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Background: The patellar height index is important; however, the measurement procedures are time-consuming and prone to significant variability among and within observers. We developed a deep learning-based automatic measurement system for the patellar height and evaluated its performance and generalization ability to accurately measure the patellar height index. Methods: We developed a dataset containing 3,923 lateral knee X-ray images. Notably, all X-ray images were from three tertiary level A hospitals, and 2,341 cases were included in the analysis after screening. By manually labeling key points, the model was trained using the residual network (ResNet) and high-resolution network (HRNet) for human pose estimation architectures to measure the patellar height index. Various data enhancement techniques were used to enhance the robustness of the model. The root mean square error (RMSE), object keypoint similarity (OKS), and percentage of correct keypoint (PCK) metrics were used to evaluate the training results. In addition, we used the intraclass correlation coefficient (ICC) to assess the consistency between manual and automatic measurements. Results: The HRNet model performed excellently in keypoint detection tasks by comparing different deep learning models. Furthermore, the pose_hrnet_w48 model was particularly outstanding in the RMSE, OKS, and PCK metrics, and the Insall–Salvati index (ISI) automatically calculated by this model was also highly consistent with the manual measurements (intraclass correlation coefficient [ICC], 0.809–0.885). This evidence demonstrates the accuracy and generalizability of this deep learning system in practical applications. Conclusion: We successfully developed a deep learning-based automatic measurement system for the patellar height. The system demonstrated accuracy comparable to that of experienced radiologists and a strong generalizability across different datasets. It provides an essential tool for assessing and treating knee diseases early and monitoring and rehabilitation after knee surgery. Due to the potential bias in the selection of datasets in this study, different datasets should be examined in the future to optimize the model so that it can be reliably applied in clinical practice. Trial registration: The study was registered at the Medical Research Registration and Filing Information System (medicalresearch.org.cn) MR-61-23-013065. Date of registration: May 04, 2023 (retrospectively registered). [ABSTRACT FROM AUTHOR]

Multiple Sclerosis (MS) is an immune-related disease and the relationship between MS and cancer has raised attention. Previous studies of the relationship between MS and cancer have reached conflicting conclusions. In this study, the two-sample MR method is used to investigate whether MS has a causal correlation with cancers and offer scientific evidence for cancer prevention. Single nucleotide polymorphisms (SNPs) related to MS were obtained from the genome-wide association study (GWAS) based on International Multiple Sclerosis Genetics Consortium (IMSGC) and SNPs related to 15 types of cancers were obtained from the GWASs based on UK Biobank. Inverse variance weighted (IVW) method was mainly used to assess causal effects. Sensitivity analyses were conducted with Cochran's Q-test, MR Egger intercept, leave-one-out test, and MR Steiger method. IVW analysis showed that MS was only associated with a marginal increased risk of cervical cancer (OR 1.0004, 95% CI 1.0002–1.0007, p = 0.0003). Sensitivity analyses showed that the results of MR analysis were robust and found no heterogeneity, no pleiotropy, and no reverse causation. In conclusion, this study finds no causal relationship between MS and 15 types of cancers except cervical cancer. [ABSTRACT FROM AUTHOR]

The PTEN-induced kinase 1 (PINK1)-Parkin pathway plays a vital role in maintaining a healthy pool of mitochondria in higher eukaryotic cells. While the downstream components of this pathway are well understood, the upstream triggers remain less explored. In this study, we conducted an extensive analysis of inhibitors targeting various mitochondrial electron transport chain (ETC) complexes to investigate their potential as activators of the PINK1–Parkin pathway. We identified cloflucarban, an antibacterial compound, as a novel pathway activator that simultaneously inhibits mitochondrial complexes III and V, and V. RNA interference (RNAi) confirmed that the dual inhibition of these complexes activates the PINK1–Parkin pathway. Intriguingly, we discovered that albumin, specifically bovine serum albumin (BSA) and human serum albumin (HSA) commonly present in culture media, can hinder carbonyl cyanide m-chlorophenyl hydrazone (CCCP)-induced pathway activation. However, cloflucarban's efficacy remains unaffected by albumin, highlighting its reliability for studying the PINK1–Parkin pathway. This study provides insights into the activation of the upstream PINK1–Parkin pathway and underscores the influence of culture conditions on research outcomes. Cloflucarban emerges as a promising tool for investigating mitochondrial quality control and neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Background: The accumulation of myofibroblasts is the key pathological feature of pulmonary fibrosis (PF). Aberrant differentiation of lung-resident mesenchymal stem cells (LR-MSCs) has been identified as a critical source of myofibroblasts, but the molecular mechanisms underlying this process remain largely unknown. In recent years, N6-methyladenosine (m6A) RNA modification has been implicated in fibrosis development across diverse organs; however, its specific role in promoting the differentiation of LR-MSCs into myofibroblasts in PF is not well defined. Methods: In this study, we examined the levels of m6A RNA methylation and the expression of its regulatory enzymes in both TGF-β1-treated LR-MSCs and fibrotic mouse lung tissues. The downstream target genes of m6A and their related pathways were identified according to a literature review, bioinformatic analysis and experimental verification. We also assessed the expression levels of myofibroblast markers in treated LR-MSCs and confirmed the involvement of the above-described pathway in the aberrant differentiation direction of LR-MSCs under TGF-β1 stimulation by overexpressing or knocking down key genes within the pathway. Results: Our results revealed that METTL3-mediated m6A RNA methylation was significantly upregulated in both TGF-β1-treated LR-MSCs and fibrotic mouse lung tissues. This process directly led to the aberrant differentiation of LR-MSCs into myofibroblasts by targeting the miR-21/PTEN pathway. Moreover, inhibition of METTL3 or miR-21 and overexpression of PTEN could rescue this abnormal differentiation. Conclusion: Our study demonstrated that m6A RNA methylation induced aberrant LR-MSC differentiation into myofibroblasts via the METTL3/miR-21/PTEN signaling pathway. We indicated a novel mechanism to promote PF progression. Targeting METTL3-mediated m6A RNA methylation and its downstream targets may present innovative therapeutic approaches for the prevention and treatment of PF. [ABSTRACT FROM AUTHOR]

Coxsackievirus A10 (CVA10) has recently emerged as one of the major causative agents of hand, foot, and mouth disease. CVA10 may also cause a variety of complications. No approved vaccine or drug is currently available for CVA10. The residues of CVA10 critical for viral attachment, infectivity and in vivo pathogenicity have not been identified by experiment. Here, we report the identification of CVA10 residues important for binding to cellular receptor KREMEN1. We identified VP2 N142 as a key receptor-binding residue by screening of CVA10 mutants resistant to neutralization by soluble KREMEN1 protein. The receptor-binding residue N142 is exposed on the canyon rim but highly conserved in all naturally occurring CVA10 strains, which provides a counterexample to the canyon hypothesis. Residue N142 when mutated drastically reduced receptor-binding activity, resulting in decreased viral attachment and infection in cell culture. More importantly, residue N142 when mutated reduced viral replication in limb muscle and spinal cord of infected mice, leading to lower mortality and less severe clinical symptoms. Additionally, residue N142 when mutated could decrease viral binding affinity to anti-CVA10 polyclonal antibodies and a neutralizing monoclonal antibody and render CVA10 resistant to neutralization by the anti-CVA10 antibodies. Overall, our study highlights the essential role of VP2 residue N142 of CVA10 in the interactions with KREMEN1 receptor and neutralizing antibodies and viral virulence in mice, facilitating the understanding of the molecular mechanisms of CVA10 infection and immunity. Our study also provides important information for rational development of antibody-based treatment and vaccines against CVA10 infection. Author summary: Coxsackievirus A10 (CVA10) is an emerging pathogen that causes hand, foot, and mouth disease. No approved vaccines or antiviral treatments for CVA10 infection are yet available. Here we identified VP2 N142 of CVA10 as a key residue essential for viral recognition by KREMEN1 receptor by selection of soluble receptor neutralization-resistant mutant and mutational analysis. Residue N142 when mutated could significantly reduce receptor-binding activity, viral attachment, and infection in vitro. Mouse infection experiments show that residue N142 when mutated could reduce fatality rate and severity of symptoms by decreasing viral loads in limb muscle and spinal cord. Furthermore, residue N142 when mutated could confer resistance to neutralization by anti-CVA10 neutralizing antibodies. Additionally, N142, which is exposed on the canyon rim but highly conserved in CVA10, is identified as a key receptor-binding residue, providing a counterexample to the canyon hypothesis. Overall, our findings promote a better understanding of the molecular basis of CVA10 attachment and infection and in vivo pathogenicity, and also provide useful information for rational research and development of vaccines and antibody-based treatment against CVA10 infection. [ABSTRACT FROM AUTHOR]

To solve the problems mechanically caused by parallel direct‐drive permanent magnet motors (DD‐PMSM). This paper proposes a concave‐core stator direct‐drive permanent magnet motor (CCSDD‐PMSM) structure. In this study, an auxiliary yoke structure is proposed to optimise the magnetic circuit and analyse the cogging torque to achieve the minimum detent force. Based on the unit motor and combined with the magnetomotive force to analyse the symmetry of different winding distributions, the stability characteristics of the motor are studied. The magnetic field distribution of the motor load air gap is calculated using the finite element method. The contribution of different spatial order harmonics to the motor output torque is calculated using the Maxwell tensor method. The torque calculation expression of the CCSDD‐PMSM is given. Finally, an experimental prototype is made to verify the accuracy of the analysis in this paper. [ABSTRACT FROM AUTHOR]

Bisphenols are environmental toxins with endocrine disruptor activity, yet bisphenol A (BPA) and its analogs are still widely used in manufacturing plastic products. There is evidence showing that BPA elicits inflammation in humans and animals, but the target cell types of BPA are not well understood. In this study, we sought to determine BPA's direct effect on macrophages and BPA immunotoxicity in mouse intestine. Ghrelin is an important nutrient-sensing hormone, acting through its receptor growth hormone secretagogue receptor (GHSR) to regulate metabolism and inflammation. We found that BPA promotes intestinal inflammation, showing increased infiltrating immune cells in colons and enhanced expression of Ghsr and pro-inflammatory cytokines and chemokines, such as Il6 and Ccl2, in colonic mucosa. Moreover, we found that both long- and short-term BPA exposure elevated pro-inflammatory monocytes and macrophages in mouse peripheral blood mononuclear cells (PBMC) and peritoneal macrophages (PM), respectively. To determine the role of GHSR in BPA-mediated inflammation, we generated Ghsr deletion mutation in murine macrophage RAW264.7 using CRISPR gene editing. In wild-type RAW264.7 cells, the BPA exposure promotes macrophage pro-inflammatory polarization and increases Ghsr and cytokine/chemokine Il6 and Ccl2 expression. Interestingly, Ghsr deletion mutants showed a marked reduction in pro-inflammatory cytokine/chemokine expression in response to BPA, suggesting that GHSR is required for the BPA-induced pro-inflammatory response. Further understanding how nutrient-sensing GHSR signaling regulates BPA intestinal immunotoxicity will help design new strategies to mitigate BPA immunotoxicity and provide policy guidance for BPA biosafety. [ABSTRACT FROM AUTHOR]

Background: The atherogenic index of plasma (AIP) is an important alternative metabolic biomarker of atherosclerosis and cardiovascular diseases. Nevertheless, the correlation between the AIP and carotid atherosclerosis is unknown among the general population. Methods: A total of 52,380 community residents, aged ≥ 40 years who underwentcervical vascular ultrasound from December 2017 to December 2020 in Hunan China, were selected for retrospective analysis. The AIP was calculated as a logarithmically converted ratio of triglycerides (TG) to high-density lipoprotein-cholesterol (HDL-C). The participants were divided into AIP quartile groups (Q1-Q4). Logistic regression models and restricted cubic spline analyses were used to examine the association of the AIP with carotid atherosclerosis. Stratified analyses were applied to control for confounding factors. The incremental predictive value of the AIP was further assessed. Results: After adjusting for traditional risk factors, an increased AIP was associated with a higher rate of carotid atherosclerosis (CA), increased carotid intima-media thickness (CIMT), and plaques [odds ratio, OR (95% confidence interval, CI): 1.06 (1.04, 1.08), 1.07 (1.05, 1.09), and 1.04 (1.02, 1.06) per 1-SD increase in the AIP, respectively]. Compared with those participants in the quartile 1 group, those in the quartile 4 group had a greater risk of CA [OR 1.18, 95% CI (1.12, 1.25)], increased CIMT [OR 1.20, 95% CI (1.13, 1.26)], and plaques [OR 1.13, 95% CI (1.06, 1.19)]. However, we did not observe an association between the AIP and stenosis [0.97 (0.77, 1.23), p for trend = 0.758]. Restricted cubic spline analyses also showed a cumulative increase in the risk of CA, increased CIMT, and plaques but not stenosis severity (> 50%) with an increase of the AIP. Subgroup analyses showed that a more significant association between the AIP and the prevalence of increased CA was detected in younger subjects (aged < 60 years) with a body mass index (BMI) of ≥ 24 and fewer comorbidities. Additionally, the AIP provided incremental predictive capacity over established risk factors for CA, as shown by an improvement in the net reclassification index (NRI) and integrated discrimination index (IDI) (all P < 0.05). Conclusions: An elevated AIP in a community-based population is associated with a higher rate of CA. the AIP could serve as a potential biomarker for CA risk assessment. [ABSTRACT FROM AUTHOR]

Background: This study focussed on exploring the prognostic prediction performance of the growth arrest and DNA damage-inducible 45 beta (GADD45B) and its associations with T-cell activity and immune soakage in different malignancies, especially lung squamous cell carcinoma (LUSC). Methods: We applied TIMER database for comparing the expressions of GADD45B among different cancers. OncoLnc, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Kaplan-Meier Plotter were utilised to evaluate the prognostic prediction performance of GADD45B. Besides, the associations of GADD45B with clinical stage, associated gene markers, and immune infiltration were examined through TISIDB, GEPIA2, and Tumour Immune Estimation Resource (TIMER). Biological processes (BPs) and KEGG enrichment analyses were performed to illustrate the possible role of GADD45B in LUSC. The miRWalk database was adopted to analyse the gene miRNA interaction network of GADD45B in LUSC. Results: GADD45B expression was decreased in most of the malignancies, with relation to the poor prognosis in LUSC. GADD45B also significantly affected the survival of LUSC subgroups divided by clinic data. GADD45B significantly correlates with and may stimulate T cell exhaustion in LUSC. Conclusions: GADD45B is a prognostic indicator in multiple tumours, especially in LUSC. Moreover, modulating GADD45B expression may improve immunotherapy efficacy in LUSC. [ABSTRACT FROM AUTHOR]

Shrinkage greatly influences the mechanical and fatigue properties of compacted graphite iron and it is necessary in order to study the causes of shrinkage in compacted graphite iron and to predict it effectively. In this paper, a kind of cylindrical necking test sample was designed to evaluate the shrinkage in compacted graphite iron, and a method to calculate the size of shrinkage was proposed. By observing the microstructure around the shrinkage zone, it is concluded that concentrated shrinkage mainly appears in the solidification region where the dendritic gap is closed, and the isolated shrinkage mainly occurs in the final solidification region, and the supersaturated carbon elements are gathered on the surface of the shrinkage. The cause of shrinkage in compacted graphite iron is caused by its solidification method, where the austenite dendrites and the eutectic clusters are generated close to the melt zone during the solidification process, leading to the inability to feed the shrinkage. Based on the thermodynamic analysis, the equations between the volume change of each phase, solid phase rate, and time during solidification of compacted graphite iron were established to theoretically explain the formation mechanism of the shrinkage. Taking nine parameters such as the chemical elements and characteristic values of thermal analysis as the input nods, a four-layer BP neural network model for predicting the size of shrinkage in compacted graphite iron was constructed, and the R-squared of the model reached 97%, which indicates it could be used to predict the shrinkage tendency. [ABSTRACT FROM AUTHOR]

Disruption of the epithelial-mesenchymal transition (EMT) of activated lung cells is an important strategy to inhibit the progression of idiopathic pulmonary fibrosis (IPF). The present study investigated the role of exosomes derived from airway basal cells on EMT of lung cells and elucidate the underlying mechanism. Exosomes were characterized by nanoparticle tracking analysis, transmission electron microscopy imaging and markers detection. The role of exosome on the EMT of lung epithelial cells and lung fibroblasts induced by TGF-β1 was detected. RNA sequencing screened dysregulated genes in exosome-treated group, followed by the bioinformatical analysis. One of the candidates, anoctamin-1 (ANO1), was selected for further gain-and-loss phenotype assays. A bleomycin-induced pulmonary fibrosis model was used to evaluate the treatment effect of exosomes. Exosomes were round-like and positively expressed CD63 and tumor susceptibility gene 101 protein. Treatment with exosomes inhibited the EMT of lung cells activated by TGF-β1. 4158 dysregulated genes were identified in exosome-treated group under the threshold of |log2 fold-change| value >1 and they were involved in the metabolism of various molecules, as well as motility-related biological processes. A key gene, ANO1, was verified by reverse transcription-quantitative PCR, whose overexpression induced the EMT of lung cells. By contrast, ANO1 knockdown reversed the EMT induced by TGF-β1. In vivo assay indicated that exosome treatment ameliorated pulmonary fibrosis and inhibited the upregulation of ANO1 induced by bleomycin. In conclusion, airway basal cell-derived exosomes suppressed the EMT of lung cells via the downregulation of ANO1. These exosomes represent a potential therapeutic option for patients with IPF. [ABSTRACT FROM AUTHOR]

Sepsis is a life-threatening condition, caused by the body's extreme response to an infection. In the United States, 1.7 million cases of sepsis occur annually, resulting in 265,000 deaths. Delayed diagnosis and treatment are associated with higher mortality rates. An exponential rise in the availability of medical data has allowed for the development of sophisticated machine learning algorithms to predict sepsis earlier than the onset. However, these models often underperform, as the training data are retrospective and do not fully capture the uncertain future. In this study, we develop a novel framework, which we refer to as MLePOMDP, to leverage and combine the underlying, high-level knowledge about sepsis progression and machine learning (ML) for classification. Specifically, we use a hidden Markov model to describe sepsis development at a high level, where the ML model makes the higher-order "observations" from temporal data. Consequently, a partially observable Markov decision process (POMDP) model is developed to make classification decisions. We analytically establish that the optimal policy is of threshold-type, which we exploit to efficiently optimize MLePOMDP. MLePOMDP is calibrated and tested using high-frequency physiological data collected from bedside monitors. Different from past POMDP-based frameworks, MLePOMDP is developed for a prediction task using a very small state definition, produces highly interpretable results, and accounts for a novel and clinically meaningful action space. Our results show that MLePOMDP outperforms machine learning–based benchmarks by up to 8% in precision. Importantly, MLePOMDP is able to reduce false alarms by up to 28%. An additional experiment is conducted to show the generalizability of MLePOMDP to different patient cohorts. Summary of Contribution: This study develops a novel real-time decision support framework for early sepsis prediction by integrating well-known machine learning models (random forest and neural networks) with a well-established sequential decision-making model, namely, a partially observable Markov decision process (POMDP). The structural properties of the optimal policy are further explored and a threshold-type structure is established, which is then leveraged to develop a customized algorithm to solve the problem more efficiently. The resulting framework demonstrates the benefit of applying POMDPs to augment machine learning outputs. Specifically, the framework results in the reduction of false alarms in sepsis predictions where decisions are made in real time, hence improving the overall prediction precision. [ABSTRACT FROM AUTHOR]

This article presents a novel asymmetric spoke‐type rotor structure. It is used to reduce rotor magnetic flux leakage, torque ripple and no‐load back‐EMF distortion rate while increasing the motor output torque. The traditional method of optimizing torque pulsation is the inverse cosine function, which gives a sinusoidal distribution of the air‐gap magnetic field under no‐load conditions of the motor. The fundamental wave magnetic field of the air‐gap synthetic magnetic field under the load is offset from the no‐load air‐gap magnetic field. This paper presents the design theory and method of the new type of the asymmetric rotor. Asymmetric spatial harmonics are introduced to the rotor so that the motor has a sinusoidal distribution of the rated load air‐gap field under MTPA control. In order to verify the superiority of the new rotor, the performance of four different spoke‐type rotor structure motors under the same pole‐slot combination was compared. Finally, an experimental prototype is built to verify the theoretical reliability against the design of this paper. [ABSTRACT FROM AUTHOR]

It has been reported that introducing Ag interlayer at the Cu/Bi 2 Te 3 interface can achieve ultra-low electrical contact resistivity. However, there is no consensus on the influence of Ag diffusion induced by Ag interlayer on electrical contact. Thus, the impact of Ag diffusion on electrical contact conductivity for Cu/Ag/Bi 2 Te 3 multilayers was investigated. The generation of interfacial compounds induced by Ag diffusion was analyzed and the contact resistivity was measured in Cu/Ag/Bi 2 Te 3 multilayers with different Ag interlayer thickness before and after annealing. It was found that Ag diffusion induced interfacial compounds Cu 4 Ag 3 Te 4 at the Cu/Ag interface before annealing, which could decrease contact resistivity to 3.728×10−12 Ω∙m2. After annealing, the relative amount of Cu 4 Ag 3 Te 4 at the Cu/Ag interface slightly decreased, and the Ag 2 Te was found to appear at the Ag/Bi 2 Te 3 interface, which could further decrease contact resistivity to 3.187×10−12 Ω∙m2. With Ag interlayer thickness increasing from 50 nm to 300 nm, the contact resistivity decreased from 3.726×10−10 Ω∙m2 to 3.728×10−12 Ω∙m2 before annealing because the relative amount of Cu 4 Ag 3 Te 4 increased about 5 times, after annealing the contact resistivity further decreased by 10.27∼41.7 % because the relative amount of Ag 2 Te increased about 1.1 times. In addition, we had optimized the ultra-low contact resistivity test method by redesigning the structure of test samples and modifying the formula of contact resistivity to eliminate two errors. One is caused by Cu electrode short-circuit resistance due to the test current being short-circuited by the middle electrode between two test electrodes. The other is caused by the increased electrical resistance of Bi 2 Te 3 thin film due to Te atom volatilization after annealing. The results showed that the errors of the test results were reduced by at least 21.50 %. Our work provides guidance for further optimizing electrical contact of thin-film thermoelectric devices. [Display omitted] • The influence of Ag diffusion on contact resistivity is investigated. • The variation of contact resistivity with Ag interlayer thickness is studied. • Interfacial compounds induced by Ag diffusion is semi-quantitatively analyzed. • Ultra-low contact resistivity test method is optimized by eliminating two errors. [ABSTRACT FROM AUTHOR]

[Display omitted] • The incorporation of Al provided abundant As 2 O 3 adsorption sites. • Facilitates the dissociation of O 2 and promotes reaction with chained As 2 O 3. • Lower activation energy for the oxidation of As(III) to As(V). • Transformation of the Ca site from physisorption sites to chemisorption sites. Doping techniques have the potential to enhance the adsorption and oxidation of As 2 O 3 by metal oxides for the augmentation of arsenic capture. However, the mechanisms of this facilitating effect, especially concerning the oxidation of As 2 O 3 , require further exploration. This study focuses on the effect of Al doping on As 2 O 3 adsorption and oxidation through experimental and density functional theory calculations. The introduction of aluminum increases the specific surface area and stimulates charge transfer, converting Ca atoms into new As 2 O 3 adsorption sites with strong adsorption capacity. The arsenic capture capacity of Al 2 O 3 /CaO is almost twice that of CaO when the molar ratio of Al and Ca is 1:6. For arsenic oxidation, Al doping promotes the dissociation of O 2 adsorbed on the sorbent surface, making it more prone to react with As 2 O 3. This catalytic effect lowered the activation energy for the conversion of As(III) to As(V), increasing the oxidation efficiency by 2–10%. These results serve as valuable references for the development of efficient arsenic sorbents. [ABSTRACT FROM AUTHOR]

This paper makes use of the characteristics of initial sensitivity and randomness of the chaotic map to design an image encryption algorithm based on the sine map and the tent map. The sine map is used to improve the tent map; then, the improved sine-tent map is proposed. The traditional tent map proposed in this paper has an expanded control parameter range and better chaos. In this algorithm, bit rearrangement is adopted to further improve the improved sine-tent map, which can reconstruct the output value and expand the chaotic characteristics of the map. In this algorithm, the image parameters are connected with the algorithm to generate the key. In the encryption step, a method of replacing the most significant bit and scrambling-diffusion algorithm is designed to encrypt the plaintext image. Finally, the algorithm is simulated with the experiment and evaluated with analysis; then, the experimental results are given. The evaluation results show that the ciphertext of the algorithm has high randomness, strong robustness, and better resistance to differential attacks after comparison. The correlation of the ciphertext image pixels is very low, and the algorithm is highly secure as a conclusion. [ABSTRACT FROM AUTHOR]

The online version of the original article can be found at https://doi.org/10.1186/s12933-023-01839-y B Correction to: Cardiovascular Diabetology (2023) 22:125 b https://doi.org/10.1186/s12933-023-01839-y Following publication of the original article [[1]], the author noticed the error in figure. In the image of Figure 1D, the forest plot of Figure 1D does not match the corresponding odds ratio (OR) and 95% confidence interval (CI). [Extracted from the article]

With the integration of multiple types of loads and renewable generations, the number of system states significantly grows. As a result, running optimal power flow (OPF) to analyze a myriad of system states is challenging and this seriously restricts the efficiency of the state enumeration method. To address that, this paper proposes a Lagrange Multiplier based State Enumeration (LMSE) approach to accelerate the analysis without loss of accuracy. The core idea is to directly obtain the optimal load shedding of contingency states by Lagrange multiplier-based functions, rather than the time-consuming OPF algorithms. This approach can also be conveniently integrated with the impact-increment method and the clustering technique for further efficiency enhancement. Case studies are performed on the RTS-79 and IEEE 118-bus systems considering multiple types of loads, photovoltaics (PVs), and wind turbines (WTs). Results indicate that the proposed method can significantly reduce the computing time without compromising the calculation accuracy. [ABSTRACT FROM AUTHOR]

Recently, Shuhong Xu et al. reported theoretical calculation of molecular structure, bonding, aromaticity, electron delocalization, and electronic spectrum of cyclo[18]carbon in J. Mol. Model., 26, 111 (2020). Due to inappropriate consideration of calculation strategy, misunderstanding of some analysis methods and concepts, and some errors in the data, there are misleading statements and unconvincing conclusions in their paper. Here, we will point out inadequacies of Shuhong Xu's paper and put forward our own views. The contents of this comment will also help those who are studying cyclo[18]carbon to better understand this system and its analogues. [ABSTRACT FROM AUTHOR]

Over the past decades, complex deposition patterns after the evaporation of particle-laden droplets spark intense interest in interpreting the formation of deposition patterns due to their numerous applications in biomedicine, ink-jet printing, biopsy, etc. This work experimentally studies the formation of deposition patterns during evaporation of the magnetic nanofluid (MNF) droplet stands on a smooth glass/hydrophobic surface at different substrate temperatures. A CCD camera mounted on the microscopy is used to capture the process of droplet evaporation. An infrared camera is applied to quantify the temperature distribution along the vapour-liquid interface of the evaporating droplet. Additionally, 3 μm sized microbeads are applied to track the flow motion of the solute inside for different temperatures. The evaporation of sessile droplets has been conducted by controlling substrate temperature, which ranges from 10 °C to 70 °C. The experimental results show that there are three distinct patterns with the increasing temperature, namely a uniform pattern, a typical 'coffee ring' pattern, and a dual ring pattern. The experimental results show that Marangoni flow becomes essential for the formation of a secondary ring pattern with increasing substrate temperatures. This study shows that controlling substrate temperature is an efficient and simple method to control the formation of the sessile droplet. [ABSTRACT FROM AUTHOR]

Regional integrated system (RIES) bridges the gaps among different energy systems by various energy conversion equipment. While this integration brings forth numerous benefits, it introduces cross-system failures, where a contingency in one system may affect others. This poses significant challenges when evaluating the consequences of such contingencies. To address this, a risk assessment approach is developed for RIES, considering cross-system failures, as well as fluctuations in renewable generation and multi-energy loads. Event tree analysis (ETA) is adopted to simulate the propagation of failures and identify the affected components. Nine risk indices are proposed to quantify the operational risk of RIES at various levels. Additionally, root cause identification and weak point location are developed to formulate risk alleviation strategies. To validate the proposed method, a RIES with 101 nodes is utilized for risk assessment, and multiple risk alleviation strategies are determined. The results demonstrate the effectiveness of the proposed method, providing valuable insights for operators in ensuring the safety of RIES. • RIES risk assessment approach quantifies uncertainties of component failure and source-load fluctuation with nine indices. • Cross-system failures in RIES are classified into three categories to describe the interaction between subsystems. • Techniques for root cause identification and weak point location are proposed to alleviate risk. [ABSTRACT FROM AUTHOR]

• Open-cage fullerene derivatives react readily with ortho -phenylenediamine. • Open-cage fullerenes form stable mono-Pt and bis-Pt complexes. • Fullerene C C on the rim of the orifice form η 2-type coordination complex with Pt. Three new open-cage fullerene derivatives with a 19-membered orifice have been prepared, two of which readily formed Pt complexes when treated with Pt(PPh 3) 4. Several related open-cage fullerene derivatives were also found to form very stable platinum complexes, which could be purified by chromatography on silica gel under ambient conditions. Single crystal X-ray diffraction data revealed that the Pt metal formed η 2-type coordination pattern with a fullerene double bond on the rim of the orifice. Regio-selectivity of the platinum coordination is determined by the electron density of double bonds on the cage. The most electron deficient double bond shows the highest reactivity. [ABSTRACT FROM AUTHOR]

• GHz acoustic resonator based microfluidic sonoelectrochemical platform was developed. • Flexibly and accurately controlling the fluid flow in microfluidic channel was achieved. • On-chip sonoelectrochemical deposition of nanoparticles and sensing of H 2 O 2 was improved. • Tracking intracellular H 2 O 2 release to identify the cancer cells from normal cells was evaluated. Developing effective strategies for the flexible control of fluid is vital for microfluidic electrochemical biosensing. In this study, a gigahertz (GHz) acoustic streaming (AS) based sonoelectrochemical system was developed to realize an on-chip surface modification and sensitive hydrogen peroxide (H 2 O 2) detection from living cells. The flexible and controlled fluid surrounding the electrochemical chip was optimized theoretically and applied in the sonoelectrochemical deposition of Au nanoparticles (AuNPs) first. Under the steady and fast flow stimulus of AS, AuNPs could be synthesized with a smaller and evener size distribution than the normal condition, allowing AuNPs to show an excellent peroxidase-like activity. Moreover, the AS also accelerated the mass transport of target molecules and improved the catalytic rate, leading to the enhancement of H 2 O 2 detection, with an extremely low detection limit of 32 nM and a high sensitivity of 4.34 μA/ (mM·mm2). Finally, this system was successfully applied in tracking H 2 O 2 release from different cell lines to distinguish the cancer cells from normal cells. This study innovatively integrated the surface modification and molecules detection process on a chip, and also proposed a simple but sensitive platform for microfluidic biosensing application. [ABSTRACT FROM AUTHOR]

Background: Aberrant DNA methylation patterns are involved in the pathogenesis of papillary renal cell carcinoma (pRCC). This study aimed to investigate the potential of methylation-driven genes as biomarkers in determining the prognosis of pRCC by bioinformatics analysis. Methods: DNA methylation and transcriptome profiling data were downloaded from The Cancer Genome Atlas database. Methylation-driven genes (MDGs) were obtained using MethylMix R package. A Cox regression model was used to screen for pRCC prognosis-related MDGs, and a linear risk model based on MDG methylation profiles was constructed. A combined methylation and gene expression survival analysis was performed to further explore the prognostic value of MDGs independently. Results: A total of 31 MDGs were obtained. Univariate and multivariate Cox regression analysis identified eight genes (CASP1, CD68, HOXD3, HHLA2, HOXD9, HOXA10-AS, TMEM71, and PLA2G16), which were used to construct a predictive model associated with overall survival in pRCC patients. Combined DNA methylation and gene expression survival analysis revealed that C19orf33, GGT6, GIPC2, HHLA2, HOXD3, HSD17B14, PLA2G16, and TMEM71 were significantly associated with patients' survival. Conclusion: Through the analysis of MDGs in pRCC, this study identified potential biomarkers for precision treatment and prognosis prediction, and provided the basis for future research into the molecular mechanism of pRCC. [ABSTRACT FROM AUTHOR]

This paper investigate the downlink transmission, especially the interference coordination for the cell-edge users in multi-cell full-dimension multiple-input multiple-output (FD-MIMO) systems. We assume that each base station (BS) can only obtain statistical channel state information (CSI), so as to reduce the CSI required at each BS. We propose a fractional-frequency-reuse(FFR) scheme for multi-cell FD-MIMO systems, in which all the cell-center users occupy the same frequency band, while all the cell-edge users use the rest of the frequency band. Based on this FFR scheme, two joint three-dimensional (3D) beamforming interference coordination strategies, i.e., the full-cooperative strategy, and a more energy-efficient partial-cooperative strategy, are proposed to alleviate the inter-cell interference for the cell-edge users. Moreover, tractable approximations of the ergodic rate for both cell-center and cell-edge users are derived. Simulations show that the proposed interference coordination strategies can significantly improve the cell-edge performance, while maintain relatively high total throughput. The full-cooperative strategy performs best in the cell-edge performance, and the partial-cooperative strategy performs best in the aspects of total throughput and energy-efficiency. [ABSTRACT FROM AUTHOR]

Coronary artery disease (CAD), the leading cause of morbidity and mortality, has imposed huge health and economic burdens globally. Zinc-α2-glycoprotein (ZAG) is a novel adipokine. Increasing evidence suggests the close relationship between serum ZAG levels and various cardiometabolic risk factors. However, the relationship between serum ZAG levels and CAD is still not fully clarified. We conducted this study to evaluate serum ZAG levels and its association with cardiovascular risk factors. A total of 129 patients with CAD, 99 patients with noncoronary artery disease (NCAD), and 121 controls were recruited in this retrospective study. CAD (coronary artery stenosis ≥50%) or NCAD (coronary artery stenosis <50%) patients who underwent coronary angiography were diagnosed according to the American Heart Association criteria. Serum ZAG levels were determined via commercial enzyme-linked immunosorbent assay (ELISA) kits. The results showed that serum ZAG levels in CAD and NCAD groups were significantly decreased when compared with those in the control group. Multiple stepwise regression analysis revealed that the grouping variable (control, NCAD, and CAD) was an independent determinant of serum ZAG levels (β = −0.328, P < 0.001) after controlling other confounding factors. Further multivariate ordinary logistic regression analysis demonstrated that the risk of grouping at one level higher in subjects with the lowest tertile of ZAG levels was 2.28-fold higher than those with the highest tertile levels (OR = 3.281, 95% CI 1.782–6.038, P < 0.001). The receiver-operating characteristic (ROC) curve analysis showed that serum ZAG could distinguish CAD patients (AUC = 0.706, 95% CI, 0.643–0.770, P < 0.05), NCAD patients (AUC = 0.673, 95% CI, 0.602–0.743, P < 0.05), and NCAD and CAD patients (AUC = 0.692, 95% CI, 0.633–0.750, P < 0.05) from controls. In conclusion, serum ZAG levels were significantly decreased in NCAD/CAD patients. The decreased serum ZAG levels were independently associated with the presence of NCAD/CAD. ZAG might serve as a candidate diagnostic biomarker for NCAD/CAD. [ABSTRACT FROM AUTHOR]

This Letter investigates the transmission method for downlink full‐dimension multiple‐input multiple‐output systems. To balance the performance and the amount of channel information acquired at base station, a dual‐layer beamforming method is proposed, which exploits the statistical as well as effective channel state information (CSI) of a small fraction of users. User scheduling and grouping algorithms utilising only statistical CSI are also proposed. Simulations verify that the proposed transmission method can achieve high throughput with much less CSI, and can flexibly balance the requirement of CSI and performance. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanization, industrial prosperity and economic development, China has attracted great attention as one of the largest sources of nitrogen dioxide (NO 2) pollution in Asia. Many studies have carried out on the source analysis, spatial and temporal distribution, physical and chemical properties of pollutants. However, there are a few studies on the high-resolution spatial distribution of atmospheric pollutants in small-scale cities, especially by using land use regression (LUR) model. LUR model is a common method for predicting the spatial variation of pollutants. It expresses spatially local changes in the results through potential variables in the equation, thus fully reflecting the spatial differentiation of small-scale pollutant concentrations. In our study, along with 40 types potential predictor, we used LUR model to simulate the concentration of NO 2 in Xi'an and to generate a high-resolution spatial distribution map of the concentrations, to provide better support for health risk assessment. In addition to using traditional predictors, due to the different classifications of roads in our study area, the use of road length as a predictor did not reflect traffic volumes well. For this reason, we weighted the roads with grades and calculated their area to fit the model. The results show that the fitting effect of the model in this study is good (adjusted R2 > 0.85), and the deviation (<2.27%) and LOOCV RMSE (<2.22 μg/m³) are both small for all time periods. Compared with traditional interpolation models, the LUR model has better prediction accuracy and greater ability to express spatial differences. Using a grid of 500 m * 500 m, 3494 grids were defined in Xi'an to simulate the spatial distribution of NO 2 concentrations. High NO 2 values appeared around the factory and represented the highest health risk. Due to abundant surface vegetation coverage, the concentrations of NO 2 and the consequent health risks in tourist spots, parks and universities were low. Image 1 • Land use regression models of NO 2 were produced for Xi'an. • Road length was weighted by different grades to express vehicle exhaust. • Industrial emissions and green plants had great impact on NO2. • The results were good, deviations and LOOCVRMSE were both small in all periods. • Health risk of children (8–10 years old) was the highest in all functional areas. [ABSTRACT FROM AUTHOR]

Surface wettability and structure have been proved as two important influential factors to the thermal transport at the solid-liquid interface at nano scale, however, the combined enhancement mechanism has not been clearly understood till now. In this study, the rapid boiling behaviors of nano thin liquid argon film on the heterogeneous wetting surfaces were examined with the non-equilibrium molecular dynamics (MD) method. Meanwhile, the ring-patterned and stripe-patterned surfaces were designed and analyzed, respectively. By analyzing the trajectory of argon atoms, the bubble nucleation behavior, heat flux and interfacial thermal resistance, it is found that the lower hydrophobic area fraction is favorable for the bubble formation and the ring-patterned surface shows an advantage in the nucleate boiling compared with the stripe-patterned one. Meanwhile, the nanostructure has a great influence on the boiling phenomena, which accelerates the development of bubble nuclei and improves the maximum heat flux compared with the planar one. In present simulations, the ring-patterned surface with nanostructure of 40% hydrophobic area fraction is the optimal design for the efficiency enhancement of explosive boiling process. The findings in this work contribute to the design of the coating nanostructured surface to enhance the boiling heat transfer performance under the high heat fluxes. • Ring-patterned surface is superior to stripe-patterned one in boiling heat transfer. • Nanostructure realizes a higher maximum heat flux and a lower evaporation ratio. • Optimal coating nanostructured surface is achieved for explosive boiling process. [ABSTRACT FROM AUTHOR]

NO 2 – detection based on Au-Ni-Rh/LIG electrochemical sensor. [Display omitted] • Au, NiO, and Rh nanoparticles were deposited onto LIG by one-step electrodeposition. • DFT calculation confirmed the enhanced adsorption energy and electron transfer. • Three metals promoted the detection of nitrite in terms of catalysis and adsorption. • The developed sensor obtained a very low detection limit of 0.3 μM for nitrite. • This sensor can be used for portable determination of NO 2 – in real water samples. In this study, we employed a straightforward and rapid one-step electrodeposition method to enhance modify an Au/NiO/Rh composite on laser-induced graphene (LIG) for nitrite (NO 2 –) detection. We extensively characterized and tested the morphological composition and electrochemical properties of the electrode using scanning electron microscopy and other characterization techniques. To compare the electrochemical active surface areas of the electrode before and after modification, we conducted cyclic voltammetry experiments. Additionally, we confirmed the changes in electron transfer performance and adsorption energy of the modified electrode through by density functional theory calculations. The experimental results demonstrate that the combined modification of LIG with rhodium nanoparticles (RhNPs) and gold nanoparticles (AuNPs) improves electron transport ability at the electrode interface and enhances the electrode's electrocatalytic performance. The incorporation of nickel oxide (NiO) also provides a larger reaction area and more active sites for NO 2 – detection. The synergistic effects of these three modified components significantly enhance NO 2 – detection at the electrode, surpassing the performance of the bimetallic modified electrode. Under optimized experimental conditions, the sensor exhibits a linear range of 1 μmol/L to 1 mmol/L and a detection limit of 0.3 μmol/L. Furthermore, the sensor demonstrates excellent anti-interference and repeatability properties. We successfully applied the sensor for determination of NO 2 – in tap water, yielding satisfactory results. This research presents a promising strategy for the portable, sensitive, and in-situ detection of NO 2 – in water environments using metal-based electrochemical sensors. [ABSTRACT FROM AUTHOR]

A neural network (NN) is a powerful tool for approximating bounded continuous functions in machine learning. The NN provides a framework for numerically solving ordinary differential equations (ODEs) and partial differential equations (PDEs) combined with the automatic differentiation (AD) technique. In this work, we explore the use of NN for the function approximation and propose a universal solver for ODEs and PDEs. The solver is tested for initial value problems and boundary value problems of ODEs, and the results exhibit high accuracy for not only the unknown functions but also their derivatives. The same strategy can be used to construct a PDE solver based on collocation points instead of a mesh, which is tested with the Burgers equation and the heat equation (i.e., the Laplace equation). [ABSTRACT FROM AUTHOR]

Abstract Due to high-speed and extensive economic development, increasing urbanization, and booming industry in China, there is a growing public concern over PM 2.5 pollution. The identification of possible sources of PM 2.5 is a basis for studying air pollution. In this paper, the contribution of PM 2.5 from both combustion and non-combustion sources is calculated using the selected tracers of SO 2 , CO and NO 2. Changes in the characteristics of natural and anthropogenic PM 2.5 sources were analyzed by combining the use of satellite imagery and the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The results showed that the PM 2.5 in Xi'an and Lanzhou originated from combustion sources, the contribution of non-combustion sources increased from east to west, high values appeared in Zhangye and Jiuquan (over 70%). In Lanzhou, Zhangye and Jiuquan, PM 2.5 was mainly from anthropogenic sources during non-episode periods, and from natural sources (namely, dust storms) during episode days, and the proportion from natural sources increased from east to west. In addition, in our research, although the sources of PM 2.5 in the four cities are different, they all face the problem of excessive PM 2.5 concentration, and its pollution control problem is worth studying. Graphical abstract Image [ABSTRACT FROM AUTHOR]

A novel fractional two-dimensional triangle function combination discrete chaotic map is proposed by use of the discrete fractional calculus. The chaos behaviors are then discussed when the difference order is a fractional one. The bifurcation diagrams, the largest Lyapunov exponent and the phase portraits are displayed, especially, the elliptic curve public key cryptosystem is used in color image encryption algorithm. [ABSTRACT FROM AUTHOR]

A new fractional two-dimensional triangle function combination discrete chaotic map (2D-TFCDM) with the discrete fractional difference is proposed. We observe the bifurcation behaviors and draw the bifurcation diagrams, the largest Lyapunov exponent plot, and the phase portraits of the proposed map, respectively. On the application side, we apply the proposed discrete fractional map into image encryption with the secret keys ciphered by Menezes-Vanstone Elliptic Curve Cryptosystem (MVECC). Finally, the image encryption algorithm is analysed in four main aspects that indicate the proposed algorithm is better than others. [ABSTRACT FROM AUTHOR]

Water evaporation confined in nanoscale is a ubiquitous phenomenon in nature, which has a crucial importance in a broad range of technical applications. In this work, the evaporation of the ultra-thin liquid film confined below the graphene nanopore is simulated with MD approach, and the influences of the functional group and ion concentration on the evaporation process are analyzed based on the obtained data. It is found that the modification with hydroxyl functional groups on the graphene nanoporous membrane can enhance the heat transfer between solid and liquid, and the electrostatic interaction breaks the ordered hydrogen bond network among water molecules, thus the evaporation rate can be improved accordingly. For the electrolytic solution at a higher ion concentration, the oxidized-pore nanoporous membrane has an evaporation deterioration due to the ion aggregation effect, which results in a decreasing equilibrium temperature of water molecules. There exists one optimal ion concentration that can realize the highest evaporation rate. It is found the rotational and translational inertias of the ions are the main factors affecting the evaporation rate of electrolytic solution under the hydroxyl group functionalized graphene nanoporous membrane. • Hydroxyl functional groups on holey graphene membrane increase the evaporation rate. • Electrostatic interaction breaks ordered hydrogen bond network among water molecules. • One optimal ion concentration can realize the highest evaporation rate of water. • Ions' rotational and translational inertias affect evaporation of saline water. [ABSTRACT FROM AUTHOR]

Carbonyl compounds are important precursors of free radicals, ozone (O 3), and secondary organic aerosols (SOA) in the atmosphere. Biomass burning is an important source of carbonyl compounds. To explore the formation pathway of carbonyl compounds from biomass burning and the effects of fuel composition and burning conditions, this study performed tube-furnace combustion experiments using three biomass types (rice straw, pine, and poplar) and their three component extracts (cellulose, hemicellulose, and lignin) at seven ignition temperatures (300–900 °C, 100 °C gradient) and two oxygen concentrations (21% and 10.5%). The results showed that the average emission factors of carbonyl compounds (EF CC) from rice straw, pine, and poplar were 2.28 ± 1.72, 3.09 ± 2.98, and 2.90 ± 2.78 g/kg, respectively. EF CC were significantly higher (5.37 ± 0.25 g/kg) in lower temperature (300–500 °C) stage than in higher temperature (0.55 ± 0.03 g/kg). Furthermore, oxygen reduction promoted the emission of carbonyl compounds, increasing the EF CC by 21.6% on average. The average EF CC for the three components of biomass decreased in the order of cellulose (3.78 ± 3.90 g/kg), hemicellulose (2.90 ± 2.60 g/kg) and lignin (1.98 ± 1.72 g/kg), and their CCs profiles were also different. Cellulose and hemicellulose produced more formaldehyde and acetaldehyde than lignin, contributing 71.1 ± 12.6%, 69.0 ± 4.4% and 62.4 ± 15.5% in CCs, respectively. Acetone was mainly produced by the combustion of hemicellulose and lignin. Aromatic aldehydes were mainly produced by lignin burning, and also were significantly affected by temperature, the proportion under higher temperature is 2.7 times that under lower temperature. The EF CC values by weighted average calculation from the three components were good matched with those of parent fuels (r = 0.98), while the fitting results for those species such as aromatic aldehydes were relatively weak (r = 0.66), showing that there are different formation pathways and sensitivity to fuel composition and burning condition among different CCs. [Display omitted] • Emission factors(EF) and compositions of 19 carbonyls are quantified from the combustion of cellulose, hemicellulose and lignin. • The formation pathways of carbonyl compounds under various conditions are discussed. • The calculated EFs of carbonyls from the three components are good agreement with parent fuels. [ABSTRACT FROM AUTHOR]

Ischemic stroke is a prevalent disease that seriously threatens human health. It is characterized by high morbidity, mortality, disability, and recurrence rates, causing a significant economic burden on individuals and society. Circular RNA, a novel non-coding RNA, not only serves as the sponge for microRNAs and proteins but also promotes transcription of their parental genes and translates into peptides. In recent years, circRNAs have emerged as key regulators in ischemic stroke. This article aims to provide new ideas about the pathogenesis and progression of ischemic stroke by reviewing the roles of circRNAs in cerebral ischemic injury and summarizing the association between circRNAs and risk factors for ischemic stroke. [Display omitted] • The incidence of IS has been increasing consistently, while effective prevention and treatment methods are still lacking. • CircRNA is closely associated with risk factors for IS and plays a vital role in neuronal injury and vascular endothelial injury after IS. • Coronavirus infections have been linked to cerebrovascular diseases. • CircRNAs have potential as biomarkers for the diagnosis of IS. [ABSTRACT FROM AUTHOR]

The dual Z-scheme heterojunction CuBi2O4/Bi2Sn2O7/Sn3O4(CBS) was successfully constructed through in situ growth methods, and its photocatalytic performance was evaluated via degradation of tetracycline hydrochloride under visible light. Out of all samples, CBS-2 exhibited the highest photocatalytic activity, with an apparent rate constant of 2.34, 20.16, and 44.17 times that of Bi2Sn2O7, CuBi2O4, and Sn3O4, respectively. Even after four cycles, the photocatalytic efficiency remained above 85%. The improvement can be attributed to the construction of the Z-scheme heterojunction, which effectively promotes the separation and migration of photogenerated carriers. The possible photocatalytic degradation mechanism of dual Z-scheme heterojunction CBS was deduced based on the theory of free radical capture and energy band. [ABSTRACT FROM AUTHOR]

Ballistic thermal transport at nanoscale hotspots will greatly reduce the performance of a Gallium nitride (GaN) device when its characteristic length reaches the nanometer scale. In this work, the authors develop a tip‐enhanced Raman thermometry approach to study ballistic thermal transport within the range of 10 nm in GaN, simultaneously achieving laser heating and measuring the local temperature. The Raman results show that the temperature increase from an Au‐coated tip‐focused hotspot up to two times higher (40 K) than that in a bare tip‐focused region (20 K). To further investigate the possible mechanisms behind this temperature difference, the authors perform electromagnetic simulations to generate a highly focused heating field, and observe a highly localized optical penetration, within a range of 10 nm. The phonon mean free path (MFP) of the GaN substrate can thus be determined by comparing the numerical simulation results with the experimentally measured temperature increase which is in good agreement with the average MFP weighted by the mode‐specific thermal conductivity, as calculated from first‐principles simulations. The results demonstrate that the phonon MFP of a material can be rapidly predicted through a combination of experiments and simulations, which can find wide application in the thermal management of GaN‐based electronics. [ABSTRACT FROM AUTHOR]

Cancer driver genes (CDGs) and the driver mutations disrupt the homeostasis of numerous critical cell activities, thereby playing a critical role in tumor initiation and progression. In this study, integrative bioinformatics analyses were performed based on a series of online databases, aiming to identify driver genes with high frequencies of mutations in head and neck cancers. Higher myeloma overexpressed (MYEOV) genetic variation frequency and expression level were connected to a poorer prognosis in head and neck cancer patients. MYEOV was dramatically upregulated within head and neck tumor samples and cells. Consistently, MYEOV overexpression remarkably enhanced the aggressiveness of head and neck cancer cells by promoting colony formation, cell invasion, and cell migration. Conversely, MYEOV knockdown attenuated cancer cell aggressiveness and inhibited tumor growth and metastasis in the oral orthotopic tumor model. In conclusion, MYEOV is overexpressed in head and neck cancer, with greater mutation frequencies correlating to a poorer prognosis in head and neck cancer patients. MYEOV serves as an oncogene in head and neck cancer through the promotion of tumor cell colony formation, invasion, and migration, as well as promoting tumor growth and metastasis in the oral orthotopic tumor model. [ABSTRACT FROM AUTHOR]

• Machine learning-based method is used in SHM of a composite sandwich structure. • Numerical approach is conducted for the purpose of data enrichment. • Gaussian process classification is achieved for crack type damage identification. • The pertinence of sensors from different locations is discussed. Structural damage of composite materials used in aeronautics and aerospace has attracted increasing attention. Efficient and reliable Structural Health Monitoring (SHM) systems are required to provide a probabilistic interpretation of diagnostics. In this study, crack damage identification of a thick composite sandwich structure based on Gaussian Processes (GP) classification is reported by numerical simulations. The goal of the study is to obtain a data-driven probabilistic interpretation of damage detection. The investigation is carried out based on healthy and damaged status of a sandwich panel with a honeycomb core modelled in ANSYS. Instantaneous signals with different frequencies are applied to the structure and finite element analysis is performed to obtain vibration responses in both statuses. Features extracted by Discrete Wavelet Transform (DWT) are used to train and test the GP model to assess the health status of the structure. Impacts of mother wavelet in DWT, likelihood function and inference method, as well as iteration numbers are investigated on the classification accuracy. The pertinence of sensors located at different positions is also investigated. This proposed method is effective for crack-type damage detection in the studied composite sandwich structure. It is expected to be suitable for damage detection of more complex structures. [ABSTRACT FROM AUTHOR]

A phase change heat sink has higher heat transfer efficiency compared to a traditional metal solid heat sink, and is thus more preferred for the heat dissipation of high-power light-emitting diodes (LEDs) with very high heat flux. The boiling structure at the evaporation surface is the biggest factor that affects heat sink resistance. It is necessary to investigate the plastic deformation law during the machining process of boiling structures. In this study, a novel phase change radial heat sink was developed for high-power LED heat dissipation. First, a working principle and a fabrication process for the heat sink were introduced. Subsequently, to achieve an excellent heat dissipation performance, the machining process of boiling structures was numerically simulated and investigated. To be specific, plastic deformation generated during the formation was analyzed, and key parameters related to the morphology of the boiling structures were discussed including feeding angles and machining depths. Moreover, the finite element (FE) simulation results were compared with those of experiments. Last but not least, the heat transfer performance of the fabricated heat sink was tested. Results showed that the developed heat sink was well suited for a high-power LED application. [ABSTRACT FROM AUTHOR]

The purpose of the study is to evaluate the positive predictive value of the combined pituitary dynamic enhanced MRI (dMRI) and high-dose dexamethasone suppression tests (HDDST) in the diagnosis of Cushing's disease (CD) bypassing bilateral inferior petrosal sinus sampling (BIPSS). A total of 118 patients with Cushing's syndrome (CS), who underwent pituitary dMRI, HDDST and BIPSS were included. Positive predictive value of pituitary dMRI, HDDST, BIPSS and the combined test were calculated and tumor lateralization accuracy was further analyzed. The positive predictive value of the combined pituitary dMRI and HDDST was 98.6%, higher than that of BIPSS. There were 96.8% of patients, who had either negative findings in pituitary dMRI or HDDST, showing centralizing BIPSS results. For tumor lateralization, the accuracy by pituitary dMRI was 88.6%, whereas BIPSS was 57.5%. Therefore, CS patients with both positive findings in pituitary dMRI and HDDST need no further invasive evaluation to establish the definite diagnosis of CD. BIPSS will improve the diagnostic accuracy when negative findings were found in either pituitary dMRI or HDDST. [ABSTRACT FROM AUTHOR]

Evidence regarding the need for surgery for primary intestinal non-Hodgkin lymphoma (PINHL) patients with chemotherapy is limited and controversial. We aimed to investigate the specific impact of surgery on survival of PINHL patients. Data from PINHL patients (aged > 18 years) with chemotherapy between 1983 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We concerned about overall survival (OS) and improved cancer-specific survival (CSS). Propensity score matching (PSM) analysis was also used to explore the reliability of the results to further control for confounding factors. Finally, we screened 3537 patients. Multivariate regression analysis showed that patients with surgery and chemotherapy had better OS (hazard ratio [HR] 0.83; 95% confidence interval [CI] 0.75–0.93; p = 0.0009) and CSS (HR 0.87; 95% CI 0.77–0.99; p = 0.0404) compared with the non-operation group after adjusting for confounding factors. After PSM analysis, compared with non-surgery, surgery remained associated with improved OS (HR 0.77; 95% CI 0.68–0.87; p < 0.0001) and improved CSS (HR 0.82; 95% CI 0.72–0.95; p = 0.008) adjusted for baseline differences. In the large cohort of PINHL patients with chemotherapy older than 18 years, surgery was associated with significantly improved OS and CSS before and after PSM analysis. [ABSTRACT FROM AUTHOR]

Soil fungi are involved in the decomposition of organic matter, and they alter soil structure and physicochemical properties and drive the material cycle and energy flow in terrestrial ecosystems. Fungal community assembly processes were dissimilar in different soil layers and significantly affected soil microbial community function and plant growth. Grazing exclusion is one of the most common measures used to restore degraded grasslands worldwide. However, changes in soil fungal community characteristics during grazing exclusion in different types of grasslands are unknown. Here, we investigated the effects of a 9‐year grazing exclusion on soil properties, fungal community composition, and diversity in three grassland types (temperate desert, temperate steppe, and mountain meadow). The results showed that (1) in the 0–5 cm soil layer, grazing exclusion significantly increased the differences in SWC, SOC, KN, and N:P among the three grassland types, while the final pH, BD, TP, C:N, and C:P values were consistent with the results before exclusion. In the 5–10 cm soil layer, grazing exclusion significantly increased total phosphorus (TP) in temperate deserts by 34.1%, while significantly decreasing bulk density (BD) by 9.8% and the nitrogen: phosphorus ratio (N:P) by 47.1%. (2) The soil fungal community composition differed among the grassland types, For example, significant differences were found among the three grassland types for the Glomeromycota and Mucoromycota. (3) Under the influence of both grazing exclusion and grassland type, there was no significant change in soil fungal alpha diversity, but there were significant differences in fungal beta diversity. (4) Grassland type was the most important factor influencing changes in fungal community diversity, and vegetation cover and soil kjeldahl nitrogen were the main factors influencing fungal diversity. Our research provides a long‐term perspective for better understanding and managing different grasslands, as well as a better scientific basis for future research on grass–soil–microbe interactions. [ABSTRACT FROM AUTHOR]

[Display omitted] Distinguishing substituted aromatic isomers is a challenging task because of the great similarity of their physicochemical properties. Considering xylene isomers have drastically different geometrical shapes, we predict this would show great impact on the self-assembling behavior of various xylene isomer@cyclodextrin inclusion complex. Through host–guest crystalline self-assembly, among three isomers, only ortho -xylene is capable to form hydrogels with α-cyclodextrin. ROESY NMR, molecular simulations and circular dichroism spectra suggest that the ortho selectivity comes from the difference in the conformation of host–guest building block. The larger volume, and steric hinderance of the ortho isomer make it most possibly decrease their tendency to adopt more mobile orientations in cyclodextrin-based complex as meta and para isomers do, resulting in gel formation. Herein, we report a novel, facile and environmentally-friendly protocol on the recognition of ortho benzene isomers using α-cyclodextrin through host–guest crystalline self-assembly. Visual recognition of ortho -xylene is achieved through amplifying the structural difference of xylene isomers at molecular scale into macroscopic scale. We believe this work unveils subtle rules to control macroscopic assemblies at the molecular level and highlights the potential of using macrocyclic compounds to improve the quality and reduce the energy bill for separation in petrochemical industry. [ABSTRACT FROM AUTHOR]

Background: Despite worldwide calls for precautionary measures to combat COVID-19, the public's preventive intention still varies significantly among different regions. Exploring the influencing factors of the public's preventive intention is very important to curtail the spread of COVID-19. Previous studies have found that fear can effectively improve the public's preventive intention, but they ignore the impact of differences in cultural values. The present study examines the combined effect of fear and collectivism on the public's preventive intention towards COVID-19 through the analysis of social media big data.Methods: The Sina microblog posts of 108,914 active users from Chinese mainland 31 provinces were downloaded. The data was retrieved from January 11 to February 21, 2020. Afterwards, we conducted a province-level analysis of the contents of downloaded posts. Three lexicons were applied to automatically recognise the scores of fear, collectivism, and preventive intention of 31 provinces. After that, a multiple regression model was established to examine the combined effect of fear and collectivism on the public's preventive intention towards COVID-19. The simple slope test and the Johnson-Neyman technique were used to test the interaction of fear and collectivism on preventive intention.Results: The study reveals that: (a) both fear and collectivism can positively predict people's preventive intention and (b) there is an interaction of fear and collectivism on people's preventive intention, where fear and collectivism reduce each other's positive influence on people's preventive intention.Conclusion: The promotion of fear on people's preventive intention may be limited and conditional, and values of collectivism can well compensate for the promotion of fear on preventive intention. These results provide scientific inspiration on how to enhance the public's preventive intention towards COVID-19 effectively. [ABSTRACT FROM AUTHOR]

Introduction of silicon into hydroxyapatite (HA) is one of the effective ways to modulate the bioactivity of HA-based biomaterials. The bulk and surface structures of silicate-substituted HA (Si-HA) were characterized by using density functional theory calculations. The energetically favorable structures were identified from a number of candidate structures. Particular attention was paid to the surface structures of Si-HA, whose bioactivity is closely relevant to their surface atoms. Compared to the surface of pure HA, the Si-HA surface has similar surface energy but different charge distribution. Under the implicit solvent model, the exposed calcium/oxygen atoms become more positive/negative in net charge, resulting in a considerable change in the surface electrostatic potential at van der Waals distances. However, changes in the dissolution of surface calcium ions are not remarkable, as depicted by their activation energy leaving from the surface. Our calculations reveal that the surface structures and properties of HA were changed to some extent by silicate substitution, which provides some hints for understanding the experimentally observed changes in bioactivity and biodegradability of Si-HA that still remain controversial in many aspects. [ABSTRACT FROM AUTHOR]

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of adult non-Hodgkin's lymphoma (NHL). While DLBCL is sensitive to chemotherapy, a certain percentage of patients with DLBCL experience relapse. Previous studies have indicated that Yiqichutan treatment, which was developed to treat NHL, can inhibit DLBCL cell growth, but the mechanism is not fully understood. The present study identified 991 differentially expressed mRNAs, with 498 upregulated and 493 downregulated (P<0.05), in SUDHL-6 cells exposed to Yiqichutan. The underlying pathways included the Jak/Stat and PI3K signaling pathways. In total, six representative mRNAs were selected for validation with reverse transcription-quantitative PCR (RT-qPCR), and a strong correlation was identified between the RT-qPCR results and microarray data. Since the transcription factor C-MYC is involved in both the Jak/Stat and PI3K signaling pathways, C-MYC and its associated microRNA (miR) were selected for further analysis. It was found that knockdown of C-MYC increased miR-34a expression levels, inhibited forkhead box P1 (Foxp1) expression levels and promoted DLBCL cell apoptosis. In addition, the miR-34a mimics further enhanced the role of C-MYC knockdown. It was demonstrated that, the expression levels of apoptotic factors Bax and poly (ADP-ribose) polymerase were significantly upregulated with C-MYC knockdown and miR-34a mimics in SUDHL-6 cells, while the Bcl2 expression level was significantly reduced. Moreover, Yiqichutan treatment increased miR-34a expression levels and induced apoptosis, as well as reducing Foxp1 expression level in SUDHL-6 cells. Therefore, the present results suggested that Yiqichutan treatment affected DLBCL cells via several signaling pathways. Furthermore, Yiqichutan may inhibit the proliferation of DLBCL cells by blocking the C-MYC/miR-34a signaling pathway. [ABSTRACT FROM AUTHOR]