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Valleytronics has attracted much attention due to its potential applications in information progress and data storage. In this paper, monolayer Cr2S3 is proven to be a ferromagnetic (FM) semiconductor by using first-principles calculations. Moreover, monolayer Cr2S3 exhibits a perpendicular magnetic anisotropy energy of 30 μeV/f.u. Surprisingly, monolayer Cr2S3 presents spontaneous valley polarization, which means that it will be nonvolatile for data storage. Notably, monolayer Cr2S3 changes to an antiferromagnetic (AFM) state from the original FM state under biaxial tensile strain, and its easy axis will be reorientated from out-of-plane to in-plane when the compressive strain is larger than −2%. Importantly, for AFM monolayer Cr2S3, the valley polarization reversion can be realized by an external electric field along the z direction. In brief, valley polarization has been achieved in both FM and AFM monolayer Cr2S3, which is very rare in other valleytronics research. The present research provides a tantalizing candidate for realizing and manipulating valley and spin physics. [ABSTRACT FROM AUTHOR]

Finding efficient photocatalysts is the key to achieving sustainable hydrogen production. In this work, a rational design of Cd2+-doped Zn3In2S6 (ZIS) and a heterojunction structure with g-C3N4 (GCN) was carried out to form a GCN/Cd/ZIS composite. The synergistic effect of Cd2+ doping and heterojunction construction in the photocatalytic hydrogen production process was probed. The results showed that doping Cd2+ modified the bandgap structure of ZIS and improved the photocatalytic activity. The heterojunction construction between Cd/ZIS and GCN also effectively promoted the separation and migration of photogenerated carriers, which significantly improved the hydrogen production performance of the GCN/Cd/ZIS composite. The hydrogen production rate of 15% Cd/ZIS and 5% GCN/Cd/ZIS was 2.45 mmol g−1 h−1, 3.34 mmol g−1 h−1, which was 4.3 and 5.9 times higher than that of ZIS (0.57 mmol g−1 h−1), respectively. This study provides strong evidence that doping and heterojunction construction can synergistically improve photocatalytic activity. [ABSTRACT FROM AUTHOR]

The reduction of aromatic compounds constitutes a fundamental and ongoing area of investigation. The selective reduction of polycyclic aromatic compounds to give either fully or partially reduced products remains a challenge, especially in applications to complex molecules at scale. Herein, we present a selective electrochemical hydrogenation of polycyclic arenes conducted under mild conditions. A noteworthy achievement of this approach is the ability to finely control both the complete and partial reduction of specific aromatic rings within polycyclic arenes by judiciously varying the reaction solvents. Mechanistic investigations elucidate the pivotal role played by in situ proton generation and interface regulation in governing reaction selectivity. The reductive electrochemical conditions show a very high level of functional‐group tolerance. Furthermore, this methodology represents an easily scalable reduction (demonstrated by the reduction of 1 kg scale starting material) using electrochemical flow chemistry to give key intermediates for the synthesis of specific drugs. [ABSTRACT FROM AUTHOR]

Along with the digital transformation of the administrative environment and the end of the COVID-19 pandemic, official endorsers have nurtured a new channel for tourism destination marketing, which is of great significance to local economic recovery. However, less attention has been paid to the different effects of endorsement between ordinary endorsers and official endorsers, mainly due to their contrasting social statuses. To bridge the research gap, the source credibility model and social identity theory are integrated to construct the distinctive attributes of officials, as well as structural equation model is utilized to explore the underlying mechanism of official endorsement. Findings indicate that trustworthiness, the sense of authority, expertise, and attractiveness have direct positive effects on official identification, while also indirectly influencing tourists' attitudes toward the destination through official identification. These findings provide theoretical and managerial implications for the local government managers involved in tourism destination marketing. [ABSTRACT FROM AUTHOR]

Introduction: Ael is known to be one of the weakest A subgroups and can be identified through either the adsorption-elution technique or molecular analysis. Single nucleotide variation in the ABO gene can potentially disrupt the function of ABO glycosyltransferase, resulting in decreased ABO antigen expression. Case Presentation: We reported 1 case of the missense SNV c.1024A>C in the ABO*A1.02 allele was associated with an Ael phenotype. The proband was a 19-year-old male Chinese Han blood donor who was initially stereotyped as type B. Based on the findings from absorption elution, genotype tests, and a family investigation, both the proband and his mother were classified as the AelB phenotype. An uncommon allele was detected in both the proband and his mother, differing by a single nucleotide at position 1,024 from A to C (c.1024A>C) when compared to the ABO*A1.02 allele. The c.1024A>C SNV induces an amino acid substitution, specifically p.Thr342Pro, which consequently leads to the loss of two sheets (p214–p216, p340–p344) in the wild-type A glycosyltransferase (GTA) 3D structure. The removal of these two sheets, situated at the protein’s core, implies the occurrence of an interaction within this domain that affects the stability of the protein structure. Conclusion: AelB is prone to misidentification as type B, and the accurate determination of blood type can be achieved through the integration of the adsorption-elution technique and molecular analysis. [ABSTRACT FROM AUTHOR]

High‐efficiency spatial light phase modulation with wide operating bandwidth is highly significant yet challenging. Dynamic metasurfaces leveraging active materials with tunable optical response provide a promising solution. Current work is generally confronted with restricted operation bandwidth and diminished modulation efficiency, constrained by the limited tunable range and inherent absorption of active materials particular at optical frequency. Recently, the emergence of lossless phase‐change material Sb2Se3 has garnered widespread attention. Its unique characteristics, including near‐zero absorption at near‐infrared and a substantial refractive index contrast ≈0.93 during phase transition, enable the possibility of high‐performance spatial light modulation. Pioneering studies have validated the capability of lossless phase‐change metasurfaces for wavefront control, but are typically restricted to limited efficiency. Here, a hybrid phase‐change metasurface utilizing over‐coupled resonances supported by Sb2Se3 nanoholes is proposed. For the first time in optical frequency, high‐efficiency 4‐level phase modulation covering over π range is experimentally demonstrated with a sizable operating bandwidth of 42 nm and a minimum reflectance of exceeding 0.5. Leveraging optically driven localized phase‐transition technique, dynamic beam deflection is further demonstrated. The work validates the tremendous potential of phase‐change metasurfaces in achieving advanced spatial light control, signifying significant progress for the development and application of phase‐change photonic devices. [ABSTRACT FROM AUTHOR]

Background: In the context of increasing exposure to silica nanoparticles (SiNPs) and ensuing respiratory health risks, emerging evidence has suggested that SiNPs can cause a series of pathological lung injuries, including fibrotic lesions. However, the underlying mediators in the lung fibrogenesis caused by SiNPs have not yet been elucidated. Results: The in vivo investigation verified that long-term inhalation exposure to SiNPs induced fibroblast activation and collagen deposition in the rat lungs. In vitro, the uptake of exosomes derived from SiNPs-stimulated lung epithelial cells (BEAS-2B) by fibroblasts (MRC-5) enhanced its proliferation, adhesion, and activation. In particular, the mechanistic investigation revealed SiNPs stimulated an increase of epithelium-secreted exosomal miR-494-3p and thereby disrupted the TGF-β/BMPR2/Smad pathway in fibroblasts via targeting bone morphogenetic protein receptor 2 (BMPR2), ultimately resulting in fibroblast activation and collagen deposition. Conversely, the inhibitor of exosomes, GW4869, can abolish the induction of upregulated miR-494-3p and fibroblast activation in MRC-5 cells by the SiNPs-treated supernatants of BEAS-2B. Besides, inhibiting miR-494-3p or overexpression of BMPR2 could ameliorate fibroblast activation by interfering with the TGF-β/BMPR2/Smad pathway. Conclusions: Our data suggested pulmonary epithelium-derived exosomes serve an essential role in fibroblast activation and collagen deposition in the lungs upon SiNPs stimuli, in particular, attributing to exosomal miR-494-3p targeting BMPR2 to modulate TGF-β/BMPR2/Smad pathway. Hence, strategies targeting exosomes could be a new avenue in developing therapeutics against lung injury elicited by SiNPs. [ABSTRACT FROM AUTHOR]

Background: The axillary lymph-node metastatic burden is closely associated with treatment decisions and prognosis in breast cancer patients. This study aimed to explore the value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT)–based radiomics in combination with ultrasound and clinical pathological features for predicting axillary lymph-node metastatic burden in breast cancer. Methods: A retrospective analysis was conducted and involved 124 patients with pathologically confirmed early-stage breast cancer who had undergone 18F-FDG PET/CT examination. The ultrasound, PET/CT, and clinical pathological features of all patients were analysed, and radiomic features from PET images were extracted to establish a multi-parameter predictive model. Results: The ultrasound lymph-node positivity rate and PET lymph-node positivity rate in the high nodal burden group were significantly higher than those in the low nodal burden group (χ2 = 19.867, p < 0.001; χ2 = 33.025, p < 0.001). There was a statistically significant difference in the PET-based radiomics score (RS) for predicting axillary lymph-node burden between the high and low lymph-node burden groups. (-1.04 ± 0.41 vs. -1.47 ± 0.41, t = -4.775, p < 0.001). The ultrasound lymph-node positivity (US_LNM) (odds ratio [OR] = 3.264, 95% confidence interval [CI] = 1.022–10.423), PET lymph-node positivity (PET_LNM) (OR = 14.242, 95% CI = 2.960–68.524), and RS (OR = 5.244, 95% CI = 3.16–20.896) are all independent factors associated with high lymph-node burden (p < 0.05). The area under the curve (AUC) of the multi-parameter (MultiP) model was 0.895, which was superior to those of US_LNM, PET_LNM, and RS models (AUC = 0.703, 0.814, 0.773, respectively), with statistically significant differences (Z = 2.888, 3.208, 3.804, respectively; p = 0.004, 0.002, < 0.001, respectively). Decision curve analysis indicated that the MultiP model provided a higher net benefit for all patients. Conclusion: A MultiP model based on PET-based radiomics was able to effectively predict axillary lymph-node metastatic burden in breast cancer. Trial registration: This study was registered with ClinicalTrials.gov (registration number: NCT05826197) on May 7, 2023. [ABSTRACT FROM AUTHOR]

Anion‐derived solid‐electrolyte interphase (SEI) has received growing attention owing to its appealing properties like fast ion transport and excellent passivation effect. However, a sophisticated understanding of anion‐derived SEI is lacking. To common wisdom, anion‐derived SEI features an inorganic‐rich composition. Herein, it is reveal that the freshly formed anion‐derived SEI consists of a polymer‐rich outer layer and an inorganic inner layer. Then, the organic components dissolve during the discharge process, while the inorganic species with low solubility are retained in the empty SEI husk. The accumulation of empty SEI husks during cycling forms a reacted lithium (Li) layer, which features a much higher content of anion‐derived inorganic species than the newly formed SEI. Therefore, the acknowledged "anion‐derived inorganic‐rich SEI" actually refers to the reacted Li layer instead of the freshly formed SEI. This work provides fruitful insights on the compositional features of anion‐derived SEI. [ABSTRACT FROM AUTHOR]

Lymphocyte subsets are the most intuitive expression of the body's immune ability, and the lymphocyte-to-monocyte ratio (LMR) also clearly reflect the degree of chronic inflammation activity. The purpose of this study is to investigate their predictive value of lymphocyte subsets and LMR to neoadjuvant therapy (NAT) efficacy in breast cancer patients. In this study, lymphocyte subsets and LMR were compared between breast cancer patients (n = 70) and benign breast tumor female populations (n = 48). Breast cancer patients were treated with NAT, and the chemotherapy response of the breast was evaluated using established criteria. The differences in lymphocyte subsets and LMR were also compared between pathological complete response (pCR) and non-pCR patients before and after NAT. Finally, data were analyzed using SPSS. The analytical results demonstrated that breast cancer patients showed significantly lower levels of CD3 + T cells, CD4 + T cells, CD4 + /CD8 + ratio, NK cells, and LMR compared to benign breast tumor women (P < 0.05). Among breast cancer patients, those who achieved pCR had higher levels of CD4 + T cells, NK cells, and LMR before NAT (P < 0.05). NAT increased CD4 + /CD8 + ratio and decreased CD8 + T cells in pCR patients (P < 0.05). Additionally, both pCR and non-pCR patients exhibited an increase in CD3 + T cells and CD4 + T cells after treatment, but the increase was significantly higher in pCR patients (P < 0.05). Conversely, both pCR and non-pCR patients experienced a decrease in LMR after treatment. However, this decrease was significantly lower in pCR patients (P < 0.05). These indicators demonstrated their predictive value for therapeutic efficacy. In conclusion, breast cancer patients experience tumor-related immunosuppression and high chronic inflammation response. But this phenomenon can be reversed to varying degrees by NAT. It has been found that lymphocyte subsets and LMR have good predictive value for pCR. Therefore, these markers can be utilized to identify individuals who are insensitive to NAT early on, enabling the adjustment of treatment plans and achieving precise breast cancer treatment. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) is more aggressive and has a higher metastasis rate compared with other subtypes of breast cancer. Due to the lack of drug-targetable receptors, chemotherapy is now the only available systemic treatment for TNBC. However, some patients might still develop drug resistance and have poor prognosis. Therefore, novel molecular biomarkers and new treatment targets are urgently needed for patients with TNBC. To provide molecular insights into TNBC progression, we investigated the function and the underlying mechanism of Defective in cullin neddylation 1 domain containing 5 (DCUN1D5) in the regulation of TNBC. By TCGA dataset and surgical specimens with immunohistochemical (IHC) staining method, DCUN1D5 was identified to be significantly upregulated in TNBC tumor tissues and negatively associated with prognosis. A series of in vitro and in vivo experiments were performed to confirm the oncogenic role of DCUN1D5 in TNBC. Overexpression of FN1 or PI3K/AKT activator IGF-1 could restore the proliferative and invasive ability induced by DCUN1D5 knockdown and DCUN1D5 could act as a novel transcriptional target of transcription factor Yin Yang 1 (YY1). In conclusion, YY1-enhanced DCUN1D5 expression could promote TNBC progression by FN1/PI3K/AKT pathway and DCUN1D5 might be a potential prognostic biomarker and therapeutic target for TNBC treatment. [ABSTRACT FROM AUTHOR]

Objective: The genomic and molecular ecology involved in the stepwise continuum progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) remains unclear and requires further elucidation. We aimed to characterize gene mutations and expression landscapes, and explore the association between differentially expressed genes (DEGs) and significantly mutated genes (SMGs) during the dynamic evolution from AIS to IAC. Methods: Thirty‐five patients with ground‐glass nodules (GGNs) lung adenocarcinomas were enrolled. Whole‐exome sequencing (WES) and transcriptome sequencing (RNA‐Seq) were conducted on all patients, encompassing both tumor samples and corresponding noncancerous tissues. Data obtained from WES and RNA‐Seq were subsequently analyzed. Results: The findings from WES delineated that the predominant mutations were observed in EGFR (49%) and ANKRD36C (17%). SMGs, including EGFR and RBM10, were associated with the dynamic evolution from AIS to IAC. Meanwhile, DEGs, including GPR143, CCR9, ADAMTS16, and others were associated with the entire process of invasive LUAD. We found that the signaling pathways related to cell migration and invasion were upregulated, and the signaling pathways of angiogenesis were downregulated across the pathological stages. Furthermore, we found that the messenger RNA (mRNA) levels of FAM83A, MAL2, DEPTOR, and others were significantly correlated with CNVs. Gene set enrichment analysis (GSEA) showed that heme metabolism and cholesterol homeostasis pathways were significantly upregulated in patients with EGFR/RBM10 co‐mutations, and these patients may have poorer overall survival than those with EGFR mutations. Based on the six calculation methods for the immune infiltration score, NK/CD8+ T cells decreased, and Treg/B cells increased with the progression of early LUAD. Conclusions: Our findings offer valuable insights into the unique genomic and molecular features of LUAD, facilitating the identification and advancement of precision medicine strategies targeting the invasive progression of LUAD from AIS to IAC. [ABSTRACT FROM AUTHOR]

We consider the initial‐boundary problem of the chemotaxis system with indirect consumption ut=Δ(uv−α),x∈Ω,t>0,vt=Δv−vz,x∈Ω,t>0,zt=Δz−z+u,x∈Ω,t>0$$\begin{equation*} {\hspace*{92.5pt}\begin{cases} u_t=\Delta (uv^{-\alpha }),\ \ \ &x\in \Omega,\ t>0,\\[4pt] v_t=\Delta v-vz,\ \ \ &x\in \Omega,\ t>0,\\[4pt] z_t=\Delta z-z+u,\ \ \ &x\in \Omega,\ t>0 \end{cases}} \end{equation*}$$in a smoothly bounded domain Ω⊂Rn$\Omega \subset \mathbb {R}^n$ with n∈{2,3}$n\in \lbrace 2,3\rbrace$. It is shown that for all suitably regular initial data, global solvability in classical sense can be established even with singularly signal‐dependent motilities involved. To be specific, the global classical solution is constructed for arbitrary α>0$\alpha >0$. [ABSTRACT FROM AUTHOR]

A gear form-grinding optimization method is proposed to obtain an optimal profile of a form-grinding wheel by solving a transcendental equation of the contact line between a form-grinding wheel and a helical gear workpiece. Since the equation of the contact line is transcendental, the relationship between the installation angle of the form-grinding wheel and the shape of the contact line cannot be represented by explicit functions, which makes it difficult to obtain the optimal profile of the form-grinding wheel. An optimization method of the contact line between the form-grinding wheel and the gear is proposed using three evaluation parameters that are the overrun, the shift, and the offset. Some gear form-grinding performances, such as machining stroke, tooth deviation, and grinding chatter, can be quantitatively described using those evaluation parameters. Further, a method for optimizing evaluation parameters is proposed, which uses a particle swarm optimization-support vector machine (PSO-SVM) model with the advantage of small-sample robustness to solve evaluation parameters. The PSO-SVM model is trained under the condition of different installation angles of the form-grinding wheel as the input and the evaluation function as the output. The R-squared value of the overrun is 0.986 that vilidate the high accuracy of the PSO-SVM model. Gear form-grinding test results show the proposed method can effectively improve grinding accuracy. • Effects of the contact line shape on gear form-grinding are studied. • A particle swarm optimization-support vector machine (PSO-SVM) model is developed. • A form-grinding wheel optimization method using the PSO-SVM model is developed. • The optimization method can improve accuracy of gear form-grinding. • Effectiveness of the optimization method is verified by form-grinding tests. [ABSTRACT FROM AUTHOR]

The phytoplankton size structure exerts a significant influence on ecological processes and biogeochemical cycles. In this study, the interannual variations in remotely sensed phytoplankton size structure in the southern Tropical Indian Ocean (TIO) and the underlying physical mechanisms were investigated. Significant interannual fluctuations in phytoplankton size structure occur in the southeastern TIO and central southern TIO and are very sensitive to Indian Ocean Dipole (IOD) events. During positive IOD events, the southeast wind anomalies reinforce coastal upwelling off of Java and Sumatra, leading to a shift toward a larger phytoplankton structure in the southeastern TIO. The anomalous anticyclonic circulation deepened the thermocline and triggered the oceanic downwelling Rossby waves, resulting in a smaller phytoplankton structure in the southwestern TIO. During the decay phase of the strong positive IOD events, the sustained warming in the southwestern TIO induced basin-wide warming, thereby maintaining such an anomalous phytoplankton size structure into the following spring. The response of phytoplankton size structure and ocean dynamics displayed inverse patterns during the negative IOD events, with an anomalous larger phytoplankton structure in the central southern TIO. These findings enhance our understanding of phytoplankton responses to climate events, with serious implications for ecosystem changes in a warming climate. [ABSTRACT FROM AUTHOR]

Given the insidious and high-fatality nature of cardiovascular diseases (CVDs), the emergence of fluoride as a newly identified risk factor demands serious consideration alongside traditional risk factors. While vascular smooth muscle cells (VSMCs) play a pivotal role in the progression of CVDs, the toxicological impact of fluoride on VSMCs remains largely uncharted. In this study, we constructed fluorosis model in SD rats and A7R5 aortic smooth muscle cell lines to confirm fluoride impaired VSMCs. Fluoride aggravated the pathological damage of rat aorta in vivo. Then A7R5 were exposed to fluoride with concentration ranging from 0 to 1200 μmol/L over a 24-h period, revealing a dose-dependent inhibition of cell proliferation and migration. The further metabolomic analysis showed alterations in metabolite profiles induced by fluoride exposure, notably decreasing organic acids and lipid molecules level. Additionally, gene network analysis underscored the frequency of fluoride's interference with amino acids metabolism, potentially impacting the tricarboxylic acid (TCA) cycle. Our results also highlighted the ATP-binding cassette (ABC) transporters pathway as a central element in VSMC impairment. Moreover, we observed a dose-dependent increase in osteopontin (OPN) and α-smooth muscle actin (α-SMA) mRNA level and a dose-dependent decrease in ABC subfamily C member 1 (ABCC1) and bestrophin 1 (BEST1) mRNA level. These findings advance our understanding of fluoride as a CVD risk factor and its influence on VSMCs and metabolic pathways, warranting further investigation into this emerging risk factor. [ABSTRACT FROM AUTHOR]

In this paper, the piezomagnetic response of single-lap shear failure of wire arc additively manufactured (WAAM) steel bolted connections was investigated. It aims to explore the use of piezomagnetic measurement as a nondestructive method to detect the failure process of WAAM steel connections under shear loads. The mechanical properties of the materials were obtained by monotonic tensile tests on coupons with different directions of loading relative to the deposition direction. Then, 36 connecting specimens with two printing layer orientations and varying dimensions were tested to failure. The stress-induced magnetic fields around the specimens were monitored online by magnetic probes throughout the loading process. It is found that the anisotropy of WAAM steel can be observed from the piezomagnetic response. The failure modes of lap connections include net section tension, end-splitting, shear-out and tilt-bearing. The results show that the magnetic response exhibits similar behavior to the mechanical response. It is possible to predict the failure mode of the specimens using the magnetic field-displacement curve. The study demonstrates that the piezomagnetic field can be an important indicator of impending shear failure of WAAM steel elements. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a chronic, degenerative neurological disorder characterized by progressive cognitive decline and mental behavioral abnormalities. Mild cognitive impairment (MCI) is regarded as a transitional stage in the progression from normal elderly individuals to patients with AD. While studies have identified abnormalities in brain connectivity in patients with MCI, including functional and structural connectivity, accurately identifying patients with MCI in clinical screening remains challenging. We hypothesized that utilizing machine learning (ML) based on both functional and structural connectivity could yield meaningful results in distinguishing between patients with MCI and normal elderly individuals, so as to provide valuable information for early diagnosis and precise evaluation of patients with MCI. Following clinical criteria, we recruited 32 patients with MCI for the patient group, and 32 normal elderly individuals for the control group. All subjects underwent examinations for resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI). Subsequently, significant functional and structural connectivity features were selected and combined with a support vector machine for classification of the patient and control groups. We observed significantly different functional connectivity in the frontal lobe and putamen between the MCI group and normal controls. The results based on functional connectivity features demonstrated a classification accuracy of 71.88% and an area under the curve (AUC) value of 0.78. In terms of structural connectivity, we found that decreased fractional anisotropy in patients with MCI was significantly associated with Montreal Cognitive Assessment scores, specifically in regions such as the precuneus and cingulate gyrus. The classification results using the structural connectivity feature yielded an accuracy of 92.19% and an AUC value of 0.99. Lastly, combining functional and structural connectivity features resulted in a classification accuracy and AUC value of 93.75% and 0.99, respectively. In this study, we demonstrated a high classification performance, underscoring the potential of both brain functional and structural connectivity in distinguishing patients with MCI from normal elderly individuals. Furthermore, the integration of functional connectivity and structural connectivity features indicated that utilizing rs-fMRI and DTI could enhance the accuracy and specificity of identifying patients with MCI compared with relying on a single neuroimaging technique. • Improving the diagnostic ability for patients with MCI is crucial for diagnosis and intervention in early AD. • Single neuroimaging techniques have limited value in identifying patients with MCI. • The support vector machine model achieved good performance in classification accuracy. • The integration of functional and structural connectivity may enhance cognitive assessment and classification. [ABSTRACT FROM AUTHOR]

To enhance the mechanical properties of polypropylene random copolymer (PPR), polystyrene (PS) with four different contents were added to the PPR matrix through melt blending. Subsequently, using the Multi-Flow Vibration Injection Molding (MFVIM) technology, PPR/PS in situ microfiber composites (MFC) with different blending ratios were prepared. The results indicated that blending ratio had a great impact on the phase morphology and crystal structure of MFVIM samples, which was different from those of conventional injection molding (CIM) samples. PS ultrafine fibers could be formed under the shear field and could absorb the PPR molecular chains to form hybrid shish-kebab structures. Meanwhile, the PPR matrix could also form shish-kebab structures under the effect of strong shear. When the PS content reached 20%, under the combined action of PS in situ microfibers and highly oriented crystal structure, the tensile strength and Young's modulus of the sample were obviously improved and the impact strength remained at a relatively high level. So a strong and tough balanced PPR based material was obtained. These results provide valuable insights for expanding the industrial and daily-life applications of PPR and show promising development prospects. [ABSTRACT FROM AUTHOR]

With the rapid development of sensor and communication technology, multi-sensor data is available to monitor the degradation of complex systems and predict the failure modes. However, two huge challenges remain to be resolved: (i) how to predict the failure modes with limited failure mode labeled systems to alleviate the heavy dependence on expert experience; (ii) how to effectively fuze the useful information from the multi-sensor data to achieve an accurate estimation of the degradation status automatically. To address these issues, we propose a novel semi-supervised prognostic model for the systems with partially observable failure modes, where only a small fraction of the systems in the training set are known for their failure modes. First, we develop a graph-based semi-supervised learning method to extract features characterizing the failure modes. Then, we input these features as well as the multi-sensor streams into an elastic net functional regression model to predict the residual useful lifetime. The proposed model is validated by extensive simulation studies and a case study of aircraft turbofan engines available from the NASA repository. [ABSTRACT FROM AUTHOR]

In this study, we introduce a novel class of partially coherent vector sources, namely radially polarized spatiotemporally partially coherent cosine-Gaussian-correlated Schell-model pulsed (CGCSMP) beams, which are natural extensions of the scalar Gaussian Schell-model pulsed beams. The conditions for the physical realization of this source are established, and analytical formulae for the two-point, two-frequency cross-spectral density matrix elements of a beam propagating through turbulent atmosphere are derived within the framework of the extended Huygens–Fresnel principle and the atmospheric turbulence spectrum model. The behaviors of the spectral intensity, the spectral degree of polarization (DOP), and the spectral degree of coherence (DOC) of the beam during transmission are investigated numerically. Our work enriches the classical theory of propagating stochastic electromagnetic beams and may be useful for applications requiring a specified degree of beam coherence. [ABSTRACT FROM AUTHOR]

Plant essential oils contain many secondary metabolites, some of which can effectively inhibit the growth of pathogenic microorganisms, so it is a very promising antibacterial agent. In this study, a qualitative and quantitative method based on high performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS) was developed for the simultaneous determination of three bioactive substances, cinnamaldehyde (CNM), thymol (THY), and eugenol (EUG), in the essential oils of plants. Necessary tests for linearity, limit of quantification, recovery, carryover contamination and precision of the method were carried out. Then, the antibacterial activity of 3 bioactive compounds against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) was evaluated by minimal inhibitory concentration and the synergistic antimicrobial effect. The results indicated that CNM, THY and EUG had good antibacterial activity. According to the results of fractional inhibitory concentration index (FICI), it is considered that CNM + THY and CNM + THY + EUG has obvious synergistic inhibitory effect on E. coli, and CNM + THY and CNM + EUG has obvious synergistic inhibitory effect on S. aureus. Finally, we analyzed the effect of the bioactive compounds on trace elements in bacteria and found significant changes in magnesium, calcium, copper and iron. [ABSTRACT FROM AUTHOR]

The computational intelligence-based digital forecasting for social systems has been a novel tendency. This work takes forecasting of regional economy as the problem scenario, and introduces radial basis function neural network (RBFNN) to deal with this concern. Hence, an RBFNN-based fast forecasting model for regional economy is constructed in this paper. First, the economic flow data are encoded into sequential format, and RBFNN is employed to establish a sequential forecasting model that fits flow data. In addition, a fuzzy clustering method is further utilized to complete missing data in flow sequence, in order to improve the data quality for model calculation. In simulation procedure, the proposal is implemented on real economic operation data for assessment, and mean absolute error (MAE) is introduced to measure the forecasting performance. Several typical regression-based forecasting methods are introduced as the baseline. The experimental results show that MAE of the proposal is about 20%–30% lower than that of baseline methods, showing a better forecasting performance. [ABSTRACT FROM AUTHOR]

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor of the urinary system. To explore the potential mechanisms of DHODH in ccRCC, we analyzed its molecular characteristics using public databases. TCGA pan-cancer dataset was used to analyze DHODH expression in different cancer types and TCGA ccRCC dataset was used to assess differential expression, prognosis correlation, immune infiltration, single-gene, and functional enrichment due to DHODH. The GSCALite and CellMiner databases were employed to explore drugs and perform molecular docking analysis with DHODH. Protein–protein interaction networks and ceRNA regulatory networks of DHODH were constructed using multiple databases. The effect of DHODH on ccRCC was confirmed in vitro. DHODH was highly expressed in ccRCC. Immune infiltration analysis revealed that DHODH may be involved in regulating the infiltration of immunosuppressive cells such as Tregs. Notably, DHODH influenced ccRCC progression by forming regulatory networks with molecules, such as hsa-miR-26b-5p and UMPS and significantly enhanced the malignant characteristics of ccRCC cells. Several drugs, such as lapatinib, silmitasertib, itraconazole, and dasatinib, were sensitive to DHODH expression and exhibited strong molecular binding with it. Thus, DHODH may promote ccRCC progression and is a candidate effective therapeutic target for ccRCC. [ABSTRACT FROM AUTHOR]

Ferroptosis is a regulatory cell death that is dependent on iron‐mediated lipid peroxidation and cell membrane damage. The use of iron‐based nanocarriers to activate ferroptosis is of great significance in oncotherapy. However, the limited endogenous hydrogen peroxide (H2O2) and high expression of glutathione (GSH) in tumor cells restrict the efficiency of iron‐based nanocarriers in inducing ferroptosis. Herein, a ferric phosphate nanotherapeutic system (denoted as FeP@HCPT‐HA) is reported with H2O2‐supply and GSH‐elimination properties for tumor self‐enhanced ferroptosis and chemotherapy. FeP@HCPT‐HA is obtained by a coprecipitation method with the in situ loading of 10‐hydroxycamptothecin (HCPT), followed by the modification of hyaluronic acid (HA). FeP@HCPT‐HA actively targets CD44‐overexpressed tumor cells and degrades in acidic tumor microenvironment to release HCPT, Fe2+ and Fe3+. As a chemotherapy drug, HCPT not only induces tumor cell apoptosis but also supplies H2O2 for Fe2+‐mediated Fenton reaction to enhance ferroptosis. The released Fe3+ depletes GSH by the redox reaction between Fe3+ and GSH, which down‐regulates the expression of glutathione peroxidase 4 (GPX4) and enhances lipid peroxidation, resulting in enhanced ferroptosis. The integration of tumor targeting and tumor‐specific activation, as well as H2O2‐supply and GSH‐elimination, endow the FeP@HCPT‐HA with effective tumor growth inhibition by the enhanced ferroptosis and chemotherapy. [ABSTRACT FROM AUTHOR]

In this study, a novel dynamic model of a ball bearing based on rigid–elastic–liquid (REL) coupling structure considering external load excitation is established, and the dynamic response of its outer ring under external load excitation is examined. First, the differential equation of the journal motion (i.e. the outer ring) is derived based on Newton’s law, and the oil film force induced by the REL coupling structure is determined by using the central finite difference method, planar bending theory of thin ring, and Simpson’s rule. Further, the fourth and fifth-order variable step length Runge–Kutta method is used to solve the kinematic differential equation. Second, the dynamic characteristics of the outer ring of the bearing under different speeds and elastic support structural parameters are examined. Finally, the feasibility of the theoretical model is verified through experiments. The results show that compared with the traditional squeeze film damper (SFD) system, the ball bearing with REL coupling structure is more stable, and the vibration damping effect is better under higher bearing speed, lower squirrel cage stiffness, and smaller elastic ring flexibility coefficient. The above findings provide useful insights into the dynamic characteristics of REL coupled ball bearings under unbalanced excitation, which can serve as a reference for the optimization design of such ball bearings. [ABSTRACT FROM AUTHOR]

The flowability and mechanical properties are increasingly crucial in the filling process of deep metal mines with mining depths exceeding 1000 m. The rheological properties of filling slurry in the pipeline were analyzed through rheological tests, L-tube self-flow tests, and semi-industrial loop tests. The results revealed that with an increase in the cement-to-tailings mass ratio (c/t ratio) and mass concentration, the slurry exhibited a higher flow resistance and decreased stowing gradient. During slurry transportation, the pressure loss in the straight pipe was positively correlated with the slurry flow rate, c/t ratio, and mass concentration. A uniaxial compressive strength (UCS) test was conducted to analyze the mechanical properties of the cemented paste backfill containing BMC (CCPB) in both standard and deep-underground curing environments. The UCS of the CCPB showed an increasing trend with the rise in curing age, mass concentration, and the c/t ratio. The comprehensive analysis concluded that when the c/t ratio is 1:4, and the mass concentration is approximately 74%, and parameters such as the slump, bleeding rate, and flowability of the filling slurry meet the criteria for conveying and goaf filling, resulting in a high-strength filling body. [ABSTRACT FROM AUTHOR]

Background: Oxidative stress is implicated in the pathogenesis of heart failure. Dual oxidase 1 (DUOX1) might be important in heart failure development through its mediating role in oxidative stress. This study was designed to evaluate the potential role of DUOX1 in heart failure. Materials and methods: AC16 cells were treated with 2 µmol/L of doxorubicin (DOX) for 12, 24, and 48 h to construct a heart failure model. DUOX1 overexpression and silencing in AC16 cell were established. DUOX1 expression was detected by Quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. Pyroptosis and reactive oxygen species (ROS) production were measured by flow cytometry. Results: Increased DUOX1 expression levels were observed after DOX treatment for 24 h in AC16 cells. DUOX1 silencing inhibited DOX-induced pyroptosis and ROS production. The release of IL-1β, IL-18, and lactate dehydrogenase (LDH), and expression levels of pyroptosis-related proteins were also decreased. DUOX1 overexpression increased pyroptosis, ROS production, IL-1β, IL-18, and LDH release, and pyroptosis-related protein expression. N-acetyl-cysteine (NAC) significantly reversed DUOX1-induced pyroptosis, ROS, and related factors. Conclusion: These results suggest that DUOX1-derived genotoxicity could promote heart failure development. In the process, oxidative stress and pyroptosis may be involved in the regulation of DUOX1 in heart failure. [ABSTRACT FROM AUTHOR]

Remote sensing image change detection (CD) is an important means in remote sensing data analysis tasks, which can help us understand the surface changes in high-resolution (HR) remote sensing images. Traditional pixel-based and object-based methods are only suitable for low- and medium-resolution images, and are still challenging for complex texture features and detailed image detail processing in HR images. At present, the method based on deep learning has problems such as inconsistent fusion and difficult model training in the combination of the difference feature information of the deep and shallow layers and the attention mechanism, which leads to errors in the distinction between the changing region and the invariant region, edge detection and small target detection. In order to solve the above problems of inconsistent fusions of feature information aggregation and attention mechanisms, and indistinguishable change areas, we propose a multi-scale feature fusion Siamese network based on attention mechanism (ABMFNet). To tackle the issues of inconsistent fusion and alignment difficulties when integrating multi-scale fusion and attention mechanisms, we introduce the attention-based multi-scale feature fusion module (AMFFM). This module not only addresses insufficient feature fusion and connection between different-scale feature layers, but also enables the model to automatically learn and prioritize important features or regions in the image. Additionally, we design the cross-scale fusion module (CFM) and the difference feature enhancement pyramid structure (DEFPN) to assist the AMFFM module in integrating differential information effectively. These modules bridge the spatial disparity between low-level and high-level features, ensuring efficient connection and fusion of spatial difference information. Furthermore, we enhance the representation and inference speed of the feature pyramid by incorporating a feature enhancement module (FEM) into DEFPN. Finally, the BICD dataset proposed by the laboratory and public datasets LEVIR-CD and BCDD are compared and tested. We use F1 score and MIoU values as evaluation metrics. For AMBMFNet, the F1 scores on the three datasets are 77.69%, 81.57%, and 77.91%, respectively, while the MIoU values are 84.65%, 85.84%, and 84.54%, respectively. The experimental results show that ABMFNet has better effectiveness and robustness. [ABSTRACT FROM AUTHOR]

Simple Summary: Partial hepatectomy (PH) is a common clinical surgery for managing hepatocellular carcinoma (HCC). A common concern about PH is the high tumor recurrence rate following PH. Previous studies have reported that PH can promote the growth of transplanted HCC in rodents. In the current study, we have used an inducible krasG12V-driven zebrafish HCC model to investigate the effects of PH on the oncogene-induced de novo HCC development. We found that PH can significantly promote the development of krasG12V-induced HCC in zebrafish. This enhancing effect could be attributed to the increased oxidative stress and the enhanced deregulation of molecular factors. Our findings may provide references for the future development of novel therapeutic strategies. The purpose of this study was to investigate the effects of PH on the development of oncogenic krasG12V-induced HCC in zebrafish. The inducible HCC model in Tg(fabp10a:rtTA2s-M2; TRE2:EGFP-krasG12V) zebrafish was used. PH or sham surgery was performed before the induction of oncogenic krasG12V expression in the livers of transgenic zebrafish. Histological analysis was carried out to determine the progression of HCC and other HCC-associated features including hepatocyte proliferation, extracellular matrix production, and local oxidative stress. The similarity between the process of PH-induced liver regeneration and that of krasG12V-induced HCC development was further compared by RNA-Seq analysis. The results show that PH promotes the development of krasG12V-induced HCC in zebrafish possibly through enhancing neutrophil-mediated oxidative stress and promoting the upregulation of s100a1, and the downregulation of ribosome biogenesis. [ABSTRACT FROM AUTHOR]

The Plateau–Rayleigh instability (PRI) of a liquid column, which always spontaneously breaks into droplets to minimize surface energy, underlies a variety of fascinating phenomena in daily life and industrial applications. Different from the free liquid column, the evolution of the liquid film on a fiber involves solid‐liquid interfaces which allow for regulating the PRI. Recently, natural fibers with certain topologies have witnessed various dynamic liquid behaviors from droplet manipulation to continuous liquid films. Tailoring the topology of local curved liquid film by the structural‐confinement is the key to manipulating liquids, where the asymmetric Laplace pressure generated by the asymmetric/non‐spherical liquid film promotes the liquid motion. In nature, the spider silk collects droplets efficiently by the spindle‐knot structure; while the mulberry silk enables a smooth surface‐coating on dual‐parallel fibers. Drawing inspirations, many artificial structured fibers are developed to precisely regulate liquid behaviors in the form of either separated droplets or continuous liquid films, which have demonstrated applications as fluidic coating, micro‐patterning, and materials fabrication. Here, recent research progress on bioinspired fibrous PRI from the viewpoints of tailoring the Laplace pressure by rationally designing the surface topology, which offers inspiration for liquid manipulation using open fibrous media, is reviewed. [ABSTRACT FROM AUTHOR]

Exploring on reliability modeling and analysis on a marine equipment in a dynamic environment is a meaningful and challenging issue, because the system commonly carries out the task at sea away from land and suffers a distinct influence of environment. Thus, a reliability model of a multi‐state repairable system operating in dynamic environment is developed by introducing the background of the marine power system in this paper. The novelty of the research lies in the modeling and computing methods are relatively innovative by employing the aggregated stochastic processes, Hadamard production and matrix‐analytic method. First, the working modes of the marine power system under several different kinds of conditions are introduced. Then, the evolution of both the system states and environment are described as discrete‐time Markov chains with multiple and different transition probability matrices. The failure probability and repair probability of components are also distinct in different environments. Furthermore, some performance indexes, especially the index relevant to the environment, are derived, respectively. Finally, the conclusion is obtained by a numerical example of the marine power system, which also illustrates the validity and applicability of the proposed model. [ABSTRACT FROM AUTHOR]

In this paper, a novel parametrized guaranteed cost control (PGCC) method with prescribed performance control (PPC) is proposed for nonlinear systems with unknown bounded uncertainties and external disturbances described by Euler‐Lagrange (EL) equations. The proposed method is capable of ensuring a robust optimal performance in the presence of dynamics constraints without the specific information of nonlinear perturbation. As a consequence, the conditions in the form of disturbances and uncertainties are also relaxed. The augmented model is converted by transforming the uncertainties and disturbances in the original system to a mismatched term using asymmetric PPC. By designing and modifying the novel guaranteed cost function to account for the maximum value of the nonlinear perturbation, an infinite‐horizon PGCC problem is proposed by the unconstrained stationary optimal control problem. The relevant proposed linear parametrized Hamilton‐Jacobian‐Bellman (PHJB) equation is approximated to solve by a critic‐only neural network (NN) with efficient computationally. Uniformly ultimately bounded stability is guaranteed via a Lyapunov‐based stability analysis. Finally, numerical simulation results demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

AbstractRheumatoid arthritis (RA) is a chronic autoimmune inflammation. Excessive proliferation and inadequate apoptosis of synovial macrophages are the crucial events of RA. Therefore, delivering therapeutic molecules to synovial macrophages specifically to tackle apoptotic insufficiency probably can be an efficient way to reduce joint inflammation and bone erosion. Based on the characteristics of dextran sulphate (DS) specifically binding scavenger receptor A (SR-A) on macrophage and celastrol (CLT) inducing apoptosis, we designed synovial macrophage-targeted nano-emulsions encapsulated with CLT (SR-CLTNEs) and explored their anti-RA effect. After intravenous injection, fluorescence-labelled SR-CLTNEs successfully targeted inflammatory joints and synovial macrophages in a mouse model of RA, with the macrophage targeting efficiency of SR-CLTNEs, CLTNEs and free DID was 20.53%, 13.93% and 9.8%, respectively. In vivo and in vitro studies showed that SR-CLTNEs effectively promoted the apoptosis of macrophages, reshaped the balance between apoptosis and proliferation, and ultimately treated RA in a high efficiency and low toxicity manner. Overall, our work demonstrates the efficacy of using SR-CLTNEs as a novel nanotherapeutic approach for RA therapy and the great translational potential of SR-CLTNEs. [ABSTRACT FROM AUTHOR]

The electrochemical C‐N coupling process, facilitating the production of organic nitrogen substances (such as urea, methylamine, formamide, and ethylamine) via the simultaneous reduction of carbon dioxide (CO2) and small nitrogen‐based substances, stands at the forefront of advancing carbon neutrality and the artificial nitrogen cycle. This method has garnered substantial interest due to its potential economic and environmental benefits. Although considerable progress has been achieved in this emerging field, it still faces challenges, including slow reactant adsorption, competing side reactions, and complex multi‐step pathways, resulting in low yields and selectivity. Strategically designing and developing low‐cost and exceptionally performant catalysts is crucial for cost‐effective and precise electrochemical C─N bonding. This article offers an in‐depth review of the electrosynthesis of valuable organic nitrogen compounds at ambient conditions from earth‐abundant resources/wastes, such as CO2 and small nitrogenous molecules (nitrogen: N2, nitrite: NO2−, nitrate: NO3−, ammonia: NH3, etc.), via electrochemical C─N bond formation reactions, especially using carbon‐based catalysts. The relevant electrochemical C─N bond formation mechanisms, the design principles of advanced carbon‐based electrocatalysts, and the impact of different electrolyser designs are discussed, along with the present obstacles and upcoming prospects in this dynamic field. [ABSTRACT FROM AUTHOR]

High-quality gridded data on industrial water use are vital for research and water resource management. However, such data in China usually have low accuracy. In this study, we developed a gridded dataset of monthly industrial water withdrawal (IWW) for China, which is called the China Industrial Water Withdrawal (CIWW) dataset; this dataset spans a 56-year period from 1965 to 2020 at spatial resolutions of 0.1 and 0.25°. We utilized > 400 000 records of industrial enterprises, monthly industrial product output data, and continuous statistical IWW records from 1965 to 2020 to facilitate spatial scaling, seasonal allocation, and long-term temporal coverage in developing the dataset. Our CIWW dataset is a significant improvement in comparison to previous data for the characterization of the spatial and seasonal patterns of the IWW dynamics in China and achieves better consistency with statistical records at the local scale. The CIWW dataset, together with its methodology and auxiliary data, will be useful for water resource management and hydrological models. This new dataset is now available at 10.6084/m9.figshare.21901074 (Hou and Li, 2023). [ABSTRACT FROM AUTHOR]

BACKGROUND: Although cone beam computed tomography (CBCT) plays an important role in the diagnosis and treatment of oral diseases, its image segmentation method needs to be further improved, and there are still objections about the clinical application effect of general anesthesia (GA) on children's dental fear (CDF). OBJECTIVE: This study aimed to investigate the application value of CBCT based on intelligent computer segmentation model in oral diagnosis and treatment of children in the context of biomedical signals, and to analyze the alleviating effect of GA on CDF. METHODS: Based on the regional level set (CV) algorithm, the local binary fitting (LBF) model was introduced to optimize it, and the tooth CBCT image segmentation model CV-LBF was established to compare the segmentation accuracy (SA), maximum symmetric surface distance (MSSD), average symmetric surface distance (ASSD), over segmentation rate (OR), and under segmentation rate (UR) between these model and other algorithms. 82 children with CDF were divided into general anesthesia group (GAG) (n = 38) and controls (n = 44) according to the voluntary principle of their families. Children in GAG were treated with GA and controls with protective fixed intervention. Children's fear survey schedule-dental subscale (CFSS-DS) and Venham scores were counted before intervention in the two groups. CFSS-DS scores were recorded at 2 hours after intervention and after recovery in children in GAG. CFSS-DS and Venham scores were performed in all children 1 week after surgery. RESULTS: The results showed that the S ⁢ A value of CV-LBF algorithm was higher than that of region growing algorithm (P < 0.05). OR, UR, MSSD, and ASSD values of CV-LBF algorithm were evidently lower than those of other algorithms (P < 0.05). CFSS-DS scores were lower in GAG than in controls 2 hours after intervention and at return visits after 1 week of intervention (P < 0.001), and Venham scores were lower in GAG than in controls after intervention (P < 0.001). After intervention, the proportion of children with Venham grade 0, 1, 2, and 3 was obviously higher in GAG than in controls (P < 0.001), while the proportion of children with Venham grade 4 and 5 was clearly higher in controls than in GAG (P < 0.001). CONCLUSION: The results revealed that the computer intelligent segmentation model CV-LBF has potential application value in CBCT image segmentation of children's teeth, and GA can effectively alleviate anxiety of children with CDF and can be used as biomedical signals. [ABSTRACT FROM AUTHOR]

Replicability is the cornerstone of modern scientific research. Reliable identifications of genotype-phenotype associations that are significant in multiple genome-wide association studies (GWASs) provide stronger evidence for the findings. Current replicability analysis relies on the independence assumption among single-nucleotide polymorphisms (SNPs) and ignores the linkage disequilibrium (LD) structure. We show that such a strategy may produce either overly liberal or overly conservative results in practice. We develop an efficient method, ReAD, to detect replicable SNPs associated with the phenotype from two GWASs accounting for the LD structure. The local dependence structure of SNPs across two heterogeneous studies is captured by a four-state hidden Markov model (HMM) built on two sequences of p values. By incorporating information from adjacent locations via the HMM, our approach provides more accurate SNP significance rankings. ReAD is scalable, platform independent, and more powerful than existing replicability analysis methods with effective false discovery rate control. Through analysis of datasets from two asthma GWASs and two ulcerative colitis GWASs, we show that ReAD can identify replicable genetic loci that existing methods might otherwise miss. Replicability is one of the central issues in scientific research. We develop a robust and powerful method to assess replicability in GWAS via the repeated significance of SNPs. By accounting for the linkage disequilibrium structure, our method can identify replicable genetic loci that existing methods might otherwise miss. [ABSTRACT FROM AUTHOR]

Actin is a highly conserved cytoskeletal protein that is present in all eukaryotes. Polymerization of actin to filamentous actin is essential for numerous cellular processes. Abnormal actin dynamics are directly associated with a variety of diseases, including cancer, immunological and neurological disorders. However, the dynamics of actin are not fully understood. In this work, we study the effects of nucleotides and metal ions on conformation of F/G-actin using molecular dynamics (MD) simulations. Our results show that different nucleotides and metal ions change the conformation of actin. The state of Adenosine Triphosphate (ATP) binding on F-actin conformation is more stable than G-actin. The D-loop has a large fluctuation when Ca 2 + binds to G-ATP-actin than Mg 2 + binds. Adenosine Diphosphate (ADP) binding leads to a stronger residual correlation on F-actin conformation, while it is opposite on G-actin. In addition, the detailed interactions between nucleotides and adjacent residues are discussed on different states of actin. This work provides a structural basis for understanding how the different nucleotides/metal ions binding influences the conformation of actin. Actin is crucial for cellular processes through its polymerization. Abnormal actin dynamics are linked to diseases, including cancer. This study investigates how nucleotides and metal ions impact F/G-actin conformation, providing a structural basis for understanding their influence on actin dynamics. [ABSTRACT FROM AUTHOR]

Summary: Soybean is a short‐day plant that typically flowers earlier when exposed to short‐day conditions. However, the identification of genes associated with earlier flowering time but without a yield penalty is rare. In this study, we conducted genome‐wide association studies (GWAS) using two re‐sequencing datasets that included 113 wild soybeans (G. soja) and 1192 cultivated soybeans (G. max), respectively, and simultaneously identified a candidate flowering gene, qFT13‐3, which encodes a protein homologous to the pseudo‐response regulator (PRR) transcription factor. We identified four major haplotypes of qFT13‐3 in the natural population, with haplotype H4 (qFT13‐3H4) being lost during domestication, while qFT13‐3H1 underwent natural and artificial selection, increasing in proportion from 4.5% in G. soja to 43.8% in landrace and to 81.9% in improve cultivars. Notably, most cultivars harbouring qFT13‐3H1 were located in high‐latitude regions. Knockout of qFT13‐3 accelerated flowering and maturity time under long‐day conditions, indicating that qFT13‐3 functions as a flowering inhibitor. Our results also showed that qFT13‐3 directly downregulates the expression of GmELF3b‐2 which is a component of the circadian clock evening complex. Field trials revealed that the qft13‐3 mutants shorten the maturity period by 11 days without a concomitant penalty on yield. Collectively, qFT13‐3 can be utilized for the breeding of high‐yield cultivars with a short maturity time suitable for high latitudes. [ABSTRACT FROM AUTHOR]

Hematologic toxicities (HTs) are among the most common toxicities of combined immunotherapy and radiation therapy (RT). It remains essential to prevent RT-induced HTs because they can cause treatment discontinuation (influencing antitumoral effects) and because lymphopenia might dampen the effects of immunotherapy. To date, there are no studies examining the effect of thoracic vertebral body (TVB) RT dose on HTs in patients with non-small cell lung cancer receiving combined lung RT and programmed cell death (ligand) 1 immunotherapy. For standardization, all doses were reported as 2-Gy equivalents (EQD2). Mirroring publications before the immunotherapy era, TVB volumes referred to T1-T10, and specific dosimetric parameters (Dmean EQD2, V5 EQD2 -V60 EQD2) were analyzed. Logistic regression estimated associations between grade ≥3 HTs (HT3+) and dosimetric/clinical parameters. Normal tissue complication probability (NTCP) models were constructed by logistic regression analysis modeling for HT3+. Receiver operating characteristic (ROC) analysis delineated TVB dosimetric thresholds, the stratification of which was able to evaluate post-RT absolute lymphocyte count and immunotherapy responses. Areas under the curve (AUCs) for NTCP models were corroborated by bootstrapping (optimism-corrected) methodology. In 132 patients, there were 26 (19.7%) instances of HT3+. On multivariate analysis, Dmean EQD2 and V5 EQD2 to V20 EQD2 were associated with HT3+ (P <.05 for all). The NTCP models illustrated a 50% probability of HT3+ at a Dmean EQD2 = 39.8 Gy, V5 EQD2 = 87.4%, V10 EQD2 = 77.0%, and V20 EQD2 = 68.4%. ROC analysis delineated optimal thresholds of HT3+ with Dmean EQD2 ± 30.2 Gy, V5 EQD2 ± 69.1%, V10 EQD2 ± 64.6%, and V20 EQD2 ± 53.5%. Patients treated with values above those cutoffs had over double the risk of HT3+, with significant differences in post-RT absolute lymphocyte count and immunotherapy responses (P <.05 for all). AUCs for each individual parameter ranged from 0.743 to 0.798, and combining all 4 aforementioned cutoffs into a ROC curve resulted in a qualitatively higher AUC (0.836). This hypothesis-generating work suggests that TVB dosimetry may equate with HT3+ in patients with non-small cell lung cancer undergoing combined lung RT/immunotherapy. Applying TVB dose constraints in this population could reduce HT3+ and avoid dampening of immunotherapy responses, but prospective validation is required. [Display omitted] [ABSTRACT FROM AUTHOR]

Timely and accurate forecasting of well production in tight gas reservoirs is of paramount importance for comprehensive field development and financial decision-making. Despite the application of deep learning (DL) models in constructing predictive frameworks, their intricate nature and limited interpretability present challenges for petroleum engineers, hindering their understanding of learned inference mechanisms and trust in predictions. This study advocates for the adoption of interpretable DL solutions, incorporating SHapley Additive exPlanations (SHAP), to provide explicit elucidations of a prediction model by implemented by gated recurrent networks. The method's efficacy is substantiated using data from the Tao2 gas field in the Ordos Basin, China. The outcomes underscore the model's exceptional predictive capabilities. Leveraging the SHAP method for global interpretation provides valuable insights into the collective impact of various factors. Simultaneously, employing SHAP for local interpretation furnishes personalized explanations for well productivity predictions. The findings gleaned from this research are poised to enhance well operations and field development planning. [ABSTRACT FROM AUTHOR]

Cr3+‐activated near‐infrared (NIR) phosphors have gained extensive attention for use in NIR phosphor‐converted light‐emitting diodes (pc‐LEDs), which are required for smart NIR spectroscopy techniques. Nevertheless, obtaining broadband NIR‐emitting phosphors with outstanding thermal stabilities and photoluminescence (PL) efficiencies remains a significant challenge. Herein, considering NaSr2XGe5O14 (X = Al, Ga, Sc, and In) as hosts, which possess a large band gap and multiple sites for the substitution of Cr3+ ions. NaSr2XGe5O14:Cr3+ phosphors are successfully prepared using a solid‐state reaction technology. Upon blue light excitation, the phosphors cover a broad NIR emission band in 650–1100 nm region. Notably, an abnormal blueshift and PL enhancement are observed following the substitution of Al/Ga with Sc/In. In particular, the PL internal quantum efficiency is improved from 34.5% (NaSr2GaGe5O14: Cr3+) to 87.5% (NaSr2ScGe5O14: Cr3+). Moreover, the manufactured NIR pc‐LED exhibited an exceptional photoelectric efficiency of 17.7% with an NIR output power of 10.2 mW at 20 mA, and its potential application in nondestructive detection is demonstrated. [ABSTRACT FROM AUTHOR]

Manganese molybdate has garnered considerable interest in supercapacitor research owing to its outstanding electrochemical properties and nanostructural stability but still suffers from the common problems of transition metal oxides not being able to reach the theoretical specific capacitance and lower electrical conductivity. Doping phosphorus elements is an effective approach to further enhance the electrochemical characteristics of transition metal oxides. In this study, MnMoO4·H2O nanosheets were synthesized on nickel foam via a hydrothermal route, and the MnMoO4·H2O nanosheet structure was successfully doped with a phosphorus element using a gas–solid reaction method. Phosphorus element doping forms phosphorus–metal bonds and oxygen vacancies, thereby increasing the charge storage and conductivity of the electrode material. The specific capacitance value is as high as 2.112 F cm−2 (1760 F g−1) at 1 mA cm−2, which is 3.2 times higher than that of the MnMoO4·H2O electrode (0.657 F cm−2). The P–MnMoO4//AC ASC device provides a high energy density of 41.9 Wh kg−1 at 666.8 W kg−1, with an 84.5% capacity retention after 10,000 charge/discharge cycles. The outstanding performance suggests that P–MnMoO4 holds promise as an electrode material for supercapacitors. [ABSTRACT FROM AUTHOR]

Anaerobic digestion is an important means to turn agricultural waste into resources and an important way to address the challenges in treating vegetable residues in China. In this study, the co-digestion of dairy manure with tomato residue was investigated to clarify the effect of the total solids (TS) of the digestion substrate on methane's production and mechanism using the self-made anaerobic digestion device. The results showed that all treatments could rapidly ferment methane and that the daily methane production showed a trend of increasing first and then decreasing. The optimal concentrations of the digestion substrate for liquid anaerobic digestion (L-AD), hemi-solid-state anaerobic digestion (HSS-AD), and solid-state anaerobic digestion (SS-AD) were 10%, 18%, and 25%, respectively. Compared with SS-AD and HSS-AD, L-AD gas production peaked 3–6 days earlier. Treatment TS25 had the best cumulative methane production, reaching 117.4 mL/g VS. However, treatment TS6 had acid accumulation and a very unstable system. The cumulative methane production of SS-AD was higher than that of HSS-AD and L-AD. Firmicutes and Bacteroidetes were the dominant flora, and Methanoculleus, Methanosarcina, and Methanobrevibacter were the main archaeal groups. The TS significantly changed the microbial community composition of the digestion system, especially the low TS treatment. The results presented herein indicated that TS significantly changed the bacterial and archaeal community composition of the digestion system, and thus with the increase in TS from 6% to 25%, the methane yield increased. [ABSTRACT FROM AUTHOR]

The significance of noncontrast computer tomography (CT) image markers in predicting hematoma expansion (HE) following intracerebral hemorrhage (ICH) within different time intervals in the initial 24 hours after onset may be uncertain. Hence, our objective was to examine the predictive value of clinical factors and CT image markers for HE within the initial 24 hours using machine learning algorithms. Four machine learning algorithms, including extreme gradient boosting (XGBoost), support vector machine, random forest, and logistic regression, were employed to assess the predictive efficacy of HE within every 6-hour interval during the first 24 hours post-ICH. The area under the receiver operating characteristic curves was utilized to appraise predictive performance across various time periods within the initial 24 hours. A total of 604 patients were included, with 326 being male, and 112 experiencing hematoma expansion (HE). The findings from machine learning algorithms revealed that computed tomography (CT) image markers, baseline hematoma volume, and other factors could accurately predict HE. Among these algorithms, XGBoost demonstrated the most robust predictive model results. XGBoost's accuracy at different time intervals was 0.89, 0.82, 0.87, and 0.94, accompanied by F1-scores of 0.89, 0.80, 0.87, and 0.93, respectively. The corresponding area under the curve was 0.96, affirming the precision of the predictive capability. Computed tomography (CT) imaging markers and clinical factors could effectively predict HE within the initial 24 hours across various time periods by machine learning algorithms. In the expansive landscape of big data and multimodal cerebral hemorrhage, machine learning held significant potential within the realm of neuroscience. [ABSTRACT FROM AUTHOR]

Whether to use face priors in the face super-resolution (FSR) methods is a symmetry problem.Various face priors are used to describe the overall and local face features, making the generation of super-resolution face images expensive and laborious. FSR methods that do not require any prior information tend to focus too much on the local features of the face, ignoring the modeling of global information. To solve this problem, we propose a dual-path facial image super-resolution network (SwinDPSR) fused with Swin Transformer. The network does not require additional face priors, and it learns global face shape and local face components through two independent branches. In addition, the channel attention ECA module is used to aggregate the global and local face information in the above dual-path sub-networks, which can generate corresponding high-quality face images. The results of face super-resolution reconstruction experiments on public face datasets and a real-scene face dataset show that SwinDPSR is superior to previous advanced methods both in terms of visual effects and objective indicators. The reconstruction results are evaluated with four evaluation metrics: peak signal-to-noise ratio (PSNR), structural similarity (SSIM), learned perceptual image patch similarity (LPIPS), and mean perceptual score (MPS). [ABSTRACT FROM AUTHOR]

Objective: A clock relating amyloid positron emission tomography (PET) to time was used to estimate the timing of biomarker changes in sporadic Alzheimer disease (AD). Methods: Research participants were included who underwent cerebrospinal fluid (CSF) collection within 2 years of amyloid PET. The ages at amyloid onset and AD symptom onset were estimated for each individual. The timing of change for plasma, CSF, imaging, and cognitive measures was calculated by comparing restricted cubic splines of cross‐sectional data from the amyloid PET positive and negative groups. Results: The amyloid PET positive sub‐cohort (n = 118) had an average age of 70.4 ± 7.4 years (mean ± standard deviation) and 16% were cognitively impaired. The amyloid PET negative sub‐cohort (n = 277) included individuals with low levels of amyloid plaque burden at all scans who were cognitively unimpaired at the time of the scans. Biomarker changes were detected 15–19 years before estimated symptom onset for CSF Aβ42/Aβ40, plasma Aβ42/Aβ40, CSF pT217/T217, and amyloid PET; 12–14 years before estimated symptom onset for plasma pT217/T217, CSF neurogranin, CSF SNAP‐25, CSF sTREM2, plasma GFAP, and plasma NfL; and 7–9 years before estimated symptom onset for CSF pT205/T205, CSF YKL‐40, hippocampal volumes, and cognitive measures. Interpretation: The use of an amyloid clock enabled visualization and analysis of biomarker changes as a function of estimated years from symptom onset in sporadic AD. This study demonstrates that estimated years from symptom onset based on an amyloid clock can be used as a continuous staging measure for sporadic AD and aligns with findings in autosomal dominant AD. ANN NEUROL 2024;95:951–965 [ABSTRACT FROM AUTHOR]

Background: Spinal meningiomas coexisting with schwannomas in patients without neurofibromatosis are extremely rare lesions. There were only 15 cases reported to date, which were concurrent intradural tumors of different pathological types. Case presentation: Herein, we present a rare case of a 15-year-old child with concurrent spinal dorsal meningioma and ventral giant invasive schwannoma at C7-T3 and T10-S5 spinal levels. Preoperative magnetic resonance imaging and computed tomography indicated the schwannoma across the thoracic and lumbosacral transitional vertebra, with extensive bony erosion of the sacrum. The results of surgical resection were mostly satisfactory. Conclusions: The present case is the youngest patient diagnosed with concurrent intradural tumors at different spinal levels. The pathogenetic mechanism remains unclear. The clinical presentations are always atypical. Surgical resection of the tumors is the first choice. We use the non-fusion surgery to preserve the function of the lumbar spine. [ABSTRACT FROM AUTHOR]

Objective: This study aims to investigate the role of Acyl-CoA synthetase 4 (ACSL4) in mediating mitochondrial fatty acid metabolism and dendritic cell (DC) antigen presentation in the immune response associated with asthma. Methods: RNA sequencing was employed to identify key genes associated with mitochondrial function and fatty acid metabolism in DCs. ELISA was employed to assess the levels of fatty acid metabolism in DCs. Mitochondrial morphology was evaluated using laser confocal microscopy, structured illumination microscopy, and transmission electron microscopy. Flow cytometry and immunofluorescence were utilized to detect changes in mitochondrial superoxide generation in DCs, followed by immunofluorescence co-localization analysis of ACSL4 and the mitochondrial marker protein COXIV. Subsequently, pathological changes and immune responses in mouse lung tissue were observed. ELISA was conducted to measure the levels of fatty acid metabolism in lung tissue DCs. qRT-PCR and western blotting were employed to respectively assess the expression levels of mitochondrial-associated genes (ATP5F1A, VDAC1, COXIV, TFAM, iNOS) and proteins (ATP5F1A, VDAC1, COXIV, TOMM20, iNOS) in lung tissue DCs. Flow cytometry was utilized to analyze changes in the expression of surface antigens presented by DCs in lung tissue, specifically the MHCII molecule and the co-stimulatory molecules CD80/86. Results: The sequencing results reveal that ACSL4 is a crucial gene regulating mitochondrial function and fatty acid metabolism in DCs. Inhibiting ACSL4 reduces the levels of fatty acid oxidases in DCs, increases arachidonic acid levels, and decreases A-CoA synthesis. Simultaneously, ACSL4 inhibition leads to an increase in mitochondrial superoxide production (MitoSOX) in DCs, causing mitochondrial rupture, vacuolization, and sparse mitochondrial cristae. In mice, ACSL4 inhibition exacerbates pulmonary pathological changes and immune responses, reducing the fatty acid metabolism levels within lung tissue DCs and the expression of mitochondria-associated genes and proteins. This inhibition induces an increase in the expression of MHCII antigen presentation molecules and co-stimulatory molecules CD80/86 in DCs. Conclusions: The research findings indicate that ACSL4-mediated mitochondrial fatty acid metabolism and dendritic cell antigen presentation play a crucial regulatory role in the immune response of asthma. This discovery holds promise for enhancing our understanding of the mechanisms underlying asthma pathogenesis and potentially identifying novel targets for its prevention and treatment. [ABSTRACT FROM AUTHOR]