a catalyst for future exploration into photocatalysis, solar cells, nonlinear optics, thermoelectric generators, and ultraviolet selective photodetectors of Bi2Te3 nanosheet-based photodetectors.