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Abstract Background Lip behaviors can lead to maxillofacial developmental disorders such as anterior open bite, posterior crossbite, increased overjet, and a higher risk of developing a Class II malocclusion. However, lip-sucking, a behavior often underreported and overlooked, may adversely affect the periodontal health of permanent teeth in adolescents under extreme conditions if not promptly identified and managed. Case presentation We report a unique case of an 11-year-old boy with a severe periodontal-endodontic lesion on tooth 32, caused by prolonged, high-frequency, and high-intensity lip sucking. Initial clinical examination revealed gingival recession, Grade III mobility, deep periodontal pocket, and alveolar bone loss without obvious pathogenesis. The therapeutic schedule encompassed behavioral modification, the repeated application of various dental splints due to splint breakage caused by strong lip-sucking habits, and root canal therapy. The periodontal condition and tooth stability were improved through collaborative management. At the 18-month follow-up, improvements in dental stability, alveolar bone density, and reduced periodontal pocket depth were observed. Conclusions This is the first case report exploring the complex relationship between lip-sucking and dental health, emphasizing that severe oral habits can lead to serious dental consequences. Timely identification and intervention in managing oral habits can halt disease progression and ensure favorable outcomes. Additionally, this report offers treatment guidelines and recommendations for severe dental diseases caused by detrimental oral habits.

IntroductionThis research seeks to investigate how early rehabilitation nursing, guided by Orem’s self-care theory, affects cognitive function, neurological function, and daily living skills in individuals who have suffered a traumatic brain injury (TBI).MethodsA study was conducted with 108 patients with traumatic brain injury who were hospitalized at our facility from January 2021 to March 2023. Based on their admission dates, the participants were separated into a control group (n = 56) and an observation group (n = 52). The control group received standard nursing care, while the observation group received a combination of conventional treatment and nursing interventions based on Orem’s self-care model. The research assessed alterations in the ability to perform daily tasks (Activities of Daily Living, ADL), neurological health (National Institutes of Health Stroke Scale, NIHSS; Glasgow Coma Scale, GCS), and cognitive abilities (Montreal Cognitive Assessment Scale, MoCA; Mini-Mental State Examination, MMSE) in both sets of participants prior to and following 4 and 8 weeks of nursing assistance.ResultsFollowing the intervention, the group being observed showed notably increased ADL scores at 4 weeks (p

Abstract A multi-class classification model for acute coronary syndrome (ACS) remains to be constructed based on multi-fluid metabolomics. Major confounders may exert spurious effects on the relationship between metabolism and ACS. The study aims to identify an independent biomarker panel for the multiclassification of HC, UA, and AMI by integrating serum and urinary metabolomics. We performed a liquid chromatography-tandem mass spectrometry (LC–MS/MS)-based metabolomics study on 300 serum and urine samples from 44 patients with unstable angina (UA), 77 with acute myocardial infarction (AMI), and 29 healthy controls (HC). Multinomial machine learning approaches, including multinomial adaptive least absolute shrinkage and selection operator (LASSO) regression and random forest (RF), and assessment of the confounders were applied to integrate a multi-class classification biomarker panel for HC, UA and AMI. Different metabolic landscapes were portrayed during the transition from HC to UA and then to AMI. Glycerophospholipid metabolism and arginine biosynthesis were predominant during the progression from HC to UA and then to AMI. The multiclass metabolic diagnostic model (MDM) dependent on ACS, including 2-ketobutyric acid, LysoPC(18:2(9Z,12Z)), argininosuccinic acid, and cyclic GMP, demarcated HC, UA, and AMI, providing a C-index of 0.84 (HC vs. UA), 0.98 (HC vs. AMI), and 0.89 (UA vs. AMI). The diagnostic value of MDM largely derives from the contribution of 2-ketobutyric acid, and LysoPC(18:2(9Z,12Z)) in serum. Higher 2-ketobutyric acid and cyclic GMP levels were positively correlated with ACS risk and atherosclerosis plaque burden, while LysoPC(18:2(9Z,12Z)) and argininosuccinic acid showed the reverse relationship. An independent multiclass biomarker panel for HC, UA, and AMI was constructed using the multinomial machine learning methods based on serum and urinary metabolite signatures.

Milk-derived extracellular vesicles (mEVs) derived from bovine colostrum (C-mEVs) and mature milk (M-mEVs) are known to carry bioactive molecules with significant immunomodulatory properties and biological effects. However, most research on mEVs has focused on their proteomics, lipidomics, and transcriptome, while metabolome analysis are still lacking. This study aims to explore the metabolomic profiles of C-mEVs and M-mEVs to uncover their molecular characteristics and potential biological functions. The mEVs were purified from both bovine colostrum and mature milk using ultracentrifugation combined with size exclusion chromatography. Through untargeted metabolomic analysis employing liquid chromatography-tandem mass spectrometry (LC-MS/MS), 76 differential metabolites, such as leucylproline, levonordefrin, adenine, polyglycerol esters of fatty acids, and hypoxanthine were identified. Among them, lipid-related metabolites were the most prominent. Hierarchical cluster analysis and principal component analysis revealed distinct metabolic signatures between C-mEVs and M-mEVs. Pathway enrichment analysis indicated that the metabolites were involved in purine metabolism and ABC transporter pathways, which was closely related to cancer, inflammation, gastrointestinal disorders, and metabolic diseases. The findings highlight the potential of metabolomics to provide a temporally precise and detailed snapshot of the molecular properties of mEVs, contributing valuable insights into mEVs-mediated molecular mechanisms and offering new avenues for research into their biological effects and therapeutic applications.

For a hypergraph $ H $ with vertex set $ X $ and edge set $ Y $, the incidence graph of hypergraph $ H $ is a bipartite graph $ I(H) = (X, Y, E) $, where $ xy\in E $ if and only if $ x\in X $, $ y\in Y $ and $ x\in y $. A total dominating set of graph $ G $ is a vertex subset that intersects every open neighborhood of $ G $. Let $ \mathscr{M} $ be a family of (not necessarily distinct) total dominating sets of $ G $ and $ r_{\mathscr{M}} $ be the maximum times that any vertex of $ G $ appears in $ \mathscr{M} $. The fractional domatic number $ G $ is defined as $ FTD(G) = \sup_{\mathscr{M}}\frac{|\mathscr{M}|}{r_{\mathscr{M}}} $. In 2018, Goddard and Henning showed that the incidence graph of every complete $ k $-uniform hypergraph $ H $ with order $ n $ has $ FTD(I(H)) = \frac{n}{n-k+1} $ when $ n\geq 2k\geq 4 $. We extend the result to the range $ n > k\geq 2 $. More generally, we prove that every balanced $ n $-partite complete $ k $-uniform hypergraph $ H $ has $ FTD(I(H)) = \frac{n}{n-k+1} $ when $ n\geq k $ and $ H\ncong K_n^{(n)} $, where $ FTD(I(K_n^{(n)})) = 1 $.

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease with a high prevalence in the elderly population over 65 years of age. Intervention in the early stages of AD is of great significance to alleviate the symptoms. Recent advances in deep learning have shown extreme advantages in computer-aided diagnosis of AD. However, most studies only focus on extracting features from slices in specific directions or whole brain images, ignoring the complementarity between features from different angles. To overcome the above problem, attention-based multi-view slice fusion (AMSF) is proposed for accurate early diagnosis of AD. It adopts the fusion of three-dimensional (3D) global features with multi-view 2D slice features by using an attention mechanism to guide the fusion of slice features for each view, to generate a comprehensive representation of the MRI images for classification. The experiments on the public dataset demonstrate that AMSF achieves 94.3% accuracy with 1.6–7.1% higher than other previous promising methods. It indicates that the better solution for AD early diagnosis depends not only on the large scale of the dataset but also on the organic combination of feature construction strategy and deep neural networks.

Abstract The pathological features of cerebral edema are complicated. The intracranial pressure (ICP) is regarded as the most important indicator for monitoring cerebral edema. Recently, multi-parameter has been used to explore the types and pathogenesis of cerebral edema and design effective treatment strategies. This research focused on investigating the characteristic of the cerebral edema induced by lipopolysaccharide (LPS) in rats by using simultaneous electrophysical and hemodynamic parameters. The results showed that neurophysiologic parameters (firing rate (FR) and the power spectrum of local field potential (LFP power)) and hemodynamic parameters (relative concentration of oxygenated hemoglobin (ΔCHbO2), relative concentration of deoxyhemoglobin ΔCHbR) and relative cerebral blood flow (rCBF)) were linearly correlated, and the Pearson’s correlation coefficient was changed by pathological progression of cerebral edema induced by LPS. Furtherly, the treatment after two agents were observed successfully through these multi-parameters. Our findings revealed the relationship between neural activity and hemodynamic response during the progression of cerebral edema and provided a multi-parameter solution for cerebral edema functional monitoring and anti-edema drug efficacy evaluation.

Multiple sclerosis is a chronic autoimmune demyelinating disease of the central nervous system and is difficult to diagnose in early stages. Without homeostatic control, urine was reported to have the ability to accumulate early changes in the body. We expect that urinary proteome can reflect early changes in the nervous system. The early urinary proteome changes in a most employed multiple sclerosis rat model (experimental autoimmune encephalomyelitis) were analysed to explore early urinary candidate biomarkers, and early treatment of methylprednisolone was used to evaluate the therapeutic effect. Twenty-five urinary proteins were altered at day 7 when there were no clinical symptoms and obvious histological changes. Fourteen were reported to be differently expressed in the serum/cerebrospinal fluid/brain tissues of multiple sclerosis patients or animals such as angiotensinogen and matrix metallopeptidase 8. Functional analysis showed that the dysregulated proteins were associated with asparagine degradation, neuroinflammation and lipid metabolism. After the early treatment of methylprednisolone, the incidence of encephalomyelitis in the intervention group was only 1/13. This study demonstrates that urine may be a good source of biomarkers for the early detection of multiple sclerosis. These findings may provide important information for early diagnosis and intervention of multiple sclerosis in the future.

Abstract The recovery of low-quality waste heat is a major problem in energy utilization. In order to solve this problem and improve energy utilization, the research group designed a low-quality waste heat power generation device with Roots power machine as the core. However, the device has poor ability to adjust the rotation speed and it is difficult to generate electricity stably. The fundamental reason is that the system has many variables and strong coupling. According to the actual working conditions, the power of the device is 10 kW, and the fluctuation range should be within ± 7%. On the one hand, it can be improved by hardware, on the other hand, the design of software is also very critical. At present, through the investigation of domestic and foreign researches on the control system, it is found that the stability of the system is gradually improved, but the problem of strong coupling between variables has not been effectively solved. Therefore, the research group modeled the variables in the system and obtained a coupled model. Based on the couple model, the research group introduced nonlinear multi-model adaptive closed-loop decoupling control and designed a control system. The simulation results show that the maximum overshoot of the control system is 3.9%, the adjustment time is also reduced, and it is stable in low quality waste heat recovery device. Experimental results show that under the control of the system, the rotational speed of roots motor can keep stable, the maximum deviation is not more than 21.4 r/min, and the fluctuation range is within ± 7%, which meets the requirements of the index. This has laid the foundation for the follow-up research of grid-connected power generation.

Abstract Claudins, the integral tight junction proteins that regulate paracellular permeability and cell polarity, are frequently dysregulated in cancer; however, their roles in regulating EGFR tyrosine kinase inhibitors (EGFR-TKIs) resistance in non-small cell lung cancer (NSCLC) are unknown. To this end, we performed GEO dataset analysis and identified that claudin1 was a critical regulator of EGFR-TKI resistance in NSCLC cells. We also found that claudin1, which was highly induced by continuous gefitinib treatment, was significantly upregulated in EGFR-TKI-resistant NSCLC cells. By knocking down claudin1 in cell lines and xenograft models, we established that gefitinib resistance was decreased. Moreover, claudin1 knockdown suppressed the expression levels of pluripotency markers (Oct4, Nanog, Sox2, CD133, and ALDH1A1). Claudin1 loss inhibited phosphorylated AKT (p-AKT) expression and reduced cancer cell stemness by suppressing AKT activation. Furthermore, SKL2001, a β-catenin agonist, upregulated the expression levels of claudin1, p-AKT, and pluripotency markers, and 1,25-dihydroxy-vitamin D3 (1,25(OH)2D3) reduced claudin1 expression, AKT activation, and cancer cell stemness by inhibiting β-catenin, and suppressed claudin1/AKT pathway mediated cancer stem-like properties and gefitinib resistance. Collectively, inhibition of claudin1-mediated cancer stem-like properties by 1,25(OH)2D3 may decrease gefitinib resistance through the AKT pathway, which may be a promising therapeutic strategy for inhibiting gefitinib resistance in EGFR-mutant lung adenocarcinoma.

The effective recovery and utilization of waste heat is an important part of the energy industry chain, but the gas source of waste heat has large fluctuations and strong random frequency changes, which easily affects the quality of power generation. In order to obtain more continuous and stable electricity in the process of waste heat power generation, this paper proposes an intelligent adaptive control method. This control method decouples the variables for the characteristics of strong coupling of the waste heat power generation system, which improves the anti-disturbance performance of the system on the one hand and reduces the steady-state tracking error of the system on the other hand. Experiments show that when the gas source fluctuates, the system fluctuation rate is stable within 7%; when the set value changes, the adjustment time is within 7 s, and the overshoot is small, so the performance is better than the traditional PID control method. The intelligent adaptive control method proposed in this paper is of great significance for the future development of intelligent grid-connected power generation.

Silurus lanzhouensis is a large endemic fish exclusively found in the middle and upper reaches of China’s Yellow River, with a restricted distribution range and a small population size and is listed as an endangered species. To investigate the potential genetic factors contributing to the observed decrease in the population of S. lanzhouensis, we have successfully assembled the first chromosome-level genome of S. lanzhouensis. This genome comprises a total of 30 chromosomes, with a size of 794.43 Mb, and 23,093 protein-coding genes. Comparative genomics analysis reveals that the genetic relationship between S. lanzhouensis and S. meridionalis Chen is the closest, and their common ancestor experienced two rounds of whole genome duplication (WGD) before diverging. Notably, amino acid metabolism-related pathways are enriched in the unique S. lanzhouensis gene family. In addition, we observed that the chemokine receptor and scavenger receptor gene families contracted in S. lanzhouensis, which may be associated with its diminished immune response. Our research findings provide valuable insights into the endangered mechanism of S. lanzhouensis and enhance our understanding of the evolution of Siluriformes fish.

Nitrogen pollution in water bodies presents a serious threat to ecosystems due to its role in eutrophication. In this study, the aerobic denitrifying bacterium Alcaligenes faecalis was used as a model microorganism to investigate the optimal operating conditions for nitrogen removal from nitrogen-containing wastewater by Alcaligenes faecalis under different aeration modes, microbial dosages and C/N ratios. The results showed that the optimal aeration mode for efficient bacterial denitrification was 10 min of aeration with a 30 min interval, and the total nitrogen removal reached 87.82%. At different bacterial doses, NO3−–N was completely denitrified and NO2−–N accumulation levels were reduced, all of which resulted in significant denitrification, and the final total nitrogen removal efficiencies reached 86.39–98.50%. With an increase in the C/N ratio, the pollutant removal performance of denitrifying bacteria increased. When the C/N ratio was 17, the final rates of NO3−–N, TN and COD removal were 100%, 98.50% and 96.13%, respectively. At lower C/N ratios, the growth and metabolism of microorganisms were inhibited and fewer electron acceptors were available during the denitrification process, which seriously affected denitrification performance. In this study, the denitrification performance of aerobic denitrifying bacterium Alcaligenes faecalis was explored in experiments using changes in aeration mode, microbial dosage and C/N ratio, and the optimal operating conditions of Alcaligenes faecalis for treating nitrogenous wastewater were indicated. This provides technical support for Alcaligenes faecalis in improving the remediation effect of nitrogenous wastewater and provides a theoretical basis for further in-depth research on the performance of Alcaligenes faecalis in the future.

BackgroundDiabetes-associated cognitive impairment (DACI) is a common complication of diabetes, and studies have shown that DACI is more severe in postmenopausal patients with diabetes. Forsythoside B (FTS⋅B) can inhibit inflammation and reduce synaptic dysfunction, which can improve cognitive function. However, it has not been confirmed whether FTS⋅B has a reversing or retarding effect on postmenopausal diabetic encephalopathy.MethodsSeven days after bilateral ovariectomy (OVX) or sham surgery, adult female C57 mice (n = 15/group) received intraperitoneal injection of streptozotocin (60 mg/kg/day/L) and citrate buffer for 5 consecutive days to induce diabetes mellitus (DM). Fourteen days later, ovariectomized diabetic mice were given intraperitoneal injection of FTS⋅B (100, 150 mg/kg/day/L) and subcutaneous injection of 17β-estradiol (1 mg/kg) for 8 weeks [OVX + DM + low-FTS⋅B group (L-F), OVX + DM + high-FTS⋅B group (H-F), and OVX + DM + 17β-estradiol (ER)]. In addition, the following control groups were defined: Sham, OVX, DM, and OVX + DM (O + D). Fasting plasma glucose, body weight and blood insulin levels were determined in each group of mice. Next, their cognitive function was tested through behavioral experiments. Hematoxylin & eosin (H&E) and Nissl staining were used to detect the morphological changes in the hippocampus. The aggregation of amyloid beta (Aβ) and the hyperaggregation of p-tau were assessed by immunohistochemistry. Interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), brain-derived neurotrophic factor (BDNF), post-synaptic density-95 (PSD-95), synaptophysin, and synapsin-1 expression in the hippocampus was detected by real-time polymerase chain reaction (RT-PCR) and western blot analysis.ResultsFTS⋅B can decrease fasting glucose and blood insulin level. Behavioral results showed that cognitive decline was the most severe in the O + D group, and the ER, L-F, and H-F groups revised the cognitive decline. Compared to the O + D group, more normal morphology, which has obvious nucleoli and clear nuclear membrane, was observed by H&E and Nissl staining in the ER, L-F, and H-F groups. FTS⋅B alleviated DACI by reducing the aggregation of Aβ and the hyperaggregation of p-tau in the hippocampus. Moreover, the protein and mRNA expression showed that FTS⋅B not only inhibited inflammation by decreasing IL-1β, IL-6, and TNF-α but also modulated synaptic plasticity by increasing BDNF, PSD-95, synaptophysin, and synapsin-1.ConclusionThese results suggest that FTS⋅B may be a novel therapeutic target for postmenopausal diabetic encephalopathy treatment.

At present, the recovery of low-quality waste heat is a major problem in energy utilization. To solve this problem and improve energy efficiency, this research group designed a low-quality waste heat power generation device with a roots-type power machine as the core component. However, the power generation device produces a large hysteresis in power generation regulation. While the hardware can be improved, the design of the measurement and control system is also critical. In view of the problems existing in low-quality waste heat power generation devices, this research group introduced an internal model controller into the control system and designed an internal model controller and filter through the analysis of each module. In addition, to improve the performance of the controller, this research group applied the deep learning method to optimize the control system and used the prediction function of the deep learning method to further improve the stability of the device. The simulation and experimental results show that the control strategy can make this device for the recovery of low-quality waste heat respond quickly to fluctuations in the gas source and improve the hysteresis problem.

The reuse of industrial waste heat is an important way to promote energy conservation and reduce emissions. However, low-quality waste heat has a wide distribution range. It is difficult to recover, and the recycling technology needs to be a breakthrough. Therefore, in this paper, we propose a Roots waste heat power generation device which is used to recover low-quality waste heat. However, the relative fluctuation of the air source is greater with the low-quality waste heat than that with the medium- and high-quality waste heat, which makes it difficult for the actual working condition of the device to maintain stability and even causes the generator to cut off automatically. Therefore, it is necessary to perform a study on the robustness of the measurement and control system of the Roots waste heat power generation process and to improve the stability of the device operation. To solve these problems, we propose a control method that combines a robust controller and an internal model controller to improve the robustness of the device. The experimental results showed that the robust internal model controller has a strong anti-interference ability and that the tracking performance is obviously improved.

A novel polysaccharide (ZOP) was extracted from Zingiber officinale with ultrasonic assisted extraction method. ZOP monosaccharide composition and mole ratio is GlcA: GalA: Glc: Gal: Ara = 1.97:1.15:94.33:1.48:1.07. Then, the particle size of ZOP-NPs prepared by nano-precipitation method was 230.5 nm, and the polydispersity index (PDI) was 0.260. Using ZOP and ZOP-NPs as reductants and stabilizers, ZOP-AgNPs and ZOP-NPs-AgNPs were prepared. They were characterized by ultraviolet-visible spectrophotometer (UV-Vis), fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), transmission electron microscope (TEM), and X-ray diffraction (XRD). The silver chelation rate of polysaccharide silver nanoparticles (AgNPs) ranged from 68.70 to 82.12%. ZOP-AgNPs (0.5%, w/v; 1%, w/v) and ZOP-NPs-AgNPs (0.5%, w/v; 1%, w/v) exhibited a narrow particle size distribution of 31.1, 34.6, 25.1 and 27.6 nm, respectively. And the zeta potential values of them were−19.4,−21.6,−19.7,−23.8mV, respectively. The antioxidant and antibacterial activities of ZOP-NPs-AgNPs were superior to those of ZOP, ZOP-NPs and ZOP-AgNPs.

Constructed wetlands (CWs) have been proven as a reliable alternative to traditional wastewater treatment technologies. Microorganisms in CWs, as an important component, play a key role in processes such as pollutant degradation and nutrient transformation. Therefore, an in-depth analysis of the community structure and diversity of microorganisms, especially for functional microorganisms, in CWs is important to understand its performance patterns and explore optimized strategies. With advances in molecular biotechnology, it is now possible to analyze and study microbial communities and species composition in complex environments. This review performed bibliometric analysis of microbial studies in CWs to evaluate research trends and identify the most studied pollutants. On this basis, the main functional microorganisms of CWs involved in the removal of these pollutants are summarized, and the effects of these pollutants on microbial diversity are investigated. The result showed that the main phylum involved in functional microorganisms in CWs include Proteobacteria, Bacteroidetes, Actinobacteria and Firmicutes. These functional microorganisms can remove pollutants from CWs by catalyzing chemical reactions, biodegradation, biosorption, and supporting plant growth, etc. Regarding microbial alpha diversity, heavy metals and high concentrations of nitrogen and phosphorus significantly reduce microbial richness and diversity, whereas antibiotics can cause large fluctuations in alpha diversity. Overall, this review can provide new ideas and directions for the research of microorganisms in CWs.

Thanks to the popularization of mobile smart devices equipped with various sensors like smartphones, the concept of mobile crowdsensing has come forth as a promising data collecting paradigm. Event detection in urban areas (i.e., traffic jam monitoring) is an important application of mobile crowdsensing, which can be implemented by recruiting a set of smart device users to collect plenty of fine-grained sensing data. However, as users are mobile and their sensing data are unreliable, it is hard to ensure that all events can be detected accurately. Thus, which users are recruited should be carefully determined to achieve a high detection accuracy and control the costs of users within a given budget. Unfortunately, we prove that the user recruitment problem in mobile crowdsensing for event detection is a NP-hard problem, indicating that there is no polynomial-time algorithm to achieve the optimal solution unless P = NP. In this work, we propose a polynomial-time near-optimal user recruitment algorithm, by leveraging the properties of adaptive monotonicity and adaptive submodularity. Our algorithm is theoretically proved to achieve a constant approximation ratio, compared with the optimum. Moreover, a data-dependent upper bound of our solution is also derived, providing a tighter performance guarantee. We also provide an accelerated version of our proposed algorithm by reducing its computation load. Extensive simulations are conducted, which show our proposed algorithm outperforms baselines under different settings and achieves near-optimal performance. Besides, the execution time of the accelerated version is significantly reduced.

Visceral white nodules disease (VWND), caused by Pseudomonas plecoglossicida, is a common disease among cage-farmed large yellow croaker (Larimichthys crocea) in China. However, comprehensive investigations of the molecular defensive mechanisms used by L. crocea in response to P. plecoglossicida infection remain relatively rare. Here, we constructed transcriptomes of the L. crocea spleen at 12 h and 24 h after P. plecoglossicida challenge. We identified 518 novel miRNAs and 823 known miRNAs in the spleen of L. crocea. Between the challenge and control groups, 32 differentially expressed miRNAs (DEmiRNAs), predicted to target 356 genes, and 1152 differentially expressed mRNAs (DEmRNAs) were identified at 12 h post-infection, while 33 DEmiRNAs, predicted to target 278 genes, and 1067 DEmRNAs were identified at 24 h post-infection. Gene ontology (GO) analysis showed that 146 and 126 GO terms were significantly enriched in the target genes at 12 h and 24 h, respectively. Twenty-eight and four immune-associated Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched in the target genes at 12 h and 24 h, respectively. Three immune-associated pathways were among those most enriched in the target genes: Toll-like receptor signaling, endocytosis, and C-type lectin receptor signaling. Network analysis identified 47 DEmRNA-DEmiRNA pairs. In particular, the immune-related genes TLR5S and PIGR were targeted by the miRNAs lcr-miR-7132c and dre-miR-183-5p, respectively. Dual-luciferase assays verified that lcr-miR-7132c downregulated TLR5S, suggesting that this miRNA may participate in regulating the immune response of L. crocea to P. plecoglossicida infection through the TLR5S-mediated signaling pathway. Our results help to clarify the miRNA-mediated immune response of L. crocea to P. plecoglossicida infection.

Tubulointerstitial fibrosis is one of the most common pathological features of diabetic nephropathy. Autophagy, an intracellular mechanism to remove damaged or dysfunctional cell parts and maintain metabolic homeostasis, is inhibited in diabetic neuropathy. Icariin is a traditional Chinese medicine extract known for nourishing the kidney and reinforcing Yang. In this study, we investigated the effects and mechanism of Icariin on renal function, autophagy, and fibrosis in type 2 diabetic nephropathic rats and in high-glucose-incubated human renal tubular epithelial cells and rat renal fibroblasts (in vitro). Icariin improved diabetes, renal function, restored autophagy, and alleviated fibrosis in type 2 diabetic neuropathic rats and in vitro. After we applied autophagy-related gene 5-small interfering RNA, we found that fibrosis improvement by Icariin was related to autophagy restoration. By detecting serum sex hormone levels, and using dihydrotestosterone, siRNA for androgen receptor, and the androgen receptor antagonist Apalutamide (ARN-509), we found that Icariin had an androgen-like effect and restored autophagy and reduced fibrosis by regulating the androgen receptor. In addition, miR-192-5p levels were increased under high glucose but reduced after dihydrotestosterone and Icariin treatment. Furthermore, dihydrotestosterone and Icariin inhibited miR-192-5p overexpression-induced fibrosis production and autophagy limitation. Glucagon-like peptide-1 receptor (GLP-1R) was downregulated by high glucose and overexpression of miR-192-5p and could be restored by dihydrotestosterone and Icariin. By using ARN-509, we found that Icariin increased GLP-1R expression by regulating the androgen receptor. GLP-1R-siRNA transfection weakened the effects of Icariin on autophagy and fibrosis. These findings indicate that Icariin alleviates tubulointerstitial fibrosis by restoring autophagy through the miR-192-5p/GLP-1R pathway and is a novel therapeutic option for diabetic fibrosis.

Most proteins given orally have low bioavailability and are easily eliminated by rapid metabolism in vivo. In order to immobilize the drug at the site of administration and delay its release, a natural, gentle release system was designed. In this study, a heteropolysaccharide (ZOP) was isolated from Zingiber officinale using an ultrasonic assisted extraction method. ZOP Ara = 1.97: 1.15: 94.33: 1.48: 1.07. The ZOP/Chitosan (CS) composite hydrogel was synthesized using epichlorohydrin (ECH) as a cross-linking agent. The structure, morphology, and water-holding capacity of the composite hydrogel were characterized. The data showed that the addition of ZOP improved the hardness and water-holding capacity of the material. A swelling ratio test showed that the prepared hydrogel was sensitive to pH and ionic strength. In addition, the degradation rate of the hydrogel in a phosphate-buffered saline (PBS) solution with a pH value of 1.2 was higher than that in PBS with pH value of 7.4. Similarly, the release kinetics of Bovine serum albumin (BSA) showed higher release in an acidic system by the hydrogel composed of ZOP/CS. The hydrogel prepared by this study provided a good microenvironment for protein delivery. In summary, this composite polysaccharide hydrogel is a promising protein-drug-delivery material.

ObjectiveTo analyze the effect of statins on cytokines levels in gingival crevicular fluid (GCF) and saliva and on clinical periodontal parameters of middle-aged and elderly patients with type 2 diabetes mellitus (T2DM).MethodsSystemically healthy controls (C group, n = 62), T2DM patients not taking statins (D group, n = 57) and T2DM patients taking statins (S group, n = 24) were recruited. In each group, subjects (40-85 years) were subclassified into the h (periodontal health)group, the g (gingivitis)group or the p (periodontitis) group according to different periodontal conditions. 17 cytokines in gingival crevicular fluid (GCF) and saliva samples of each subject were measured utilizing the Luminex technology kit. Further, HbA1c (glycated hemoglobin), FPG (fasting plasma glucose), PD (probing depth), CAL (clinical attachment level), BOP (bleeding on probing), GI (gingival index) and PI (periodontal index) were recorded. Data distribution was tested through the Shapiro-Wilk test, upon which the Kruskal-Wallis test was applied followed by Mann-Whitney U test and Bonferroni's correction.ResultsLevels of IFN-γ, IL-5, IL-10 and IL-13 in the saliva of the Dh group were significantly lower than those in the Ch group, while factor IL-4 was higher (pConclusionStatins are associated with reduced PD and cytokines levels in the GCF and saliva of T2DM patients with periodontitis.

ObjectivesTo investigate three-dimensional morphological variation of the occipital bone between sexes and among populations, to determine how ancestry, sex and size account for occipital shape variation and to describe the exact forms by which the differences are expressed.MethodsCT data for 214 modern crania of Asian, African and European ancestry were compared using 3D geometric morphometrics and multivariate statistics, including principal component analysis, Hotelling's T2 test, multivariate regression, ANOVA, and MANCOVA.ResultsSex differences in average occipital morphology are only observed in Europeans, with males exhibiting a pronounced inion. Significant ancestral differences are observed among all samples and are shared by males and females. Asian and African crania have smaller biasterionic breadths and flatter clivus angles compared to Europeans. Asian and European crania are similar in their nuchal and occipital plane proportions, nuchal and occipital angles, and lower inion positions compared to Africans. Centroid size significantly differs between sexes and among populations. The overall allometry, while significant, explains little of the shape variation. Larger occipital bones were associated with a more curved occipital plane, a pronounced inion, a narrower biasterionic breadth, a more flexed clivus, and a lower and relatively smaller foramen magnum.ConclusionsAlthough significant shape differences were observed among populations, it is not recommended to use occipital morphology in sex or population estimation as both factors explained little of the observed variance. Other factors, relating to function and the environment, are suggested to be greater contributors to occipital variation. For the same reason, it is also not recommended to use the occiput in phylogenetic studies.

Recently, advances in noninvasive detection techniques have shown that it is possible to decode visual information from measurable brain activities. However, these studies typically focused on the mapping between neural activities and visual information, such as the image or video stimulus, on the individual level. Here, the common decoding models across individuals that classifying behavior tasks from brain signals were investigated. We proposed a cross-subject decoding approach using deep transfer learning (DTL) to decipher the behavior tasks from functional magnetic resonance imaging (fMRI) recording during subjects performing different tasks. We connected parts of the state-of-the-art networks pre-trained on the ImageNet dataset to our defined adaption layers to classify the behavior tasks from fMRI data. Our experiments on the Human Connectome Project (HCP) dataset showed that the proposed method achieved a higher decoding accuracy across subjects than the previous studies. We also conducted an experiment on five subsets of HCP data, which further demonstrated that our DTL approach is more effective on small dataset than the traditional methods.

Background Urine, as a potential biomarker source among body fluids, can accumulate many early changes in the body due to the lack of mechanisms to maintain a homeostatic state. This study aims to detect early changes in the urinary proteome in a rat liver tumour model. Methods The tumour model was established with the Walker-256 carcinosarcoma cell line (W256). Urinary proteins at days 3, 5, 7 and 11 were profiled by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Compared with controls, differential proteins were selected. Associations of differential proteins with cancer were retrieved. Results At days 3, 5, 7 and 11, five, fifteen, eleven and twelve differential proteins were identified, respectively. Some of the differential proteins were reported to be associated with liver cancer. This differential urinary protein pattern was different from the patterns in W256 subcutaneous, lung metastasis and intracerebral tumour models. Conclusions This study demonstrates that (1) early changes in urinary proteins can be found in the rat liver tumour model; (2) urinary proteins can be used to differentiate the same tumour cells grown in different organs.

This paper is devoted to the investigation of optimality conditions for approximate quasi weak efficient solutions for a class of vector equilibrium problem (VEP). First, a necessary optimality condition for approximate quasi weak efficient solutions to VEP is established by utilizing the separation theorem with respect to the quasirelative interior of convex sets and the properties of the Clarke subdifferential. Second, the concept of approximate pseudoconvex function is introduced and its existence is verified by a concrete example. Under the assumption of introduced convexity, a sufficient optimality condition for VEP in sense of approximate quasi weak efficiency is also presented. Finally, by using Tammer’s function and the directed distance function, the scalarization theorems of the approximate quasi weak efficient solutions of the VEP are proposed.

Laser speckle contrast imaging (LSCI) is an optical imaging method, which can monitor microvascular flow variation directly without addition of any ectogenous dye. All the existing laser speckle contrast analysis (LASCA) methods are a combination of spatial and temporal statistics. In this study, we have proposed a new method, Gaussian kernel laser speckle contrast analysis (gLASCA), which processes the raw images primarily with the Gaussian kernel operator along the spatial direction of blood flow. We explored the properties of gLASCA in the simulation and animal cerebral ischemia perfusion model. Compared with the other existing speckle processing methods based on spatial, temporal, spatial-temporal or anisotropic linear structure; the present gLASCA method has a high spatial-temporal resolution to respond the change of velocity especially in microvasculature. Besides, the gLASCA method obtains approximately 10.2% and 7.1% higher contrast-to-noise ratio (CNR) over the anisotropic linear method (aLASCA) in the simulation and experiment models. For these advantages, gLASCA could be a better method for local microvascular laser speckle imaging in terms of cerebral ischemia reperfusion, spreading depression and brain injury diseases.

This paper is dedicated to the study of the geometric average Asian call option pricing under non-extensive statistical mechanics for a time-varying coefficient diffusion model. We employed the non-extensive Tsallis entropy distribution, which can describe the leptokurtosis and fat-tail characteristics of returns, to model the motion of the underlying asset price. Considering that economic variables change over time, we allowed the drift and diffusion terms in our model to be time-varying functions. We used the I t o ^ formula, Feynman⁻Kac formula, and P a d e ´ ansatz to obtain a closed-form solution of geometric average Asian option pricing with a paying dividend yield for a time-varying model. Moreover, the simulation study shows that the results obtained by our method fit the simulation data better than that of Zhao et al. From the analysis of real data, we identify the best value for q which can fit the real stock data, and the result shows that investors underestimate the risk using the Black⁻Scholes model compared to our model.