Microfluidic Approaches for Microactuators: From Fabrication, Actuation, to Functionalization.

Microactuators can autonomously convert external energy into specific mechanical motions. With the feature sizes varying from the micrometer to millimeter scale, microactuators offer many operation and control possibilities for miniaturized devices. In recent years, advanced microfluidic techniques have revolutionized the fabrication, actuation, and functionalization of microactuators. Microfluidics can not only facilitate fabrication with continuously changing materials but also deliver various signals to stimulate the microactuators as desired, and consequently improve microfluidic chips with multiple functions. Herein, this cross-field that systematically correlates microactuator properties and microfluidic functions is comprehensively reviewed. The fabrication strategies are classified into two types according to the flow state of the microfluids: stop-flow and continuous-flow prototyping. The working mechanism of microactuators in microfluidic chips is discussed in detail. Finally, the applications of microactuator-enriched functional chips, which include tunable imaging devices, micromanipulation tools, micromotors, and microsensors, are summarized. The existing challenges and future perspectives are also discussed. It is believed that with the rapid progress of this cutting-edge field, intelligent microsystems may realize high-throughput manipulation, characterization, and analysis of tiny objects and find broad applications in various fields, such as tissue engineering, micro/nanorobotics, and analytical devices.

Role of Ezrin in Asthma-Related Airway Inflammation and Remodeling.

Ezrin is an actin binding protein connecting the cell membrane and the cytoskeleton, which is crucial to maintaining cell morphology, intercellular adhesion, and cytoskeleton remodeling. Asthma involves dysfunction of inflammatory cells, cytokines, and airway structural cells. Recent studies have shown that ezrin, whose function is affected by extensive phosphorylation and protein interactions, is closely associated with asthma, may be a therapeutic target for asthma treatment. In this review, we summarize studies on ezrin and discuss its role in asthma-related airway inflammation and remodeling.

[Anti-asthma components and mechanism of Kechuanting acupoint application therapy: based on serum metabolomics and network pharmacology].

This study aims to explore the anti-asthma components and mechanism of Kechuanting acupoint application therapy(KAAT) based on serum metabolomics and network pharmacology. A total of 60 asthma patients who had used low-dose inhaled corticosteroids-formoterol(ICS-formoterol) for a long time were randomized into the western medicine group(low-dose ICS-formoterol) and western medicine+Kechuanting group(KAAT+low-dose ICS-Formoterol), 30 in either group. In addition, 30 healthy people were included as the control(no intervention). The asthma control test(ACT) score, forced expiratory volume in 1 second(FEV1), and peak expiratory flow(PEF) were measured in the western medicine group and western medicine+Kechuanting group before and after treatment. The potential biomarkers of KAAT in the treatment of asthma were screened by gas chromatography-mass spectrometry combined with multivariate analysis, and the related metabolic pathways were further analyzed. UPLC/LTQ-Orbitrap-MS, together with network pharmacology, was employed to construct the component-target-pathway network. Thereby, the effective components and me-chanism of KAAT in the treatment of asthma were clarified. According to the ACT score, FEV1, and PEF, KAAT was effective in the treatment of asthma. A total of 10 endogenous biomarkers of KAAT in the treatment of asthma were screened by serum metabolomics, and the pathways of the metabolism of glycine, serine and threonine, and the metabolism of glyoxylic acid and dicarboxylic acid were obtained. UPLC/LTQ-Orbitrap-MS identified 51 chemical components of KAAT: 24 flavonoids, 11 alkaloids, 8 phenols, 2 diterpenoids, 2 triterpenoids, 2 glycosides, and 2 aldehydes. Network pharmacology analysis suggested that KAAT mainly acted on serum crea-tinine(SRC), matrix metalloproteinase 9(MMP-9), and other target proteins. The treatment was closely related to metabolic pathway, phosphatidylinositol 3-kinase-protein kinase B(PI3 K-Akt), mitogen-activated protein kinase(MAPK), and calcium signaling pathway. Sinapine thiocyanate, corydaline, dihydroberberine, stylopine, leonticine, N-methyl tetrahydroberberine, kaempferide, erio-dictyol, quercetin, catechin, 6-gingerol, 6-shogaol, ingenol, and luteolin may be potential effective compounds of KAAT in the treatment of asthma. This study preliminarily revealed that the effective components and mechanism of KAAT in treatment of asthma based on serum metabolomics and network pharmacology. It lays a theoretical foundation for in-depth study of the mechanism and clinical development and application.

[Components of drugs in acupoint sticking therapy and its mechanism of intervention on bronchial asthma based on UPLC-Q-TOF-MS combined with network pharmacology and experimental verification].

UPLC-Q-TOF-MS combined with network pharmacology and experimental verification was used to explore the mechanism of acupoint sticking therapy(AST) in the intervention of bronchial asthma(BA). The chemical components of Sinapis Semen, Cory-dalis Rhizoma, Kansui Radix, Asari Radix et Rhizoma, and Zingiberis Rhizoma Recens were retrieved from TCMSP as self-built database. The active components in AST drugs were analyzed by UPLC-Q-TOF-MS, and the targets were screened out in TCMSP and Swiss-TargetPrediction. Targets of BA were collected from GeneCards, and the intersection of active components and targets was obtained by Venny 2.1.0. The potential targets were imported into STRING and DAVID for PPI, GO, and KEGG analyses. The asthma model induced by house dust mite(HDM) was established in mice. The mechanism of AST on asthmatic mice was explored by pulmonary function, Western blot, and flow cytometry. The results indicated that 54 active components were obtained by UPLC-Q-TOF-MS and 162 potential targets were obtained from the intersection. The first 53 targets were selected as key targets. PPI, GO, and KEGG analyses showed that AST presumedly acted on SRC, PIK3 CA, and other targets through active components such as sinoacutine, sinapic acid, dihydrocapsaicin, and 6-gingerol and regulated PI3 K-AKT, ErbB, chemokine, sphingolipid, and other signaling pathways to intervene in the pathological mechanism of BA. AST can improve lung function, down-regulate the expression of PI3 K and p-AKT proteins in lung tissues, enhance the expression of PETN protein, and reduce the level of type Ⅱ innate immune cells(ILC2 s) in lung tissues of asthmatic mice. In conclusion, AST may inhibit ILC2 s by down-regulating the PI3 K-AKT pathway to relieve asthmatic airway inflammation and reduce airway hyperresponsiveness.

Automatic couch position calculation using eclipse scripting for external beam radiotherapy.

PURPOSE: The treatment couch position of a patient in external beam radiation therapy (EBRT) is usually acquired during initial treatment setup. This procedure has shown potential failure modes leading to near misses and adverse events in radiation treatment. This study aims to develop a method to automatically determine the couch position before setting up a patient for initial treatment. METHODS: The Qfix couch-tops (kVue and DoseMax) have embedded reference marks (BBs) indicating its index levels and couch centerline. With the ESAPI, a C# script was programmed to automatically find the couch-top and embedded BBs in the planning CT and derive the treatment couch position according to treatment isocenter of a plan. Couch positions of EBRT plans with the kVue couch-top and SBRT plans using the DoseMax were calculated using the script. The calculation was evaluated by comparing calculated positions with couch coordinates captured during the initial treatment setup after image guidance. The calculations were further compared with daily treatment couch positions post image-guided adjustment for each treatment fraction. RESULTS: For plans using the kVue couch-top for various treatment sites, the median (5-95 percentiles) differences between calculated and captured couch positions were 0.1 (-0.2 - 0.9), 0.5 (-1.1-2.0), 0.10 (-1.3-1.3) cm in the vertical, longitudinal, and lateral direction respectively. For the DoseMax couch-top, the median differences were 0.1 (-0.2-0.7), 0.2 (-0.3-1.1), and 0.2 (-0.7-0.9) cm in respective direction. The calculated positions were within 1 and 2 cm from the mean fraction positions for 95% patients on DoseMax and kVue couch-top respectively. CONCLUSIONS: A method that automatically and accurately calculates treatment couch position from simulation CT was implemented in Varian Eclipse for Qfix couch-tops. This technique increases the efficiency of patient setup and enhances patient safety by reducing the risks of positioning errors.

Adaptive radiotherapy based on statistical process control for oropharyngeal cancer.

PURPOSE: The purpose of this study is to quantify dosimetric changes throughout the delivery of oropharyngeal cancer treatment and to investigate the application of statistical process control (SPC) for the management of significant deviations during the course of radiotherapy. METHODS: Thirteen oropharyngeal cancer patients with daily cone beam computed tomography (CBCT) were retrospectively reviewed. Cone beam computed tomography images of every other fraction were imported to the Velocity software and registered to planning CT using the 6 DOF (degrees of freedom) couch shifts generated during patient setup. Using Velocity "Adaptive Monitoring" module, the setup-corrected CBCT was matched to planning CT using a deformable registration. Volumes and dose metrics at each fraction were calculated and rated with plan values to evaluate interfractional dosimetric variations using a SPC framework. T-tests between plan and fraction volumes were performed to find statistically insignificant fractions. Average upper and lower process capacity limits (UCL, LCL) of each dose metric were derived from these fractions using conventional SPC guidelines. RESULTS: Gross tumor volume (GTV) and organ at risk (OAR) volumes in the first 13 fractions had no significant changes from the pretreatment planning CT. The GTV and the parotid glands subsequently decreased by 10% at the completion of treatment. There were 3-4% increases in parotid mean doses, but no significant differences in dose metrics of GTV and other OARs. The changes were organ and patient dependent. Control charts for various dose metrics were generated to assess the metrics at each fraction for individual patient. CONCLUSIONS: Daily CBCT could be used to monitor dosimetric variations of targets and OARs resulting from volume changes and tissue deformation in oropharyngeal cancer radiotherapy. Treatment review with the guidance of a SPC tool allows for an objective and consistent clinical decision to apply adaptive radiotherapy.

Emerging role of MRI in radiation therapy.

Advances in multimodality imaging, providing accurate information of the irradiated target volume and the adjacent critical structures or organs at risk (OAR), has made significant improvements in delivery of the external beam radiation dose. Radiation therapy conventionally has used computed tomography (CT) imaging for treatment planning and dose delivery. However, magnetic resonance imaging (MRI) provides unique advantages: added contrast information that can improve segmentation of the areas of interest, motion information that can help to better target and deliver radiation therapy, and posttreatment outcome analysis to better understand the biologic effect of radiation. To take advantage of these and other potential advantages of MRI in radiation therapy, radiologists and MRI physicists will need to understand the current radiation therapy workflow and speak the same language as our radiation therapy colleagues. This review article highlights the emerging role of MRI in radiation dose planning and delivery, but more so for MR-only treatment planning and delivery. Some of the areas of interest and challenges in implementing MRI in radiation therapy workflow are also briefly discussed. Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;48:1468-1478.

A cable-driven soft robot surgical system for cardiothoracic endoscopic surgery: preclinical tests in animals.

BACKGROUND: Minimally invasive surgery attracts more and more attention because of the advantages of minimal trauma, less bleeding and pain and low complication rate. However, minimally invasive surgery for beating hearts is still a challenge. Our goal is to develop a soft robot surgical system for single-port minimally invasive surgery on a beating heart. MATERIALS AND METHODS: The soft robot described in this paper is inspired by the octopus arm. Although the octopus arm is soft and has more degrees of freedom (DOFs), it can be controlled flexibly. The soft robot is driven by cables that are embedded into the soft robot manipulator and can control the direction of the end and middle of the soft robot manipulator. The forward, backward and rotation movement of the soft robot is driven by a propulsion plant. The soft robot can move freely by properly controlling the cables and the propulsion plant. The soft surgical robot system can perform different thoracic operations by changing surgical instruments. To evaluate the flexibility, controllability and reachability of the designed soft robot surgical system, some testing experiments have been conducted in vivo on a swine. RESULTS: Through the subxiphoid, the soft robot manipulator could enter into the thoracic cavity and pericardial cavity smoothly and perform some operations such as biopsy, ligation and ablation. The operations were performed successfully and did not cause any damage to the surrounding soft tissues. From the experiments, the flexibility, controllability and reachability of the soft robot surgical system have been verified. Also, it has been shown that this system can be used in the thoracic and pericardial cavity for different operations. CONCLUSIONS: Compared with other endoscopy robots, the soft robot surgical system is safer, has more DOFs and is more flexible for control. When performing operations in a beating heart, this system maybe more suitable than traditional endoscopy robots.

Effectiveness of Antibiotic Use Management in Tianjin (2011-2013): A Quasi-Experimental Study.

BACKGROUND In this study we investigated changes in the status of antibiotic use in Tianjin since the implementation of the Antibiotic Stewardship Program (ASP) (2011-2013), as well as existing problems, strategies, and outcomes to promote rational clinical antibiotic use. MATERIAL AND METHODS A quasi-experimental study was performed to investigate situations of antibiotic use in secondary and tertiary general hospitals in Tianjin from April 2011 to 2013. Five major indicators were analyzed: percentage of antibiotic use in inpatient cases (%), antibacterial use density (AUD), proportion of prophylactic antibiotic application for type I surgical incision, compliance rate of medication administration 0.5-2.0 h before such procedures, and antibiotic prophylaxis for ≤24 h in patients receiving these surgeries. RESULTS There was a decrease in the percentage of antibiotic use across general hospitals (60.38% to 46.88%), in AUD (51.60% to 35.37%), and in the proportion of prophylactic antibiotic applications for type I incisions (86.67% to 25.08%). For patients undergoing these procedures, there was an increased compliance rate of medication administration of 0.5-2.0 h prior to surgery (86.38% to 100%), and of antibiotic prophylactic use for ≤24 h (40.30% to 96.37%). CONCLUSIONS Implementation of the ASP campaign has reduced irrational antibiotic use, promoted rational antibiotic use, and delayed antibiotic resistance.

Plant diversity accurately predicts insect diversity in two tropical landscapes.

Plant diversity surely determines arthropod diversity, but only moderate correlations between arthropod and plant species richness had been observed until Basset et al. (Science, 338, 2012 and 1481) finally undertook an unprecedentedly comprehensive sampling of a tropical forest and demonstrated that plant species richness could indeed accurately predict arthropod species richness. We now require a high-throughput pipeline to operationalize this result so that we can (i) test competing explanations for tropical arthropod megadiversity, (ii) improve estimates of global eukaryotic species diversity, and (iii) use plant and arthropod communities as efficient proxies for each other, thus improving the efficiency of conservation planning and of detecting forest degradation and recovery. We therefore applied metabarcoding to Malaise-trap samples across two tropical landscapes in China. We demonstrate that plant species richness can accurately predict arthropod (mostly insect) species richness and that plant and insect community compositions are highly correlated, even in landscapes that are large, heterogeneous and anthropogenically modified. Finally, we review how metabarcoding makes feasible highly replicated tests of the major competing explanations for tropical megadiversity.

[Vertebroplasty compared with conservative method of integrated Chinese and Western Medicine in patients with osteoporotic vertebral compression fractures].

OBJECTIVE: To compare the effects of percutaneous vertebroplasty (PVP) versus conservative method of integrated Chinese and Western Medicine for pain relief and functional outcome in patients with painful osteoporotic vertebral fractures. New fractures and secondary adverse effects were also analyzed during a mid-long term follow-up period. METHODS: Patients were recruited to this prospective nonrandomized trial from a single hospital. Patients were aged 55 years or older, had vertebral compression fractures on spine radiograph (level of fracture at T6 or lower; bone oedema on MRI), with back pain for 6 weeks or less, and a visual analogue scale (VAS) score of 6 or more. Patients were nonrandomly assigned to PVP group or conservative treatment group according to their own desire. After 2 weeks, patients from the conservative group could change therapy to PVP. VAS for pain and Oswestry disability index (ODI) questionnaire scores were assessed before and 1 week, 1 month, 3, 6, 12, 24, 36, 48, and 60 months after the treatment. Other data included patients' baseline characteristics before the treatment, new fractures and secondary adverse effects were also recorded. RESULTS: A total of 181 consecutive patients were nonrandomly allocated to receive PVP (n=103) or conservative treatment (n=78) between December 2009 and August 2013. Six patients transferred to PVP group after 2 weeks conservative therapy. Pain relief and functional outcomes were significantly better in PVP group than in conservative group, as determined by VAS scores (3.67-1.13 vs 7.38-2.39) and ODI scores (23.55-5.83 vs 36.10-13.88) at 1 week, 1 month, 3 and 6 months (all P< 0.01). Both VAS and ODI scores decreased in PVP group showed no statistical significance at 1 year when compared with conservative group (P>0.05). However, pain relief and functional outcomes were significantly better at most of the subsequent follow-up points. The patients with complete pain relief (VAS<1) were significantly better in PVP group than in conservative group (P< 0.01) at all of the follow-up points. There were 17 patients died (PVP group: n=8) and 31 cases occurred secondary vertebral fractures (PVP group: n=19) during the follow-up periods. No serious complications or adverse events were related to PVP technique. CONCLUSION: PVP has immediate pain relief and functional improvement compared with conservative treatment. PVP should be considered as the treatment of first choice for symptomatic osteoporotic vertebral fractures. However, for patients with VAS < 5, conservative method of integrated Chinese and Western Medicine may perform well.

[Effect of Acupuncture Combined Physical Training and Relearning on Stroke Rehabilitation: a Multi-center Randomized Controlled Clinical Study].

OBJECTIVE: To observe the effect of acupuncture combined physical training and relearning on stroke patients. METHODS: A multi-center, randomized controlled trial design was adopted. A total of 364 stroke patients were recruited and randomly assigned to the experimental group (184 cases) and the control group (180 cases). Patients in the experimental group received acupuncture combined with physical training and relearning, while those in the control group only received physical training and relearning. All received four weeks of treatment. Effects on Fugl-Meyer motor function, neurological impairment, activities of daily living difference were compared before treatment, after treatment, 2 and 5 months after follow-ups between the two groups. RESULTS: Totally 353 patients completed this trial, 179 in the experimental group and 174 in the control group. (1) compared with before treatment, brief Fugl-Meyer motor functions scores and FIM scored obviously increased, and scores for neurological impairment obviously decreased in the two group. Besides, the increment of brief Fugl-Meyer motor functions scores and FIM scores was obviously higher in the experimental group than in the control group at month 2 and 5 of follow-ups; scores for neurological impairment was obviously lower in the experimental group than in the control group. The increment of FIM scores was obviously higher in the experimental group than in the control group at month 5 of follow-ups (P < 0.05, P < 0.01). (2) There was statistical difference in inter-group comparison of total Fugl-Meyer motor functions scores and FIM scores, or scores for neurological impairment (P < 0.01). The improvement of Fugl-Meyer motor functions grading and neurological impairment grading was obviously superior in the experimental group at month 2 and 5 of follow-ups. The distribution of FIM grading was also better in the experimental group at month 5 of follow-ups (P < 0.05, P < 0. 01). CONCLUSIONS: Both acupuncture combined exercise training and relearning and physical training and relearning could effectively promote the rehabilitation of stroke patients, reduce their neurological impairment degrees, improve motor functions and independent capacities. Better long-term efficacy could be obtained by acupuncture combined exercise training and relearning.

BDNF attenuates IL-1ß-induced F-actin remodeling by inhibiting NF-κB signaling in hippocampal neurons.

OBJECTIVES: To examine the effect of BDNF on F-actin during the stimulation of IL-1ß in hippocampal neurons. MATERIALS & METHODS: We cultured hippocampal neurons from rat embryos. Cell stimulation was induced by IL-1ß. Cell culture success was evaluated by an activity analysis of CCK-8, staining of gliocyte by immunohistochemistry. Changes in F-actin, BDNF and NF-ĸB were examined using molecular analyses. RESULTS: Our results demonstrate that a high concentration of IL-1ß exaggerates the stimulation-induced degradation of F-actin by BDNF, whereas a low concentration of IL-1ß protects F-actin against this degradation. These beneficial effects might be associated with the inhibition or exaggeration of the NF-ĸB signaling cascade. CONCLUSIONS: Taken together, our findings indicate that BDNF acts as an F-actin-protective regulator during stimulation by IL-1ß and that this function largely occurs via the regulation of NF- ĸB signaling. These results suggest that interventions targeting the BDNF signaling system may be of therapeutic value against major depressive disorder (MDD).

Visuomotor Navigation for Embodied Robots With Spatial Memory and Semantic Reasoning Cognition.

The fundamental prerequisite for embodied agents to make intelligent decisions lies in autonomous cognition. Typically, agents optimize decision-making by leveraging extensive spatiotemporal information from episodic memory. Concurrently, they utilize long-term experience for task reasoning and foster conscious behavioral tendencies. However, due to the significant disparities in the heterogeneous modalities of these two cognitive abilities, existing literature falls short in designing effective coupling mechanisms, thus failing to endow robots with comprehensive intelligence. This article introduces a navigation framework, the hierarchical topology-semantic cognitive navigation (HTSCN), which seamlessly integrates both memory and reasoning abilities within a singular end-to-end system. Specifically, we represent memory and reasoning abilities with a topological map and a semantic relation graph, respectively, within a unified dual-layer graph structure. Additionally, we incorporate a neural-based cognition extraction process to capture cross-modal relationships between hierarchical graphs. HTSCN forges a link between two different cognitive modalities, thus further enhancing decision-making performance and the overall level of intelligence. Experimental results demonstrate that in comparison to existing cognitive structures, HTSCN significantly enhances the performance and path efficiency of image-goal navigation. Visualization and interpretability experiments further corroborate the promoting role of memory, reasoning, as well as their online learned relationships, on intelligent behavioral patterns. Furthermore, we deploy HTSCN in real-world scenarios to further verify its feasibility and adaptability.

Integrating Neural Radiance Fields End-to-End for Cognitive Visuomotor Navigation.

We propose an end-to-end visuomotor navigation framework that leverages Neural Radiance Fields (NeRF) for spatial cognition. To the best of our knowledge, this is the first effort to integrate such implicit spatial representation with embodied policy end-to-end for cognitive decision-making. Consequently, our system does not necessitate modularized designs nor transformations into explicit scene representations for downstream control. The NeRF-based memory is constructed online during navigation, without relying on any environmental priors. To enhance the extraction of decision-critical historical insights from the rigid and implicit structure of NeRF, we introduce a spatial information extraction mechanism named Structural Radiance Attention (SRA). SRA empowers the agent to grasp complex scene structures and task objectives, thus paving the way for the development of intelligent behavioral patterns. Our comprehensive testing in image-goal navigation tasks demonstrates that our approach significantly outperforms existing navigation models. We demonstrate that SRA markedly improves the agent's understanding of both the scene and the task by retrieving historical information stored in NeRF memory. The agent also learns exploratory awareness from our pipeline to better adapt to low signal-to-noise memory signals in unknown scenes. We deploy our navigation system on a mobile robot in real-world scenarios, where it exhibits evident cognitive capabilities while ensuring real-time performance.

Exploring the body surface temperature of the lumbosacral region and relevant back-shu points in patients with lumbar disc herniation induced low back pain based on infrared thermography. / åŸºäºŽçº¢å¤–çƒ­æˆåƒæŠ€æœ¯æŽ¢è®¨è °æ¤Žé—´ç›˜çªå‡ºç—‡è °ç—›æ‚£è€ è °éª¶éƒ¨åŠç›¸å ³èƒŒä¿žç©´è¡¨çš®æ¸©åº¦.

OBJECTIVES: To observe the body surface temperature of the lumbosacral region and relevant back-shu points in patients with lumbar disc herniation (LDH) induced low back pain utilizing infrared thermography, and to explore the functional attribute changes of acupoints under pathological conditions. METHODS: A total of 50 patients with LDH induced low back pain were included as the observation group, and 45 healthy subjects were included as the control group. Using infrared thermography, the body surface temperature of the lumbosacral region and bilateral Sanjiaoshu (BL 22), Shenshu (BL 23), Qihaishu (BL 24), Dachangshu (BL 25), Guanyuanshu (BL 26), Xiaochangshu (BL 27), and Pangguangshu (BL 28) was measured in both groups. The temperature difference values between the bilateral lumbosacral regions and back-shu points of the two groups were calculated. Additionally, the body surface temperature of the affected and healthy sides of the lumbosacral region and relevant back-shu points was compared in the observation group. RESULTS: Compared with the control group, the body surface temperature of the lumbosacral region and the bilateral temperature difference values of the lumbosacral regions were increased in the observation group (P<0.001). The body surface temperature difference values of bilateral Shenshu (BL 23), Qihaishu (BL 24), Dachangshu (BL 25), Guanyuanshu (BL 26) and Xiaochangshu (BL 27) in the observation group were higher than those in the control group (P<0.05, P<0.01, P<0.001). In the observation group, the body surface temperature of the affected side of the lumbosacral region as well as Shenshu (BL 23) and Dachangshu (BL 25) was elevated compared with that of healthy side (P<0.001). CONCLUSIONS: The patients with LDH induced low back pain have imbalanced and asymmetrical distribution of body surface temperature in the lumbosacral region and related back-shu points, Shenshu (BL 23) and Dachangshu (BL 25) have the relative specificity.

Whole-Genome Analyses Reveal the Distinct Taxonomic Status of the Hainan Population of Endangered Rucervus eldii and Its Conservation Implications.

Eld's deer Rucervus eldii (McClelland, 1842) is an ungulate that lives in tropical lowland forests in several countries of Indochina and Hainan Island of China. Its remaining population is small and scattered, and the species is listed as an Endangered species on the IUCN Red List. The debate over the taxonomic status of the Hainan population has persisted for over a century-as an island-endemic subspecies R. e. hainanus, or an insular population of the subspecies R. e. siamensis, would have significant conservation implications. And, given the Hainan population had experienced both population bottleneck and multiple translocations in the past, conservation genomics would be a powerful tool to evaluate the genetic impacts of these events. In this study, we used conservation genomics assessment to study population differentiation and genetic diversity of R. e. siamensis in Cambodia and three Eld's deer subpopulations on Hainan Island. Based on the unique genetic profile and demographic analysis, this study corroborated previous studies using genetic markers that the Hainan Eld's deer warrants the taxonomic status of a distinct subspecies. The Hainan population exhibits a reduction in genetic diversity and an increase in the level of inbreeding when compared to the population of Cambodia. The signs of purifying selection were found against homozygous loss-of-function mutations to decrease the deleterious burden in the Hainan population. However, there was an accumulation of more deleterious missense mutations. Furthermore, significant differences in genetic diversity and level of inbreeding found among the three Hainan subpopulations indicated population isolation and suboptimal translocation strategies, which calls for urgent, coordinated, and science-based genetic management to ensure the long-term viability of the endemic subspecies hainanus. This study provides guidance for the conservation and management of Eld's deer.

Extended nnU-Net for Brain Metastasis Detection and Segmentation in Contrast-Enhanced Magnetic Resonance Imaging With a Large Multi-Institutional Data Set.

PURPOSE: The purpose of this study was to investigate an extended self-adapting nnU-Net framework for detecting and segmenting brain metastases (BM) on magnetic resonance imaging (MRI). METHODS AND MATERIALS: Six different nnU-Net systems with adaptive data sampling, adaptive Dice loss, or different patch/batch sizes were trained and tested for detecting and segmenting intraparenchymal BM with a size ≥2 mm on 3 Dimensional (3D) post-Gd T1-weighted MRI volumes using 2092 patients from 7 institutions (1712, 195, and 185 patients for training, validation, and testing, respectively). Gross tumor volumes of BM delineated by physicians for stereotactic radiosurgery were collected retrospectively and curated at each institute. Additional centralized data curation was carried out to create gross tumor volumes of uncontoured BM by 2 radiologists to improve the accuracy of ground truth. The training data set was augmented with synthetic BMs of 1025 MRI volumes using a 3D generative pipeline. BM detection was evaluated by lesion-level sensitivity and false-positive (FP) rate. BM segmentation was assessed by lesion-level Dice similarity coefficient, 95-percentile Hausdorff distance, and average Hausdorff distance (HD). The performances were assessed across different BM sizes. Additional testing was performed using a second data set of 206 patients. RESULTS: Of the 6 nnU-Net systems, the nnU-Net with adaptive Dice loss achieved the best detection and segmentation performance on the first testing data set. At an FP rate of 0.65 ± 1.17, overall sensitivity was 0.904 for all sizes of BM, 0.966 for BM ≥0.1 cm3, and 0.824 for BM <0.1 cm3. Mean values of Dice similarity coefficient, 95-percentile Hausdorff distance, and average HD of all detected BMs were 0.758, 1.45, and 0.23 mm, respectively. Performances on the second testing data set achieved a sensitivity of 0.907 at an FP rate of 0.57 ± 0.85 for all BM sizes, and an average HD of 0.33 mm for all detected BM. CONCLUSIONS: Our proposed extension of the self-configuring nnU-Net framework substantially improved small BM detection sensitivity while maintaining a controlled FP rate. Clinical utility of the extended nnU-Net model for assisting early BM detection and stereotactic radiosurgery planning will be investigated.

Nonlinear Observer-Based Visual Servoing and Vibration Control of Flexible Robotic Manipulators With a Fixed Camera.

This article studies the visual servoing and vibration suppression control for flexible manipulators when the system states are unmeasurable and only the image feedback is available. The dynamic equations of flexible manipulators are decomposed into the slow and fast subsystems based on the singular perturbation theory. The nonlinear observers based on the state transformation using the Lie derivatives are proposed to estimate the unmeasurable system states and unknown camera intrinsic parameters at the same time. Then, the image-based controllers utilizing the estimated states are, respectively, designed in the slow and fast subsystems to regulate the image positions of feature points and suppress the vibration of flexible manipulators simultaneously. In the proposed approach, only the visual feedback is required to generate the control input for flexible manipulators, which simplifies the controller implementation. The stability of the proposed control scheme is proved based on the Lyapunov theory. Finally, experimental results on a flexible single-link manipulator are provided to demonstrate the effectiveness of the proposed control approach.

Efficient 3D Deep LiDAR Odometry.

An efficient 3D point cloud learning architecture, named EfficientLO-Net, for LiDAR odometry is first proposed in this article. In this architecture, the projection-aware representation of the 3D point cloud is proposed to organize the raw 3D point cloud into an ordered data form to achieve efficiency. The Pyramid, Warping, and Cost volume (PWC) structure for the LiDAR odometry task is built to estimate and refine the pose in a coarse-to-fine approach. A projection-aware attentive cost volume is built to directly associate two discrete point clouds and obtain embedding motion patterns. Then, a trainable embedding mask is proposed to weigh the local motion patterns to regress the overall pose and filter outlier points. The trainable pose warp-refinement module is iteratively used with embedding mask optimized hierarchically to make the pose estimation more robust for outliers. The entire architecture is holistically optimized end-to-end to achieve adaptive learning of cost volume and mask, and all operations involving point cloud sampling and grouping are accelerated by projection-aware 3D feature learning methods. The superior performance and effectiveness of our LiDAR odometry architecture are demonstrated on KITTI, M2DGR, and Argoverse datasets. Our method outperforms all recent learning-based methods and even the geometry-based approach, LOAM with mapping optimization, on most sequences of KITTI odometry dataset. We open sourced our codes at: https://github.com/IRMVLab/EfficientLO-Net.