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IntroductionClinical studies have revealed the existence of circadian rhythms in pain intensity and treatment response for chronic pain, including orofacial pain. The circadian clock genes in the peripheral ganglia are involved in pain information transmission by modulating the synthesis of pain mediators. However, the expression and distribution of clock genes and pain-related genes in different cell types within the trigeminal ganglion, the primary station of orofacial sensory transmission, are not yet fully understood.MethodsIn this study, data from the normal trigeminal ganglion in the Gene Expression Omnibus (GEO) database were used to identify cell types and neuron subtypes within the human and mouse trigeminal ganglion by single nucleus RNA sequencing analysis. In the subsequent analyses, the distribution of the core clock genes, pain-related genes, and melatonin and opioid-related genes was assessed in various cell clusters and neuron subtypes within the human and mouse trigeminal ganglion. Furthermore, the statistical analysis was used to compare the differences in the expression of pain-related genes in the neuron subtypes of trigeminal ganglion.ResultsThe present study provides comprehensive transcriptional profiles of core clock genes, pain-related genes, melatonin-related genes, and opioid-related genes in different cell types and neuron subtypes within the mouse and human trigeminal ganglion. A comparative analysis of the distribution and expression of the aforementioned genes was conducted between human and mouse trigeminal ganglion to investigate species differences.DiscussionOverall, the results of this study serve as a primary and valuable resource for exploring the molecular mechanisms underlying oral facial pain and pain rhythms.

Redundant dual-arm robots provide an effective strategy for the automated achievement of complex assembly operations. Moreover, being kinematically redundant, they simultaneously perform numerous tasks with different priorities. The principal task, obstacle avoidance is generally used as a subtask mainly when the robot is interacting with humans. This paper presents a real-time obstacle avoidance algorithm based on the self-motion characteristic of a redundant dual-arm robot, solving the problem of collision between environmental obstacles and manipulators during operation. The method leans on the gradient “projection method’’, obtaining the shortest distance between the middle of the obstacle and the connecting rod axis of the two arms in the environment. Moreover, two obstacle avoidance factors are introduced to change the manipulator avoidance speed in real-time; then, the workability of the dual-arm robot is ameliorated increasing the robot’s efficiency. By establishing the absolute and relative pose variables, the stability of the two arms during the cooperative task operation is defined, making the problem of self-collision avoidance in the working environment continuous and smooth. The simulation experiment verifies the practicability and efficacy of the proposed algorithm

In order to obtain and analyze the operator’s intention comprehensively and accurately in human-robot interaction, an array-type flexible tactile sensor was designed. The sensor was encapsulated into a tactile handle to sense the grasping state of the human hand in real time. According to the analysis of different operators’ grasping posture and grasping habits, the grasping state was defined as 5 modes. Based on Harris feature point positioning and extraction, a method of grasping posture conversion was proposed to ensure the completeness and standard of the extracted grasping features. A set of Convolutional Neural Networks (CNN) suitable for the real-time classification of the grasping intention was built to distinguish the grasping state sensed by the handle in real time, accurately determine the operator’s intention, and complete the interaction with the robot. Using a UR collaborative robot as the experimental platform and the haptic handle as the intent sensing device, the intent-behaviour mapping relationship was constructed to control the motion of the UR collaborative robot. The experimental results show that the classification accuracy of operation intention is as high as 97.87%.

The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development. This Perspective outlines the Human Developmental Cell Atlas initiative, which uses state-of-the-art technologies to map and model human development across gestation, and discusses the early milestones that have been achieved.

Background: Few epidemiological studies have explored the effects of air pollution on the risk of drug-resistant tuberculosis (DR-TB). Objective: To investigate the short and long term residential concentrations of ambient air pollutants (particulate matter

Qiqi An,1 Wanmei Song,1 Jinyue Liu,2 Ningning Tao,3 Yao Liu,4 Qianyun Zhang,1 Tingting Xu,4 Shijin Li,1 Siqi Liu,1 Yifan Li,4 Chunbao Yu,5 Huaichen Li1,4,6 1Department of Respiratory Medicine, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People’s Republic of China; 2Intensive Care Unit, Shandong Provincial Third Hospital, Jinan, Shandong 100191, People’s Republic of China; 3Peking Union Medical College, Beijing 100005, People’s Republic of China; 4Department of Respiratory Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250021, People’s Republic of China; 5Department of Respiratory Medicine, Shandong Provincial Chest Hospital, Jinan, Shandong 250013, People’s Republic of China; 6Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250355, People’s Republic of ChinaCorrespondence: Chunbao Yu; Huaichen Li Email 13505412137@139.com; lihuaichen@163.comBackground: With an aging population, China is facing a huge burden of elderly patients with drug resistant tuberculosis (DR-TB), which has become a significant obstacle for the global TB control. There is still little study on DR-TB in the elderly in China so far. Thus, more research on the epidemiological characteristics and trend of primary DR-TB among the elderly will be necessary.Methods: A retrospective study was conducted in Shandong, China from 2004 to 2019. We collected 12,661 primary TB cases, of which 4368 elderly (≥ 60 years) primary TB cases were involved. Clinical characteristics including age, sex, cavity, smoking, drinking, comorbidity and drug susceptibility data were collected from 36 TB prevention and control institutions of Shandong Province. Sputum samples were collected by each surveillance site, and examined in the TB Reference Laboratory of SPCH. Descriptive statistical analysis, chi-square and linear regression were used for analyzing.Results: Among 4368 elderly patients with primary TB, the DR-TB and multi-resistant tuberculosis (MDR-TB) accounted for 17.19% and 2.29%, respectively. During 2004– 2019, the proportions of MDR-TB, polydrug resistant tuberculosis (PDR-TB), rifampin (RFP)-resistance increased by 160.00%, 18.18%, 231.82%, respectively and the rate of DR-TB among elderly patients with primary cavitary TB increased by 255%. Among the elderly with primary DR-TB during 2004– 2019, the proportion of male (from 85.19 to 89.06), cavity (from 7.41 to 46.88), RFP-resistance (from 3.70 to 21.88), and streptomycin (SM)-resistance (from 37.04 to 62.5) increased significantly (P< 0.05). And the proportion of female (from 14.81 to 10.94), non-cavity (from 92.59 to 32.81), INH-resistance (from 66.67 to 57.81) decreased significantly (P< 0.05).Conclusion: Among the elderly, the proportions of MDR-TB, PDR-TB, RFP-resistance and cavitary DR-TB increased significantly. The pattern of DR-TB changed from female, non-cavity and INH-resistant groups to male, cavity, RFP or SM-resistant groups. For a better control on the elderly DR-TB in the future, we should pay more attention to male, smoking, drinking, chronic obstructive pulmonary disease (COPD) and diabetes subgroups and take targeted measures to control these subgroups.Keywords: primary DR-TB, the elderly, epidemiology, chi-square regression, linear regression

With precision components on circuit boards and other detection techniques becoming increasingly demanding, AOI has the characteristic of non-contact, high speed and high precision, which makes it widely used in the detection field. In order to improve the detection efficiency, detection area trajectory of CCD camera needs to be planed before the test. In this paper, the genetic algorithm is used for clustering component to be detected, thus determine the area for detecting. Generate the individual of local optimal solution on the basis of actual constraints, which could quickly find the optimal solution to clustering, reducing the number of iterations. This algorithm effectively solves the problem of detection range optimization during the automated optical detection, which has a great impact on improving the detection efficiency.

Seismic amplitude variation versus offset (AVO) inversion is widely used technology in reservoir geophysics, for estimating the elastic parameters of the Earth subsurface media. Following the ray-impedance concept, I conducted the AVO inversion in the ray-parameter domain. The pre-stack seismic gathers are constructed in the ray-parameter domain, by using a bending ray-tracing method. One of my research objectives is to estimate three elastic parameters from the single P-wave data with limited angle/offsets. The conventional single P-wave AVO inversion has difficulty in estimating three elastic parameters simultaneously, especially for the bulk density. I attempted to constrain the non-linear AVO inversion results with the geological interpreted horizons, assuming each stratified layer is homogeneous. This geological operator transforms the sample-based models into the layer-based models and hence produces geologically meaningful inversion results. I also applied the first-order spatial derivative as the Tikhonov regularisation operator to control the lateral continuity. I demonstrated that, using the proposed geological layer constraints and the spatial regularisation operator, reliable inversion results with high lateral continuity can be obtained. I employed a subspace inversion method, in which three elastic parameters are separated into different subspaces in order to invert for the three elastic parameters simultaneously: P-wave impedance, S-wave impedance and the density. I parameterised each model of single elastic parameter by a Fourier series in which the Fourier coefficients of different wavenumber components are grouped into different subspaces. In order to further handle different sensitivities associated to different groups of coefficients, the Hessian matrix is also modified by applying a range of damping factors to different coefficients within each subspace. This inversion scheme is referred to as multi-damped subspace method. I applied the ray-parameter domain, multi-damped subspace method to two field datasets. One of field datasets is from the Tarim basin where deposited an Ordovician carbonate reservoir, and the other is from Ordos basin where deposited a coal bearing gas reservoir. The multi-damped inversion results show a high resolution and a good lateral continuity of the elastic parameters. For the first field dataset, the inversion results clearly delineate the top of the carbonate reservoir by a sharp increase in all the P-wave impedance, S-wave impedance and the density. For the second field dataset, the Possion’s ratio is calculated from the inverted elastic parameters and is used as the gas indicator. The low Possion’s ratio area matches the gas production zones explored in the wells. The horizon slices of the three elastic parameters, the P-wave impedance, S-wave impedance and the density as well as the Possion’s ratio are studied to exploit the potential gas reservoir targets in the whole area. Based on field data application, the inverted elastic parameters are reliably used for reservoir characterisation. The main conclusions I have drawn from this PhD studies are: (1) The ray-parameter domain seismic elastic inversion can exhibit superior features for reservoir characterisation, following the ray-impedance theory. (2) The AVO inversion constrained by the geological horizons enables the inversion results to satisfy the geological background. Further applied Tikhonov regularisation operator is able to control the lateral continuity. (3) The multi-damped subspace AVO inversion has shown potential in estimating P-wave impedance, S-wave impedance and the density simultaneously using P-wave seismic data with the limited offset range. Open Access