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ObjectiveThe early recurrence of hepatocellular carcinoma (HCC) correlates with decreased overall survival. Microvascular invasion (MVI) stands out as a prominent hazard influencing post-resection survival status and metastasis in patients with HBV-related HCC. The study focused on developing a web-based nomogram for preoperative prediction of MVI in HBV-HCC.Materials and methods173 HBV-HCC patients from 2017 to 2022 with complete preoperative clinical data and Gadopentetate dimeglumine-enhanced magnetic resonance images were randomly divided into two groups for the purpose of model training and validation, using a ratio of 7:3. MRI signatures were extracted by pyradiomics and the deep neural network, 3D ResNet. Clinical factors, blood-cell-inflammation markers, and MRI signatures selected by LASSO were incorporated into the predictive nomogram. The evaluation of the predictive accuracy involved assessing the area under the receiver operating characteristic (ROC) curve (AUC), the concordance index (C-index), along with analyses of calibration and decision curves.ResultsInflammation marker, neutrophil-to-lymphocyte ratio (NLR), was positively correlated with independent MRI radiomics risk factors for MVI. The performance of prediction model combined serum AFP, AST, NLR, 15 radiomics features and 7 deep features was better than clinical and radiomics models. The combined model achieved C-index values of 0.926 and 0.917, with AUCs of 0.911 and 0.907, respectively.ConclusionNLR showed a positive correlation with MRI radiomics and deep learning features. The nomogram, incorporating NLR and MRI features, accurately predicted individualized MVI risk preoperatively.

ObjectivesThis research aimed to assess the value of radiomics combined with multiple machine learning algorithms in the diagnosis of pancreatic ductal adenocarcinoma (PDAC) lymph node (LN) metastasis, which is expected to provide clinical treatment strategies.MethodsA total of 128 patients with pathologically confirmed PDAC and who underwent surgical resection were randomized into training (n=93) and validation (n=35) groups. This study incorporated a total of 13 distinct machine learning algorithms and explored 85 unique combinations of these algorithms. The area under the curve (AUC) of each model was computed. The model with the highest mean AUC was selected as the best model which was selected to determine the radiomics score (Radscore). The clinical factors were examined by the univariate and multivariate analysis, which allowed for the identification of factors suitable for clinical modeling. The multivariate logistic regression was used to create a combined model using Radscore and clinical variables. The diagnostic performance was assessed by receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA).ResultsAmong the 233 models constructed using arterial phase (AP), venous phase (VP), and AP+VP radiomics features, the model built by applying AP+VP radiomics features and a combination of Lasso+Logistic algorithm had the highest mean AUC. A clinical model was eventually constructed using CA199 and tumor size. The combined model consisted of AP+VP-Radscore and two clinical factors that showed the best diagnostic efficiency in the training (AUC = 0.920) and validation (AUC = 0.866) cohorts. Regarding preoperative diagnosis of LN metastasis, the calibration curve and DCA demonstrated that the combined model had a good consistency and greatest net benefit.ConclusionsCombining radiomics and machine learning algorithms demonstrated the potential for identifying the LN metastasis of PDAC. As a non-invasive and efficient preoperative prediction tool, it can be beneficial for decision-making in clinical practice.

BackgroundOvarian mucinous tumor with a mural nodule is a rare and special type of ovarian surface epithelial–stromal tumor. Mural nodules are morphologically classified into three types: sarcoma-like, anaplastic carcinomatous, and true sarcomatous nodules. Ovarian mucinous tumors with true sarcomatous mural nodules are rare and challenging to diagnose, with only 10 cases reported worldwide. Currently, liposarcoma mural nodules remain unreported.Case presentationA 91-year-old woman was hospitalized for postmenopausal vaginal bleeding for 3 weeks. Imaging revealed a large cystic mass (20.0 cm × 17.7 cm × 12.8 cm) on the right ovary. The mass was multilocular cystic, with a mural nodule (1.4 cm × 1.2 cm × 1.0 cm) in the focal cyst wall. Based on histological morphology, immunohistochemical staining, and MDM2/CDK4 fluorescence in situ hybridization testing, the diagnosis was ovarian mucinous cystadenoma with a mural nodule of well-differentiated liposarcoma. To the best of our knowledge, this has never been reported before. High-throughput sequencing identified KRAS mutations in the ovarian mucinous cystadenoma. However, the liposarcoma mural nodule did not exhibit KRAS mutations but displayed copy number amplifications of CDK4 and DDR2, as well as a frameshift mutation in exon 13 of ASXL1 (p. A627Gfs*8).ConclusionsThis case broadens the morphological spectrum of mural nodules in ovarian mucinous tumors, deepening our knowledge of this rare morphology. Meanwhile, through high-throughput sequencing, we found no overlapping genetic evidence between the liposarcoma mural nodule and associated ovarian mucinous cystadenoma.

ObjectiveTo construct and validate radiomics models for hepatocellular carcinoma (HCC) grade predictions based on contrast-enhanced CT (CECT).MethodsPatients with pathologically confirmed HCC after surgery and underwent CECT at our institution between January 2016 and December 2020 were enrolled and randomly divided into training and validation datasets. With tumor segmentation and feature extraction, radiomic models were constructed using univariate analysis, followed by least absolute shrinkage and selection operator (LASSO) regression. In addition, combined models with clinical factors and radiomics scores (Radscore) were constructed using logistic regression. Finally, all models were evaluated using the receiver operating characteristic (ROC) curve with the area under the curve (AUC), calibration curve, and decision curve analysis (DCA).ResultsIn total 242 patients were enrolled in this study, of whom 170 and 72 formed the training and validation datasets, respectively. The arterial phase and portal venous phase (AP+VP) radiomics model were evaluated as the best for predicting HCC pathological grade among all the models built in our study (AUC = 0.981 in the training dataset; AUC = 0.842 in the validation dataset) and was used to build a nomogram. Furthermore, the calibration curve and DCA indicated that the AP+VP radiomics model had a satisfactory prediction efficiency.ConclusionsLow- and high-grade HCC can be distinguished with good diagnostic performance using a CECT-based radiomics model.

Abstract Background Acute lung injury (ALI) is a critical inflammatory response syndrome that rapidly develops into acute respiratory distress syndrome (ARDS). Currently, no effective therapeutic modalities are available for patients with ALI/ARDS. According to recent studies, inhibiting both the release of pro-inflammatory cytokines and the formation of reactive oxygen species (ROS) as early as possible may be a promising therapy for ALI. Results In this study, a ROS-responsive nano-delivery system based on oxidation-sensitive chitosan (Ox-CS) was fabricated for the simultaneous delivery of Ce NPs and RT. The in vitro experiments have shown that the Ox-CS/Ceria-Resatorvid nanoparticles (Ox-CS/CeRT NPs) were rapidly and efficiently internalised by inflammatory endothelial cells. Biological evaluations validated the significant attenuation of ROS-induced oxidative stress and cell apoptosis by Ox-CS/CeRT NPs, while maintaining mitochondrial function. Additionally, Ox-CS/CeRT NPs effectively inhibited the release of pro-inflammatory factors. After intraperitoneal (i.p.) administration, Ox-CS/CeRT NPs passively targeted the lungs of LPS-induced inflamed mice and released the drug activated by the high ROS levels in inflammatory tissues. Finally, Ox-CS/CeRT NPs significantly alleviated LPS-induced lung injury through inhibiting both oxidative stress and pro-inflammatory cytokine expression. Conclusions The created Ox-CS/CeRT NPs could act as a prospective nano-delivery system for a combination of anti-inflammatory and anti-oxidant therapy of ALI. Graphical Abstract

Purposes Diseases such as hypertension and malaria infection often raise the rigidity of red blood cells (RBCs). Consequently, the morphology and rheological characteristics of RBCs change, which means understanding the deformability and flow characteristics of sick RBCs is of great significance for clinical diagnosis and drug treatment. Methods In this work, RBCs were treated with a series of fixatives to mimic sick RBCs. Devices such as microfluidic chip, injection pump, fluorescence inverted microscope, and high-speed camera were used to study the flow characteristics of treated RBCs flowing in microchannel in vitro. The relationships between the deformability of RBCs and Cell free Layer (CFL) thickness, flow velocity, and other parameters were explored. Findings The results show that, after treating with fixative solution, the diameter of RBCs increases, the width of CFL becomes thinner, and the velocity of RBCs becomes lower. After the disease, the rigidity of RBCs is enhanced, the deformability is reduced, and the flow characteristics of red blood cells are obviously changed.

The NLRP3 inflammasome’s core and most specific protein, NLRP3, has a variety of functions in inflammation-driven diseases. Costunolide (COS) is the major active ingredient of the traditional Chinese medicinal herb Saussurea lappa and has anti-inflammatory activity, but the principal mechanism and molecular target of COS remain unclear. Here, we show that COS covalently binds to cysteine 598 in NACHT domain of NLRP3, altering the ATPase activity and assembly of NLRP3 inflammasome. We declare COS’s great anti-inflammasome efficacy in macrophages and disease models of gouty arthritis and ulcerative colitis via inhibiting NLRP3 inflammasome activation. We also reveal that the α-methylene-γ-butyrolactone motif in sesquiterpene lactone is the certain active group in inhibiting NLRP3 activation. Taken together, NLRP3 is identified as a direct target of COS for its anti-inflammasome activity. COS, especially the α-methylene-γ-butyrolactone motif in COS structure, might be used to design and produce novel NLRP3 inhibitors as a lead compound.

Liver fibrosis, a compensatory repair response to chronic liver injury, is caused by various pathogenic factors, and hepatic stellate cell (HSC) activation and phenotypic transformation are regarded as key events in its progression. Ferroptosis, a novel form of programmed cell death, is also closely related to different pathological processes, including those associated with liver diseases. Here, we investigated the effect of doxofylline (DOX), a xanthine derivative with potent anti-inflammatory activity, on liver fibrosis as well as the associated mechanism. Our results indicated that in mice with CCl4-induced liver fibrosis, DOX attenuated hepatocellular injury and the levels of liver fibrosis indicators, inhibited the TGF-β/Smad signaling pathway, and significantly downregulated the expression of HSC activation markers, both in vitro and in vivo. Furthermore, inducing ferroptosis in activated HSCs was found to be critical for its anti-liver fibrosis effect. More importantly, ferroptosis inhibition using the specific inhibitor, deferoxamine (DFO) not only abolished DOX-induced ferroptosis, but also led to resistance to the anti-liver fibrosis effect of DOX in HSCs. In summary, our results showed an association between the protective effect of DOX against liver fibrosis and HSC ferroptosis. Thus, DOX may be a promising anti-hepatic fibrosis agent.

Liver fibrosis is characterised by the activation of hepatic stellate cells (HSCs) and matrix deposition. Accumulating evidence has revealed that the oncogenic protein tyrosine phosphatase Src homology 2 domain-containing phosphatase 2 (SHP2) acts as a therapeutic target of fibrosis. Although several SHP2 inhibitors have reached early clinical trials, there are currently no FDA-approved drugs that target SHP2. In this study, we aimed to identify novel SHP2 inhibitors from an in-house natural product library to treat liver fibrosis. Out of the screened 800 compounds, a furanogermacrane sesquiterpene, linderalactone (LIN), significantly inhibited SHP2 dephosphorylation activity in vitro. Cross-validated enzymatic assays, bio-layer interferometry (BLI) assays, and site-directed mutagenesis were used to confirm that LIN directly binds to the catalytic PTP domain of SHP2. In vivo administration of LIN significantly ameliorated carbon tetrachloride (CCl4)-induced HSC activation and liver fibrosis by inhibiting the TGFβ/Smad3 pathway. Thus, LIN or its derivatives could be considered potential therapeutic agents against SHP2-related diseases, such as liver fibrosis or NASH.

Abstract Fibroblast growth factors (FGFs) and their receptors (FGFRs) play critical roles in many biological processes and developmental functions. Chromosomal translocation of FGFRs result in the formation of chimeric FGFR fusion proteins, which often cause aberrant signaling leading to the development and progression of human cancer. Due to the high recurrence rate and carcinogenicity, oncogenic FGFR gene fusions have been identified as promising therapeutic targets. Erdafitinib and pemigatinib, two FGFR selective inhibitors targeting FGFR fusions, have been approved by the U.S. Food and Drug Administration (FDA) to treat patients with urothelial cancer and cholangiocarcinoma, respectively. Futibatinib, a third-generation FGFR inhibitor, is under phase III clinical trials in patients with FGFR gene rearrangements. Herein, we review the current understanding of the FGF/FGFRs system and the oncogenic effect of FGFR fusions, summarize promising inhibitors under clinical development for patients with FGFR fusions, and highlight the challenges in this field.

Abstract Diabetes manifests as chronic inflammation and leads to the development diabetic cardiomyopathy (DCM). Targeting key proteins in inflammatory signaling may provide new therapy for DCM. In this study, the authors explore the pharmacological effects and mechanisms of Schisandrin B (Sch B), a natural compound with anti‐inflammatory activity against DCM. It is shown that Sch B prevents high‐level glucose (HG)‐induced hypertrophic and fibrotic responses in cultured cardiomyocytes. RNA sequencing and inflammatory qPCR microarray show that Sch B mainly affects myeloid differentiation primary response 88 (MyD88)‐dependent inflammatory gene expression in HG‐challenged cardiomyocytes. Further studies indicate that Sch B directly binds to and inhibits MyD88 activation, but does not alter MyD88‐independent Toll‐like receptor signaling in vivo and in vitro. Inhibiting or silencing MyD88 is associated with reduced levels of HG‐induced inflammatory cytokines and myocardial injuries in vitro. Treatment of type 1 and type 2 diabetic mice with Sch B protects heart function, reduces myocardial injuries, and decreases secretion of inflammatory cytokines. Cardiomyocyte‐specific MyD88 knockout also protects mice against cardiac inflammation and injury in type 1 diabetic mice. In conclusion, these studies show that cardiomyocyte MyD88 plays an apathogenetic role in DCM and Sch B specifically targets MyD88 to reduce inflammatory DCM.

Soft fingertips have distinct intrinsic features that allow robotic hands to offer adjustable and manageable stiffness for grasping. The stability of the grasp is determined by the contact stiffness between the soft fingertip and the object. Within this work, we proposed a line vector representation method based on the Winkler Model and investigated the contact stiffness between soft fingertips and objects to achieve control over the gripping force and fingertip displacement of the gripper without the need for sensors integrated in the fingertip. First, we derived the stiffness matrix of the soft fingertip, analyzed the contact stiffness, and constructed the global stiffness matrix; then, we established the grasp stiffness matrix based on the contact stiffness model, allowing for the analysis and evaluation of the soft fingertip’s manipulating process. Finally, our experiment demonstrated that the variation in object orientation caused by external forces can indicate the contact force status between the fingertip and the object. This contact force status is determined by the contact stiffness. The position error between the theoretical work and tested data was less than 9%, and the angle error was less than 5.58%. The comparison between the theoretical contact stiffness and the experimental results at the interface indicate that the present model for the contact stiffness is appropriate and the theoretical contact stiffness is consistent with the experiment data.

Background: Moderate renal artery stenosis (50–70%) may lead to uncontrolled hypertension and eventually cause irreversible damage to renal function. However, the clinical criteria for interventional treatment are still ambiguous in this condition. This study investigated the impact of the position and degree of renal artery stenosis on hemodynamics near the renal artery to assess the short-term and long-term risks associated with this disease. Methods: Calculation models with different degrees of stenosis (50%, 60%, and 70%) located at different positions in the right renal artery were established based on the computed tomography angiography (CTA) of a personalized case. And computational fluid dynamics (CFD) was used to analyze hemodynamic surroundings near the renal artery. Results: As the degree of stenosis increases and the stenosis position is far away from the aorta, there is a decrease in renal perfusion. An analysis of the wall shear stress (WSS)-related parameters indicated areas near the renal artery (downstream of the stenosis and the entrance of the right renal artery) with potential long-term risks of thrombosis and inflammation. Conclusion: The position and degree of stenosis play a significant role in judging short-term risks associated with renal perfusion. Moreover, clinicians should consider not only short-term risks but also independent long-term risk factors, such as certain regions of 50% stenosis with adequate renal perfusion may necessitate prompt intervention.

Image-based refined 3D reconstruction relies on high-resolution and multi-angle images of scenes. The assistance of multi-rotor drones and gimbal provides great convenience for image acquisition. However, capturing images with manual control generally takes a long time. It could easily lead to redundant or insufficient local area coverage, resulting in poor quality of the reconstructed model. We propose a surface geometric primitive-guided UAV path planning method (SGP-G) that aims to automatically and quickly plan a collision-free path to capture fewer images, based on which high-quality models can be obtained. The geometric primitives are extracted by plane segmentation on the proxy, which performs three main functions. First, a more representative evaluation of the reconstructability of the whole scene is realized. Second, two optimization strategies for different geometric primitives are executed to quickly generate a near-global optimized set of viewpoints. Third, regularly arranged viewpoints are generated to improve the efficiency of image acquisition. Experiments on virtual and real scenes demonstrate the remarkable performance of our method. Compared with the state of the art, we accomplish the planning of the photographic path with higher efficiency in a relatively simple way, achieving equivalent and even higher quality of the reconstructed model with fewer images.

Abstract Background Platinum-based anticancer drugs have been at the frontline of cancer therapy for the last 40 years, and are used in more than half of all treatments for different cancer types. However, they are not universally effective, and patients often suffer severe side effects because of their lack of cellular selectivity. There is therefore a compelling need to investigate the anticancer activity of alternative metal complexes. Here we describe the potential anticancer activity of rhenium-based complexes with preclinical efficacy in different types of solid malignancies. Methods Kinase profile assay of rhenium complexes. Toxicology studies using zebrafish. Analysis of the growth of pancreatic cancer cell line-derived xenografts generated in zebrafish and in mice upon exposure to rhenium compounds. Results We describe rhenium complexes which block cancer proliferation in vitro by inhibiting the signalling cascade induced by FGFR and Src. Initially, we tested the toxicity of rhenium complexes in vivo using a zebrafish model and identified one compound that displays anticancer activity with low toxicity even in the high micromolar range. Notably, the rhenium complex has anticancer activity in very aggressive cancers such as pancreatic ductal adenocarcinoma and neuroblastoma. We demonstrate the potential efficacy of this complex via a significant reduction in cancer growth in mouse xenografts. Conclusions Our findings provide a basis for the development of rhenium-based chemotherapy agents with enhanced selectivity and limited side effects compared to standard platinum-based drugs.

The modular inner branched stent-graft (MIBSG), a novel interventional therapy, has demonstrated good effects in the endovascular treatment of aortic arch pathologies, especially those involving the supra-aortic branches. Nevertheless, the long-term efficacy of the MIBSG and in-depth quantitative evaluation of postoperative outcomes remain to be examined. Moreover, the regularity of postoperative vascular remodeling induced by MIBSG implantation has yet to be explored. To address these questions, we constructed four models (normal, preoperative, 1 week postoperative, and 6 months postoperative) based on a single patient case to perform computational fluid dynamics simulations. The morphological and hemodynamic characteristics, including the velocity profile, flow rate distribution, and hemodynamic parameter distribution (wall shear stress and its derivative parameters), were investigated. After MIBSG implantation, the morphology of the supra-aortic branches changed significantly, and the branch point moved forward to the proximal ascending aorta. Moreover, the curvature radius of the aortic arch axis continued to change. These changes in morphology altered the characteristics of the flow field and wall shear stress distribution. As a result, the local forces exerted on the vessel wall by the blood led to vessel remodeling. This study provides insight into the vascular remodeling process after MIBSG implantation, which occurs as a result of the interplay between vascular morphological characteristics and blood flow characteristics.

Pancreatic adenocarcinoma is by far the deadliest type of cancer. Inflammation is one of the important risk factors in tumor development. However, it is not yet clear whether deterioration in pancreatic cancer patients is related to inflammation, as well as the underlying mechanism. In addition, JNK is abnormally activated in pancreatic cancer cells and the JNK inhibitor C66 reduces the inflammatory microenvironment in the tumor. Therefore, the aim of this study was to evaluate the role of C66 in the proliferation and migration of pancreatic cancer. Our results showed that various inflammatory cytokines, such as IL-1β, IL-6, IL-8, and IL-15, were more expressed in pancreatic cancer than in the matching normal tissue. Furthermore, C66, a curcumin analogue with good anti-inflammatory activity, inhibited the proliferation and migration of pancreatic cancer cells in a dose-dependent manner, and effectively inhibited the expression of the above inflammatory factors. Our previous research demonstrated that C66 prevents the inflammatory response by targeting JNK. Therefore, in this study, JNK activity in pancreatic cancer cells was investigated, revealing that JNK was highly activated, and the treatment with C66 inhibited the phosphorylation of JNK. Next, shJNK was used to knockdown JNK expression in pancreatic cancer cells to further confirm the role of JNK in the proliferation and migration of this tumor, as well as in the inflammatory tumor microenvironment (TME). The results demonstrated that JNK knockdown could significantly inhibit the proliferation and migration of pancreatic cancer. Moreover, the low JNK expression in pancreatic cancer cells significantly inhibited the expression of various inflammatory factors. These results indicated that C66 inhibited the progression of pancreatic cancer through the inhibition of JNK-mediated inflammation.

In the past decades, epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) had been proved as an effective treatment strategy for the patients with EGFR-mutated non-small-cell lung cancer (NSCLC). However, the tolerance for the EGFR-TKI always occurred after continuous administration for a period of time and limiting the application of these drugs. Activation of FGFR1 signaling pathway was one of the important escape mechanisms for EGFR-TKI resistant in NSCLC. Here, a novel dual inhibitor of EGFRL858R/T790M and FGFR1, compound15c, was found and can efficiently overcame the EGFR-TKI resistance via its simultaneous inhibition of their kinase activities. Comparison with EGFRL858R/T790M and FGFR1 inhibitor treatment alone or combined revealed that the inhibition of EGFRL858R/T790M and FGFR1 activity by 15c was responsible for surmounting the intrinsic EGFR-TKI resistance in EGFRL858R/T790M-mutated H1975 cells and the acquired resistance in Afatinib-tolerant PC9 cells (AFA-PC9). Flow Cytometry and Caspase3 activity analysis assay showed that 15c induced significant the early apoptosis of H1975 cells. Xenograft tumor formation in BALB/c mice induced by a H1975 cells was suppressed by 15c treatment, with no changes in animal body weight. Generally, 15c may act as a new-generation EGFR-TKI for the therapy of NSCLC patients suffering a resistance to current TKI.

Cancer therapy might benefit significantly from nanotechnology. These nano-drug delivery systems (NDDS) have been established to improve the therapeutic benefits of anticancer medications by enhancing their bioavailability, degradation, and biocompatibility. One of the most promising NDDS for cancer therapy is high-performance hydroxyapatite (HA) nanoparticles, which have many advantages. The metabolite marizomib inhibits tumor cell growth and progression, functioning as a biochemical inhibitor in many malignancies. However, this substance’s low bioavailability is the most significant problem with its use. In this work, a pH-sensitive biopolymer was employed to encapsulate HA nanoparticles with chitosan to increase marizomib’s (MARI) efficacy and bioavailability. The sol-gel process was used to fabricate HA nanoparticles for this purpose. It was then coated with chitosan before encasing the marizomib drug in the nanocarrier, which was done under controlled circumstances. The newly fabricated nanoparticles effectively kill ovarian A2780 cancer cells and induce apoptosis. The morphological examination of the cancer cells was examined by AO/EB and DAPI staining methods. Further, the cell uptake was measured by the flow cytometry methods, and the result shows the nanoparticles were effectively uptake the cancer cells under different incubation times. In principle, nanoparticles have great potential for future pre-clinical applications in treating ovarian cancer cells and suppressing other types of tumors.

Adhesive and migratory behavior can be cell type, integrin, and substrate dependent. We have compared integrin and substrate differences using three integrin receptors: α5β1, α6β1, and αLβ2 expressed in a common cell type, CHO.B2 cells, which lack integrin α subunits, as well as in different cell types that express one or more of these integrins. We find that CHO.B2 cells expressing either α6β1 or αLβ2 integrins migrate and protrude faster and are more directionally persistent on laminin or ICAM-1, respectively, than CHO.B2 cells expressing α5β1 on fibronectin. Despite rapid adhesion maturation and the presence of large adhesions in both the α6β1- and αLβ2-expressing cells, they display robust tyrosine phosphorylation. In addition, whereas myosin II regulates adhesion maturation and turnover, protrusion rates, and polarity in cells migrating on fibronectin, surprisingly, it does not have comparable effects in cells expressing α6β1 or αLβ2. This apparent difference in the integration of myosin II activity, adhesion, and migration arises from alterations in the ligand-integrin-actin linkage (molecular clutch). The elongated adhesions in the protrusions of the α6β1-expressing cells on laminin or the αLβ2-expressing cells on ICAM-1 display a novel, rapid retrograde flux of integrin; this was largely absent in the large adhesions in protrusions of α5β1-expressing cells on fibronectin. Furthermore, the force these adhesions exert on the substrate in protrusive regions is reduced compared to similar regions in α5-expressing cells, and the adhesion strength is reduced. This suggests that intracellular forces are not efficiently transferred from actomyosin to the substratum due to altered adhesion strength, that is, avidity, affinity, or the ligand-integrin-actin interaction. Finally, we show that the migration of fast migrating leukocytes on fibronectin or ICAM-1 is also largely independent of myosin II; however, their adhesions are small and do not show retrograde fluxing suggesting other intrinsic factors determine their migration differences.

We introduce a new generalized theoretical framework for image correlation spectroscopy (ICS). Using this framework, we extend the ICS method in time–frequency ( ν , nu) space to map molecular flow of fluorescently tagged proteins in individual living cells. Even in the presence of a dominant immobile population of fluorescent molecules, nu-space ICS (nICS) provides an unbiased velocity measurement, as well as the diffusion coefficient of the flow, without requiring filtering. We also develop and characterize a tunable frequency-filter for spatio-temporal ICS (STICS) that allows quantification of the density, the diffusion coefficient and the velocity of biased diffusion. We show that the techniques are accurate over a wide range of parameter space in computer simulation. We then characterize the retrograde flow of adhesion proteins ( α 6- and α L β 2-GFP integrins and mCherry-paxillin) in CHO.B2 cells plated on laminin and intercellular adhesion molecule 1 (ICAM-1) ligands respectively. STICS with a tunable frequency filter, in conjunction with nICS, measures two new transport parameters, the density and transport bias coefficient (a measure of the diffusive character of a flow/biased diffusion), showing that molecular flow in this cell system has a significant diffusive component. Our results suggest that the integrin–ligand interaction, along with the internal myosin-motor generated force, varies for different integrin–ligand pairs, consistent with previous results.