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Abstract Candida tropicalis (C. tropicalis) is a zoonotic pathogen that is widespread in the environment and in recent years an increasing number of dairy cows have been infected with the fungus causing mastitis in cows.In this study, 37 milk samples from the udders of cows with clinical mastitis were collected from a dairy farm in Guangxi Province, China, from which C. tropicalis was isolated and identified, and then the isolated fungi were subjected to genome frame map sequencing, genome functional analysis as well as comparative genome analysis of the sequencing results, and combined with the virulence test of the fungi and drug sensitivity test of the fungi determined in infected mice, the resistance genes and pathogenicity of the fungi were Analysis of resistance genes and pathogenicity.Our study results revealed the isolation and characterisation of C. tropicalis from diseased cows, with a genome length of approximately 14.27 Mb. Functional annotation of the genome identified 4068 genes associated with C. tropicalis. The strain exhibited a chemoresistance mutation in the gene cyp51,a virulence-enhancing mutation in the gene VTC4, and mutations in genes linked to drug resistance. Pathogenicity tests demonstrated that C. tropicalis could induce damage to the internal organs of mice, leading to different levels of cyanosis in the abdominal cavity, white necrotic foci on the surface of internal organs, lung hemorrhage, and enlargement of the spleen and thymus.Histological sections also revealed varying degrees of hemorrhage and degenerative changes in the cells of different organs in the mice. Drug sensitivity tests showed that the fungus was highly sensitive to nystatin and ketoconazole, moderately sensitive to amphotericin B, and insensitive to antibiotics such as itraconazole, gentamicin, and penicillin. In conclusion, C. tropicalis isolated from dairy cows in the Guangxi region in this study was pathogenic and resistant to azoles such as itraconazole and fluconazole, and this study provides a theoretical basis for the further screening of novel resistance genes in C. tropicalis, as well as providing a certain reference for the drugs used for the treatment of fungal cow mastitis in this region.

Abstract In order to reveal adsorption-regulation micromechanism and debonding micromechanism between wall surface and magnetorheological (MR) wall-climbing robot legs, an interparticle normal magnetic attraction (NMA) mechanics model was constructed based upon the magnetic-dipole theory. According to analysis of NMA mechanics, it was confirmed that the interparticle NMA could be intensified with enhancing magnetic-particle diameter but was weakened with ratio of adjacent magnetic-particles distance to magnetic-particle radius. It means that the adhesive capacity between MR wall-climbing robot legs and wall surface could be strengthened by increasing magnetic-particle size and decreasing interparticle distance. Furthermore, it was found that the NMA of the first particle in the magnetic chain was positively related to magnetic-particles number until the magnetic-particles number reached a critical value. Consequently, the adsorption ability between MR wall-climbing robot legs and wall surface could be effectively controlled by changing magnetic-particles number. Besides, the strongest NMA appeared at the middle of the magnetic chain. However, the weakest NMA locates at both ends of the magnetic chain. Thus, it could be concluded that the end of the magnetic chain would be separated from wall surface rather than fracture occurred in the middle of the magnetic chain when the MR wall-climbing robot legs divorced from wall surface.

ABSTRACT: Exposure to copper (Cu) has been associated with metabolic disorders in animals and humans, but the underlying mechanism remains unclear. One-day-old broiler chickens, numbering a total of 192, were nourished with dietary intakes that contained varying concentrations of Cu, specifically 11, 110, 220, and 330 mg/kg of Cu, for a period extending over a duration of 7 wk. As a result of the study, Cu exposure resulted in vacuolization, fragmentation of mitochondria cristae, and the increase of autophagosomes in hepatocytes. Metabolomics analysis illustrated that Cu caused a total of 59 different metabolites in liver, predominantly associated with the glycerophospholipid metabolic pathway, leading to metabolic disruption. Moreover, high-Cu diet markedly reduced the levels of AMPKα1, p-AMPKα1, mTOR, and p-mTOR and enhanced the expression levels of the autophagy-related factors (Atg5, Dynein, Beclin1, and LC3-II). Overall, Cu exposure caused chicken liver injury and resulted in disturbed metabolic processes and mediated autophagy primarily through the AMPK-mTOR axis.

ABSTRACT: Berberine (BBR), a well-known quaternary ammonium alkaloid, is recognized for its ability to prevent and alleviate metabolic disorders because of its anti-oxidative and anti-inflammatory properties. However, the underlying mechanisms of BBR to mitigate fatty liver hemorrhagic syndrome (FLHS) through the modulation of gut microbiota and their metabolism remained unclear. The results revealed that BBR ameliorates lipid metabolism disorder in high-energy and low-protein (HELP) diet-induced FLHS laying hens, as evidenced by improved liver function and lipid deposition of the liver, reduced blood lipids, and the expression of liver lipid synthesis-related factors. Moreover, BBR alleviated HELP diet-induced barrier dysfunction, increased microbial population, and dysregulated lipid metabolism in the ileum. BBR reshaped the HELP-perturbed gut microbiota, particularly declining the abundance of Desulfovibrio_piger and elevating the abundance of Bacteroides_salanitronis_DSM_18170. Meanwhile, metabolomic profiling analysis revealed that BBR reshaped microbial metabolism and function, particularly by reducing the levels of hydrocinnamic acid, dehydroanonaine, and leucinic acid. Furthermore, fecal microbiota transplantation (FMT) experiments revealed that BBR-enriched gut microbiota alleviated hepatic lipid deposition and intestinal inflammation compared with those chicks that received a gut microbiota by HELP. Collectively, our study provided evidence that BBR effectively alleviated FLHS induced by HELP by reshaping the microbial and metabolic homeostasis within the liver-gut axis.

ABSTRACT: Yolk Peritonitis can lead to a rapid decline in egg production, which seriously affects the health of laying hens and the profitability of chicken farms. Escherichia coli (E. coli) is the most common cause of yolk peritonitis in laying hens. In this study, bacterial samples were collected from the ovaries and fallopian tubes of laying hens with suspected yolk peritonitis from a laying farm in Jiangsu Province, and their pathogenicity and drug resistance were investigated. Initially, morphological and biochemical detection methods were employed to isolate and identify the pathogenic bacteria. The results showed that a total of 16 strains of E. coli were isolated from laying hens with yolk peritonitis. Subsequently, the drug resistance and pathogenicity of a randomly selected E. coli strain were analyzed and predicted by genome sequencing technology, and the drug resistance of E. coli was verified by drug sensitivity test and PCR. Finally, the virulence was verified by infection experiment in mice. The study revealed that the egg-yolk peritonitis in laying hens was caused by E. coli infection, and the genome sequencing analysis revealed that the bacteria had multidrug resistance and high virulence. The drug susceptibility testing indicates that E. coli exhibited resistance to aminoglycosides, β-lactam, macrolides, fluoroquinolones, and sulfonamides. In this study, resistance genes including KdpE, aadA5, APH(3 '')-ID, APH(6)-ID, and TEM-1 were identified, and their expression levels varied across different stages of bacterial growth. The results of virulence analysis indicated a mortality rate of 50% in mice infected with E. coli at a concentration of 2.985 × 107 CFU/mL. E. coli infection resulted in damage to various tissues and organs in mice, with the intestinal tissue structure being the most severely affected. This study provides a reference for the study of drug resistance mechanisms in E. coli and provides valuable insights into the selection of drugs for the treatment of vitelline peritonitis.

To improve the characteristics of traditional model predictive control (MPC) semi-active suspension that cannot achieve the optimal suspension control effect under different conditions, a variable horizon model predictive control (VHMPC) method is devised for magnetorheological semi-active suspension with air springs. Mathematical models are established for the magnetorheological dampers and air springs. Based on the improved hyperbolic tangent model, a forward model is established for the magnetorheological damper. The adaptive fuzzy neural network method is used to establish the inverse model of the magnetorheological damper. The relationship between different road excitation frequencies and the control effect of magnetorheological semi-active suspension with air springs is simulated, and the optimal prediction horizons under different conditions are obtained. The VHMPC method is designed to automatically switch the predictive horizon according to the road surface excitation frequency. The results demonstrate that under mixed conditions, compared with the traditional MPC, the VHMPC can improve the smoothness of the suspension by 2.614% and reduce the positive and negative peaks of the vertical vibration acceleration by 11.849% and 6.938%, respectively. Under variable speed road conditions, VHMPC improved the sprung mass acceleration, dynamic tire deformation, and suspension deflection by 7.191%, 7.936%, and 22.222%, respectively, compared to MPC.

Aiming at the problem of system controller performance failure caused by improperly setting the value of each weighting coefficient of the model predictive control (MPC), a fractional-order MPC strategy with Takagi–Sugeno fuzzy optimization (T–SFO MPC) is proposed for a vehicle active suspension system. Firstly, the fractional-order model predictive control framework for active suspension systems is designed based on a 1/4 vehicle model. Then, we analyze the influence of different weighting coefficients on the suspension performance and introduce the Takagi–Sugeno fuzzy optimization theory to adaptively adjust the weighting coefficients of the fractional-order MPC controller. Finally, the system responses of the T–SFO MPC, traditional MPC, linear quadratic regulator (LQR), and passive suspension control are numerically analyzed under various road conditions. Simulation results show that suspension response with the T–SFO MPC is significantly improved compared with passive suspension control, traditional MPC control, and LQR control, and the weight coefficients of the T–SFO MPC can be adaptively adjusted according to the dynamic changes of suspension response. Compared with passive suspension, the root mean square (RMS) value of the vertical acceleration of the T–SFO MPC under various roads decreased by a maximum of 37.97%, and the RMS value of suspension dynamic deflection and tire dynamic load decreased by a maximum of 32.94% and 37.8%, respectively. These results validate that the proposed control method can achieve coordinated optimization of vehicle comfort and handling stability.

This paper proposes a mixed-mode (combining shear and squeeze working modes) vibration isolator using magnetorheological elastomer (MRE), which enables the isolator to have a larger working area and better isolation performance by combining the working modes of the MRE. Firstly, based on the magnetorheological effect working principle of the MRE, the material selection and dimensional parameters of each component are determined through structural design and magnetic circuit calculation. On this basis, magnetic field simulation is conducted using Maxwell 16.0 software to analyze the distribution of magnetic field lines and magnetic induction in the working area. Simultaneously, equivalent stiffness and equivalent damping models are established to explore the variation of vibration response with external current and excitation frequency conditions. Finally, a vibration isolation experimental platform is built to test the mixed-mode MRE isolator. The experimental results are basically consistent with the simulation modeling results. The experimental results showed that when the external excitation is in the frequency range of 16 Hz, effective semi-active vibration isolation control could be achieved by applying different current inputs. The isolation effect of the system is difficult to effectively control using current input when the external excitation is at high frequency. These results validate the rationality and feasibility of the mixed-mode MRE isolator structure, which provides a good reference for the design of MRE isolators.

ABSTRACT: Pulmonary artery remodeling is a characteristic feature of broiler ascites syndrome (BAS). Pulmonary artery endothelial cells (PAECs) regulated by HIF-1α play a critical role in pulmonary artery remodeling, but the underlying mechanisms of HIF-1α in BAS remain unclear. In this experiment, primary PAECs were cultured in vitro and were identified by coagulation factor VIII. After hypoxia and RNA interference, the mRNA and protein expression levels of HIF-1α and VEGF were determined by qPCR and Western blotting. The transcriptome profiles of PAECs were obtained by RNA sequencing. Our results showed that the positive rate of PAECs was more than 90%, hypoxia-induced promoted the proliferation and apoptosis of PAECs, and RNA interference significantly downregulated the expression of HIF-1α, inhibited the proliferation of PAECs, and promoted the apoptosis of PAECs. In addition, transcriptome sequencing analysis indicated that HIF-1α may regulate broiler ascites syndrome by mediating COL4A, vitronectin, vWF, ITGα8, and MKP-5 in the ECM, CAMs and MAPK pathways in PAECs. These studies lay the foundation for further exploration of the mechanisms of pulmonary artery remodeling, and HIF-1α may be a potentially effective gene for the prevention and treatment of BAS.

The performance of a semi-active suspension depends on the quality of the control algorithm. Considering the limitations of conventional PID controllers within intricate nonlinear systems, such as imprecise parameter tuning and performance deterioration, we introduced a fractional-order PID (FOPID) control strategy for vehicle semi-active suspension, this approach amalgamates fractional-order theory with conventional PID control to enhance both the controllable scope and precision of the suspension system. Research on semi-active suspension control was conducted using a nonlinear dynamic model of a quarter vehicle. Simulations and analyses were performed utilizing random road excitation and impact road excitation as input signals for both FOPID control, Fuzzy-PID control, and conventional PID control strategies. The analysis findings demonstrated that in the presence of random road excitation, the semi-active suspension system controlled by FOPID reduced vehicle body acceleration by 18.9%, in contrast to a 14.7% reduction by the Fuzzy-PID-controlled suspension, and a 12% reduction achieved by the PID-controlled suspension when compared to the passive suspension. In response to impact road excitation, the suspension system under FOPID control effectively mitigated the peak value of vehicle body acceleration by 29.4%, surpassing the 25.2% reduction achieved by Fuzzy-PID-controlled suspension, and the 24.6% reduction achieved by the PID-controlled suspension. The simulation outcomes substantiated that ride comfort and handling stability of the semi-active suspension system were effectively improved by the implementation of FOPID control.

ABSTRACT: Fatty liver hemorrhagic syndrome (FLHS) is a prevalent metabolic disorder observed in egg-laying hens, characterized by fatty deposits and cellular steatosis in the liver. Our preliminary investigations have revealed a marked decrease in the concentration of butyric acid in the FLHS strain of laying hens. It has been established that sodium butyrate (NaB) protects against metabolic disorders. However, the underlying mechanism by which butyrate modulates hepato-lipid metabolism to a great extent remains unexplored. In this study, we constructed an isolated in vitro model of chicken primary hepatocytes to induce hepatic steatosis by free fatty acids (FFA). Our results demonstrate that treatment with NaB effectively mitigated FFA-induced hepatic steatosis in chicken hepatocytes by inhibiting lipid accumulation, downregulating the mRNA expression of lipo-synthesis-related genes (sterol regulatory element binding transcription factor 1 (SREBF1), acetyl-CoA carboxylase 1(ACC1), fatty acid synthase (FASN), stearoyl-CoA desaturase 1 (SCD1), liver X receptor α (LXRα), 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR)) (P < 0.05), and upregulating the mRNA and protein expression of AMP-activated protein kinase α1 (AMPKα1), peroxisome proliferator-activated receptor α (PPARα), and carnitine palmitoyl-transferase 1A (CPT1A) (P < 0.05). Moreover, AMPK and PPARα inhibitors (Compound C (Comp C) and GW6471, respectively) reversed the protective effects of NaB against FFA-induced hepatic steatosis by blocking the AMPK/PPARα pathway, leading to lipid droplet accumulation and triglyceride (TG) contents in chicken primary hepatocytes. With these findings, NaB can alleviate hepatocyte lipoatrophy injury by activating the AMPK/PPARα pathway, promoting fatty acid oxidation, and reducing lipid synthesis in chicken hepatocytes, potentially being able to provide new ideas for the treatment of FLHS.

Nickel and chromium are both common heavy metals that pose serious environmental and health hazards. However, the exact mechanism by which nickel and/or chromium cause renal injury is unclear. Therefore, we explored the molecular mechanisms of renal injury caused by nickel and/or chromium poisoning from the perspective of mitochondrial dynamics and the Nrf2 antioxidant pathway. In this study, eighty 6-week-old C57BL/6J mice were randomly divided into four groups: control (Con, untreated), nickel (Ni, 110 mg/L Ni2+), chromium (Cr, 50 mg/L Cr6+), and combined nickel–chromium (Ni + Cr, 110 mg/L Ni2+, 50 mg/L Cr6+). The results showed that chronic nickel and/or chromium exposure inhibited body weight gain and impaired kidney function and structure in mice. Chronic nickel and/or chromium exposure led to the disruption of mitochondrial dynamics and thus induced oxidative stress. On the other hand, the Nrf2 antioxidant pathway may play an important regulatory role in mitigating oxidative stress-induced oxidative damage in kidney. The present study partially elucidated the molecular mechanism of renal injury induced by nickel and/or chromium exposure in mice and the regulatory role of the Nrf2 pathway in inducing oxidative injury from the perspective of mitochondrial dynamics. This provides a theoretical basis for the development of prevention and control strategies, and environmental protection measures.

The performance of the suspension is a crucial criterion for evaluating both vehicle handling and passenger comfort. To enhance suspension performance, this study proposes the design of a Quantum Genetic Fuzzy Sliding Mode Controller (S-QFSMC) based on the Smith predictor estimator, building upon the foundation of the vehicle magneto-rheological semi-active air suspension. According to the physical model of the vehicle suspension, a mechanical model of a quarter-vehicle magneto-rheological semi-active air suspension with time delay is established. On this basis, a conventional sliding mode controller is designed, and quantum genetic algorithm and fuzzy control principles are employed to optimize the chattering issue associated with sliding mode control. The Smith predictor estimator is utilized to effectively compensate for the time delay in the suspension system. Subsequently, a simulation analysis of the vehicle suspension performance is conducted. The results indicate that, compared to passive suspension control, both the QFSMC controller and the S-QFSMC controller improve the suspension performance, with the S-QFSMC controller exhibiting superior comprehensive improvement. This validates the effectiveness of the designed controllers.

Atrazine (ATR), a water-soluble herbicide commonly used to control broad-leaf and monocotyledonous weeds, presents a significant risk to environmental soil and water quality. Exposure to ATR adversely affects human and animal health, frequently resulting in cardiac impairment. Curcumin (Cur), an acidic polyphenol derivative from plants acclaimed for its pronounced anti-inflammatory and antioxidant properties, has garnered interest as a potential therapeutic agent. However, whether it has the potential to ameliorate ATR-induced cardiac toxicity via modulation of endoplasmic reticulum stress (ERS) and apoptosis pathways in mice remains unclear. Our results showed that Cur supplementation attenuates ATR-induced cardiotoxicity, evidenced by decrease in creatine kinase and lactate dehydrogenase, key biochemical markers of myocardial injury, which have a more significant protecting effect in high-dose ATR induced injury. Histopathological and electron microscopy examinations further solidified these findings, demonstrating an amelioration in organellar damage, particularly in endoplasmic reticulum swelling and subsequent mitochondrial impairment. Additionally, ATR exposure augments ERS and triggers apoptotic pathways, as indicated by the upregulation of ERS-related gene expression (ATF6, CHOP, IRE1, GRP78) and pro-apoptotic markers (BAX, BAK1, Caspase3, Caspase. Intriguingly, Cur counteracts this detrimental response, significantly reducing ERS and pro-apoptotic signals at both transcriptional and translational levels. Collectively, our findings illuminate Cur’s cardioprotective effect against ATR-induced injury, primarily through its anti-ERS and anti-apoptotic activities, underscoring Cur’s potential as a therapeutic for ATR-induced cardiotoxicity.

Fatty liver hemorrhagic syndrome (FLHS) in laying hens is a nutritional metabolic disease commonly observed in high-yielding laying hens. Sodium butyrate (NaB) and ferroptosis were reported to contribute to the pathogenesis of fatty liver-related diseases. However, the underlying mechanism of NaB in FLHS and whether it mediates ferroptosis remains unclear. A chicken primary hepatocyte induced by free fatty acids (FFAs, keeping the ratio of sodium oleate and sodium palmitate concentrations at 2:1) was established, which received treatments with NaB, the ferroptosis inducer RAS-selective lethal 3 (RSL3), and the inhibitor ferrostatin-1 (Fer-1). As a result, NaB increased biochemical and lipid metabolism indices, and the antioxidant level, while inhibiting intracellular ROS accumulation and the activation of the ferroptosis signaling pathway, as evidenced by a reduction in intracellular iron concentration, upregulated GPX4 and xCT expression, and inhibited NCOA4 and ACSL4 expression. Furthermore, treatment with Fer-1 reinforced the protective effects of NaB, while RSL3 reversed it by blocking the ROS/GPX4/ferroptosis pathway, leading to the accumulation of lipid droplets and oxidative stress. Collectively, our findings demonstrated that NaB protects hepatocytes by regulating the ROS/GPX4-mediated ferroptosis pathway, providing a new strategy and target for the treatment of FLHS.

ABSTRACT: Riemerella anatipestifer is a Gram-negative, rod-shaped bacterium that is flagellated, non-budded, and encapsulated, measuring approximately 0.4 μm × 0.7 μm. After infecting ducklings with R. anatipestifer, the hosts exhibited pathological changes, such as bacterial meningitis, fibrinous pericarditis, and fibrinous peripheral hepatitis. The pathogenesis of meningitis caused by R. anatipestifer has not yet been elucidated. To investigate the key molecules or proteins involved in R. anatipestifer's penetration of the blood-brain barrier (BBB) and the subsequent development of duck meningitis, a duck meningitis model was established and characterized. Duckling brain tissues were collected and analyzed using 4D label-free proteomic technology. Differentially expressed proteins were analyzed using a series of bioinformatics methods and verified using RT-qPCR and Western-Blot. The results showed that the differentially expressed proteins were primarily related to intracellular transport, transport protein activity, and transmembrane transport protein activity, and were mainly enriched in pathways associated with reducing intercellular connections and adhesion and increasing cell migration and apoptosis. Thus, it is suggested that R. anatipestifer may penetrate the BBB via transcellular and paracellular pathways, causing neurological diseases such as meningitis. This study is the first to analyze R. anatipestifer-infected duckling brain tissue using proteomics, thus providing a direction for further research into the mechanisms of R. anatipestifer's penetration of the BBB.

Abstract Background Unhealthy lifestyle behaviors among adolescents have emerged as a significant public health concern worldwide, however, there is little investigation on the impact of unhealthy behaviors on non-suicidal self-injury (NSSI), suicidal ideation (SI) and suicide attempt (SA). This study aimed to investigate the prevalence of seven unhealthy behaviors as well as their associations with NSSI, SI and SA, and to explore whether the aforementioned associations differ across sex. Methods A total of 74,152 adolescents were included in this study via a multi-stage, stratified cluster, random sampling method in 2021. Information about unhealthy behaviors (insufficient physical activity, current smoking, current drinking, excessive screen time, long homework time, insufficient sleep and unhealthy BMI), NSSI, SI, SA and other demographics was collected. Sampling weights were used to estimate the prevalence, and the weighted logistic regression models were performed. Stratified analyses by sex and sensitive analyses were conducted. Results Overview, the weighted prevalence of adolescents had more than five unhealthy behaviors were 5.2%, with boys showing a higher prevalence than girls (6.5% vs.3.8%). Current smoking, current drinking, excessive screen use, long homework time, insufficient sleep, and unhealthy BMI were significantly associated with NSSI, SI and SA. Moreover, adolescents with high lifestyle risk scores were associated with an increased risk of NSSI (5–7 vs. 0: OR 6.38, 95% CI 5.24–7.77), SI (5–7 vs. 0: OR 7.67, 95% CI 6.35–9.25), and SA (5–7 vs. 0: OR 9.57, 95% CI 6.95–13.17). Significant sex differences were found in the associations of unhealthy behaviors with NSSI, SI and SA. Conclusion Unhealthy behaviors are quite common among Chinese adolescents. Adolescents with multiple unhealthy behaviors are associated with increased risks of NSSI, SI, and SA. The implementation of school and family-based interventions to promote healthy lifestyles is recommended as a preventive measure against self-injurious behavior and suicidality in adolescents.

Abstract Objectives To compare the diagnostic performance of intratumoral and peritumoral features from different contrast phases of breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) by building radiomics models for differentiating molecular subtypes of breast cancer. Methods This retrospective study included 377 patients with pathologically confirmed breast cancer. Patients were divided into training set (n = 202), validation set (n = 87) and test set (n = 88). The intratumoral volume of interest (VOI) and peritumoral VOI were delineated on primary breast cancers at three different DCE-MRI contrast phases: early, peak, and delayed. Radiomics features were extracted from each phase. After feature standardization, the training set was filtered by variance analysis, correlation analysis, and least absolute shrinkage and selection (LASSO). Using the extracted features, a logistic regression model based on each tumor subtype (Luminal A, Luminal B, HER2-enriched, triple-negative) was established. Ten models based on intratumoral or/plus peritumoral features from three different phases were developed for each differentiation. Results Radiomics features extracted from delayed phase DCE-MRI demonstrated dominant diagnostic performance over features from other phases. However, the differences were not statistically significant. In the full fusion model for differentiating different molecular subtypes, the most frequently screened features were those from the delayed phase. According to the Shapley additive explanation (SHAP) method, the most important features were also identified from the delayed phase. Conclusions The intratumoral and peritumoral radiomics features from the delayed phase of DCE-MRI can provide additional information for preoperative molecular typing. The delayed phase of DCE-MRI cannot be ignored. Critical relevance statement Radiomics features extracted and radiomics models constructed from the delayed phase of DCE-MRI played a crucial role in molecular subtype classification, although no significant difference was observed in the test cohort. Key Points The molecular subtype of breast cancer provides a basis for setting treatment strategy and prognosis. The delayed-phase radiomics model outperformed that of early-/peak-phases, but no differently than other phases or combinations. Both intra- and peritumoral radiomics features offer valuable insights for molecular typing. Graphical Abstract

Abstract In nature, structural and functional materials often form programmed three-dimensional (3D) assembly to perform daily functions, inspiring researchers to engineer multifunctional 3D structures. Despite much progress, a general method to fabricate and assemble a broad range of materials into functional 3D objects remains limited. Herein, to bridge the gap, we demonstrate a freeform multimaterial assembly process (FMAP) by integrating 3D printing (fused filament fabrication (FFF), direct ink writing (DIW)) with freeform laser induction (FLI). 3D printing performs the 3D structural material assembly, while FLI fabricates the functional materials in predesigned 3D space by synergistic, programmed control. This paper showcases the versatility of FMAP in spatially fabricating various types of functional materials (metals, semiconductors) within 3D structures for applications in crossbar circuits for LED display, a strain sensor for multifunctional springs and haptic manipulators, a UV sensor, a 3D electromagnet as a magnetic encoder, capacitive sensors for human machine interface, and an integrated microfluidic reactor with a built-in Joule heater for nanomaterial synthesis. This success underscores the potential of FMAP to redefine 3D printing and FLI for programmed multimaterial assembly.

Invar 36 alloy, renowned for its ultra-low coefficient of thermal expansion (CTE), is a functional Fe–Ni alloy that finds wide applications in aerospace and precision instruments. Additive manufacturing (AM), as a rapid digital manufacturing process, can efficiently and flexibly fabricate Invar 36 alloy parts with complex geometric and exceptional properties. Considering the advantages of AM and the increasing interest and demand for Invar 36 alloy parts fabrication by AM in recent years, it is imperative to provide a comprehensive summary of the current research status and technological advancements pertaining to AM Invar 36 alloy. Firstly, an overview of the AM processes currently employed for fabricating Invar 36 alloy is provided, including laser powder bed fusion, selective laser sintering, directed energy deposition, cold spray additive manufacturing, wire arc additive manufacturing, and binder jetting. Additionally, the microstructure, mechanical properties, and CTE of Invar 36 alloy manufactured by AM are summarized. Even eliminating the post heat treatment, the as-printed Invar 36 alloy can achieve excellent low CTE and mechanical properties, comparable to or exceeding traditional manufacturing processes. Moreover, the advantages and research progress of AM Invar 36 alloy composites are introduced. Enhancing mechanical properties while reducing CTE is a common challenge for both AM Invar 36 alloy and Invar composites. Finally, the technical gaps, research trends, and potential applications of AM Invar 36 alloy are summarized and prospected.

The exploration of intelligent machines has recently spurred the development of physical neural networks, a class of intelligent metamaterials capable of learning, whether in silico or in situ, from observed data. In this study, we introduce a back-propagation framework for lattice-based mechanical neural networks (MNNs) to achieve prescribed static and dynamic performance. This approach leverages the steady states of nodes for back-propagation, efficiently updating the learning degrees of freedom without prior knowledge of input loading. One-dimensional MNNs, trained with back-propagation in silico, can exhibit the desired behaviors on demand function as intelligent mechanical machines. The framework is then employed for the precise morphing control of the two-dimensional MNNs subjected to different static loads. Moreover, the intelligent MNNs are trained to execute classical machine learning tasks such as regression to tackle various deformation control tasks. Finally, the disordered MNNs are constructed and trained to demonstrate pre-programmed wave bandgap control ability, illustrating the versatility of the proposed approach as a platform for physical learning. Our approach presents an efficient pathway for the design of intelligent mechanical metamaterials for a wide range of static and dynamic target functionalities, positioning them as powerful engines for physical learning.

Objectives This study sought to evaluate the diagnostic value of a non-contact optical fiber mattress for apnea and hypopnea and compare it with traditional polysomnography (PSG) in adult obstructive sleep apnea hypopnea syndrome (OSAHS). Methods To determine the value of a non-contact optical fiber mattress for apnea and hypopnea, six healthy people and six OSAHS patients were selected from Tongji Hospital to design a program to identify apnea or hypopnea. A total of 108 patients who received polysomnography for drowsiness, snoring or other suspected OSAHS symptoms. All 108 patients were monitored with both the non-contact optical fiber mattress and PSG were collected. Results Six healthy controls and six patients with OSAHS were included. The mean apnea of the six healthy controls was 1.22 times/h, and the mean hypopnea of the six healthy controls was 2 times/h. Of the six patients with OSAHS, the mean apnea was 12.63 times/h, and the mean hypopnea was 19.25 times/h. The non-contact optical fiber mattress results showed that the mean apnea of the control group was 3.17 times/h and the mean hypopnea of the control group was 3.83 times/h, while the mean apnea of the OSAHS group was 11.95 times/h and the mean hypopnea of the OSAHS group was 17.77 times/h. The apnea index of the non-contact optical fiber mattress was positively correlated with the apnea index of the PSG (P < 0.05, r = 0.835), and the hypopnea index of the non-contact optical fiber mattress was also positively correlated with the hypopnea index of the PSG (P < 0.05, r = 0.959). The non-contact optical fiber mattress had high accuracy (area under curve, AUC = 0.889), specificity (83.4%) and sensitivity (83.3%) for the diagnosis of apnea. The non-contact fiber-optic mattress also had high accuracy (AUC = 0.944), specificity (83.4%) and sensitivity (100%) for the diagnosis of hypopnea. Among the 108 patients enrolled, there was no significant difference between the non-contact optical fiber mattress and the polysomnography monitor in total recording time, apnea hypopnea index (AHI), average heart rate, tachycardia index, bradycardia index, longest time of apnea, average time of apnea, longest time of hypopnea, average time of hypopnea, percentage of total apnea time in total sleep time and percentage of total hypopnea time in total sleep time. The AHI value of the non-contact optical fiber mattress was positively correlated with the AHI value of the PSG (P < 0.05, r = 0.713). The specificity and sensitivity of the non-contact optical fiber mattress AHI in the diagnosis of OSAHS were 95% and 93%, with a high OSAHS diagnostic accuracy (AUC = 0.984). Conclusion The efficacy of the non-contact optical fiber mattress for OSAHS monitoring was not significantly different than PSG monitoring. The specificity of the non-contact optical mattress for diagnosing OSAHS was 95% and its sensitivity was 93%, with a high OSAHS diagnostic accuracy.

Steel-fiber reinforced polymer (FRP) composite bars (SFCBs) can enhance the controllability of damage in concrete structures; thus, studying the interfacial bonding between them is fundamental and a prerequisite for achieving deformation coordination and collaboration. However, research on the interfacial bonding performance between SFCBs and concrete remains inadequate. This study conducted central pullout tests on SFCB-concrete specimens with different concrete strengths (C30, C50, and C70), bar diameters (12, 16 and 20 mm), and hoop reinforcement constraints, analyzing variations in failure modes, bond-slip curves, bond strength, etc. Additionally, finite element simulations were performed using ABAQUS software to further validate the bonding mechanism of SFCB-concrete. The results showed that the failure mode of the specimens was related to the confinement effect on the bars. Insufficient concrete cover and lack of hoop restraint led to splitting failure, whereas pullout failure occurred otherwise. For the specimens with pullout failure, the interfacial damage between the SFCB and concrete was mainly caused by the surface fibers wear of the bar and the shear of the concrete lugs, which indicated that the bond of the SFCB-concrete interface consisted mainly of mechanical interlocking forces. In addition, the variation of concrete strength as well as bar diameter did not affect the bond-slip relationship of SFCB-concrete. However, the bond strength of SFCB-concrete increased with the increase of concrete strength. For example, compared with C30 concrete, when the concrete strength was increased to C70, the bond strength of the specimens under the same conditions was increased to 50–101.6%. In contrast, the bond strength of the specimens decreased by 13.29–28.71% when the bar diameter was increased from 12 to 14 mm. These discoveries serve as valuable references for the implementation of sustainable SFCB-reinforced concrete structures.

The major liver cancer subtype is hepatocellular carcinoma (HCC). Studies have indicated that a better prognosis is related to the presence of tumor-infiltrating lymphocytes (TILs) in HCC. However, the molecular pathways that drive immune cell variation in the tumor microenvironment (TME) remain poorly understood. Glycosylation (GLY)-related genes have a vital function in the pathogenesis of numerous tumors, including HCC. This study aimed to develop a GLY/TME classifier based on glycosylation-related gene scores and tumor microenvironment scores to provide a novel prognostic model to improve the prediction of clinical outcomes. The reliability of the signatures was assessed using receiver operating characteristic (ROC) and survival analyses and was verified with external datasets. Furthermore, the correlation between glycosylation-related genes and other cells in the immune environment, the immune signature of the GLY/TME classifier, and the efficacy of immunotherapy were also investigated. The GLY score low/TME score high subgroup showed a favorable prognosis and therapeutic response based on significant differences in immune-related molecules and cancer cell signaling mechanisms. We evaluated the prognostic role of the GLY/TME classifier that demonstrated overall prognostic significance for prognosis and therapeutic response before treatment, which may provide new options for creating the best possible therapeutic approaches for patients.

Accurate matching between in-vehicle sensor data and high-definition (HD) maps is crucial to improve the performance of perception and localization of intelligent vehicles. A novel algorithm of HD map matching based on the developed semantic likelihood model (SLM) is proposed to achieve intelligent vehicle localization and object detection simultaneously. First, semantic pavement objects are extracted from front-view images by using U-Net, and SLM is constructed with kernel density estimation (KDE). Under a particle filter framework, the likelihood between the sensor data and HD map is calculated by projecting each sample point from HD map with pose transformation onto SLM to update the weight of each particle. Simultaneously, accurate detection of pavement markings is accomplished by projecting all elements onto the HD map with the computed localization results. In the experiment, data collected on campus and on urban roads are used to validate the proposed algorithm. The experimental results show that the localization errors in both scenarios are about 14 cm, and the mean intersection over union (MIoU) of road marking detection is above 80. The results demonstrate that the proposed algorithm can significantly improve both localization and detection performance by effectively utilizing the prior information of HD maps, compared with the state of the art (SOTA) methods, such as deep learning-based detection methods.