Enhancing Carbon Nanotube Yarns via Infiltration Filling with Polyacrylonitrile in Supercritical Carbon Dioxide.

Carbon nanotube (CNT) fibers are renowned for their exceptional axial tensile strength and modulus. However, in yarn form, they frequently encounter transverse loading in practical applications, which exposes their suboptimal mechanical attributes rooted in inadequate inter-tube interactions and yarn surface defects. Efforts to mitigate micro-slippage among CNTs have encompassed gap-filling methodologies with varied materials, yet the outcomes have fallen short of expectations. This work aimed to enhance the mechanical properties of CNT yarns via infiltration with polyacrylonitrile (PAN) under supercritical carbon dioxide (sc-CO2) conditions. PAN was strategically chosen for its capability to undergo pre-oxidation and subsequent carbonization, leading to robust graphitic reinforcement. Leveraging sc-CO2's swelling and high permeability properties, the infiltration process effectively plugged interstitial spaces, elevating the yarn's tensile strength to 277.50 MPa and Young's modulus to 5094.05 MPa. Additional enhancements were realized after pre-oxidation, conferring a dense, reinforced shell structure that augmented tensile strength by 96.93% and Young's modulus by 298.80%. Scanning electron microscopy (SEM) analyses revealed a homogeneous PAN distribution within the yarn matrix, corroborated by X-ray photoelectron spectroscopy (XPS) evidence of C-N bonding, indicative of a successfully interlaced network. Consequently, this investigation introduces a novel strategy to tackle micro-slippage in CNT yarns, thereby achieving substantial improvements in their mechanical resilience.

Robust Attitude Estimation for Low-Dynamic Vehicles Based on MEMS-IMU and External Acceleration Compensation.

Attitude determination based on a micro-electro-mechanical system inertial measurement unit (MEMS-IMU) has attracted extensive attention. The non-gravitational components of the MEMS-IMU have a significant effect on the accuracy of attitude estimation. To improve the attitude estimation of low-dynamic vehicles under uneven soil conditions or vibrations, a robust Kalman filter (RKF) was developed and tested in this paper, where the noise covariance was adaptively changed to compensate for the external acceleration of the vehicle. The state model for MEMS-IMU attitude estimation was initially constructed using a simplified direction cosine matrix. Subsequently, the variance of unmodeled external acceleration was estimated online based on filtering innovations of different window lengths, where the acceleration disturbance was addressed by tradeoffs in time-delay and prescribed computation cost. The effectiveness of the RKF was validated through experiments using a three-axis turntable, an automatic vehicle, and a tractor tillage test. The turntable experiment demonstrated that the angle result of the RKF was 0.051° in terms of root mean square error (RMSE), showing improvements of 65.5% and 29.2% over a conventional KF and MTi-300, respectively. The dynamic attitude estimation of the automatic vehicle showed that the RKF achieves smoother pitch angles than the KF when the vehicle passes over speed bumps at different speeds; the RMSE of pitch was reduced from 0.875° to 0.460° and presented a similar attitude trend to the MTi-300. The tractor tillage test indicated that the RMSE of plough pitch was improved from 0.493° with the KF to 0.259° with the RKF, an enhancement of approximately 47.5%, illustrating the superiority of the RKF in suppressing the external acceleration disturbances of IMU-based attitude estimation.

Dynamic immune status analysis of peripheral blood mononuclear cells in patients with Klebsiella pneumoniae bloodstream infection sepsis using single-cell RNA sequencing.

Background: Klebsiella pneumoniae is a common Gram-negative bacterium. Blood infection caused by K. pneumoniae is one of the most common causes of human sepsis, which seriously threatens the life of patients. The immune status of peripheral blood mononuclear cells (PBMCs) based on single-cell RNA sequencing (scRNA-seq) in acute stage and recovery stage of sepsis caused by K. pneumoniae bloodstream infection has not been studied. Methods: A total of 13 subjects were included in this study, 3 healthy controls, 7 patients with K. pneumoniae bloodstream infection in the acute stage (4 patients died), and 3 patients in the recovery stage. Peripheral blood of all patients was collected and PBMCs were isolated for scRNA-seq analysis. We studied the changes of PBMCs components, signaling pathways, differential genes, and cytokines in acute and recovery stages. Results: During K. pneumoniae acute infection we observed a decrease in the proportion of T cells, most probably due to apoptosis and the function of T cell subtypes was disorder. The proportion of monocytes increased in acute stage. Although genes related to their phagocytosis function were upregulated, their antigen presentation capacity-associated genes were downregulated. The expression of IL-1ß, IL-18, IFNGR1 and IFNGR2 genes was also increased in monocytes. The proportion of DCs was depleted during the acute stage and did not recover during sepsis recovery. DCs antigen presentation was weakened during the acute stage but recovered fast during the recovery stage. pDCs response to MCP-1 chemokine was weakened, they recovered it quickly during the recovery stage. B cells showed apoptosis both in the acute stage and recovery stage. Their response to complement was weakened, but their antigen presentation function was enhanced. The proportion of NK cells stable during all disease's stages, and the expression of IFN-γ gene was upregulated. Conclusion: The proportion of PBMCs and their immune functions undergo variations throughout the course of the disease, spanning from the acute stage to recovery. These findings provide new insights into the mechanism of PBMCs immune function during K. pneumoniae bloodstream infection sepsis and recovery and sets the basis for further understanding and treatment.

Uncommon P1 Anchor-featured Viral T Cell Epitope Preference within HLA-A*2601 and HLA-A*0101 Individuals.

The individual HLA-related susceptibility to emerging viral diseases such as COVID-19 underscores the importance of understanding how HLA polymorphism influences peptide presentation and T cell recognition. Similar to HLA-A*0101, which is one of the earliest identified HLA alleles among the human population, HLA-A*2601 possesses a similar characteristic for the binding peptide and acts as a prevalent allomorph in HLA-I. In this study, we found that, compared with HLA-A*0101, HLA-A*2601 individuals exhibit distinctive features for the T cell responses to SARS-CoV-2 and influenza virus after infection and/or vaccination. The heterogeneous T cell responses can be attributed to the distinct preference of HLA-A*2601 and HLA-A*0101 to T cell epitope motifs with negative-charged residues at the P1 and P3 positions, respectively. Furthermore, we determined the crystal structures of the HLA-A*2601 complexed to four peptides derived from SARS-CoV-2 and human papillomavirus, with one structure of HLA-A*0101 for comparison. The shallow pocket C of HLA-A*2601 results in the promiscuous presentation of peptides with "switchable" bulged conformations because of the secondary anchor in the median portion. Notably, the hydrogen bond network formed between the negative-charged P1 anchors and the HLA-A*2601-specific residues lead to a "closed" conformation and solid placement for the P1 secondary anchor accommodation in pocket A. This insight sheds light on the intricate relationship between HLA I allelic allomorphs, peptide binding, and the immune response and provides valuable implications for understanding disease susceptibility and potential vaccine design.

Increase in Agricultural-Derived NHx and Decrease in Coal Combustion-Derived NOx Result in Atmospheric Particulate N-NH4+ Surpassing N-NO3- in the South China Sea.

The atmospheric deposition of anthropogenic active nitrogen significantly influences marine primary productivity and contributes to eutrophication. The form of nitrogen deposition has been evolving annually, alongside changes in human activities. A disparity arises between observation results and simulation conclusions due to the limited field observation and research in the ocean. To address this gap, our study undertook three field cruises in the South China Sea in 2021, the largest marginal sea of China. The objective was to investigate the latest atmospheric particulate inorganic nitrogen deposition pattern and changes in nitrogen sources, employing nitrogen-stable isotopes of nitrate (δ15N-NO3-) and ammonia (δ15N-NH4+) linked to a mixing model. The findings reveal that the N-NH4+ deposition generally surpasses N-NO3- deposition, attributed to a decline in the level of NOx emission from coal combustion and an upswing in the level of NHx emission from agricultural sources. The disparity in deposition between N-NH4+ and N-NO3- intensifies from the coast to the offshore, establishing N-NH4+ as the primary contributor to oceanic nitrogen deposition, particularly in ocean background regions. Fertilizer (33 ± 21%) and livestock (20 ± 6%) emerge as the primary sources of N-NH4+. While coal combustion continues to be a significant contributor to marine atmospheric N-NO3-, its proportion has diminished to 22 (Northern Coast)-35% (background area) due to effective NOx emission controls by the countries surrounding the South China Sea, especially the Chinese Government. As coal combustion's contribution dwindles, the significance of vessel and marine biogenic emissions grows. The daytime higher atmospheric N-NO3- concentration and lower δ15N-NO3- compared with nighttime further underscore the substantial role of marine biogenic emissions.

Development of injectable in situ hydrogels based on hyaluronic acid via Diels-Alder reaction for their antitumor activities studies.

The objective of this study was to develop an injectable hydrogel based on furfuryl amine-conjugated hyaluronic acid (FA-conj-HA) and evaluate the in vivo anti-4 T1 tumor activity of doxorubicin-loaded hydrogel (DOX@FA-conj-HAgel). The cargo-free hydrogel (FA-conj-HAgel) was fabricated through a Diels-Alder reaction at 37 °C with FA-conj-HA as a gel material and four armed poly(ethylene glycol)2000-maleimide (4-arm-PEG2000-Mal) as a cross-linker. The bio-safety of FA-conj-HAgel were assessed, and the in vivo antitumor activity of DOX@FA-conj-HAgel was also investigated. Many 3D network structures were observed from scanning electron microscope (SEM) photograph, confirming the successful preparation of FA-conj-HAgel. The absence of cytotoxicity from FA-conj-HAgel was proved by the high viability of 4 T1 cells. In vivo bio-safety studies suggested that the obtained FA-conj-HAgel did not induce acute toxicity or other lesions in treated mice, confirming its high bio-safety. The reduced tumor volumes, hematoxylin-eosin staining (H&E), and TdT-mediated dUTP-biotin nick end labeling (TUNEL) analysis indicated the potent in vivo anti-4 T1 tumor effects of DOX@FA-conj-HAgel. In conclusion, the favorable bio-safety and potent antitumor activity of DOX@FA-conj-HAgel highlighted its potential application in oncological therapy.

Evaluation of Trace Elements Levels and Construction of Auxiliary Prediction Model in Patients with Diabetes Ketoacidosis in Type 1 Diabetes.

Background: Trace elements play an important role in reflecting physical metabolic status, but have been rarely evaluated in diabetes ketoacidosis (DKA). Since clinical biochemical parameters are the first-line diagnostic data mastered by clinical doctors and DKA has a rapid progression, it is crucial to fully utilize clinical data and combine innovative parameters to assist in assessing disease progression. The aim of this study was to evaluate the levels of trace elements in DKA patients, followed by construction of predictive models combined with the laboratory parameters. Methods: A total of 96 T1D individuals (48 DKA patients) were collected from the First Hospital of Jilin University. Serum calcium (Ca), magnesium (Mg), zinc (Zn), copper (Cu), iron (Fe) and selenium (Se) were measured by Inductively Coupled Plasma Mass Spectrometry, and the data of biochemical parameters were collected from the laboratory information system. Training and validation sets were used to construct the model and examine the efficiency of the model. The lambda-mu-sigma method was used to evaluate the changes in the model prediction efficiency as the severity of the patient's condition increases. Results: Lower levels of serum Mg, Ca and Zn, but higher levels of serum Fe, Cu and Se were found in DKA patients. Low levels of total protein (TP), Zn and high levels of lipase would be an efficient combination for the prediction of DKA (Area under curves for training set and validation set were 0.867 and 0.961, respectively). The examination test confirmed the clinical applicability of the constructed models. The increasing predictive efficiency of the model was found with NACP. Conclusion: More severe oxidative stress in DKA led to further imbalance of trace elements. The combination of TP, lipase and Zn could predict DKA efficiently, which would benefit the early identification and prevention of DKA to improve prognosis.

Exploring temporal trends and influencing factors for thyroid cancer in Guangzhou, China: 2004-2018.

PURPOSE: Describe and analyze the trends of thyroid cancer incidence and mortality in Guangzhou, explore the potential influencing factors, and provide evidence for the government to formulate prevention and treatment measures. METHODS: Incident and death cases of thyroid cancer were retrieved from the Guangzhou cancer registry. The joinpoint regression models were used to estimate the incidence and mortality trends. Age-period-cohort models were used to estimate the age, period, and cohort effects on the time trends. Grey correlation analysis was performed to explore possible connections between thyroid cancer and social factors. RESULTS: A total of 15,955 new cases of thyroid cancer were registered in Guangzhou during 2004-2018, the age-standardized incidence rate (ASIR) of thyroid cancer increased from 4.29/105 in 2004 to 22.36/105 in 2018, with the average annual percentage change (AAPC) of 13.40%. The overall increase can be attributed to the increase in the incidence of papillary thyroid carcinoma (PTC), which was dominated by tumors <2 cm. The ASIR was higher in women (16.12/105) compared to men (5.46/105), and young and middle-aged individuals had higher incidence rates than older people. The number of thyroid cancer deaths registered between 2010 and 2018 was 356, and the age-standardized mortality rates (ASMRs) were stable (approximately 0.42/105). Men's ASMR (0.34/105) and women's (0.49/105) were similar, and those 60 and older had greater mortality. The period and cohort relative risks showed an overall increasing trend. Furthermore, there was a strong positive correlation between the ASIRs and social determinants. CONCLUSIONS: During the study period, the incidence rate of thyroid cancer among young and middle-aged people in Guangzhou showed a rapidly increasing trend, and the mortality was relatively stable. In the future, more effective preventive measures should be taken for this age group to reduce the burden of disease and avoid overdiagnosis.

Rice seed vigor detection based on near-infrared hyperspectral imaging and deep transfer learning.

Vigor is one of the important factors that affects rice yield and quality. Rapid and accurate detection of rice seed vigor is of great importance for rice production. In this study, near-infrared hyperspectral imaging technique and transfer learning were combined to detect rice seed vigor. Four varieties of artificial-aged rice seeds (Yongyou12, Yongyou1540, Suxiangjing100, and Longjingyou1212) were studied. Different convolutional neural network (CNN) models were built to detect the vigor of the rice seeds. Two transfer strategies, fine-tuning and MixStyle, were used to transfer knowledge among different rice varieties for vigor detection. The experimental results showed that the convolutional neural network model of Yongyou12 classified the vigor of Yongyou1540, Suxiangjing100, and Longjingyou1212 through MixStyle transfer knowledge, and the accuracy reached 90.00%, 80.33%, and 85.00% in validation sets, respectively, which was better or close to the initial modeling performances of each variety. MixStyle statistics are based on probabilistic mixed instance-level features of cross-source domain training samples. When training instances, new domains can be synthesized, which increases the domain diversity of the source domain, thereby improving the generalization ability of the trained model. This study would help rapid and accurate detection of a large varieties of crop seeds.

Marine biomaterials in biomedical nano/micro-systems.

Marine resources in unique marine environments provide abundant, cost-effective natural biomaterials with distinct structures, compositions, and biological activities compared to terrestrial species. These marine-derived raw materials, including polysaccharides, natural protein components, fatty acids, and marine minerals, etc., have shown great potential in preparing, stabilizing, or modifying multifunctional nano-/micro-systems and are widely applied in drug delivery, theragnostic, tissue engineering, etc. This review provides a comprehensive summary of the most current marine biomaterial-based nano-/micro-systems developed over the past three years, primarily focusing on therapeutic delivery studies and highlighting their potential to cure a variety of diseases. Specifically, we first provided a detailed introduction to the physicochemical characteristics and biological activities of natural marine biocomponents in their raw state. Furthermore, the assembly processes, potential functionalities of each building block, and a thorough evaluation of the pharmacokinetics and pharmacodynamics of advanced marine biomaterial-based systems and their effects on molecular pathophysiological processes were fully elucidated. Finally, a list of unresolved issues and pivotal challenges of marine-derived biomaterials applications, such as standardized distinction of raw materials, long-term biosafety in vivo, the feasibility of scale-up, etc., was presented. This review is expected to serve as a roadmap for fundamental research and facilitate the rational design of marine biomaterials for diverse emerging applications.

Cerebrospinal fluid proteomics in meningitis patients with reactivated varicella zoster virus.

OBJECTIVE: This study investigated the proteomic characteristics of cerebrospinal fluid (CSF) in patients with varicella zoster virus (VZV) meningitis to understanding the pathogenesis of central nervous system (CNS) infection by reactivated VZV. METHOD: We used data-independent acquisition model to analyze the CSF proteomic differences of 28 patients with VZV meningitis and 11 herpes zoster (HZ) patients. According to the clinical manifestations at discharge, 28 VZV meningitis patients were divided into favorable outcome group and unfavorable outcome (UO) group and their differences in CSF proteome were also analyzed. RESULTS: Compared with the HZ group, the proteins (CXCL10, ELANE, IL-1RN, MPO, PRTN3, etc.) related to inflammation and immune cell activation were significantly upregulated in the VZV meningitis group (p < .01). The protein related to the nerve function and energy metabolism (CKMT1B, SLITRK3, Synaptotagmin-3, KIF5B, etc.) were significantly downregulated (p < .05). The levels of a pro-inflammatory factor, IL-18, in CSF were significantly higher in patients in the UO group as compared to patients with favorable prognosis (p < .05). CONCLUSION: Inflammatory immune response is an important pathophysiological mechanism of CNS infection by VZV, and the CSF IL-18 levels might be a potential prognostic indicator of the outcomes of VZV meningitis.

Predicting Breast Cancer Subtypes Using Magnetic Resonance Imaging Based Radiomics With Automatic Segmentation.

OBJECTIVE: The aim of the study is to demonstrate whether radiomics based on an automatic segmentation method is feasible for predicting molecular subtypes. METHODS: This retrospective study included 516 patients with confirmed breast cancer. An automatic segmentation-3-dimensional UNet-based Convolutional Neural Networks, trained on our in-house data set-was applied to segment the regions of interest. A set of 1316 radiomics features per region of interest was extracted. Eighteen cross-combination radiomics methods-with 6 feature selection methods and 3 classifiers-were used for model selection. Model classification performance was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RESULTS: The average dice similarity coefficient value of the automatic segmentation was 0.89. The radiomics models were predictive of 4 molecular subtypes with the best average: AUC = 0.8623, accuracy = 0.6596, sensitivity = 0.6383, and specificity = 0.8775. For luminal versus nonluminal subtypes, AUC = 0.8788 (95% confidence interval [CI], 0.8505-0.9071), accuracy = 0.7756, sensitivity = 0.7973, and specificity = 0.7466. For human epidermal growth factor receptor 2 (HER2)-enriched versus non-HER2-enriched subtypes, AUC = 0.8676 (95% CI, 0.8370-0.8982), accuracy = 0.7737, sensitivity = 0.8859, and specificity = 0.7283. For triple-negative breast cancer versus non-triple-negative breast cancer subtypes, AUC = 0.9335 (95% CI, 0.9027-0.9643), accuracy = 0.9110, sensitivity = 0.4444, and specificity = 0.9865. CONCLUSIONS: Radiomics based on automatic segmentation of magnetic resonance imaging can predict breast cancer of 4 molecular subtypes noninvasively and is potentially applicable in large samples.

Isotopic comparison of ammonium between two summertime field campaigns in 2013 and 2021 at a background site of North China.

Ammonia (NH3) is the primary atmospheric alkaline gas, playing a crucial role in the atmospheric chemistry. Recently, non-agricultural emissions have been identified as the dominant sources of NH3 in urban areas. However, few studies have quantified the contributions of different sources to regional NH3. This study conducted two summertime field observations in 2013 and 2021 at a background site of North China to comprehensively explore the regional variations in concentration, nitrogen isotope composition (δ15N), and sources of ammonium (NH4+). The results indicate that NHx (NHx = NH3 + NH4+) concentration has increased in 2021, but the fNH4+ (NH4+/ NHx) has decreased significantly. The δ15N-NH4+ values show a significant increase, ranging from -4.7 ± 8.1 ‰ to +12.0 ± 2.4 ‰. The increase can be attributed to two primary factors: changes in fNH4+ resulting from the reduction of atmospheric acid gases and alterations in the sources of NH3. Bayesian simulation analysis reveals substantial variations in NH3 sources between 2013 and 2021 observations. Non-agricultural sources have significantly increased their contribution to NHx concentration, with vehicle exhaust and NH3 slip experiencing growth rates of 187 % and 104 %, respectively. Our results confirm the dominate contribution of non-agricultural sources to regional NH3 at the present stage and propose relevant mitigation strategies, which would provide essential insights for reducing NH3 emissions in North China.

Synthesis of the pH-sensitive nanoparticles based on the acylhydrazone bonds conjugated doxorubicin and studies on their in vivo anti-tumor effects.

The purpose of this study was to synthesize DHPD polymers through the conjugation of doxorubicin (DOX) molecules onto poly(ethylene glycol) (PEG) chains via acylhydrazone bonds, and to fabricate pH-responsive DHPD nanoparticles (NPs) for investigation of their biosecurity and in vivo anti-tumor activity. The morphology, size distribution, stability, pH-responsiveness, biosecurity, and in vivo anti-tumor effects of the DHPD NPs were evaluated. Characterization of the DHPD polymers using 1H NMR, FTIR, and Raman spectra confirmed their successful synthesis. The DHPD NPs exhibited a round morphology with an average diameter of 144.4 ± 1.7 nm and a polydispersity index (PDI) of 0.23 ± 0.02. Biosecurity studies indicated that the DHPD NPs were non-toxic to treated mice, and in vitro cell tests demonstrated their ability to be taken up by 4T1 cells. Under the acidic microenvironment of 4T1 cells, the acylhydrazone bonds were cleaved, resulting in increased DOX delivery to tumor cells and improved in vivo anti-tumor effects. Animal experiments confirmed that the DHPD NPs reduced DOX toxicity while enhancing its anti-tumor activity. Furthermore, results from the analysis of γ-interferon (INF-γ), tumor necrosis factor-α (TNF-α), epidermal growth factor (EGF), and vascular endothelial growth factor (VEGF) indicated that the DHPD NPs improved the anti-4T1 tumor effect of DOX, suggesting their potential application in the treatment of breast cancer.

Transcriptome sequencing and experiments reveal the effect of formyl peptide receptor 2 on liver homeostasis.

BACKGROUND: Formyl peptide receptor 2 (Fpr2) is an important receptor in host resistance to bacterial infections. In previous studies, we found that the liver of Fpr2-/- mice is the most severely damaged target organ in bloodstream infections, although the reason for this is unclear. AIM: To investigate the role of Fpr2 in liver homeostasis and host resistance to bacterial infections. METHODS: Transcriptome sequencing was performed on the livers of Fpr2-/- and wild-type (WT) mice. Differentially expressed genes (DEGs) were identified in the Fpr2-/- and WT mice, and the biological functions of DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) en-richment analysis. Quantitative real time-polymerase chain reaction (qRT-PCR) and western blot (WB) analyses were used to further validate the expression levels of differential genes. Cell counting kit-8 assay was employed to investigate cell survival. The cell cycle detection kit was used to measure the distribution of cell cycles. The Luminex assay was used to analyze cytokine levels in the liver. The serum biochemical indices and the number of neutrophils in the liver were measured, and hepatic histopathological analysis was performed. RESULTS: Compared with the WT group, 445 DEGs, including 325 upregulated genes and 120 downregulated genes, were identified in the liver of Fpr2-/- mice. The enrichment analysis using GO and KEGG showed that these DEGs were mainly related to cell cycle. The qRT-PCR analysis confirmed that several key genes (CycA, CycB1, Cdc20, Cdc25c, and Cdk1) involved in the cell cycle had significant changes. The WB analysis confirmed a decrease in the expression of CDK1 protein. WRW4 (an antagonist of Fpr2) could inhibit the proliferation of HepG2 cells in a concentration dependent manner, with an increase in the number of cells in the G0/G1 phase, and a decrease in the number of cells in the S phase. Serum alanine aminotransferase levels increased in Fpr2-/- mice. The Luminex assay measurements showed that interleukin (IL)-10 and chemokine (C-X-C motif) ligand (CXCL)-1 levels were significantly reduced in the liver of Fpr2-/- mice. There was no difference in the number of neutrophils, serum C-reactive protein levels, and liver pathology between WT and Fpr2-/- mice. CONCLUSION: Fpr2 participates in the regulation of cell cycle and cell proliferation, and affects the expression of IL-10 and CXCL-1, thus playing an important protective role in maintaining liver homeostasis.

Intelligent Vehicle Path Tracking Control Method Based on Curvature Optimisation.

In this study, an intelligent vehicle (IV) path tracking control method based on curvature optimisation is proposed to reduce the comprehensive performance conflict of the system. This system conflict is caused by the mutual restriction between the path tracking accuracy and the body stability during the movement of the intelligent automobile. First, the working principle of the new IV path tracking control algorithm is briefly introduced. Then, a three-degrees-of-freedom vehicle dynamics model and a preview error model considering vehicle roll are established. In addition, a path tracking control method based on curvature optimisation is designed to solve the deterioration of vehicle stability even when the path tracking accuracy of the IV is improved. Finally, the effectiveness of the IV path tracking control system is validated through simulations and the Hardware in the Loop (HIL) test with various conditions forms. Results clearly show that the optimisation amplitude of the IV lateral deviation is up to 84.10%, and the stability is improved by approximately 2% under the vx = 10 m/s and ρ = 0.15 m-1 condition; the optimisation amplitude of the lateral deviation is up to 66.80%, and the stability is improved by approximately 4% under the vx = 10 m/s and ρ = 0.2 m-1 condition; the body stability is improved by 20-30% under the vx = 15 m/s and ρ = 0.15 m-1 condition, and the boundary conditions of body stability are triggered. The curvature optimisation controller can effectively improve the tracking accuracy of the fuzzy sliding mode controller. The body stability constraint can also ensure the smooth running of the vehicle in the optimisation process.

TNF-α activates RELA expression via TNFRSF1B to upregulate OPA1 expression and inhibit chondrogenic differentiation of human adipose stem cells.

BACKGROUND: Tumor necrosis factor-alpha (TNF-α), one of the pro-inflammatory cytokines mediating the local inflammatory process in joints, inhibits cartilage formation and has a detrimental effect on stem cell-based cartilage regeneration for the treatment of osteoarthritis (OA). However, the mechanisms behind this inhibitory effect are still poorly understood. Mitochondrial morphological changes mediated by mitochondrial fusion and fission are highly plastic, are quite sensitive to environmental stimuli and play a crucial role in maintaining cell structure and function. In our study, chondrogenic differentiated human adipose stem cells (hADSCs) were exposed to TNF-α and the effect of TNF-α on the ability of hADSCs to chondrogenic differentiate and on mitochondrial fusion and fission was observed and analyzed. The aim was to investigate the role and mechanisms of mitochondrial fusion and fission regulation in the chondrogenic differentiation of hADSCs under normal conditions and under exposure to TNF-α. METHODS: We used flow cytometry to identify hADSCs immunophenotypes CD29, CD44, CD34, CD45, and HLA-DR. Alcian blue staining and Sirius red staining were used to observe the formation of proteoglycans and collagen during the chondrogenic differentiation of hADSCs, respectively. The mRNA and protein expression levels of the cartilage formation marker SOX9, type II collagen (COL2A1), and Aggrecan were measured by real-time fluorescent quantitative PCR (RT-qPCR) and western blot, respectively. The fluorescent probes MitoTracker® Red CMXRos and JC-1 were used to visualize mitochondria morphology and detect mitochondrial membrane electricity (MMP). Affymetrix PrimeView™ chips were used for gene expression profiling. RESULTS: The results showed that the chondrogenic differentiation of hADSCs was inhibited in the presence of TNF-α that optic atrophy 1 (OPA1) expression was significantly upregulated and mitochondria were prolonged and interconnected during this process. Gene microarray and RT-qPCR data showed that the presence of TNF-α led to increased expression of TNFα receptor 2 (TNFRSF1B) and RELA during chondrogenic differentiation of hADSCs. CONCLUSIONS: TNF-α inhibits chondrogenic differentiation of human adipose stem cells by activating RELA expression through TNFRSF1B upregulating OPA1 expression thereby increasing mitochondrial fusion.

Gelatin nanofiber-reinforced decellularized amniotic membrane promotes axon regeneration and functional recovery in the surgical treatment of peripheral nerve injury.

Effective recovery of peripheral nerve injury (PNI) after surgical treatment relies on promoting axon regeneration and minimizing the fibrotic response. Decellularized amniotic membrane (dAM) has unique features as a natural matrix for promoting PNI repair due to its pro-regenerative extracellular matrix (ECM) structure and anti-inflammatory properties. However, the fragile nature and rapid degradation rate of dAM limit its widespread use in PNI surgery. Here we report an engineered composite membrane for PNI repair by combining dAM with gelatin (Gel) nanofiber membrane to construct a Gel nanofiber-dAM composite membrane (Gel-dAM) through interfacial bonding. The Gel-dAM showed enhanced mechanical properties and reduced degradation rate, while retaining maximal bioactivity and biocompatibility of dAM. These factors led to improved axon regeneration, reduced fibrotic response, and better functional recovery in PNI repair. As a fully natural materials-derived off-the-shelf matrix, Gel-dAM exhibits superior clinical translational potential for the surgical treatment of PNI.