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.

An overview of autophagy in the differentiation of dental stem cells

Dental stem cells(DSCs)have attracted significant interest as autologous stem cells since they are easily accessible and give a minimal immune response.These properties and their ability to both maintain self-renewal and undergo multi-lineage differentiation establish them as key players in regenerative medicine.While many regulatory factors determine the differentiation trajectory of DSCs,prior research has predominantly been based on genetic,epigenetic,and molecular aspects.Recent evidence suggests that DSC differentiation can also be influenced by autophagy,a highly conserved cellular process responsible for maintaining cellular and tissue homeostasis under various stress conditions.This comprehensive review endeavors to elucidate the intricate regulatory mechanism and relationship between autophagy and DSC differentiation.To achieve this goal,we dissect the intricacies of autophagy and its mechanisms.Subsequently,we elucidate its pivotal roles in impacting DSC differentiation,including osteo/odontogenic,neurogenic,and angiogenic trajectories.Furthermore,we reveal the regulatory factors that govern autophagy in DSC lineage commitment,including scaffold materials,pharmaceutical cues,and the extrinsic milieu.The implications of this review are far-reaching,underpinning the potential to wield autophagy as a regulatory tool to expedite DSC-directed differentiation and thereby promote the application of DSCs within the realm of regenerative medicine.

O-linkedβ-N-acetylglucosaminylation may be a key regulatory factor in promoting osteogenic differentiation of bone marrow mesenchymal stromal cells

Cumulative evidence suggests that O-linkedβ-N-acetylglucosaminylation(OGlcNAcylation)plays an important regulatory role in pathophysiological processes.Although the regulatory mechanisms of O-GlcNAcylation in tumors have been gradually elucidated,the potential mechanisms of O-GlcNAcylation in bone metabolism,particularly,in the osteogenic differentiation of bone marrow mesenchymal stromal cells(BMSCs)remains unexplored.In this study,the literature related to O-GlcNAcylation and BMSC osteogenic differentiation was reviewed,assuming that it could trigger more scholars to focus on research related to OGlcNAcylation and bone metabolism and provide insights into the development of novel therapeutic targets for bone metabolism disorders such as osteoporosis.

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.

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.

Identifying Brand Consistency by Product Differentiation Using CNN

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions.Results show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various brands.The investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late Stage.Results show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real world.The relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style roadmaps.In addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred boundary.The study provides insights into practical problems for designers,manufacturers,and marketers in product design.It not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand consistency.Designers can use these techniques to find features that influence brand style.Then,capture these features as innovative design elements and maintain core brand values.

HHO optimized support vector machine classifier for traditional Chinese medicine syndrome differentiation of diabetic retinopathy

AIM:To develop a classifier for traditional Chinese medicine(TCM)syndrome differentiation of diabetic retinopathy(DR),using optimized machine learning algorithms,which can provide the basis for TCM objective and intelligent syndrome differentiation.METHODS:Collated data on real-world DR cases were collected.A variety of machine learning methods were used to construct TCM syndrome classification model,and the best performance was selected as the basic model.Genetic Algorithm(GA)was used for feature selection to obtain the optimal feature combination.Harris Hawk Optimization(HHO)was used for parameter optimization,and a classification model based on feature selection and parameter optimization was constructed.The performance of the model was compared with other optimization algorithms.The models were evaluated with accuracy,precision,recall,and F1 score as indicators.RESULTS:Data on 970 cases that met screening requirements were collected.Support Vector Machine(SVM)was the best basic classification model.The accuracy rate of the model was 82.05%,the precision rate was 82.34%,the recall rate was 81.81%,and the F1 value was 81.76%.After GA screening,the optimal feature combination contained 37 feature values,which was consistent with TCM clinical practice.The model based on optimal combination and SVM(GA_SVM)had an accuracy improvement of 1.92%compared to the basic classifier.SVM model based on HHO and GA optimization(HHO_GA_SVM)had the best performance and convergence speed compared with other optimization algorithms.Compared with the basic classification model,the accuracy was improved by 3.51%.CONCLUSION:HHO and GA optimization can improve the model performance of SVM in TCM syndrome differentiation of DR.It provides a new method and research idea for TCM intelligent assisted syndrome differentiation.

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.

Exercise promotes osteogenic differentiation by activating the long non-coding RNA H19/microRNA-149 axis

BACKGROUND Regular physical activity during childhood and adolescence is beneficial to bone development,as evidenced by the ability to increase bone density and peak bone mass by promoting bone formation.AIM To investigate the effects of exercise on bone formation in growing mice and to investigate the underlying mechanisms.METHODS 20 growing mice were randomly divided into two groups:Con group(control group,n=10)and Ex group(treadmill exercise group,n=10).Hematoxylin-eosin staining,immunohistochemistry,and micro-CT scanning were used to assess the bone formation-related indexes of the mouse femur.Bioinformatics analysis was used to find potential miRNAs targets of long non-coding RNA H19(lncRNA H19).RT-qPCR and Western Blot were used to confirm potential miRNA target genes of lncRNA H19 and the role of lncRNA H19 in promoting osteogenic differentiation.RESULTS Compared with the Con group,the expression of bone morphogenetic protein 2 was also significantly increased.The micro-CT results showed that 8 wk moderate-intensity treadmill exercise significantly increased bone mineral density,bone volume fraction,and the number of trabeculae,and decreased trabecular segregation in the femur of mice.Inhibition of lncRNA H19 significantly upregulated the expression of miR-149 and suppressed the expression of markers of osteogenic differentiation.In addition,knockdown of lncRNA H19 significantly downregulated the expression of autophagy markers,which is consistent with the results of autophagy-related protein changes detected in mouse femurs by immunofluorescence.CONCLUSION Appropriate treadmill exercise can effectively stimulate bone formation and promote the increase of bone density and bone volume in growing mice,thus enhancing the peak bone mass of mice.The lncRNA H19/miR-149 axis plays an important regulatory role in osteogenic differentiation.

Patient-derived induced pluripotent stem cells with a MERTK mutation exhibit cell junction abnormalities and aberrant cellular differentiation potential

BACKGROUND Human induced pluripotent stem cell(hiPSC)technology is a valuable tool for generating patient-specific stem cells,facilitating disease modeling,and invest-igating disease mechanisms.However,iPSCs carrying specific mutations may limit their clinical applications due to certain inherent characteristics.AIM To investigate the impact of MERTK mutations on hiPSCs and determine whether hiPSC-derived extracellular vesicles(EVs)influence anomalous cell junction and differentiation potential.METHODS We employed a non-integrating reprogramming technique to generate peripheral blood-derived hiPSCs with and hiPSCs without a MERTK mutation.Chromo-somal karyotype analysis,flow cytometry,and immunofluorescent staining were utilized for hiPSC identification.Transcriptomics and proteomics were employed to elucidate the expression patterns associated with cell junction abnormalities and cellular differentiation potential.Additionally,EVs were isolated from the supernatant,and their RNA and protein cargos were examined to investigate the involvement of hiPSC-derived EVs in stem cell junction and differentiation.RESULTS The generated hiPSCs,both with and without a MERTK mutation,exhibited normal karyotype and expressed pluripotency markers;however,hiPSCs with a MERTK mutation demonstrated anomalous adhesion capability and differentiation potential,as confirmed by transcriptomic and proteomic profiling.Furthermore,hiPSC-derived EVs were involved in various biological processes,including cell junction and differentiation.CONCLUSION HiPSCs with a MERTK mutation displayed altered junction characteristics and aberrant differentiation potential.Furthermore,hiPSC-derived EVs played a regulatory role in various biological processes,including cell junction and differentiation.

Cardiac differentiation is modulated by anti-apoptotic signals in murine embryonic stem cells

BACKGROUND Embryonic stem cells(ESCs)serve as a crucial ex vivo model,representing epiblast cells derived from the inner cell mass of blastocyst-stage embryos.ESCs exhibit a unique combination of self-renewal potency,unlimited proliferation,and pluripotency.The latter is evident by the ability of the isolated cells to differ-entiate spontaneously into multiple cell lineages,representing the three primary embryonic germ layers.Multiple regulatory networks guide ESCs,directing their self-renewal and lineage-specific differentiation.Apoptosis,or programmed cell death,emerges as a key event involved in sculpting and forming various organs and structures ensuring proper embryonic development.How-ever,the molecular mechanisms underlying the dynamic interplay between diffe-rentiation and apoptosis remain poorly understood.AIM To investigate the regulatory impact of apoptosis on the early differentiation of ESCs into cardiac cells,using mouse ESC(mESC)models-mESC-B-cell lym-phoma 2(BCL-2),mESC-PIM-2,and mESC-metallothionein-1(MET-1)-which overexpress the anti-apoptotic genes Bcl-2,Pim-2,and Met-1,respectively.METHODS mESC-T2(wild-type),mESC-BCL-2,mESC-PIM-2,and mESC-MET-1 have been used to assess the effect of potentiated apoptotic signals on cardiac differentiation.The hanging drop method was adopted to generate embryoid bodies(EBs)and induce terminal differentiation of mESCs.The size of the generated EBs was measured in each condition compared to the wild type.At the functional level,the percentage of cardiac differentiation was measured by calculating the number of beating cardiomyocytes in the manipulated mESCs compared to the control.At the molecular level,quantitative reverse transcription-polymerase chain reaction was used to assess the mRNA expression of three cardiac markers:Troponin T,GATA4,and NKX2.5.Additionally,troponin T protein expression was evaluated through immunofluorescence and western blot assays.RESULTS Our findings showed that the upregulation of Bcl-2,Pim-2,and Met-1 genes led to a reduction in the size of the EBs derived from the manipulated mESCs,in comparison with their wild-type counterpart.Additionally,a decrease in the count of beating cardiomyocytes among differentiated cells was observed.Furthermore,the mRNA expression of three cardiac markers-troponin T,GATA4,and NKX2.5-was diminished in mESCs overexpressing the three anti-apoptotic genes compared to the control cell line.Moreover,the overexpression of the anti-apoptotic genes resulted in a reduction in troponin T protein expression.CONCLUSION Our findings revealed that the upregulation of Bcl-2,Pim-2,and Met-1 genes altered cardiac differentiation,providing insight into the intricate interplay between apoptosis and ESC fate determination.

Characteristics of early gastric tumors with different differentiation and predictors of long-term outcomes after endoscopic submucosal dissection

BACKGROUND Gastric cancer is a common malignant tumor of the digestive tract,and endosco-pic submucosal dissection(ESD)is the preferred treatment for early-stage gastric cancer.The analysis of the epidemiological characteristics of gastric mucosal tumors with different differentiation degrees and the influencing factors of long-term ESD efficacy may have certain significance for revealing the development of gastric cancer and ESD.AIM To analyze the features of gastric mucosal tumors at different differentiation levels,and to explore the prognostic factors of ESD.METHODS We retrospectively studied 301 lesions in 285 patients at The Second Affiliated Hospital of Xi'an Jiaotong University from 2014 to 2021,according to the latest Japanese guidelines(sixth edition),and divided them into low-grade intrae-pithelial neoplasia(LGIN),high-grade intraepithelial neoplasia(HGIN),and computed tomography at 3,6 and 12 months after ESD.We compared clinicopathologic characteristics,ESD efficacy,and complications with different degrees of differentiation,and analyzed the related factors associated with ESD.RESULTS HGIN and differentiated carcinoma patients were significantly older compared with LGIN patients(P<0.001)and accounted for more 0-IIc(P<0.001),atrophic gastritis was common(P<0.001),and irregular microvascular patterns(IMVPs)and demarcation lines(DLs)were more obvious(P<0.001).There was more infiltration in the undifferentiated carcinoma tissue(P<0.001),more abnormal folds and poorer mucosal peristalsis(P<0.001),and more obvious IMVPs,irregular microsurface patterns and DLs(P<0.05)than in the LGIN and HGIN tissues.The disease-free survival rates at 2,5,and 8 years after ESD were 95.0%,90.1%,and 86.9%,respectively.Undifferen-tiated lesions(HR 5.066),white moss(HR 7.187),incomplete resection(HR 3.658),and multiple primary cancers(HR 2.462)were significantly associated with poor prognosis.CONCLUSION Differentiations of gastric mucosal tumors have different epidemiological and endoscopic characteristics,which are closely related to the safety and efficacy of ESD.

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.

Clinical study on microscopic syndrome differentiation and traditional Chinese medicine treatment for liver stomach disharmony in chronic gastritis

BACKGROUND Chronic gastritis(CG)is a common gastrointestinal disorder characterized by inflammation of the stomach lining.Liver-stomach disharmony(LSD)syndrome is believed to contribute to CG symptoms.AIM To evaluate the efficacy and safety of microcosmic syndrome differentiation and Chinese herbal medicine(CHM)treatment in patients with CG and LSD syndrome.METHODS Sixty-four patients with CG and LSD syndrome were randomly divided into two groups:The treatment group received CHM based on microcosmic syndrome differentiation and the control group received conventional Western medicine.The treatment course lasted 12 wk.The primary outcome was improvement in dyspeptic symptoms,measured using the Nepean Dyspepsia Index.The secondary outcomes included the improvement rate of endoscopic findings,histopathological findings,and microcosmic syndrome scores and the incidence of adverse events.RESULTS After 12 wk of treatment,the treatment group showed significantly greater improvement in dyspeptic symptoms than the control group(93.75%vs 65.63%,P<0.01).The treatment group also showed a significantly higher improvement rate in endoscopic findings than the control group(81.25%vs 53.13%,P<0.05).The improvement rates of histopathological findings and microcosmic syndrome scores were not significantly different between the two groups(P>0.05).No serious adverse events were observed in either group.CONCLUSION Microcosmic syndrome differentiation and CHM treatment can effectively improve dyspeptic symptoms and endoscopic findings in patients with CG and LSD syndrome and have a good safety profile.Further studies with larger sample sizes and longer follow-up periods are required to confirm the long-term efficacy and mechanism of action of this treatment.

Serum biomarkers for the differentiation of autoimmune pancreatitis from pancreatic ductal adenocarcinoma

Autoimmune pancreatitis(AIP),a chronic inflammation caused by the immune system attacking the pancreas,usually presents imaging and clinical features that overlap with those of pancreatic ductal adenocarcinoma(PDAC).Serum biomarkers,substances that quantitatively change in sera during disease development,are a promising non-invasive tool with high utility for differentiating between these diseases.In this way,the presence of AIP is currently suspected when serum concentrations of immunoglobulin G4(IgG4)antibody are elevated.However,this approach has some drawbacks.Notably,IgG4 antibody concentrations are also elevated in sera from some patients with PDAC.This review focuses on the most recent and relevant serum biomarkers proposed to differentiate between AIP and PDAC,evaluating the usefulness of immunoglobulins,autoantibodies,chemokines,and cytokines.The proposed serum biomarkers have proven useful,although most studies had a small sample size,did not examine their presence in patients with PDAC,or did not test them in humans.In addition,current evidence suggests that a single serum biomarker is unlikely to accurately differentiate these diseases and that a set of biomarkers will be needed to achieve adequate specificity and sensitivity,either alone or in combination with clinical data and/or radiological images.

Acetylated-PPARγexpression is regulated by different P53 genotypes associated with the adipogenic differentiation of polyploid giant cancer cells with daughter cells

Objective:Polyploid giant cancer cells(PGCCs)with daughter cells express epithelial–mesenchymal transition(EMT)-associated proteins.Highly malignant tumor cells with EMT properties can transdifferentiate into mature tumor cells.In this study,we elucidated the potential for,and underlying mechanism of,adipogenic differentiation of PGCCs with daughter cells(PDCs).Methods:Cobalt chloride was used to induce PGCC formation in HEY(wild-type P53)and MDA-MB-231(mutant P53)cells;these cells were then cultured in adipogenic differentiation medium.Oil red O staining was used to confirm adipogenic differentiation,and the cell cycle was detected with flow cytometry.The expression of adipogenic differentiation-associated proteins and P300 histone acetyltransferase activity were compared before and after adipogenic differentiation.Animal xenograft models were used to confirm the adipogenic differentiation of PDCs.Results:PDCs transdifferentiated into functional adipocytes.Two different cell cycle distributions were observed in PDCs after adipogenic differentiation.The expression levels of PPARγ,Ace-PPARγ,and Ace-P53 were higher in PDCs after adipogenic differentiation than in cells before adipogenic differentiation.Ace-PPARγand FABP4 expression increased in HEY cells and decreased in MDA-MB-231 PDCs after p53 knockdown.A485 treatment increased Ace-P53,Ace-PPARγ,and FABP4 expression in HEY PDCs by inhibiting SUMOylation of P53.In MDA-MB-231 PDCs,A485 treatment decreased Ace-P53,Ace-PPARγ,and FABP4 expression.Animal experiments also confirmed the adipogenic differentiation of PDCs.Conclusions:Acetylation of P53 and PPARγplays an important role in the adipogenic differentiation of PDCs.

MicroRNA-146a Promotes Embryonic Stem Cell Differentiation towards Vascular Smooth Muscle Cells through Regulation of Kruppel-like Factor 4

Objective Vascular smooth muscle cell(VSMC)differentiation from stem cells is one source of the increasing number of VSMCs that are involved in vascular remodeling-related diseases such as hypertension,atherosclerosis,and restenosis.MicroRNA-146a(miR-146a)has been proven to be involved in cell proliferation,migration,and tumor metabolism.However,little is known about the functional role of miR-146a in VSMC differentiation from embryonic stem cells(ESCs).This study aimed to determine the role of miR-146a in VSMC differentiation from ESCs.Methods Mouse ESCs were differentiated into VSMCs,and the cell extracts were analyzed by Western blotting and RT-qPCR.In addition,luciferase reporter assays using ESCs transfected with miR-146a/mimic and plasmids were performed.Finally,C57BL/6J female mice were injected with mimic or miR-146a-overexpressing ESCs,and immunohistochemistry,Western blotting,and RT-qPCR assays were carried out on tissue samples from these mice.Results miR-146a was significantly upregulated during VSMC differentiation,accompanied with the VSMC-specific marker genes smooth muscle-alpha-actin(SMαA),smooth muscle 22(SM22),smooth muscle myosin heavy chain(SMMHC),and h1-calponin.Furthermore,overexpression of miR-146a enhanced the differentiation process in vitro and in vivo.Concurrently,the expression of Kruppel-like factor 4(KLF4),predicted as one of the top targets of miR-146a,was sharply decreased in miR-146a-overexpressing ESCs.Importantly,inhibiting KLF4 expression enhanced the VSMC-specific gene expression induced by miR-146a overexpression in differentiating ESCs.In addition,miR-146a upregulated the mRNA expression levels and transcriptional activity of VSMC differentiation-related transcription factors,including serum response factor(SRF)and myocyte enhancer factor 2c(MEF-2c).Conclusion Our data support that miR-146a promotes ESC-VSMC differentiation through regulating KLF4 and modulating the transcription factor activity of VSMCs.

Poly-L-ornithine blocks the inhibitory effects of fibronectin on oligodendrocyte differentiation and promotes myelin repair

The extracellular matrix surrounding oligodendrocytes plays an important role during myelination and remyelination in the brain.In many cases,the microenvironment surrounding demyelination lesions contains inhibitory molecules,which lead to repair failure.Accordingly,blocking the activity of these inhibitory factors in the extracellular matrix should lead to more successful remyelination.In the central nervous system,oligodendrocytes form the myelin sheath.We performed primary cell culture and found that a natural increase in fibronectin promoted the proliferation of oligodendrocyte progenitors during the initial stage of remyelination while inhibiting oligodendrocyte differentiation.Poly-L-ornithine blocked these inhibitory effects without compromising fibronectin’s pro-proliferation function.Experiments showed that poly-L-ornithine activated the Erk1/2 signaling pathway that is necessary in the early stages of differentiation,as well as PI3K signaling pathways that are needed in the mid-late stages.When poly-L-ornithine was tested in a lysolecithin-induced animal model of focal demyelination,it enhanced myelin regeneration and promoted motor function recovery.These findings suggest that poly-L-ornithine has the potential to be a treatment option for clinical myelin sheath injury.

A Vector Tensor Calculus Description of a Euclidean Space

We present a tensor description of Euclidean spaces that emphasizes the use of geometric vectors which leads to greater geometric insight and a higher degree of organization in analytical expressions. We demonstrate the effectiveness of the approach by proving a number of integral identities with vector integrands. The presented approach may be aptly described as absolute vector calculus or as vector tensor calculus.

Pixel’s Quantum Image Enhancement Using Quantum Calculus

The current study provides a quantum calculus-based medical image enhancement technique that dynamically chooses the spatial distribution of image pixel intensity values.The technique focuses on boosting the edges and texture of an image while leaving the smooth areas alone.The brain Magnetic Resonance Imaging(MRI)scans are used to visualize the tumors that have spread throughout the brain in order to gain a better understanding of the stage of brain cancer.Accurately detecting brain cancer is a complex challenge that the medical system faces when diagnosing the disease.To solve this issue,this research offers a quantum calculus-based MRI image enhancement as a pre-processing step for brain cancer diagnosis.The proposed image enhancement approach improves images with low gray level changes by estimating the pixel’s quantum probability.The suggested image enhancement technique is demonstrated to be robust and resistant to major quality changes on a variety ofMRIscan datasets of variable quality.ForMRI scans,the BRISQUE“blind/referenceless image spatial quality evaluator”and the NIQE“natural image quality evaluator”measures were 39.38 and 3.58,respectively.The proposed image enhancement model,according to the data,produces the best image quality ratings,and it may be able to aid medical experts in the diagnosis process.The experimental results were achieved using a publicly available collection of MRI scans.