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Abstract Convolutional neural networks (CNNs) for extracting structural information from structural magnetic resonance imaging (sMRI), combined with functional magnetic resonance imaging (fMRI) and neuropsychological features, has emerged as a pivotal tool for early diagnosis of Alzheimer’s disease (AD). However, the fixed-size convolutional kernels in CNNs have limitations in capturing global features, reducing the effectiveness of AD diagnosis. We introduced a group self-calibrated coordinate attention network (GSCANet) designed for the precise diagnosis of AD using multimodal data, including encompassing Haralick texture features, functional connectivity, and neuropsychological scores. GSCANet utilizes a parallel group self-calibrated module to enhance original spatial features, expanding the field of view and embedding spatial data into channel information through a coordinate attention module, which ensures long-term contextual interaction. In a four-classification comparison (AD vs. early MCI (EMCI) vs. late MCI (LMCI) vs. normal control (NC)), GSCANet demonstrated an accuracy of 78.70%. For the three-classification comparison (AD vs. MCI vs. NC), it achieved an accuracy of 83.33%. Moreover, our method exhibited impressive accuracies in the AD vs. NC (92.81%) and EMCI vs. LMCI (84.67%) classifications. GSCANet improves classification performance at different stages of AD by employing group self-calibrated to expand features receptive field and integrating coordinated attention to facilitate significant interactions among channels and spaces. Providing insights into AD mechanisms and showcasing scalability for various disease predictions.

Myxofibrosarcoma is a malignant tumor originating from fibroblast or myofibroblast, with an incidence of about 5% in soft tissue sarcomas. However, myxofibrosarcomas that originate from and are restricted to the nasal vestibule are rarely seen in the clinic. These myxofibrosarcomas are susceptible to being misdiagnosed with nasal vestibular cysts due to similar physical characteristics, such as clinical symptoms and imaging findings. In this article, we report the radiological and histopathological findings of a nasal vestibular myxofibrosarcoma and discuss the different characteristics compared with a nasal vestibular cyst. Fascial tail signs in magnetic resonance imaging, abundant myxoid matrix, and pseudolipoblastic cells in pathological findings are critical standards to make a differential diagnosis of a nasal vestibular cyst.

BackgroundCyadox (CYA) is a derivative of quinoxaline 1,4-dioxide and a safe and effective synthetic antibacterial agent.ObjectiveThis study aimed to explore the drug transport in blood, distribution, depletion and hepatotoxicity of drugs in animals.MethodsThe transport of CYA in blood was studied using fluorescence, circular dichroism (CD) and molecular docking methods. Tissue distribution and depletion of CYA in rats were evaluated following oral administration of [3H]-CYA at different doses. Hepatotoxicity of drugs evaluated by transcriptomics.ResultsDuring transport in the bloodstream, the drug binds to bovine serum albumin (BSA) by hydrogen bonding and has only one binding site. Hydrogen bonds were formed between O (2) of CYA and ARG208, O (3) of CYA and LEU480, VAL481. The secondary protein conformation of BSA changed after binding with an increase in α-helix and a decrease in β-strand. After a single oral administration of [3H]-CYA, it was excreted rapidly within 7 days, with 34.81% from the urine and 60.25% from the feces. Higher and sustained levels of radioactivity were detected in the liver during the post-dose period, suggesting that the drug may concentrate in the liver. The transcriptomic data indicates that CYA exhibits low hepatotoxicity. However, there are indications that it may have an impact on steroid biosynthesis.ConclusionThis study could serve as a basis for conducting further studies on the use of CYA in food animals and improving the pharmacologic, pharmacokinetic, and toxicologic effects of CYA on food animals.

This study aimed to examine the antifungal effects of nine monoterpenes on Sclerotinia sclerotiorum via the mycelial growth rate method. The effects of carvacrol on the morphological structures of hyphae were investigated by scanning electron microscopy (SEM). The oxalic acid (OA), total protein contents, and the activity of cell wall-degrading enzymes, including chitinase, cellulase and β-1,3-glucanase, were assessed. The results showed that the antifungal rates of carvacrol, thymol and eugenol reached 100% at a concentration of 400 mg/L, and the EC50 values of carvacrol, thymol, and eugenol were 43.40, 56.22, and 86.63 mg/L, respectively. The treatment of S. sclerotiorum with carvacrol had no significant effect on sclerotia formation, but the mycelial surface was shrivelled, uneven and broken, with cytoplasm flowing out. The OA content of S. sclerotiorum was significantly reduced to 133.78 µg/mL after treatment with carvacrol. Additionally, the total protein content of S. sclerotiorum mycelia in the carvacrol treatment group was significantly reduced to 15.67 µg/mL compared with that of the control group, and the activity of cellulase in the carvacrol treatment group was significantly higher than that in the control group.

Abstract The hot corrosion experiments of René N5 alloy coated with three different NiCrAlY metal bonding layers are carried out, that the layers are prepared by different methods (APS, HVAF and MIP). Compared with bare René N5 alloy samples, the hot corrosion resistance of coated samples is improved. It can be attributed to the small internal stress of the surface oxide layer on the coating sample, which is difficult to spall, reducing the degree of hot corrosion reaction. The hot corrosion resistance of NiCrAlY layers is MIP > HVAF > APS, which is positively positively related to the density of layers, because the influence of element diffusion in the process of hot corrosion is effectively slowed down.

Dimocarpus longan Lour. is an evergreen tree of the genus Longan in the Sapindaceae family, native to tropical and subtropical regions. Longan embryonic development is closely related to fruit set and fruit quality. An in-depth study of the mechanism of longan embryonic development could therefore contribute to the development of the longan industry. DIMBOA is the principal compound representing benzoxazinoids (BXs), and is closely linked to auxin biosynthesis and signal transduction. Auxin is one of the crucial hormones for inducing somatic embryogenesis (SE) in plants. Previous research has shown that DIMBOA promotes morphogenesis in the early somatic embryogenesis of longan, but the specific regulatory mechanism has not yet been clarified. To elucidate the molecular mechanism by which DIMBOA affects early somatic embryogenesis in longan, we chose longan embryogenic cultures grown under 0 mg/L DIMBOA as the control group (the check, CK), and longan embryogenic cultures grown under 0.1 mg/L DIMBOA as the treatment group (D) to be analyzed by transcriptomic sequencing. A total of 478 differentially expressed genes (DEGs) are detected in check vs. D, of which 193 are upregulated and 285 are downregulated. These DEGs are significantly enriched in the biosynthetic and metabolic functions of various substances such as vitamin B6 (VB6) biosynthesis, phenylpropanoid pathways, and carbohydrate metabolism. DIMBOA affects SE processes in longan via TFs, including MYB, ZF, bHLH, LBD, NAC, WRKY, etc. After DIMBOA treatment, the expression of most of the key genes for IAA synthesis was significantly downregulated, VB6 content was significantly reduced, and H2O2 content was significantly increased. Therefore, it is suggested that DIMBOA directly or indirectly affects the H2O2 content through the VB6 metabolic pathway, thereby regulating the endogenous IAA level to modulate the early SE morphogenesis of longan.

Human brain gray matter (GM) has usually been clustered into multiple functional networks. The white matter (WM) fiber bundles are known to interconnect these networks simultaneously, engaging in numerous cognitive functions. However, the exact interconnections between GM and WM are still unclear, whether functional signals in WM rewires GM community organization remains to be explored. In this study, we divided brain functional connections into three types by using edge-centric method, including intra-GM, intra-WM and GM-WM connections, and calculated the edge community evaluation indexes for quantifying GM community engagement. The results showed that the involvement of WM significantly enhanced community entropy in the heteromodal system, while the sensory-attention system remained barely changed. In addition, delta community entropy showed a significant correlation with clinical cognitive scale. Our results suggested that WM rewired GM community organization, enhancing the community engagement of brain regions in the heteromodal system. This involvement was observed to be disrupted in disease groups. Our study revealed that considering the functional signals of GM and WM simultaneously could better understand the brain's functional organization.

Abstract Introduction Subjective cognitive decline (SCD) refers to individuals’ perceived decline in memory and/or other cognitive abilities relative to their previous level of performance. Sensory decline is one of the main manifestations of decline in older adults with SCD. The efficient integration of visual and auditory information, known as audiovisual integration, is a crucial perceptual process. This study aims to evaluate audiovisual integration in older adults with SCD. Methods We adopted the audiovisual detection task, the Colavita task, and the Sound‐Induced Flash Illusion (SIFI) task to evaluate the audiovisual integration by examining both redundant and illusory effects. Older adults diagnosed with SCD (N = 50, mean age = 67.8 years) and a control group of non‐SCD older adults (N = 51, mean age = 66.5 years) were recruited. All participants took part in the three aforementioned experiments. Results The outcomes showed that a redundant effect occurred in both SCD and non‐SCD older adults, with SCD older adults gaining more benefits in audiovisual detection task. Moreover, an equivalent amount of the visual dominance effect was observed among both SCD and non‐SCD older adults in Colavita task. In addition, older adults with SCD perceived an equal fission illusion but a bigger fusion illusion compared with non‐SCD older adults in SIFI task. Conclusions Overall, older adults with SCD exhibit increased audiovisual redundant effects and stronger fusion illusion susceptibility compared to non‐SCD older adults. Besides, visual dominance was observed in both groups via the Colavita task, with no significant difference between non‐SCD and SCD older adults. These findings implied that audiovisual integration might offer a potential way for the identification of SCD.

Background: In this study, we explored the interplay between exogenous orienting attention and emotional audiovisual integration (AVI) via electroencephalography (EEG). Methods: We designed a 2 (cue validity: valid, invalid) × 3 (emotion types: happiness, neutral and sadness) × 3 (modality: visual, auditory, audiovisual) discrimination task on the basis of the cue–target paradigm. Twenty-two participants (average age: 21.71 ± 1.84 years; 13 females, 9 males) were enrolled in this experiment. Participants were asked to respond to three emotional stimuli presented in different modalities by pressing a corresponding key. Results: The results indicated faster responses to multisensory stimuli than to unisensory stimuli and to the valid cue condition than to the invalid cue condition, which indicated multisensory advantage and cueing effect occurred. In addition, happiness stimuli induced the fastest response compared with neutral and sadness emotion stimuli. EEG findings indicated a reduction in audiovisual integration induced by valid exogenous orienting in the frontal, central and parietal lobe regions. Moreover, neutral emotional stimuli elicited greater audiovisual integration than stimuli expressing happiness and sadness did. Conclusions: Overall, valid exogenous cues and emotional processing decreased audiovisual integration. The present study sheds light on how exogenous attention modulates emotional audiovisual integration and highlights the complex interactions among attention, sensory processing, and the emotional context in multisensory perception.

The pinhole plate is a key component of the point diffraction interferometer (PDI). The reasonable improvement and simulation of this device would enhance the application of point diffraction interferometry technology during the measurement of wavefronts. The traditional point diffraction interferometry measurement method is easily disturbed by environmental noise, making it difficult to obtain high-precision dynamic measurements. This paper introduces a four-step phase-shift PDI that can be employed in a common optical path. By using the principle of the finite-difference time-domain method (FDTD), a simulation model of the orthogonal polarization point diffraction pinhole plate (OP-PDPP) structure is established. The results show that when Cr is used as the film material in the pinhole plate, the parameters include a film thickness of 150 nm, a pinhole diameter of 2 μm, a wire grid period of 150 nm, and a wire grid width of 100 nm; in addition, the comprehensive extinction ratio of the pinhole plate is the greatest and the diffraction wavefront error is the smallest. Finally, the constructed experimental system is used to test the wavefront of a flat sample with a 25.4 mm aperture, and the test results are compared with those of the ZYGO interferometer. The difference in the peak-to-valley (PV) value between the OP-PDI and the ZYGO interferometer measurement is 0.0028λ, with an RMS value difference of 0.0011λ; this verifies the feasibility of the scheme proposed in this paper. The experimental results show that the proposed OP-PDPP is an effective tool for high-precision dynamic measurement.

Background: To investigate the expression of high mobility group box B-1 (HMGB-1) in patients with colorectal cancer (CRC) and its association with clinicopathological features and prognosis in colorectal carcinoma by combining bioinformatics and clinical data analysis, and to clarify the role of HMGB-1. To examine whether HMGB-1 expression is related to the damage of the intestinal mucosal barrier, and then explore the potential HMGB-1-dependent mechanisms affecting the progression of CRC. Methods: CRC datasets of GSE12945, GSE17536, and GSE17537 from the public gene chip database were screened and downloaded. Clinical information and CRC tissue samples from patients with stage I-III CRC from the hospital were collected. Serum samples of patients were applied by enzyme-linked immunosorbent assay on HMGB-1, and were divided into high and low HMGB-1 expression, which was examined by 16S rDNA sequencing. Immunohistochemistry was performed to examine the relationship between the expression of HMGB-1 and tight junction protein, occludin, tumor necrosis factor-α, and interferon-γ. Results: Based on the Cutoff value of 10.24 ng/mL, the CRC patients were divided into high and low expression groups. In the HMGB-1H patient group, the TNM staging, overall survival, disease-free survival, recurrence, and metastasis were inferior to the HMGB-1L group. The results of 16S rDNA sequencing demonstrated that the Providencia genus was found to be enriched in the HMGB-1L group. Immunohistochemical results showed that HMGB-1 expression was negatively correlated with the expression of ZO-1 and occludin ( R = 0.035, R = 0.003, P

To solve the problems of information loss and nonlinear transformation of hyperspectral image dimensionality reduction methods and the problem that recognition methods are sensitive to noise and cannot be trained online, a new hyperspectral image identification method based on locality sensitive discriminant analysis (LSDA) and online sequential extreme learning machine (OSELM) is proposed. Firstly, LSDA is used to reduce the redundant information and data noise, and the local structure and discriminant information of the hyperspectral image are extracted on the basis of reducing the data dimension. Then, a real-time recognition model based on OSELM is constructed to identify various terrain targets in hyperspectral images through online real-time updates of data. According to the experimental results of the Pavia University dataset and Salinas dataset, the proposed LSDA-OSELM not only achieved the maximum overall accuracy (OA) of 97.56 and 97.88 but also obtained the maximum kappa coefficient of 0.9726 and 0.9774. Compared with several new dimensionality reduction methods and identification methods, the proposed LSDA-OSELM has achieved a leading position in both OA and kappa indicators. The proposed method improves the generalization ability and accuracy of hyperspectral image target recognition models. In the future, its computational complexity and parameter robustness are expected to be further improved and applied in practical application scenarios.

Abstract Background Noninvasive assessment of high-risk varices (HRV) in idiopathic portal hypertension (IPH) is rare. The purpose of this study was to investigate the performance of spleen stiffness (SS) for evaluating the presence of HRV in IPH patients as compared the measurements in patients with hepatitis B virus (HBV). Methods A retrospective single-center study was performed to evaluate the performance of SS for assessing HRV in IPH and HBV-infected patients, in comparison with liver stiffness (LS), spleen stiffness-to-liver stiffness ratio (SS/LS), LS spleen-diameter-to-platelet-ratio score (LSPS), portal hypertension risk score (PH risk score) and varices risk score, by using upper gastrointestinal endoscopy (UGE) as the gold standard. Finally, 86 IPH and 102 HBV-infected patients were enrolled. UGE, two-dimensional shear wave elastography (2D-SWE) and laboratory data were collected, and noninvasive parameters were calculated. Analysis of receiver operating characteristic (ROC) curves was conducted to acquire the optimal area under the ROC curve (AUC) and cutoff value for predicting the presence of HRV. Results In patients with HRV, the significantly different parameters between IPH (34.9%) and HBV-infected patients (46.1%) were as follows: spleen size (diameter 18.5 ± 3.9 cm vs. 20.8 ± 2.7 cm), SS (50.2 kPa vs. 42.9 kPa), LS (11.1 kPa vs. 18.3 kPa) and PT (prothrombin time 15.1 s vs. 16.7 s). No statistically significant differences were found in liver function, platelet counts, spleen thickness and flow volumes in the portal venous system (p > 0.05). The AUCs of SS were 0.98 and 0.96 for predicting the presence of HRV in IPH (44.0 kPa cutoff value; 0.93 sensitivity; 0.96 specificity) and HBV-infected patients (35.2 kPa cutoff value; 1.00 sensitivity; 0.82 specificity), respectively, which were significantly better than other parameters. Conclusion SS shows the optimal overall performance for predicting the presence of HRV in IPH and HBV-infected patients, in comparison with other noninvasive parameters.

Benzoxazinoids (BXs) are tryptophan-derived indole metabolites and play a role in various physiological processes, such as auxin metabolism. Auxin is essential in the process of somatic embryogenesis (SE) in plants. In this study, we used bioinformatics, transcriptome data, exogenous treatment experiments, and qPCR analysis to study the evolutionary pattern of Bx genes in green plants, the regulatory mechanism of DlBx genes during early SE, and the effect of 2,4-dihydroxy-7-methoxy-1,4-benzoxazine-3-one (DIMBOA) on the early SE in Dimocarpus longan Lour. The results showed that 27 putative DlBxs were identified in the longan genome; the Bx genes evolved independently in monocots and dicots, and the main way of gene duplication for the DlBx was tandem duplication (TD) and the DlBx were strongly constrained by purification selection during evolution. The transcriptome data indicated varying expression levels of DlBx during longan early SE, and most DlBxs responded to light, temperature, drought stress, and 2,4-dichlorophenoxyacetic acid (2,4-D) treatment; qRT-PCR results showed DlBx1, DlBx6g and DlBx6h were responsive to auxin, and treatment with 0.1mg/L DIMBOA for 9 days significantly upregulated the expression levels of DlBx1, DlBx3g, DlBx6c, DlBx6f, DlB6h, DlBx7d, DlBx8, and DlBx9b. The correlation analysis showed a significantly negative correlation between the expression level of DlBx1 and the endogenous IAA contents; DIMBOA significantly promoted the early SE and significantly changed the endogenous IAA content, and the IAA content increased significantly at the 9th day and decreased significantly at the 13th day. Therefore, the results suggested that DIMBOA indirectly promote the early SE by changing the endogenous IAA content via affecting the expression level of DlBx1 and hydrogen peroxide (H2O2) content in longan.

A low-voltage circuit breaker thermal trip plays a role in power systems, including opening and closing, control, protection, and more. Their reliability directly affects the security and stability of the power distribution system. The Wiener process model is established according to the accelerated degradation data of thermal trips, and remaining life prediction is carried out. In this paper, firstly, the constant stress accelerated degradation test is carried out on a thermal trip with temperature as the accelerated stress and specific thermal deflection as the degradation eigenquantity to characterise the degradation trajectory according to the degradation data and analyse the degradation law; then, it is verified by the test of normal distribution that the degradation data of the thermal trip conform to the Wiener process. The Wiener process, using the great likelihood estimation method to estimate the parameters of the remaining life, calculates the remaining life probability density function and reliability function under different temperature stresses and obtains the remaining life of the thermal trip under each accelerated stress conditions; finally, the remaining life of the thermal trip at the initial moment is taken as the pseudo-failure life, and the Arrhenius accelerated model is utilised to launch the external thermal trip under normal stress. Finally, the Arrhenius acceleration model is used to extrapolate the lifespan of the thermal trip under normal stress.

Background/Aims:This study aimed to explore the effect of gut microbiota-regulated Kupffer cells (KCs) on colorectal cancer (CRC) liver metastasis. Methods: A series of in vivo and in vitro researches were showed to demonstrate the gut microbiota and its possible mechanism in CRC liver metastasis. Results: Fewer liver metastases were identified in the ampicillin-streptomycin-colistin and colistin groups. Increased proportions of Parabacteroides goldsteinii, Bacteroides vulgatus, Bacteroides thetaiotaomicron, and Bacteroides uniformis were observed in the colistin group. The significant expansion of KCs was identified in the ampicillin-streptomycin-colistin and colistin groups. B. vulgatus levels were positively correlated with KC levels. More liver metastases were observed in the vancomycin group. An increased abundance of Parabacteroides distasonis and Proteus mirabilis and an obvious reduction of KCs were noted in the vancomycin group. P. mirabilis levels were negatively related to KC levels. The number of liver metastatic nodules was increased in the P. mirabilis group and decreased in the B. vulgatus group. The number of KCs decreased in the P. mirabilis group and increased in the B. vulgatus group. In vitro, as P. mirabilis or B. vulgatus doses increased, there was an opposite effect on KC proliferation in dose- and time-dependent manners. P. mirabilis induced CT26 cell migration by controlling KC proliferation, whereas B. vulgatus prevented this migration. Conclusions: An increased abundance of P. mirabilis and decreased amount of B. vulgatus play key roles in CRC liver metastasis, which might be related to KC reductions in the liver.

Dwarfing is one of the common phenotypic variations in asexually reproduced progeny of banana, and dwarfed banana is not only windproof and anti-fallout but also effective in increasing acreage yield. As a key gene in the strigolactone signalling pathway, DWARF53 (D53) plays an important role in the regulation of the height of plants. In order to gain insight into the function of the banana D53 gene, this study conducted genome-wide identification of banana D53 gene based on the M. acuminata, M. balbisiana and M. itinerans genome database. Analysis of MaD53 gene expression under high temperature, low temperature and osmotic stress based on transcriptome data and RT-qPCR was used to analyse MaD53 gene expression in different tissues as well as in different concentrations of GA and SL treatments. In this study, we identified three MaD53, three MbD53 and two MiD53 genes in banana. Phylogenetic tree analysis showed that D53 Musa are equally related to D53 Asparagales and Poales. Both high and low-temperature stresses substantially reduced the expression of the MaD53 gene, but osmotic stress treatments had less effect on the expression of the MaD53 gene. GR24 treatment did not significantly promote the height of the banana, but the expression of the MaD53 gene was significantly reduced in roots and leaves. GA treatment at 100 mg/L significantly promoted the expression of the MaD53 gene in roots, but the expression of this gene was significantly reduced in leaves. In this study, we concluded that MaD53 responds to GA and SL treatments, but “Yinniaijiao” dwarf banana may not be sensitive to GA and SL.

The DC circuit breaker is a crucial equipment for eliminating faults in DC transmission lines. The electromagnetic release functions as a critical component that restricts the circuit breaker’s lifespan. It is essential to prioritize its safety and reliability during usage and predicting its remaining useful life (RUL) is paramount. This paper proposes a new prediction technique based on particle filtering (PF) and the whale optimization algorithm (WOA) for the remaining useful life of electromagnetic release. The particle filtering algorithm is a commonly used technique in practical engineering fields such as target tracking and RUL prediction. It is a mainstream method for solving the parameter estimation of non-linear non-Gaussian systems. The WOA is introduced to improve the PF algorithm in order to ensure the diversity of particles and lessen the effect of particle degradation. The WOA replaces the traditional resampling process, and after each computation is finished, the weights of the particles in the particle set are reassigned in order to improve the particle distribution and increase algorithm accuracy. The rate of loss of the spring reaction force and the striker counterforce are chosen as the degradation characteristics after the degradation factors of electromagnetic release are analyzed. The degradation curves at different temperatures of electromagnetic release are obtained using the accelerated life test, and the full-life data during normal operation are derived using the Arrhenius equation. Finally, the RUL is predicted by comparing this paper’s method with the conventional PF method. The experimental results demonstrate that the method presented in this paper can more accurately predict the RUL of the electromagnetic release and has a higher prediction accuracy.

This paper contributes to the classification of flag-transitive symmetric 2-(v,k,λ) designs with λ prime. We investigate the structure of flag-transitive, point-quasiprimitive automorphism groups (G) of such 2-designs by applying the classification of quasiprimitive permutation groups. It is shown that the automorphism groups (G) have either an abelian socle or a non-abelian simple socle. Moreover, according to the classification of finite simple groups, we demonstrate that point-quasiprimitivity implies point-primitivity of G, except when the socle of G is PSLn(q).

Abstract Inflammatory bowel disease (IBD) comprises a group of chronic inflammatory disorders of the gastrointestinal tract. Accumulating evidence shows that the development of IBD is always accompanied by the dysbiosis of the gut microbiota (GM), causing a decrease in prebiotic levels and an increase in harmful metabolite levels. This leads to persistent immune response and inflammation in the intestine, greatly impairing the physiological function of the gastrointestinal tract. Short-chain fatty acids (SCFAs) are produced by probiotic gut bacteria from a fiber-rich diet that cannot be digested directly. SCFAs with significant anti-inflammatory functions regulate immune function and prevent an excessive immune response, thereby delaying the clinical progression of IBD. In this review, we summarize the generation of SCFAs and their potential therapeutic effects on IBD. Furthermore, we suggest that SCFAs may modulate innate immune recognition and cytokine production to intervene in the progression of IBD. Additional randomized controlled trials and prospective cohort studies should also investigate the clinical impact of SCFA. Video Abstract

Sudden sensorineural hearing loss (SSNHL) is defined as an abrupt hearing loss of more than 30 dB in three contiguous frequencies within 72 h. It is an emergency disease requiring immediate diagnosis and treatment. The incidence of SSNHL in Western countries' population is estimated between 5 and 20 per 1,00,000 inhabitants. The etiology of SSNHL remains unknown. Due to the uncertainty of the cause of SSNHL, at present, no specific treatment targets the cause of SSNHL, resulting in poor efficacy. Previous studies have reported that some comorbidities are risk factors for SSNHL, and some laboratory results may provide some clues for the etiology of SSNHL. Atherosclerosis, microthrombosis, inflammation, and the immune system may be the main etiological factors for SSNHL. This study confirms that SSNHL is a multifactorial disease. Some comorbidities, such as virus infections, are suggested to be the causes of SSNHL. In summary, by analyzing the etiology of SSNHL, more targeting treatments should be used to achieve a better effect.

Introduction: In comparison to the audiovisual integration of younger adults, the same process appears more complex and unstable in older adults. Previous research has found that stimulus intensity is one of the most important factors influencing audiovisual integration.Methods: The present study compared differences in audiovisual integration between older and younger adults using dynamic hand-held tool stimuli, such as holding a hammer hitting the floor. Meanwhile, the effects of stimulus intensity on audiovisual integration were compared. The intensity of the visual and auditory stimuli was regulated by modulating the contrast level and sound pressure level.Results: Behavioral results showed that both older and younger adults responded faster and with higher hit rates to audiovisual stimuli than to visual and auditory stimuli. Further results of event-related potentials (ERPs) revealed that during the early stage of 60–100 ms, in the low-intensity condition, audiovisual integration of the anterior brain region was greater in older adults than in younger adults; however, in the high-intensity condition, audiovisual integration of the right hemisphere region was greater in younger adults than in older adults. Moreover, audiovisual integration was greater in the low-intensity condition than in the high-intensity condition in older adults during the 60–100 ms, 120–160 ms, and 220–260 ms periods, showing inverse effectiveness. However, there was no difference in the audiovisual integration of younger adults across different intensity conditions.Discussion: The results suggested that there was an age-related dissociation between high- and low-intensity conditions with audiovisual integration of the dynamic hand-held tool stimulus. Older adults showed greater audiovisual integration in the lower intensity condition, which may be due to the activation of compensatory mechanisms.

Audiovisual integration is an essential process that influences speech perception in conversation. However, it is still debated whether older individuals benefit more from audiovisual integration than younger individuals. This ambiguity is likely due to stimulus features, such as stimulus intensity. The purpose of the current study was to explore the effect of aging on audiovisual integration, using event-related potentials (ERPs) at different stimulus intensities. The results showed greater audiovisual integration in older adults at 320–360 ms. Conversely, at 460–500 ms, older adults displayed attenuated audiovisual integration in the frontal, fronto-central, central, and centro-parietal regions compared to younger adults. In addition, we found older adults had greater audiovisual integration at 200–230 ms under the low-intensity condition compared to the high-intensity condition, suggesting inverse effectiveness occurred. However, inverse effectiveness was not found in younger adults. Taken together, the results suggested that there was age-related dissociation in audiovisual integration and inverse effectiveness, indicating that the neural mechanisms underlying audiovisual integration differed between older adults and younger adults.

As older adults experience degenerations in perceptual ability, it is important to gain perception from audiovisual integration. Due to attending to one or more auditory stimuli, performing other tasks is a common challenge for older adults in everyday life. Therefore, it is necessary to probe the effects of auditory attentional load on audiovisual integration in older adults. The present study used event-related potentials (ERPs) and a dual-task paradigm [Go / No-go task + rapid serial auditory presentation (RSAP) task] to investigate the temporal dynamics of audiovisual integration. Behavioral results showed that both older and younger adults responded faster and with higher accuracy to audiovisual stimuli than to either visual or auditory stimuli alone. ERPs revealed weaker audiovisual integration under the no-attentional auditory load condition at the earlier processing stages and, conversely, stronger integration in the late stages. Moreover, audiovisual integration was greater in older adults than in younger adults at the following time intervals: 60–90, 140–210, and 430–530 ms. Notably, only under the low load condition in the time interval of 140–210 ms, we did find that the audiovisual integration of older adults was significantly greater than that of younger adults. These results delineate the temporal dynamics of the interactions with auditory attentional load and audiovisual integration in aging, suggesting that modulation of auditory attentional load affects audiovisual integration, enhancing it in older adults.

Abstract Background Mounting evidence in the cancer literature suggests that microRNAs (miRNAs) influence the progression of human cancer cells by targeting protein-coding genes. How insulin-like growth factor 1(IGF1) and miR-186-3p contribute to the development of cervical cancer (CC) remains unclear. This study examined the regulatory roles of miR-186-3p and IGF1 in CC development. Methods Gene expression levels were determined by qRT-PCR. Proliferation, migration, and apoptosis of CC and normal cells were determined by MTT, Transwell, and caspase-3 activity assays, respectively. Dual-luciferase reporter activity and RNA pull-down assays were performed to identify the target gene of miR-186-3p. Results IGF1 was the target of miR-186-3p. The expression of miR-186-3p inhibited cell proliferation and migration abilities of CC cell lines, but induced the apoptosis rate of CC cells. IGF1 could restore the inhibitory effects of miR-186-3p on the proliferation, migration, and apoptosis abilities of CC cells. Experimental results revealed that miR-186-3p could inhibit IGF1 expression, thereby reducing the viability of CC cells. Conclusions The data suggest that targeting of IGF1 by miR-186-3p could be crucial in regulating the progression of CC.

Strain sensors based on conducting polymer hydrogels are considered highly promising candidates for wearable electronic devices. However, existing conducting polymer hydrogels are susceptible to aging, damage, and failure, which can greatly deteriorate the sensing performance of strain sensors based on these substances and the accuracy of data collection under large deformation. Developing conductive polymer hydrogels with concurrent high sensing performance and self-healing capability is a critical yet challenging task to improve the stability and lifetime of strain sensors. Herein, we design a self-healable conducting polymer hydrogel by compositing poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) nanofibers and poly(vinyl alcohol) (PVA) via both physical and chemical crosslinking. This PEDOT:PSS-PVA nanocomposite hydrogel strain sensor displays an excellent strain monitoring range (>200%), low hysteresis (83.5%). Electronic skins based on such hydrogel strain sensors can perform the accurate monitoring of various physiological signals, including swallowing, finger bending, and knee bending. This work presents a novel conducting polymer hydrogel strain sensor demonstrating both high sensing performance and self-healability, which can satisfy broad application scenarios, such as wearable electronics, health monitoring, etc.

The human gut microbiome is important for human health. The development of stable microbial communities in the gastrointestinal tract is closely related to the early growth and development of host immunity. After the birth of a baby, immune cells and the gut microbiome mature in parallel to adapt to the complex gut environment. The gut microbiome is closely linked to the immune system and influences each other. This interaction is associated with various diseases in infants and young children, such as asthma, food allergies, necrotizing colitis, obesity, and inflammatory bowel disease. Thus, the composition of the infant gut microbiome can predict the risk of disease development and progression. At the same time, the composition of the infant gut microbiome can be regulated in many ways and can be used to prevent and treat disease in infants by modulating the composition of the infant gut microbiome. The most important impacts on infant gut microbiota are maternal, including food delivery and feeding. The differences in the gut microbiota of infants reflect the maternal gut microbiota, which in turn reflects the gut microbiota of a given population, which is clinically significant.

BackgroundElectroencephalogram (EEG)-based brain-computer interface (BCI) systems are widely utilized in various fields, including health care, intelligent assistance, identity recognition, emotion recognition, and fatigue detection. P300, the main event-related potential, is the primary component detected by EEG-based BCI systems. Existing algorithms for P300 classification in EEG data usually perform well when tested in a single participant, although they exhibit significant decreases in accuracy when tested in new participants. We attempted to address this lack of generalizability associated with existing classification methods using a novel convolutional neural network (CNN) model developed using logistic regression (LR).Materials and MethodsWe proposed an LR-CNN model comprising two parts: a combined LR-based memory model and a CNN-based generalization model. The LR-based memory model can learn the individual features of participants and addresses the decrease in accuracy caused by individual differences when applied to new participants. The CNN-based generalization model can learn the common features among participants, thereby reducing overall classification bias and improving overall classification accuracy.ResultsWe compared our method with existing, commonly used classification methods through three different sets of experiments. The experimental results indicated that our method could learn individual differences among participants. Compared with other commonly used classification methods, our method yielded a marked improvement (>90%) in classification among new participants.ConclusionThe accuracy of the proposed model in the face of new participants is better than that of existing, commonly used classification methods. Such improvements in cross-subject test accuracy will aid in the development of BCI systems.

Although a dysfunctional gut microbiome is strongly linked to colorectal cancer (CRC), our knowledge of the mediators between CRC and the microbiome is limited. MicroRNAs (miRNAs) affect critical cellular processes, such as apoptosis, proliferation, and differentiation, and contribute to the regulation of CRC progression. Increasingly, studies found that miRNAs can significantly mediate bidirectional interactions between the host and the microbiome. Notably, miRNA expression is regulated by the gut microbiome, which subsequently affects the host transcriptome, thereby influencing the development of CRC. This study typically focuses on the specific functions of the microbiome in CRC and their effect on CRC-related miRNA production and reviews the role of several bacteria on miRNA, including Fusobacterium nucleatum, Escherichia coli, enterotoxigenic Bacteroides fragilis, and Faecalibacterium prausnitzii. Based on the important roles of miRNAs and the gut microbiome in CRC, strategies for modulating miRNA expression and regulating the gut microbiome composition need to be applied, such as bioactive dietary components and fecal microorganism transplantation.

Pancreatic cancer is associated with highly malignant tumors and poor prognosis due to strong therapeutic resistance. Accumulating evidence shows that activated pancreatic stellate cells (PSC) play an important role in the malignant progression of pancreatic cancer. In recent years, the rapid development of single-cell sequencing technology has facilitated the analysis of PSC population heterogeneity, allowing for the elucidation of the relationship between different subsets of cells with tumor development and therapeutic resistance. Researchers have identified two spatially separated, functionally complementary, and reversible subtypes, namely myofibroblastic and inflammatory PSC. Myofibroblastic PSC produce large amounts of pro-fibroproliferative collagen fibers, whereas inflammatory PSC express large amounts of inflammatory cytokines. These distinct cell subtypes cooperate to create a microenvironment suitable for cancer cell survival. Therefore, further understanding of the differentiation of PSC and their distinct functions will provide insight into more effective treatment options for pancreatic cancer patients.

The volatile metabolites of Salvia sclarea, Rosmarinus officinalis, Thymus serpyllum, Mentha spicata, Melissa officinalis, Origanum majorana, Mentha piperita, Ocimum basilicum and Lavandula angustifolia were determined by gas chromatography–mass spectrometry. The vapor insecticidal properties of the analyzed essential oils and their compounds were screened using Reticulitermes dabieshanensis workers. The most effective oils were S. sclarea (major constituent linalyl acetate, 65.93%), R. officinalis (1,8-cineole, 45.56%), T. serpyllum (thymol, 33.59%), M. spicata (carvone, 58.68%), M. officinalis (citronellal, 36.99%), O. majorana (1,8-cineole, 62.29%), M. piperita (menthol, 46.04%), O. basilicum (eugenol, 71.08%) and L. angustifolia (linalool, 39.58%), which exhibited LC50 values ranging from 0.036 to 1.670 μL/L. The lowest LC50 values were recorded for eugenol (0.060 μL/L), followed by thymol (0.062 μL/L), carvone (0.074 μL/L), menthol (0.242 μL/L), linalool (0.250 μL/L), citronellal (0.330 μL/L), linalyl acetate (0.712 μL/L) and 1,8-cineole (1.478 μL/L). The increased activity of esterases (ESTs) and glutathione S-transferase (GST) were observed but only alongside the decreased activity of acetylcholinesterase (AChE) in eight main components. Our results indicate that S. sclarea, R. officinalis, T. serpyllum, M. spicata, M. officinalis, O. marjorana, M. piperita, O. basilicum and L. angustifolia essential oils (EOs) and their compounds, linalyl acetate, 1,8-cineole, thymol, carvone, citronellal, menthol, eugenol and linalool could be developed as control agents against termites.

Recently, advanced electrodes have been developed, such as semi-dry, dry contact, dry non-contact, and microneedle array electrodes. They can overcome the issues of wet electrodes and maintain high signal quality. However, the variations in these electrodes are still unclear and not explained, and there is still confusion regarding the feasibility of electrodes for different application scenarios. In this review, the physical features and electroencephalogram (EEG) signal performances of these advanced EEG electrodes are introduced in view of the differences in contact between the skin and electrodes. Specifically, contact features, biofeatures, impedance, signal quality, and artifacts are discussed. The application scenarios and prospects of different types of EEG electrodes are also elucidated.

Botanical pesticides are considered the most promising alternative to synthetic pesticides, considering their less negative impacts on the environment and human health. Here, we analyzed the components of lemongrass Cymbopogon citratus essential oil (EO) and evaluated its vapor activity against Reticulitermes flaviceps, in terms of the walking and gripping abilities of workers. In addition, the effects of lemongrass EO and its major component on the cuticular content and structure of chitin in termites were also observed. Our results indicate that cis-citral (36.51%) was the main constituent of lemongrass. In the vapor toxicity assay, the LC50 values of lemongrass EO and citral were 0.328 and 0.177 μL/L, respectively. When worker antennae were treated with lemongrass EO and citral, their walking and gripping capabilities were significantly inhibited. In addition, the cuticular content, thermal stability, and crystallinity of chitin in the termites were decreased after treatment with citral. Collectively, this study provides a basis for developing and utilizing lemongrass and citral as a new environment-friendly insecticide resource to control R. flaviceps.

Auditory sensory memory indexed by mismatch negativity has been broadly studied over the past century, but far less attention has been directed to tactile sensory memory. To investigate whether tactile sensory memory is affected by attention, we recorded somatosensory mismatch negativity (sMMN) from 24 healthy adults in two experiments to distinguish sustained attention from non-sustained attention. Using the roving somatosensory oddball paradigm, we analyzed the average dynamic changes in the amplitude and latency of sMMN amplitude and found a clear sMMN component at the central region at a 100–300 ms interval. The sMMN amplitude, which indexes the early detection of tactile stimuli with the sensory memory trace, was larger in the tactile attentional task. Additionally, the sMMN latency increased with the increasing visual attentional load, which indicates a decay of tactile sensory memory. Our results indicate that the more attention resources are allocated for a tactile sensation, the more favorable it is to the generation of tactile sensory memory.

The first instar and mature larva and pupa of Cassidispa relicta Medvedev, 1957, a newly recorded species from China, are described and figured. The chaetotaxy of the head, mouthparts, legs, and dorsal and ventral surfaces of the body is described. This is the first detailed description of immatures in the genus Cassidispa. Diagnostic characters of this species are compared with other described immatures of some Hispini genera. Biological notes on C. relicta, such as host plants, feeding patterns of adults, structure of larval mines and life history, are also presented.

The larch looper, Erannis ankeraria Staudinger (Lepidoptera: Geometridae), is one of the major insect pests of larch forests, widely distributed from southeastern Europe to East Asia. A naturally occurring baculovirus, Erannis ankeraria nucleopolyhedrovirus (EranNPV), was isolated from E. ankeraria larvae. This virus was characterized by electron microscopy and by sequencing the whole viral genome. The occlusion bodies (OBs) of EranNPV exhibited irregular polyhedral shapes containing multiple enveloped rod-shaped virions with a single nucleocapsid per virion. The EranNPV genome was 125,247 bp in length with a nucleotide distribution of 34.9% G+C. A total of 131 hypothetical open reading frames (ORFs) were identified, including the 38 baculovirus core genes and five multi-copy genes. Five homologous regions (hrs) were found in the EranNPV genome. Phylogeny and pairwise kimura 2-parameter analysis indicated that EranNPV was a novel group II alphabaculovirus and was most closely related to Apocheima cinerarium NPV (ApciNPV). Field trials showed that EranNPV was effective in controlling E. ankeraria in larch forests. The above results will be relevant to the functional research on EranNPV and promote the use of this virus as a biocontrol agent.

Object detection is a challenging computer vision task with numerous real-world applications. In recent years, the concept of the object relationship model has become helpful for object detection and has been verified and realized in deep learning. Nonetheless, most approaches to modeling object relations are limited to using the anchor-based algorithms; they cannot be directly migrated to the anchor-free frameworks. The reason is that the anchor-free algorithms are used to eliminate the complex design of anchors and predict heatmaps to represent the locations of keypoints of different object categories, without considering the relationship between keypoints. Therefore, to better fuse the information between the heatmap channels, it is important to model the visual relationship between keypoints. In this paper, we present a knowledge-driven network (KDNet)—a new architecture that can aggregate and model keypoint relations to augment object features for detection. Specifically, it processes a set of keypoints simultaneously through interactions between their local and geometric features, thereby allowing the modeling of their relationship. Finally, the updated heatmaps were used to obtain the corners of the objects and determine their positions. The experimental results conducted on the RIDER dataset confirm the effectiveness of the proposed KDNet, which significantly outperformed other state-of-the-art object detection methods.

Currently, soil-moisture data extracted from microwave data suffer from poor spatial resolution. To overcome this problem, this study proposes a method to downscale the soil moisture spatial resolution. The proposed method establishes a statistical relationship between low-spatial-resolution input data and soil-moisture data from a land-surface model based on a neural network (NN). This statistical relationship is then applied to high-spatial-resolution input data to obtain high-spatial-resolution soil-moisture data. The input data include passive microwave data (SMAP, AMSR2), active microwave data (ASCAT), MODIS data, and terrain data. The target soil moisture data were collected from CLDAS dataset. The results show that the addition of data such as the land-surface temperature (LST), the normalized difference vegetation index (NDVI), the normalized shortwave-infrared difference bare soil moisture indices (NSDSI), the digital elevation model (DEM), and calculated slope data (SLOPE) to active and passive microwave data improves the retrieval accuracy of the model. Taking the CLDAS soil moisture data as a benchmark, the spatial correlation increases from 0.597 to 0.669, the temporal correlation increases from 0.401 to 0.475, the root mean square error decreases from 0.051 to 0.046, and the mean absolute error decreases from 0.041 to 0.036. Triple collocation was applied in the form of [NN, FY3C, GEOS-5] based on the extracted retrieved soil-moisture data to obtain the error variance and correlation coefficient between each product and the actual soil-moisture data. Therefore, we conclude that NN data, which have the lowest error variance (0.00003) and the highest correlation coefficient (0.811), are the most applicable to Qinghai Province. The high-spatial-resolution data obtained from the NN, CLDAS data, SMAP data, and AMSR2 data were correlated with the ground-station data respectively, and the result of better NN data quality was obtained. This analysis demonstrates that the NN-based method is a promising approach for obtaining high-spatial-resolution soil-moisture data.

Kernel fuzzy c-means (KFCM) is a significantly improved version of fuzzy c-means (FCM) for processing linearly inseparable datasets. However, for fuzzification parameter m=1, the problem of KFCM (kernel fuzzy c-means) cannot be solved by Lagrangian optimization. To solve this problem, an equivalent model, called kernel probabilistic k-means (KPKM), is proposed here. The novel model relates KFCM to kernel k-means (KKM) in a unified mathematic framework. Moreover, the proposed KPKM can be addressed by the active gradient projection (AGP) method, which is a nonlinear programming technique with constraints of linear equalities and linear inequalities. To accelerate the AGP method, a fast AGP (FAGP) algorithm was designed. The proposed FAGP uses a maximum-step strategy to estimate the step length, and uses an iterative method to update the projection matrix. Experiments demonstrated the effectiveness of the proposed method through a performance comparison of KPKM with KFCM, KKM, FCM and k-means. Experiments showed that the proposed KPKM is able to find nonlinearly separable structures in synthetic datasets. Ten real UCI datasets were used in this study, and KPKM had better clustering performance on at least six datsets. The proposed fast AGP requires less running time than the original AGP, and it reduced running time by 76–95% on real datasets.

ABSTRACT We investigated the distribution, morphology and abundance of antennae sensilla of Coboldia fuscipes (Meigen) using scanning electron microscopy. Antennae of C. fuscipes consisted of scape, pedicel, and flagellum with eight flagellomeres. Antennal scape and pedicel had only one type of sensillum, i.e., sensilla chaetica. Significant differences were found between the number and distribution of these sensilla. Four types of morphologically distinct sensilla on the flagellum were identified, including sensilla chaetica, sensilla trichoidea, sensilla coeloconica, and sensilla basiconica (three subtypes). Significant differences were found in the abundance and distribution of sensilla among the antennal flagella and diverse flagellomeres in both sexes. Sensilla trichoidea is the most abundant of sensilla discovered on the antennal flagellum. Sensilla chaetica is the largest and longest sensilla among all the types of sensilla found on the antennal surface of C. fuscipes. Sensilla coeloconica is widely distributed all over the flagellum surface except for the first of female. Some significant differences in the abundance and distribution were also observed among sensilla basiconica of flagellum. The probable biological function of each sensillum type was deduced based on the basis of their structure. These results serve as important basis for further studies on the host location mechanism and mating behavior of C. fuscipes.

Clustering nonlinearly separable datasets is always an important problem in unsupervised machine learning. Graph cut models provide good clustering results for nonlinearly separable datasets, but solving graph cut models is an NP hard problem. A novel graph-based clustering algorithm is proposed for nonlinearly separable datasets. The proposed method solves the min cut model by iteratively computing only one simple formula. Experimental results on synthetic and benchmark datasets indicate the potential of the proposed method, which is able to cluster nonlinearly separable datasets with less running time.

The estimation of heart rate (HR) based on wearable devices is of interest in fitness. Photoplethysmography (PPG) is a promising approach to estimate HR due to low cost; however, it is easily corrupted by motion artifacts (MA). In this work, a robust approach based on random forest is proposed for accurately estimating HR from the photoplethysmography signal contaminated by intense motion artifacts, consisting of two stages. Stage 1 proposes a hybrid method to effectively remove MA with a low computation complexity, where two MA removal algorithms are combined by an accurate binary decision algorithm whose aim is to decide whether or not to adopt the second MA removal algorithm. Stage 2 proposes a random forest-based spectral peak-tracking algorithm, whose aim is to locate the spectral peak corresponding to HR, formulating the problem of spectral peak tracking into a pattern classification problem. Experiments on the PPG datasets including 22 subjects used in the 2015 IEEE Signal Processing Cup showed that the proposed approach achieved the average absolute error of 1.65 beats per minute (BPM) on the 22 PPG datasets. Compared to state-of-the-art approaches, the proposed approach has better accuracy and robustness to intense motion artifacts, indicating its potential use in wearable sensors for health monitoring and fitness tracking.