Commentary on:“Human neural stem cell-derived artificial organelles to improve oxidative phosphorylation”

Mitochondrial function is fundamental to neuroregeneration,particularly in neurons,where high energy demands are essential for repair and recovery(Patrón and Zinsmaier,2016;Beckervordersandforth et al.,2017;Iwata et al.,2023).Mitochondrial dysfunction,characterized by an imbalance in ATP levels and excessive production of mitochondrial reactive oxygen species,is a key factor that impedes neural regeneration in neurodegenerative diseases and after neuronal injury(Han et al.,2016,2020;Zheng et al.,2016;Zong et al.,2024).

Human endogenous retrovirus type-W and multiple sclerosis–related smoldering neuroinflammation

Introduction to human endogenous retrovirus type-W(HERV-W): Genomic inheritance from the past includes retroviral sequences that have been stably incorporated into our genomes and account for up to 8% of human DNA.

Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive Networks and Archerfish Optimization

In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant attention.Previously developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basic features.The images captured by wearable sensors contain advanced features,allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human actions.Poor lighting and limited sensor capabilities can impact data quality,making the recognition of human actions a challenging task.The unimodal-based HAR approaches are not suitable in a real-time environment.Therefore,an updated HAR model is developed using multiple types of data and an advanced deep-learning approach.Firstly,the required signals and sensor data are accumulated from the standard databases.From these signals,the wave features are retrieved.Then the extracted wave features and sensor data are given as the input to recognize the human activity.An Adaptive Hybrid Deep Attentive Network(AHDAN)is developed by incorporating a“1D Convolutional Neural Network(1DCNN)”with a“Gated Recurrent Unit(GRU)”for the human activity recognition process.Additionally,the Enhanced Archerfish Hunting Optimizer(EAHO)is suggested to fine-tune the network parameters for enhancing the recognition process.An experimental evaluation is performed on various deep learning networks and heuristic algorithms to confirm the effectiveness of the proposed HAR model.The EAHO-based HAR model outperforms traditional deep learning networks with an accuracy of 95.36,95.25 for recall,95.48 for specificity,and 95.47 for precision,respectively.The result proved that the developed model is effective in recognizing human action by taking less time.Additionally,it reduces the computation complexity and overfitting issue through using an optimization approach.

Treatment of spinal cord injury with biomaterials and stem cell therapy in non-human primates and humans

Spinal cord injury results in the loss of sensory,motor,and autonomic functions,which almost always produces permanent physical disability.Thus,in the search for more effective treatments than those already applied for years,which are not entirely efficient,researches have been able to demonstrate the potential of biological strategies using biomaterials to tissue manufacturing through bioengineering and stem cell therapy as a neuroregenerative approach,seeking to promote neuronal recovery after spinal cord injury.Each of these strategies has been developed and meticulously evaluated in several animal models with the aim of analyzing the potential of interventions for neuronal repair and,consequently,boosting functional recovery.Although the majority of experimental research has been conducted in rodents,there is increasing recognition of the importance,and need,of evaluating the safety and efficacy of these interventions in non-human primates before moving to clinical trials involving therapies potentially promising in humans.This article is a literature review from databases(PubMed,Science Direct,Elsevier,Scielo,Redalyc,Cochrane,and NCBI)from 10 years ago to date,using keywords(spinal cord injury,cell therapy,non-human primates,humans,and bioengineering in spinal cord injury).From 110 retrieved articles,after two selection rounds based on inclusion and exclusion criteria,21 articles were analyzed.Thus,this review arises from the need to recognize the experimental therapeutic advances applied in non-human primates and even humans,aimed at deepening these strategies and identifying the advantages and influence of the results on extrapolation for clinical applicability in humans.

Effects of P301L-TAU on post-translational modifications of microtubules in human iPSC-derived cortical neurons and TAU transgenic mice

TAU is a microtubule-associated protein that promotes microtubule assembly and stability in the axon.TAU is missorted and aggregated in an array of diseases known as tauopathies.Microtubules are essential for neuronal function and regulated via a complex set of post-translational modifications,changes of which affect microtubule stability and dynamics,microtubule interaction with other proteins and cellular structures,and mediate recruitment of microtubule-severing enzymes.As impairment of microtubule dynamics causes neuronal dysfunction,we hypothesize cognitive impairment in human disease to be impacted by impairment of microtubule dynamics.We therefore aimed to study the effects of a disease-causing mutation of TAU(P301L)on the levels and localization of microtubule post-translational modifications indicative of microtubule stability and dynamics,to assess whether P301L-TAU causes stability-changing modifications to microtubules.To investigate TAU localization,phosphorylation,and effects on tubulin post-translational modifications,we expressed wild-type or P301L-TAU in human MAPT-KO induced pluripotent stem cell-derived neurons(i Neurons)and studied TAU in neurons in the hippocampus of mice transgenic for human P301L-TAU(p R5 mice).Human neurons expressing the longest TAU isoform(2N4R)with the P301L mutation showed increased TAU phosphorylation at the AT8,but not the p-Ser-262 epitope,and increased polyglutamylation and acetylation of microtubules compared with endogenous TAU-expressing neurons.P301L-TAU showed pronounced somatodendritic presence,but also successful axonal enrichment and a similar axodendritic distribution comparable to exogenously expressed 2N4R-wildtype-TAU.P301L-TAU-expressing hippocampal neurons in transgenic mice showed prominent missorting and tauopathy-typical AT8-phosphorylation of TAU and increased polyglutamylation,but reduced acetylation,of microtubules compared with non-transgenic littermates.In sum,P301L-TAU results in changes in microtubule PTMs,suggestive of impairment of microtubule stability.This is accompanied by missorting and aggregation of TAU in mice but not in i Neurons.Microtubule PTMs/impairment may be of key importance in tauopathies.

Spatial transcriptomics combined with single-nucleus RNA sequencing reveals glial cell heterogeneity in the human spinal cord

Glial cells play crucial roles in regulating physiological and pathological functions,including sensation,the response to infection and acute injury,and chronic neurodegenerative disorders.Glial cells include astrocytes,microglia,and oligodendrocytes in the central nervous system,and satellite glial cells and Schwann cells in the peripheral nervous system.Despite the greater understanding of glial cell types and functional heterogeneity achieved through single-cell and single-nucleus RNA sequencing in animal models,few studies have investigated the transcriptomic profiles of glial cells in the human spinal cord.Here,we used high-throughput single-nucleus RNA sequencing and spatial transcriptomics to map the cellular and molecular heterogeneity of astrocytes,microglia,and oligodendrocytes in the human spinal cord.To explore the conservation and divergence across species,we compared these findings with those from mice.In the human spinal cord,astrocytes,microglia,and oligodendrocytes were each divided into six distinct transcriptomic subclusters.In the mouse spinal cord,astrocytes,microglia,and oligodendrocytes were divided into five,four,and five distinct transcriptomic subclusters,respectively.The comparative results revealed substantial heterogeneity in all glial cell types between humans and mice.Additionally,we detected sex differences in gene expression in human spinal cord glial cells.Specifically,in all astrocyte subtypes,the levels of NEAT1 and CHI3L1 were higher in males than in females,whereas the levels of CST3 were lower in males than in females.In all microglial subtypes,all differentially expressed genes were located on the sex chromosomes.In addition to sex-specific gene differences,the levels of MT-ND4,MT2A,MT-ATP6,MT-CO3,MT-ND2,MT-ND3,and MT-CO_(2) in all spinal cord oligodendrocyte subtypes were higher in females than in males.Collectively,the present dataset extensively characterizes glial cell heterogeneity and offers a valuable resource for exploring the cellular basis of spinal cordrelated illnesses,including chronic pain,amyotrophic lateral sclerosis,and multiple sclerosis.

ADAS碰撞和车道偏离检测系统设计与实现

为满足交通运输领域对高级驾驶辅助系统(Advanced Driving Assistance System,ADAS)前车碰撞和车道偏离预警性能的检测和质量评价,解决手动测试中不准确、效率低的问题,设计一种能应用于实车测试的高精度动态检测系统。综合运用高精度定位技术和组合导航技术提高系统的测量精度和可靠性,使用自动化检测软件实现人机交互、测量数据分析及运动轨迹直观显示。实验结果表明,系统工作状态稳定,测量精度高,可准确评价ADAS系统碰撞和车道偏离预警性能。

Quantitation of tadalafil in human plasma using a sensitive and rapid LC-MS/MS method for a bioequivalence study

A highly sensitive liquid chromatography-tandem mass spectrometry（LC-MS/MS） method was developed for the determination of tadalafil（TAD） in human plasma. TAD and its deuterated internal standard（IS）, tadalafil-d3, were extracted from 200 mL plasma using Phenomenex Strata-X-C 33 m extraction cartridges. Chromatographic analysis was carried out on Synergi Hydro-RP C18（100 mm × 4.6 mm, 4 mm）column with a mobile phase consisting of methanol and 10 m M ammonium formate, p H 4.0（90：10, v/v）,delivered at a flow rate of 0.9 m L/min. Quantitation of the protonated analyte was done on a triple quadrupole mass spectrometer using multiple reaction monitoring via electrospray ionization. The precursor to product ions transitions monitored for TAD and TAD-d3 were m/z 390.3-268.2 and m/z393.1-271.2, respectively. The calibration curve was linear over the concentration range of 0.50–500 ng/m L with correlation coefficient, r2 Z 0.9994. Acceptable intra-batch and inter-batch precision（r3.7%） and accuracy（97.8% to 104.1%） were obtained at five concentration levels. The recovery of TAD from spiked plasma was highly precise and quantitative（98.95% to 100.61%）. Further, the effect of endogenous matrix components was minimal. TAD was found to be stable under different storage conditions in human plasma and also in whole blood samples. The validated method was successfully used to determine TAD plasma concentration in a bioequivalence study with 20 mg TAD tablets in 24 healthy volunteers. Method performance was evaluated by reanalyzing 115 study samples.

A Preliminary Study of Holocene Climate Change and Human Adaptation in the Horqin Region

Human activity during the Holocene in the Horqin region, northeastern China, has been widely documented. As an important proxy record of human activity, black carbon（BC） in sediments has been linked to climate change and human adaptation. A loess-paleosol section located in south Horqin was chosen for this study. Holocene climate change and human adaptation to the environment were discussed by analyzing BC, organic carbon（OC） and other proxies. The conclusions included：（1） before 3900 cal BP, human activity was closely related to the natural environment and cultural development was dominated by climate change. For example, the rapid decline of the agrarian Hongshan culture was caused by a slight decrease in temperature at ~5000 cal BP;（2） during 3900-3200 cal BP, the heavy dependence of human societies on nature gradually lessened and the ability of those human societies to adapt to the environment was enhanced. However, the farming-dominated Lower Xiajiadian culture was nonetheless replaced by the pastoralist Upper Xiajiadian culture due to an extremely cooling event at ~3200 cal BP;（3） during the late Holocene period, the marked influence of climate change on human activity might have lessened as a result of a clear improvement in human labor skills. After this, human living styles were influenced by cultural developments rather than climate change because humans had mastered more powerful means of productivity.

基于StyleGAN2-ADA和改进YOLO v7的葡萄叶片早期病害检测方法

为实现葡萄早期病害的快速准确识别,针对葡萄病害的相似表型症状识别率低及小病斑检测困难的问题,以葡萄黑腐病和黑麻疹病为研究对象,提出了一种基于自适应鉴别器增强的样式生成对抗网络与改进的YOLO v7相结合的葡萄黑腐病和黑麻疹病的病斑检测方法。通过自适应鉴别器增强的样式生成对抗网络和拉普拉斯滤波器的方差扩充葡萄病害数据。采用MSRCP算法进行图像增强,改善光照环境凸显病斑特征。以YOLO v7网络框架为基础,将BiFormer注意力机制嵌入特征提取网络,强化目标区域的关键特征;采用BiFPN代替PA-FPN,更好地实现低层细节特征与高层语义信息融合,以同时降低计算复杂度;在YOLO v7的检测头部分嵌入SPD模块,以提高模型对低分辨率图像的检测性能;并采用CIoU与NWD损失函数组合对损失函数重新定义,实现对小目标快速、准确识别。实验结果表明,该方法病斑检测精确率达到94.1%,相比原始算法提升5.7个百分点,与Faster R-CNN、YOLO v3-SPP和YOLO v5x等模型相比分别提高3.3、3.8、4.4个百分点,能够实现葡萄早期病害快速准确识别,对于保障葡萄产业发展具有重要意义。

肿瘤潜在侯选靶标及标志物ADAM17的生物信息学分析

目的 采用生物信息学分析肿瘤组织潜在侯选靶标及标志物ADAM17的结构和功能特点。方法 运用ProtParam和ProtScale、STRING12.0、The Human Protein Atlas和cBioPortal等不同数据库,对人ADAM17理化性质、跨膜区域、信号肽、核定位序列、磷酸化和糖基化位点、亚细胞定位、二级/三级结构、蛋白互作网络、不同肿瘤组织中的表达以及遗传改变等进行分析。采用免疫组化对肺、结肠组织的肿瘤组织和正常样本ADAM17表达进行验证。结果 人ADAM17是由824个氨基酸构成的亲水性蛋白;分子式为C_(4066)H_(6356)N_(1124)O_(1277)S_(50),理论等电点为5.50,平均亲水性为-0.573;定位于细胞质,具有1个跨膜结构域、1个信号肽以及2个核定位序列;二级结构主要由不规则卷曲组成,存在89个磷酸化位点、5个N-糖基化位点和9个O-糖基化位点;广泛分布于正常组织中,并在膀胱尿路上皮癌、宫颈鳞状细胞癌、结肠癌(COAD)、肾透明细胞癌、肝脏肝细胞癌和肺鳞状细胞癌(LUSC)中高表达,能与金属蛋白酶抑制因子3、表皮生长因子等主要蛋白发生相互作用,参与肿瘤坏死因子、核因子-κB等信号通路。免疫组化验证结果显示,ADAM17在人肺、结肠正常组织中低表达,而在LUSC、COAD组织中高表达。结论 ADAM17可能是肿瘤的潜在候选靶标及标志物。

An Approach to Human Adaptability towards its Built Environment: A Review

This paper deals with the human adaptability to its built environment. The built environment as we know it rarely finds itself adapting to its surrounding context, whether it be on the level of interaction with humans or the climate. Humans and nature both are in a constant state of flux;moving, changing, sensing, and reacting to their context and information they gather and perceive. A barrier is formed between the built environment and humans and nature due to the fact that their inherent characteristics are utterly contrasting. It is commonly estimated that persons in urban areas spend at least 80% of their time indoors. This suggests that the quality of the indoor environment can have a significant impact on comfort, health, and overall sense of well being. The indoor environment of buildings should thus be designed and controlled, as to provide a comfortable and healthy space for occupants. In order to maintain the quality of the indoor environment, we mechanically condition our buildings to achieve constant, uniform and comfortable environments. The maintenance of thermal equilibrium between the human body and its environment is one of the primary requirements. History of thermal comfort and climate design shows a definite relation between them and research is needed to know “What are comfort conditions?” and “How buildings could adapt themselves to these conditions”.

Indoor Human Detection Based on Thermal Array Sensor Data and Adaptive Background Estimation

Low Resolution Thermal Array Sensors are widely used in several applications in indoor environments. In particular, one of these cheap, small and unobtrusive sensors provides a low-resolution thermal image of the environment and, unlike cameras;it is capable to detect human heat emission even in dark rooms. The obtained thermal data can be used to monitor older seniors while they are performing daily activities at home, to detect critical situations such as falls. Most of the studies in activity recognition using Thermal Array Sensors require human detection techniques to recognize humans passing in the sensor field of view. This paper aims to improve the accuracy of the algorithms used so far by considering the temperature environment variation. This method leverages an adaptive background estimation and a noise removal technique based on Kalman Filter. In order to properly validate the system, a novel installation of a single sensor has been implemented in a smart environment: the obtained results show an improvement in human detection accuracy with respect to the state of the art, especially in case of disturbed environments.

Adaptive image enhancement algorithm based on fuzzy entropy and human visual characteristics

To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement algorithm. This algorithm introduces fuzzy entropy, makes full use of neighborhood information, fuzzy information and human visual characteristics.To enhance an image, this paper first carries out the reasonable fuzzy-3 partition of its histogram into the dark region, intermediate region and bright region. It then extracts the statistical characteristics of the three regions and adaptively selects the parameter αaccording to the statistical characteristics of the image’s gray-scale values. It also adds a useful nonlinear transform, thus increasing the ubiquity of the algorithm. Finally, the causes for the gray-scale value overcorrection that occurs in the traditional image enhancement algorithms are analyzed and their solutions are proposed.The simulation results show that our image enhancement algorithm can effectively suppress the noise of an image, enhance its contrast and visual effect, sharpen its edge and adjust its dynamic range.

Cyber-Physical-Social System Between a Humanoid Robot and a Virtual Human Through a Shared Platform for Adaptive Agent Ecology

Two artificial agents(a humanoid robot and a virtual human) are enriched with various similar intelligence,autonomy, functionalities and interaction modalities. The agents are integrated in the form of a cyber-physical-social system(CPSS) through a shared communication platform to create a social ecology. In the ecology, the agents collaborate(assist each other) to perform a real-world task(search for a hidden object)for the benefits of humans. A robot-virtual human bilateral trust model is derived and a real-time trust measurement method is developed. The role of taking initiative in the collaboration is switched between the agents following a finite state machine model triggered by bilateral trust, which results in a mixedinitiative collaboration. A scheme is developed to evaluate the performance of the agents in the ecology through the CPSS.The results show that the robot and the virtual human perform satisfactorily in the collaboration through the CPSS. The results thus prove the effectiveness of the real-world ecology between artificial agents of heterogeneous realities through a shared platform based on trust-triggered mixed-initiatives. The results can help develop adaptive social ecology comprising intelligent agents of heterogeneous realities to assist humans in various tasks through collaboration between the agents in the form of a CPSS.

Impacts of Climate Change on Human Health and Adaptation Strategies in South China

This study reviews the impacts of climate change on human health and presents corresponding adaptation strategies in South China. The daily mean surface air temperatures above or below 26.4~C increase the death risk for people in Guangzhou, especially the elderly are vulnerable to variations in temperature. Heat waves can cause insomnia, fatigue, clinical exacerbation, or death from heatstroke etc., while cold spells show increases in patients with fractures. During a cold spell period, the rates of both on-site emergency rescues and non-implementable rescues increase, and the risk of non-accidental deaths and respiratory disease deaths significantly rise as well. Both time series of hazy days and ozone concentrations have significant positive correlations with the number of patients with cardiovascular diseases. Both malaria and dengue fever reach higher altitudes and mountainous areas due to climate warming. Climate change is likely to bring stronger heat waves in the future, thereby increasing heat wave-related illnesses and deaths, particularly in the metropolitan areas of the Pearl River Delta. The projected increase of consecutive cold days in Guangdong province and parts of northern Guangxi province will affect residents＇ health in the future. The rising temperature exaggerates ozone pollution, but it is not clear whether climate change is aggravating or mitigating haze pollution. The transmission potential of malaria in South China will increase by 39%-140% and the transmission season will extend by 1 2 months with an air temperature increase of 1-2~C. By 2050, most areas in Hainan province are projected to convert from non-endemic dengue into endemic dengue areas. The aging population will cause more vulnerable people. To mitigate the adverse impacts of climate change on human health, sound and scientific adaptation strategies must be adopted in advance, such as strengthening the surveillance of epidemic diseases in potential transmission areas, conducting timely weather forecasting for human health, evaluating health vulnerability to climate change, improving environmental and health education, and strengthening hazard management and the cooperation between meteorological and health departments.

A ROBUST ADAPTIVE VIDEO ENCODER BASED ON HUMAN VISUAL MODEL

A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.

Dataset of human motion status using IR-UWB through-wall radar

Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the physiological monitoring of patients in the hospital environment and the daily monitoring at home.Although many target detection methods of UWB through-wall radar based on machine learning have been proposed,there is a lack of an opensource dataset to evaluate the performance of the algorithm.This published dataset is measured by impulse radio UWB(IR-UWB)through-wall radar system.Three test subjects are measured in different environments and several defined motion status.Using the presented dataset,we propose a human-motion-status recognition method using a convolutional neural network(CNN),and the detailed dataset partition method and the recognition process flow are given.On the well-trained network,the recognition accuracy of testing data for three kinds of motion status is higher than 99.7%.The dataset presented in this paper considers a simple environment.Therefore,we call on all organizations in the UWB radar field to cooperate to build opensource datasets to further promote the development of UWB through-wall radar.

Herbal compound 861 regulates mRNA expression of collagen synthesis- and degradation-related genes in human hepatic stellate cells

AIM： To identify the role of herbal compound 861 （Cpd 861） in the regulation of mRNA expression of collagen synthesis- and degradation-related genes in human hepatic stellate cells （HSCs）. METHODS： mRNA levels of collagen types I and III, matrix metalloproteinase 1 （MMP-1）, matrix metalloproteinase 2 （MMP-2）, membrane type-1 matrix metalloproteinase （MT1-MMP）, tissue inhibitor of metalloproteinase 1 （TIMP-1）, and transforming growth factor β1 （TGF-β1） in cultured-activated HSCs treated with Cpd 861 or interferon-γ, （IFN-γ,） were determined by real-time PCR. RESULTS： Both Cpd 861 and IFN-γ reduced the mRNA levels of collagen type Ⅲ, MMP-2 and TGF-β1. Moreover, Cpd 861 significantly enhanced the MMP-1 mRNA levels while down-regulated the TIMP-1 mRNA expression, increasing the ratio of MMP-1 to TIMP-1 to （6.3 ＋ 0.3）- fold compared to the control group. CONCLUSION： The anti-fibrosis function of Cpd 861 may be mediated by both decreased interstitial collagen sythesis by inhibiting the transcription of collagen type Ⅲ and TGF-β1 and increased degradation of these collagens by up-regulating MMP-1 and down-regulating TIMP-1 mRNA levels.

变道切入场景下ADAS系统测试与评价研究

为了满足变道切入场景下的ADAS系统测试评价需求,提出一种考虑场景风险系数的变道切入场景生成方法和客观综合评价模型。通过采集自然驾驶数据,采用阈值法自动提取变道切入功能场景并深入分析变道切入行为特征。使用单因素方差分析法与皮尔逊相关性检验法共同分析场景风险系数与场景要素的相关性来确定关键场景要素。结合Kmeans算法对离散逻辑场景参数进行聚类,从而得到5个典型测试场景。基于场景风险系数,采用AHP与CRITIC法构建多层次综合评价模型,采用灰色关联理论对ADAS系统进行客观评价。借助VTD仿真软件构建变道切入虚拟测试场景库,进行仿真试验验证。结果表明,相关性分析使场景要素维度降低了60%,生成的测试场景可以有效验证ADAS系统的综合性能,综合评价模型可对ADAS系统表现进行客观有效的评价,为智能驾驶系统开发提供有效参考。