Characteristics of Growth and Metabolism of Thermoascus aurantiacus QH-1 Derived Hongxinqu

To explore the growth metabolic characteristics of Thermoascus aurantiacus, the optimal growth conditions, ethanol tolerance, growth curve, saccharifying power and liquefaction power of Thermoascus aurantiacus QH-1 were analyzed. The results showed that Thermoascus aurantiacus QH-1 grew rapidly and had pigment in PDA, MEA and SDA mediums with rich in nutrients, and colonies growing on synthetic medium and G25N medium grew slowly and almost no pigment. The optimal growth conditions of T.aurantiacus QH-1 strain was as follows: Temperature 45 ℃, pH4.0, inoculum concentration 3%, liquied loading volume 160 mL. The lowest and highest growth temperatures of Th. aurantiacus QH-1 were 26 and 60 ℃, respectively. Among the raw materials for brewing Daqu, sorghum rice was the best for its growth, and the concentration of 6% ethanol had no effect on the grwoth of T.aurantiacus QH-1. T.aurantiacus QH-1 grew slowly with lower saccharifying power in the early stage, and the growth rate accelerated with the higher saccharifying power at 6~8 days in solid state medium of barley and pea. The growth curve of T.aurantiacus QH-1 was similar to its change curve of saccharifying power. However, its liquefying power was detected on day 10. The results provided necessary information for the further development and utilization of T.aurantiacus QH-1

Design, synthesis and antifungal activity of novel 1,4-benzoxazin-3-one derivatives containing an acylhydrazone moiety

A series of 1,4-benzoxazin-3-one derivatives containing an acylhydrazone moiety were designed, synthesized and evaluated for their in vitro antifungal activities against Gibberella zeae, Pellicularia sasakii, Phytophthora infestans, Capsicum wilt, and Phytophthora capsica. The structures of target compounds were characterized by 1H NMR, 13H NMR, 19F NMR and HRMS. The preliminary antifungal evaluation of all target compounds showed that some target compounds possessed moderate to good activities against G. zeae, P. sasakii, P. infestans and C. wilt. Among them, compounds 5L and 5o exhibited noticeable inhibition effects against G. zeae with the EC50 values (effective concentration for 50% activity) of 20.06 and 23.17 μg/ml, respectively, which were even nearly double effective than that of hymexazol (40.51 μg/ml). Meanwhile, compound 5q displayed a notable inhibitory effect toward P. sasakii, with the EC50 value of 26.66 μg/ml, which was better than that of hymexazol (32.77 μg/ml). In addition, compound 5r yielded the EC50 value of 15.37 μg/ml against P. infestans, which was less than those of hymexazol (18.35 μg/ml) and carbendazim (34.41 μg/ml). Eventually, compound 5p showed higher inhibitory effect against C. wilt, with EC50 value of 26.76 μg/ml, which was better than that of hymexazol (>50 μg/ml)

Brain entropy changes in classical trigeminal neuralgia

BackgroundClassical trigeminal neuralgia (CTN) is a common and severe chronic neuropathic facial pain disorder. The pathological mechanisms of CTN are not fully understood. Recent studies have shown that resting-state functional magnetic resonance imaging (rs-fMRI) could provide insights into the functional changes of CTN patients and the complexity of neural processes. However, the precise spatial pattern of complexity changes in CTN patients is still unclear. This study is designed to explore the spatial distribution of complexity alterations in CTN patients using brain entropy (BEN).MethodsA total of 85 CTN patients and 79 age- and sex-matched healthy controls (HCs) were enrolled in this study. All participants underwent rs-fMRI and neuropsychological evaluations. BEN changes were analyzed to observe the spatial distribution of CTN patient complexity, as well as the relationship between these changes and clinical variables. Sixteen different machine learning methods were employed to classify the CTN patients from the HCs, and the best-performing method was selected.ResultsCompared with HCs, CTN patients exhibited increased BEN in the thalamus and brainstem, and decreased BEN in the inferior semilunar lobule. Further analyses revealed a low positive correlation between the average BEN values of the thalamus and neuropsychological assessments. Among the 16 machine learning methods, the Conditional Mutual Information Maximization-Random Forest (CMIM-RF) method yielded the highest area under the curve (AUC) of 0.801.ConclusionsOur study demonstrated that BEN changes in the thalamus and pons and inferior semilunar lobule were associated with CTN and machine learning methods could effectively classify CTN patients and HCs based on BEN changes. Our findings may provide new insights into the neuropathological mechanisms of CTN and have implications for the diagnosis and treatment of CTN

Frequency-dependent alterations in functional connectivity in patients with Alzheimer’s Disease spectrum disorders

BackgroundIn the spectrum of Alzheimer’s Disease (AD) and related disorders, the resting-state functional magnetic resonance imaging (rs-fMRI) signals within the cerebral cortex may exhibit distinct characteristics across various frequency ranges. Nevertheless, this hypothesis has not yet been substantiated within the broader context of whole-brain functional connectivity. This study aims to explore potential modifications in degree centrality (DC) and voxel-mirrored homotopic connectivity (VMHC) among individuals with amnestic mild cognitive impairment (aMCI) and AD, while assessing whether these alterations differ across distinct frequency bands.MethodsThis investigation encompassed a total of 53 AD patients, 40 aMCI patients, and 40 healthy controls (HCs). DC and VMHC values were computed within three distinct frequency bands: classical (0.01–0.08 Hz), slow-4 (0.027–0.073 Hz), and slow-5 (0.01–0.027 Hz) for the three respective groups. To discern differences among these groups, ANOVA and subsequent post hoc two-sample t-tests were employed. Cognitive function assessment utilized the mini-mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA). Pearson correlation analysis was applied to investigate the associations between MMSE and MoCA scores with DC and VMHC.ResultsSignificant variations in degree centrality (DC) were observed among different groups across diverse frequency bands. The most notable differences were identified in the bilateral caudate nucleus (CN), bilateral medial superior frontal gyrus (mSFG), bilateral Lobule VIII of the cerebellar hemisphere (Lobule VIII), left precuneus (PCu), right Lobule VI of the cerebellar hemisphere (Lobule VI), and right Lobule IV and V of the cerebellar hemisphere (Lobule IV, V). Likewise, disparities in voxel-mirrored homotopic connectivity (VMHC) among groups were predominantly localized to the posterior cingulate gyrus (PCG) and Crus II of the cerebellar hemisphere (Crus II). Across the three frequency bands, the brain regions exhibiting significant differences in various parameters were most abundant in the slow-5 frequency band.ConclusionThis study enhances our understanding of the pathological and physiological mechanisms associated with AD continuum. Moreover, it underscores the importance of researchers considering various frequency bands in their investigations of brain function

Risk factors of infection after transarterial chemoembolization for hepatocellular carcinoma: A protocol for systematic review and meta-analysis

Background:Transarterial chemoembolization (TACE) has the characteristics of minimally invasive, strong repeatability and good curative effect, so it is commonly used in the non-operative treatment of hepatocellular carcinoma (HCC). However, infection will occur after TACE, which not only increases the hospitalization time and medical expenses, but also affects the efficacy of TACE treatment. At present, there is a lack of analysis of the risk factors of infection after TACE of patients with HCC. In this study, meta-analysis was used to further explore the risk factors of postoperative infection in patients with HCC after TACE, and to provide strategies for infection prevention and intervention. Methods:To search the literatures about the influencing factors of post-TACE infection in patients with HCC published from the establishment of PubMed, Embase, The Cochrane Library, Web of Science, China Biology Medicine Database, China National Knowledge Infrastructure, China Science and Technology Journal Database, and WANFANG to April 2021. Screening was carried out according to inclusion criteria and exclusion criteria. A meta-analysis was performed using RevMan 5.3 software. Results: We disseminated the findings of this systematic review and meta-analysis via publications in peer-reviewed journals. Conclusion: This study systematically reviewed the existing evidence and determined the incidence and predictors of infection after TACE of patients with HCC

Molecular Identification of Keratinase DgokerA from <i>Deinococcus gobiensis</i> for Feather Degradation

Keratin is a tough fibrous structural protein that is difficult to digest with pepsin and trypsin because of the presence of a large number of disulfide bonds. Keratin is widely found in agricultural waste. In recent years, especially, the development of the poultry industry has resulted in a large accumulation of feather keratin resources, which seriously pollute the environment. Keratinase can specifically attack disulfide bridges in keratin, converting them from complex to simplified forms. The keratinase thermal stability has drawn attention to various biotechnological industries. It is significant to identify keratinases and improve their thermostability from microorganism in extreme environments. In this study, the keratinases DgoKerA was identified in Deinococcus gobiensis I-0 from the Gobi desert. The amino acid sequence analysis revealed that DgoKerA was 58.68% identical to the keratinase MtaKerA from M. thermophila WR-220 and 40.94% identical to the classical BliKerA sequence from B. licheniformis PWD-1. In vitro enzyme activity analysis showed that DgoKerA exhibited an optimum temperature of 60 °C, an optimum pH of 7 and a specific enzyme activity of 51147 U/mg. DgoKerA can degrade intact feathers at 60 °C and has good potential for industrial applications. The molecular modification of DgoKerA was also carried out using site-directed mutagenesis, in which the mutant A350S enzyme activity was increased by nearly 30%, and the results provide a theoretical basis for the development and optimization of keratinase applications

Force Tracking Control Method for Robotic Ultrasound Scanning System under Soft Uncertain Environment

Robotic ultrasound scanning has excellent potential to reduce physician workload, obtain higher-quality imaging, and reduce costs. However, the traditional admittance control strategy for robotics cannot meet the high-precision force control requirements for robots, which are critical for improving image quality and ensuring patient safety. In this study, an integral adaptive admittance control strategy is proposed for contact force control between an ultrasound probe and human skin to enhance the accuracy of force tracking. First, a robotic ultrasound scanning system is proposed, and the system’s overall workflow is introduced. Second, an adaptive admittance control strategy is designed to estimate the uncertain environmental information online, and the estimated parameters are used to modify the reference trajectory. On the basis of ensuring the stability of the system, an integral controller is then introduced to improve the steady-state response. Subsequently, the stability of the proposed strategy is analysed. In addition, a gravity compensation process is proposed to obtain the actual contact force. Finally, through a simulation analysis, the effectiveness of the strategy is discussed. Simultaneously, a series of experiments are carried out on the robotic ultrasound scanning system, and the results show that the strategy can successfully maintain a constant contact force under soft uncertain environments, which effectively improves the efficiency of scanning

Autonomous ultrasound scanning robotic system based on human posture recognition and image servo control: an application for cardiac imaging

In traditional cardiac ultrasound diagnostics, the process of planning scanning paths and adjusting the ultrasound window relies solely on the experience and intuition of the physician, a method that not only affects the efficiency and quality of cardiac imaging but also increases the workload for physicians. To overcome these challenges, this study introduces a robotic system designed for autonomous cardiac ultrasound scanning, with the goal of advancing both the degree of automation and the quality of imaging in cardiac ultrasound examinations. The system achieves autonomous functionality through two key stages: initially, in the autonomous path planning stage, it utilizes a camera posture adjustment method based on the human body’s central region and its planar normal vectors to achieve automatic adjustment of the camera’s positioning angle; precise segmentation of the human body point cloud is accomplished through efficient point cloud processing techniques, and precise localization of the region of interest (ROI) based on keypoints of the human body. Furthermore, by applying isometric path slicing and B-spline curve fitting techniques, it independently plans the scanning path and the initial position of the probe. Subsequently, in the autonomous scanning stage, an innovative servo control strategy based on cardiac image edge correction is introduced to optimize the quality of the cardiac ultrasound window, integrating position compensation through admittance control to enhance the stability of autonomous cardiac ultrasound imaging, thereby obtaining a detailed view of the heart’s structure and function. A series of experimental validations on human and cardiac models have assessed the system’s effectiveness and precision in the correction of camera pose, planning of scanning paths, and control of cardiac ultrasound imaging quality, demonstrating its significant potential for clinical ultrasound scanning applications

Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic

Background. There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies. Aim. To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire. Methods. We enrolled consecutive patients from a sleep clinic who had undergone apnea-hypopnea index (AHI) testing by type III portable monitor device at the hospital and completed the STOP-Bang questionnaire. The NoSAS score was assessed by reviewing medical records. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of both screening tools were calculated at different AHI cutoffs to compare the performance of SDB screening. Results. Of the 596 eligible patients (397 males and 199 female), 514 were diagnosed with SDB. When predicting overall (AHI ≥ 5), moderate-to-severe (AHI ≥ 15), and severe (AHI ≥ 30) SDB, the sensitivity and specificity of the NoSAS score were 71.2, 80.4, and 83.1% and 62.4, 49.3, and 40.7%, respectively. At all AHI cutoffs, the AUC ranged from 0.688 to 0.715 for the NoSAS score and from 0.663 to 0.693 for the STOP-Bang questionnaire. The NoSAS score had the largest AUC (0.715, 95% CI: 0.655–0.775) of diagnosing SDB at AHI cutoff of ≥5 events/h. NoSAS performed better in discriminating moderate-to-severe SDB than STOP-Bang with a marginally significantly higher AUC (0.697 vs. 0.663, P=0.046). Conclusion. The NoSAS score had good performance on the discrimination of SDB patients in sleep clinic and can be utilized as an effective screening tool in clinical practice