Enhanced Recognition of a Herbal Compound Epiberberine by a DNA Quadruplex-Duplex Structure.

The small molecule epiberberine (EPI) is a natural alkaloid with versatile bioactivities against several diseases including cancer and bacterial infection. EPI can induce the formation of a unique binding pocket at the 5' side of a human telomeric G-quadruplex (HTG) sequence with four telomeric repeats (Q4), resulting in a nanomolar binding affinity (KD approximately 26 nM) with significant fluorescence enhancement upon binding. It is important to understand (1) how EPI binding affects HTG structural stability and (2) how enhanced EPI binding may be achieved through the engineering of the DNA binding pocket. In this work, the EPI-binding-induced HTG structure stabilization effect was probed by a peptide nucleic acid (PNA) invasion assay in combination with a series of biophysical techniques. We show that the PNA invasion-based method may be useful for the characterization of compounds binding to DNA (and RNA) structures under physiological conditions without the need to vary the solution temperature or buffer components, which are typically needed for structural stability characterization. Importantly, the combination of theoretical modeling and experimental quantification allows us to successfully engineer Q4 derivative Q4-ds-A by a simple extension of a duplex structure to Q4 at the 5' end. Q4-ds-A is an excellent EPI binder with a KD of 8 nM, with the binding enhancement achieved through the preformation of a binding pocket and a reduced dissociation rate. The tight binding of Q4 and Q4-ds-A with EPI allows us to develop a novel magnetic bead-based affinity purification system to effectively extract EPI from Rhizoma coptidis (Huang Lian) extracts.

Relationship between serum uric acid levels and the outcome of STN-DBS in Parkinson's disease.

BACKGROUND: Uric acid is a natural antioxidant and it has been shown that low levels of uric acid may be a risk factor for the development of Parkinson's disease. We aimed to investigate the relationship between uric acid and improvement of motor symptoms in patients with Parkinson's disease after subthalamic nucleus deep brain stimulation. METHODS: We analyzed the correlation between serum uric acid levels in 64 patients with Parkinson's disease and the rate of improvement of motor symptoms 2 years after subthalamic nucleus deep brain stimulation. RESULTS: A non-linear correlation was observed between uric acid levels and the rate of motor symptom improvement after subthalamic nucleus deep brain stimulation, during both the drug-off and drug-on periods. CONCLUSIONS: Uric acid is positively associated with the rate of motor symptom improvement in subthalamic nucleus deep brain stimulation within a certain range.

Development and Validation of a Prediction Model for Anxiety Improvement after Deep Brain Stimulation for Parkinson Disease.

BACKGROUND: Parkinson's disease (PD) represents one of the most frequently seen neurodegenerative disorders, while anxiety accounts for its non-motor symptom (NMS), and it has greatly affected the life quality of PD cases. Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) can effectively treat PD. This study aimed to develop a clinical prediction model for the anxiety improvement rate achieved in PD patients receiving STN-DBS. METHODS: The present work retrospectively enrolled 103 PD cases undergoing STN-DBS. Patients were followed up for 1 year after surgery to analyze the improvement in HAMA scores. Univariate and multivariate logistic regression were conducted to select factors affecting the Hamilton Anxiety Scale (HAMA) improvement. A nomogram was established to predict the likelihood of achieving anxiety improvement. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and calibration curve analysis were conducted to verify nomogram performance. RESULTS: The mean improvement in HAMA score was 23.9% in 103 patients; among them, 68.9% had improved anxiety, 25.2% had worsened (Preop) anxiety, and 5.8% had no significant change in anxiety. Education years, UPDRS-III preoperative score, and HAMA preoperative score were independent risk factors for anxiety improvement. The nomogram-predicted values were consistent with real probabilities. CONCLUSIONS: Collectively, a nomogram is built in the present work for predicting anxiety improvement probability in PD patients 1 year after STN-DBS. The model is valuable for determining expected anxiety improvement in PD patients undergoing STN-DBS.

Prediction of STN-DBS for Parkinson's disease by uric acid-related brain function connectivity: A machine learning study based on resting state function MRI.

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder characterized by dyskinesia and is closely related to oxidative stress. Uric acid (UA) is a natural antioxidant found in the body. Previous studies have shown that UA has played an important role in the development and development of PD and is an important biomarker. Subthalamic nucleus deep brain stimulation (STN-DBS) is a common treatment for PD. Methods: Based on resting state function MRI (rs-fMRI), the relationship between UA-related brain function connectivity (FC) and STN-DBS outcomes in PD patients was studied. We use UA and DC values from different brain regions to build the FC characteristics and then use the SVR model to predict the outcome of the operation. Results: The results show that PD patients with UA-related FCs are closely related to STN-DBS efficacy and can be used to predict prognosis. A machine learning model based on UA-related FC was successfully developed for PD patients. Discussion: The two biomarkers, UA and rs-fMRI, were combined to predict the prognosis of STN-DBS in treating PD. Neurosurgeons are provided with effective tools to screen the best candidate and predict the prognosis of the patient.

Orthographic Pooling: Learned Maximum Intensity Projection for Vertebrae Labelling.

Maximum intensity projection (MIP) is a standard volume-rendering technique for 3D volumetric data processing. For example, given a 3D CT data, it simply projects the voxel values with its maximum intensity on a specific view to output a 2D image. Recently, MIP is further combined with Btrfly Net for vertebrae labelling task. However, this simple reformations of 3D data leads to loss of rich context information in volumetric data. In this paper, we propose a learned orthographic pooling approach instead of image processing based MIP. Typically, a simple conv-simple and bottleneck pooling modules are introduced to learn the orthographic projection of 3D data and output 2D intermediate feature maps. To this end, the learned orthographic pooling helps preserve detail information of 3D context during projection. Furthermore, an unified Btrfly Net is provided for vertebrae labelling by integrating the orthographic pooling sub-network. The novel Btrfly Net with orthographic pooling sub-network is evaluated on the 2014 MICCAI vertebra localization challenge dataset. Compared to original Butfly Net with MIP, orthographic pooling, the learned MIP largely boosts the performance of vertebrae labelling.

Nomogram for Predicting Depression Improvement after Deep Brain Stimulation for Parkinson's Disease.

BACKGROUND: Parkinson's disease is a common neurodegenerative disease, with depression being a common non-motor symptom. Bilateral subthalamic nucleus deep brain stimulation is an effective method for the treatment of Parkinson's disease. Thus, this study aimed to establish a nomogram of the possibility of achieving a better depression improvement rate after subthalamic nucleus deep brain stimulation in patients with Parkinson's disease. METHODS: We retrospectively analyzed 103 patients with Parkinson's disease who underwent subthalamic nucleus deep brain stimulation and were followed up for the improvement of their Hamilton Depression scale scores 1 year postoperatively. Univariate and multivariate logistic regression analyses were used to select factors affecting the improvement rate of depression. A nomogram was then developed to predict the possibility of achieving better depression improvement. Furthermore, the discrimination and fitting performance was evaluated using a calibration diagram, receiver operating characteristics, and decision curve analysis. RESULTS: The mean and median improvement rates of Hamilton Depression scores were 13.1 and 33.3%, respectively. Among the 103 patients, 70.8% had an improved depression, 23.3% had a worsened depression, and 5.8% remained unchanged. Logistic multivariate regression analysis showed that age, preoperative Parkinson's Disease Questionnaire, Hamilton Anxiety, and Hamilton Depression scores were independent factors for the possibility of achieving a better depression improvement rate. Based on these results, a nomogram model was developed. The nomogram had a C-index of 0.78 (95% confidence interval: 0.69-0.87) and an area under the receiver operating characteristics of 0.78 (95% confidence interval: 0.69-0.87). The calibration plot and decision curve analysis further demonstrated goodness-of-fit between the nomogram predictions and actual observations. CONCLUSION: We developed a nomogram to predict the possibility of achieving good depression improvement 1 year after subthalamic nucleus deep brain stimulation in patients with Parkinson's disease, which showed a certain value in judging the expected depression improvement of these patients.

Stereotactic co-axial projection imaging for augmented reality neuronavigation: a proof-of-concept study.

Background: Lack of intuitiveness and poor hand-eye coordination present a major technical challenge in neurosurgical navigation. Methods: We developed an integrated dexterous stereotactic co-axial projection imaging (sCPI) system featuring orthotopic image projection for augmented reality (AR) neurosurgical navigation. The performance characteristics of the sCPI system, including projection resolution and navigation accuracy, were quantitatively verified. The resolution of the sCPI was tested with a USAF1951 resolution test chart. The stereotactic navigation accuracy of the sCPI was measured using a calibration panel with a 7×7 circle array pattern. In benchtop validation, the navigation accuracy of the sCPI and the BrainLab Kick Navigation Station was compared using a skull phantom with 8 intracranial targets. Finally, we demonstrated the potential clinical application of sCPI through a clinical trial. Results: The resolution test showed that the resolution of the sCPI was 1.3 mm. In a stereotactic navigation accuracy test, the maximum and minimum error of the sCPI was 2.9 and 0.3 mm, and the mean error was 1.5 mm. The stereotactic navigation accuracy test also showed that the navigation error of the sCPI would increase with the pitch and yaw angle, but there was no obvious difference in navigation errors caused by different yaw directions, which meant that the navigation error is unbiased across all directions. The benchtop validation showed that the average navigation errors for the sCPI system and the Kick Navigation Station were 1.4±0.8 and 1.8±0.7 mm, the medians were 1.3 and 1.9 mm, and the average preparation times were 3 min 24 sec and 6 min 8 sec, respectively. The clinical feasibility of sCPI-assisted neurosurgical navigation was demonstrated in a clinical study. In comparison with the BrainLab device, the sCPI system required less time for preoperative preparation and enhanced the clinician experience in intraoperative visualization and navigation. Conclusions: The sCPI technique can be potentially used in many surgical applications for intuitive visualization of medical information and intraoperative guidance of surgical trajectories.

Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson's Disease.

PURPOSE: Parkinson's disease (PD) is a common neurodegenerative disease, for which cognitive impairment is a non-motor symptom (NMS). Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for PD. This study established a nomogram to predict cognitive improvement rate after STN-DBS in PD patients. METHODS: We retrospectively analyzed 103 PD patients who underwent STN-DBS. Patients were followed up to measure improvement in MoCA scores one year after surgery. Univariate and multivariate logistic regression analyses were used to identify factors affecting improvement in cognitive status. A nomogram was developed to predict this factor. The discrimination and fitting performance were evaluated by receiver operating characteristics (ROC) analysis, calibration diagram, and decision curve analysis (DCA). RESULTS: Among 103 patients, the mean improvement rate of the MoCA score was 37.3% and the median improvement rate was 27.3%, of which 64% improved cognition, 27% worsened cognition, and 8.7% remained unchanged. Logistic multivariate regression analysis showed that years of education, UPDRSIII drug use, MoCA Preop, and MMSE Preop scores were independent factors affecting the cognitive improvement rate. A nomogram model was subsequently developed. The C-index of the nomogram was 0.98 (95%CI, 0.97-1.00), and the area under the ROC was 0.98 (95%CI 0.97-1.00). The calibration plot and DCA demonstrated the goodness-of-fit between nomogram predictions and actual observations. CONCLUSION: Our nomogram could effectively predict the possibility of achieving good cognitive improvement one year after STN-DBS in patients with PD. This model has value in judging the expected cognitive improvement of patients with PD undergoing STN-DBS.

A New Application of Functional Zonal Image Reconstruction in Programming for Parkinson's Disease Treated Using Subthalamic Nucleus-Deep Brain Stimulation.

Objective: Programming plays an important role in the outcome of deep brain stimulation (DBS) for Parkinson's disease (PD). This study introduced a new application for functional zonal image reconstruction in programming. Methods: Follow-up outcomes were retrospectively compared, including first programming time, number of discomfort episodes during programming, and total number of programming sessions between patients who underwent image-reconstruction-guided programming and those who underwent conventional programming. Data from 142 PD patients who underwent subthalamic nucleus (STN)-DBS between January 2017 and June 2019 were retrospectively analyzed. There were 75 conventional programs and 67 image reconstruction-guided programs. Results: At 1-year follow-up, there was no significant difference in the rate of stimulus improvement or superposition improvement between the two groups. However, patients who underwent image reconstruction-guided programming were significantly better at the first programming time, number of discomfort episodes during programming, and total number of programming sessions than those who underwent conventional programming. Conclusion: Imaging-guided programming of directional DBS leads was possible and led to reduced programming time and reduced patient side effects compared with conventional programming.

Pileadanxiaensis (Urticaceae), a new species in the Danxia landform from Guangdong, China including a description of the entire chloroplast genome.

Pileadanxiaensis L.F.Fu, A.K.Monro & Y.G.Wei, a new species of Urticaceae from Danxia landform, Guangdong, China, is described and photographed. Phylogenetic analyses based on three DNA regions (ITS, trnL-F and rbcL) suggest that the new species belongs to P.sect.Pilea. Within the section, the new species is morphologically most similar to P.sinocrassifolia and P.peploides. Plastid genome and ribosomal DNA (rDNA) sequences of the new species are assembled and annotated. The plastid genome is 151,857 bp in length and comprises two inverted repeats (IRs) of 25,307 bp separated by a large single-copy of 82,836 bp and a small single-copy of 18,407 bp. A total of 113 functional genes are recovered, comprising 79 protein-coding genes, 30 tRNA genes, and four rRNA genes. A global conservation assessment suggests that P.danxiaensis should be classified as of Least Concern (LC).

Primulinanana (Gesneriaceae), a new species from eastern Guangxi, China.

Primulinanana C.Xiong, W.C.Chou & F.Wen, a new species of Gesneriaceae from limestone areas of Guangxi, China, is described and illustrated here. It morphologically resembles P.yangshuoensis Y.G.Wei & F.Wen in papillose leaf surface, but can be easily distinguished from the latter by noting a combination of characteristics, especially in its leaf blades, leaf blade indumentum characteristic, calyx lobes, corolla and the disc. We found only one population at the type locality, about 200 mature individuals. According to the IUCN Red List Categories and Criteria (Version 3.1), the new species is provisionally assessed as Critically Endangered (CR).

Bilateral Globus Pallidus Interna Combined With Subthalamic Nucleus Variable Frequency Deep Brain Stimulation in the Treatment of Young-Onset Parkinson's Disease With Refractory Dyskinesia: A Case Report.

Background: Main motor characteristics in Parkinson's disease (PD) include bradykinesia, rigidity, and tremors. With the development of neuromodulation techniques, it has become possible to use deep brain stimulation (DBS) to control the symptoms of PD. However, since the subthalamic nucleus(STN) and globus pallidus interna (GPi) DBS have their own advantages and disadvantages, it is difficult to control symptoms of the patients. It is essential to find new stimulation methods. Case Presentation: A 33-year-old male PD patient with onset at the age of 12 years. The onset of the disease is presented with bradykinesia and progressively developed severe choreic dyskinesia with the use of medications. We then performed a thorough evaluation of the patient and decided to perform bilateral globus pallidus interna combined with subthalamic nucleus variable frequency DBS (bSGC-DBS) implantation, and after 2 years of follow-up the patient's bradykinesia and dyskinesia symptoms and quality of life improved significantly. Conclusions: This is the first case of bSCG-DBS in a PD patient with refractory dyskinesia, and the first report of encouraging results from this clinical condition. This important finding explores multi-electrode and multi-target stimulation for the treatment of dystonia disorders.

CGHS Black Hole Analog Moving Mirror and Its Relativistic Quantum Information as Radiation Reaction.

The Callan-Giddings-Harvey-Strominger black hole has a spectrum and temperature that correspond to an accelerated reflecting boundary condition in flat spacetime. The beta coefficients are identical to a moving mirror model, where the acceleration is exponential in laboratory time. The center of the black hole is modeled by the perfectly reflecting regularity condition that red-shifts the field modes, which is the source of the particle creation. In addition to computing the energy flux, we find the corresponding moving mirror parameter associated with the black hole mass and the cosmological constant in the gravitational analog system. Generalized to any mirror trajectory, we derive the self-force (Lorentz-Abraham-Dirac), consistently, expressing it and the Larmor power in connection with entanglement entropy, inviting an interpretation of acceleration radiation in terms of information flow. The mirror self-force and radiative power are applied to the particular CGHS black hole analog moving mirror, which reveals the physics of information at the horizon during asymptotic approach to thermal equilibrium.

Vectorizing Quantum Turbulence Vortex-Core Lines for Real-Time Visualization.

Vectorizing vortex-core lines is crucial for high-quality visualization and analysis of turbulence. While several techniques exist in the literature, they can only be applied to classical fluids. As quantum fluids with turbulence are gaining attention in physics, extracting and visualizing vortex-core lines for quantum fluids is increasingly desirable. In this article, we develop an efficient vortex-core line vectorization method for quantum fluids enabling real-time visualization of high-resolution quantum turbulence structure. From a dataset obtained through simulation, our technique first identifies vortex nodes based on the circulation field. To vectorize the vortex-core lines interpolating these vortex nodes, we propose a novel graph-based data structure, with iterative graph reduction and density-guided local optimization, to locate sub-grid-scale vortex-core line samples more precisely, which are then vectorized by continuous curves. This vortex-core representation naturally captures complex topology, such as branching during reconnection. Our vectorization approach reduces memory consumption by orders of magnitude, enabling real-time visualization performance. Different types of interactive visualizations are demonstrated to show the effectiveness of our technique, which could help further research on quantum turbulence.

Free blood use among voluntary blood donors in Shiyan city / 中国输血杂志

【Objective】 To analyze the situation of free blood use and direct reimbursement of blood expenses in Shiyan city, so as to provide basis for more effective service of free blood use and direct reimbursement of blood expense after blood donation, and recruitment and retain of blood donors. 【Methods】 The data of free blood use from 1999 to 2019 in Shiyan city were collected for statistical analysis. Measurement data were described by mean±SD, and enumeration data were described by rate or construction ratio. Chi-square test was used for comparison of construction ratio or rate of stratified groups. 【Results】 In the past 21 years, free blood use has developed from the overall increasing stage (1999~2014) to the overall stable stage (2014~2019). Free blood use accounted for 3.52%(40 722.11/1 156 307.85)of the blood donation. Among the blood recipients, blood donors themselves accounted for only 18.83%(2 240/11 898), far lower than the proportion of their direct relatives. Since 2013, Shiyan has carried out the direct reimbursement of clinical blood expenses of voluntary blood donors according to the unified requirements of Hubei Province. The direct reimbursement rate over the past 7 years was 76.49%(5 397/7 056), and the proportion of people from other cities who applied for reimbursement was 4.02%(284/7 056). 【Conclusion】 The policy of free blood use and blood expense direct reimbursement has promoted the development of blood donation. It can also be further improved by relaxing the reimbursement scope of free blood use, strengthening publicity, optimizing services, strengthening supervision, using WeChat public service platform to carry out remote free blood, and strengthening national network construction.

Dynamic computational optical fringe mitigation in tunable laser absorption spectroscopy.

In optical spectroscopic systems where unwanted optical scattering cannot be eliminated, Fabry-Pérot etalons cause unpredictable changes in the spectral background. Frequent system calibration is then required to maintain the desired measurement accuracy, which presents a major limitation to the spectrometer. We introduce a computational approach to mitigate the adverse effects of optical fringing without hardware modifications. Motivated by experimental observations of complicated fringe behaviors, we simplify the problem by decomposing the fringe background into component etalons that can be addressed according to their individual characteristics. The effectiveness of the proposed method is demonstrated on a silicon photonic methane sensor, where accurate measurements of methane concentration are obtained from spectral data strongly affected by optical fringes.

Adaptive thermal stabilization of an integrated photonic spectrometer using parasitic interference fringes.

Parasitic fringe drift from unwanted scatterings limits the long-term stability of waveguide-based optical spectrometers. Yet their spectral features provide relevant information that can be used to improve performance of the spectrometer. We show that fringe drift can be extracted and utilized to perform accurate thermal stabilization, especially in the case of integrated waveguide sensors. In this Letter, effective stabilization of a methane silicon photonic sensor is demonstrated, and significant reduction in fringe noise is clearly observed.

Early onset of disc degeneration in SM/J mice is associated with changes in ion transport systems and fibrotic events.

Intervertebral disc degeneration (IDD) causes back pain and sciatica, affecting quality of life and resulting in high economic/social burden. The etiology of IDD is not well understood. Along with aging and environmental factors, genetic factors also influence the onset, progression and severity of IDD. Genetic studies of risk factors for IDD using human cohorts are limited by small sample size and low statistical power. Animal models amenable to genetic and functional studies of IDD provide desirable alternatives. Despite differences in size and cellular content as compared to human intervertebral discs (IVDs), the mouse is a powerful model for genetics and assessment of cellular changes relevant to human biology. Here, we provide evidence for early onset disc degeneration in SM/J relative to LG/J mice with poor and good tissue healing capacity respectively. In the first few months of life, LG/J mice maintain a relatively constant pool of notochordal-like cells in the nucleus pulposus (NP) of the IVD. In contrast, chondrogenic events are observed in SM/J mice beginning as early as one-week-old, with progressive fibrotic changes. Further, the extracellular matrix changes in the NP are consistent with IVD degeneration. Leveraging on the genomic data of two parental and two recombinant inbred lines, we assessed the genetic contribution to the NP changes and identified processes linked to the regulation of ion transport systems. Significantly, "transport" system is also in the top three gene ontology (GO) terms from a comparative proteomic analysis of the mouse NP. These findings support the potential of the SM/J, LG/J and their recombinant inbred lines for future genetic and biological analysis in mice and validation of candidate genes and biological relevance in human cohort studies. The proteomic data has been deposited to the ProteomeXchange Consortium via the PRIDE [1] partner repository with the dataset identifier PXD008784.

Towards High-Quality Visualization of Superfluid Vortices.

Superfluidity is a special state of matter exhibiting macroscopic quantum phenomena and acting like a fluid with zero viscosity. In such a state, superfluid vortices exist as phase singularities of the model equation with unique distributions. This paper presents novel techniques to aid the visual understanding of superfluid vortices based on the state-of-the-art non-linear Klein-Gordon equation, which evolves a complex scalar field, giving rise to special vortex lattice/ring structures with dynamic vortex formation, reconnection, and Kelvin waves, etc. By formulating a numerical model with theoretical physicists in superfluid research, we obtain high-quality superfluid flow data sets without noise-like waves, suitable for vortex visualization. By further exploring superfluid vortex properties, we develop a new vortex identification and visualization method: a novel mechanism with velocity circulation to overcome phase singularity and an orthogonal-plane strategy to avoid ambiguity. Hence, our visualizations can help reveal various superfluid vortex structures and enable domain experts for related visual analysis, such as the steady vortex lattice/ring structures, dynamic vortex string interactions with reconnections and energy radiations, where the famous Kelvin waves and decaying vortex tangle were clearly observed. These visualizations have assisted physicists to verify the superfluid model, and further explore its dynamic behavior more intuitively.