Spatio-temporal Differentiation in the Incidence of Influenza and Its Relationship with Air Pollution in China from 2004 to 2017

The Healthy China Initiative is a major health strategy being pursued by the country.To prevent and control different types of diseases as well as their complex variants,research on the spatio-temporal differentiation among and mechanisms of influence of epidemic diseases is growing worldwide.This study analyzed monthly data on the incidence of influenza by using different methods,including Moran’s I,the hotspot analysis model,concentration analysis,and correlation analysis,to determine the characteristics of spatiotemporal differentiation in the incidence of influenza across prefecture-level cities in China from 2004 to 2017,and to examine its relationship with air pollution.According to the results,the overall incidence of influenza in China exhibited a trend of increase from 2004 to 2017,with small peaks in 2009 and 2014.More cases of influenza were recorded in the first and fourth quarters of each year.Regions with higher incidences of influenza were concentrated in northwestern and northern China,and in the coastal areas of southeastern China.Over time,the distribution of regions with a higher incidence of influenza has shifted from the west to the east of the country.A significant relationship was observed between the incidence of influenza and factors related to air pollution.The contents of five air pollutants(PM_(2.5),PM10,SO_(2),NO_(2),and CO)were significantly positively correlated with the incidence of influenza,with a decreasing order of contribution to it of SO_(2)>CO>NO_(2)>PM_(2.5)>PM_(10).The content of O_(3) in the air was negatively correlated with the incidence of influenza.The influence of air pollution-related factors on the incidence of influenza in different regions and seasons showed minor differences.The large-scale empirical results provided here can supply a scientific basis for governmental disease control authorities to formulate strategies for regional prevention and control.

Spatio-temporal Differentiation and Driving Factors of Industrial Ecology of Restricted Development Zone from Adaptive Perspective:A Case Study of Shandong,China

Based on the adaptive analysis paradigm,this paper constructs an evaluation index system and an evaluation model of the level of industrial ecology of a restricted development zone from the perspective of the industrial system and of the environmental system,and studies the spatial-temporal differentiation characteristics and the driving factors of the level of industrial ecology of the restricted development zone of the Shandong Province,China,by using a variety of measurement methods.The results show that:1)In the temporal dimension,the level of industrial ecology of the research area increased from 2005 to 2017,while in the regional dimension,it was higher in the eastern coastal areas,followed by the northwestern area and the southwestern area;2)In the spatial dimension,from 2005 to 2017 the level of industrial ecology of the research area had a clear spatial dependence,and the regional spatial agglomeration of the restricted development zones with similar industrial ecology levels become increasingly evident;3)On the whole,the industrial ecology level in the study area had a clear spatial differentiation pattern,as it was higher in the north and in the east and lower in the south and in the west.Moreover,its evolution model changed from a‘three-core driven model’to a‘spatial scattered mosaic distribution model’,and then to a‘single-core driven model’;4)Industrial ecology was positively correlated with economic development,foreign investment,science and technology,and negatively correlated with the government role,while industrial structure and environmental regulation failed to pass the statistical significance test.

Spatio-temporal differentiation of landscape ecological niche in western ecological frangible region： A case study of Yan＇an region in northwestern China

In this study, we attempt to put forward a conception of landscape ecological niche, enlightened by international scholars on extending the ecological niche theory from spatial niche to functional niche. That is helpful for comprehensively appraising landscape spatial patterns and ecological functions, also, presents a new method for analyzing landscape features from multidimensional aspects. The practice process is demonstrated by taking Yan＇an region in northwestern China as a case. Firstly, the indices system including spatial attribute and functional attribute is established for assessing landscape ecological niche. Additionally, two-dimensional figures are drawn for comparing the spatio-temporal features of landscape ecological niche in 1987 and 2000 among the 13 administrative counties. The results show that from 1987 to 2000, towards Yan＇an region, spatial attribute value of landscape ecological niche changes from 1.000 to 1.178 with an obvious increment, and functional attribute value changes from 0.989 to 1.069 with a little increment, both of which enhance the regional landscape ecological niche. Towards each county, spatial attribute value of landscape ecological niche increases to different extent while functional attribute value changes dissimilarly with an increment or a decrement.

Spatio-temporal Differentiation of Residential Land for Coastal Town: A Case Study of Dalian Jinshitan

Based on SPOT5 satellite remote sensing images and land use data in five time phases covering the period 1988–2012, the distribution characteristics, spatial differentiation processes, and driving mechanisms affecting the residential land of the Jinshitan Tourist Resort were studied. The work included a combination of GIS technology, adoption of the differentiation index D, and the multi-group differentiation-measure model D(m). The results provided a basis for the following conclusions: 1) From 1988 to 2012, the degree of differentiation of the rural residential land first decreased, and then increased. The general residential, commercial residential and garden-house land-types all showed declining trends, of which the garden-house type presented the most intense volatility. 2) The overall background of the traditional residential land type was gradually replaced by a new residential land type, and the total area of residential land increased year by year, significantly improving the overall residential conditions. The areas of the new residential land type showed growth, and were increasingly widely distributed in the coastal tourist resorts, transportation corridors, and scenic areas. 3) Government policy, social differentiation, market mechanisms, and individual choices(along with other factors) were mutually promoted, although still restrained. However, all of these factors interacted to constrain the developmental direction and the processes affecting tourism real estate in the Dalian Jinshitan Tourist Resort.

Spatio-temporal differentiation of spring phenology in China driven by temperatures and photoperiod from 1979 to 2018

Large amounts of data accumulated in ecology and related environmental sciences arouses urgent need to explore useful patterns and information in it.Here we propose coclustering-based methods and a temperatures-photoperiod driven phenological model to explore spatio-temporal differentiation in long-term spring phenology in China.First,we created the first bloom date(FBD)dataset in China from 1979 to 2018 using the extended spring indices and China Meteorological Forcing Dataset.Then we analyzed the dataset using Bregman block average co-clustering algorithm with I-divergence(BBAC_I)and kmeans algorithm.Such analysis delineated the spatially-continuous phenoregions in China for the first time.Results showed three spatial patterns of FBD in China and their temporal dynamics for 40 years(1979–2018).More specifically,overall late spring onsets occur in 1979–1996,in which areas located in Jiangxi,northern Xinjiang and middle Inner Mongolia experienced constant changing spring onsets.Overall increasingly earlier spring onsets occur in 1997–2012,in which areas located in Fujian,Hunan and eastern Heilongjiang experienced the most variable spring onsets.Stable early spring onsets over China occur after 2012.Results also showed 15 temporal patterns of spring phenology over the study period and their spatial delineation in China.More specifically,most areas in China have the same FBD category for 40 years while northern Guizhou,Hunan and southern Hubei have the same category in 1979–1997 and then fluctuate between different categories.Finally,our results have certain directive significance on the design of existing observational sites in Chinese Phenological Network.

Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

Research on Spatio-Temporal Differentiation Characteristics of the Construction Level of Green and Plaza Land in China

Green and plaza land(GPL)is one of the basic elements of urban construction,and is also the most basic public space to meet the needs of citizens for a better life.The exploration on its internal development laws can provide theoretical foundations for the planning of GPL and creating good human settlements.Taking 612 cities in China as the study area and from the"people-land"perspective,this paper selects the total GPL area,the per capita GPL area,and the land use proportion of per capita GPL as indicators to analyze the spatio-temporal differentiation characteristics and evolution rules of the construction level of GPL in China from 1996 to 2016,by using mathematical statistics and spatial analysis methods.The result shows:(1)from a national perspective,the construction level of GPL in China has been rapidly improved along with the temporal evolution,but there is still a big gap from the upper limit of the standard.In terms of the spatial distribution,regional differences have always been great,and the cities scoring below the standard are concentrated in the eastern and central regions,while high-scoring cities are more concentrated in the western region;the distribution of the land use proportion of per capita GPL is in a pattern that the eastern region has the highest proportion,followed by the western region,central region,and northeastern region successively.(2)From the perspective of scale,differences between cities of different sizes exist over a long period of time,and there is an obvious imbalance in the per capita GPL area as well as the land use proportion of per capita GPL between different cities.The construction level shows that small cities have the highest level,followed by medium-sized cities and then large cities.

Photobiomodulation:a novel approach to promote trans-differentiation of adipose-derived stem cells into neuronal-like cells

Photobiomodulation,originally used red and near-infrared lasers,can alter cellular metabolism.It has been demonstrated that the visible spectrum at 451-540 nm does not necessarily increase cell proliferation,near-infrared light promotes adipose stem cell proliferation and affects adipose stem cell migration,which is necessary for the cells homing to the site of injury.In this in vitro study,we explored the potential of adipose-derived stem cells to differentiate into neurons for future translational regenerative treatments in neurodegenerative disorders and brain injuries.We investigated the effects of various biological and chemical inducers on trans-differentiation and evaluated the impact of photobiomodulation using 825 nm near-infrared and 525 nm green laser light at 5 J/cm2.As adipose-derived stem cells can be used in autologous grafting and photobiomodulation has been shown to have biostimulatory effects.Our findings reveal that adipose-derived stem cells can indeed trans-differentiate into neuronal cells when exposed to inducers,with pre-induced cells exhibiting higher rates of proliferation and trans-differentiation compared with the control group.Interestingly,green laser light stimulation led to notable morphological changes indicative of enhanced trans-differentiation,while near-infrared photobiomodulation notably increased the expression of neuronal markers.Through biochemical analysis and enzyme-linked immunosorbent assays,we observed marked improvements in viability,proliferation,membrane permeability,and mitochondrial membrane potential,as well as increased protein levels of neuron-specific enolase and ciliary neurotrophic factor.Overall,our results demonstrate the efficacy of photobiomodulation in enhancing the trans-differentiation ability of adipose-derived stem cells,offering promising prospects for their use in regenerative medicine for neurodegenerative disorders and brain injuries.

Maintaining moderate levels of hypochlorous acid promotes neural stem cell proliferation and differentiation in the recovery phase of stroke

It has been shown clinically that continuous removal of ischemia/reperfusion-induced reactive oxygen species is not conducive to the recovery of late stroke.Indeed,previous studies have shown that excessive increases in hypochlorous acid after stroke can cause severe damage to brain tissue.Our previous studies have found that a small amount of hypochlorous acid still exists in the later stage of stroke,but its specific role and mechanism are currently unclear.To simulate stroke in vivo,a middle cerebral artery occlusion rat model was established,with an oxygen-glucose deprivation/reoxygenation model established in vitro to mimic stroke.We found that in the early stage(within 24 hours)of ischemic stroke,neutrophils produced a large amount of hypochlorous acid,while in the recovery phase(10 days after stroke),microglia were activated and produced a small amount of hypochlorous acid.Further,in acute stroke in rats,hypochlorous acid production was prevented using a hypochlorous acid scavenger,taurine,or myeloperoxidase inhibitor,4-aminobenzoic acid hydrazide.Our results showed that high levels of hypochlorous acid(200μM)induced neuronal apoptosis after oxygen/glucose deprivation/reoxygenation.However,in the recovery phase of the middle cerebral artery occlusion model,a moderate level of hypochlorous acid promoted the proliferation and differentiation of neural stem cells into neurons and astrocytes.This suggests that hypochlorous acid plays different roles at different phases of cerebral ischemia/reperfusion injury.Lower levels of hypochlorous acid(5 and 100μM)promoted nuclear translocation ofβ-catenin.By transfection of single-site mutation plasmids,we found that hypochlorous acid induced chlorination of theβ-catenin tyrosine 30 residue,which promoted nuclear translocation.Altogether,our study indicates that maintaining low levels of hypochlorous acid plays a key role in the recovery of neurological function.

Spatio-temporal Differentiation of Trade-offs and Synergies of Ecosystem Services in Typical Mountain Areas of China

Mountain area accounts for a high proportion of the land area in China,and it is the focal area to solve the contradiction of imbalanced regional development,as well as an important source of ecosystem services.Therefore,this area has been facing long-term pressure and challenges in economic development and ecological protection.In this paper,we selected a rocky desertification mountain area,an active mountain area of new tectonic movement and a typical northern earth-rock mountain area,as Qian-Gui karst Mountain area,Hengduan Mountain area and Taihang Mountain area,as examples to represent three main types of mountain areas.Three representative types of ecosystem services,including NPP(Net Primary Productivity)as a support service,water conservation as a regulation service,and agricultural produce as a supply service,were incorporated into this study.Linear regression,correlation analysis and other methods were then used to investigate the spatial-temporal characteristics of the trade-offs and synergies in each of the three kinds of mountain areas during 1990-2015 in China.The analysis yielded three main conclusions for the three mountainous areas.(1)The agricultural produce supply service decreased relatively,while the support and regulation services of NPP and hydrological regulation increased significantly.(2)There was a synergistic relationship between NPP and the hydrological regulation services in the three mountainous areas.The synergistic relation in Qian-Gui karst Mountain area became enhanced,while those in Hengduan and Taihang Mountain areas became weakened,and the former was weakened to a greater extent.There was a trade-off between NPP,the hydrological regulation service and the agricultural produce supply service among the three mountainous areas.In particular,the trade-off between NPP and the agricultural produce supply service in Qian-Gui karst Mountain area became weaker,while those in Hengduan and Taihang Mountain areas were enhanced,and the latter was enhanced to a greater degree.(3)Significant spatial differentiation was evident in the trade-offs and synergies of ecosystem services among the three mountain areas.

Analysis of the Spatio-temporal Differentiation of Cultivated Land Pressure in the Pearl River-Xijiang Economic Zone and Its Influencing Factors

Cultivated land pressure is often used to reflect the shortage of cultivated land resources. By using the methods of the Cultivated Land Pressure Index, coefficient of variation and cold-hot spot analysis, this paper analyzes the spatial-temporal differentiation pattern and dynamic change processes of cultivated land pressure in the counties of the Pearl River-Xijiang Economic Zone from 2008 to 2017, and measures the factors which influence cultivated land pressure by using Principal Component Analysis. The results show that the cultivated land pressure in the Pearl River-Xijiang Economic Zone has been in a “high pressure” state, and the Cultivated Land Pressure Index has been rising continuously from 2008 to 2017. The coefficient of variation of the Cultivated Land Pressure Index in the Pearl River-Xijiang Economic Zone and various prefecture-level cities is fluctuating and rising, which indicates that the overall spatial differences in the cultivated land pressure in this region are expanding and polarization is obvious. In addition, the area where the municipal district of the provincial capital city is located is the core area of urban development and also the area with the greatest cultivated land pressure. The spatial pattern of cultivated land pressure cold-hot spots in the Pearl River-Xijiang Economic Zone is obviously heterogeneous, in which the Pearl River Economic Zone is the main hot spot gathering area and the Xijiang Economic Zone is the main cold spot gathering area. Farmers’ income, investment in fixed assets, GDP, population and other socio-economic factors are the main factors driving the changes in the cultivated land pressure in the Pearl River-Xijiang Economic Zone. Furthermore, farming production factors, such as the multiple cropping index and grain yield per unit area,will also have an important impact on the changes in the cultivated land pressure.

Prognostic significance of grade of malignancy based on histopathological differentiation and Ki-67 in pancreatic ductal adenocarcinoma

Objective:Tumor cell malignancy is indicated by histopathological differentiation and cell proliferation.Ki-67,an indicator of cellular proliferation,has been used for tumor grading and classification in breast cancer and neuroendocrine tumors.However,its prognostic significance in pancreatic ductal adenocarcinoma(PDAC)remains uncertain.Methods:Patients who underwent radical pancreatectomy for PDAC were retrospectively enrolled,and relevant prognostic factors were examined.Grade of malignancy(GOM),a novel index based on histopathological differentiation and Ki-67,is proposed,and its clinical significance was evaluated.Results:The optimal threshold for Ki-67 was determined to be 30%.Patients with a Ki-67 expression level>30%rather than≤30%had significantly shorter 5-year overall survival(OS)and recurrence-free survival(RFS).In multivariate analysis,both histopathological differentiation and Ki-67 were identified as independent prognostic factors for OS and RFS.The GOM was used to independently stratify OS and RFS into 3 tiers,regardless of TNM stage and other established prognostic factors.The tumor-nodemetastasis-GOM stage was used to stratify survival into 5 distinct tiers,and surpassed the predictive performance of TNM stage for OS and RFS.Conclusions:Ki-67 is a valuable prognostic indicator for PDAC.Inclusion of the GOM in the TNM staging system may potentially enhance prognostic accuracy for PDAC.

Spatial-temporal differentiation and influencing factors of rural settlements in mountainous areas: an example of Liangshan Yi Autonomous Prefecture, Southwestern China

Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.

How mesenchymal stem cells transform into adipocytes:Overview of the current understanding of adipogenic differentiation

Mesenchymal stem cells(MSCs)are stem/progenitor cells capable of self-renewal and differentiation into osteoblasts,chondrocytes and adipocytes.The transformation of multipotent MSCs to adipocytes mainly involves two subsequent steps from MSCs to preadipocytes and further preadipocytes into adipocytes,in which the process MSCs are precisely controlled to commit to the adipogenic lineage and then mature into adipocytes.Previous studies have shown that the master transcription factors C/enhancer-binding protein alpha and peroxisome proliferation activator receptor gamma play vital roles in adipogenesis.However,the mechanism underlying the adipogenic differentiation of MSCs is not fully understood.Here,the current knowledge of adipogenic differentiation in MSCs is reviewed,focusing on signaling pathways,noncoding RNAs and epigenetic effects on DNA methylation and acetylation during MSC differentiation.Finally,the relationship between maladipogenic differentiation and diseases is briefly discussed.We hope that this review can broaden and deepen our understanding of how MSCs turn into adipocytes.

T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma

BACKGROUND The study on predicting the differentiation grade of colorectal cancer(CRC)based on magnetic resonance imaging(MRI)has not been reported yet.Developing a non-invasive model to predict the differentiation grade of CRC is of great value.AIM To develop and validate machine learning-based models for predicting the differ-entiation grade of CRC based on T2-weighted images(T2WI).METHODS We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023.Patients were randomly assigned to a training cohort(n=220)or a validation cohort(n=95)at a 7:3 ratio.Lesions were delineated layer by layer on high-resolution T2WI.Least absolute shrinkage and selection operator regression was applied to screen for radiomic features.Radiomics and clinical models were constructed using the multilayer perceptron(MLP)algorithm.These radiomic features and clinically relevant variables(selected based on a significance level of P<0.05 in the training set)were used to construct radiomics-clinical models.The performance of the three models(clinical,radiomic,and radiomic-clinical model)were evaluated using the area under the curve(AUC),calibration curve and decision curve analysis(DCA).RESULTS After feature selection,eight radiomic features were retained from the initial 1781 features to construct the radiomic model.Eight different classifiers,including logistic regression,support vector machine,k-nearest neighbours,random forest,extreme trees,extreme gradient boosting,light gradient boosting machine,and MLP,were used to construct the model,with MLP demonstrating the best diagnostic performance.The AUC of the radiomic-clinical model was 0.862(95%CI:0.796-0.927)in the training cohort and 0.761(95%CI:0.635-0.887)in the validation cohort.The AUC for the radiomic model was 0.796(95%CI:0.723-0.869)in the training cohort and 0.735(95%CI:0.604-0.866)in the validation cohort.The clinical model achieved an AUC of 0.751(95%CI:0.661-0.842)in the training cohort and 0.676(95%CI:0.525-0.827)in the validation cohort.All three models demonstrated good accuracy.In the training cohort,the AUC of the radiomic-clinical model was significantly greater than that of the clinical model(P=0.005)and the radiomic model(P=0.016).DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process.CONCLUSION In this study,we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC.This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

RPLP0/TBP are the most stable reference genes for human dental pulp stem cells under osteogenic differentiation

BACKGROUND Validation of the reference gene(RG)stability during experimental analyses is essential for correct quantitative real-time polymerase chain reaction(RT-qPCR)data normalisation.Commonly,in an unreliable way,several studies use genes involved in essential cellular functions[glyceraldehyde-3-phosphate dehydro-genase(GAPDH),18S rRNA,andβ-actin]without paying attention to whether they are suitable for such experimental conditions or the reason for choosing such genes.Furthermore,such studies use only one gene when Minimum Information for Publication of Quantitative Real-Time PCR Experiments guidelines recom-mend two or more genes.It impacts the credibility of these studies and causes dis-tortions in the gene expression findings.For tissue engineering,the accuracy of gene expression drives the best experimental or therapeutical approaches.We cultivated DPSCs under two conditions:Undifferentiated and osteogenic dif-ferentiation,both for 35 d.We evaluated the gene expression of 10 candidates for RGs[ribosomal protein,large,P0(RPLP0),TATA-binding protein(TBP),GAPDH,actin beta(ACTB),tubulin(TUB),aminolevulinic acid synthase 1(ALAS1),tyro-sine 3-monooxygenase/tryptophan 5-monooxygenase activation protein,zeta(YWHAZ),eukaryotic translational elongation factor 1 alpha(EF1a),succinate dehydrogenase complex,subunit A,flavoprotein(SDHA),and beta-2-micro-globulin(B2M)]every 7 d(1,7,14,21,28,and 35 d)by RT-qPCR.The data were analysed by the four main algorithms,ΔCt method,geNorm,NormFinder,and BestKeeper and ranked by the RefFinder method.We subdivided the samples into eight subgroups.RESULTS All of the data sets from clonogenic and osteogenic samples were analysed using the RefFinder algorithm.The final ranking showed RPLP0/TBP as the two most stable RGs and TUB/B2M as the two least stable RGs.Either theΔCt method or NormFinder analysis showed TBP/RPLP0 as the two most stable genes.However,geNorm analysis showed RPLP0/EF1αin the first place.These algorithms’two least stable RGs were B2M/GAPDH.For BestKeeper,ALAS1 was ranked as the most stable RG,and SDHA as the least stable RG.The pair RPLP0/TBP was detected in most subgroups as the most stable RGs,following the RefFinfer ranking.CONCLUSION For the first time,we show that RPLP0/TBP are the most stable RGs,whereas TUB/B2M are unstable RGs for long-term osteogenic differentiation of human DPSCs in traditional monolayers.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Recent advances in spatio-temporally controllable systems for management of glioma

Malignant glioma remains one of the most aggressive intracranial tumors with devastating clinical outcomes despite the great advances in conventional treatment approaches,including surgery and chemotherapy.Spatio-temporally controllable approaches to glioma are now being actively investigated due to the preponderance,including spatio-temporal adjustability,minimally invasive,repetitive properties,etc.External stimuli can be readily controlled by adjusting the site and density of stimuli to exert the cytotoxic on glioma tissue and avoid undesired injury to normal tissues.It is worth noting that the removability of external stimuli allows for on-demand treatment,which effectively reduces the occurrence of side effects.In this review,we highlight recent advancements in drug delivery systems for spatio-temporally controllable treatments of glioma,focusing on the mechanisms and design principles of sensitizers utilized in these controllable therapies.Moreover,the potential challenges regarding spatio-temporally controllable therapy for glioma are also described,aiming to provide insights into future advancements in this field and their potential clinical applications.

Epidemic Characteristics and Spatio-Temporal Patterns of HFRS in Qingdao City,China,2010-2022

Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.

Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting

Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.