Digital economy, technological innovation, and sustainable development.

This paper examines the impact of the digital economy on sustainable development, using panel data from cities at the prefecture level and above in China from 2011 to 2019. The results indicate: (1) The digital economy is conducive to boosting growth, increasing employment, reducing energy consumption, and cutting emissions, thereby promoting sustainable development. These findings prove robust. (2) Mechanism test outcomes reveal that, from the perspective of technological innovation, the digital economy can promote sustainable development through increasing R&D input and enhancing innovation output. (3) An extended analysis of the risk of a digital "divide" demonstrates that "dividend" of the digital economy is primarily manifests in spurring economic growth, enhancing energy efficiency, and strengthening environmental protection in lagging regions, while the digital "divide" effect is manifested in the stronger employment stimulating effect of developed regions versus backward areas. The results of this study not only enrich the relevant research system, but also provide empirical evidence to support accelerating digital transformation, strengthening technological innovation governance, and advancing sustainable development.

Differential Contributions of Fibroblast Subpopulations to Intercellular Communication in Eosinophilic Esophagitis.

Fibroblast heterogeneity remains undefined in eosinophilic esophagitis (EoE), an allergic inflammatory disorder complicated by fibrosis. We utilized publicly available single-cell RNA sequencing data (GSE201153) of EoE esophageal biopsies to identify fibroblast sub-populations, related transcriptomes, disease status-specific pathways and cell-cell interactions. IL13-treated fibroblast cultures were used to model active disease. At least 2 fibroblast populations were identified, F_A and F_B. Several genes including ACTA2 were more enriched in F_A. F_B percentage was greater than F_A and epithelial-mesenchymal transition upregulated in F_B vs. F_A in active and remission EoE. Epithelial-mesenchymal transition was also upregulated in F_B in active vs. remission EoE and TNF-α signaling via NFKB was downregulated in F_A. IL-13 treatment upregulated ECM-related genes more profoundly in ACTA2- fibroblasts than ACTA2+ myofibroblasts. After proliferating epithelial cells, F_B and F_A contributed most to cell-cell communication networks. ECM-Receptor interaction strength was stronger than secreted or cell-cell contact signaling in active vs. remission EoE and significant ligand-receptor pairs were driven mostly by F_B. This unbiased analysis identifies at least 2 fibroblast sub-populations in EoE in vivo, distinguished in part by ACTA2. Fibroblasts play a critical role in cell-cell interactions in EoE, most profoundly via ECM-receptor signaling via the F_B sub-group.

Sensory ASIC3 channel exacerbates psoriatic inflammation via a neurogenic pathway in female mice.

Psoriasis is an immune-mediated skin disease associated with neurogenic inflammation, but the underlying molecular mechanism remains unclear. We demonstrate here that acid-sensing ion channel 3 (ASIC3) exacerbates psoriatic inflammation through a sensory neurogenic pathway. Global or nociceptor-specific Asic3 knockout (KO) in female mice alleviates imiquimod-induced psoriatic acanthosis and type 17 inflammation to the same extent as nociceptor ablation. However, ASIC3 is dispensable for IL-23-induced psoriatic inflammation that bypasses the need for nociceptors. Mechanistically, ASIC3 activation induces the activity-dependent release of calcitonin gene-related peptide (CGRP) from sensory neurons to promote neurogenic inflammation. Botulinum neurotoxin A and CGRP antagonists prevent sensory neuron-mediated exacerbation of psoriatic inflammation to similar extents as Asic3 KO. In contrast, replenishing CGRP in the skin of Asic3 KO mice restores the inflammatory response. These findings establish sensory ASIC3 as a critical constituent in psoriatic inflammation, and a promising target for neurogenic inflammation management.

Classification of psychedelic drugs based on brain-wide imaging of cellular c-Fos expression.

Psilocybin, ketamine, and MDMA are psychoactive compounds that exert behavioral effects with distinguishable but also overlapping features. The growing interest in using these compounds as therapeutics necessitates preclinical assays that can accurately screen psychedelics and related analogs. We posit that a promising approach may be to measure drug action on markers of neural plasticity in native brain tissues. We therefore developed a pipeline for drug classification using light sheet fluorescence microscopy of immediate early gene expression at cellular resolution followed by machine learning. We tested male and female mice with a panel of drugs, including psilocybin, ketamine, 5-MeO-DMT, 6-fluoro-DET, MDMA, acute fluoxetine, chronic fluoxetine, and vehicle. In one-versus-rest classification, the exact drug was identified with 67% accuracy, significantly above the chance level of 12.5%. In one-versus-one classifications, psilocybin was discriminated from 5-MeO-DMT, ketamine, MDMA, or acute fluoxetine with >95% accuracy. We used Shapley additive explanation to pinpoint the brain regions driving the machine learning predictions. Our results support a novel approach for screening psychoactive drugs with psychedelic properties.

[Synthesis of fluorinated nitrogen-rich porous organic polymers and removal of perfluorooctanoic acid from water].

Perfluorooctanoic acid (PFOA) is a persistent contaminant with detrimental effects on the natural environment. This persistence leads to potential enrichment and osmotic transfer, which can affect normal circulation in the environment. PFOA poses significant threats to both the natural environment and human health. Therefore, the development of cost-effective, highly efficient, and environment-friendly PFOA adsorbents is a crucial endeavor. This paper presents the catalyst-free one-pot synthesis of fluorinated nitrogen-rich porous organic polymers (POP-3F) via a Schiff-base condensation reaction. The reaction between the nitrogen-rich compound 1,4-bis(2,4-diamino-1,3,5-triazine)benzene and p-trifluoromethylbenzaldehyde yielded POP-3F. The introduction of fluorine atoms into the nitrogen-rich porous organic polymer enhanced its hydrophobicity, thereby facilitating favorable fluoro-fluorine interactions with PFOA and, thus, improving the efficacy of the adsorbent. Scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), solid-state nuclear magnetic resonance (ssNMR) spectroscopy, X-ray photoelectron spectroscopy (XPS), nitrogen adsorption-desorption analysis, and thermogravimetric analysis (TGA) were used to confirm the successful synthesis and characterization of POP-3F. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was conducted in negative electrospray ionization (ESI) mode coupled with multi-reaction monitoring mode (MRM). The instrument was equipped with an Atlantis T3 column (100 mm×2.1 mm, 3 µm), and analysis was conducted using an external standard method. The influences of various factors on PFOA adsorption by POP-3F, including pH, salt concentration, and humic acid presence, were investigated. The highest PFOA removal rate (98.6%) was achieved at a pH of 2, indicating the applicability of POP-3F for the effective removal of PFOA from acidic industrial wastewater. The removal rate of PFOA was unaffected by increases in NaCl concentration. This phenomenon can be attributed to electrostatic interactions between the protonated secondary amines in POP-3F and deprotonated PFOA. Upon the addition of NaCl, a double electric layer is formed on the POP-3F surface, with Cl- ions in the outer layer and Na+ ions in the inner layer, which weakened these interactions. Humic acid is competitively adsorbed with PFOA. However, POP-3F demonstrated good removal rates even in the presence of high humic acid concentrations in water. Adsorption isotherm and kinetics experiments were conducted at the optimal pH to explore the relevant adsorption mechanism. The results showed a rapid initial adsorption rate, with 95.4% PFOA removal within 5 min. Optimal adsorption equilibrium was achieved within 6 h, and the removal rate decreased by only 0.3% after 24 h. This finding indicates that POP-3F exhibits sustained efficacy for PFOA removal. Langmuir fitting analysis revealed a theoretical maximum adsorption capacity of 191 mg/g for POP-3F; this value surpasses those of activated carbon materials and most other adsorbents, highlighting the superior PFOA-adsorption performance of POP-3F. Additionally, matrix effects minimally affected the removal of PFOA by POP-3F, with only a slight reduction (0.1%) observed in simulated natural water. The recyclability of POP-3F was assessed over five adsorption-desorption cycles. The removal efficenecy exhibited a minor decrease of only 0.67% after five cycles. These results demonstrate the recyclability of the proposed adsorbent, which translates into cost reduction through reusability. This characteristic renders POP-3F a promising candidate for the economical and efficient removal of PFOA from wastewater in practical applications.

Influence of Heat Treatment Condition on the Microstructure, Microhardness and Corrosion Resistance of Ag-Sn-In-Ni-Te Alloy Wire.

Ag-Sn-In-Ni-Te alloy ingots were produced through a heating-cooling combined mold continuous casting technique; they were then drawn into wires. However, during the drawing process, the alloy wires tended to harden, making further diameter reduction challenging. To overcome this, heat treatment was necessary to soften the previously drawn wires. The study investigated how variations in heat treatment temperature and holding time affected the microstructure, microhardness and corrosion resistance of the alloy wires. The results indicate that the alloy wires subjected to heat treatment at 700 °C for 2 h not only exhibited a uniform microstructure distribution, but also demonstrated low microhardness and excellent corrosion resistance.

ECEA: Extensible Co-Existing Attention for Few-Shot Object Detection.

Few-shot object detection (FSOD) identifies objects from extremely few annotated samples. Most existing FSOD methods, recently, apply the two-stage learning paradigm, which transfers the knowledge learned from abundant base classes to assist the few-shot detectors by learning the global features. However, such existing FSOD approaches seldom consider the localization of objects from local to global. Limited by the scarce training data in FSOD, the training samples of novel classes typically capture part of objects, resulting in such FSOD methods being unable to detect the completely unseen object during testing. To tackle this problem, we propose an Extensible Co-Existing Attention (ECEA) module to enable the model to infer the global object according to the local parts. Specifically, we first devise an extensible attention mechanism that starts with a local region and extends attention to co-existing regions that are similar and adjacent to the given local region. We then implement the extensible attention mechanism in different feature scales to progressively discover the full object in various receptive fields. In the training process, the model learns the extensible ability on the base stage with abundant samples and transfers it to the novel stage of continuous extensible learning, which can assist the few-shot model to quickly adapt in extending local regions to co-existing regions. Extensive experiments on the PASCAL VOC and COCO datasets show that our ECEA module can assist the few-shot detector to completely predict the object despite some regions failing to appear in the training samples and achieve the new state-of-the-art compared with existing FSOD methods. Code is released at https://github.com/zhimengXin/ECEA.

A Survey of Label-Efficient Deep Learning for 3D Point Clouds.

In the past decade, deep neural networks have achieved significant progress in point cloud learning. However, collecting large-scale precisely-annotated point clouds is extremely laborious and expensive, which hinders the scalability of existing point cloud datasets and poses a bottleneck for efficient exploration of point cloud data in various tasks and applications. Label-efficient learning offers a promising solution by enabling effective deep network training with much-reduced annotation efforts. This paper presents the first comprehensive survey of label-efficient learning of point clouds. We address three critical questions in this emerging research field: i) the importance and urgency of label-efficient learning in point cloud processing, ii) the subfields it encompasses, and iii) the progress achieved in this area. To this end, we propose a taxonomy that organizes label-efficient learning methods based on the data prerequisites provided by different types of labels. We categorize four typical label-efficient learning approaches that significantly reduce point cloud annotation efforts: data augmentation, domain transfer learning, weakly-supervised learning, and pretrained foundation models. For each approach, we outline the problem setup and provide an extensive literature review that showcases relevant progress and challenges. Finally, we share our views on the current research challenges and potential future directions. A project associated with this survey has been built at https://github.com/xiaoaoran/3D label efficient learning.

Regulation of optimized new Shengmai powder on cardiomyocyte apoptosis and ferroptosis in ischemic heart failure rats: The mediating role of phosphatidylinositol-3-kinase/protein kinase B/tumor protein 53 signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Optimized New Shengmai Powder (ONSMP) is a sophisticated traditional Chinese medicinal formula renowned for bolstering vital energy, optimizing blood circulation, and mitigating fluid retention. After years of clinical application, ONSMP has shown a significant impact in improving myocardial injury and cardiac function and has a positive effect on treating heart failure. However, many unknowns exist about the molecular biological mechanisms of how ONSMP exerts its therapeutic effects, which require further research and exploration. AIM OF THE STUDY: Exploring the potential molecular biological mechanisms by which ONSMP ameliorates cardiomyocyte apoptosis and ferroptosis in ischemic heart failure (IHF). MATERIALS AND METHODS: First, we constructed a rat model of IHF by inducing acute myocardial infarction through surgery and using echocardiography, organ coefficients, markers of heart failure, antioxidant markers, and histopathological examination to assess the effects of ONSMP on cardiomyocyte apoptosis and ferroptosis in IHF rats. Next, we used bioinformatics analysis techniques to analyze the active components, signaling pathways, and core targets of ONSMP and calculated the interactions between core targets and corresponding elements. Finally, we detected the positive expression of apoptosis and ferroptosis markers and core indicators of signaling pathways by immunohistochemistry; detected the mean fluorescence intensity of core indicators of signaling pathways by immunofluorescence; detected the protein expression of signaling pathways and downstream effector molecules by western blotting; and detected the mRNA levels of p53 and downstream effector molecules by quantitative polymerase chain reaction. RESULTS: ONSMP can activate the Ser83 site of ASK by promoting the phosphorylation of the PI3K/AKT axis, thereby inhibiting the MKK3/6-p38 axis and the MKK4/7-JNK axis signaling to reduce p53 expression, and can also directly target and inhibit the activity of p53, ultimately inhibiting p53-mediated mRNA and protein increases in PUMA, SAT1, PIG3, and TFR1, as well as mRNA and protein decreases in SLC7A11, thereby inhibiting cardiomyocyte apoptosis and ferroptosis, effectively improving cardiac function and ventricular remodeling in IHF rat models. CONCLUSION: ONSMP can inhibit cardiomyocyte apoptosis and ferroptosis through the PI3K/AKT/p53 signaling pathway, delaying the development of IHF.

Interaction among homeodomain transcription factors mediates ethylene biosynthesis during pear fruit ripening.

Fruit ripening is manipulated by the plant phytohormone ethylene in climacteric fruits. While the transcription factors (TFs) involved in ethylene biosynthesis and fruit ripening have been extensively studied in tomato, their identification in pear remains limited. In this study, we identified and characterized a HOMEODOMAIN TF, PbHB.G7.2, through transcriptome analysis. PbHB.G7.2 could directly bind to the promoter of the ethylene biosynthetic gene, 1-aminocyclopropane-1-carboxylic acid synthase (PbACS1b), thereby enhancing its activity and resulting in increased ethylene production during pear fruit ripening. Yeast-two-hybrid screening revealed that PbHB.G7.2 interacted with PbHB.G1 and PbHB.G2.1. Notably, these interactions disrupted the transcriptional activation of PbHB.G7.2. Interestingly, PbHB.G1 and PbHB.G2.1 also bind to the PbACS1b promoter, albeit different regions from those bound by PbHB.G7.2. Moreover, the regions of PbHB.G1 and PbHB.G2.1 involved in their interaction with PbHB.G7.2 differ from the regions responsible for binding to the PbACS1b promoter. Nonetheless, these interactions also disrupt the transcriptional activation of PbHB.G1 and PbHB.G2.1. These findings offer a new mechanism of ethylene biosynthesis during climacteric fruit ripening.

Predictive factors and the management of hyperglycemia in patients with acromegaly and Cushing's disease receiving pasireotide treatment: post hoc analyses from the SOM230B2219 study.

Introduction: Pasireotide, a somatostatin receptor ligand, is approved for treating acromegaly and Cushing's disease (CD). Hyperglycemia during treatment can occur because of the drug's mechanism of action, although treatment discontinuation is rarely required. The prospective, randomized, Phase IV SOM230B2219 (NCT02060383) trial was designed to assess optimal management of pasireotide-associated hyperglycemia. Here, we investigated predictive factors for requiring antihyperglycemic medication during pasireotide treatment. Methods: Participants with acromegaly or CD initiated long-acting pasireotide 40 mg/28 days intramuscularly (acromegaly) or pasireotide 600 µg subcutaneously twice daily during pre-randomization (≤16 weeks). Those who did not need antihyperglycemic medication, were managed with metformin, or received insulin from baseline entered an observational arm ending at 16 weeks. Those who required additional/alternative antihyperglycemic medication to metformin were randomized to incretin-based therapy or insulin for an additional 16 weeks. Logistic-regression analyses evaluated quantitative and qualitative factors for requiring antihyperglycemic medication during pre-randomization. Results: Of 190 participants with acromegaly and 59 with CD, 88 and 15, respectively, did not need antihyperglycemic medication; most were aged <40 years (acromegaly 62.5%, CD 86.7%), with baseline glycated hemoglobin (HbA1c) <6.5% (<48 mmol/mol; acromegaly 98.9%, CD 100%) and fasting plasma glucose (FPG) <100 mg/dL (<5.6 mmol/L; acromegaly 76.1%, CD 100%). By logistic regression, increasing baseline HbA1c (odds ratio [OR] 3.6; P=0.0162) and FPG (OR 1.0; P=0.0472) and history of diabetes/pre-diabetes (OR 3.0; P=0.0221) predicted receipt of antihyperglycemic medication in acromegaly participants; increasing baseline HbA1c (OR 12.6; P=0.0276) was also predictive in CD participants. Investigator-reported hyperglycemia-related adverse events were recorded in 47.9% and 54.2% of acromegaly and CD participants, respectively, mainly those with diabetes/pre-diabetes. Conclusion: Increasing age, HbA1c, and FPG and pre-diabetes/diabetes were associated with increased likelihood of requiring antihyperglycemic medication during pasireotide treatment. These risk factors may be used to identify those who need more vigilant monitoring to optimize outcomes during pasireotide treatment.

Sleep Patterns and Traditional Cardiovascular Health Metrics: Joint Impact on Major Adverse Cardiovascular Events in a Prospective Cohort Study.

BACKGROUND: This study examines the association between traditional cardiovascular health (CVH) metrics and major adverse cardiovascular events (MACE) incidence in individuals with diverse sleep patterns. METHODS AND RESULTS: We analyzed data from 208 621 participants initially free of cardiovascular disease (CVD) in the UK Biobank study. Sleep patterns were assessed using scores for chronotype, duration, insomnia, snoring, and daytime dozing. Traditional CVH scores were derived from the Life's Simple 7 metrics. Cox proportional hazards multivariate regression assessed associations between distinct combinations of CVH and sleep scores and MACE, including nonfatal myocardial infarction, nonfatal stroke, and CVD mortality. Over a mean follow-up of 12.73 years, 9253 participants experienced incident MACE. Individuals with both a healthy sleep pattern and ideal CVH levels had the lowest MACE risk compared with those with a poor sleep pattern and poor CVH levels (hazard ratio, 0.306 [95% CI, 0.257-0.365]; P<0.001). Elevated CVH scores were associated with a reduced risk of MACE across different sleep patterns. Similar trends were observed for individual MACE components, heart failure, and all-cause mortality. These findings remained robust in sensitivity analyses and across various subgroups. CONCLUSIONS: In individuals without known CVD, maintaining a favorable sleep pattern and achieving optimal CVH levels, as measured by traditional metrics, were associated with the lowest MACE risk. Enhanced CVH significantly reduced CVD risk, even in individuals with a poor sleep pattern. These results emphasize the importance of considering multiple dimensions of sleep health alongside CVH to mitigate CVD risk. REGISTRATION: URL: https://www.ukbiobank.ac.uk; Unique identifier: 91090.

Cardiovascular health metrics defined by Life's Essential 8 scores and subsequent macrovascular and microvascular complications in individuals with type 2 diabetes: A prospective cohort study.

AIM: To investigate the association between cardiovascular health metrics defined by Life's Essential 8 (LE8) scores and vascular complications among individuals with type 2 diabetes (T2D). MATERIALS AND METHODS: This prospective study included 11 033 participants with T2D, all devoid of macrovascular diseases (including cardiovascular and peripheral artery disease) and microvascular complications (e.g. diabetic retinopathy, neuropathy and nephropathy) at baseline from the UK Biobank. The LE8 score comprised eight metrics: smoking, body mass index, physical activity, non-high-density lipoprotein cholesterol, blood pressure, glycated haemoglobin, diet and sleep duration. Cox proportional hazards models were established to assess the associations of LE8 scores with incident macrovascular and microvascular complications. RESULTS: During a median follow-up of 12.1 years, we identified 1975 cases of incident macrovascular diseases and 1797 cases of incident microvascular complications. After adjusting for potential confounders, each 10-point increase in the LE8 score was associated with an 18% lower risk of macrovascular diseases and a 15% lower risk of microvascular complications. Comparing individuals in the highest and lowest quartiles of LE8 scores revealed hazard ratios of 0.55 (95% confidence interval 0.47-0.62) for incident macrovascular diseases, and 0.61 (95% confidence interval 0.53-0.70) for incident microvascular complications. This association remained robust across a series of sensitivity analyses and nearly all subgroups. CONCLUSION: Higher LE8 scores were associated with a lower risk of incident macrovascular and microvascular complications among individuals with T2D. These findings underscore the significance of adopting fundamental strategies to maintain optimal cardiovascular health and curtail the risk of developing diabetic vascular complications.

Effect of Chemical Composition on the Thermoplastic Formability and Nanoindentation of Ti-Based Bulk Metallic Glasses.

A series of Ti41Zr25Be34-xNix (x = 4, 6, 8, 10 at.%) and Ti41Zr25Be34-xCux (x = 4, 6, 8 at.%) bulk metallic glasses were investigated to examine the influence of Ni and Cu content on the viscosity, thermoplastic formability, and nanoindentation of Ti-based bulk metallic glasses. The results demonstrate that Ti41Zr25Be30Ni4 and Ti41Zr25Be26Cu8 amorphous alloys have superior thermoplastic formability among the Ti41Zr25Be34-xNix and Ti41Zr25Be34-xCux amorphous alloys due to their low viscosity in the supercooled liquid region and wider supercooled liquid region. The hardness and modulus exhibit obvious variations with increasing Ni and Cu content in Ti-based bulk metallic glasses, which can be attributed to alterations in atomic density. Optimal amounts of Ni and Cu in Ti-based bulk metallic glasses enhance thermoplastic formability and mechanical properties. The influence of Ni and Cu content on the hardness of Ti-based bulk metallic glasses is discussed from the perspective of the mean atomic distance.

Latent Semantic Consensus for Deterministic Geometric Model Fitting.

Estimating reliable geometric model parameters from the data with severe outliers is a fundamental and important task in computer vision. This paper attempts to sample high-quality subsets and select model instances to estimate parameters in the multi-structural data. To address this, we propose an effective method called Latent Semantic Consensus (LSC). The principle of LSC is to preserve the latent semantic consensus in both data points and model hypotheses. Specifically, LSC formulates the model fitting problem into two latent semantic spaces based on data points and model hypotheses, respectively. Then, LSC explores the distributions of points in the two latent semantic spaces, to remove outliers, generate high-quality model hypotheses, and effectively estimate model instances. Finally, LSC is able to provide consistent and reliable solutions within only a few milliseconds for general multi-structural model fitting, due to its deterministic fitting nature and efficiency. Compared with several state-of-the-art model fitting methods, our LSC achieves significant superiority for the performance of both accuracy and speed on synthetic data and real images.

Demonstration of real-time positron emission tomography biology-guided radiotherapy delivery to targets.

BACKGROUND: Biology-guided radiotherapy (BgRT) is a novel technology that uses positron emission tomography (PET) data to direct radiotherapy delivery in real-time. BgRT enables the precise delivery of radiation doses based on the PET signals emanating from PET-avid tumors on the fly. In this way, BgRT uniquely utilizes radiotracer uptake as a biological beacon for controlling and adjusting dose delivery in real-time to account for target motion. PURPOSE: To demonstrate using real-time PET for BgRT delivery on the RefleXion X1 radiotherapy machine. The X1 radiotherapy machine is a rotating ring-gantry radiotherapy system that generates a nominal 6MV photon beam, PET, and computed tomography (CT) components. The system utilizes emitted photons from PET-avid targets to deliver effective radiation beamlets or pulses to the tumor in real-time. METHODS: This study demonstrated a real-time PET BgRT delivery experiment under three scenarios. These scenarios included BgRT delivering to (S1 ) a static target in a homogeneous and heterogeneous environment, (S2 ) a static target with a hot avoidance structure and partial PET-avid target, and (S3 ) a moving target. The first step was to create stereotactic body radiotherapy (SBRT) and BgRT plans (offline PET data supported) using RefleXion's custom-built treatment planning system (TPS). Additionally, to create a BgRT plan using PET-guided delivery, the targets were filled with 18F-Fluorodeoxyglucose (FDG), which represents a tumor/target, that is, PET-avid. The background materials were created in the insert with homogeneous water medium (for S1 ) and heterogeneous water with styrofoam mesh medium. A heterogeneous background medium simulated soft tissue surrounding the tumor. The treatment plan was then delivered to the experimental setups using a pre-commercial version of the X1 machine. As a final step, the dosimetric accuracy for S1 and S2 was assessed using the ArcCheck analysis tool-the gamma criteria of 3%/3 mm. For S3 , the delivery dose was quantified using EBT-XD radiochromic film. The accuracy criteria were based on coverage, where 100% of the clinical target volume (CTV) receives at least 97% of the prescription dose, and the maximum dose in the CTV was ≤130% of the maximum planned dose (97 % ≤ CTV ≤ 130%). RESULTS: For the S1, both SBRT and BgRT deliveries had gamma pass rates greater than 95% (SBRT range: 96.9%-100%, BgRT range: 95.2%-98.9%), while in S2 , the gamma pass rate was 98% for SBRT and between 95.2% and 98.9% for BgRT plan delivering. For S3 , both SBRT and BgRT motion deliveries met CTV dose coverage requirements, with BgRT plans delivering a very high dose to the target. The CTV dose ranges were (a) SBRT:100.4%-120.4%, and (b) BgRT: 121.3%-139.9%. CONCLUSIONS: This phantom-based study demonstrated that PET signals from PET-avid tumors can be utilized to direct real-time dose delivery to the tumor accurately, which is comparable to the dosimetric accuracy of SBRT. Furthermore, BgRT delivered a PET-signal controlled dose to the moving target, equivalent to the dose distribution to the static target. A future study will compare the performance of BgRT with conventional image-guided radiotherapy.

Effect of comprehensive nursing intervention on the quality of life and clinical outcomes of patients with thyroid nodules treated by ultrasound-guided microwave ablation.

Objective: To evaluate the effects of comprehensive nursing intervention on the quality of life and clinical outcomes of patients with thyroid nodules treated by ultrasound-guided microwave ablation. Methods: This was a prospective study conducted from December 2020 to December 2022 at The Fifth Medical Center of Chinese PLA General Hospital. One hundred and twenty patients with benign thyroid nodules undergoing microwave ablation were included. Patients were randomly divided into control group and experimental group. Patients in the control group were given conventional intervention mode during the perioperative period, while those in the experimental group were given comprehensive nursing intervention mode on the basis of the control group. The differences in quality of life, cognitive level before and after intervention and satisfaction between the two groups were compared and analyzed. Results: The SF-36 scores in the experimental group were significantly higher than that in the control group after intervention. After the intervention, the SAS and SDS scores in the experimental group were significantly lower than those in the control group, with a statistically significant difference. The VAS scores in the experimental group were better than those in the control group at six, twelve and twenty four hour after operation, with statistically significant differences. After the intervention, the cognitive score of the experimental group was significantly higher than that of the control group. Conclusion: Comprehensive nursing intervention is worthy of clinical promotion in the treatment of patients with thyroid nodules treated by ultrasound-guided microwave ablation, leading to various benefits such as effectively improving patients' quality of life and relieving pain.

Efficient Gene Editing for Heart Disease via ELIP-Based CRISPR Delivery System.

Liposomes as carriers for CRISPR/Cas9 complexes represent an attractive approach for cardiovascular gene therapy. A critical barrier to this approach remains the efficient delivery of CRISPR-based genetic materials into cardiomyocytes. Echogenic liposomes (ELIP) containing a fluorescein isothiocyanate-labeled decoy oligodeoxynucleotide against nuclear factor kappa B (ELIP-NF-κB-FITC) were used both in vitro on mouse neonatal ventricular myocytes and in vivo on rat hearts to assess gene delivery efficacy with or without ultrasound. In vitro analysis was then repeated with ELIP containing Cas9-sg-IL1RL1 (interleukin 1 receptor-like 1) RNA to determine the efficiency of gene knockdown. ELIP-NF-κB-FITC without ultrasound showed limited gene delivery in vitro and in vivo, but ultrasound combined with ELIP notably improved penetration into heart cells and tissues. When ELIP was used to deliver Cas9-sg-IL1RL1 RNA, gene editing was successful and enhanced by ultrasound. This innovative approach shows promise for heart disease gene therapy using CRISPR technology.

Adaptive Relation-Aware Network for zero-shot classification.

Supervised learning-based image classification in computer vision relies on visual samples containing a large amount of labeled information. Considering that it is labor-intensive to collect and label images and construct datasets manually, Zero-Shot Learning (ZSL) achieves knowledge transfer from seen categories to unseen categories by mining auxiliary information, which reduces the dependence on labeled image samples and is one of the current research hotspots in computer vision. However, most ZSL methods fail to properly measure the relationships between classes, or do not consider the differences and similarities between classes at all. In this paper, we propose Adaptive Relation-Aware Network (ARAN), a novel ZSL approach that incorporates the improved triplet loss from deep metric learning into a VAE-based generative model, which helps to model inter-class and intra-class relationships for different classes in ZSL datasets and generate an arbitrary amount of high-quality visual features containing more discriminative information. Moreover, we validate the effectiveness and superior performance of our ARAN through experimental evaluations under ZSL and more practical GZSL settings on three popular datasets AWA2, CUB, and SUN.

Identification of a novel Scn3b mutation in a Chinese Brugada syndrome pedigree: implications for Nav1.5 electrophysiological properties and intracellular distribution of Nav1.5 and Navß3.

Background: The Scn3b gene encodes for Navß3, a pivotal regulatory subunit of the fast sodium channel in cardiomyocytes. However, its mutation status in the Chinese population suffering from Brugada Syndrome (BrS) has not been characterized, and the contributory pathophysiological mechanisms to disease pathology remain undefined. Methods and Results: A Scn3b (c.260C>T, p.P87l) mutation was identified in a patient with BrS of Chinese descent. Functional analyses demonstrated that sodium channel activation for the wild type, mutant samples, and co-expression of both commenced at -55 mv and peaked at -25 mv. The mutant group exhibited a notable reduction, approximately 60%, in peak sodium channel activation current (INa) at -25 mv. The parameters for half-maximal activation voltages (V1/2) and slope factors (k) showed no significant differences when comparing wild type, mutant, and combined expression groups (P = 0.98 and P = 0.65, respectively). Additionally, no significant disparities were evident in terms of the steady-state sodium channel inactivation parameters V1/2 and k (with P-values of 0.85 and 0.25, respectively), nor were there significant differences in the activation time constant τ (P = 0.59) and late sodium current density (P = 0.23) across the wild-type, mutant, and co-expressed groups. Confocal imaging and Western blot analysis demonstrated decreased plasma membrane localization of SCN3B and SCN5A in the P87l group. Computational simulations of cardiac action potentials suggested that SCN3B P87l can alter the morphology of the action potentials within the endocardium and epicardium while reducing the peak of depolarization. Conclusions: The pathogenic impact of the Scn3b P87l mutation predominantly originates from a reduction in peak INa activation current coupled with decreased cell surface expression of Nav1.5 and Navß3. These alterations may influence cardiac action potential configurations and contribute to the risk of ventricular arrhythmias in individuals with BrS.