Dynamic fracture mechanism and fragment characteristics of sandstone specimens with asymmetrical conjugate fissures under static pre-compression.

This paper systematically investigates the dynamic mechanical response and fragment characteristics of sandstone with asymmetrical conjugate fissures subjected to preexisting static stress based on the split Hopkinson pressure bar apparatus. The cross-fissured sandstone exhibits significant variations in mechanical behavior when exposed to higher dynamic strain rates under identical static pre-stress. The cross-fissured sandstone with a higher dynamic strain rate is characterized by a greater coupled strength under the same static pre-stress; for a given dynamic load, the highest coupled strength occurs under the static pre-stress of 60% UCS. The failure mode of the cross-fissured sandstone is predominantly governed by the dynamic strain rate, independent of static pre-stress variations considered in this investigation. At lower dynamic strain rates, the specimens typically exhibit a mixed tensile-shear failure mode, characterized by the dominance of larger fragments in the broken specimens. In contrast, under high dynamic impacts, the sandstone tends to fail in a shear-dominated manner, resulting in smaller fragments with a more uniform size distribution. Furthermore, the study explores how varying dynamic strain rates and static pre-stress influence the fragment characteristics of the cross-fissured sandstone. Higher dynamic strain rates and increased static pre-stress generally lead to smaller mean fragment sizes. This phenomenon is quantitatively described by fitting fragment size distributions using the Generalized Extreme Value (GEV) distribution, revealing a decrease in the location parameter (µ) and an increase in fractal dimension. These metrics indicate that higher dynamic strain rates and static pre-stress result in sandstone specimens breaking into smaller fragments with a more homogeneous size distribution. These findings contribute to a deeper understanding of rock dynamics, with potential implications for engineering applications involving similar geological configuration under dynamic loading conditions.

Volatile oil from Acori graminei Rhizoma affected the synaptic plasticity of rats with tic disorders by modulating dopaminergic and glutamatergic systems.

ETHNOPHARMACOLOGICAL RELEVANCE: Acori graminei Rhizoma is a commonly used traditional Chinese medicine for treating TD, with its main component being calamus volatile oil. Volatile Oil from Acori graminei Rhizoma (VOA)can protect nerve cells and alleviate learning and memory disorders. However, the mechanism of anti-tic of VOA is still unclear. AIM OF THE STUDY: We aimed to explore the effects of Volatile Oil from Acori Tatarinowii Rhizoma (VOA) on striatal dopaminergic and glutamatergic systems and synaptic plasticity of rats with Tic Disorder (TD), as well as its pharmaceutical mechanism against TD. MATERIALS AND METHODS: This study involved 48 (three-week-old) Sprague Dawley (SD) rats, which were randomly divided into two primary groups: Control (8) and TD (40). Rats in the TD group were injected intraperitoneally with 3,3-iminodipropionitrile (IDPN) to construct the TD rat model. They were divided into five subgroups: Model, Tiapride, VOA-high, VOA-medium, and VOA-low (N = 8). After modeling, VOA was administrated to rats in the VOA groups through gavage (once/day for four consecutive weeks), while rats in the blank control and model groups received normal saline of the same volume. The animals' behavioral changes were reflected using the stereotypic and motor behavior scores. After interferences, patterns of striatal neurons and the density of dendritic spines were investigated using H&E and Golgi staining, and the ultrastructure of striatal synapses was examined using Transmission Electron Microscopy (TEM). Furthermore, Ca2+ content was determined using the Ca2+ detector, and Dopamine (DA) and Glutamate (GLU) contents in serum and striatum were detected through ELISA. Finally, DRD1, DRD2, AMPAR1, NMPAR1, DAT, VMAT2, CAMKⅡ, and CREB expression in the striatum was detected using Quantitative real-time PCR (qRT-PCR), Western Blotting (WB) and Immunohistochemical (IHC) methods. RESULTS: Compared to rats in the blank control and model groups, rats in the VOA groups showed lower stereotypic behavior scores. Furthermore, rats in the VOA groups exhibited relieved, neuron damage and increased quantities of neuronal dendrites and dendritic spines Additionally, based on TEM images show that, the VOA groups showed a clear synaptic structure and increased amounts of postsynaptic dense substances and synaptic vesicles. The VOA groups also exhibited reduced Ca2+ contents, and upregulation of DRD1, DRD2, DAT, AMPAR1, and NMPAR1 and downregulation of VMAT-2, CAMKⅡ, and CREB in the striatum. CONCLUSIONS: In summary, VOA could influence synaptic plasticity by tuning the dopaminergic and glutamatergic systems, thus relieving TD.

Association of M2 macrophages with EMT in glioma identified through combination of multi-omics and machine learning.

Background: The incidence of glioma, a prevalent brain malignancy, is increasing, particularly among the elderly population. This study aimed to elucidate the clinical importance of epithelial-mesenchymal transition (EMT) in gliomas and its association with malignancy and prognosis. Background: The incidence of glioma, particularly among elderly individuals, is on the rise. The malignancy of glioma is determined not only by the oncogenic properties of tumor cells but also by the composition of the tumor microenvironment, which includes immune system macrophages. The prevalence of M2-type macrophages typically fosters tumor progression, yet the underlying mechanism remains elusive. Our study explored the clinical importance of epithelial-mesenchymal transition (EMT) in gliomas and its association with malignancy and prognosis. Methods: Our study used the gene set variation analysis (GSVA) algorithm to classify different levels of EMT activation based on the transcriptomic and multi-omics data. Machine learning (ML) and single-cell analysis were integrated into our model for comprehensive analysis. A predictive model was constructed and in vitro experiments were performed to validate our findings. Results: Our study classified 1,641 samples into two clusters based on EMT activation: the EMT-hot group and the EMT-cold group. The EMT-hot group had elevated copy number loss, tumor mutational burden (TMB), and a poorer survival rate. Conversely, the EMT-cold group showed a better survival rate, likely attributed to lower stromal and immune cell scores, as well as decreased expression of human leukocyte antigen-related genes. Driving genes were identified through weighted gene coexpression network analysis (WGCNA) and dimensionality reduction techniques. These genes were then utilized in the construction of a prognostic model using ML and protein-protein interaction (PPI) network analysis. Furthermore, the impact of the core genes identified through single-cell analysis on glioma prognosis was examined. Conclusion: Our research underscores the efficacy of our model in predicting glioma prognosis and elucidates the connection between the M2 macrophages and EMT. Additionally, core genes such as LY96, C1QB, LGALS1, CSPG5, S100A8, and CHGB were identified as pivotal for mediating the occurrence of EMT induced by M2 macrophages.

GNN-DDAS: Drug discovery for identifying anti-schistosome small molecules based on graph neural network.

Schistosomiasis is a tropical disease that poses a significant risk to hundreds of millions of people, yet often goes unnoticed. While praziquantel, a widely used anti-schistosome drug, has a low cost and a high cure rate, it has several drawbacks. These include ineffectiveness against schistosome larvae, reduced efficacy in young children, and emerging drug resistance. Discovering new and active anti-schistosome small molecules is therefore critical, but this process presents the challenge of low accuracy in computer-aided methods. To address this issue, we proposed GNN-DDAS, a novel deep learning framework based on graph neural networks (GNN), designed for drug discovery to identify active anti-schistosome (DDAS) small molecules. Initially, a multi-layer perceptron was used to derive sequence features from various representations of small molecule SMILES. Next, GNN was employed to extract structural features from molecular graphs. Finally, the extracted sequence and structural features were then concatenated and fed into a fully connected network to predict active anti-schistosome small molecules. Experimental results showed that GNN-DDAS exhibited superior performance compared to the benchmark methods on both benchmark and real-world application datasets. Additionally, the use of GNNExplainer model allowed us to analyze the key substructure features of small molecules, providing insight into the effectiveness of GNN-DDAS. Overall, GNN-DDAS provided a promising solution for discovering new and active anti-schistosome small molecules.

The response mechanism analysis of HMX1 knockout strain to levulinic acid in Saccharomyces cerevisiae.

Levulinic acid, a hydrolysis product of lignocellulose, can be metabolized into important compounds in the field of medicine and pesticides by engineered strains of Saccharomyces cerevisiae. Levulinic acid, as an intermediate product widely found in the conversion process of lignocellulosic biomass, has multiple applications. However, its toxicity to Saccharomyces cerevisiae reduces its conversion efficiency, so screening Saccharomyces cerevisiae genes that can tolerate levulinic acid becomes the key. By creating a whole-genome knockout library and bioinformatics analysis, this study used the phenotypic characteristics of cells as the basis for screening and found the HMX1 gene that is highly sensitive to levulinic acid in the oxidative stress pathway. After knocking out HMX1 and treating with levulinic acid, the omics data of the strain revealed that multiple affected pathways, especially the expression of 14 genes related to the cell wall and membrane system, were significantly downregulated. The levels of acetyl-CoA and riboflavin decreased by 1.02-fold and 1.44-fold, respectively, while the content of pantothenic acid increased. These findings indicate that the cell wall-membrane system, as well as the metabolism of acetyl-CoA and riboflavin, are important in improving the resistance of Saccharomyces cerevisiae to levulinic acid. They provide theoretical support for enhancing the tolerance of microorganisms to levulinic acid, which is significant for optimizing the conversion process of lignocellulosic biomass to levulinic acid.

Needle-free, Novel Fossa Ovalis Puncture with Percutaneous Transluminal Coronary Angioplasty Guidewire and Microcatheter in Pigs and a Human with an Extremely Tortuous Inferior Vena Cava.

Background: Transseptal puncture (TSP) performed with the Brockenbrough (BRK) needle is technically demanding and carries potential risks. The back end of the percutaneous transluminal coronary angioplasty (PTCA) guidewire is blunt and flexible, with good support, it can puncture the right ventricle-free wall, which is thicker than the atrial-septum. The guidewire is thin and easy to manipulate. This study evaluated the performance of TSP with a PTCA guidewire and microcatheter without a needle. Methods: The back end of a PTCA guidewire was advanced into the Tiger (TIG) catheter, within the SL1 sheath, to puncture the fossa ovalis (FO) under fluoroscopy. Subsequently, the microcatheter was inserted into the left atrium (LA) above the guidewire, and the front end of the guidewire was exchanged in the LA. After the puncture site was confirmed by contrast, the TIG catheter and a 0.032 inch wire were advanced into the LA. Finally, the sheath, with the dilator, was advanced over the wire into the LA. The safety margin of this method was tested in a pig model. Results: The puncture was successful in all seven pigs tested with a puncture-to-sheath entry time of < 20 minutes and no procedure-related complications. The method was successfully used to perform a difficult TSP in a patient with an extremely tortuous inferior vena cava, in whom puncture with a BRK needle had repeatedly failed. Conclusions: Cardiologists may use the PTCA guidewire and microcatheter as an alternative to the needle while performing TSP in special conditions, such as an extremely tortuous inferior vena cava.

The failure mechanism of the Baishi landslide in Beichuan County, Sichuan, China.

The Baishi landslide was located in the western part of Beichuan County, Sichuan Province, China. The landslide experienced multiple minor collapses at the front part, accompanying with numerous tensile cracks. To comprehensively grasp the stability conditions and predict the moment of failure of the landslide, deformation monitoring of the landslide has been carried out from the moment that the landslide was reported until it failed. This study analyzed the different phases of landslide deformation and its failure mechanism through the analysis of monitoring data. The result showed that the failure manifests both the retrogressive and advancing features. The landslide was divided into several zones based on the spatial variation of the deformation characteristics. Moreover, the improved tangential angle criterion is applied to categorize the deformation phases of a landslide. Investigating the surface displacement vectors and vector angles of landslides plays a significant role for ascertaining the failure and sliding mechanism. The monitoring results revealed that the front part of the landslide played a key role in the stability of the landslide. Therefore, the monitoring data from this zone were crucial for predicting the moment of complete landslide failure.

A 64 × 128 3D-Stacked SPAD Image Sensor for Low-Light Imaging.

Low-light imaging capabilities are in urgent demand in many fields, such as security surveillance, night-time autonomous driving, wilderness rescue, and environmental monitoring. The excellent performance of SPAD devices gives them significant potential for applications in low-light imaging. This article presents a 64 (rows) × 128 (columns) SPAD image sensor designed for low-light imaging. The chip utilizes a three-dimensional stacking architecture and microlens technology, combined with compact gated pixel circuits designed with thick-gate MOS transistors, which further enhance the SPAD's photosensitivity. The configurable digital control circuit allows for the adjustment of exposure time, enabling the sensor to adapt to different lighting conditions. The chip exhibits very low dark noise levels, with an average DCR of 41.5 cps at 2.4 V excess bias voltage. Additionally, it employs a denoising algorithm specifically developed for the SPAD image sensor, achieving two-dimensional grayscale imaging under 6 × 10-4 lux illumination conditions, demonstrating excellent low-light imaging capabilities. The chip designed in this paper fully leverages the performance advantages of SPAD image sensors and holds promise for applications in various fields requiring low-light imaging capabilities.

Physicochemical and structural insights into lyophilized mRNA-LNP from lyoprotectant and buffer screenings.

The surge in RNA therapeutics has revolutionized treatments for infectious diseases like COVID-19 and shows the potential to expand into other therapeutic areas. However, the typical requirement for ultra-cold storage of mRNA-LNP formulations poses significant logistical challenges for global distribution. Lyophilization serves as a potential strategy to extend mRNA-LNP stability while eliminating the need for ultra-cold supply chain logistics. Although recent advancements have demonstrated the promise of lyophilization, the choice of lyoprotectant is predominately focused on sucrose, and there remains a gap in comprehensive evaluation and comparison of lyoprotectants and buffers. Here, we aim to systematically investigate the impact of a diverse range of excipients including oligosaccharides, polymers, amino acids, and various buffers, on the quality and performance of lyophilized mRNA-LNPs. From the screening of 45 mRNA-LNP formulations under various lyoprotectant and buffer conditions for lyophilization, we identified previously unexplored formulation compositions, e.g., polyvinylpyrrolidone (PVP) in Tris or acetate buffers, as promising alternatives to the commonly used oligosaccharides to maintain the physicochemical stability of lyophilized mRNA-LNPs. Further, we delved into how physicochemical and structural properties influence the functionality of lyophilized mRNA-LNPs. Leveraging high-throughput small-angle X-ray scattering (SAXS) and cryogenic transmission electron microscopy (cryo-TEM), we showed that there is complex interplay between mRNA-LNP structural features and cellular translation efficacy. We also assessed innate immune responses of the screened mRNA-LNPs in human peripheral blood mononuclear cells (PBMCs), and showed minimal alterations of cytokine secretion profiles induced by lyophilized formulations. Our results provide valuable insights into the structure-activity relationship of lyophilized formulations of mRNA-LNP therapeutics, paving the way for rational design of these formulations. This work creates a foundation for a comprehensive understanding of mRNA-LNP properties and in vitro performance change resulting from lyophilization.

Macro-characteristics and micro-mechanisms of Na2SO4 precipitation dissolved by KNO3 molten salt in a continuous supercritical water system.

This work aims to explore the ability of molten salt to solve salt deposition in supercritical water (SCW) related technologies including supercritical water oxidation and supercritical water gasification, with KNO3 and Na2SO4 as examples. In the pure KNO3 solution, the two-phase layering of high-density KNO3 molten salt (settling at the reactor bottom) and low-density saturated KNO3-SCW salt solution (flowing out at the top outlet of the reactor) was formed in a kettle-reactor with about 6.5 ratio of depth to inner diameter, thereby improving the accuracy of measured solubilities. The precipitation macro-characteristics of mixed KNO3 and Na2SO4 in SCW were investigated under different feed concentration conditions. The results showed that Na2SO4 deposition on the reactor sidewall could be reduced by more than 90 % when the mass ratio of KNO3 to Na2SO4 in the feed was only 0.167. No visible salt deposition was observed on the sidewall when the ratio was 0.374. All solid deposited salts were converted into the liquid molten salt as the ratio reached 3.341, and thus could easily flow out of the reactor, without plugging. 'Molten salt dissolution' mechanism may provide a more plausible explanation for mixed KNO3 and Na2SO4 in SCW. In addition, the precipitation micro-mechanisms of mixed KNO3 and Na2SO4, and the critical conditions of avoiding sidewall deposition and reactor plugging were proposed. This work is valuable for overcoming the salt deposition problem in SCW-related technologies.

A Degraded Finger Vein Image Recovery and Enhancement Algorithm Based on Atmospheric Scattering Theory.

With the development of biometric identification technology, finger vein identification has received more and more widespread attention for its security, efficiency, and stability. However, because of the performance of the current standard finger vein image acquisition device and the complex internal organization of the finger, the acquired images are often heavily degraded and have lost their texture characteristics. This makes the topology of the finger veins inconspicuous or even difficult to distinguish, greatly affecting the identification accuracy. Therefore, this paper proposes a finger vein image recovery and enhancement algorithm using atmospheric scattering theory. Firstly, to normalize the local over-bright and over-dark regions of finger vein images within a certain threshold, the Gamma transform method is improved in this paper to correct and measure the gray value of a given image. Then, we reconstruct the image based on atmospheric scattering theory and design a pixel mutation filter to segment the venous and non-venous contact zones. Finally, the degraded finger vein images are recovered and enhanced by global image gray value normalization. Experiments on SDUMLA-HMT and ZJ-UVM datasets show that our proposed method effectively achieves the recovery and enhancement of degraded finger vein images. The image restoration and enhancement algorithm proposed in this paper performs well in finger vein recognition using traditional methods, machine learning, and deep learning. The recognition accuracy of the processed image is improved by more than 10% compared to the original image.

Distortion measurement of a lithography projection lens based on multichannel grating lateral shearing interferometry.

The optical distortion of the lithographic projection lens can reduce imaging quality and cause overlay errors in lithography, thus preventing the miniaturization of printed patterns. In this paper, we propose a technique to measure the optical distortion of a lithographic projection lens by sensing the wavefront aberrations of the lens. A multichannel dual-grating lateral shearing interferometer is used to measure the wavefront aberrations at several field points in the pupil plane simultaneously. Then, the distortion at these field points is derived according to the proportional relationship between the Z 2 and Z 3 Zernike terms (the tilt terms) and the image position shifts. Without the need for additional devices, our approach can simultaneously retrieve both the wavefront aberrations and the image distortion information. Consequently, it improves not only measurement speed and accuracy but also enables accounting for displacement stage positioning error. Experiments were conducted on a lithographic projection lens with a numerical aperture of 0.57 to verify the feasibility of the proposed method.

LA-ViT: A Network With Transformers Constrained by Learned-Parameter-Free Attention for Interpretable Grading in a New Laryngeal Histopathology Image Dataset.

Grading laryngeal squamous cell carcinoma (LSCC) based on histopathological images is a clinically significant yet challenging task. However, more low-effect background semantic information appeared in the feature maps, feature channels, and class activation maps, which caused a serious impact on the accuracy and interpretability of LSCC grading. While the traditional transformer block makes extensive use of parameter attention, the model overlearns the low-effect background semantic information, resulting in ineffectively reducing the proportion of background semantics. Therefore, we propose an end-to-end network with transformers constrained by learned-parameter-free attention (LA-ViT), which improve the ability to learn high-effect target semantic information and reduce the proportion of background semantics. Firstly, according to generalized linear model and probabilistic, we demonstrate that learned-parameter-free attention (LA) has a stronger ability to learn highly effective target semantic information than parameter attention. Secondly, the first-type LA transformer block of LA-ViT utilizes the feature map position subspace to realize the query. Then, it uses the feature channel subspace to realize the key, and adopts the average convergence to obtain a value. And those construct the LA mechanism. Thus, it reduces the proportion of background semantics in the feature maps and feature channels. Thirdly, the second-type LA transformer block of LA-ViT uses the model probability matrix information and decision level weight information to realize key and query, respectively. And those realize the LA mechanism. So, it reduces the proportion of background semantics in class activation maps. Finally, we build a new complex semantic LSCC pathology image dataset to address the problem, which is less research on LSCC grading models because of lacking clinically meaningful datasets. After extensive experiments, the whole metrics of LA-ViT outperform those of other state-of-the-art methods, and the visualization maps match better with the regions of interest in the pathologists' decision-making. Moreover, the experimental results conducted on a public LSCC pathology image dataset show that LA-ViT has superior generalization performance to that of other state-of-the-art methods.

Genome-wide identification of resistance genes and response mechanism analysis of key gene knockout strain to catechol in Saccharomyces cerevisiae.

Engineering Saccharomyces cerevisiae for biodegradation and transformation of industrial toxic substances such as catechol (CA) has received widespread attention, but the low tolerance of S. cerevisiae to CA has limited its development. The exploration and modification of genes or pathways related to CA tolerance in S. cerevisiae is an effective way to further improve the utilization efficiency of CA. This study identified 36 genes associated with CA tolerance in S. cerevisiae through genome-wide identification and bioinformatics analysis and the ERG6 knockout strain (ERG6Δ) is the most sensitive to CA. Based on the omics analysis of ERG6Δ under CA stress, it was found that ERG6 knockout affects pathways such as intrinsic component of membrane and pentose phosphate pathway. In addition, the study revealed that 29 genes related to the cell wall-membrane system were up-regulated by more than twice, NADPH and NADP+ were increased by 2.48 and 4.41 times respectively, and spermidine and spermine were increased by 2.85 and 2.14 times, respectively, in ERG6Δ. Overall, the response of cell wall-membrane system, the accumulation of spermidine and NADPH, as well as the increased levels of metabolites in pentose phosphate pathway are important findings in improving the CA resistance. This study provides a theoretical basis for improving the tolerance of strains to CA and reducing the damage caused by CA to the ecological environment and human health.

Effect evaluation of competency-based education (CBE) combined with multi-disciplinary team (MDT) teaching mode in respiratory rehabilitation nursing teaching：A randomized controlled trial.

AIM: To explore the application effect of competency-based education (CBE) combined with multi-disciplinary team (MDT) teaching mode in respiratory rehabilitation nursing teaching. BACKGROUND: Respiratory rehabilitation, as an important non drug treatment for chronic respiratory disease, started late in China, with low implementation rate in hospitals and insufficient knowledge of nursing staff. Therefore, it is urgent to cultivate high professional level nurses with strong professional ability. DESIGN: A randomized controlled trial. METHODS: We selected nurses from the respiratory and critical care department at a Grade III, Level A hospital in Beijing, who participated in the respiratory rehabilitation training program between March 2020 and August 2022, as our study participants. Participants were grouped using a random number method. Nurses who participated in the study from March 2020 to May 2021 were set as the control group, and the nurses who participated in the study from June 2021 to August 2022 were set as the test group. The control group used traditional teaching methods, and the test group used the CBE combined MDT teaching model. At the end of the test, the theory, operating skills, satisfaction and core competence were assessed. RESULTS: After training, the theoretical examination score of the test group (93.71 ± 1.94) was higher than that of the control group (92.37 ± 1.92), the operational examination score of the test group (93.11 ± 2.12) was higher than that of the control group (91.61 ± 1.93), the overall teaching satisfaction of the test group (4.45 ± 0.50) was higher than that of the control group (4.13 ± 0.57), and the total score of the core competence of the test group (148.73 ± 7.08) was higher than that of the control group (141.02 ± 6.41). The difference between the two groups was statistically significant (P<0.05). CONCLUSION: CBE combined with MDT teaching mode has a good effect in Pulmonary and Critical Care Medicine (PCCM) respiratory rehabilitation nursing teaching.

Super-Resolution Exciton Imaging of Nanobubbles in 2D Semiconductors with Near-Field Nanophotoluminescence Microscopy.

Two-dimensional (2D) semiconductors, such as transition metal dichalcogenides, have emerged as important candidate materials for next-generation chip-scale optoelectronic devices with the development of large-scale production techniques, such as chemical vapor deposition (CVD). However, 2D materials need to be transferred to other target substrates after growth, during which various micro- and nanoscale defects, such as nanobubbles, are inevitably generated. These nanodefects not only influence the uniformity of 2D semiconductors but also may significantly alter the local optoelectronic properties of the composed devices. Hence, super-resolution discrimination and characterization of nanodefects are highly demanded. Here, we report a near-field nanophotoluminescence (nano-PL) microscope that can quickly screen nanobubbles and investigate their impact on local excitonic properties of 2D semiconductors by directly visualize the PL emission distribution with a very high spatial resolution of ∼10 nm, far below the optical diffraction limit, and a high speed of 10 ms/point under ambient conditions. By using nano-PL microscopy to map the exciton and trion emission intensity distributions in transferred CVD-grown monolayer tungsten disulfide (1L-WS2) flakes, it is found that the PL intensity decreases by 13.4% as the height of the nanobubble increases by every nanometer, which is mainly caused by the suppression of trion emission due to the strong doping effect from the substrate. In addition to the nanobubbles, other types of nanodefects, such as cracks, stacks, and grain boundaries, can also be characterized. The nano-PL method is proven to be a powerful tool for the nondestructive quality inspection of nanodefects as well as the super-resolution exploration of local optoelectronic properties of 2D materials.

Development of an online calculator for the prediction of seizure freedom following pediatric hemispherectomy using the Hemispherectomy Outcome Prediction Scale (HOPS).

OBJECTIVES: Although hemispheric surgeries are among the most effective procedures for drug-resistant epilepsy (DRE) in the pediatric population, there is a large variability in seizure outcomes at the group level. A recently developed HOPS score provides individualized estimation of likelihood of seizure freedom to complement clinical judgement. The objective of this study was to develop a freely accessible online calculator that accurately predicts the probability of seizure freedom for any patient at 1-, 2-, and 5-years post-hemispherectomy. METHODS: Retrospective data of all pediatric patients with DRE and seizure outcome data from the original Hemispherectomy Outcome Prediction Scale (HOPS) study were included. The primary outcome of interest was time-to-seizure recurrence. A multivariate Cox proportional-hazards regression model was developed to predict the likelihood of post-hemispheric surgery seizure freedom at three time points (1-, 2- and 5- years) based on a combination of variables identified by clinical judgment and inferential statistics predictive of the primary outcome. The final model from this study was encoded in a publicly accessible online calculator on the International Network for Epilepsy Surgery and Treatment (iNEST) website (https://hops-calculator.com/). RESULTS: The selected variables for inclusion in the final model included the five original HOPS variables (age at seizure onset, etiologic substrate, seizure semiology, prior non-hemispheric resective surgery, and contralateral fluorodeoxyglucose-positron emission tomography [FDG-PET] hypometabolism) and three additional variables (age at surgery, history of infantile spasms, and magnetic resonance imaging [MRI] lesion). Predictors of shorter time-to-seizure recurrence included younger age at seizure onset, prior resective surgery, generalized seizure semiology, FDG-PET hypometabolism contralateral to the side of surgery, contralateral MRI lesion, non-lesional MRI, non-stroke etiologies, and a history of infantile spasms. The area under the curve (AUC) of the final model was 73.0%. SIGNIFICANCE: Online calculators are useful, cost-free tools that can assist physicians in risk estimation and inform joint decision-making processes with patients and families, potentially leading to greater satisfaction. Although the HOPS data was validated in the original analysis, the authors encourage external validation of this new calculator.

Profibrotic role of transcription factor SP1 in cross-talk between fibroblasts and M2 macrophages.

Fibrosis disrupts tissue balance and links to severe illnesses, impairing organ function and, in some cases, even fatality. The interaction between M2 macrophages and fibroblasts is vital for tissue equilibrium. Transforming growth factor ß1 (TGF-ß1) released by M2 macrophages plays a central role in fibrosis, regulating fibroblast activity and extracellular matrix metabolism. Targeting TGF-ß1 is key to fibrosis treatment. In our study using three fibroblast cell lines, we reveal that the M2 macrophage transcription factor SP1 enhances binding to the TGF-ß1 promoter motif, promoting TGF-ß1 transcription and activating fibroblasts (This process does not involve changes in DNA methylation levels surrounding the motif sequence). The zinc fingers in SP1's DNA-binding domain 3 are crucial for this binding. In vivo, targeting SP1 in rat ligaments significantly reduces extracellular matrix accumulation. Our findings highlight SP1 as a promising target for regulating tissue extracellular matrix and combating fibrosis.

Genome-wide identification of resistance genes and cellular analysis of key gene knockout strain under 5-hydroxymethylfurfural stress in Saccharomyces cerevisiae.

In bioethanol production, the main by-product, 5-hydroxymethylfurfural (HMF), significantly hinders microbial fermentation. Therefore, it is crucial to explore genes related to HMF tolerance in Saccharomyces cerevisiae for enhancing the tolerance of ethanol fermentation strains. A comprehensive analysis was conducted using genome-wide deletion library scanning and SGAtools, resulting in the identification of 294 genes associated with HMF tolerance in S. cerevisiae. Further KEGG and GO enrichment analysis revealed the involvement of genes OCA1 and SIW14 in the protein phosphorylation pathway, underscoring their role in HMF tolerance. Spot test validation and subcellular structure observation demonstrated that, following a 3-h treatment with 60 mM HMF, the SIW14 gene knockout strain exhibited a 12.68% increase in cells with abnormal endoplasmic reticulum (ER) and a 22.41% increase in the accumulation of reactive oxygen species compared to the BY4741 strain. These findings indicate that the SIW14 gene contributes to the protection of the ER structure within the cell and facilitates the clearance of reactive oxygen species, thereby confirming its significance as a key gene for HMF tolerance in S. cerevisiae.

Imaging Threading Dislocations and Surface Steps in Nitride Thin Films Using Electron Backscatter Diffraction.

Extended defects, like threading dislocations, are detrimental to the performance of optoelectronic devices. In the scanning electron microscope, dislocations are traditionally imaged using diodes to monitor changes in backscattered electron intensity as the electron beam is scanned over the sample, with the sample positioned so the electron beam is at, or close to the Bragg angle for a crystal plane/planes. Here, we use a pixelated detector instead of single diodes, specifically an electron backscatter diffraction (EBSD) detector. We present postprocessing techniques to extract images of dislocations and surface steps, for a nitride thin film, from measurements of backscattered electron intensities and intensity distributions in unprocessed EBSD patterns. In virtual diode (VD) imaging, the backscattered electron intensity is monitored for a selected segment of the unprocessed EBSD patterns. In center of mass (COM) imaging, the position of the center of the backscattered electron intensity distribution is monitored. Additionally, both methods can be combined (VDCOM). Using both VD and VDCOM, images of only threading dislocations, or dislocations and surface steps can be produced, with VDCOM images exhibiting better signal-to-noise. The applicability of VDCOM imaging is demonstrated across a range of nitride semiconductor thin films, with varying surface step and dislocation densities.