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In light of the escalating global energy imperatives, mining of challenging-to-access resources, such as steeply inclined extra-thick coal seams (SIEC), has emerged as one of the future trends within the domain of energy advancement. However, there is a risk of gas and coal spontaneous combustion coupling disasters (GCC) within the goaf of SIEC due to the complex goaf structure engendered by the unique mining methodologies of SIEC. To ensure that SIEC is mined safely and efficiently, this study conducts research on the GCC within the goaf of SIEC using field observation, theoretical analysis, and numerical modeling. The results demonstrate that the dip angle, the structural dimensions in terms of width-to-length ratio, and compressive strength of the overlying rock are the key factors contributing to the goaf instability of SIEC. The gangue was asymmetrically filled, primarily accumulating within the central and lower portions of the goaf, and the filling height increased proportionally with the advancing caving height, the expansion coefficient, and the thickness of the surrounding rock formation. The GCC occurs in the goaf of SIEC, with an air-return side range of 41 m and an air-intake side range of 14 m, at the intersection area of the “”-shaped gas concentration distribution (gas explosion). The optimal nitrogen flow rate is 1000 m3/h with an injection port situated 25 m away from the working face for the highest nitrogen diffusion efficacy and lowest risk of gas explosion, coal spontaneous combustion, and GCC. It has significant engineering applications for ensuring the safe mining of SIEC threatened by the GCC.

This study examines the impact of judicial protection of intellectual property rights on firms' independent innovation. Using a staggered difference-in-differences model with panel data from Chinese manufacturing listed businesses (2014–2021) and the successive establishment of intellectual property courts in Chinese prefectural-level cities as a quasi-natural experiment, we find that establishing intellectual property courts in China encourages businesses to accumulate more technology-based intangible assets. Mechanism analysis suggests that judicial intellectual property protection enhances enterprises' independent innovation capacity by establishing a conducive institutional framework. This stimulating effect is particularly significant for industry-leading companies with technological supremacy. Heterogeneity analysis reveals that judicial intellectual property protection increases the generation of patents and trade secrets, with a more pronounced effect on firms receiving higher government research and development subsidies and better tax incentives. This study offers valuable insights for policymakers to encourage corporate independent innovation.

Microseismic source location is crucial for the early warning of rockburst risks. However, the conventional methods face challenges in terms of the microseismic wave velocity and arrival time accuracy. Intelligent techniques, such as the full convolutional neural network (FCNN), can capture spatial information but struggle with complex microseismic sequence. Combining the FCNN with the long short-term memory (LSTM) network enables better time-series signal classification by integrating multi-scale information and is therefore suitable for waveform location. The LSTM-FCNN model does not require extensive data preprocessing and it simplifies the microseismic source location through feature extraction. In this study, we utilized the LSTM-FCNN as a regression learning model to locate the seismic focus. Initially, the method of short-time-average/long-time-average (STA/LTA) arrival time picking was employed to augment spatiotemporal information. Subsequently, oversampling the on-site data was performed to address the issue of data imbalance, and finally, the performance of LSTM-FCNN was tested. Meanwhile, we compared the LSTM-FCNN model with previous deep-learning models. Our results demonstrated remarkable location capabilities with a mean absolute error (MAE) of only 7.16 m. The model can realize swift training and high accuracy, thereby significantly improving risk warning of rockbursts.

In the energy harvesting field, it is critical to efficiently convert ambient vibrations into usable electrical energy, especially under conditions characterized by low amplitude and random excitations. This study introduces a novel hybrid bistable piezoelectric energy harvester (HBPEH) designed to optimize energy conversion in challenging environmental conditions. The HBPEH features a unique piezoelectric cantilever beam integrated with a dynamic amplifier at the fixed end, significantly enhancing both rotational and lateral displacements of the beam. This innovation lowers the threshold for snap-through events, crucial for maximizing energy transfer in bistable systems, and enables superior energy harvesting capabilities. Furthermore, the HBPEH demonstrates significantly higher power outputs when subjected to excitation intensities beyond critical levels, outperforming conventional energy harvesters. Extensive numerical and theoretical analyses confirm that the HBPEH offers a promising solution for applications hindered by suboptimal energy conversion rates. Its ability to operate effectively under diverse and unpredictable excitation conditions underscores the HBPEH's robustness and superiority in advanced energy harvesting scenarios. The design improvements introduced in this study highlight the potential of the HBPEH to transform energy harvesting approaches. By addressing the limitations of traditional harvesters, the HBPEH provides enhanced efficiency and reliability, making it suitable for a broader range of practical applications in variable environmental conditions.

Rock failure can cause serious geological disasters, and the non-extensive statistical features of electric potential (EP) are expected to provide valuable information for disaster prediction. In this paper, the uniaxial compression experiments with EP monitoring were carried out on fine sandstone, marble and granite samples under four displacement rates. The Tsallis entropy q value of EPs is used to analyze the self-organization evolution of rock failure. Then the influence of displacement rate and rock type on q value are explored by mineral structure and fracture modes. A self-organized critical prediction method with q value is proposed. The results show that the probability density function (PDF) of EPs follows the q-Gaussian distribution. The displacement rate is positively correlated with q value. With the displacement rate increasing, the fracture mode changes, the damage degree intensifies, and the microcrack network becomes denser. The influence of rock type on q value is related to the burst intensity of energy release and the crack fracture mode. The q value of EPs can be used as an effective prediction index for rock failure like b value of acoustic emission (AE). The results provide useful reference and method for the monitoring and early warning of geological disasters.

Abstract In August 2022, an unprecedented compound heatwave and drought event (CHDE) lasting 24 days occurred in the Yangtze River valley (YRV), leading to a severe reduction of the crop, fresh water, and power supply. We constructed a joint cumulative probability distribution of heatwave and drought intensity, and found that the lowest probability-based index (PI) of 0.06 in 2022 was estimated as a 1-in-662-year event over the 1961–2022 climate. We then detected the fingerprint of greenhouse gas forcing to the observed PI in a generalized extreme value framework, but not the aerosol forcing, suggesting the leading contribution of greenhouse gas forcing on such extreme CHDE. Furthermore, anthropogenic influence had increased the probability of such CHDE by more than 10 times compared to the counterfactual climate. Also, the PI decreased from about 0.30 at the present climate to about 0.14 at the 3 °C global warming level, indicating that CHDE will become more extreme over YRV.

Abstract Background Non-syndromic tooth agenesis (NSTA) is a type of ectodermal dysplasia (ED) in which patients with non-syndromic oligodontia may only affect teeth. No pathological findings were found in other tissues of the ectodermal. Herein, we report a case of a NSTA patient with severe dental anxiety and poor oral health. Case presentation A 5-year-old boy without systemic diseases presented as a patient with oligodontia, extensive caries, and periapical periodontitis. Molecular genetic analysis found a mutation in the Ectodysplasin A (EDA) gene, confirming the diagnosis of NSTA. Conclusion Tooth agenesis (TA) is the most common ectodermal developmental abnormality in humans. Non-syndromic oligodontia patients often seek treatment in the department of stomatology. Because of their complex oral conditions, these patients should be provided with a systematic and personalized treatment plan.

Abstract Objectives The performance of the new Respiratory Pathogen panel (fluorescent probe melting curve, FPMC) for the qualitative detection of 12 organisms (chlamydia pneumoniae, mycoplasma pneumoniae, adenovirus, influenza A virus, influenza B virus, parainfluenza virus, rhinovirus, etc.) was assessed. Methods Prospectively collected nasopharyngeal swab (NPS) and sputum specimens (n = 635) were detected by using the FPMC panel, with the Sanger sequencing method as the comparative method. Results The overall percent concordance between the FPMC analysis method and the Sanger sequencing method was 100% and 99.66% for NPS and sputum specimens, respectively. The FPMC testified an overall positive percent concordance of 100% for both NPS and sputum specimens. The FPMC analysis method also testified an overall negative percent concordance of 100% and 99.38% for NPS and sputum specimens, respectively. Conclusions The FPMC analysis method is a stable and accurate assay for rapid, comprehensive detecting for respiratory pathogens.

This study systematically investigates the flow behavior of 7050 aluminum (Al) alloy produced via spray forming and subjected to a proposed pretreatment through thermal compression tests. The experimental findings reveal that the peak stress increased with decreasing deformation temperature or increasing strain rates. The parameters in the Arrhenius constitutive model were determined and verified by experimental results for spray formed (SFed) 7050 Al alloy. Hot deformation activation energy of the SFed 7050 Al alloy (147.38 kJ/mol) is notably lower than that of cast Al–Zn–Mg–Cu–Zr alloys, which is attributed to factors such as fine grains, low segregation, pores, and dispersed Al3Zr induced by pretreatment. Furthermore, processing maps have been constructed at various strains, revealing optimal stable deformation conditions at 300–450 °C/0.001–0.15s−1 and 425–450 °C/0.2–1s−1. Microstructural analysis of deformed samples highlights the critical role of dynamic recrystallization in influencing the stable and unstable areas of the alloy, which may be activated by high temperature and slow strain rate. The hot deformation mechanism of the SFed Al alloy is governed by interactions among η-Mg(Zn,Al,Cu)2 precipitates, dispersed Al3Zr particles, dislocation structures, and (sub-)grain boundaries.

Abstract Breast cancer has become the most common type of cancers worldwide. Its high prevalence and malignant features are associated with various environmental factors and molecules. The KH-type splicing regulatory protein (KHSRP) participates in the development of breast cancer, while the underlying mechanisms are largely unknown. In this study, we silenced KHSRP expression in MDA-MB-231 cells by small interfering RNA (siKHSRP), and then assessed its effects on cellular features. Finally, we performed whole transcriptome sequencing (RNA-seq) experiments to explore the downstream targets of KHSRP, and validated their changed pattern using quantitative polymerase chain reaction. We found KHSRP showed higher expression level and was associated with worse prognosis in breast cancer patients. In siKHSRP samples, the proliferation, invasion, and migration abilities were significantly repressed compared with negative control (NC) samples, while the apoptosis level was increased. By investigating the RNA-seq data, we found KHSRP globally regulates the expression and alternative splicing profiles of MDA-MB-231 cells by identifying 1632 differentially expressed genes (DEGs) and 1630 HKSRP-regulated AS events (RASEs). Functional enriched analysis of DEGs demonstrated that cilium assembly and movement and extracellular matrix organization pathways were specifically enriched in up DEGs, consistent with the repressed migration and invasion abilities in siKHSRP cells. Interestingly, the cell cycle and DNA damage and repair associated pathways were enriched in both down DEGs and RASE genes, suggesting that KHSRP may modulate cell proliferation by regulating genes in these pathways. Finally, we validated the changed expression and AS patterns of genes in cell cycle and DNA damage/repair pathways. Expression levels of BIRC5, CCNA2, CDK1, FEN1, FOXM1, PTTG1, and UHRF1 were downregulated in siKHSRP samples. The AS patterns of PARK7, ERCC1, CENPX, and UBE2A were also dysregulated in siKHSRP samples and confirmed PCR experiments. In summary, our study comprehensively explored the downstream targets and their functions of KHSRP in breast cancer cells, highlighting the molecular mechanisms of KHSRP on the oncogenic features of breast cancer. The identified molecular targets could be served as potential therapeutic targets for breast cancer in future.

Abstract Background Acupuncture is a method for treating tic disorder. However, there is a lack of sufficient clinical objective basis in regards of its treatment efficacy. Indeed, there are structural abnormalities present in energy metabolism and infrared thermography in children with tic disorder. Therefore, this study proposes a clinical trial scheme to explore the possible mechanism of acupuncture in treating tic disorder. Methods This randomized controlled trial will recruit a total of 90 children, in which they will be divided into non-intervention group and intervention group. The non-intervention group consists of 30 healthy children while the intervention group consists of 60 children with tic disorder. The intervention group will be randomly allocated into either the treatment group or the control group, with 30 children randomly assigned in each group. Children either received acupuncture treatment and behavioral therapy (treatment group) or sham acupuncture treatment and behavioral therapy (control group), 3 treatment sessions per week for a period of 12 weeks, with a total of 36 treatment sessions. Outcome measures include YGTSS, urinary and fecal metabolomics, infrared thermography of body surface including governor vessel. For the intervention group, these outcome measures will be collected at the baseline and 90th day prior to intervention. Whereas for the non-intervention group, outcome measures (excluding YGTSS) will be collected at the baseline. Discussion The main outcome will be to observe the changes of the severity of tic condition, the secondary outcome will be to observe the changes of structural characteristic of infrared thermography of body surface/acupoints along the governor vessel and to evaluate the changes of urinary and fecal metabolomics at the end of the treatment, so as to analyze the relationship between them and to provide further knowledge in understanding the possible mechanism of acupuncture in improving the clinical symptoms via regulating and restoring the body metabolomics network, which in future it can develop as a set of clinical guideline (diagnosis, treatment, assessment, prognosis) in treating tic disorder. ChiCTR2300075188(Chinese Clinical Trial Registry, http://www.chictr.org.cn , registered on 29 August 2023).

BackgroundMinimally invasive techniques have significantly gained popularity for hepatocellular carcinoma (HCC) based on the Milan criteria. However, whether or not laparoscopic liver resection (LLR) or radiofrequency ablation (RFA) is a better treatment option remains debatable. We conducted a meta-analysis to review the published data comparing LLR and RFA for HCC through Milan criteria depending on tumor recurrence risk and survival.MethodsPubMed, OvidSP, Web of Science, and Cochrane Library databases were searched from inception to December 31, 2023. The studies comparing the outcomes and methods between LLR and RFA for HCC within the Milan criteria were included.ResultsWe recruited 19 cohort studies with 2532 patients. The postoperative complication rate was low, and hospital stays were shorter in the RFA group than in the LLR group. The total tumor recurrence, the local tumor recurrence rate, and the intrahepatic tumor recurrence rate were lower within the LLR group than in the RFA group. There was no significant difference in the extrahepatic recurrence rate between the two groups. Moreover, no significant differences were observed between the groups concerning 1-, 3-, and 5-year overall survival (OS) and 1-year recurrence-free survival (RFS). However, 3-year and 5-year RFS were better within the LLR group than among the RFA group.ConclusionsThe treatment of HCC within the Milan criteria is moving toward multidisciplinary and minimally invasive approaches. Our meta-analysis identified a lower postoperative complication rate and higher recurrence rate for RFA than LLR. RFA could be an alternative treatment due to its comparable long-term efficacy with LLR.

IntroductionJapanese encephalitis virus (JEV) and Zika virus (ZIKV) pose a severe threat to human health. Our previous research results, as well as those of other research groups, indicated that antibodies (Abs) induced by JEV infection or JEV vaccine vaccination could enhance ZIKV infection in vitro and exacerbate the mortality of ZIKV-infected mice, vice versa, which is known as antibody-dependent enhancement (ADE). Although studies on other flaviviruses revealed that altering the amino acid residues located in the fusion loop (FL) of envelope (E) protein can reduce the level of flavivirus-cross-reactive Abs, thereby abating the ADE of heterologous flavivirus infection, it is unclear whether this strategy is equally applicable to JEV.MethodsIn this study, we constructed recombinant adenoviruses and nucleotide-modified mRNA-lipid nanoparticle (LNP) encoding JEV wild-type E protein or E protein mutant (designated as Ad5-JEV-EWT and Ad5-JEV-Emut; JEV-EWT mRNA-LNP, and JEV-Emut mRNA-LNP). We evaluated the immunogenicity of these vaccine candidates in mice and the capacity of vaccine-immune mouse sera to neutralize JEV infection or mediate ADE of ZIKV infection in vitro and in vivo.ResultsAd5-JEV-Emut or JEV-Emut mRNA-LNP immunization induced ZIKV-cross-reactive Ab response which is dramatically lower than that induced by Ad5-JEV-EWT and JEV-EWT mRNA-LNP, respectively. The levels of JEV-neutralizing Abs induced by Ad5-JEV-Emut or JEV-Emut mRNA-LNP are comparable to that induced by Ad5-JEV-EWT and JEV-EWT mRNA-LNP, respectively. The ability of Abs induced by Ad5-JEV-Emut to enhance ZIKV infection in vitro is attenuated as compared with that induced by Ad5-JEV-EWT. Moreover, JEV-Emut mRNA-LNP immunization elicited potent T cell response similar to JEV-EWT mRNA-LNP in mice. Mice immunized with each mRNA-LNP exhibited lower level of serum viral load than the mock-immunized mice post JEV challenge. Mice receiving JEV-EWT mRNA-LNP-immune mouse sera exhibited ADE post ZIKV challenge whereas passively transferred JEV-Emut mRNA-LNP-immune mouse sera did not lead to obvious ADE of ZIKV infection in recipient mice. Most importantly, maternally acquired Abs did not enhance the mortality of 1-day-old neonates born to JEV-Emut mRNA-LNP-immunized mice post ZIKV challenge.DiscussionThese results suggest that optimizing the FL sequence of JEV could significantly reduce the level of JEV/ZIKV-cross-reactive Abs and abrogate the ADE of ZIKV infection, providing a promising strategy to develop effective and safety JEV vaccine.

Purpose: To evaluate the efficacy of retinal massage combined with autologous blood covering in the treatment of persistent macular holes following vitrectomy in eyes with high myopia. Settings and Design: Retrospective, consecutive case series in a tertiary eye center. Methods: A total of 12 highly myopic eyes with persistent macular holes after vitrectomy and internal limiting membrane peeling received combined retinal massage, air/fluid exchange, autologous blood covering, and gas/silicone oil tamponade. Best-corrected visual acuity, axial length, and optical coherence tomographic images before and after the treatment were compared. Results: The mean hole diameter before this intervention was 931.58 ± 244.58 μm (range, 508–1270), and the axial length was 30.39 ± 2.13 mm (range, 27.08–34.64). During the 6-month follow-up period, hole closure was achieved in eight eyes (66.67%). The mean best-corrected visual acuity improved significantly from 1.40 ± 0.50 logarithm of the minimum angle of resolution (logMAR) at baseline to 1.10 ± 0.30 logMAR (P < 0.05). No complications were observed. Conclusions: Combined retinal massage and autologous blood covering, which is easy to manipulate, can promote the closure of persistent macular holes after vitrectomy and improve vision in high myopia with an axial length less than 29 mm.

This research aimed to enhance the strength and ductility of spray formed (SFed) 7050 aluminum (Al) alloy through hot extrusion and subsequent heat treatment. Microstructure and mechanical properties evolution during these processes were investigated. It was found that the low densification of the SFed 7050 Al alloy due to various defects such as pores, with an average size of 7.6 μm and an area fraction of 3.7 % could be notably enhanced by hot extrusion, even achieving a level close to theoretical density. This process led to a transformation of grains from equiaxed to elongated shapes along extrusion direction and significant grain refinement, exhibiting a strong fiber texture. While the employed extrusion ratio exceeds 16 with proper heat treatment, the SFed 7050 Al alloys achieves superior strength-ductility combination compared with reported Al alloys. The achieved high performance should be attributed to the grain refinement, strong texture and high densification that suppress defect-induced plastic instability. Furthermore, the combination of hot extrusion and heat treatment, provides an effective way to enhance strength and ductility for SFed 7050 Al alloy.

Over the past few years, a growing number of researchers have dedicated their efforts to focusing on temporal modeling. The advent of transformer-based methods has notably advanced the field of 2D image-based vision tasks. However, with respect to 3D video tasks such as action recognition, applying temporal transformations directly to video data significantly increases both computational and memory demands. This surge in resource consumption is due to the multiplication of data patches and the added complexity of self-aware computations. Accordingly, building efficient and precise 3D self-attentive models for video content represents as a major challenge for transformers. In our research, we introduce an Long and Short-term Temporal Difference Vision Transformer (LS-VIT). This method incorporates short-term motion details into images by weighting the difference across several consecutive frames, thereby equipping the original image with the ability to model short-term motions. Concurrently, we integrate a module designed to understand long-term motion details. This module enhances the model's capacity for long-term motion modeling by directly integrating temporal differences from various segments via motion excitation. Our thorough analysis confirms that the LS-VIT achieves high recognition accuracy across multiple benchmarks (e.g., UCF101, HMDB51, Kinetics-400). These research results indicate that LS-VIT has the potential for further optimization, which can improve real-time performance and action prediction capabilities.

AimThyroid dysfunction is closely associated with periodontitis. We aim to explore the association between sensitivity to thyroid hormones (THs) and periodontitis and to investigate the mediating role of serum 25-hydroxyvitamin D[25(OH)D] in this relationship in Chinese euthyroid populations.MethodsThis population-based retrospective study included 2,530 euthyroid participants. Central sensitivity to THs was assessed by the thyroid feedback quantile-based index (TFQI), parametric thyroid feedback quantile-based index (PTFQI), thyrotrophic thyroxine resistance index (TT4RI) and thyroid-stimulating hormone index (TSHI), while FT3/FT4 was evaluated to assess peripheral sensitivity. Multivariable regression analysis and restricted cubic spline were performed to explore the association between sensitivity to THs and periodontitis. Threshold effect and subgroup analysis were also conducted. Mediation analysis was performed to estimate direct and indirect effects through 25(OH)D.ResultsMultivariable regression analysis indicated that central sensitivity to THs indices(per SD increase) were positively associated with periodontitis risk [TFQI: OR=1.19,95% CI (1.09, 1.31); PTFQI: OR=1.22, 95% CI(1.12,1.34); TSHI: OR=1.36, 95% CI (1.21,1.52); TT4RI: OR=1.43, 95% CI (1.25,1.63)](all P value

Instructional image editing has received a significant surge of attention recently. In this work, we are interested in the challenging problem of instructional image editing within the particular fashion realm, a domain with significant potential demand in both commercial and personal contexts. This specific domain presents heightened challenges owing to the stringent quality requirements. It necessitates not only the creation of vivid details in alignment with instructions, but also the preservation of precise attributes unrelated to the text guidance. Naive extensions of existing image editing methods produce noticeable artifacts. In order to achieve high-fidelity fashion editing, we propose a novel framework, leveraging the generative prior of a pre-trained human generator and performing edit in the latent space. In addition, we introduce a novel CLIP-based loss to better align the generated target with the instruction. Extensive experiments demonstrate that our approach outperforms prior works including GAN-based editing as well as diffusion-based editing by a large margin, showing impressive visual quality.

As the negative repercussions of environmental devastation, such as air quality decline and air pollution, become more apparent, environmental consciousness is growing across the world, forcing nations to take steps to mitigate the damage. China pledged to achieve air quality improvement goal to combat global environment issue, yet the spatial-temporal differentiation and its driving factors of environment-meteorology-economic index for air quality are not fully analysed. To promote regional collaborative control of air pollution and achieve sustainable urban development, spatial and temporal different and its driving factors of air quality in Shandong Province during 2013–2020. Results revealed that concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), and carbon monoxide (CO-95per) exhibited decreasing trend (SO2 concentrations decreasing 84 % and CO-95per concentrations decreasing 90 %). Air quality was improved from inland areas to coastal areas. Pollutant indicators of SO2, NO2, PM10, PM2.5, and CO-95per demonstrated significant positive correlation (P < 0.05). Air temperature and precipitation are significantly negatively correlated with concentrations of SO2, NO2, PM10, PM2.5, and CO-95per but significantly positively correlated with ozone (O3-8 h). SO2, NO2, PM2.5, PM10, CO-95per, and proportion of days with heavy pollution are strongly positively correlated with proportion of secondary industry but strongly negatively correlated with proportion of tertiary industry and volume of household waste. Except for O3-8 h, pollutant index of Provincial Capital Economic Circle (PCEC) and Southern Shandong Economic Circle (SSEC) has significant negative correlation (P < 0.05) with regional gross domestic product and investment in environmental protection; however, investment in environmental protection of Eastern Shandong Economic Circle (ESEC) has no significant correlation with air pollution index. There was significant negative correlation between vegetable sowing area and SSEC pollutant index. The relationship between pollution emission and investment in environmental protection has shifted from high pollution-low investment to low pollution-low investment in PCEC, ESEC and SSEC, and the inflection point was in 2020 for PCEC, 2019 for ESEC, and 2020 for SSEC. Those results provide empirical evidence and theoretical support for the improvement of regional air quality, aiming to achieve high-quality development. According to these findings, it has been found that meteorological elements, pollutant emission, socio-economic factors and agricultural data affect air quality. Those results could provide meaningful and significant supporting for synergistic regulation of diverse pollutants.

Background: Drug-resistant epilepsy (DRE) affects approximately one-third of epilepsy patients who do not achieve adequate seizure control with medication. Vagus nerve stimulation (VNS) is an adjunctive therapy for DRE, but its long-term effects on cortical excitability remain unclear. Objectives: This study aims to elucidate the long-term effects of VNS on electroencephalography (EEG) aperiodic components in patients with DRE. Our objective is to identify biomarkers that can serve as indicators of therapeutic efficacy and provide mechanistic insights into the underlying neural processes. Design: This longitudinal observational study focused on patients with DRE undergoing VNS therapy at Sanbo Brain Hospital. The reduction in seizure frequency rates was quantified over short-term (⩽1 year), medium-term (1–3 years), and long-term (⩾3 years) intervals to assess the therapeutic efficacy of VNS. Both the periodic and aperiodic components of EEG data were analyzed. Methods: Advanced signal processing techniques were utilized to parameterize the periodic and aperiodic components of EEG data, focusing particularly on “offset” and “exponent.” These measures were compared before and after VNS therapy. Correlation analyses were conducted to explore the relationship between these EEG parameters and clinical outcomes. Results: In all, 18 patients with DRE participated in this study. During the long-term follow-up period, the responder rate was 55.56%. Significant decreases were observed in aperiodic offset ( p = 0.022) and exponent ( p = 0.039) among responders. The impact of age on these results was not significant. Correlation analyses revealed a negative association between therapeutic efficacy and a decrease in offset ( R = −0.546, p = 0.019) and exponent ( R = −0.636, p = 0.019). Conclusion: EEG aperiodic parameters, including offset and exponent, have the potential to serve as promising biomarkers for evaluating the efficacy of VNS. An understanding of the regulatory influence of VNS on cortical excitability through these aperiodic parameters could provide a basis for the development of more effective stimulation parameters and therapeutic strategies.

ObjectiveNanotechnology offers many advantages in various fields of cancer therapy. This study describes a new method of self-forming nanoparticles (self-nano) using ferric chloride (FeCl₃) and hydrogen peroxide (H2O2) to form the self-nanoparticles in an in vivo tumor. The treatment effect is evaluated.MethodA solution of 3% FeCl3 (0.5 mL) and 1.8% H2O2 (1.0 mL) was injected into the tumor. At various time points post-injection, tumors were collected, and sections were prepared for electron microscopy to evaluate the size of the self-nano particles. Single-cell RNA sequencing (scRNA-seq) was used to analyze the immune changes and their effect on tumor growth.ResultThe formation of self-nano in vitro was observed and confirmed, with particles averaging 421 nm in size for the FeCl3 + H2O2 solution. Over time points ranging from 1 to 14 days, the formed self-nano remained stable at a regular size of 421 ± 8 nm. The self-nano, primarily consisting of iron, induced ferroptosis under the influence of an external magnetic field, leading to tumor growth control through iron-induced cell death and immune reactions. These self-nanoparticles also showed stronger enrichment of pathways related to CD8+ T effect cells (Teff), T cell activation, and regulation of T cell proliferation.ConclusionThe FeCl3 + H2O2 solution can form Fe₂O₃-based self-nanoparticles within tumors through H2O2-incubated oxidation of FeCl3. The self-nano remains effective for over 14 days, inducing ferroptosis and upregulating immune cells under magnetic field treatment. This method offers a novel approach for cancer treatment that can be combined with other modalities.

Objectives: Heparanase (HPSE), an endoglycosidase that cleaves heparan sulfate, regulates various biological processes related to tumor progression. We explore the prognostic value of HPSE and its relationship with immunotherapy response in patients with breast cancer, to improve the effectiveness of immunotherapy and increase the survival outcomes. Methods: In the study, we explored the prognostic value of HPSE through the The Cancer Genome Atlas (TCGA) database. By using the single-sample gene set enrichment analysis ( ssGSEA) method, we measured the infiltration levels of 24 immune cell types in the tumor microenvironment. Cancer Therapeutics Response Portal (CTRP) and PRISM datasets provide the area under the dose-response curve (AUC) to measure drug sensitivity. Using nomograms, we predicted overall survival ability. In vivo studies, we investigated the relationship between HPSE and immune checkpoint proteins and pro-inflammatory cytokines by immunohistochemistry of Triple-Negative Breast Cancer tumors in mice. Results: Our model demonstrated that the integrating of HPSE with the clinical stage effectively predicts patients’ survival time, highlighting high HPSE expression as a prognostic risk factor for breast cancer. Then the Receiver Operating Characteristic (ROC) curve [AUC of 1 year = 0.747, AUC of 3 years = 0.731] and Decision Curve Analysis (DCA) curve illustrated the satisfactory discriminative capacity of our model, emphasizing its valuable clinical applicability. Immune-related results showed that HPSE correlates strongly with immune infiltrating cells, immune-related genes, and the anti-cancer immunity cycle. In vivo studies have demonstrated that HPSE in breast cancer is associated with increased expression of immune checkpoint proteins CD274 and cytotoxic T lymphocyte-associated protein 4 (CTLA-4) and is positively correlated with the pro-inflammatory cytokine TNF-α. Meanwhile, we analyzed the 11 types of drugs that are sensitive to the HPSE gene. Conclusion: Our results show that HPSE can serve as an effective biomarker to predict the prognosis of breast cancer patients and reflect the impact of immunotherapy.

The Yangtze River basin experienced record-breaking high temperatures in July–August 2022, leading the China Meteorological Administration to issue its first ever “red heat warning”. We use simulations from the Detection and Attribution Model Intercomparison Project (DAMIP) of the Coupled Model Intercomparison Project 6 (CMIP6) to investigate the role of anthropogenic drivers in this extreme event. We have demonstrated that the strong Western Pacific Subtropical High (WPSH), attributed to internal variability, serves as the clear proximate driver for such extreme event, whether in the factual world or in the counterfactual world. When considering similar circulation patterns in 2022, the results show that anthropogenic forcing has contributed to the 2022-like heatwave by a factor about 7 compared to natural forcing under the present climate of the past 30 years. Specifically, the anthropogenic greenhouse gases made the event about 10 times more likely, while anthropogenic aerosols had negative effect. The results were similar but differed in exact contribution values when specific circulation regimes of 2022 were not considered. In general, global warming caused by anthropogenic activities has made extreme summer heatwaves far more frequent, especially in recent decades.

Abstract Background Individuals may be more likely to engage in NSSI due to negative cognitive bias, while the use of negative emotional regulation mechanisms may further contribute to NSSI. Currently, there is a dearth of studies regarding the correlation among the three variables. Method The study employed convenience sampling to collect data via online platforms from a total of 572 college students in Harbin, Heilongjiang Province, China, over the period of January 2024 to February 2024. The questionnaires comprise the Non-Adaptive Cognitive Emotion Srategy Regulation Subscale, the Negative Cognitive Processing Bias Questionnaire, and the NSSI Questionnaire. Outcome Negative cognitive bias significantly and directly influences NSSI, as indicated by a beta coefficient of 0.3788 and a confidence interval of [0.2878, 0.4698]. The existence of negative cognitive bias significantly enhances the impact of non-adaptive cognitive emotion control approaches (β = 0.5613, CI [0.4808, 0.6418]). Non-adaptive cognitive emotion regulation strategies showed a significant effect on NSSI, as indicated by a beta coefficient of 0.2033 and a confidence interval of [0.0942, 0.3125]. The non-adaptive cognitive emotion control strategy serves as an intermediary between negative cognitive bias and NSSI, explaining 30.12% of the overall impact. In conclusion The results demonstrate that non-adaptive cognitive emotion regulation strategies play a partially moderating role in the relationship between negative cognitive bias and NSSI among nursing students. We emphasize the importance of non-adaptive cognitive emotion regulation strategies, negative cognitive biases, and NSSI among nursing students. In order to reduce the occurrence of NSSI, it is important for schools, families, and teachers to work together closely and implement a well-organized and efficient intervention to protect the mental well-being of nursing students.

Abstract Inorganic semiconductors typically have limited p-type behavior due to the scarcity of holes and the localized valence band maximum, hindering the progress of complementary devices and circuits. In this work, we propose an inorganic blending strategy to activate the hole-transporting character in an inorganic semiconductor compound, namely tellurium-selenium-oxygen (TeSeO). By rationally combining intrinsic p-type semimetal, semiconductor, and wide-bandgap semiconductor into a single compound, the TeSeO system displays tunable bandgaps ranging from 0.7 to 2.2 eV. Wafer-scale ultrathin TeSeO films, which can be deposited at room temperature, display high hole field-effect mobility of 48.5 cm2/(Vs) and robust hole transport properties, facilitated by Te-Te (Se) portions and O-Te-O portions, respectively. The nanosphere lithography process is employed to create nanopatterned honeycomb TeSeO broadband photodetectors, demonstrating a high responsibility of 603 A/W, an ultrafast response of 5 μs, and superior mechanical flexibility. The p-type TeSeO system is highly adaptable, scalable, and reliable, which can address emerging technological needs that current semiconductor solutions may not fulfill.

Abstract A key strategy for designing environmental barrier coatings is to incorporate multiple rare-earth (RE) components into β- and γ-RE2Si2O7 to achieve multifunctional performance optimization. However, the polymorphic phase presents significant challenges for the design of multicomponent RE disilicates. Here, employing decision fusion, a machine learning (ML) method is crafted to identify multicomponent RE disilicates, showcasing notable accuracy in prediction. The well-trained ML models evaluated the phase formation capability of 117 (RE10.25RE20.25Yb0.25Lu0.25)2Si2O7 and (RE11/6RE21/6RE31/6Gd1/6Yb1/6Lu1/6)2Si2O7, which are unreported in experiments and validated by first-principles calculations. Utilizing model visualization, essential factors governing the formation of (RE10.25RE20.25Yb0.25Lu0.25)2Si2O7 are pinpointed, including the average radius of RE3+ and variations in different RE3+ combinations. On the other hand, (RE11/6RE21/6RE31/6Gd1/6Yb1/6Lu1/6)2Si2O7 must take into account the average mass and the electronegativity deviation of RE3+. This work combines material-oriented ML methods with formation mechanisms of multicomponent RE disilicates, enabling the efficient design of superior materials with exceptional properties for the application of environmental barrier coatings.

Insulators are crucial insulation components and structural supports in power grids, playing a vital role in the transmission lines. Due to temperature fluctuations, internal stress, or damage from hail, insulators are prone to injury. Automatic detection of damaged insulators faces challenges such as diverse types, small defect targets, and complex backgrounds and shapes. Most research for detecting insulator defects has focused on a single defect type or a specific material. However, the insulators in the grid's transmission lines have different colors and materials. Various insulator defects coexist, and the existing methods have difficulty meeting the practical application requirements. Current methods suffer from low detection accuracy and mAP0.5 cannot meet application requirements. This paper proposes an improved you only look once version 7 (YOLOv7) model for multi-type insulator defect detection. First, our model replaces the spatial pyramid pooling cross stage partial network (SPPCSPC) module with the receptive filed block (RFB) module to enhance the network's feature extraction capability. Second, a coordinate attention (CA) mechanism is introduced into the head part to enhance the network's feature representation ability and to improve detection accuracy. Third, a wise intersection over union (WIoU) loss function is employed to address the low-quality samples hindering model generalization during training, thereby improving the model's overall performance. The experimental results indicate that the proposed model exhibits enhancements across various performance metrics. Specifically, there is a 1.6% advancement in mAP_0.5, a corresponding 1.6% enhancement in mAP_0.5:0.95, a 1.3% elevation in precision, and a 1% increase in recall. Moreover, the model achieves parameter reduction by 3.2 million, leading to a decrease of 2.5 GFLOPS in computational cost. Notably, there is also an improvement of 2.81 milliseconds in single-image detection speed. This improved model can detect insulator defects for diverse materials, color insulators, and partial damage shapes in complex backgrounds.

Abstract Background Sleep quality may be related to benign prostatic hyperplasia (BPH), however causal associations have not been established. This study aimed to evaluate causal relationships between six sleep traits ([i] day time napping, [ii] daytime sleepiness, [iii] insomnia, [iv] long sleep duration, [v] short sleep duration, and [vi] sleep duration per hour) and BPH through a bidirectional Mendelian randomization (MR) study. Methods Genome-wide association summary statistics of sleep traits and BPH were downloaded from public databases. Inverse variance weighting (IVW) was used as the main approach for causal inference. For causal estimates identified by IVW, various sensitivity analyses were performed to assess the reliability of the results: (i) four additional MR methods to complement IVW; (ii) Cochran’s Q test to assess heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test to assess horizontal pleiotropy; and (iv) leave-one-out method to assess stability. Results Forward MR analyses indicated that genetically predicted insomnia symptom significantly increased BPH risk (OR = 1.267, 95% CI: 1.003–1.601, P = 0.048), while reverse MR analyses identified that genetically predicted liability to BPH significantly increased the incidence of insomnia (OR = 1.026, 95% CI: 1.000-1.052, P = 0.048). In a replicate MR analysis based on summary statistics including exclusively male participants, the finding of increased risk of BPH due to genetically predicted insomnia symptom was further validated (OR = 1.488, 95% CI: 1.096–2.022, P = 0.011). No further causal links were identified. In addition, sensitivity tests demonstrated the reliability of the MR results. Conclusion This study identified that a higher prevalence of genetically predicted insomnia symptoms may significantly increase the risk of BPH, while genetically predicted liability to BPH may in turn increase the incidence of insomnia symptom. Therefore, improving sleep quality and reducing the risk of insomnia could be a crucial approach for the prevention of BPH.

Abstract Background High-mobility group B1 (HMGB1) is both a DNA binding nuclear factor modulating transcription and a crucial cytokine that mediates the response to both infectious and noninfectious inflammation such as autoimmunity, cancer, trauma, and ischemia reperfusion injury. HMGB1 has been proposed to control ribosome biogenesis, similar as the other members of a class of HMGB proteins. Results Here, we report that HMGB1 selectively promotes transcription of genes involved in the regulation of transcription, osteoclast differentiation and apoptotic process. Improved RNA immunoprecipitation by UV cross-linking and deep sequencing (iRIP-seq) experiment revealed that HMGB1 selectively bound to mRNAs functioning not only in signal transduction and gene expression, but also in axon guidance, focal adhesion, and extracellular matrix organization. Importantly, HMGB1-bound reads were strongly enriched in specific structured RNAs, including the domain II of 28S rRNA, H/ACA box snoRNAs including snoRNA63 and scaRNAs. RTL-P experiment showed that overexpression of HMGB1 led to a decreased methylation modification of 28S rRNA at position Am2388, Cm2409, and Gm2411. We further showed that HMGB1 overexpression increased ribosome RNA expression levels and enhanced protein synthesis. Conclusion Taken together, our results support a model in which HMGB1 binds to multiple RNA species in human cancer cells, which could at least partially contribute to HMGB1-modulated rRNA modification, protein synthesis function of ribosomes, and differential gene expression including rRNA genes. These findings provide additional mechanistic clues to HMGB1 functions in cancers and cell differentiation.

Abstract Gastric cancer is a highly prevalent disease that poses a serious threat to public health. In clinical practice, gastroscopy is frequently used by medical practitioners to screen for gastric cancer. However, the symptoms of gastric cancer at different stages of advancement vary significantly, particularly in the case of early gastric cancer (EGC). The manifestations of EGC are often indistinct, leading to a detection rate of less than 10%. In recent years, researchers have focused on leveraging deep learning algorithms to assist medical professionals in detecting EGC and thereby improve detection rates. To enhance the ability of deep learning to detect EGC and segment lesions in gastroscopic images, an Improved Mask R-CNN (IMR-CNN) model was proposed. This model incorporates a “Bi-directional feature extraction and fusion module” and a “Purification module for feature channel and space” based on the Mask R-CNN (MR-CNN). Our study includes a dataset of 1120 images of EGC for training and validation of the models. The experimental results indicate that the IMR-CNN model outperforms the original MR-CNN model, with Precision, Recall, Accuracy, Specificity and F1-Score values of 92.9%, 95.3%, 93.9%, 92.5% and 94.1%, respectively. Therefore, our proposed IMR-CNN model has superior detection and lesion segmentation capabilities and can effectively aid doctors in diagnosing EGC from gastroscopic images.

Abstract Background Given the importance of perceptions of decent work for nursing students' future career choices, we attempted to determine potential classifications and characteristics of nursing students' perceptions of decent work so that targeted interventions could be developed. Methods A convenience sample of 1004 s- to fourth-year nursing students completed the General Information Questionnaire, Self-Regulatory Fatigue Scale, Occupational Identity Questionnaire, and Decent Work Perceptions Scale in a cross-sectional survey in Heilongjiang Province, China, resulting in 630 valid questionnaires with a valid return rate of 62.75%. Nursing students' perceptions of decent work were defined using descriptive and regression analysis. Results Latent profile analysis (LPA) identified three subgroups: low perceived decent work group, medium perceived decent work group, and high perceived decent work group, accounting for 4.76%, 69.37%, and 25.87% of the sample, respectively. The results of unordered multiclass logistic regression show that nursing students with relatively low levels of perceived decent work are more likely to have a low professional identity, a lack of respect for nursing seniors, an involuntary choice of nursing major, and a low family income. Conclusion Different types of nursing students have different perceptions of decent work, and these universities and related departments can use different educational guidance strategies.

Abstract Background Clinical nurses play an important role in ensuring patient safety. Nurses’ work experience, organizational environment, psychological cognition, and behavior can all lead to patient safety issues. Improving nurses’ attention to patient safety issues and enhancing their competence in dealing with complex medical safety issues can help avoid preventable nursing adverse events. Therefore, it is necessary to actively identify the latent profiles of patient safety competency of clinical nurses and to explore the influencing factors. Methods A cross-sectional design was conducted. A total of 782 Chinese registered nurses were included in the study. Demographic characteristics questionnaire, Error Management Climate scale, Security Questionnaire, Proactive Behavior Performance scale and Patient Safety Competency Self-Rating Scale of Nurses were used. Latent profile analysis (LPA) was performed to categorize nurses into latent subgroups with patient safety competency differences. Multinomial logistic regression was conducted to explore the influencing factors of nurses’ patient safety competency (PSC) in different latent profiles. Results A total of 782 questionnaires were valid. Nurses’ PSC was positively related to error management climate, and psychological safety and proactive behavior. The PSC score was 121.31 (SD = 19.51), showing that the PSC of clinical nurses was at the level of the medium on the high side. The error management climate score was 70.28 (SD = 11.93), which was at a relatively high level. The psychological safety score was 61.21 (SD = 13.44), indicating a moderate to low level. The proactive behavior score was 37.60 (SD = 7.33), which was at a high level. The latent profile analysis result showed that three groups of profile models were fitted acceding to the evaluation of PSC. They were defined as Low-competency Group (74 (9.5%)), Medium-competency Group (378 (48.3%)) and High-competency Group (330 (42.2%). Working years, professional titles, departments, error management climate, psychological security and proactive behavior were the influencing factors of PSC in three latent profiles. Conclusions The PSC of clinical nurses had obvious classification characteristics, and the main influencing factors were working years, professional titles, working departments, error management climate, psychological security and proactive behavior. This study suggests that managers should pay attention to the continuous cultivation of patient safety competence among clinical nurses, provide targeted intervention measures for nurses at different work stages, professional titles, and departments, and use efficient management strategies to create a positive error management atmosphere. In patient safety management, providing nurses with more psychological security is conducive to stimulating more proactive behaviors and continuously improving the level of patient safety competence.

Abstract Hepatocellular carcinoma (HCC) remains a formidable malignancy that significantly impacts human health, and the early diagnosis of HCC holds paramount importance. Therefore, it is imperative to develop an efficacious signature for the early diagnosis of HCC. In this study, we aimed to develop early HCC predictors (eHCC-pred) using machine learning-based methods and compare their performance with existing methods. The enhancements and advancements of eHCC-pred encompassed the following: (i) utilization of a substantial number of samples, including an increased representation of cirrhosis tissues without HCC (CwoHCC) samples for model training and augmented numbers of HCC and CwoHCC samples for model validation; (ii) incorporation of two feature selection methods, namely minimum redundancy maximum relevance and maximum relevance maximum distance, along with the inclusion of eight machine learning-based methods; (iii) improvement in the accuracy of early HCC identification, elevating it from 78.15 to 97% using identical independent datasets; and (iv) establishment of a user-friendly web server. The eHCC-pred is freely accessible at http://www.dulab.com.cn/eHCC-pred/ . Our approach, eHCC-pred, is anticipated to be robustly employed at the individual level for facilitating early HCC diagnosis in clinical practice, surpassing currently available state-of-the-art techniques.

Recycling precious metals with high-efficiency is undoubtedly beneficial to optimize resource utilization for environmental remediation and sustainable development. Herein, we report an efficient route to recycle the palladium (Pd) and platinum (Pt) electrocatalysts using a phase transfer method. This strategy involves acidic dissolution of deactivated precious metal (Pd/Pt) electrocatalysts from their loading substrates, mixing with an ethanolic solution of dodecylamine (DDA), subsequent extraction of metal ions into a non-polar organic phase, and final reduction by sodium borohydride to reproduce high-performance electrocatalysts towards typical electrochemical reactions, e.g., oxygen reduction reaction (ORR) and ethanol oxidation reaction (EOR). In specific, the transfer efficiencies are up to 98% and the final recovery rate is over 85% for Pd and Pt electrocatalysts in each cycle. This approach symbolizes a facile and efficient way to recover precious metals, which might be applied to recycling a wide range of metals in various realms after appropriate modifications.

Hydrogen removal from particle-reinforced Al composite is critical for preventing porosities near particle clusters and improving comprehensive material properties. This study investigated the effects of different argon flow schemes and power ultrasound on bubble dispersion in water. Based on similarity theory, the optimal argon flow scheme for ultrasonic-assisted argon (UAA) treatment was identified and applied to TiB2/2024 Al composite to explore the degassing mechanism. Three argon flow schemes for UAA treatment: EV-EC (External ventilation, equal channel), IV-EC (Internal ventilation, equal channel), and IV-RC (Internal ventilation, reduced channel) were evaluated through numerical simulation and water simulation experiments. The results demonstrated that IV-RC scheme exhibits superior bubble dispersion characteristics and a broader bubbling range. Experimental results in Al composite confirmed that UAA treatment with IV-RC scheme achieved the highest degassing efficiency, with a relative density improvement of up to 98.01 % and the lowest hydrogen content (0.0235 ppm). Synchrotron radiation X-ray computed tomography results indicated that UAA treatment effectively reduces the pore size and volume, transforming interconnected, complex pores into dispersed, nearly spherical ones. Ultrasonic cavitation aids this process by breaking small argon bubbles into numerous tiny bubbles that penetrate deeply into the melt, reducing the wettability angle between particles and the matrix and thereby improving hydrogen removal efficiency.

The full-grouted sleeve connection (FGSC) is widely used in prefabricated structural connections, but the complexity of the grouting process often leads to defects, primarily grouting voids. The mechanical properties of FGSCs with these defects under fire exposure are not well understood. This study examines 144 FGSCs with various grouting voids exposed to specific temperatures before cooling to room temperature for static tensile testing. Key parameters include defect type, volume defect rates, and temperature. The study identifies two primary failure modes: rebar tensile and pull-out failures, influenced by void size, distribution, and temperature. Below 300 °C, tensile failure occurs when the defect rate is ≤0.05; above this rate, pull-out failure dominates. Above 300 °C, all specimens exhibit pull-out failure. Specimens with concentrated voids show lower bearing capacities. The research provides a bond stress-slip constitutive model for FGSCs and a fitting formula for characteristic points. A neural network model predicts the ultimate bond stress based on defect type, volume defect rate, temperature, and grouting material strength, with sensitivity analysis indicating the volume defect rate as a critical factor. This work offers a comprehensive theoretical foundation for studying the impact of grouting defects on FGSCs' post-fire mechanical properties.

Background: Acute myeloid leukemia (AML) is a heterogeneous disease, for which identifying reliable prognostic markers is critical for accurate clinical prognosis and treatment optimization. The inhibition of emopamil-binding protein gene (EBP) expression has been demonstrated to induce cancer cell death via depleting downstream sterols. Nevertheless, no comprehensive studies have been conducted specifically in tumors, including AML.Method: Herein, survival analyses were performed on the dataset obtained from The Cancer Genome Atlas (TCGA). Besides, the EBP levels were quantified using real-time qPCR in a cohort of 120 AML patients, and the value of EBP was further assessed using our clinical data.Results: Patients with high EBP expression had worse overall survival (OS) and event-free survival (EFS) than patients with low EBP expression, both in the TCGA dataset and our clinical data. Additionally, white blood cell (WBC) counts were higher in patients with high EBP expression (P = 0.032). Moreover, in patients with intermediate-risk AML, it was discovered that elevated EBP expression was linked to a worse EFS (P = 0.038). Multivariate analysis demonstrated that high EBP expression was an independent prognostic factor in AML patients and was associated with a shorter OS and EFS (OS: P = 0.041; EFS: P = 0.017). Furthermore, the data revealed that transplantation in the high-EBP group led to an improvement in survival (OS: P = 0.001; EFS: P = 0.001). The same benefit was also observed in intermediate-risk AML patients (OS: P = 0.026; EFS: P = 0.026).Conclusion: Collectively, our findings indicated that high expression of EBP in AML patients was an adverse prognostic factor, but transplantation had the otential to alleviate its negative effects.

Dense-granule deficiency (DGD) is an inherited platelet disorder due to the absence of dense granules essential for activation of platelets in the event of vascular injury. Decreased platelet dense granules can be detected by electron microscopy, while other tests of hemostasis, including platelet function analyzer (PFA®) closure times, may be normal. The present case report describes a patient with a lifelong history of mucocutaneous bleeding and excessive hemorrhage with resection of vestibular Schwannoma. After hemostasis was obtained the case was aborted and the neurosurgeon noted bleeding resembled as if patient was on an antiplatelet drug. Subsequent hematologic workup revealed a severe platelet function disorder. There is a paucity of literature on management of intracranial neurosurgery in patients with inherited platelet disorders. Patients undergoing major surgical procedures often receive tranexamic acid (TXA), desmopressin, and/or human-leukocyte antigen (HLA)-matched platelet transfusions. We review the clinical management of intracranial tumor surgery, as well as Cyberknife radiosurgery, in our patient with DGD. After diagnosis was known, thoughtful hemostatic planning with empiric platelet transfusions and TXA prevented recurrent bleeding.

Precision weed management (PWM), driven by machine vision and deep learning (DL) advancements, not only enhances agricultural product quality and optimizes crop yield but also provides a sustainable alternative to herbicide use. However, existing DL-based algorithms on weed detection are mainly developed based on supervised learning approaches, typically demanding large-scale datasets with manual-labeled annotations, which can be time-consuming and labor-intensive. As such, label-efficient learning methods, especially semi-supervised learning, have gained increased attention in the broader domain of computer vision and have demonstrated promising performance. These methods aim to utilize a small number of labeled data samples along with a great number of unlabeled samples to develop high-performing models comparable to the supervised learning counterpart trained on a large amount of labeled data samples. In this study, we assess the effectiveness of a semi-supervised learning framework for multi-class weed detection, employing two well-known object detection frameworks, namely FCOS (Fully Convolutional One-Stage Object Detection) and Faster-RCNN (Faster Region-based Convolutional Networks). Specifically, we evaluate a generalized student-teacher framework with an improved pseudo-label generation module to produce reliable pseudo-labels for the unlabeled data. To enhance generalization, an ensemble student network is employed to facilitate the training process. Experimental results show that the proposed approach is able to achieve approximately 76% and 96% detection accuracy as the supervised methods with only 10% of labeled data in CottonWeedDet3 and CottonWeedDet12, respectively. We offer access to the source code (https://github.com/JiajiaLi04/SemiWeeds), contributing a valuable resource for ongoing semi-supervised learning research in weed detection and beyond.

Fractures play a crucial role in tight sandstone gas reservoirs with low permeability and low effective porosity. If open, they not only significantly increase the permeability of the reservoir but also serve as channels connecting the storage space. Among numerous fracture identification methods, seismic data provide unique advantages for fracture identification owing to the provision of three-dimensional information between wells. How to accurately identify the development of fractures in geological bodies between wells using seismic data is a major challenge. In this study, a tight sandstone gas reservoir in the Kuqa Basin (China) was used as an example for identifying reservoir fractures using deep-learning-based method. First, a feasibility analysis is necessary. Intersection analysis between the fracture density and seismic attributes (the characteristics of frequency, amplitude, phase, and other aspects of seismic signals) indicates that there is a correlation between the two when the fracture density exceeds a certain degree. The development of fractures is closely related to the lithology and structure, indirectly affecting differences in seismic attributes. This indicates that the use of seismic attributes for fracture identification is feasible and reasonable. Subsequently, the effective fracture density data obtained from imaging logging were used as label data, and the optimized seismic attribute near the well data were used as feature data to construct a fracture identification sample dataset. Based on a feed-forward neural network algorithm combined with natural fracture density and effectiveness control factor constraints, a trained identification model was obtained. The identification model was applied to seismic multi-attribute data for the entire work area. Finally, the accuracy of the results from the training, testing, and validation datasets were used to determine the effectiveness of the method. The relationship between the fracture identification results and the location of the fractures in the target reservoir was used to determine the reasonableness of the results. The results indicate that there is a certain relationship between multiple seismic attributes and fracture development, which can be established using deep learning models. Furthermore, the deep-learning-based seismic data fracture identification method can effectively identify fractures in the three-dimensional space of reservoirs.

Background and aims: Tumor recurrence significantly affects the prognostic outcomes for liver cancer patients following liver transplantation. However, existing predictive models often neglect the inclusion of body composition indicators. Hence, this research aimed to investigate the significance of the psoas muscle index (PMI) in evaluating the post-transplant prognosis of liver cancer. Methods: A retrospective analysis was conducted on liver cancer patients who underwent liver transplantation surgery. Imaging analysis was performed using CT data to calculate PMI based on the left and right psoas muscle areas. Subsequently, the patients were categorized into PMI-Low and PMI-High groups using the established cut-off values. Univariate and multivariate analyses were performed using Cox proportional hazards regression to assess the correlation between PMI and clinical outcomes, and a nomogram was constructed accordingly. Results: Among the 225 patients included in the analysis, the PMI-High group exhibited significantly improved overall survival (P

BackgroundPortal vein tumor thrombus (PVTT) is a major risk factor of recurrence of hepatocellular carcinoma (HCC) after hepatectomy. Whether postoperative adjuvant immunotherapy and molecular targeted therapy (I-O and MTT) is effective in reducing the risk of recurrence of HCC with minimal portal invasion after hepatectomy and improving prognosis is unknown.MethodsWe collected the data of HCC with Vp1 or Vp2 PVTT patients who underwent hepatectomy at our center between January 2019 and June 2022 from the hospital database. We utilized propensity score matching (PSM) to establish a 1:1 match between the postoperative group treated with I-O and MTT and the postoperative group without I-O and MTT. To compare the recurrence-free survival (RFS) and overall survival (OS) between the two groups, we employed the Kaplan-Meier method. Additionally, we conducted Cox regression analysis to identify the prognostic factors that influence patient prognosis. To account for different high-risk factors, subgroup analyses were carried out.ResultsAmong the 189 patients included in the study, 42 patients received postoperative adjuvant I-O and MTT. After PSM, the 1, 2-years RFS were 59.2%, 21.3% respectively in the I-O and MTT group and 40.8%, 9.6% respectively in the non-I-O and MTT group. The median RFS was 13.2 months for the I-O and MTT group better than 7.0 months for the non-I-O and MTT group (P = 0.028). 1, 2-years OS were 89.8%, 65.8% respectively in the I-O and MTT group and 42.4%, 27.7% respectively in the non-I-O and MTT group. The median OS was 23.5 months for the I-O and MTT group better than 17.2 months for the non-I-O and MTT group (P = 0.027). Multivariate analysis showed that postoperative adjuvant I-O and MTT was a prognostic protective factor associated with OS and RFS. The most frequent AE observed in this study was pruritus, and rare AEs included decreased platelet, hypothyroidism, proteinuria, myocarditis and hypoadrenocorticism. The incidence of GRADE ≥3 AE with no deaths recorded.ConclusionThe study suggested that postoperative adjuvant I-O and MTT strategy was beneficial to improve the prognosis of HCC patients with PVTT patients, while the therapy was safe and reliable.

Zika virus (ZIKV) and Japanese encephalitis virus (JEV) are antigenically related flaviviruses that co-circulate in many countries/territories. The interaction between the two viruses needs to be determined. Recent findings by ourselves and other labs showed that JEV-elicited antibodies (Abs) and CD8+ T cells exacerbate and protect against subsequent ZIKV infection, respectively. However, the impact of JEV envelope (E) protein domain III (EDIII)-induced immune responses on ZIKV infection is unclear. We show here that sera from JEV-EDIII-vaccinated mice cross-react with ZIKV-EDIII in vitro, and transfer of the same sera to mice significantly decreases death upon lethal ZIKV infection at a dose-dependent manner. Maternally acquired anti-JEV-EDIII Abs also significantly reduce the mortality of neonatal mice born to JEV-EDIII-immune mothers post ZIKV challenge. Similarly, transfer of ZIKV-EDIII-reactive IgG purified from JEV-vaccinated humans increases the survival of ZIKV-infected mice. Notably, transfer of an extremely low volume of JEV-EDIII-immune sera or ZIKV-EDIII-reactive IgG does not mediate the Ab-mediated enhancement (ADE) of ZIKV infection. Similarly, transfer of JEV-EDIII-elicited CD8+ T cells protects recipient mice against ZIKV challenge. These results demonstrate that JEV-EDIII-induced immune components including Abs and T cells have protective roles in ZIKV infection, suggesting EDIII is a promising immunogen for developing effective and safety JEV vaccine.

Abstract Aedes sp. mosquitoes are changing their geographic range in response to climate change. This is of concern because these mosquitoes can carry dengue fever and other viral diseases. Changing weather patterns can also increase the numbers of Aedes mosquitoes, leading to greater human exposure and enhancing population health risks. We project the geographic distribution of Aedes and associated changes in populations exposed to dengue in Asian metropolitan areas under warming scenarios from 1.5°C to 5.0°C above pre‐industrial temperatures, using multi‐model ensembles. With global warming, the southern part of the Arabian Peninsula, the coast of the Arabian Sea in southern Iran, southern Pakistan in West Asia, the Korean Peninsula, most of the Japanese islands, and parts of North China in East Asia are projected to become suitable for dengue transmission. The numbers of metropolitan areas exposed to dengue is projected to change from 142 (48%) in the reference period (1995–2014) to 211 (71%) at 5.0°C warming. With the combined impact of socioeconomic and climate change, population exposure to dengue in Asian metropolitan areas is projected to increase from 263 (multi‐model range 252–268) million in 1995–2014 to 411 (394–432) million, 446 (420–490) million, 509 (475–601), 558 (493–685) and 587 (529–773) million, respectively, at 1.5°C, 2.0°C, 3.0°C, 4.0°C and 5°C warming, with an average of 2.9 million new people exposed to dengue fever in metropolitan areas each year.

Background Adequate bowel preparation is essential for successful colonoscopy and polypectomy procedures. However, a significant proportion of patients still exhibit suboptimal bowel preparation, ranging from 18% to 35%. The effectiveness of bowel preparation agents can be hampered by volume and taste, adversely affecting patient compliance and tolerance. Therefore, exploring strategies to minimise laxative volume and improve patient tolerance and adherence is imperative to ensure optimal bowel preparation quality.Methods and analysis This study is a two-arm, single-blinded, parallel-group randomised controlled trial designed to compare the efficacy of 2 L polyethylene glycol (PEG) combined with linaclotide with 4 L PEG in bowel cleansing. A total of 422 participants will be randomly assigned in a 1:1 ratio to either the intervention group (2 L PEG combined with 580 µg linaclotide) or the control group (4 L PEG). The primary outcome measure is bowel cleansing efficacy, which is assessed using the Boston Bowel Preparation Scale. Secondary outcomes include evaluating the tolerability and safety of the bowel preparation regimens, bowel diary assessments, postpolypectomy complications (such as bleeding and perforation) and the size and number of removed polyps.Ethics and dissemination The study has received approval from the Clinical Research Ethics Committee of The First Affiliated Hospital, Zhejiang University School of Medicine. The findings of this trial will serve as a valuable resource for clinicians and patients undergoing colonoscopy polypectomy by guiding the selection of appropriate bowel preparation regimens. Study findings will be disseminated to participants, presented at professional society meetings, and published in peer-reviewed journals. This trial was registered on the Chinese Clinical Trial Registry with registration number ChiCTR2300075410

ABSTRACT Pathogenic bacteria of the Acinetobacter genus pose a severe threat to human health worldwide due to their strong adaptability, tolerance, and antibiotic resistance. Most isolates of these bacteria harbor a type VI secretion system (T6SS) that allows them to outcompete co-residing microorganisms, but whether this system is involved in acquiring nutrients from preys remains less studied. In this study, we found that Ab25, a clinical isolate of Acinetobacter nosocomialis, utilizes a T6SS to kill taxonomically diverse microorganisms, including bacteria and fungi. The T6SS of Ab25 is constitutively expressed, and among the three predicted effectors, T6e1, a member of the RHS effector family, contributes the most for its antimicrobial activity. T6e1 undergoes self-cleavage, and a short carboxyl fragment with nuclease activity is sufficient to kill target cells via T6SS injection. Interestingly, strain Ab25 encodes an orphan VgrG protein, which when overexpressed blocks the firing of its T6SS. In niches such as dry plastic surfaces, the T6SS promotes prey microorganism-dependent survival of Ab25. These results reveal that A. nosocomialis employs T6SSs that are highly diverse in their regulation and effector composition to gain a competitive advantage in environments with scarce nutrient supply and competing microbes.IMPORTANCEThe type VI secretion system (T6SS) plays an important role in bacterial adaptation to environmental challenges. Members of the Acinetobacter genus, particularly A. baumannii and A. nosocomialis, are notorious for their multidrug resistance and their ability to survive in harsh environments. In contrast to A. baumannii, whose T6SS has been well-studied, few research works have focused on A. nosocomialis. In this study, we found that an A. nosocomialis strain utilizes a contitutively active T6SS to kill diverse microorganisms, including bacteria and fungi. Although T6SS structural proteins of A. nosocomialis are similar to those of A. baumannii, the effector repertoire differs greatly. Interestingly, the T6SS of the A. nosocomialis strain codes for an ophan VgrG protein, which blocks the firing of the system when overexpressed, suggesting the existence of a new regulatory mechanism for the T6SS. Importantly, although the T6SS does not provide an advantage when the bacterium is grown in nutrient-rich medium, it allows A. nosocomialis to survive better in dry surfaces that contain co-existing bacteria. Our results suggest that killing of co-residing microorganisms may increase the effectiveness of strategies designed to reduce the fitness of Acinetobacter bacteria by targeting their T6SS.

BackgroundOsteoarthritis (OA) holds the distinction of being the most widespread musculoskeletal disorder. Any disruptions in the integrity of the articular cartilage can result in joint malfunction, discomfort, and impaired physical functioning. Increasing evidence indicates the negative impacts of caffeine intake on hyaline cartilage. The primary objective of this study was to delve deeper into understanding the potential link between the consumption of caffeine and the risk of developing OA.MethodsIn this study, we constructed logistic regression models to evaluate the correlation between caffeine consumption and the risk of osteoarthritis using data from the National Health and Nutrition Examination Survey. Following that, we utilized genome-wide association studies to conduct a Mendelian randomization (MR) analysis investigating the association between coffee consumption and the likelihood of developing knee OA. We employed various statistical methods, including inverse variance weighting (IVW), weighted median, weighted mode, simple mode, and MR-Egger regression, to ensure comprehensive analysis and robust conclusions. To evaluate heterogeneity and the potential impact of pleiotropy, we conducted several statistical tests, including Cochran's Q test, MR-Egger intercept test, MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO), and MR Steiger test.ResultsThe weighted multivariate logistic regression analysis showed that the relationship between high caffeine intake (95–206 and ≥206 mg/day) and OA prevalence remained significantly high even after adjusting for covariates using the lowest caffeine intake (< 11 mg/day) as reference: Model 1—OR (95% Cl) = 1.365 (1.18–1.58) and 1.59 (1.38–1.83); Model 2—OR (95% Cl) = 1.21 (1.04–1.42) and 1.44 (1.23–1.68); and Model 3—OR (95% Cl) = 1.19 (1.01–1.40) and 1.30 (1.10–1.52), respectively (p < 0.05). The findings from the fixed effects inverse variance weighted (IVW) analysis revealed a statistically significant link between coffee intake and the likelihood of developing knee osteoarthritis: OR = 1.94; 95% confidence interval (Cl) =1.471–2.517; (p < 0.001). Consistent findings were obtained across various other methods, including MR-Egger regression, weighted median, weighted mode, and simple mode analyses.ConclusionOur study showed a positive correlation between OA prevalence and high caffeine intake (≥95 mg/day).

Background: The resistance of multiple myeloma (MM) to bortezomib (BTZ) has brought multiple challenges to its clinical use. Numerous ginsenosides have potential anti-tumor effects, however, the research on the role of Rg1 in MM has not been reported. Objective: To examine the inhibitory impact of Rg1 on the growth of MM and reduce the drug resistance of MM to BTZ through in vivo and in vitro experiments, and to explore their potential mechanism. Methods: BTZ drug-resistant cell line RPMI8226R was constructed. Mouse tumor-bearing model was developed by abdominal subcutaneous injection of MM cells. MM cells were treated with AMPK inhibitor Compound C or autophagy inhibitor Chloroquine together with Rg1. RPMI8226R cells were treated with BTZ and Rg1. Cell multiplication was detected using Methylthiazolyldiphenyl-tetrazolium bromide assay. Apoptosis was assessed using flow cytometry. Immunofluorescence assay was employed to assess the autophagy markers LC3. Western blot was utilized to assess the protein expression. Immunohistochemistry was used to detect cell proliferation and apoptosis in tumor tissues. Results: In vitro experiments demonstrated that Rg1 could hinder the proliferation of MM cells, promote apoptosis and enhance autophagy. Rg1 could also increase the sensitivity of RPMI8226R to BTZ. In vivo experiments illustrated that Rg1 could hinder the development of MM cells in mice, weaken the proliferation of tumor cells and enhance their apoptosis. Further study found that the anti-MM impact of Rg1 was linked to AMPK-mTOR pathway, the autophagy degree of RPMI8226R was higher than that of RPMI8226, and that Rg1 could inhibit MM and overcome drug resistance through autophagy induced by AMPK-mTOR pathway. Conclusion: Rg1 has significant anti-MM effect and can overcome BTZ resistance, and its potential mechanism is related to the regulation of autophagy induced by AMPK-mTOR pathway. Rg1 is a promising adjuvant drug for the treatment of MM.

Breast cancer (BC) is the most prevalent cancer among women around the world. Finding new and efficient drugs has become a crucial aspect of BC treatment. Liensinine diperchlorate (LIN) and artemisitene (ATT) are natural compounds with potential anti-cancer activities extracted from lotus (Nelumbo nucifera Gaertn) seeds and Artemisia annua, respectively. However, the synergistic anti-breast cancer effectiveness and mechanism of LIN and ATT remain unknown. This study intended to reveal the biological functions and underlying mechanism of combined LIN and ATT treatment in BC. Herein, we first reported that LIN and ATT synergistically mitigated the proliferation, migration as well as invasion of BC cells. Besides, LIN boosted the stimulatory effect of ATT on reactive oxygen species (ROS)-mediated apoptosis in BC cells. Interestingly, LIN and ATT synergistically attenuated the growth of BC patient-derived organoids. Moreover, LIN augmented the inhibitory efficacy of ATT on BC growth in vivo without obvious side effects. Furthermore, the inactivation of PI3K-AKT pathway and its regulated proteins contributed to the therapeutic role of LIN and ATT treatment in BC. Intriguingly, a prediction model constructed as per RNA sequencing data indicated that the combination of LIN and ATT treatment might ameliorate the prognosis of BC patients. In conclusion, our present investigation demonstrated that LIN and ATT synergistically inhibited BC cell proliferation, migration as well as invasion and enhanced ROS-mediated apoptosis via suppressing the PI3K-AKT signaling, and suggested that combining LIN and ATT treatment might be a promising choice for BC therapy.