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Abstract Asthma is a complex chronic respiratory inflammatory disease affected by both genetic and environmental factors. Therefore, our study explored the influence of TRIM11 on asthma and its underlying mechanisms. Our research involved patients diagnosed with asthma and healthy volunteers recruited from our hospital. We observed a reduction in serum TRIM11 expression in asthma patients, which positively correlated with the levels of anti-IgE or IgE. Additionally, both TRIM11 mRNA and protein expression in lung tissue were diminished. The introduction of the TRIM11 gene resulted in a reduction in inflammation in an in vitro asthma model and prevented the development of asthma in a mouse model. Moreover, the TRIM11 gene exhibited a suppressive effect on Ferroptosis and mitigated ROS-induced mitochondrial damage in the asthma model. TRIM11 was found to stimulate UBE2N-TAX1BP1 signaling in the asthma model, with UBE2N being identified as the specific target for TRIM11’s effects on Ferroptosis. Furthermore, TRIM11 protein interacted with UBE2N protein and facilitated the dissociation of UBE2N-UBE2N in the asthma model. In conclusion, TRIM11 plays a vital role in preventing Ferroptosis in the asthma model through UBE2N-TAX1BP1 signaling. This indicates that targeting the TRIM11 mechanism could serve as a promising strategy for anti-Ferroptosis immunotherapy in asthma treatment.

Abstract The main cause of gastric cancer (GC)-related death is due to malignant cell unregulated distant metastasis and proliferation. Heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) has been shown to play an important role in carcinogenesis and the development of metastasis in several tumors. However, its downstream regulatory mechanism in GC is not well defined. Our study aims to investigate the function and regulatory mechanism of hnRNPA1 in GC. We analyzed the differential expression of hnRNPA1 in gastric cancer and paired adjacent normal tissues in the TCGA database. Kaplan-Meier analysis was employed for survival assessment. The expressions of hnRNPA1 in GC cells were measured by qRT-PCR and Western blot. Transwell assay, CCK8 and colony formation assay were used to detect the effect of hnRNPA1 on the metastasis and proliferation ability of GC cells. Additionally, Western blotting was performed to examine the expression of proteins related to the Wnt/β-catenin signaling pathway as well as epithelial-mesenchymal transition (EMT), while further investigations were carried out to explore potential regulatory mechanisms. The results showed that hnRNPA1 was highly expressed differentially in GC over normal gastric tissue. Knocking down hnRNPA1 inhibited the metastasis and proliferation of human gastric cancer cells. Overexpression of hnRNPA1 significantly enhanced the metastatic potential and proliferative capacity of human GC cells. Further mechanism exploration revealed that knocking down hnRNPA1 inhibited the Wnt/β-catenin signaling pathway and WNT1 inducible signaling pathway protein-2 (WISP2), an activator of the Wnt/β-catenin signaling pathway. Whereas overexpression of hnRNPA1 had the opposite effects. Our results demonstrated that hnRNPA1 promoted metastasis and proliferation of GC cells by activating Wnt/β-catenin signaling pathway via WISP2. hnRNPA1 may serve as a potential biomarker and novel therapeutic targets for GC.

We propose a malaria model involving the sensitive and resistant strains, which is described by reaction-diffusion equations. The model reflects the scenario that the vector and host populations disperse with distinct diffusion rates, susceptible individuals or vectors cannot be infected by both strains simultaneously, and the vector population satisfies the logistic growth. Our main purpose is to get a threshold type result on the model, especially the interaction effect of the two strains in the presence of spatial structure. To solve this issue, the basic reproduction number (BRN) R0i and invasion reproduction number (IRN) Rˆ0i of each strain (i = 1 and 2 are for the sensitive and resistant strains, respectively) are defined. Furthermore, we investigate the influence of the diffusion rates of populations and vectors on BRNs and IRNs.

Abstract The complex anatomy and biology of craniofacial bones pose difficulties in their effective and precise reconstruction. Injectable hydrogels (IHs) with water-swollen networks are emerging as a shape-adaptive alternative for noninvasively rebuilding craniofacial bones. The advent of versatile nanomaterials (NMs) customizes IHs with strengthened mechanical properties and therapeutically favorable performance, presenting excellent contenders over traditional substitutes. Structurally, NM-reinforced IHs are energy dissipative and covalently crosslinked, providing the mechanics necessary to support craniofacial structures and physiological functions. Biofunctionally, incorporating unique NMs into IH expands a plethora of biological activities, including immunomodulatory, osteogenic, angiogenic, and antibacterial effects, further favoring controllable dynamic tissue regeneration. Mechanistically, NM-engineered IHs optimize the physical traits to direct cell responses, regulate intracellular signaling pathways, and control the release of biomolecules, collectively bestowing structure-induced features and multifunctionality. By encompassing state-of-the-art advances in NM-integrated IHs, this review offers a foundation for future clinical translation of craniofacial bone reconstruction.

Abstract. Background:. Copper and zinc are involved in the development of multiple malignancies; yet, epidemiological evidence on hepatocellular carcinoma (HCC) is limited. This study aimed to investigate the association between dietary intake and serum levels of copper and zinc with the risk of HCC. Methods:. A total of 434 case-control pairs matched for sex and age (±1 year) were included in this study. Cases with newly diagnosed HCC were from the Guangdong Liver Cancer Cohort (GLCC) study, and healthy controls were from the Guangzhou Nutrition and Health Study (GNHS). A semi-quantitative 79-item food frequency questionnaire (FFQ) was used to assess habitual dietary intakes of copper and zinc. Serum levels of copper and zinc were measured by using inductively coupled plasma mass spectrometry. The copper (Cu)/ zinc (Zn) ratio was computed by dividing copper levels by zinc levels. Conditional logistic regression models were performed to calculate the odds ratio (OR) and 95% confidence intervals (CI) for per 1 standard deviation increase (per-SD increase) in copper and zinc levels. Results:. Higher dietary intake (ORper-SD increase = 0.65, 95% CI: 0.44, 0.96, Ptrend = 0.029) and serum levels of zinc (ORper-SD increase = 0.11, 95% CI: 0.04, 0.30, Ptrend

This research was conducted to examine the impact of Wei Qi Booster (WQB) on immune parameters and anti-oxidative function in aged mice. Fifty aged mice were randomly assigned to five different groups. Group A was designated as the control group. Mice in Group B were receiving Levamisole at 10 mg/kg body weight. Each mouse in groups C, D and E received 0.1, 1, and 2% WQB, respectively. Another ten young mice, designated as group F, were fed regularly. The mice were fed according to the above methods for 28 days. Results showed that relative to the control group, the body weight and immune organs indexes experienced a substantial rise in the group with 1% WQB. In addition, 1% WQB could improve the activity of SOD and reduce the MDA levels. Expressions of CD4 and sIgA increased while CD8 decreased in the jejunum of aged mice treated with WQB. IL2 and IFN-γ levels increased in the 1% WQB group, showing no notable difference compared to the young mice group. The results demonstrated that WQB can elevate immune levels and enhance anti-oxidative functions in aged mice.

Abstract Background Distant metastasis is the major cause of lung adenocarcinoma (LUAD)-associated mortality. However, molecular mechanisms involved in LUAD metastasis remain to be fully understood. While the role of long non-coding RNAs (lncRNAs) in cancer development, progression, and treatment resistance is being increasingly appreciated, the list of dysregulated lncRNAs that contribute to LUAD pathogenesis is also rapidly expanding. Methods Bioinformatics analysis was conducted to interrogate publicly available LUAD datasets. In situ hybridization and qRT-PCR assays were used to test lncRNA expression in human LUAD tissues and cell lines, respectively. Wound healing as well as transwell migration and invasion assays were employed to examine LUAD cell migration and invasion in vitro. LUAD metastasis was examined using mouse models in vivo. RNA pulldown and RNA immunoprecipitation were carried out to test RNA–protein associations. Cycloheximide-chase assays were performed to monitor protein turnover rates and Western blotting was employed to test protein expression. Results The expression of the lncRNA LINC01559 was commonly upregulated in LUADs, in particular, in those with distant metastasis. High LINC01559 expression was associated with poor outcome of LUAD patients and was potentially an independent prognostic factor. Knockdown of LINC01559 diminished the potential of LUAD cell migration and invasion in vitro and reduced the formation of LUAD metastatic lesions in vivo. Mechanistically, LINC01559 binds to vimentin and prevents its ubiquitination and proteasomal degradation, leading to promotion of LUAD cell migration, invasion, and metastasis. Conclusion LINC01559 plays an important role in LUAD metastasis through stabilizing vimentin. The expression of LINC01559 is potentially an independent prognostic factor of LUAD patients, and LINC01559 targeting may represent a novel avenue for the treatment of late-stage LUAD.

Abstract Potassium‐ion batteries (PIBs) have garnered significant attention as a promising alternative to commercial lithium‐ion batteries (LIBs) due to abundant and cost‐efficient potassium reserves. However, the large size of potassium ions and the resulting sluggish reaction kinetics present major obstacles to the widespread use of PIBs. Herein, we present a simple method to ingeniously encapsulate SnS2 nanoparticles within sulfurized polyacrylonitrile (SPAN) fibers (SnS2@SPAN) for serving as a high‐performance PIB anode. The large interlayer spacing of SnS2 provides a fast transport channel for potassium ions during charge–discharge cycles, while the one‐dimensional SPAN skeleton offers massive binding sites and shortens the diffusion path for potassium ions, facilitating faster reaction kinetics. Additionally, the excellent ductility of SPAN can effectively accommodate the large volume changes that occur in SnS2 upon potassium‐ion insertion, thereby enhancing the cyclic stability of SnS2. Benefiting from the above advantages, the SnS2@SPAN composites exhibit impressive cyclability over 500 cycles at 4 A g−1, with a capacity retention rate close to 100%. This study provides an effective approach for stabilizing high‐capacity PIB anode materials with large volume variations.

The proposed method involves the utilization of a strip roll-forming technique to fulfill the specific requirements for constructing large-scale structures in orbit and space station trusses during extraterrestrial exploration. This involves progressively rolling out a metal strip with an L+V-shaped locking edge through multiple passes of forming rolls featuring different section shapes. The process of helical locking enables the formation of a slender, spiral-shaped tube, which can be utilized for the in-orbit assembly of exceptionally large structures. The proposed approach introduces a two-step optimization method to enhance the maximum stress, equivalent plastic strain, and wrapping torque of roll-forming L+V cross-sections and wrap-forming helical tubes. The optimized sample points in the second step are established based on the optimal roll distance and roll gap obtained in the first optimal step, resulting in the determination of the optimal folding height and V-shaped angle of the L+V strip cross-section after optimization. The design of the strip wrapping configuration that follows is highly dependent on these four parameters.

The automatic recognition and quantitative analysis of abnormal behavior in mice play a crucial role in behavioral observation experiments in neuroscience, pharmacology, and toxicology. Due to the challenging definition of abnormal behavior and difficulty in collecting training samples, directly applying behavior recognition methods to identify abnormal behavior is often infeasible. This paper proposes ABNet, an AI-empowered abnormal action recognition approach for mice. ABNet utilizes an enhanced Spatio-Temporal Graph Convolutional Network (ST-GCN) as an encoder; ST-GCN combines graph convolution and temporal convolution to efficiently capture and analyze spatio-temporal dynamic features in graph-structured data, making it suitable for complex tasks such as action recognition and traffic prediction. ABNet trains the encoding network with normal behavior samples, then employs unsupervised clustering to identify abnormal behavior in mice. Compared to the original ST-GCN network, the method significantly enhances the capabilities of feature extraction and encoding. We conduct comprehensive experiments on the Kinetics-Skeleton dataset and the mouse behavior dataset to evaluate and validate the performance of ABNet in behavior recognition and abnormal motion detection. In the behavior recognition experiments conducted on the Kinetics-Skeleton dataset, ABNet achieves an accuracy of 32.7% for the top one and 55.2% for the top five. Moreover, in the abnormal behavior analysis experiments conducted on the mouse behavior dataset, ABNet achieves an average accuracy of 83.1%.

By using a scaffold hopping/ring equivalent and intermediate derivatization strategies, a series of compounds of 2,5-diphenyl-1,3-oxazoline with substituent changes at the 5-phenyl position were prepared, and their acaricidal activity was studied. However, the synthesized 2,5-diphenyl-1,3-oxazolines showed lower activity against mite eggs and larvae compared to the 2,4-diphenyl-1,3-oxazolines with the same substituents. We speculate that there is a significant difference in the spatial extension direction of the substituents between the two skeletons of compounds, resulting in differences in their ability to bind to the potential target chitin synthase 1. This work is helpful in inferring the internal structure of chitin synthase binding pockets.

This study introduces RTEEMF (Real-Time Evaluation Electromagnetic Field)-PhoneAnts, a novel Deep Learning (DL) framework for the efficient evaluation of mobile phone antenna performance, addressing the time-consuming nature of traditional full-wave numerical simulations. The DL model, built on convolutional neural networks, uses the Near-field Electromagnetic Field (NEMF) distribution of a mobile phone antenna in free space to predict the Effective Isotropic Radiated Power (EIRP), Total Radiated Power (TRP), and Specific Absorption Rate (SAR) across various configurations. By converting antenna features and internal mobile phone components into near-field EMF distributions within a Huygens’ box, the model simplifies its input. A dataset of 7000 mobile phone models was used for training and evaluation. The model’s accuracy is validated using the Wilcoxon Signed Rank Test (WSR) for SAR and TRP, and the Feature Selection Validation Method (FSV) for EIRP. The proposed model achieves remarkable computational efficiency, approximately 2000-fold faster than full-wave simulations, and demonstrates generalization capabilities for different antenna types, various frequencies, and antenna positions. This makes it a valuable tool for practical research and development (R&D), offering a promising alternative to traditional electromagnetic field simulations. The study is publicly available on GitHub for further development and customization. Engineers can customize the model using their own datasets.

Abstract The indiscriminate utilization of nondegradable polyethylene terephthalate (PET)‐based products has triggered serious environmental pollution that has to be resolved vigorously. A simple synthesis of N‐doped carbon nanotubes from recycled PET (NCNTsr‐PET) was developed by a nitric acid‐assisted hydrothermal method. Experimental results and theoretical calculations show that the intrinsic defects in CNTsr‐PET would induce N‐doping by NH3 generated from nitric acid during the hydrothermal process, thus producing the NCNTsr‐PET. The life cycle assessment proves that the developed method for N‐doped CNTs using r‐PET as the carbon source is more environmentally friendly than the conventional chemical vapor deposition using acetylene as the carbon source. As a typical application, the NCNTsr‐PET delivered an impressive sodium storage capacity with an ultralong lifespan. This work not only provides a new route to upcycling waste plastics into valuable carbonaceous materials in an ecofriendly manner, but also reveals a basic understanding of the N‐doping mechanism in carbonaceous materials.

Abstract Electrospun nanofibers (NFs) have shown excellent properties including high porosity, abundant active sites, controllable diameter, uniform and designable structure, high mechanical strength, and superior resistance to external destruction, which are ideal nanoreactors for in situ characterizations. Among various techniques, in situ transmission electron microscopy (TEM) has enabled operando observation at the atomic level due to its high temporal and spatial resolution combined with excellent sensitivity, which is of great importance for rational materials design and performance improvement. In this review, the basic knowledge of in situ TEM techniques and the advantages of electrospun nanoreactors for in situ TEM characterization are first introduced. The recent development in electrospun nanoreactors for studying the physical properties, structural evolution, phase transition, and formation mechanisms of materials using in situ TEM is then summarized. The electrochemical behaviors of carbon nanofibers (CNFs), metal/metal oxide NFs, and solid‐electrolyte interphase for different rechargeable batteries are highlighted. Finally, challenges faced by electrospun nanoreactors for in situ TEM characterization are discussed and potential solutions are proposed to advance this field.

ABSTRACTIn this work, we first modify a Lotka–Volterra predator–prey system to incorporate an opportunistic predator and weak Allee effect in prey. The prey will be extinct if the combined effect of hunting and other food resources of predator is large. Otherwise, the dynamic behaviour of the system is extremely rich. A series of bifurcations such as saddle-node bifurcation, Hopf bifurcation, and Bogdanov–Takens bifurcation can happen. The validity of the theoretical results are supported with numerical simulations.

This paper investigates the leader-following consensus of general linear singular multi-agent systems. A fully distributed adaptive event-triggered control protocol is first proposed by using the relative state estimate information between neighboring agents. Moreover, the proposed protocol does not require continuous communication between neighbors, which greatly alleviate the negative impact of communication. In addition, a novel adaptive gain is proposed, which will avoid using the Laplace of communication graph. Zeno behavior is excluded by proving that the inter-event times are lower bounded by a positive constant. Finally, a numerical simulation is proposed to verify the effectiveness and reliability of the protocol.

We incorporate the strong Allee effect and fear effect in prey into a Leslie-Gower model. The origin is an attractor, which implies that the ecological system collapses at low densities. Qualitative analysis reveals that both effects are crucial in determining the dynamical behaviors of the model. There can be different types of bifurcations such as saddle-node bifurcation, non-degenerate Hopf bifurcation with a simple limit cycle, degenerate Hopf bifurcation with multiple limit cycles, Bogdanov-Takens bifurcation, and homoclinic bifurcation.

Abstract Background The associations of multimorbidity patterns with transitions between frailty states remain unclear in older individuals. Methods We used data from the National Health and Aging Trends Study 2011–2019. Frailty was measured annually using the Fried frailty phenotype. Multimorbidity patterns at baseline were identified using latent class analysis based on 14 chronic conditions. We used the semi‐Markov multi‐state model to investigate the influences of multimorbidity characterized by condition counts and patterns on subsequent frailty transitions over follow‐ups. Results Among 9450 participants aged ≥65 years at baseline, 34.8% were non‐frail, 48.1% were pre‐frail and 17.0% were frail. Over a median follow‐up of 4.0 years, 16 880 frailty transitions were observed, with 10 527 worsening and 6353 improving. For 7675 participants with multimorbidity, four multimorbidity patterns were identified: osteoarticular pattern (62.4%), neuropsychiatric–sensory pattern (17.2%), cardiometabolic pattern (10.3%) and complex multimorbidity pattern (10.1%). Compared with no disease, multimorbidity was significantly associated with an increased risk of worsening transitions, including from non‐frail to pre‐frail (hazard ratio [HR] = 1.35; 95% confidence interval [CI] = 1.21–1.52), from non‐frail to frail (HR = 1.68; 95% CI = 1.04–2.73), from pre‐frail to frail (HR = 2.19; 95% CI = 1.66–2.90) and from pre‐frail to death (HR = 1.64; 95% CI = 1.11–2.41). Compared with the osteoarticular pattern, neuropsychiatric–sensory, cardiometabolic and complex multimorbidity patterns had a significantly higher risk of worsening frailty (all P

In recent years, with the rapid development of medicine, pathology, toxicology, and neuroscience technology, animal behavior research has become essential in modern life science research. However, the current mainstream commercial animal behavior recognition tools only provide a single behavior recognition method, limiting the expansion of algorithms and how researchers interact with experimental data. To address this issue, we propose an AI-enabled, highly usable platform for analyzing experimental animal behavior, which aims to provide better flexibility, scalability, and interactivity to make the platform more usable. Researchers can flexibly select or extend different behavior recognition algorithms for automated recognition of animal behaviors or experience more convenient human-computer interaction through natural language descriptions only. A case study at a medical laboratory where the platform was used to evaluate behavioral differences between sick and healthy animals demonstrated the high usability of the platform.

The corrosion resistance and antibacterial properties of fixed orthodontic devices are insufficient in the complex oral cavity, which delays tooth movement and causes enamel demineralization. To overcome the challenges, this research constructs a series of polydopamine-graphene oxide (PDA-GO) nanocoatings on representative NiTi archwires via self-assembly. The morphology, chemical structure, and multifunctional properties of coatings showed tunability dependent on the PDA/GO ratio. Optimized PDA-GO coatings with uniform and dense characteristics prolonged the diffusion path for the corrosive medium and reduced Ni dissolution in NiTi alloys. Meanwhile, the applied coatings endowed NiTi alloys with antibacterial activity against Streptococcus mutans due to the surface structures and inherent properties of PDA-GO. In vitro cytotoxicity tests further verified their good biocompatibility. This bio-inspired nanocomposite coating provides a practical reference for modification of dental metal surfaces to better behave in the intraoral environment.

Background: Trace elements such as copper are essential for human health. Recently the journal Nat Rev Cancer has put forward the concept of Cuproplasia, a way of promoting tumor growth through reliance on copper. We attempted to conduct a comprehensive analysis of Cuproplasia-related genes in lung adenocarcinoma (LUAD) to explore the mechanism of action of Cuproplasia-related genes in LUAD.Method: Transcriptome data and clinical information of LUAD were obtained from TCGA-LUAD and GSE31210, and prognostic models of Cuproplasia-related genes were constructed and verified by regression analysis of GSVA, WGCNA, univariate COX and lasso. The signal pathways affected by Cuproplasia-related genes were analyzed by GO, KEGG and hallmarK pathway enrichment methods. Five immunocell infiltration algorithms and IMVIGOR210 data were used to analyze immune cell content and immunotherapy outcomes in the high-low risk group.Results: In the results of WGCNA, BROWN and TURQUOISE were identified as modules closely related to Cuproplasia score. In the end, lasso regression analysis established a Cuproplasia-related signature (CRS) based on 24 genes, and the prognosis of high-risk populations was worse in TCGA-LUAD and GSE31210 datasets. The enrichment analysis showed that copper proliferation was mainly through chromosome, cell cycle, dna replication, g2m checkpoint and other pathways. Immunoinfiltration analysis showed that there were differences in the content of macrophages among the four algorithms. And IMVIGOR210 found that the lower the score, the more effective the immunotherapy was.Conclusion: The Cuproplasia related gene can be used to predict the prognosis and immunotherapy outcome of LUAD patients, and may exert its effect by affecting chromosome-related pathways and macrophages.

Abstract Orthodontic tooth movement (OTM) is biologically based on the spatiotemporal remodeling process in periodontium, the mechanisms of which remain obscure. Noncoding RNAs (ncRNAs), especially microRNAs and long noncoding RNAs, play a pivotal role in maintaining periodontal homeostasis at the transcriptional, post-transcriptional, and epigenetic levels. Under force stimuli, mechanosensitive ncRNAs with altered expression levels transduce mechanical load to modulate intracellular genes. These ncRNAs regulate the biomechanical responses of periodontium in the catabolic, anabolic, and coupling phases throughout OTM. To achieve this, down or upregulated ncRNAs actively participate in cell proliferation, differentiation, autophagy, inflammatory, immune, and neurovascular responses. This review highlights the regulatory mechanism of fine-tuning ncRNAs in periodontium remodeling during OTM, laying the foundation for safe, precise, and personalized orthodontic treatment.

Mobile cloud computing (MCC) brings rich computational resources to mobile users, network operators, and cloud computing providers. The battery capacity of mobile devices poses several complex challenges, hence it is necessary to save energy by offloading applications to the remote cloud resources, especially when the scheduling is in a dynamic mobile cloud computing environment. To make a tradeoff decision involving energy consumption, deadline, and the system load, we proposed an iterated greedy taboo-mechanism algorithm (IGTMA) to solve the above issues in MCC environment. Compared to state-of-art approaches such as Adaptive First Come First Served (AFCFS), Minimize Execution Time (MINET), and tradeoff decisions for code offloading (TRADEOFF), the simulation experiment results show that our proposed IGTMA reduces energy consumption and enhances the number of finished jobs.

Abstract Background Excessive accumulation of reactive oxygen species (ROS) has been documented as the crucial cellular mechanism of cisplatin-induced ototoxicity. However, numerous antioxidants have failed in clinical studies partly due to inefficient drug delivery to the cochlea. A drug delivery system is an attractive strategy to overcome this drawback. Methods and results In the present study, we proposed the combination of antioxidant astaxanthin (ATX) and ROS-responsive/consuming nanoparticles (PPS-NP) to combat cisplatin-induced ototoxicity. ATX-PPS-NP were constructed by the self-assembly of an amphiphilic hyperbranched polyphosphoester containing thioketal units, which scavenged ROS and disintegrate to release the encapsulated ATX. The ROS-sensitivity was confirmed by 1H nuclear magnetic resonance spectroscopy, transmission electron microscopy and an H2O2 ON/OFF stimulated model. Enhanced release profiles stimulated by H2O2 were verified in artificial perilymph, the HEI-OC1 cell line and guinea pigs. In addition, ATX-PPS-NP efficiently inhibited cisplatin-induced HEI-OC1 cell cytotoxicity and apoptosis compared with ATX or PPS-NP alone, suggesting an enhanced effect of the combination of the natural active compound ATX and ROS-consuming PPS-NP. Moreover, ATX-PPS-NP attenuated outer hair cell losses in cultured organ of Corti. In guinea pigs, NiRe-PPS-NP verified a quick penetration across the round window membrane and ATX-PPS-NP showed protective effect on spiral ganglion neurons, which further attenuated cisplatin-induced moderate hearing loss. Further studies revealed that the protective mechanisms involved decreasing excessive ROS generation, reducing inflammatory chemokine (interleukin-6) release, increasing antioxidant glutathione expression and inhibiting the mitochondrial apoptotic pathway. Conclusions Thus, this ROS-responsive nanoparticle encapsulating ATX has favorable potential in the prevention of cisplatin-induced hearing loss. Graphical Abstract

We consider a 2mth-order nonlinear p-Laplacian difference equation containing both advance and retardation. Using the critical point theory, we establish some new and weaker criteria on the existence of homoclinic solutions with mixed nonlinearities.

In this paper, we investigate the global dynamics of a viral infection model with defectively infected cells. The explicit expression of the basic reproduction number of virus is obtained by using the next generation matrix approach, where each term has a clear biological interpretation. We show that the basic reproduction number serves as a threshold parameter. The virus dies out if the basic reproduction number is not greater than unity, otherwise the virus persists and the viral load eventually approaches a positive number. The result is established by Lyapunov's direct method. Our novel arguments for the stability of the infection equilibrium not only simplify the analysis (compared with some traditional ones in the literature) but also demonstrate some correlation between the two Lyapunov functions for the infection-free and infection equilibria.

Abstract Background and project Non-alcoholic fatty liver disease (NAFLD) is viewed as the hepatic manifestation of metabolic syndrome. Methionine metabolites have been linked to metabolic syndrome and its related diseases. Whether serum methionine metabolites levels are associated with NAFLD remains unclear. The study aimed to assess the association between methionine metabolites and NAFLD. Methods This cross-sectional study included a total of 2814 individuals aged 40–75 years old. All participants underwent anthropometric measurements, laboratory tests, dietary assessment and abdominal ultrasonography. Multivariable logistic regression analysis was performed to estimate the association of methionine metabolites with NAFLD. Results Overall, 1446 with and 1368 without NAFLD were enrolled in this study. Participants with NAFLD had significantly higher serum S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH) and homocysteine (Hcy) levels, and a lower S-adenosylmethionine/S-adenosylhomocysteine (SAM/SAH) ratio than those without NAFLD (all P

This paper proposes an underground power cable dqn model that can be used for both electric machines analysis and control at or around the fundamental rated power frequencies (50Hz or 60Hz). The model can be used as an observer to estimate the cable output states. This makes the far end measurements available through estimations for long cable applications such as electrical submersible pumps and wind generations. The model can be used also in simulation analysis with accelerated simulation time. Advantages include fast computation, decoupled network, and ability to work under unbalanced supply or network conditions without requiring an interface stage, such as the Eigen vectors calculation, between the cable and electric machine models. Detailed model derivations and analyses, including balanced, unbalanced, and transient conditions, are provided. Verifying using MATLAB SIMULINK, the model has a higher accuracy in balanced and unbalanced conditions when compared to the per-phase shifted frequency analysis (SFA) model in simulations, along with one of the shortest computation times among all simulated models. For the experiment, the researchers design a test consisting of a 20 ft cable operating at 6 kHz used to emulate an equivalent 2,000 ft cable with the proposed cable model as an observer., the results prove to be accurate, with the maximum error between the measured cable output and the model output estimation at 0.12%. Therefore, the model is verified by the experiments in the same given conditions as the simulations, and it can be considered as a reference in the future.

Room-temperature sodium-sulfur batteries are promising electrochemical energy storage systems. Here, the authors proposed a Fe3N/carbon composite to regulate the polysulfides chemistry and improve the performances of sodium-sulfur cells.

The extensive application of graphene oxide (GO) nanomaterials increases the risk of their release into the environment, thus posing a threat to the human body. Multiple studies indicate that GO could lead to neurotoxicity, while the intricate biological effects of GO in astrocytes remain unclear. The autophagic disorder was considered an important part of the exposure risk of GO in the application of neuromedicine. This study explored the key regulators mediating the autophagic process in rat astroglioma-derived F98 cells caused by GO, especially the dynamic changes in the cellular physiological state over time. We identified transcription factor EB (TFEB), a critical regulator of the autophagy-lysosome pathway (ALP), as a crucial factor in GO-induced autophagy flux blockade and cell apoptosis. Specifically, the prolonged exposure to GO increased the amount of its cellular internalization, which gradually prevented TFEB from entering the nucleus, thereby leading to the subsequent ALP dysfunction and excessive cell apoptosis. Furthermore, STIP1 homology and U-Box containing protein 1 (STUB1), an E3 ubiquitin ligase, was responsible for GO-triggered TFEB dysregulation, and overexpression of STUB1 helped alleviate GO cytotoxicity. Our study highlights that impaired TFEB activity underlies compromised autophagy flux in GO-induced apoptosis and opens up new avenues for the application of GO-based nanotherapeutics with specific autophagy-regulating properties in the central nervous system.

Parabacteroides levels are reported to be low in obese individuals, and this genus has shown an anti-obesity capacity in animal studies. Nevertheless, the relationship between Parabacteroides and obesity in different subpopulations, e.g., with respect to age and sex, and its association with subsequent weight change have rarely been explored. The cross-sectional associations of Parabacteroides genus- and species-level OTU abundance with obesity were explored in the Guangdong Gut Microbiome Project (GGMP), which included 5843 adults, and replicated in the Guangzhou Nutrition and Health Study (GNSH), which included 1637 individuals. Furthermore, we assessed the prospective associations of Parabacteroides and its main OTUs’ abundance with the subsequent changes in body mass index (BMI) in the GNSH. We found that Parabacteroides was inversely associated with obesity among females and participants aged 40–69 years in the GGMP and the replicated cohort in the GNSH. After a 3-year follow-up, there was no significant correlation between Parabacteroides and the subsequent changes in BMI. However, Seq4172 (P. johnsonii) showed a negative correlation with subsequent BMI changes in the female and middle-aged (40–69 years) subpopulations. Overall, our results indicate that Parabacteroides have an inverse relationship with obesity and that Seq4172 (P. johnsonii) have a negative association with subsequent changes in BMI among females and middle-aged populations in perspective analyses.

AimTo examine the relationship of C1 metabolites of the methionine cycle with the risk of subclinical atherosclerosis (SA) in the Chinese population.MethodsA total of 2,991 participants aged 45–75 years old were included for data analyses based on the baseline data of the Guangzhou Nutrition and Health Cohort. Three core serum methionine metabolites including serum S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), and homocysteine (Hcy) were measured by UPLC-MS/MS. SA was determined by B-mode ultrasound measured carotid intima-media thickness (CIMT) at the common artery and bifurcation segments. Multivariable logistic and linear regression models were performed to estimate the associations of C1 metabolites of the methionine cycle with SA risk or CIMT.ResultsAfter controlling for potential cofounders and other C1 metabolites, in comparison with the lowest quartile, participants in the highest quartile had lower risk of SA by 27.6% (OR = 0.724; 95% CI:0.563–0.93, Ptrend = 0.007) for SAM and 32.2% (OR = 0.678; 95% CI:0.538–0.855, Ptrend < 0.001) for SAM/SAH, while increased SA risk by 27.9% (OR = 1.279; 95% CI: 1.065–1.535, Ptrend < 0.001) for SAH. No significant association was observed for Hcy with SA after further adjustment of SAH and SAM. The results of multivariable linear regression showed similar findings. The highest two standardized coefficients were observed for SAH (β = 0.104 for CCA and 0.121 for BIF, P< 0.001) and SAM/SAH (β = −0.071 for CCA and −0.084 for BIF, P< 0.001). Subgroup analyses suggested more evident associations of SAH with SA were observed in participants of higher cardiovascular risk profiles.ConclusionOur cross-sectional data showed higher serum SAH, but lower SAM/SAH were independently associated with increased risk of SA among the Chinese middle-aged and elderly population.

The present work developed an electrochemical genosensor for the detection of virulence outer membrane protein A (ompA, tDNA) gene of Cronobacter sakazakii (C. sakazakii) by exploiting the excellent glucose-oxidase-mimicking activity of copper Metal-organic frameworks (Cu-MOF) doped with gold nanoparticle (AuNPs). The signal nanotags of signal probes (sDNA) that biofunctionalized AuNPs@Cu-MOF (sDNA-AuNPs@Cu-MOF) were designed using an Au-S bond. The biosensor was prepared by immobilization capture probes (cDNA) onto an electrodeposited AuNPs-modified glassy carbon electrode (GCE). AuNPs@Cu-MOF was introduced onto the surface of the GCE via a hybridization reaction between cDNA and tDNA, as well as tDNA and sDNA. Due to the enhanced oxidase-mimicking activity of AuNPs@Cu-MOF to glucose, the biosensor gave a linear range of 1.0 × 10−15 to 1.0 × 10−9 mol L−1 to tDNA with a detection limit (LOD) of 0.42 fmol L−1 under optimized conditions using differential pulse voltammetry measurement (DPV). It can be applied in the direct detection of ompA gene segments in total DNA extracts from C. sakazakii with a broad linear range of 5.4−5.4 × 105 CFU mL−1 and a LOD of 0.35 CFU mL−1. The biosensor showed good selectivity, fabricating reproducibility and storage stability, and can be used for the detection of ompA gene segments in real samples with recovery between 87.5% and 107.3%.

Abstract Rechargeable room temperature sodium–sulfur (RT Na–S) batteries are seriously limited by low sulfur utilization and sluggish electrochemical reaction activity of polysulfide intermediates. Herein, a 3D “branch-leaf” biomimetic design proposed for high performance Na–S batteries, where the leaves constructed from Co nanoparticles on carbon nanofibers (CNF) are fully to expose the active sites of Co. The CNF network acts as conductive “branches” to ensure adequate electron and electrolyte supply for the Co leaves. As an effective electrocatalytic battery system, the 3D “branch-leaf” conductive network with abundant active sites and voids can effectively trap polysulfides and provide plentiful electron/ions pathways for electrochemical reaction. DFT calculation reveals that the Co nanoparticles can induce the formation of a unique Co–S–Na molecular layer on the Co surface, which can enable a fast reduction reaction of the polysulfides. Therefore, the prepared “branch-leaf” CNF-L@Co/S electrode exhibits a high initial specific capacity of 1201 mAh g−1 at 0.1 C and superior rate performance.

In this paper, with eclipse stage in consideration, we propose an HIV-1 infection model with a general incidence rate and CTL immune response. We first study the existence and local stability of equilibria, which is characterized by the basic infection reproduction number $ \mathcal {R}_0 $ and the basic immunity reproduction number $ \mathcal {R}_1 $ . The local stability analysis indicates the occurrence of transcritical bifurcations of equilibria. We confirm the bifurcations at the disease-free equilibrium and the infected immune-free equilibrium with transmission rate and the decay rate of CTLs as bifurcation parameters, respectively. Then we apply the approach of Lyapunov functions to establish the global stability of the equilibria, which is determined by the two basic reproduction numbers. These theoretical results are supported with numerical simulations. Moreover, we also identify the high sensitivity parameters by carrying out the sensitivity analysis of the two basic reproduction numbers to the model parameters.

ObjectiveThis study aimed to develop and validate a multimorbidity index using self-reported chronic conditions for predicting 5-year mortality risk.MethodsWe analyzed data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and included 11,853 community-dwelling older adults aged 65–84 years. Restrictive association rule mining (ARM) was used to identify disease combinations associated with mortality based on 13 chronic conditions. Data were randomly split into the training (N = 8,298) and validation (N = 3,555) sets. Two multimorbidity indices with individual diseases only (MI) and disease combinations (MIDC) were developed using hazard ratios (HRs) for 5-year morality in the training set. We compared the predictive performance in the validation set between the models using condition count, MI, and MIDC by the concordance (C) statistic, the Integrated Discrimination Improvement (IDI), and the Net Reclassification Index (NRI).ResultsA total of 13 disease combinations were identified. Compared with condition count (C-statistic: 0.710), MIDC (C-statistic: 0.713) showed significantly better discriminative ability (C-statistic: p = 0.016; IDI: 0.005, p < 0.001; NRI: 0.038, p = 0.478). Compared with MI (C-statistic: 0.711), the C-statistic of the model using MIDC was significantly higher (p = 0.031), while the IDI was more than 0 but not statistically significant (IDI: 0.003, p = 0.090).ConclusionAlthough current multimorbidity status is commonly defined by individual chronic conditions, this study found that the multimorbidity index incorporating disease combinations showed supreme performance in predicting mortality among community-dwelling older adults. These findings suggest a need to consider significant disease combinations when measuring multimorbidity in medical research and clinical practice.

Abstract Aims/Introduction The role of irisin in maternal glucose metabolism and how it would respond to dietary n‐3 polyunsaturated fatty acid (n‐3 PUFA) intake remains unclear. This study aimed to explore whether maternal plasma irisin is associated with glucose metabolism and whether this association is modified by dietary n‐3 PUFA. Materials and Methods A total of 932 pregnant women (20–28 weeks’ gestation) aged 20–45 years were recruited. Dietary n‐3 PUFA was estimated using a validated quantitative food frequency questionnaire. Plasma irisin and insulin were tested by enzyme‐linked immunosorbent assay, and insulin resistance (IR) was estimated using the homeostatic model assessment (HOMA). Gestational diabetes mellitus was diagnosed with a 75‐g oral glucose tolerance test. Adjusted multivariable linear regression and logistic regression were carried out to examine the associations between plasma irisin and glucose metabolism. The moderating effect of dietary n‐3 PUFA intake was determined by fully multiplicative models by including the interaction term. Results Maternal plasma irisin was negatively associated with HOMA‐IR and oral glucose tolerance test 0 h glucose level (β −0.250, −0.067; corrected P‐value for false discovery rate = 0.012, 0.018, respectively), positively associated with HOMA of insulin sensitivity (β 0.028; corrected P‐value for false discovery rate = 0.012), but not associated with postprandial glucose or the risk of gestational diabetes mellitus. Furthermore, we found a moderating effect of dietary n‐3 PUFA on the relationships of plasma irisin with HOMA‐IR and HOMA of insulin sensitivity; these associations were strengthened with increased n‐3 PUFA intake (β −0.037, 0.004; P = 0.014, 0.041, respectively). Conclusions Plasma irisin was negatively associated with HOMA‐IR and fasting glucose, whereas it was positively associated with HOMA of insulin sensitivity in pregnant women. We first showed that these associations were modified by dietary n‐3 PUFA intake.

In this paper, we propose and analyze a delayed diffusive viral dynamic model incorporating cell-mediated immunity and both cell-free and cell-to-cell transmission. After discussing the well-posedness, we provide some preliminary results on solutions. Then we study the existence and uniqueness of homogeneous steady states, which turned out to be completely determined by the basic reproduction number of infection R0 and the basic reproduction number of immunity R1. Note that when R1 is defined, it is necessary that R0 > 1. The main result is a threefold dynamics. Roughly speaking, when R0 < 1 the infection-free steady state is globally asymptotically stable; when R1 ≤ 1 < R0 the immunity-free infected steady state is globally asymptotically stable; when R1 > 1 the infected-immune steady state is globally asymptotically stable. The approaches are linearization technique and the Lyapunov functional method. The theoretical results are also illustrated with numerical simulations.

Abstract Background Ototoxicity is one of the major side effects of platinum-based chemotherapy, especially cisplatin therapy. To date, no FDA approved agents to alleviate or prevent this ototoxicity are available. However, ototoxicity is generally believed to be produced by excessive generation of reactive oxygen species (ROS) in the inner ear, thus leading to the development of various antioxidants, which act as otoprotective agents. Astaxanthin (ATX) is an interesting candidate in the development of new therapies for preventing and treating oxidative stress-related pathologies, owing to its unique antioxidant capacity. Methods and results In this study, we aimed to evaluate the potential antioxidant properties of ATX in the inner ear by using the HEI-OC1 cell line, zebrafish, and guinea pigs. Because ATX has poor solubility and cannot pass through round window membranes (RWM), we established lipid-polymer hybrid nanoparticles (LPN) for loading ATX. The LPN enabled ATX to penetrate RWM and maintain concentrations in the perilymph in the inner ear for 24 h after a single injection. ATX-LPN were found to have favorable biocompatibility and to strongly affect cisplatin-induced generation of ROS, on the basis of DCFHDA staining in HEI-OC1 cells. JC-1 and MitoTracker Green staining suggested that ATX-LPN successfully reversed the decrease in mitochondrial membrane potential induced by cisplatin in vitro and rescued cells from early stages of apoptosis, as demonstrated by FACS stained with Annexin V-FITC/PI. Moreover, ATX-LPN successfully attenuated OHC losses in cultured organ of Corti and animal models (zebrafish and guinea pigs) in vivo. In investigating the protective mechanism of ATX-LPN, we found that ATX-LPN decreased the expression of pro-apoptotic proteins (caspase 3/9 and cytochrome-c) and increased expression of the anti-apoptotic protein Bcl-2. In addition, the activation of JNK induced by CDDP was up-regulated and then decreased after the administration of ATX-LPN, while P38 stayed unchanged. Conclusions To best of our knowledge, this is first study concluded that ATX-LPN as a new therapeutic agent for the prevention of cisplatin-induced ototoxicity.

In this paper, we consider the following system of delayed differential equations, \[ \left\{ \begin {array}{rcl} \frac {dS(t)}{dt} & = & \sigma \phi-\beta S(t)I(t-\tau)-\eta S(t), \\ \frac {dI(t)}{dt} & = & \sigma(1-\phi)+\beta S(t)I(t-\tau)-(\eta+\omega)I(t), \end {array} \right. \] which can be used to model plant diseases. Here $\phi\in (0,1]$, $\tau\ge 0$, and all other parameters are positive. The case where $\phi=1$ is well studied and there is a threshold dynamics. The system always has a disease-free equilibrium, which is globally asymptotically stable if the basic reproduction number $R_0\triangleq \frac{\beta\sigma}{\eta(\eta+\omega)}\le 1$ and is unstable if $R_0>1$; when $R_0>1$, the system also has a unique endemic equilibrium, which is globally asymptotically stable. In this paper, we study the case where $\phi\in (0,1)$. It turns out that the system only has an endemic equilibrium, which is globally asymptotically stable. The local stability is established by the linearization method while the global attractivity is obtained by the Lyapunov functional approach. The theoretical results are illustrated with numerical simulations.

Deep convolutional neural networks have achieved tremendous success in a variety of applications across many disciplines. However, their superior performance relies on correctly annotated large-scale datasets. It is very expensive and time-consuming to get the annotated large-scale datasets, especially in the medical field. While collecting a large amount of data is relatively easy, given the amount of data available on the web, but these data are highly unreliable, and they often include a massive amount of noisy labels. The past research works have shown that these noisy labels could significantly affect the performance of the deep convolutional neural networks on image classification. However, training a robust deep convolutional neural network with extremely noisy labels is a very challenging task. Inspired by the co-teaching concept, this paper proposes a novel method for training a robust convolutional neural network with extremely noisy labels, which is called group-teaching. Specifically, we train a group of convolutional neural networks simultaneously, and let them teach each other by selecting possibly clean samples for each network in each mini-batch. Each network back propagates the samples selected by other networks except itself and then it updates itself. The empirical results on noisy versions of CIFAR-10 and CIFAR-100 datasets demonstrate that our method is superior to the state-of-the-art methods in the robustness for noisy labels. Particularly, to verify the efficacy of our group-teaching in real-world noisy labels distribution, we have also validated the effectiveness of our method on the real-world noisy WebVision1000-100 dataset. The results show that our method has achieved higher performance than the state-of-the-art methods.

This paper is concerned with the free boundary problem for a reaction-diffusion SIRI model with relapse and bilinear incidence rate. After studying the (global) existence and uniqueness of solutions, we provide some sufficient conditions on the disease spreading-vanishing dichotomies for both cases with and without relapse.

Vector-borne infectious diseases may involve both horizontal transmission between hosts and transmission from infected vectors to susceptible hosts. In this paper, we incorporate these two transmission modes into a vector-borne disease model that includes general nonlinear incidence rates and the age of infection for both hosts and vectors. We show the existence, uniqueness, nonnegativity, and boundedness of solutions for the model. We study the existence and local stability of steady states, which is shown to be determined by the basic reproduction number. By showing the existence of a global compact attractor and uniform persistence of the system, we establish the threshold dynamics using the Fluctuation Lemma and the approach of Lyapunov functionals. When the basic reproduction number is less than one, the disease-free steady state is globally asymptotically stable and otherwise the disease will be established when there is initial infection force for the hosts. We also study a model with the standard incidence rate and discuss the effect of different incidence rates on the disease dynamics.

Under the epidemic, closed management has turned a large number of communities into lonely islands, and the contactless delivery method of UAV has become the rigid demand in this special period. This paper studies a collaborative system of multi-UAV multitruck transportation, which can deliver emergency materials such as medicine to remote areas or closed communities. In this system, delivery tasks are assigned to multiple trucks and multiple drones on each truck can perform delivery tasks in parallel, thereby improving delivery efficiency. We study the routing problem of this system specifically for medical supplying road network and establish mixed-integer model and hybrid algorithm. We show by experiments that the number of trucks has more significant impact on the optimal solution than the number of drones and the performance of hybrid particle swarm optimization is better than the performance of the other algorithms.

Metals and their alloys have been applied widely in the field of stomatology due to their good properties. However, as the oral environment and oral therapeutic schemes are complex, most dental metals have the problems of low biocompatibility and insufficient efficacy. With the development of nanotechnology, nanomodification has provided new opportunities for the surface modification of dental metals. Materials with nanoscale morphology and nanocoatings endow dental metal surfaces with nanoproperties that stimulate and guide various biological processes, providing potential solutions to clinical problems. This review characterizes current applications of nanotechnology for dental metal surface modification, with discussion of the resulting materials’ biocompatibility, interactions with cells and antibacterial activity. We also summarize the available information on the main preparation programs and key parameters of surface nanomodification, with discussion of the special advantages and difficulties associated with the nanomodification of metals employed in the oral cavity. We provide suggestions and references for improvement of the surface performance of dental metals and facilitation of their broad application.

This study aimed to evaluate the potential associations of dietary BCAAs (isoleucine, leucine, and valine) with physical function in the elderly Chinese population. A validated semiquantitative food frequency questionnaire and anthropometric and physical function measurements were used to collect data. We modeled trends in physical function indicators for BCAA quartiles using multivariate linear regression models. Among 4336 (43.97% men) participants aged 72.73 ± 5.48 years, a higher dietary intake of BCAAs was positively associated with increased handgrip strength (all p trends < 0.001), shorter times for 4-m fast walking (all p trends < 0.001) and repeated chair rises (all p trends < 0.001). No linear association was found between subtypes of amino acids and any physical functions (all p trends > 0.05). Individuals in the highest quartiles of BCAA intake had a reduced risk of developing low muscle strength, and the multiadjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) for women and men were 0.50 (0.38–0.65) and 0.67 (0.50–0.91), respectively. Similarly, higher BCAA consumption was associated with a lower risk of developing low physical performance (4-m walking speed: OR = 0.68 [0.50–0.93]; repeated chair rises: OR = 0.66 [0.54–0.81]). Higher dietary BCAA intake might be beneficial for physical function in the elderly population.

Animal diseases impose a huge burden on the countries where diseases are endemic. Conventional control strategies of vaccines and veterinary drugs are to control diseases from a pharmaceutical perspective. Another alternative approach is using pre-existing genetic disease resistance or tolerance. We know that the Yunling goat is an excellent local breed from Yunnan, southwestern China, which has characteristics of strong disease resistance and remarkable adaptability. However, genetic information about the selection signatures of Yunling goats is limited. We reasoned that the genes underlying the observed difference in disease resistance might be identified by investigating selection signatures between two different goat breeds. Herein, we selected the Nubian goat as the reference group to perform the population structure and selection signature analysis by using RAD-seq technology. The results showed that two goat breeds were divided into two clusters, but there also existed gene flow. We used Fst (F-statistics) and π (pi/θπ) methods to carry out selection signature analysis. Eight selected regions and 91 candidate genes were identified, in which some genes such as DOK2, TIMM17A, MAVS, and DOCK8 related to disease and immunity and some genes such as SPEFI, CDC25B, and MIR103 were associated with reproduction. Four GO (Gene Ontology) terms (GO:0010591, GO:001601, GO:0038023, and GO:0017166) were associated with cell migration, signal transduction, and immune responses. The KEGG (Kyoto Encyclopedia of Genes and Genomes) signaling pathways were mainly associated with immune responses, inflammatory responses, and stress reactions. This study preliminarily revealed the genetic basis of strong disease resistance and adaptability of Yunling goats. It provides a theoretical basis for the subsequent genetic breeding of disease resistance of goats.

Abstract Background Capsid (C) protein plays an important role in the replication of classical swine fever virus (CSFV). The ubiquitin proteasome system (UPS) involves in replication of many viruses via modulation of viral proteins. The relationship of CSFV with UPS is poorly understood and the impact of 26S proteasome on C protein has never been reported before. Methods In this study, fused C protein with an EGFP tag is expressed in PK-15 and 3D4/2 cells. MG132 and 3-methyladenine (3-MA) are used to detect the roles of 26S proteasome and autophagolysosome in expression levels of C protein. Truncated and mutant C proteins are used to find the exact residues responsible for the degradation of C protein. Immunoprecipitaion is performed to find whether C protein is ubiquitinated or not. Results C-EGFP protein expresses in a cleaved form at a low level and is degraded by 26S proteasome which could be partly inhibited by MG132. C-terminal residues play more important roles in the degradation of C protein than N-terminal residues. Residues 260 to 267, especially M260 and L261, are crucial for the degradation. In addition, C-terminal residues 262 to 267 determine cleavage efficiency of C protein. Conclusions CSFV C protein is degraded by 26S proteasome in a ubiquitin-independent manner. Last 8 residues at C-terminus of immature C protein play a major role in proteasomal degradation of CSFV C protein and determine the cleavage efficiency of C protein by signal peptide peptidase (SPP). Our findings provide valuable help for fully understanding degradation process of C protein and contribute to fully understanding the role of C protein in CSFV replication.

In this paper, we investigate a delayed HIV-1 infection model with immune response. Though a logistic growth is incorporated in the growth of the target cells, our focus is on the effect of delays on the infection dynamics. We first study the existence of steady states, which depends on the basic reproduction number $R_0$. When $R_0\le 1$, there is only the infection-free steady state, which is globally asymptotically stable if $R_0 < 1$. When $R_0> 1$, besides the unstable infection-free steady state, there is a unique infected steady state. We then study the local stability of the infected steady state and local Hopf bifurcation at it. The theoretical analysis indicates that the dynamics scenario is complicated. For example, there can be three sequences of critical values, stability switches and double Hopf bifurcation can occur. Some of the theoretical results are also illustrated with numerical simulations.