Evidence for Chiral Wobbler in Nuclei

Three ΔI=1 bands with the πg_{9/2}⊗νg_{9/2} configuration have been identified in _{35}^{74}Br_{39}. Angular distribution, linear polarization, and lifetime measurements were performed to determine the multipolarity, type, mixing ratio, and absolute transition probability of the transitions. By comparing these experimental observations with the corresponding fingerprints and the quantum particle rotor model calculations, the second and third lowest bands are, respectively, suggested as the chiral partner and one-phonon wobbling excitation built on the yrast band. The evidence indicates the first chiral wobbler in nuclei.

Modified prairie dog optimization algorithm for global optimization and constrained engineering problems

The prairie dog optimization (PDO) algorithm is a metaheuristic optimization algorithm that simulates the daily behavior of prairie dogs. The prairie dog groups have a unique mode of information exchange. They divide into several small groups to search for food based on special signals and build caves around the food sources. When encountering natural enemies, they emit different sound signals to remind their companions of the dangers. According to this unique information exchange mode, we propose a randomized audio signal factor to simulate the specific sounds of prairie dogs when encountering different foods or natural enemies. This strategy restores the prairie dog habitat and improves the algorithm's merit-seeking ability. In the initial stage of the algorithm, chaotic tent mapping is also added to initialize the population of prairie dogs and increase population diversity, even use lens opposition-based learning strategy to enhance the algorithm's global exploration ability. To verify the optimization performance of the modified prairie dog optimization algorithm, we applied it to 23 benchmark test functions, IEEE CEC2014 test functions, and six engineering design problems for testing. The experimental results illustrated that the modified prairie dog optimization algorithm has good optimization performance.

Prognostic Significance of Serum Lipids in Patients with Non-Small Cell Lung Cancer Treated with Radiotherapy: A Multicenter Prospective Study

PURPOSE/OBJECTIVE(S)

Although lipids have been assessed for their possible roles in cancer survival prediction, studies on the association between serum lipids levels and the prognosis of non-small cell lung cancer (NSCLC) patients are limited. This study aimed to evaluate whether serum lipids are associated with outcomes in patients with NSCLC treated with radiotherapy.

MATERIALS/METHODS

We conducted a multicenter prospective study on patients diagnosed with NSCLC between January 2018 and February 2021. Participants received thoracic radiotherapy of 60ཞ80 Gy to the primary lung tumor and positive lymph node metastases. We measured patients' serum lipids levels (serum triglyceride, TGs; total cholesterol, TC, high density lipoprotein cholesterol, HDL-C; low density lipoprotein cholesterol, LDL-C) before radiotherapy. The association between serum lipids levels and overall survival (OS) was evaluated using hazard ratios. We sought to determine a threshold point using optimal stratification. Survival analysis was performed using Kaplan-Meier curves.

RESULTS

Of the 300 participants diagnosed with NSCLC treated with radiotherapy, 165 (55.0%) were men. Median follow-up time was 24.4 months (range 1.0- 101.9 months). Using univariate and multivariate Cox proportional hazard analysis, among those serum lipids, only serum TG was shown to be independent prognostic factors for OS (hazard ratio: 1.203, 95% confidence interval: 1.038 - 1.393, p = 0.014). The cut-off for TG associated with OS was 2.04 mmol/L. Based on the TG cut-off value, 55 NSCLC patients were categorized into the high TG group (>2.04 mmol/L) and 245 in the low TG group (<2.04 mmol/L). The NSCLC patients in the low TG group exhibited higher OS than the high group (median OS, not reach vs 41.4 months, p = 0.025).

CONCLUSION

TG levels were found to be a significant negative prognostic biomarker for OS in NSCLC patients treated with radiotherapy.

An improved fused feature residual network for 3D point cloud data

Point clouds have evolved into one of the most important data formats for 3D representation. It is becoming more popular as a result of the increasing affordability of acquisition equipment and growing usage in a variety of fields. Volumetric grid-based approaches are among the most successful models for processing point clouds because they fully preserve data granularity while additionally making use of point dependency. However, using lower order local estimate functions to close 3D objects, such as the piece-wise constant function, necessitated the use of a high-resolution grid in order to capture detailed features that demanded vast computational resources. This study proposes an improved fused feature network as well as a comprehensive framework for solving shape classification and segmentation tasks using a two-branch technique and feature learning. We begin by designing a feature encoding network with two distinct building blocks: layer skips within, batch normalization (BN), and rectified linear units (ReLU) in between. The purpose of using layer skips is to have fewer layers to propagate across, which will speed up the learning process and lower the effect of gradients vanishing. Furthermore, we develop a robust grid feature extraction module that consists of multiple convolution blocks accompanied by max-pooling to represent a hierarchical representation and extract features from an input grid. We overcome the grid size constraints by sampling a constant number of points in each grid using a simple K-points nearest neighbor (KNN) search, which aids in learning approximation functions in higher order. The proposed method outperforms or is comparable to state-of-the-art approaches in point cloud segmentation and classification tasks. In addition, a study of ablation is presented to show the effectiveness of the proposed method.

Hybrid Slime Mold and Arithmetic Optimization Algorithm with Random Center Learning and Restart Mutation

The slime mold algorithm (SMA) and the arithmetic optimization algorithm (AOA) are two novel meta-heuristic optimization algorithms. Among them, the slime mold algorithm has a strong global search ability. Still, the oscillation effect in the later iteration stage is weak, making it difficult to find the optimal position in complex functions. The arithmetic optimization algorithm utilizes multiplication and division operators for position updates, which have strong randomness and good convergence ability. For the above, this paper integrates the two algorithms and adds a random central solution strategy, a mutation strategy, and a restart strategy. A hybrid slime mold and arithmetic optimization algorithm with random center learning and restart mutation (RCLSMAOA) is proposed. The improved algorithm retains the position update formula of the slime mold algorithm in the global exploration section. It replaces the convergence stage of the slime mold algorithm with the multiplication and division algorithm in the local exploitation stage. At the same time, the stochastic center learning strategy is adopted to improve the global search efficiency and the diversity of the algorithm population. In addition, the restart strategy and mutation strategy are also used to improve the convergence accuracy of the algorithm and enhance the later optimization ability. In comparison experiments, different kinds of test functions are used to test the specific performance of the improvement algorithm. We determine the final performance of the algorithm by analyzing experimental data and convergence images, using the Wilcoxon rank sum test and Friedman test. The experimental results show that the improvement algorithm, which combines the slime mold algorithm and arithmetic optimization algorithm, is effective. Finally, the specific performance of the improvement algorithm on practical engineering problems was evaluated.

An improved multi-strategy beluga whale optimization for global optimization problems

This paper presents an improved beluga whale optimization (IBWO) algorithm, which is mainly used to solve global optimization problems and engineering problems. This improvement is proposed to solve the imbalance between exploration and exploitation and to solve the problem of insufficient convergence accuracy and speed of beluga whale optimization (BWO). In IBWO, we use a new group action strategy (GAS), which replaces the exploration phase in BWO. It was inspired by the group hunting behavior of beluga whales in nature. The GAS keeps individual belugas whales together, allowing them to hide together from the threat posed by their natural enemy, the tiger shark. It also enables the exchange of location information between individual belugas whales to enhance the balance between local and global lookups. On this basis, the dynamic pinhole imaging strategy (DPIS) and quadratic interpolation strategy (QIS) are added to improve the global optimization ability and search rate of IBWO and maintain diversity. In a comparison experiment, the performance of the optimization algorithm (IBWO) was tested by using CEC2017 and CEC2020 benchmark functions of different dimensions. Performance was analyzed by observing experimental data, convergence curves, and box graphs, and the results were tested using the Wilcoxon rank sum test. The results show that IBWO has good optimization performance and robustness. Finally, the applicability of IBWO to practical engineering problems is verified by five engineering problems.

Modified reptile search algorithm with multi-hunting coordination strategy for global optimization problems

The reptile search algorithm (RSA) is a bionic algorithm proposed by Abualigah. et al. in 2020. RSA simulates the whole process of crocodiles encircling and catching prey. Specifically, the encircling stage includes high walking and belly walking, and the hunting stage includes hunting coordination and cooperation. However, in the middle and later stages of the iteration, most search agents will move towards the optimal solution. However, if the optimal solution falls into local optimum, the population will fall into stagnation. Therefore, RSA cannot converge when solving complex problems. To enable RSA to solve more problems, this paper proposes a multi-hunting coordination strategy by combining Lagrange interpolation and teaching-learning-based optimization (TLBO) algorithm's student stage. Multi-hunting cooperation strategy will make multiple search agents coordinate with each other. Compared with the hunting cooperation strategy in the original RSA, the multi-hunting cooperation strategy has been greatly improved RSA's global capability. Moreover, considering RSA's weak ability to jump out of the local optimum in the middle and later stages, this paper adds the Lens pposition-based learning (LOBL) and restart strategy. Based on the above strategy, a modified reptile search algorithm with a multi-hunting coordination strategy (MRSA) is proposed. To verify the above strategies' effectiveness for RSA, 23 benchmark and CEC2020 functions were used to test MRSA's performance. In addition, MRSA's solutions to six engineering problems reflected MRSA's engineering applicability. It can be seen from the experiment that MRSA has better performance in solving test functions and engineering problems.

MGF360-12L of ASFV-SY18 is an immune-evasion protein that inhibits host type I IFN, NF-κB, and JAK/STAT pathways

African swine fever virus (ASFV) causes feverous and hemorrhagic disease of domestic pigs and European wild boars with high mortality, yet no commercial vaccine is currently available. Several ASFV strains with natural deletion or gene-targeted knockout of multiple MGF360 and MGF505 genes are attenuated in vitro and in vivo, and can offer full protection against homologous challenge. However, the mechanisms underlying the protection are not fully understood. This study aims to investigate the effects of MGF360-12L of ASFV-SY18 on the cGAS-STING signaling pathway and explore the potential mechanisms. We identified that ASFV-SY18 MGF360-12L could inhibit cGAS-STING, TBK1, or IRF3-5D-stimulated IFN-β expression and ISRE activation. Specifically, MGF360-12L inhibits both the activation of PRD(III-I) in a dose-dependent manner, and suppresses the exogenous expression of TBK1 and IRF3-5D. MGF360-12L could block NF-κB activation induced by overexpression of cGAS-STING, TBK1, IKKβ. Downstream of the IFN-β signaling, MGF360-12L blocks the ISRE promoter activation by reducing total protein level of IRF9. Moreover, MGF360-12L protein can inhibit IFN-β-mediated antiviral effects. In conclusion, our findings suggest that MGF360-12L is a multifunctional immune-evasion protein that inhibits both the expression and effect of IFN-β, which could partially explain the attenuation of relevant gene-deleted ASFV strains, and shed light on the development of efficient ASFV live attenuated vaccines in the future.

Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation

This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. The proposed method introduces a better search space to find the optimal solution at each iteration. However, we proposed RSA-SSA to avoid the searching problem in the same area and determine the optimal multi-level thresholds. The obtained solutions by the proposed method are represented using the image histogram. The proposed RSA-SSA employed Otsu's variance class function to get the best threshold values at each level. The performance measure for the proposed method is valid by detecting fitness function, structural similarity index, peak signal-to-noise ratio, and Friedman ranking test. Several benchmark images of COVID-19 validate the performance of the proposed RSA-SSA. The results showed that the proposed RSA-SSA outperformed other metaheuristics optimization algorithms published in the literature.

Effects of Beta-Hydroxy-Beta-Methylbutyrate Supplementation on Older Adults with Sarcopenia: A Randomized, Double-Blind, Placebo-Controlled Study

OBJECTIVES

Sarcopenia is recognized as a major public health concern because of its association with several adverse health events. Beta-hydroxy-beta-methylbutyrate (HMB) supplementation reportedly delays the loss of muscle mass and function; however, the effect of HMB on sarcopenia remains inconclusive. We aimed to evaluate the impact of HMB intervention on muscle strength, physical performance, body compositions, and inflammatory factors in older adults with sarcopenia.

DESIGN

Randomized, double-blind, placebo-controlled trial.

SETTING AND PARTICIPANTS

This study included subjects aged ≥60 years with sarcopenia which were assigned to the HMB group (HMBG, n=18) and the placebo group (PG, n=16).

INTERVENTION

The HMBG and PG were supplied with HMB and placebo products twice daily for 12 weeks, and both received resistance exercise training twice a week in 12 weeks.

MEASUREMENTS

Hand grip strength was selected as the primary outcome; gait speed, five-time chair stand test, body composition and inflammatory indicators were selected as the secondary outcomes. The differences in changes from baseline between the two groups were analyzed using the analysis of covariance(ANCOVA).

RESULTS

After the 12-week intervention, the HMBG demonstrated significantly greater improvements in handgrip strength (4.61(95%CI:2.93,6.28) kg, P<0.001), gait speed (0.11(95%CI:0.02,0.20)m/s, P=0.014), five-time chair stand test (-3.65 (95%CI:-5.72, -1.58)s, P=0.001), muscle quality (2.47(95%CI:1.15,3.80),kg.kg-1 P=0.001) and tumor necrosis factor-like weak inducer of apoptosis (-15.23(95%CI:-29.80,-0.66)pmol/mL, P=0.041) compared with the PG; no significant differences in skeletal muscle mass, skeletal muscle index, and other body composition parameters were found between the two groups.

CONCLUSION

In older adults with sarcopenia, HMB significantly enhance the effect of resistance exercise training on muscle strength, physical performance, muscle quality, and reduced inflammatory factors. Therefore, HMB supplementation could be an effective treatment for sarcorpenia. The trial protocol was registered at http://www.chictr.org.cn/showproj.aspx?proj=47571 as ChiCTR2000028778.

Enhanced Aquila optimizer algorithm for global optimization and constrained engineering problems

The Aquila optimizer (AO) is a recently developed swarm algorithm that simulates the hunting behavior of Aquila birds. In complex optimization problems, an AO may have slow convergence or fall in sub-optimal regions, especially in high complex ones. This paper tries to overcome these problems by using three different strategies: restart strategy, opposition-based learning and chaotic local search. The developed algorithm named as mAO was tested using 29 CEC 2017 functions and five different engineering constrained problems. The results prove the superiority and efficiency of mAO in solving many optimization issues.

[Differential diagnosis and management of hemangioma at geniculate ganglion]

Objective: To investigate the clinical characteristics, differential diagnosis, treatments and prognosis of facial nerve hemangioma and schwannoma at genicular ganglion, so as to provide reference for clinical diagnosis and treatments of facial nerve tumor at genicular ganglion. Methods: Clinical data of 13 patients with facial nerve tumors at genicular ganglion confirmed by postoperative pathology in the Ninth People's Hospital affiliated to Shanghai Jiaotong University School of Medicine from March 2018 to April 2020 were retrospectively analyzed, including seven cases of hemangioma and six cases of schwannoma. There were eight males and five females. Their ages ranged from 20 to 65, with an average age of 40. The course of disease ranged from 3 to 118 months, with an average of 52 months. All the patients underwent preoperative HRCT of the temporal bone and facial nerve dynamic contrast-enhanced(DCE) MRI examinations. All the patients had detailed surgical procedures and at least one-year postoperative follow-up. Results: On HRCT of the temporal bone, (4/7) hemangioma at geniculate ganglion showed characteristic honeycomb appearance, while 6/6 schwannoma and 3/7 hemangiomas showed expansive bone changes. On DCE-MRI, geniculate ganglion hemangioma (7/7) showed characteristic "point-to-surface" enhancement, and schwannoma (6/6) showed characteristic "face-to-surface" enhancement. For five hemangioma-patients with HB-Ⅱ-Ⅳ before surgery, the facial nerve anatomy was completely preserved through transcanal endoscopic approach(TEA), and the facial nerve function improved one year after surgery (two cases of HB-I, two cases of HB-Ⅱ, and one case of HB-Ⅲ). For two patients, with preoperative facial nerve function HB-Ⅴ-Ⅵ, since their tumors was inseparable from the nerves, they were performed with facial nerve anastomosis during the surgery, and the facial nerve function was improved to HB-Ⅳ level one year after surgery. For six patients with meningioma whose facial nerve function was greater than or equal to HB-Ⅲ, based on the preoperative hearing level, the involved segments, and duration of facial paralysis, three of them were conducted surgeries through middle cranial fossa approach, one by translabyrinthine approach, and one via mastoid approach. Two patients among them with complete facial paralysis over three years preoperatively were not performed facial nerve anastomosis after total resections of the tumors, and there was no improvement in facial nerve function one year after surgery. Three patients underwent facial nerve anastomosis after total tumor resections, and their facial nerve function was HB-Ⅲ in one patient, HB-Ⅳ in two patients one year after surgery. One patient (preoperative HB-Ⅲ) had a normal hearing level preoperatively, and the tumor involved the labyrinth segment. To protect the hearing, partial tumor was resected through the middle cranial fossa approach, and facial nerve function improved to HB-Ⅱ one year after surgery. Conclusions: Temporal bone HRCT combined with DCE-MRI are useful for the differential diagnosis of hemangioma and schwannoma at geniculate ganglion and provide references for preoperative clinical decision makings. It is extremely necessary to select the appropriate surgical approach based on the patient's hearing and involved segments. For geniculate ganglion hemangioma, early surgery can improve the possibilities of anatomical integrity of facial nerve, thereby improving facial nerve function postoperatively.TEA is a kind of surgical method worth consideration, with the characteristics of minimally invasive, favorable postoperative features, and so on. For schwannoma, one-stage functional reconstruction of the facial nerve is recommended during the resection of the tumors because of the inevitable damage to the anatomical integrity of the facial nerve.

Hydrogen sulphide regulates the growth of tomato root cells by affecting cell wall biosynthesis under CuO NPs stress

Copper oxide nanoparticles (CuO NPs) show strong nano-toxic effects on organisms. Hydrogen sulphide (H₂ S) plays a pivotal role in plant response to abiotic stress. In this study, we examine the crucial role of the cell wall as regulated by H₂ S in response to CuO NPs stress. The digestion method was employed to determine Cu content using atomic absorption spectrometry. The TraKine pro-tubulin staining kit was used to investigate the microtubule cytoskeleton using confocal laser-scanning microscopy. Cell wall component analysis utilized the ICS-3000 HPLC system. Application of H₂ S reduced growth inhibition caused by CuO NPs. Furthermore, most of the CuO NPs accumulates in roots, indicating a low transfer rate, and H₂ S significantly decreased CuO NPs content in roots, leaves and stems. Subcellular distribution analysis implied most Cu accumulated in root cell walls, and that H₂ S reduced the content of Cu in root cell walls. Cortical microtubules in the plasma membrane, guide cell wall biosynthesis. H₂ S obviously alleviated microtubule cytoskeleton disorders caused by CuO NPs. In addition, the content of cellulose, hemicellulose, pectin and other monosaccharides in root cell walls was reduced by CuO NPs treatment. H₂ S enhanced the monosaccharide and polysaccharide contents compared with that after CuO NPs treatment. In conclusion, H₂ S regulates cell wall development in response to CuO NPs stress by stabilizing microtubules. H₂ S affected Cu distribution and alleviated growth inhibition of tomato seedlings. The research results provide a theoretical basis for further study of nano-toxicity regulation in plants.

Enhanced slime mould algorithm with multiple mutation strategy and restart mechanism for global optimization

 Slime mould algorithm (SMA) is a new metaheuristic algorithm proposed in 2020, which has attracted extensive attention from scholars. Similar to other optimization algorithms, SMA also has the drawbacks of slow convergence rate and being trapped in local optimum at times. Therefore, the enhanced SMA named as ESMA is presented in this paper for solving global optimization problems. Two effective methods composed of multiple mutation strategy (MMS) and restart mechanism (RM) are embedded into the original SMA. MMS is utilized to increase the population diversity, and the RM is used to avoid the local optimum. To verify the ESMA’s performance, twenty-three classical benchmark functions are employed, as well as three well-known engineering design problems, including welded beam design, pressure vessel design and speed reducer design. Several famous optimization algorithms are also chosen for comparison. Experimental results show that the ESMA outperforms other optimization algorithms in most of the test functions with faster convergence speed and higher solution accuracy, which indicates the merits of proposed ESMA. The results of Wilcoxon signed-rank test also reveal that ESMA is significant superior to other comparative optimization algorithms. Moreover, the results of three constrained engineering design problems demonstrate that ESMA is better than comparative algorithms.

An improved remora optimization algorithm with autonomous foraging mechanism for global optimization problems

The remora optimization algorithm (ROA) is a newly proposed metaheuristic algorithm for solving global optimization problems. In ROA, each search agent searches new space according to the position of host, which makes the algorithm suffer from the drawbacks of slow convergence rate, poor solution accuracy, and local optima for some optimization problems. To tackle these problems, this study proposes an improved ROA (IROA) by introducing a new mechanism named autonomous foraging mechanism (AFM), which is inspired from the fact that remora can also find food on its own. In AFM, each remora has a small chance to search food randomly or according to the current food position. Thus the AFM can effectively expand the search space and improve the accuracy of the solution. To substantiate the efficacy of the proposed IROA, twenty-three classical benchmark functions and ten latest CEC 2021 test functions with various types and dimensions were employed to test the performance of IROA. Compared with seven metaheuristic and six modified algorithms, the results of test functions show that the IROA has superior performance in solving these optimization problems. Moreover, the results of five representative engineering design optimization problems also reveal that the IROA has the capability to obtain the optimal results for real-world optimization problems. To sum up, these test results confirm the effectiveness of the proposed mechanism.

Comparison of the Diagnostic Value of SARC-F and Its Three Modified Versions for Screening Sarcopenia in Chinese Community-Dwelling Older Adults

OBJECTIVES

Sarcopenia refers to age-related loss of skeletal muscle mass. SARC-F is a screening tool for sarcopenia with high specificity and relatively good overall diagnostic accuracy but with low sensitivity. This study evaluated the diagnostic utility of SARC-F and its three modified versions (SARC-CalF, SARC-F+AC, and SARC-CalF+AC) for screening sarcopenia in community-dwelling older adults.

DESIGN

Diagnostic accuracy study.

SETTINGS AND PARTICIPANTS

We screened sarcopenia of older adults (age ≥ 60 years) in three communities in 2020. The participants' information and anthropometric measurements were collected, respectively.

METHODS

The updated consensuses of AWGS2019 and the EWGSOP2 were applied as the reference standards. we performed sensitivity/specificity analyses and estimated the areas under the receiver operating characteristic curves (AUCs) of the four scales.

RESULTS

The prevalence of sarcopenia was 26.4% and 12.5% based on the AWGS2019 and EWGSOP2 criteria, respectively. The sensitivities/specificities of SARC-F, SARC-CalF, SARC-F+AC, and SARC-CalF+AC were 12.26%/95.59%, 47.17%/91.53%, 82.08%/68.47%, and 75.47%/83.73%, respectively, using the AWGS2019 criteria. Further, the corresponding AUCs of SARC-F, SARC-CalF, SARC-F+AC, and SARC-CalF+AC were 0.650 (95% confidence interval [CI]: 0.601-0.697), 0.811 (95% CI: 0.769-0.848), 0.801 (95% CI: 0.759-0.839), and 0.848 (95% CI: 0.809-0.881), respectively. Using the EWGSOP2 criteria, the sensitivities/specificities of SARC-F, SARC-CalF, SARC-F+AC, and SARC-CalF+AC were 20.00%/95.44%, 56.00%/86.61%, 70.00%/81.20%, and 80.00%/74.93%, respectively. The AUCs of SARC-F, SARC-CalF, SARC-F+AC, and SARC-CalF+AC were 0.706 (95% CI: 0.659-0.750), 0.799 (95% CI: 0.756-0.837), 0.815 (95% CI: 0.774-0.852), and 0.834 (95% CI: 0.794-0.869), respectively.

CONCLUSIONS

The modified versions of SARC-F+AC and SARC-CalF+AC, which have superior sensitivity, can be used to screen sarcopenia in community-dwelling older adults. SARC-CalF+AC had the highest overall diagnostic accuracy for screening sarcopenia among community-dwelling older adults.

An improved arithmetic optimization algorithm with forced switching mechanism for global optimization problems

Arithmetic optimization algorithm (AOA) is a newly proposed meta-heuristic method which is inspired by the arithmetic operators in mathematics. However, the AOA has the weaknesses of insufficient exploration capability and is likely to fall into local optima. To improve the searching quality of original AOA, this paper presents an improved AOA (IAOA) integrated with proposed forced switching mechanism (FSM). The enhanced algorithm uses the random math optimizer probability (RMOP) to increase the population diversity for better global search. And then the forced switching mechanism is introduced into the AOA to help the search agents jump out of the local optima. When the search agents cannot find better positions within a certain number of iterations, the proposed FSM will make them conduct the exploratory behavior. Thus the cases of being trapped into local optima can be avoided effectively. The proposed IAOA is extensively tested by twenty-three classical benchmark functions and ten CEC2020 test functions and compared with the AOA and other well-known optimization algorithms. The experimental results show that the proposed algorithm is superior to other comparative algorithms on most of the test functions. Furthermore, the test results of two training problems of multi-layer perceptron (MLP) and three classical engineering design problems also indicate that the proposed IAOA is highly effective when dealing with real-world problems.

Enhanced Slime Mould Algorithm for Multilevel Thresholding Image Segmentation Using Entropy Measures

Image segmentation is a fundamental but essential step in image processing because it dramatically influences posterior image analysis. Multilevel thresholding image segmentation is one of the most popular image segmentation techniques, and many researchers have used meta-heuristic optimization algorithms (MAs) to determine the threshold values. However, MAs have some defects; for example, they are prone to stagnate in local optimal and slow convergence speed. This paper proposes an enhanced slime mould algorithm for global optimization and multilevel thresholding image segmentation, namely ESMA. First, the Levy flight method is used to improve the exploration ability of SMA. Second, quasi opposition-based learning is introduced to enhance the exploitation ability and balance the exploration and exploitation. Then, the superiority of the proposed work ESMA is confirmed concerning the 23 benchmark functions. Afterward, the ESMA is applied in multilevel thresholding image segmentation using minimum cross-entropy as the fitness function. We select eight greyscale images as the benchmark images for testing and compare them with the other classical and state-of-the-art algorithms. Meanwhile, the experimental metrics include the average fitness (mean), standard deviation (Std), peak signal to noise ratio (PSNR), structure similarity index (SSIM), feature similarity index (FSIM), and Wilcoxon rank-sum test, which is utilized to evaluate the quality of segmentation. Experimental results demonstrated that ESMA is superior to other algorithms and can provide higher segmentation accuracy.

Impact of nodular calcification on the outcomes of patients with acute coronary syndrome (ACS) treated with primary percutaneous coronary intervention (PCI)

Background

Calcified plaque is thought to adversely impact clinical outcomes but the impact of nodular calcification after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS) remains unclear.

Purpose

This study sought to explore the impact of nodular calcification on the outcomes of patients undergoing percutaneous coronary intervention for acute coronary syndromes.

Methods

Five-hundred culprit plaque with calcification were analysed from 495 ACS patients in whom PCI was performed. Plaques were divided into nodular calcification group (n=238) and non-nodular calcification group (n=262). Calcification is defined as an area with low back-scattering signal and a sharp border. Nodular calcification was defined as a protruding mass with an irregular surface, high backscattering, and signal attenuation on optical coherence tomography (OCT).

Results

Patients with nodular calcification were older (p&lt;0.001) and had lower left ventricular ejection fraction (p=0.006) compared to patients with non-nodular calcification. Lesion length (31 (25.2, 38.5) vs. 29 (22.8, 34.1), p&lt;0.001) was longer in plaques with nodular calcification. A higher prevalence of superficial calcium (p&lt;0.001) was observed in plaques with nodular calcification compared with non-nodular calcification group. Minimum stent area (MSA) (5.0 (3.9, 6.3) vs. 5.4 (4.2, 6.7), p=0.011) and stent expansion (70 (62.7, 81.8) vs. 75 (65.2, 86.6), p=0.004) were significantly smaller in the nodular calcification group than in the non-nodular calcification group. Independent predictors of nodular calcification were age (p&lt;0.001) lesion length (p=0.002) and calcium depth (p&lt;0.001).

Conclusion

This study demonstrated that the presence of nodular calcification is associated with unfavourable outcomes with smaller minimum stent area and higher incidence of stent under expansion in patients with ACS treated with primary PCI.

Funding Acknowledgement

Type of funding sources: None.

Frequency and predictors of thin-cap fibroatheroma progression: a comprehensive and dynamic in-vivo OCT study

Purpose

To assess the evolution of thin-cap fibroatheroma (TCFA) and to explore predictors for its progression by using optical coherence tomography (OCT) in patients with acute coronary syndrome (ACS).

Methods

We enrolled ACS patients with non-culprit TCFA at baseline and corresponding OCT images at follow-up of 9 to 15 months. Clinical, angiographic and OCT data were collected and analyzed according to established methods. TCFA was defined as a lipid plaque with maximum lipid arc &gt;90° and fibrous cap thickness &lt;65μm. Considering the resolution of OCT, the regression of TCFA was defined as an increase of fibrous cap thickness &gt;10μm. Inversely, TCFA progression was defined as a decrease, constant or ≤10μm increase of fibrous cap thickness.

Results

41 patients with 55 non-culprit TCFAs were taken into final analysis. 17 patients (41.5%) had patient-level progression and 22 TCFAs (40.0%) progressed at plaque-level with a median follow-up duration of 371 days. 11 (20.0%) of the 55 TCFAs happened subclinical rupture at follow-up, including 10 with the formation a new layer and 1 without the detection of the new layer. Besides, another patient suffered re-myocardial infarction because of the rupture of TCFA induced acute thrombosis and lumen occlusion during follow-up. The baseline clinical and angiographic characteristics were similar between the two cohorts. The progression group had a significantly higher prevalence of macrophage infiltration and vasa vasorum at baseline than the non-progression group (Figure 1). Multivariate analysis identified macrophage infiltration (odds ratio [OR]: 5.30; 95% confidence interval [CI]: 1.01 to 27.91; p=0.049]) as the independent predictor of TCFA progression. When it came to the evolution of lesion morphology and lipid components, the progression cohort had a higher percent change of lumen stenosis and lipid length (Figure 2).

Conclusions

About 40% of non-culprit TCFAs in ACS patients progressed in fibrous cap thickness at a median interval of 1 year. Macrophage infiltration was the independent predictor of non-culprit TCFA progression. The progression of fibrous cap thickness was usually accompanied with an aggressive evolution of other lesion characteristics.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): the National Key R&D Program of China Baseline OCT characteristicsPercent change of lesion morphology

Prevalence, predictors, and clinical prognosis of macrophage infiltrates in patients with ST-segment elevation myocardial infarction caused by plaque erosion as assessed by OCT

Background

Autopsy series showed that one of most common plaque phenotypes underlying coronary thrombi was plaque erosion. Identification of erosion may permit a less invasive management. Chronic inflammation is a common process in atherosclerosis. The severity of plaque inflammation can be assessed by optical coherence tomography (OCT) defined macrophages density. The impact of macrophage infiltrates (MØI) in ST-segment elevation myocardial infarction (STEMI) patients caused by plaque erosion was still unknown.

Purpose

The aim of this study was to evaluate plaque morphology and clinical prognosis associated with MØI as assessed by optical coherence tomography in STEMI patients caused by plaque erosion.

Methods

From October 2014 to December 2017, 1561 STEMI with OCT imaging before percutaneous coronary intervention were enrolled in this study. Finally, 312 STEMI patients caused by plaque erosion were split into two group according to the presence of MØI in culprit eroded plaques.

Results

163 (52.2%) STEMI patients presented plaque erosion with MØI, whereas 149 (47.8%) patients had no evidence of MØI. MØI were more frequency appeared in older patients (p=0.015). The severity and vulnerability of culprit lesions were higher in patients with MØI characterized by more aggressive and vulnerable features. Patients with MØI had worse long-term prognosis, compared with patient without MØI, mainly driven by a higher rate of target lesion revascularization (p=0.046), especially in STEMI patients presented plaque erosion with intensive antiplatelet therapy (p=0.035).

Conclusions

In the present study, we demonstrated that macrophage infiltrates at the site of erode plaques were associated with severity and vulnerability of culprit lesions. The long-term prognosis in patients with MØI were poorer especially in patients without stent implantation.

Funding Acknowledgement

Type of funding sources: None. Study flow chartPredictors of plaque erosion with MØI

Gender-specific difference of clinical and plaque characteristics in myocardial infarction with non-obstructive artery (MINOCA): insights from optical coherence tomography

Background

To date, sparse data are available with regard to gender differences in coronary plaque morphology and composition as underlying mechanism of MINOCA.

Purpose

To assess the differences in coronary plaque morphology in culprit lesion between women and men with MINOCA using intravascular optical coherence tomography.

Methods

Totally, 7404 consecutives acute myocardial infarction patients who underwent emergency coronary angiography between 2016 and 2019 were screened. MINOCA were identified in 292 patients (mean age: 72.6% male, 54.1% with ST-segment elevation). Optical coherence tomography was performed in 190 patients (men, n=142).

Results

Women with MINOCA were older (62.5±10.6 vs. 54.0±11.5, P&lt;0.001) and more over 55 years (75.3% vs. 43.6%, P&lt;0.001). Although women with MINOCA more frequently presented with NSTEMI (56.8% vs. 41.7%, P=0.025) and prior coronary artery disease (CAD) (33.3% vs. 6.3%, P&lt;0.001), they were less likely smoker (27.2% vs. 58.8%, P&lt;0.001). There was no significant difference in incidence of plaque rupture, erosion and calcified nodule between men and women. However, women were more likely to have thin-cap fibroatheroma (TCFA) (39.6% vs. 22.5%, P=0.025).

Conclusion

Women with MINOCA were older, more frequently presented with NSTEMI and less smoking compared to men. Besides, more TCFA were observed in women.

Funding Acknowledgement

Type of funding sources: None. Clinical and OCT plaque profilesProportion of clinical and OCT profiles

A Hybrid SSA and SMA with Mutation Opposition-Based Learning for Constrained Engineering Problems

Based on Salp Swarm Algorithm (SSA) and Slime Mould Algorithm (SMA), a novel hybrid optimization algorithm, named Hybrid Slime Mould Salp Swarm Algorithm (HSMSSA), is proposed to solve constrained engineering problems. SSA can obtain good results in solving some optimization problems. However, it is easy to suffer from local minima and lower density of population. SMA specializes in global exploration and good robustness, but its convergence rate is too slow to find satisfactory solutions efficiently. Thus, in this paper, considering the characteristics and advantages of both the above optimization algorithms, SMA is integrated into the leader position updating equations of SSA, which can share helpful information so that the proposed algorithm can utilize these two algorithms' advantages to enhance global optimization performance. Furthermore, Levy flight is utilized to enhance the exploration ability. It is worth noting that a novel strategy called mutation opposition-based learning is proposed to enhance the performance of the hybrid optimization algorithm on premature convergence avoidance, balance between exploration and exploitation phases, and finding satisfactory global optimum. To evaluate the efficiency of the proposed algorithm, HSMSSA is applied to 23 different benchmark functions of the unimodal and multimodal types. Additionally, five classical constrained engineering problems are utilized to evaluate the proposed technique's practicable abilities. The simulation results show that the HSMSSA method is more competitive and presents more engineering effectiveness for real-world constrained problems than SMA, SSA, and other comparative algorithms. In the end, we also provide some potential areas for future studies such as feature selection and multilevel threshold image segmentation.

An improved hybrid Aquila Optimizer and Harris Hawks Optimization for global optimization

This paper introduces an improved hybrid Aquila Optimizer (AO) and Harris Hawks Optimization (HHO) algorithm, namely IHAOHHO, to enhance the searching performance for global optimization problems. In the IHAOHHO, valuable exploration and exploitation capabilities of AO and HHO are retained firstly, and then representative-based hunting (RH) and opposition-based learning (OBL) strategies are added in the exploration and exploitation phases to effectively improve the diversity of search space and local optima avoidance capability of the algorithm, respectively. To verify the optimization performance and the practicability, the proposed algorithm is comprehensively analyzed on standard and CEC2017 benchmark functions and three engineering design problems. The experimental results show that the proposed IHAOHHO has more superior global search performance and faster convergence speed compared to the basic AO and HHO and selected state-of-the-art meta-heuristic algorithms.

[Effect of electrode array type and insertion technique on the insertion force: in vitro cochlear model study]

Objective: To investigate the effect of insertion technique and electrode array type on the insertion force of electrode array, and to provide a basis for further optimizing electrode design and facilitating mini-invasive electrode insertion. Methods: Three types of electrode array from Nurotron (Standard Electrode, Slim-medium Electrode, Slim-long Electrode) were studied. from July 2019 to December 2019. These electrode arrays were inserted into the phantom models of the cochlea, manually or robot-assisted(medium speed and low speed). The real-time force during electrode array insertion was recorded by ATI Nano 17 Ti sensors and was analyzed by accessory software. Origin 2020b software was used for statistical processing. Results: The insertion force of all electrode arrays progressively increased with the insertion depth. With the manual technique, the peak force of slim-medium electrode insertion was significantly smaller than that of the standard electrode insertion((71.0±16.6) mN vs (140.9±52.7) mN, Z=3.683, P<0.01), and the peak force of the slim-long electrode insertion was between the peak force of standard electrode and slim-medium electrode(P>0.05). No difference was found in the force variation of insertion among the three electrodes(P>0.05). With medium-speed and low-speed robotic assistance, the peak force characteristics of three electrodes were similar to those with the manual technique, but the force variation of standard electrode insertion ((83.9±9.7) mN/s) at medium speed was significantly larger than that of the slim-long electrode insertion ((69.2±4.0)mN/s), and the force variation of the standard electrode insertion at low speed was significantly greater than the other two electrodes. For the same electrode, robot-assisted insertion presented significantly lower peak force and force variation than manual insertion for each type of electrode array. But there was no difference in the peak force and force variation between two-speed levels of robot assistance (P>0.05). Conclusions: The insertion force of the electrode array will be lower when a slim electrode array or robot technique is applied. Long electrode array might make manual insertion difficult or less precise. Robot assistance has advantage on force control during electrode array insertion.

Identification of the pivotal differentially expressed genes and pathways involved in Staphylococcus aureus-induced infective endocarditis by using bioinformatics analysis

OBJECTIVE

Infective endocarditis (IE), particularly by Staphylococcus aureus, is an uncommon bacteremia-associated infection of the endocardium and cardiac valves. Herein, we evaluated predictive noninvasive biomarkers for IE caused by S. aureus through bioinformatics analysis.

MATERIALS AND METHODS

Staphylococcus aureus-associated and IE-associated differentially expressed genes (DEGs) were identified by bioinformatics analysis of the GSE6269 and GSE29161 Gene Expression Omnibus (GEO) datasets. The DEGs were analyzed with the LIMMA package, and the coregulated genes were chosen as the intersection of DEGs between the two datasets, called common differentially expressed genes (CDEGs). The enrichment study of CDEGs was subsequently performed with the DAVID and KOBAS web resources. Finally, protein-protein interaction (PPI) network, microRNA (miRNA)-transcription factor (TF)-mRNA (messenger RNA) regulatory network, and the network of drug-genes were identified.

RESULTS

From GSE6269 and GSE29161, respectively, a total of 201 and 741 DEGs were obtained. Gene Ontology (GO) analysis showed that CDEGs were primarily involved in innate immune response, extracellular exosome, as well as calcium ion binding, while the pathway analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that CDEGs were significantly enriched in the B-cell receptor, IL-17, and NF-kappa B signaling pathways. The hub genes in the PPI network included HP, S100A12, SPI1, CD14, CCR1, S100A9 and so on. In the miRNA-TF-mRNA regulatory network, SPI1 could target miR-361-5p, miR-155-5p, and miR-339-5p in the progression of IE.

CONCLUSIONS

Several pivotal genes and pathways were identified in the progression of S. aureus-induced IE, which may have the potential for early detection.

A hybrid equilibrium optimizer algorithm for multi-level image segmentation

Threshlod image segmentation is a classic method of color image segmentation. In this paper, we propose a hybrid equilibrium optimizer algorithm for multi-level image segmentation. When multi-level threshold method calculates the neighborhood mean and median of color image, it takes huge challenge to find the optimal threshold. We use the proposed method to optimize the multi-level threshold method and get the optimal threshold from the color image. In order to test the performance of the proposed method, we select the CEC2015 dataset as the benchmark function. The result shows that the proposed method improves the optimization ability of the original algorithm. And then, the classic images and wood fiber images are taken as experimental objects to analyze the segmentation result. The experimental results show that the proposed method has a good performance in Uniformity measure, Peak Signal-to-Noise Ratio and Feature Similarity Index and CPU time.

Salp swarm algorithm with crossover scheme and Lévy flight for global optimization

Salp swarm algorithm (SSA) is a meta-heuristic algorithm proposed in recent years, which shows certain advantages in solving some optimization tasks. However, with the increasing difficulty of solving the problem (e.g. multi-modal, high-dimensional), the convergence accuracy and stability of SSA algorithm decrease. In order to overcome the drawbacks, salp swarm algorithm with crossover scheme and Lévy flight (SSACL) is proposed. The crossover scheme and Lévy flight strategy are used to improve the movement patterns of salp leader and followers, respectively. Experiments have been conducted on various test functions, including unimodal, multimodal, and composite functions. The experimental results indicate that the proposed SSACL algorithm outperforms other advanced algorithms in terms of precision, stability, and efficiency. Furthermore, the Wilcoxon’s rank sum test illustrates the advantages of proposed method in a statistical and meaningful way.

Excitation functions of proton induced reactions on titanium and copper

Excitation functions of the Tnati(p,x)S43,47c, V48 and Cnatu(p,x)⁶⁴Cu, Z62,65n reactions were measured in the energy range of 8.8-18.4 MeV by using the stacked-foil activation technique and off-line gamma spectroscopy. The irradiation was carried out at the superconducting linac of the Institute of Modern Physics, Chinese Academy of Sciences. Besides, the reliability and effectiveness of theoretical data from the TALYS code, recommended data of the International Atomic Energy Agency (IAEA) and evaluated nuclear data of the ENDF/B-VIII.0, JENDL-4.0/HE and PADF-2007 libraries were evaluated and verified by comparing with experimental data. Our experimental results agree with most of the available literature data. TALYS-1.95 code could not reproduce, in most cases, the experimental data. Evaluated nuclear data from the ENDF/B-VIII.0, JENDL-4.0/HE and PADF-2007 libraries are able to reproduce, in most cases, the experimental data trend. Recommended data of the IAEA are in good consistent with our work and most of the available literature data.

Multilevel thresholding using a modified ant lion optimizer with opposition-based learning for color image segmentation

Multilevel thresholding has important research value in image segmentation and can effectively solve region analysis problems of complex images. In this paper, Otsu and Kapur's entropy are adopted among thresholding segmentation methods. They are used as the objective functions. When the number of threshold increases, the time complexity increases exponentially. In order to overcome this drawback, a modified ant lion optimizer algorithm based on opposition-based learning (MALO) is proposed to determine the optimum threshold values by the maximization of the objective functions. By introducing the opposition-based learning strategy, the search accuracy and convergence performance are increased. In addition to IEEE CEC 2017 benchmark functions validation, 11 state-of-the-art algorithms are selected for comparison. A series of experiments are conducted to evaluate the segmentation performance of the algorithm. The evaluation metrics include: fitness value, peak signal-to-noise ratio, structural similarity index, feature similarity index, and computational time. The experimental data are analyzed and discussed in details. The experimental results significantly demonstrate that the proposed method is superior over others, which can be considered as a powerful and efficient thresholding technique.

High equilibrium optimizer for global optimization

With the advent of the information age, people have higher requirements for basic algorithms. Meta-heuristic algorithms have received wide attention as a high-level strategy to study and generate fully optimized solutions to data-driven optimization problems. Using the advantage of equilibrium optimizer (EO) with better balance mode, combined with the strategy of memetic algorithm, different proportion of temperature is introduced in different stages. That is, EO and thermal exchange optimization (TEO) are fused to obtain a new highly balanced optimizer (HEO). While keeping the guiding strategy and memory mode unchanged of EO, the accuracy of optimization is greatly improved. 14 well-known benchmark functions and 7 selective algorithms were used for HEO evaluation comparison experiments. On the basis of the fitness function curve, the optimal solution and other experimental data are tested statistically. The experimental results show that the improved algorithm has high accuracy and stability, but at the cost of running a little more time. Application testing of complex engineering problems is also one of the main purposes of algorithm design. In this paper, three typical engineering design problems (three truss, welded beam and rolling bearing design) are tested and the experimental results show that this algorithm has certain competitiveness and superiority in classical engineering design.

[Auditory brainstem implantation: current status and prospects]

Auditory brainstem implantation is a hearing restoration technique on the central auditory pathway, which directly stimulates neural tissues of cochlear nucleus by electrode array to produce hearing, so it will not be restricted by abnormalities of the cochlea and cochlear nerve. In the past 30 years since the birth of multi-channel ABI, its indications have expanded from patients with neurofibromatosis type 2 (NF2) to congenital deafness patients with severe inner ear and/or cochlear nerve malformations, and the age of recipients decreases from adults to young children. This article summarizes the principle, indications, surgical techniques, complications and auditory outcomes of ABI.

Hybrid improved slime mould algorithm with adaptive β hill climbing for numerical optimization

Slime mould algorithm (SMA) is a novel metaheuristic that simulates foraging behavior of slime mould. Regarding its drawbacks and properties, a hybrid optimization (BTβSMA) based on improved SMA is proposed to produce the higher-quality optimal results. Brownian motion and tournament selection mechanism are introduced into the basic SMA to improve the exploration capability. Moreover, a local search algorithm (Adaptive β-hill climbing, AβHC) is hybridized with the improved SMA. It is considered from boosting the exploitation trend. The proposed BTβSMA algorithm is evaluated in two main phases. Firstly, the two improved hybrid variants (BTβSMA-1 and BTβSMA-2) are compared with the basic SMA algorithm through 16 benchmark functions. Also, the performance of winner is further evaluated through comparisons with 7 state-of-the-art algorithms. The simulation results report fitness and computation time. The convergence curve and boxplot visualize the effects of fitness. The comparison results on the function optimization suggest that BTβSMA is superior to competitors. Wilcoxon rank-sum test is also employed to investigate the significance of the results. Secondly, the applicability on real-world tasks is proved by solving structure engineering design problems and training multilayer perceptrons. The numerical results indicate the merits of the BTβSMA algorithm in terms of solution precision.

Impact of macrophage infiltration in patients with st-segment elevation myocardial infarction caused by plaque erosion: an in vivo optical coherence tomography study

Background

Chronic inflammatory infiltration is a common process for atherosclerosis development. However, autopsy studies reveal that incidence rate of inflammatory infiltrates are less abundant in plaque erosion compared with plaque rupture.

Purpose

Studies performed by optical coherence tomography (OCT) have allowed to establish the severity of plaque inflammation by assessing macrophage infiltration (MØI). In this study, we aimed at assessing the impaction of MØI in plaque erosion among patients with STEMI by using OCT.

Methods

A total of 1561 patients with ST-segment elevation myocardial infarctions (STEMI) who underwent OCT imaging were enrolled in this study. According to the exclusion criteria, 312 patients with STEMI exhibiting plaque erosion were classified as MØI or no MØI.

Results

163 (52.2%) patients had MØI at the site of plaque erosion, whereas 149 (47.8%) patients had no evidence of MØI and patients of MØI group were significantly older (P=0.015). The result of angiography showed the prevalence of multi-vessel disease appeared more frequency (P=0.021) and diameter stenosis% were higher (P=0.031) in MØI group. OCT results showed the minimum fibrous-cap thickness was thinner (P&lt;0.001) and the maximum lipid arc was larger (P=0.005) in MØI group. Some patients underwent imaging follow-up at 1 year. There was no significant difference in the culprit plaque morphology progress among two groups (Figure 1A-1D).

Conclusions

This study demonstrated that plaque inflammation can increase culprit lesion severity and plaque vulnerability in patients with STEMI caused by plaque erosion.

Figure 1

Funding Acknowledgement

Type of funding source: None

The probiotic Lactobacillus casei Shirota attenuates symptoms of vestibular migraine: a randomised placebo-controlled double-blind clinical trial

Vestibular migraine (VM) has emerged as one of the major vestibular syndromes. Although probiotics have exhibited beneficial effects on migraine headache, its effect on VM is not clear. This trial aimed to investigate the treatment efficacy of the probiotic Lactobacillus casei Shirota (LcS) on symptoms of VM. 247 VM patients were enrolled, of which 204 eligible patients receiving either LcS or placebo on a daily basis completed the 4 month study. They were re-visited at 2 and 4 months after study initiation to assess treatment outcomes. The primary endpoints were vestibular symptoms, evaluated by the number of vertiginous attacks during the past week, the Vertigo Severity Score (VSS), and Dizziness Handicap Inventory (DHI) scores. The secondary endpoints were anxiety and depressive symptoms, evaluated using Beck Anxiety Inventory (BAI) and Beck Depression Inventory (BDI) scores. Efficacy of LcS over placebo was not obvious at 2 month follow-up. At 4 month follow-up, while both LcS and placebo groups of VM patients displayed alleviated symptoms, the extents of the improvements were significantly better in LcS group than those of placebo group, with regard to vestibular symptoms using DHI and VSS, as well as anxiety and depressive symptoms using BAI and BDI. Although placebo effect cannot be ignored in intervention for VM patients, the probiotic LcS still exhibits considerable efficacy against VM symptoms over a 4 month study period, supporting further clinical study of a larger and more diverse cohort.

Isolation and sequence analysis of the complete VP2 gene of canine parvovirus from Chinese domestic pets and determination of the pathogenesis of these circulating strains in beagles

Canine parvovirus (CPV) causes acute gastroenteritis in domestic dogs, cats, and several wild carnivore species. In this study, the full-length VP2 gene of 36 CPV isolates from dogs and cats infected between 2016 and 2017 in Beijing was sequenced and analyzed. The results showed that, in dogs, the new CPV-2a strain was the predominant variant (n = 18; 50%), followed by the new CPV-2b (n = 6; 16.7%) and CPV-2c (n = 3; 8.3%) strains, whereas, among cats, the predominant strain was still CPV-2 (n = 9; 25%). One new CPV-2a strain, 20170320-BJ-11, and two CPV-2c strains, 20160810-BJ-81 and 20170322-BJ-26, were isolated and used to perform experimental infections. Multiple organs of beagles that died tested PCR positive for CPV, and characteristic histopathological lesions were observed in organs, including the liver, spleen, lungs, kidneys, small intestines, and lymph nodes. Experimental infections showed that the isolates from the epidemic caused high morbidity in beagles, indicating their virulence in animals and suggesting the need to further monitor evolution of CPV in China.

pUC18-CpG stimulates RAW 264.7 via TBK1-mediated pathway and presents adjuvanticity in mice

Phosphorothioate CpG oligodeoxynucleotides (ODN) are reported to be recognized by the membrane-bound TLR9 and trigger the MyD88-dependent up-regulation of Type I interferons and pro-inflammatory cytokines. Whether plasmids containing multiple CpG motifs stimulate the same signaling pathway is yet to be determined. The present results show that the CpG motifs enrich plasmid pUC18-CpG stimulates RAW 264.7 in vitro, mainly through the TBK1-mediated signaling pathway, causing the up-regulation of IFN-β, and pro-inflammatory cytokines TNF-α and IL-6. When pUC18-CpG is co-administered with the recombinant Echinococcus granulosus antigen, the antigen-specific antibody titers are markedly increased compared to the Quil-A adju- vanted group. Antigen specific cytokine quantification shows that cytokine profiles from the pUC18-CpG adjuvanted-group are switched to a Th1-biased immune response.