Search

Asphalt pavement exhibits different dynamic responses to vehicle loading in different conditions. It is essential to conduct field full-scale tests to systematically investigate the comprehensive influence of various factors on the dynamic response of asphalt pavement. Based on accelerated pavement testing (APT), this paper presents research on the effects of several factors on the dynamic response of semi-rigid base pavement and fatigue damage of the asphalt layer. The factors include groundwater level, vehicle speed, wheel–ground contact pressure, and temperature. The results show that the amplitudes of vertical stress, vertical strain, and transverse strain decreased with the rise of groundwater level, while the amplitude of longitudinal strain increased. The amplitudes of three-dimensional strain and vertical stress increased with the increase in the wheel–ground contact pressure and temperature, and the decrease in the vehicle speed. Based on the controlled environment-multiaxial loading facility (CE-MLF) system, a dynamic response prediction model of coupled vehicle speed and temperature was established. Based on the natural environment-automatically loaded track (NE-ALT) system, a dynamic response prediction model of coupled vehicle speed and wheel–ground contact pressure was established. According to the dynamic response results, the fatigue life of the upper layer of two test roads was calculated. The fatigue life increased slightly with the increase in the test temperature and speed in the CE-MLF system. In the NE-ALT system, the fatigue life decreased with the increase in the wheel–ground contact pressure and the decrease in speed. Therefore, the coupling effect of speed, wheel–ground contact pressure, and temperature should be considered in evaluating the fatigue life of the asphalt layer. [ABSTRACT FROM AUTHOR]

Bacterial infection at wound sites can easily induce robust inflammation. M1 macrophages at wound sites can cause cascade inflammatory reactions to mediate a vicious inflammation cycle. Meanwhile, the hypoxia situation further aggravates the destruction and contraction of blood vessels in the wound microenvironment, therefore, hindering the infected wound healing process. Here, a thermosensitive hydrogel is reported to solve the above challenges by eliminating bacteria based on the photothermal effect, regulating the inflammatory immune microenvironment, and providing oxygen (O2). In vitro and in vivo experiments confirmed that the hydrogel has great O2‐producing properties. Based on the excellent photothermal properties of AIEgens, the hydrogel has a good bactericidal effect against S. aureus (100%) and E. coli (98.85%). The RNA‐sequencing revealed that Cur@AIE@MnO2/gel can interfere with the metabolic process and genetic material repair process to impact bacteria proliferation and biofilm dispersal, thus achieving excellent anti‐bacterial efficacy. Moreover, Cur@AIE@MnO2/gel can also up‐regulate anti‐inflammatory genes, down‐regulate pro‐inflammatory genes in macrophages, and facilitate the promotion of macrophage polarization from M1 to M2 to relieve inflammation. The therapeutic experiments show that this hydrogel accelerated the wound‐healing process. Therefore, this work may open new avenues for the development of novel dressings for bacterial‐infected wounds. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to introduce a new classification system for paediatric femoral neck fractures (PFNFs) and to evaluate its reliability. Methods: Two hundred and eight unilateral PFNFs (mean patient age: 9.0 ± 4.8 years) were included. Based on preoperative radiographs, the new classification system distinguished PFNFs without anterior or posterior translation (Type I), PFNFs with anterior (Type II) or posterior (Type III) translation, PFNFs with a comminuted medial or posterior column (Type IV), and subtrochanteric femoral fractures (SFFs; Type V). Radiographs were evaluated twice with an interval of two weeks by 19 raters with different specialties, experiences and geographical origins. The results were compared with a selection of 50 patient age-matched unilateral PFNFs and SFFs (mean patient age: 9.1 ± 4.9 years). These were graded twice by the same graders according to the Delbet-Colonna (D-C) classification. Results: Four radiologists and 15 paediatric orthopaedic surgeons from Europe and Asia graded the radiographs. Fair agreement was found between radiologists (κ = 0.296 ± 0.01) and surgeons (κ = 0.3 ± 0.005) (P = 0.17), although more experienced surgeons performed better than less experienced ones; a similar fair assessment was found for raters from Europe (κ = 0.309 ± 0.021) and Asia (κ = 0.3 ± 0.006) and for type II, III and IV fractures; the κ value in the first evaluation (0.309) was similar to that in the second evaluation (0.298). The overall κ value of the D-C classification subtypes was significantly higher (0.599 ± 0.217) than that of the new classification, 0.326 ± 0.162 (t = 3.190 P = 0.005). Conclusions: The new classification system showed fair reliability relative to the D-C classification. The reliability of the new classification system was not affected by the specialty or geographic origin of the rater or the evaluation round, only by rater experience level. The concordance was worse for PFNFs with anterior or posterior translation or with a comminuted medial or posterior columns. [ABSTRACT FROM AUTHOR]

The model of lateral β-Ga2O3 metal–oxide–semiconductor field-effect transistor (MOSFET) was established using Sentaurus Technology Computer Aided Design software. The gate-to-drain distance of the device was 13.7 μm, and the breakdown voltage was 1135 V. The single event effect simulation model caused by heavy ion irradiation was introduced, and the effects of heavy ions' incident position, angle, drain bias voltage, and linear energy transfer on the single event effect were studied. It is found that x = 7.7 μm is the sensitive location of the single event effect at the gate corner near the drain side and the peak value of the transient current is 177 mA/mm. The effect of the terminal structure of the field plate on the transient effect of the single event effect of β-Ga2O3 MOSFET is studied. It is also found that the sensitive position of the single event effect of the conventional structure, gate-field plate structure, and gate–source composite field plate structure is around x = 7.7 μm when VDS = 10 V. The peak transient currents obtained are 177, 161, and 148 mA/mm. The single event effect pulse current of the three structures increases with an increase in the drain bias voltage, while the peak pulse current of the conventional structure is larger than that of the gate-field plate structure and the gate–source composite structure. The research shows that the terminal structure of the field plate is reliable means to reduce the single particle effect. [ABSTRACT FROM AUTHOR]

A highly efficient oxidative desulfurization composite catalyst NH2‐Uio‐66‐Mo has been prepared and applied in the catalytic oxidative desulfurization. It was elucidated that Mo6+ could increase the oxygen vacancies and active sites on the catalyst and increase the pore size of UiO‐66. Meanwhile, the removal rate of dibenzothiophene (DBT) reached 99.2 % after 60 min under optimal conditions and remained above 90 % after 5 cycles, showing the composite catalyst's remarkable catalytic performance and satisfactory reusability NH2‐UiO‐66‐Mo. In addition, kinetic studies revealed that the desulfurization process can present a pseudo‐first‐order kinetic process. The apparent activation energy was 10.6 kJ/mol. Finally, in combination with oxides, possible oxidation pathways were identified. [ABSTRACT FROM AUTHOR]

Background & Aims: We aimed to develop a Transformer‐based deep learning (DL) network for prognostic stratification in hepatocellular carcinoma (HCC) patients undergoing RFA. Methods: A Swin Transformer DL network was trained to establish associations between magnetic resonance imaging (MRI) datasets and the ground truth of microvascular invasion (MVI) based on 696 surgical resection (SR) patients with solitary HCC ≤3 cm, and was validated in an external cohort (n = 180). The multiphase MRI‐based DL risk outputs using an optimal threshold of.5 was employed as a MVI classifier for prognosis stratification in the RFA cohort (n = 180). Results: Over 90% of all enrolled patients exhibited hepatitis B virus infection. Liver cirrhosis was significantly more prevalent in the RFA cohort compared to the SR cohort (72.2% vs. 44.1%, p <.001). The MVI risk outputs exhibited good performance (area under the curve values =.938 and.883) for predicting MVI in the training and validation cohort, respectively. The RFA patients at high risk of MVI classified by the MVI classifier demonstrated significantly lower recurrence‐free survival (RFS) and overall survival rates at 1, 3 and 5 years compared to those classified as low risk (p <.001). Multivariate cox regression modelling of a‐fetoprotein > 20 ng/mL [hazard ratio (HR) = 1.53; 95% confidence interval (95% CI): 1.02–2.33, p =.047], high risk of MVI (HR = 3.76; 95% CI: 2.40–5.88, p <.001) and unfavourable tumour location (HR = 2.15; 95% CI: 1.40–3.29, p =.001) yielded a c‐index of.731 (bootstrapped 95% CI:.667–.778) for evaluating RFS after RFA. Among the three risk factors, MVI was the most powerful predictor for intrahepatic distance recurrence. Conclusions: The proposed MVI classifier can serve as a valuable imaging biomarker for prognostic stratification in early‐stage HCC patients undergoing RFA. [ABSTRACT FROM AUTHOR]

Seismic damage to components and structures may cause extensive degradation of the seismic capacities of the damaged buildings. The analysis of the residual hysteretic behavior of post-earthquake damaged components and structures is a critical step in the assessment of their residual seismic capacities. Whereas, the difficulty in quantifying the damage distribution of materials in post-earthquake damaged components leads to the challenge of quantitative analysis of their residual behavior (i.e. residual stiffness, strength, energy dissipation). In this study, a visual data-informed fiber beam-column model was developed to analyze the residual hysteretic behavior of post-earthquake damaged RC columns under cyclic loads. To begin with, the method for quantifying the damage strain fields of the columns according to their inspected visual data was proposed. Then, the stress-strain relations of the materials considering the effect of damage strain fields were constructed, and the visual data-informed fiber beam-column model was proposed for the analysis of the residual hysteretic behavior of post-earthquake damaged RC columns subjected to cyclic lateral loads. At last, the proposed model was validated by comparing model results with existing test data. The comparison shows that the proposed visual data-informed fiber beam-column model can accurately analyze the concrete crushing surfaces, the residual load-displacement responses, and the energy dissipation capacities of post-earthquake damaged RC columns, facilitating the evaluation of the residual seismic capacities of post-earthquake damaged RC columns. [ABSTRACT FROM AUTHOR]

Asphalt pavement, which is mainly made up of the asphalt mixture, exhibits complicated mechanical behaviors under the combined effects of moving vehicle loads and external service environments. Multi-scale numerical simulation can well characterize behaviors of asphalt materials and asphalt pavement, and the essential research progress is systematically summarized from an entire view. This paper reviews extensive research works concerning aspects of the design, characterization, and prediction of performance for asphalt materials and asphalt pavement based on multi-scale numerical simulation. Firstly, full-scale performance modeling on asphalt pavement is discussed from aspects of structural dynamic response, structural and material evaluation, and wheel–pavement interaction. The correlation between asphalt material properties and pavement performance is also analyzed, and so is the hydroplaning phenomenon. Macro- and mesoscale simulations on the mechanical property characterization of the asphalt mixture and its components are then investigated, while virtual proportion design for the asphalt mixture is introduced. Features of two-dimensional and three-dimensional microscale modeling on the asphalt mixture are summarized, followed by molecular dynamics simulation on asphalt binders, aggregates, and their interface, while nanoscale behavior modeling on asphalt binders is presented. Finally, aspects that need more attention concerning this study's topic are discussed, and several suggestions for future investigations are also presented. [ABSTRACT FROM AUTHOR]

Starting around 6 to 9 months of age, children begin acquiring their first words, linking spoken words to their visual counterparts. How much of this knowledge is learnable from sensory input with relatively generic learning mechanisms, and how much requires stronger inductive biases? Using longitudinal head-mounted camera recordings from one child aged 6 to 25 months, we trained a relatively generic neural network on 61 hours of correlated visual-linguistic data streams, learning feature-based representations and cross-modal associations. Our model acquires many word-referent mappings present in the child’s everyday experience, enables zero-shot generalization to new visual referents, and aligns its visual and linguistic conceptual systems. These results show how critical aspects of grounded word meaning are learnable through joint representation and associative learning from one child’s input. [ABSTRACT FROM AUTHOR]

Ultrafast transmission electron microscope (UTEM) with the multimodality of time-resolved diffraction, imaging, and spectroscopy provides a unique platform to reveal the fundamental features associated with the interaction between free electrons and matter. In this review, we summarize the principles, instrumentation, and recent developments of the UTEM and its applications in capturing dynamic processes and non-equilibrium transient states. The combination of the transmission electron microscope with a femtosecond laser via the pump–probe method guarantees the high spatiotemporal resolution, allowing the investigation of the transient process in real, reciprocal and energy spaces. Ultrafast structural dynamics can be studied by diffraction and imaging methods, revealing the coherent acoustic phonon generation and photo-induced phase transition process. In the energy dimension, time-resolved electron energy-loss spectroscopy enables the examination of the intrinsic electronic dynamics of materials, while the photon-induced near-field electron microscopy extends the application of the UTEM to the imaging of optical near fields with high real-space resolution. It is noted that light–free-electron interactions have the ability to shape electron wave packets in both longitudinal and transverse directions, showing the potential application in the generation of attosecond electron pulses and vortex electron beams. [ABSTRACT FROM AUTHOR]

We consider the global existence of solutions and input‐to‐state stability for a class of stochastic delayed recurrent neural networks without uniform Lipschitz condition. Under local Lipschitz condition, we find new sufficient conditions that ensure the solutions of given neural networks exist globally and are mean‐square exponentially input‐to‐state stable. Furthermore, we highlight the advantages of our novel results by comparing with some known results as well as a numerical example. [ABSTRACT FROM AUTHOR]

Objective: Multi‐segmental thoracolumbar fracture (MSF) generally refers to fractures occurring in two or more segments of the thoracolumbar spine. With the development of minimally invasive concept, there is little research on its application in the field of MSF. The purpose of this study is to compare two minimally invasive surgical techniques and determine which one is more suitable for treating patients with neurologically intact MSF. Methods: We retrospectively analyzed the clinical data of 49 MSF patients with intact nerves who were admitted from January 2017 to February 2019. Among them, 25 cases underwent percutaneous pedicle screw fixation (PPSF), and 24 cases underwent Wiltse approach pedicle screw fixation (WAPSF). The operation time, number of fixed segments, blood loss, length of incision, postoperative ambulation time, accuracy of pedicle screw placement, facet joint violation (FJV), number of C‐arm exposures, as well as pre‐ and postoperative visual analogue scale (VAS), Oswestry disability index (ODI), local Cobb's angle (LCA), and percentage of anterior vertebral body height (PAVBH) were recorded for both groups. Paired sample t‐test was used for intra‐group comparison before and after surgery while independent sample t‐test was used for inter‐group comparison. Results: The differences in the number of fixed segments, intraoperative bleeding, postoperative bed time, accuracy rate of pedicle screw placement, VAS, and ODI between the two groups were not statistically significant (p > 0.05). However, the operative time and total surgical incision length were significantly shorter in the WAPSF group than in the PPSF group (p < 0.05), and the FJV was significantly higher in the PPSF group than in the WAPSF group (p < 0.05). Also, the PPSF group received more intraoperative fluoroscopy (p < 0.05). The result of LCA and PAVBH in the WAPSF group were significantly better than in the PPSF group (p < 0.05). Conclusions: Both PPSF and WAPSF were found to be safe and effective in the treatment of MSF without neurological deficits through our study. However, considering radiation exposure, FJV, vertebral height restoration, correction of kyphosis, and learning curve, WAPSF may be a better choice for neurologically intact MSF. [ABSTRACT FROM AUTHOR]

Neural network models have recently made striking progress in natural language processing, but they are typically trained on orders of magnitude more language input than children receive. What can these neural networks, which are primarily distributional learners, learn from a naturalistic subset of a single child's experience? We examine this question using a recent longitudinal dataset collected from a single child, consisting of egocentric visual data paired with text transcripts. We train both language‐only and vision‐and‐language neural networks and analyze the linguistic knowledge they acquire. In parallel with findings from Jeffrey Elman's seminal work, the neural networks form emergent clusters of words corresponding to syntactic (nouns, transitive and intransitive verbs) and semantic categories (e.g., animals and clothing), based solely on one child's linguistic input. The networks also acquire sensitivity to acceptability contrasts from linguistic phenomena, such as determiner‐noun agreement and argument structure. We find that incorporating visual information produces an incremental gain in predicting words in context, especially for syntactic categories that are comparatively more easily grounded, such as nouns and verbs, but the underlying linguistic representations are not fundamentally altered. Our findings demonstrate which kinds of linguistic knowledge are learnable from a snapshot of a single child's real developmental experience. [ABSTRACT FROM AUTHOR]

Integrating responsive photonic crystals (RPCs) and quantum dots (QDs) effectively to realize multimode dynamic color regulation is of great significance for promoting advances in color display science. Herein, a new type of flexible dynamic color display with multimode reversible switching between transparent and colorful states based on the combination of RPCs and CdTe QDs is designed. This unique system is fabricated by encapsulating a thin layer of ordered arrays of SiO2@CdTe@SiO2 (SQS) colloids with poly(dimethylsiloxane) (PDMS), which generates an elastic film with sandwiched structure of PDMS/SQS/PDMS. Owing to the similarity in the optical properties of PDMS and SQS, the display is highly transparent in the normal state. Moreover, the resultant flexible display exhibits obvious change in color by mechanical stimuli or UV exposure. Finally, the ability to display joints motion amplitudes of human body as well as the applications in advanced security is demonstrated. [ABSTRACT FROM AUTHOR]

Objective. Lung squamous cell carcinoma (LUSC) is a common respiratory malignancy and presents an increasing prevalence. Ferroptosis is a newly identified controlled cell death that has captured clinical attention worldwide. However, the ferroptosis-related lncRNA expression in LUSC and its relevance to prognosis remain elusive. Methods. The research measured predictive ferroptosis-related lncRNAs in LUSC samples from the TCGA datasets. Data on the stemness indices (mRNAsi) and corresponding clinical characteristics were obtained from TCGA. A prognosis model was established using the LASSO regression. Changes within the neoplasm microenvironment (TME) and medicine association were examined to grasp higher immune cell infiltration in numerous risk teams. In line with coexpression studies, the expression of lncRNAs is closely associated with that of ferroptosis. They were overexpressed in unsound people in the absence of alternative clinical symptoms. Results. The low-risk and speculative teams were considered to have substantial differences in CCR and inflammation-promoting genes. C10orf55, AC016924.1, AL161431.1, LUCAT1, AC104248.1, and MIR3945HG were highly expressed in the high-risk group, suggesting their involvement in the oncology process of LUSC. Moreover, AP006545.2 and AL122125.1 were considerably higher in the low-risk group, implying the potential of these genes as LUSC tumor suppressor genes. The biomarkers listed above may serve as therapeutic targets for LUSC. lncRNAs were also linked to patient outcomes in the LUSC trial. Conclusion. lncRNAs of ferroptosis were overexpressed in the high-risk cohort without other clinical signs, implying their potential to predict BLCA prognosis. GSEA highlighted immunological and tumor-related pathways in the high-risk group. LUSC occurrence and progression are linked to lncRNAs of ferroptosis. Corresponding prognostic models help forecast the prognosis of LUSC patients. lncRNAs of ferroptosis and associated immune cell infiltration in the tumor microenvironment (TME) may serve as potential therapeutic targets in LUSC, which requires further trials. In addition, the lncRNAs of ferroptosis signature offer a viable alternative to predict LUSC, and these ferroptosis-lncRNAs show a prospective research area for LUSC-targeted treatment in the future. [ABSTRACT FROM AUTHOR]

The previous technology-centric development of smart cities mainly focuses on the numbers, diversities, and types of applied intelligent technologies, while the citizen-centric smart city has become an important paradigm for improving the sustainability of cities around the world. The citizens' sense of gain (CSG), which considers both material acquisition and spiritual feelings of smart city services, is thus proposed and regarded as one of the core orientations in the smart cities' transformation development process from the centric of advanced technology applied to the centric of citizen subjective perception. To shift smart cities from being technology-centric to citizen-centric, it is critical to identify the factors influencing CSG and develop appropriate strategies to enhance CSG in smart cities. Hence, this work identifies 17 key CSG influencing factors based on the dimensions dissected from the definition of CSG and it further formulates 15 strategies for enhancing CSG by adopting the SWOT-AHP-TOWS method based on data collected from Nanjing citizens. The results indicate that the most important criteria for enhancing CSG in smart cities are the external opportunities, which are originated from citizens' attitudes and behaviors, and the top-ranked strategy is "dividing smart infrastructure into different categories according to the hierarchy needs of citizens and promoting the synergy development of smart infrastructure within and among different categories". Finally, four implications are proposed, including (i) strengthening publicity and encouraging citizen participation, (ii) clarifying the responsibilities of local governments, (iii) prioritizing citizens' needs, and (iv) promoting age-friendly, vulnerable-friendly, and environmental-friendly development. [ABSTRACT FROM AUTHOR]

Archimedes optimization algorithm (AOA) is a new meta-heuristic algorithm which is based on Archimedes principle and mimics the buoyancy force received by an object in water. The AOA is designed according to physical principles and has been the object of many scholars' research because of its simple and reliable performance. In the course of the study, this paper finds that the AOA is flawed. In the iterative update of the algorithm, the buoyancy principle applied to the object is not completely followed. Through the investigation and analysis of this problem, it is found that the algorithm design which follows the buoyancy principle completely is more advantageously and persuasively, and named the corrected algorithm CAOA. The performance of the CAOA and other comparison optimization algorithms is tested in benchmark functions CEC2017 under equal conditions to verify the ideas proposed in this paper. In the solution accuracy with dimensions of 30 and 50, the comprehensive score of the CAOA is 31 and 33 and ranks first in all algorithms. In the statistical analysis, the CAOA compared with other algorithms one by one, and achieved the best results in all test functions. When compared with other algorithms, the CAOA ranked first. It is hoped that the verification of the ideas in this paper will help the AOA to develop better and optimize the development of the algorithm. [ABSTRACT FROM AUTHOR]

We consider a class of stochastic fuzzy delayed Cohen-Grossberg neural networks without global Lipschitz condition. Based on local Lipschitz condition, we prove the solutions of the given neural networks exist globally and are mean-square exponentially input-to-state stable. Moreover, we highlight the advantages of our novel results by comparing with the results in Zhu and Li (2012) as well as a numerical example. [ABSTRACT FROM AUTHOR]

Scutellaria baicalensis Georgi is an annual herb from the Scutellaria genus that has been extensively used as a traditional medicine for over 2000 years in China. Baicalin and other flavonoids have been identified as the principal bioactive ingredients. The biosynthetic pathway of baicalin in S. baicalensis has been elucidated; however, the specific functions of R2R3-MYB TF, which regulates baicalin synthesis, has not been well characterized in S. baicalensis to date. Here, a S20 R2R3-MYB TF (SbMYB12), which encodes 263 amino acids with a length of 792 bp, was expressed in all tested tissues (mainly in leaves) and responded to exogenous hormone methyl jasmonate (MeJA) treatment. The overexpression of SbMYB12 significantly promoted the accumulation of flavonoids such as baicalin and wogonoside in S. baicalensis hairy roots. Furthermore, biochemical experiments revealed that SbMYB12 is a nuclear-localized transcription activator that binds to the SbCCL7-4, SbCHI-2, and SbF6H-1 promoters to activate their expression. These results illustrate that SbMYB12 positively regulates the generation of baicalin and wogonoside. In summary, this work revealed a novel S20 R2R3-MYB regulator and enhances our understanding of the transcriptional and regulatory mechanisms of baicalin biosynthesis, as well as sheds new light on metabolic engineering in S. baicalensis. [ABSTRACT FROM AUTHOR]

Feature pyramid networks and attention mechanisms are the mainstream methods to improve the detection performance of many current models. However, when they are learned jointly, there is a lack of information association between multi-level features. Therefore, this paper proposes a feature pyramid of the multi-level local attention method, dubbed as MLA-Net (Feature Pyramid Network with Multi-Level Local Attention for Object Detection), which aims to establish a correlation mechanism for multi-level local information. First, the original multi-level features are deformed and rectified using the local pixel-rectification module, and global semantic enhancement is achieved through the multi-level spatial-attention module. After that, the original features are further fused through the residual connection to achieve the fusion of contextual features to enhance the feature representation. Extensive ablation experiments were conducted on the MS COCO (Microsoft Common Objects in Context) dataset, and the results demonstrate the effectiveness of the proposed method with a 0.5% enhancement. An improvement of 1.2% was obtained on the PASCAL VOC (Pattern Analysis Statistical Modelling and Computational Learning, Visual Object Classes) dataset, reaching 81.8%, thereby, indicating that the proposed method is robust and can compete with other advanced detection models. [ABSTRACT FROM AUTHOR]

NAD(P)H quinone oxidoreductase1 (NQO1) is a flavoenzyme that regulates the redox potential level in cells. Overexpression of NQO1 has been proven to be relevant to some malignant tumors. Herein a bioluminescent probe NQO1-Luc equipped with an NQO1-targeting group, trimethyl-locked quinone propionic acid (QPA), was constructed. The reduction of NQO1-Luc could be triggered by NQO1, resulting in the release of free D -luciferin, and concomitantly a bright bioluminescence emission. NQO1-Luc exhibits high selectivity and sensitivity toward NQO1 activity and the capability of distinguishing NQO1-overexpressing cells in vitro and in vivo, which offers a promising tool for investigations of NQO1 related biological processes including tumors in living organisms. [ABSTRACT FROM AUTHOR]

Cold stress can promote fat metabolism and reduce fat deposition. The present study compared differentially expressed (DE) lncRNAs and mRNAs in the subcutaneous back fat of Min pigs subjected to 24 h acute cold stress. Transcriptome sequencing was used to identify DE lncRNAs and mRNAs. A lncRNA mRNA co expression network was constructed using the confirmed lncRNAs. GO and KEGG analyses were performed to investigate the biological processes involved in the response to acute cold stress. A total of 166 DE lncRNAs and 269 DE mRNAs were found. Several genes such as ANGPTL4, KLF11 and NUPR1 were related to lipid metabolism. Interferon stimulating genes (ISGS) such as RSAD2, ISG20, ISG15, DDX60, MX2, MX1 and IFI6 were all significantly up-regulated. In addition, genes related to blood flow, respiration, and oxidative stress were also up-regulated. Many terms related to defense response to a virus were found in the GO annotation. A lncRNA mRNA co expression network comprising 46 specific mRNAs and the top 10 up-regulated DE lncRNAs was constructed. According to the results, the interaction between lncRNAs and mRNAs was complex. This study provides genome-wide gene and lncRNA expression profiles in adipose tissue of pigs after acute cold stress. [ABSTRACT FROM AUTHOR]

The exploration of multifunctional nanomedicine has prompted interest in improving glioblastoma (GBM) prognosis. In this study, we constructed tumor microenvironment (TME)-responsive magnetic therapeutic nanoparticles (BK@MTNPs) as a multifunctional drug delivery platform. It contains the following components. [Des-arg(Sheets et al., 2020 [ 9 ])]bradykinin (BK), which contributes to the transient opening of the blood-brain barrier (BBB) and targeting of GBM cells; nanoparticles (NPs) encapsulated in MTNPs, which act as an in vivo magnetic resonance (MR) imaging agent; crizotinib, which is an inhibitor of protein kinase c-Met; and the immune drug anti-PDL1 antibody. These components were loaded into BK@MTNPs for complete tumoricidal effects. Abundant glutathione in the TME can promote BK@MTNP degradation by interrupting the disulfide bonds between cysteine residues. Such BK@MTNPs support a synergistic tumoricidal effect by inducing DNA damage, activating the transcription of the tumor suppressor gene PTEN, inhibiting glioblastoma stem cell function, activating cytotoxic T lymphocytes, and reprogramming tumor-associated macrophages. BK@MTNPs showed a significant increase in antitumor activity compared with free drugs in vitro. Furthermore, in mice bearing orthotopic GBM, treatment with BK@MTNPs resulted in marked tumor inhibition and greatly extended survival time with minimal side effects. This study demonstrates the advantages of chemo-immunotherapeutic NPs accumulated in the GBM area and their effective inhibition of GBM growth, thus establishing a delivery platform to promote antitumor immunity against GBM. [Display omitted] [ABSTRACT FROM AUTHOR]

Asphalt binder plays an important role in the overall resistance of asphalt mixture to the moisture damage induced by a dynamic pore water pressure environment. This study evaluates the moisture sensitivity of asphalt binder from the perspective of rheological behaviors using the dynamic shear rheometer (DSR) and the bending beam rheometer (BBR) methods at high, medium, and low temperatures. The damage mechanism is further discussed quantitatively based on the Fourier transform infrared spectroscopy (FTIR) method. The results indicate that a longer conditioning duration is beneficial for asphalt binder to recover its adhesion at 60 °C in multiple stress creep recover (MSCR) tests, but the increasing pore water pressure magnitude of 60 psi held an opposite effect in this study. The asphalt binder's fatigue life at 20 °C in linear amplitude sweep (LAS) tests decreased obviously with conditioning duration and environmental severity, but the reducing rate gradually slowed down, while the groups of 50 psi—4000 cycles and 60 psi—4000 cycles held a comparable erosion effect. Both the stiffness and relaxation moduli at −12 °C in the BBR tests exhibited an obvious decreasing trend with conditioning duration and environmental severity. The erosion effect on the asphalt binder was gradually enhanced, but it also exhibited a slightly more viscous performance. Water conditioning induced several obvious characteristic peaks in the FTIR absorbance spectra of the asphalt binder. The functional group indexes presented a trend of non-monotonic change with conditioning duration and environmental severity, which made the asphalt binder show complicated rheological behaviors, such as non-monotonic variations in performance and the abnormal improving effect induced by dynamic pore water pressure conditioning. [ABSTRACT FROM AUTHOR]

Counterfeiting is a growing global issue causing severe negative impacts on the social economy and posing serious security threats to individuals and communities. However, the current anticounterfeiting technologies are relatively well known to fakers and lack sufficient security owing to the development and commercialization of high‐resolution equipment. Thus, designing new anticounterfeiting materials and systems is urgently needed. Photonic crystals (PCs) with vivid structural colors are promising materials for advanced security applications because of their unique optical characteristics. In particular, responsive PCs (RPCs), whose optical signals can be readily adjusted by external stimuli, are expected to provide improved security and may be used to determine the authenticity of banknotes, documents, and drugs. In this review, the strategies are summarized for designing RPCs, including filling responsive materials into the interstitial space of periodic photonic structures and using responsive materials as construction blocks of PCs. Subsequently, the latest progress in developing RPCs constructed for optical encryption and information security is discussed in detail. Finally, the challenges and outlook of using RPCs for optical encryption technologies are presented. [ABSTRACT FROM AUTHOR]

Solar energy is one of the most economical sources of renewable energy. The conventional solar cells are generally configured as PN or Schottky junctions where the absorbed sunlight is used to generate mobile electron-hole pairs and a built-in electric field separates the charge carriers. Further advances in solar photovoltaics are urgently desired to increase the performance at affordable cost. Herein, we introduce a new kind of solar cell concept which utilizes the surface bound charges of a ferroelectric (BaTiO 3) for separating the charge carriers in silicon (Si). Based on the new type of charge separation mechanism, a high open circuit voltage (V oc) can be established in this type of cell configuration. The results have shown that after forward polarization, the photovoltaic effect can be achieved in the cell with both Al and Ti- electrodes. The photovoltaic properties on polarized cells of Al–Ti and Au–Ti electrodes were significantly improved where the polarization induced voltage (V P) increased greatly to be 52% of the V oc after poling. Furthermore, the results also indicated that the asymmetric ferroelectric polarization makes the major contribution to the photovoltaic effect. Theoretical simulations were also conducted for the cells, which confirmed that the electric field induced by the polarization of BaTiO 3 also extended into the Si layer, resulting in the charge separation in Si. This study provides a new paradigm to design ferroelectric/semiconductor heterostructures for non-PN junction photovoltaic devices and solar energy harvesting. [Display omitted] [ABSTRACT FROM AUTHOR]

Distinct from the existing spin–orbit torque devices to only generate Rashba‐like spin current, it is proposed to generate Dresselhaus‐like spin current based on a single‐crystal ferromagnetic metal. By employing the second harmonic Hall measurement, it is found that the second harmonic Hall signal in single‐crystal ferromagnet exhibits an antisymmetric angular dependence induced by Dresselhaus‐like spin current, opposite to the reported symmetric angular dependence induced by Rashba‐like spin current. Such anomalous Dresselhaus‐like spin current is further confirmed by the current‐induced shift of the hysteresis loop when the magnetic field is swept along the current direction. However, when the ferromagnetic metal exhibits amorphous crystal structure or polycrystal structure, the Dresselhaus‐like spin current is absent. This result complements the missing type of spin currents due to charge‐to‐spin conversion and benefits the formulation of comprehensive spin–orbit coupling mechanism, by considering additional broken symmetry caused by ferromagnetic order and the structure symmetry of the crystalline lattice. [ABSTRACT FROM AUTHOR]

R2R3-MYB transcription factors participate in multiple critical biological processes, particularly as relates to the regulation of secondary metabolites. The dried root of Scutellaria baicalensis Georgi is a traditional Chinese medicine and possesses various bioactive attributes including anti-inflammation, anti-HIV, and anti-COVID-19 properties due to its flavonoids. In the current study, a total of 95 R2R3-MYB genes were identified in S. baicalensis and classified into 34 subgroups, as supported by similar exon–intron structures and conserved motifs. Among them, 93 R2R3-SbMYBs were mapped onto nine chromosomes. Collinear analysis revealed that segmental duplications were primarily responsible for driving the evolution and expansion of the R2R3-SbMYB gene family. Synteny analyses showed that the ortholog numbers of the R2R3-MYB genes between S. baicalensis and other dicotyledons had a higher proportion compared to that which is found from the monocotyledons. RNA-seq data indicated that the expression patterns of R2R3-SbMYBs in different tissues were different. Quantitative reverse transcriptase-PCR (qRT-PCR) analysis showed that 36 R2R3-SbMYBs from different subgroups exhibited specific expression profiles under various conditions, including hormone stimuli treatments (methyl jasmonate and abscisic acid) and abiotic stresses (drought and cold shock treatments). Further investigation revealed that SbMYB18/32/46/60/70/74 localized in the nucleus, and SbMYB18/32/60/70 possessed transcriptional activation activity, implying their potential roles in the regulatory mechanisms of various biological processes. This study provides a comprehensive understanding of the R2R3-SbMYBs gene family and lays the foundation for further investigation of their biological function. [ABSTRACT FROM AUTHOR]

Variable selection has been a hot topic, with various popular methods including lasso, SCAD, and elastic net. These penalized regression algorithms remain sensitive to noisy data. Furthermore, "concept drift" fundamentally distinguishes streaming data learning from batch learning. This article presents a method for noise-resistant regularization and variable selection in noisy data streams with multicollinearity, dubbed canal-adaptive elastic net, which is similar to elastic net and encourages grouping effects. In comparison to lasso, the canal adaptive elastic net is especially advantageous when the number of predictions (p) is significantly larger than the number of observations (n), and the data are multi-collinear. Numerous simulation experiments have confirmed that canal-adaptive elastic net has higher prediction accuracy than lasso, ridge regression, and elastic net in data with multicollinearity and noise. [ABSTRACT FROM AUTHOR]

This paper proposed a fast convergence and balanced adolescent identity search algorithm (FCBAISA) for numerical and engineering design problems. The main contributions are as follows. Firstly, a hierarchical optimization strategy is proposed to balance the exploration and exploitation better. Secondly, a fast search strategy is proposed to avoid the local optimization and improve the accuracy of the algorithm; that is, the current optimal solution combines with the random disturbance of Brownian motion to guide other adolescents. Thirdly, the Chebyshev functional-link network (CFLN) is improved by recursive least squares estimation (RSLE), so as to find the optimal solution more effectively. Fourthly, the terminal bounce strategy is designed to avoid the algorithm falling into local optimization in the later stage of iteration. Fifthly, FCBAISA and comparison algorithms are tested by CEC2017 and CEC2022 benchmark functions, and the practical engineering problems are solved by algorithms above. The results show that FCBAISA is superior to other algorithms in all aspects and has high precision, fast convergence speed, and excellent performance. [ABSTRACT FROM AUTHOR]

State-of-Health (SOH) estimation of lithium-ion batteries is critical for reliable and efficient energy storage and usage. Traditional SOH estimation approaches either compromise on real-time performance or on estimation accuracy. This paper introduces an end-cloud collaboration approach that synergistically combines a cloud-based deep learning model with an end-based empirical model to achieve both high-accuracy and real-time SOH estimation. Utilizing the Transformer architecture, the cloud-side model employs multiple features extracted through signal analysis technology. On the other hand, the end-side employs a fast, iterative double exponential empirical model that provides real-time estimates. Two methods of end-cloud collaborative updating are presented, both leveraging Kalman Filter and Unscented Kalman Filter (UKF) to integrate and iteratively update the models. Evaluation shows that the cloud-side model achieves a Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of around 0.8 %, while the end-cloud collaboration system maintains these metrics at 1 %, successfully capturing nonlinear capacity rebound phenomena. The work contributes to the domain by offering an approach that balances computational load and latency, making it suitable for online applications. Under the Cyber Hierarchy and Interactional Network (CHAIN) framework, this end-cloud collaboration architecture holds promise for high-accuracy, real-time health management of lithium-ion batteries across their full lifecycle. The entire end-cloud collaboration system includes a cloud based deep learning model, an end-side fast empirical model and an end-cloud collaboration algorithm. On the cloud-side, firstly, data preprocessing such as data cleaning and filtering is performed on the data. Then, multiple features are extracted based on various signal analysis methods, including differential thermal voltammetry analysis, incremental capacity analysis and equal voltage discharge interval discharge time analysis. The deep learning model based on Transformer is constructed. On the end-side, the fast model is constructed based on a dual exponential empirical model. And the end-cloud collaboration algorithm is arranged on the end-side. Two end-cloud collaboration methods are used simultaneously, including result fusion and iterative update based on Kalman filter, and online parameter identification based on UKF by sequentially linking end and cloud models. Finally, under the cyber hierarchy and interactional network framework, the end-cloud collaboration approach proposed in this paper has the potential to realize high-accuracy and high-real-time health management of lithium batteries throughout the full life cycle. [Display omitted] • A high accuracy and real-time SOH estimation method is presented. • Deep learning model on cloud-side is constructed with Transformer model as the core. • Feature extraction is based on multi feature collaborative analysis. • Two end-cloud collaboration methods are proposed to update the end-side. [ABSTRACT FROM AUTHOR]

Compared to traditional air conditioning systems, the multi-stage air treatment system has a higher energy efficiency by using lower grade energy, but the reasonable temperature differences for each stage (∆ t stage) and heat transfer between air and water (Δ t trans) needed to ensure an efficient system design remain unclear. To obtain the reasonable ∆ t stage and Δ t trans values required to maximize the energy efficiency of the multi-stage air treatment system, mathematical models are established to calculate the system's energy consumption. Six representative climate zones, two operating modes, and several working conditions are selected to evaluate the effects of different ∆ t stage and Δ t trans values on the performance of the multi-stage air treatment system. Reasonable ∆ t stage and Δ t trans values are obtained by minimizing the energy consumption of the system. The results show that: (1) the difference in reasonable ∆ t stage and Δ t trans under the different conditions is small, and it is possible to have a unified reasonable ∆ t stage and Δ t trans. (2) In the cooling season, the reasonable ∆ t stage and Δ t trans values are 6–8 and 4–5 °C, respectively; in the heating season, these values are 10–12 and 5–7 °C, respectively. (3) Compared to the traditional system, the maximum and annual average energy-saving rates of multi-stage air treatment system in an office building in Beijing are 34.5% and 17.9%, respectively. This study's results provide a solid foundation for building multi-stage air treatment system. • Reasonable heat transfer temperature difference between air and water is obtained. • Reasonable stage number of air treatment is provided for different inlet parameters. • Optimized multi-stage air treatment system has good energy-saving performance. • Results are conducive for using lower grade energy and simplifying the system. [ABSTRACT FROM AUTHOR]

Jointing YBa 2 Cu 3 O 7-z (YBCO) superconducting coated-conductor (CC) tapes is becoming increasingly significant for magnet applications because of the limited length of single tapes. In this work, YBCO CC tapes stabilized by silver were connected by low-temperature sintering of nano-silver paste. The effect of sintering time and lapped length on the electrical properties of YBCO joints were systematically investigated. And the correlation between microstructure and bonding force of the joints with extending the sintering time was established. It is found that joints sintered within 1∼5 min exhibit relatively lower resistance, while the maximum axial tensile strength at room temperature (RT) was improved with increasing sintering time. Considering the electromechanical properties, ten min is selected as the optimal sintering time for nano-silver paste. The joint by this efficient technology possesses closely connected interface, similar critical current and axial tensile strength (RT) to the single CC tape. The joint resistivity is as low as ∼12.5 nΩ·cm2, which is much less than the traditional soldering joint. [ABSTRACT FROM AUTHOR]

Hearing loss (HL) is a health burden that seriously affects the quality of life of cancer patients receiving platinum-based chemotherapy, and few FDA-approved treatment specifically targets this condition. The main mechanisms that contribute to cisplatin-induced hearing loss are oxidative stress and subsequent cell death, including ferroptosis revealed by us as a new mechanism recently. In this study, we employed the frontier molecular orbital (FMO) theory approach as a convenient prediction method for the glutathione peroxidase (GPx)-like activity of isoselenazolones and discovered new isoselenazolones with great GPx-like activity. Notably, compound 19 exhibited significant protective effects against cisplatin-induced hair cell (HC) damage in vitro and in vivo and effectively reverses cisplatin-induced hearing loss through oral administration. Further investigations revealed that this compound effectively alleviated hair cell oxidative stress, apoptosis and ferroptosis. This research highlights the potential of GPx mimics as a therapeutic strategy against cisplatin-induced hearing loss. The application of quantum chemistry (QC) calculations in the study of GPx mimics sheds light on the development of new, innovative treatments for hearing loss. [Display omitted] • • New isoselenazolones with great GPx-like activity were discovered. • • FMO approach was used as a convenient prediction method for the GPx-like activity. • • Comp. 19 showed good protective effects against cisplatin-induced hair cell damage. • • Comp. 19 effectively reversed cisplatin-induced hearing loss by oral administration. • • Comp. 19 could alleviate hair cell oxidative stress, apoptosis and ferroptosis. [ABSTRACT FROM AUTHOR]

Summary: The traditional ultrasonic computerized tomography (UCT) method needs numerous measurements to detect the inside conditions of concrete. Considering the damage is sparsely distributed in the reinforced concrete, compressive sampling (CS) is applied to advance the UCT method at both the measurement stage and the imaging stage to localize damage part in the structure. The proposed detection algorithm requires much fewer measurements compared to the traditional UCT with the same accuracy. In the measurement stage, the pitch–catch paths are randomly selected to capture the travel time of ultrasonic wave from one side to the other side in the dense measurement net. When ultrasonic waves propagate in the structure, they will interact with the damaged part, prolong the propagation length, and delay the time of flight (ToF). In the imaging stage, the whole specimen is divided into small pixels based on the desired accuracy. The conventional Rando equation is advanced based on ℓ1‐minimization algorithm from CS method to solve the slowness of each pixel to reconstruct the damaged part. The functionality of the proposed algorithm is validated via both numerical model and experimental testing on a reinforced concrete beam in the laboratory. The results reveal the UCT based on CS is more efficient for localizing and imaging the damage with much fewer measurements, which has the immense potential in the development of structural health monitoring (SHM). [ABSTRACT FROM AUTHOR]

Representation learning has been proven to play an important role in the unprecedented success of machine learning models in numerous tasks, such as machine translation, face recognition and recommendation. The majority of existing representation learning approaches often require a large number of consistent and noise-free labels. However, due to various reasons such as budget constraints and privacy concerns, labels are very limited in many real-world scenarios. Directly applying standard representation learning approaches on small labeled data sets will easily run into over-fitting problems and lead to sub-optimal solutions. Even worse, in some domains such as education, the limited labels are usually annotated by multiple workers with diverse expertise, which yields noises and inconsistency in such crowdsourcing settings. In this paper, we propose a novel framework which aims to learn effective representations from limited data with crowdsourced labels. Specifically, we design a grouping based deep neural network to learn embeddings from a limited number of training samples and present a Bayesian confidence estimator to capture the inconsistency among crowdsourced labels. Furthermore, to expedite the training process, we develop a hard example selection procedure to adaptively pick up training examples that are misclassified by the model. Extensive experiments conducted on three real-world data sets demonstrate the superiority of our framework on learning representations from limited data with crowdsourced labels, comparing with various state-of-the-art baselines. In addition, we provide a comprehensive analysis on each of the main components of our proposed framework and also introduce the promising results it achieved in our real production to fully understand the proposed framework. To encourage reproducible results, we make our code available online at https://github.com/tal-ai/RECLE. [ABSTRACT FROM AUTHOR]

In general, mixed modes and dispersion of guided wave occur at any excitation frequency, while single modes are needed for effective nondestructive evaluation of structures. In this work, we present an approach to generate a selective single-mode guided wave in plate-like structures by exploiting the unique directionality of the d36 type piezoelectric wafer and the symmetry of fundamental guided wave modes. Specifically, we devise a unified fundamental shear horizontal (SH0) wave/fundamental antisymmetric mode (A0) wave directional transducer pair by attaching the d36 type piezoelectric wafers back to back on the opposite sides of the plate to provide selective, directional single-mode guided waves for actuation and sensing. Originally, the d36-type piezoelectric wafer, poled and cut from the lead magnesium niobate-lead titanate crystal, produces a mixture of the in-plane SH0 (symmetric) mode and out-of-plane A0 (asymmetric) and S0 (symmetric) modes. By applying the in-phase or out-of-phase applied electrical field to the coupled d36-type piezoelectric wafer pair, our devised approach generates selective single modes, SH0 or A0, respectively, to propagate in the structure. We describe the theoretical development of our approach and conduct both numerical simulations and laboratory experiments for validations. [ABSTRACT FROM AUTHOR]

The WRKY gene family is an important inducible regulatory factor in plants, which has been extensively studied in many model plants. It has progressively become the focus of investigation for the secondary metabolites of medicinal plants. Currently, there is no systematic analysis of the WRKY gene family in Scutellaria baicalensis Georgi. For this study, a systematic and comprehensive bioinformatics analysis of the WRKY gene family was conducted based on the genomic data of S. baicalensis. A total of 77 WRKY members were identified and 75 were mapped onto nine chromosomes, respectively. Their encoded WRKY proteins could be classified into three subfamilies: Group I, Group II (II-a, II-b, II-c, II-d, II-e), and Group III, based on the characteristics of the amino acid sequences of the WRKY domain and genetic structure. Syntenic analysis revealed that there were 35 pairs of repetitive fragments. Furthermore, the transcriptome data of roots, stems, leaves, and flowers showed that the spatial expression profiles of WRKYs were different. qRT-PCR analysis revealed that 11 stress-related WRKYs exhibited specific expression patterns under diverse treatments. In addition, sub cellular localization analysis indicated that SbWRKY26 and SbWRKY41 were localized in nucleus. This study is the first to report the identification and characterization of the WRKY gene family in S. baicalensis, which is valuable for the further exploration of the biological function of SbWRKYs. It also provides valuable bioinformatics data for S. baicalensis and provides a reference for assessing the medicinal properties of the genus. [ABSTRACT FROM AUTHOR]

By introducing some parameters perturbed by white noises, we propose a class of stochastic inertial neural networks in random environments. To describe dynamics behaviours of this stochastic system accurately, we introduce the concept of mean-square exponential stability. By constructing two Lyapunov–Krasovskii functionals, we establish the mean-square exponential stability on the addressed system, which extend and improve the latest results. In addition, an example with numerical simulation is provided to support the theoretical findings. [ABSTRACT FROM AUTHOR]

To investigate the damage pattern and acoustic emission pattern of temperature on laminated shales, numerical experiments were carried out using the RFPA2D-Thermal numerical software under the effect of thermosolid coupling. During the tests, temperatures of 30°C, 60°C, and 90°C were controlled, and five sets of shales containing different laminar dips were numerically modeled at each temperature, with dips of 0°, 22.5°, 45°, 67.5°, and 90°. The test results show that (1) the increase in temperature reduced the linear elastic phase of the shale specimens in each group, with a significant reduction in the linear elastic phase of the shale at lamina dips of 22.5° and 45°. (2) The lamination effect decreased slightly as the temperature rose from 30°C to 60°C, and the most significant enhancement of the lamination effect on the shale occurred when the temperature reached 90°C. (3) The shale damage pattern is divided into five types (N, ʌ, v, slanted I-type, and cluttered-type), in which the lamina effect is stronger for high-angle lamina dips, and the lamina surface has a strong dominant effect on the entire shale crack expansion. At a temperature of 90°C, the lamina effect and temperature effect of the shale reached their maximum at the same time, and the thermal and load stresses inside the shale acted together causing the shale to show a complex damage mode. (4) The fractal dimension was used to analyze the damage pattern of the shale. The larger the fractal dimension was, the greater the crack rate of the specimen. The fractal dimension curve was flatter at a temperature of 60°C, while at 90°C, the fractal dimension rose rapidly, indicating the most favorable crack expansion in the shale at a temperature of 90°C. [ABSTRACT FROM AUTHOR]

The use of nanoparticles (NPs) to deliver small inhibiting microRNAs (miRNAs) has shown great promise for treating cancer. However, constructing a miRNA delivery system that targets brain cancers, such as glioblastoma multiforme (GBM), remains technically challenging due to the existence of the blood‐tumor barrier (BTB). In this work, a novel targeted antisense miRNA‐21 oligonucleotide (ATMO‐21) delivery system is developed for GBM treatment. Bradykinin ligand agonist‐decorated spermine‐modified acetalated dextran NPs (SpAcDex NPs) could temporarily open the BTB by activating G‐protein‐coupled receptors that are expressed in tumor blood vessels and tumor cells, which increase transportation to and accumulation in tumor sites. ATMO‐21 achieves high loading in the SpAcDex NPs (over 90%) and undergoes gradual controlled release with the degradation of the NPs in acidic lysosomal compartments. This allows for cell apoptosis and inhibition of the expression of vascular endothelial growth factor by downregulating hypoxia‐inducible factor (HIF‐1α) protein. An in vivo orthotopic U87MG glioma model confirms that the released ATMO‐21 shows significant therapeutic efficacy in inhibiting tumor growth and angiogenesis, demonstrating that agonist‐modified SpAcDex NPs represent a promising strategy for GBM treatment combining targeted gene therapy and antiangiogenic therapy. [ABSTRACT FROM AUTHOR]

Trigeminal neuralgia (TN) is a common pain syndrome of the nervous system,. Although about 90% patients who were refractory to medications could be free from pain after microvascular decompression (MVD), some patients did experience recurrence. The study aimed to analyze clinical characteristics of patients with recurrent TN, recurrence factors of TN, and prognosis after re-do MVD. Clinical data and at least 12 months follow-up of patients with recurrent TN who underwent re-do MVD in our hospital from 2005 to 2020 were collected and analyzed. A total of 14 patients with recurrent TN were enrolled eventually; adhesive arachnoid membranes were found in all patients. Teflon granuloma was found in 10 patients, new neurovascular compression (NVC) in 3 patients, and vascular displacement in 1 patient. Pain disappeared in 12 patients and relieved in 2 patients, but 4 patients experienced mild facial numbness and 1 patient suffered from incision infection after re-do MVC. No serious surgery-related complications and pain recurrences were recorded. Teflon granuloma was the most common cause of TN recurrence in current study, new NVC was also saw in some patients. Patients with recurrent TN could get satisfactory results from re-do MVD. [ABSTRACT FROM AUTHOR]

The use of nanoparticles (NPs) to deliver small inhibiting microRNAs (miRNAs) has shown great promise for treating cancer. However, constructing a miRNA delivery system that targets brain cancers, such as glioblastoma multiforme (GBM), remains technically challenging due to the existence of the blood‐tumor barrier (BTB). In this work, a novel targeted antisense miRNA‐21 oligonucleotide (ATMO‐21) delivery system is developed for GBM treatment. Bradykinin ligand agonist‐decorated spermine‐modified acetalated dextran NPs (SpAcDex NPs) could temporarily open the BTB by activating G‐protein‐coupled receptors that are expressed in tumor blood vessels and tumor cells, which increase transportation to and accumulation in tumor sites. ATMO‐21 achieves high loading in the SpAcDex NPs (over 90%) and undergoes gradual controlled release with the degradation of the NPs in acidic lysosomal compartments. This allows for cell apoptosis and inhibition of the expression of vascular endothelial growth factor by downregulating hypoxia‐inducible factor (HIF‐1α) protein. An in vivo orthotopic U87MG glioma model confirms that the released ATMO‐21 shows significant therapeutic efficacy in inhibiting tumor growth and angiogenesis, demonstrating that agonist‐modified SpAcDex NPs represent a promising strategy for GBM treatment combining targeted gene therapy and antiangiogenic therapy. [ABSTRACT FROM AUTHOR]

Cell imaging technology is undoubtedly a powerful tool for studying single-cell heterogeneity due to its non-invasive and visual advantages. It covers microscope hardware, software, and image analysis techniques, which are hindered by low throughput owing to abundant hands-on time and expertise. Herein, a cellular nucleus image-based smarter microscope system for single-cell analysis is reported to achieve high-throughput analysis and high-content detection of cells. By combining the hardware of an automatic fluorescence microscope and multi-object recognition/acquisition software, we have achieved more advanced process automation with the assistance of Robotic Process Automation (RPA), which realizes a high-throughput collection of single-cell images. Automated acquisition of single-cell images has benefits beyond ease and throughout and can lead to uniform standard and higher quality images. We further constructed a single-cell image database-based convolutional neural network (Efficient Convolutional Neural Network, E-CNN) exceeding 20618 single-cell nucleus images. Computational analysis of large and complex data sets enhances the content and efficiency of single-cell analysis with the assistance of Artificial Intelligence (AI), which breaks through the super-resolution microscope's hardware limitation, such as specialized light sources with specific wavelengths, advanced optical components, and high-performance graphics cards. Our system can identify single-cell nucleus images that cannot be artificially distinguished with an accuracy of 95.3%. Overall, we build an ordinary microscope into a high-throughput analysis and high-content smarter microscope system, making it a candidate tool for Imaging cytology. [ABSTRACT FROM AUTHOR]

Though both iron (hydr)oxides and soil organic matter (SOM) significantly influence heavy metal behaviors in soils, studies on the characteristics of natural minerals and the synergic effects of the two on Cr(VI) transformation are limited. This study investigated Cr(VI) retention mechanisms in four soils from tropical and subtropical regions of China based on a comprehensive characterization of Fe (hydr)oxides. These soils exhibited varying quantities of hematite, ferrihydrite and goethite, with distinct Al substitution levels and varied exposed crystallographic facets. Adsorption experiments revealed a positive correlation between Fe (hydr)oxide content and Cr(VI) fixation amount on colloid, which was influenced by the mineral types, Al substitution levels and facet exposures. Further, Cr(VI) was sequestered on soil by adsorption and reduction. In soils enriched with crystalline Fe (hydr)oxides, Cr(VI) reduction was primarily governed by SOM, while in soils enriched with poorly crystalline Fe (hydr)oxides, mineral-associated Fe(II) also contributed to Cr(VI) reduction. Aging experiments demonstrated that SOM and mineral-associated Fe(II) expedited Cr (VI) passivation and diminished the Cr leaching. These results improve our understanding of natural Fe (hydr)oxide structures and their impact on Cr(VI) behavior in soils, and shed light on complex soil-contaminant interactions and remediation of Cr(VI) polluted soils. [Display omitted] • Al substitution levels and exposed faces of soil Fe (hydr)oxides were determined. • Fe (hydr)oxides significantly contributed to Cr(VI) adsorption on colloids. • In soils dominated by crystalline Fe (hydr)oxides, SOM governed Cr(VI) reduction. • In ferrihydrite-enriched soils, mineral-associated Fe(II) and SOM facilitated Cr(VI) reduction. • Cr(VI) adsorbed on upland soils had a greater risk than that on paddy soils. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) has a high incidence and dismal prognosis, making it a significant global health burden. To change this, the development of new therapeutic strategies is imminent. The claudin (CLDN) family, as key components of tight junctions (TJs), plays an important role in the initiation and development of cancer. Dysregulated expression of CLDNs leads to loss of intercellular adhesion and aberrant cell signaling, which are closely related to cancer cell invasion, migration, and epithelial–mesenchymal transition (EMT). CLDN1, CLDN3, CLDN4, CLDN5, CLDN6, CLDN7, CLDN9, CLDN10, CLDN11, CLDN14, and CLDN17 are aberrantly expressed in HCC, which drives the progression of the disease. Consequently, they have tremendous potential as prognostic indicators and therapeutic targets. This article summarizes the aberrant expression, molecular mechanisms, and clinical application studies of different subtypes of CLDNs in HCC, with a particular emphasis on CLDN1. [Display omitted] ● The claudin family plays a vital role in the pathogenesis and progression of HCC. ● Comprehensive analysis of different subtypes of claudins in HCC. ● Most claudin subtypes are aberrantly expressed in HCC. ● Claudin1 contributes to HCC's malignant biological behavior in multiple ways. [ABSTRACT FROM AUTHOR]

Taking the specific geometry and gesture of the diamond grains into consideration, a novel simulation model to predict the machined surface topography in grinding of superalloy (GH4169) is presented, where the arrangements of abrasive grains and the plowing induced pile-up ridges are also integrated. Based on the designed surface topography of the grains arrayed brazed diamond wheels, the grinding wheel was firstly reconstructed according to the following factors of the abrasive grains, including the shape, dimension, protrusion height, attitude, and position. In accordance with the kinematics of the grains, the pile-up ridges corresponding to the real-time depth of cut were then achieved, and the superposition resulting from the interference of successive abrasive particles was thoroughly discussed to simulate the final ground topography accurately. Finally, the grinding experiments at the selected parameters were undertaken to verify the proposed model, where the measured and simulated surface topography and the surface statistics (Sa, Sq) were investigated and compared. The favorable accordance between the simulated and experimental results indicated the accuracy and the practicability of the proposed model for optimizing the grain arrangement in the diamond wheel design and improving the grinding surface uniformity. [ABSTRACT FROM AUTHOR]

Objective: To design a deep transfer learning framework for modeling fluence map predictions for stereotactic body radiation therapy (SBRT) of adrenal cancer and similar sites that usually have a small number of cases. Approach: We developed a transfer learning framework for adrenal SBRT planning that leverages knowledge in a pancreas SBRT planning model. Treatment plans from the two sites had different dose prescriptions and beam settings but both prioritized gastrointestinal sparing. A base framework was first trained with 100 pancreas cases. This framework consists of two convolutional neural networks (CNN), which predict individual beam doses (BD-CNN) and fluence maps (FM-CNN) sequentially for 9-beam intensity-modulated radiation therapy (IMRT) plans. Forty-five adrenal plans were split into training/validation/test sets with the ratio of 20/10/15. The base BD-CNN was re-trained with transfer learning using 5/10/15/20 adrenal training cases to produce multiple candidate adrenal BD-CNN models. The base FM-CNN was directly used for adrenal cases. The deep learning (DL) plans were evaluated by several clinically relevant dosimetric endpoints, producing a percentage score relative to the clinical plans. Main results: Transfer learning significantly reduced the number of training cases and training time needed to train such a DL framework. The adrenal transfer learning model trained with 5/10/15/20 cases achieved validation plan scores of 85.4/91.2/90.7/89.4, suggesting that model performance saturated with 10 training cases. Meanwhile, a model using all 20 adrenal training cases without transfer learning only scored 80.5. For the final test set, the 5/10/15/20-case models achieved scores of 73.5/75.3/78.9/83.3. Significance: It is feasible to use deep transfer learning to train an IMRT fluence prediction framework. This technique could adapt to different dose prescriptions and beam configurations. This framework potentially enables DL modeling for clinical sites that have a limited dataset, either due to few cases or due to rapid technology evolution. [ABSTRACT FROM AUTHOR]

Plant SNF1-Related Kinase1 (SnRK1) is an evolutionarily conserved energy-sensing protein kinase that orchestrates transcriptional networks to maintain cellular energy homeostasis when energy supplies become limited. However, the mechanism by which SnRK1 regulates this gene expression switch to gauge cellular energy status remains largely unclear. In this work, we show that the rice histone H3K27me3 demethylase JMJ705 is required for low energy stress tolerance in rice plants. The genetic inactivation of JMJ705 resulted in similar effects as those of the rice snrk1 mutant on the transcriptome, which impairs not only the promotion of the low energy stress-triggered transcriptional program but also the repression of the program under an energy-sufficient state. We show that the α-subunit of OsSnRK1 interacts with and phosphorylates JMJ705 to stimulate its H3K27me3 demethylase activity. Further analysis revealed that JMJ705 directly targets a set of low energy stress-responsive transcription factor genes. These results uncover the chromatin mechanism of SnRK1-regulated gene expression in both energy-sufficient and -limited states in plants and suggest that JMJ705 functions as an upstream regulator of the SnRK1α-controlled transcriptional network. [ABSTRACT FROM AUTHOR]