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Introduction: Many research studies have well investigated Alzheimer's disease (AD) detection and progression. However, the continuous-time survival prediction of AD is not yet fully explored to support medical practitioners with predictive analytics. In this study, we develop a survival analysis approach to examine interactions between patients' inherent temporal and medical patterns and predict the probability of the AD next stage progression during a time period. The likelihood of reaching the following AD stage is unique to a patient, helping the medical practitioner analyze the patient's condition and provide personalized treatment recommendations ahead of time., Methodologies: We simulate the disease progression based on patient profiles using non-linear survival methods-non-linear Cox proportional hazard model (Cox-PH) and neural multi-task logistic regression (N-MTLR). In addition, we evaluate the concordance index (C-index) and Integrated Brier Score (IBS) to describe the evolution to the next stage of AD. For personalized forecasting of disease, we also developed deep neural network models using the dataset provided by the National Alzheimer's Coordinating Center with their multiple-visit details between 2005 and 2017., Results: The experiment results show that our N-MTLR based survival models outperform the CoxPH models, the best of which gives Concordance-Index of 0.79 and IBS of 0.09. We obtained 50 critical features out of 92 by applying recursive feature elimination and random forest techniques on the clinical data; the top ones include normal cognition and behavior, criteria for dementia, community affairs, etc. Our study demonstrates that selecting critical features can improve the effectiveness of probabilities at each time interval., Conclusions: The proposed deep learning-based survival method and model can be used by medical practitioners to predict the patients' AD shift efficiently and recommend personalized treatment to mitigate or postpone the effects of AD. More generally, our proposed survival analysis approach for predicting disease stage shift can be used for other progressive diseases such as cancer, Huntington's disease, and scleroderma, just to mention a few, using the corresponding clinical data., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper., (© 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Introduction: Survival period prediction through early diagnosis of cancer has many benefits. It allows both patients and caregivers to plan resources, time and intensity of care to provide the best possible treatment path for the patients. In this paper, by focusing on lung cancer patients, we build several survival prediction models using deep learning techniques to tackle both cancer survival classification and regression problems. We also conduct feature importance analysis to understand how lung cancer patients' relevant factors impact their survival periods. We contribute to identifying an approach to estimate survivability that are commonly and practically appropriate for medical use., Methodologies: We have compared the performance across three of the most popular deep learning architectures - Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) while comparing the performing of deep learning models against traditional machine learning models. The data was obtained from the lung cancer section of Surveillance, Epidemiology, and End Results (SEER) cancer registry., Results: The deep learning models outperformed traditional machine learning models across both classification and regression approaches. We obtained a best of 71.18 % accuracy for the classification approach when patients' survival periods are segmented into classes of '<=6 months',' 0.5 - 2 years' and '>2 years' and Root Mean Squared Error (RMSE) of 13.5 % andR 2 value of 0.5 for the regression approach for the deep learning models while the traditional machine learning models saturated at 61.12 % classification accuracy and 14.87 % RMSE in regression., Conclusions: This approach can be a baseline for early prediction with predictions that can be further improved with more temporal treatment information collected from treated patients. In addition, we evaluated the feature importance to investigate the model interpretability, gaining further insight into the survival analysis models and the factors that are important in cancer survival period prediction., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Individuals suffer from chronic diseases without being identified in time, which brings lots of burden of disease to the society. This paper presents a multiple disease risk prediction method to systematically assess future disease risks for patients based on their longitudinal medical records. In this study, medical diagnoses based on International Classification of Diseases (ICD) are aggregated into different levels for prediction to meet the needs of different stakeholders. The proposed approach gets validated using two independent hospital medical datasets, which includes 7105 patients with 18, 893 patients and 4170 patients with 13, 124 visits, respectively. The initial analysis reveals a high variation in patients' characteristics. The study demonstrates that recurrent neural network with long-short time memory units performs well in different levels of diagnosis aggregation. Especially, the results show that the developed model can be well applied to predicting future disease risks for patients, with the exact-match score of 98.90% and 95.12% using 3-digit ICD code aggregation, while 96.60% and 96.83% using 4-digit ICD code aggregation for these two datasets, respectively. Moreover, the approach can be developed as a reference tool for hospital information systems, enhancing patients' healthcare management over time.

We present a new hybrid compound, namely (Me2NH2)[KFe(CN)5(NO)], possessing a unique nitroprusside-based inorganic host framework in 4-connected sra topology encapsulating organic guest cations. The flexible host-guest hydrogen bonds and synchronously deformed inorganic framework give rise to thermal-responsive switching behaviours on both thermal expansion and nonlinear optical properties during the phase transition at around room temperature.

The International Classification of Diseases (ICD) not only serves as the bedrock for health statistics but also provides a holistic overview of every health aspect of life. This study aims to facilitate the computer-assisted coding of the 11th revision of the ICD (ICD-11) by leveraging the data structures of ICD-11 and semantics in WordNet. First, a computer-assisted coding framework using WordNet and ICD-11 application programming interface (API) is proposed. Secondly, a network based on entity relations in ICD-11 and synonym sets in WordNet, called CodeNet, is developed. Thirdly, an algorithm for generating ICD-11 code candidates from CodeNet with two tuning parameters on the basis of the input of disease-related text is illustrated. Finally, the discharge summaries in the Medical Information Mart for Intensive Care III database and textual information from ICD-11 entities are used to evaluate the proposed method. Experimental results indicate that the proposed coding method achieves a precision of 84% and a recall of 89% relative to a precision of 65% and a recall of 81% achieved with the existing ICD-11 API. The proposed method also outperforms other methods in the literature by reducing a failure rate of up to 8% in ICD-11 coding. The proposed thresholds of similarity and percentage can be applied to tuning the performance of our method to meet different coding needs. In sum, improving the new structures of ICD-11 with the use of semantics in WordNet can help develop more reliable computer-aided coding systems for ICD-11 coders.

The number of service visits of Alzheimer's disease (AD) patients is different from each other and their visit time intervals are non-uniform. Although the literature has revealed many approaches in disease progression modeling, they fail to leverage these time-relevant part of patients' medical records in predicting disease's future status. This paper investigates how to predict the AD progression for a patient's next medical visit through leveraging heterogeneous medical data. Data provided by the National Alzheimer's Coordinating Center includes 5432 patients with probable AD from August 31, 2005 to May 25, 2017. Long short-term memory recurrent neural networks (RNN) are adopted. The approach relies on an enhanced "many-to-one" RNN architecture to support the shift of time steps. Hence, the approach can deal with patients' various numbers of visits and uneven time intervals. The results show that the proposed approach can be utilized to predict patients' AD progressions on their next visits with over 99% accuracy, significantly outperforming classic baseline methods. This study confirms that RNN can effectively solve the AD progression prediction problem by fully leveraging the inherent temporal and medical patterns derived from patients' historical visits. More promisingly, the approach can be customarily applied to other chronic disease progression problems.

We disclosed that acetamidinium perchlorate is a plastic crystal undergoing a near-room-temperature plastic transition. Thanks to drastic symmetry breaking during the plastic transition, it displays remarkable nonlinear optical switching with a high on/off contrast and a superior reversibility, as well as rapid dielectric switching between the high and low dielectric states.

The tumor-suppressor protein p53 is considered to be one of the most important transport hubs of cell signal transduction, playing critical roles in the control of cell cycle arrest, apoptosis and many other processes as a nuclear transcription factor. p53 also acts in the cytoplasm to trigger apoptosis. Paclitaxel and other microtubule inhibitors can inhibit the growth of different types of cancer cells and induce apoptosis which is believed to be p53-independent. In the present study, we demonstrated that UTD1, a genetically engineered epothilone analog and a new microtubule inhibitor, activated p53 as a transcription factor at low concentrations demonstrated by its enhanced transcriptional activity and accumulation of p21, which led to cell cycle arrest. However, at high concentrations of UTD1, p53 was accumulated in the cytoplasm which contributed to induction of apoptosis. These observations indicate that the epothilone analog has differential effects on intracellular signaling and implies that p53 plays different roles in cells exposed to different concentrations of the anticancer agent.

Type I polyketides are natural products with diverse functions that are important for medical and agricultural applications. Manipulation of large biosynthetic gene clusters containing type I polyketide synthases (PKS) for heterologous expression is difficult due to the existence of conservative sequences of PKS in multiple modules. Red/ET mediated recombination has permitted rapid manipulation of large fragments; however, it requires insertion of antibiotic selection marker in the cassette, raising the problem of interference of expression by leaving "scar" sequence. Here, we report a method for precise seamless stitching of large polyketide biosynthetic gene cluster using a 48.4kb fragment containing type I PKS involved in fostriecin biosynthesis as an example. rpsL counter-selection was used to assist seamless stitching of large fragments, where we have overcome both the size limitations and the restriction on endonuclease sites during the Red/ET recombination. The compatibility and stability of the co-existing vectors (p184 and pMT) which respectively accommodate 16kb and 32.4kb inserted fragments were demonstrated. The procedure described here is efficient for manipulation of large DNA fragments for heterologous expression., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Microblog that provides us a new communication and information sharing platform has been growing exponentially since it emerged just a few years ago. To microblog users, recommending followees who can serve as high quality information sources is a competitive service. To address this problem, in this paper we propose a matrix factorization model with structural regularization to improve the accuracy of followee recommendation in microblog. More specifically, we adapt the matrix factorization model in traditional item recommender systems to followee recommendation in microblog and use structural regularization to exploit structure information of social network to constrain matrix factorization model. The experimental analysis on a real-world dataset shows that our proposed model is promising.

Fostriecin (FST, 1) is a natural product with promising antitumor activity produced by Streptomyces pulveraceus. Its antitumor activity is associated with the selective inhibition of protein phosphatase activities. The biosynthetic gene cluster for FST has recently been cloned and sequenced. To better understand the post-polyketide synthase (PKS) modification steps in the biosynthetic pathway of FST, we constructed and characterized three post-PKS modification gene mutants of fosG, fosK, and fosM by knockout inactivation in S. pulveraceus. As a result, we determined that a fosK-encoded cytochrome P450 monooxygenase is responsible for C-18 hydroxylation, formation of an unsaturated lactone is dependent upon FosM, and the fosG gene product is involved in hydroxylation at C-4 after the action of FosM to yield PD 113,271 from FST. The accumulated analogues from the ΔfosK and ΔfosM mutant strains possessed a malonyl ester moiety that suggested that all the post-PKS modification steps in FST biosynthesis occur with the polyketide chain bearing a malonyl ester at the C-3 position, with formation of the unsaturated six-membered lactone as the last step in FST biosynthesis.

The epothilones represent a new class of bacterial natural products with broad spectrum of antiproliferative activity against various types of human tumors and tumor cell lines. The attractive preclinical profile of epothilones has made them promising lead compounds for novel anticancer agents and has spurred a strong interest in obtaining different derivatives to fully evaluate their therapeutic potentials. We have generated a number of novel epothilone D and 10,11-dehydroepothilone D (Epo490) analogs via biotransformation using Amycolata autotrophica to alter the oxidation state of the parental compounds. The bioconverted compounds displayed different degrees of potency in cytotoxicity assays against a panel of human tumor cell lines, with 11-hydroxyepothilone D, 14-hydroxyepothilone D, and 21-hydroxyepothilone D showing comparable activity to that of epothilone D, and 21-hydroxy Epo490 being comparable to Epo490. The addition of hydroxyl group(s) seems to cause a decrease in cytotoxic activity against multiple drug resistant cell lines (with overexpressed P-glycoprotein). The compounds generated by biotransformation exert differential effects on tubulin polymerization, which correlate with their biological activities.

A new epothilone, 10,11-didehydroepothilone D (5), was isolated from a strain of the heterologous host Myxococcus xanthus genetically engineered to produce epothilone D (4). The structure of 5 was determined from NMR and MS data. The epothilone polyketide synthase was further modified in a recombinant M. xanthus strain to produce 5 as the major epothilone-related metabolite. The cytotoxicity of 5 against a panel of tumor cell lines, including several with multidrug resistance, and its effect on tubulin polymerization were comparable to epothilone D (4).

Transfection of Rat1 fibroblasts with an activated form of rac1 (V12rac1) stimulated cell migration in vitro compared to transfection of Rat1 fibroblasts with vector only or with dominant negative rac1 (N17rac1). To investigate the involvement of proteases in this migration, we used a novel confocal assay to evaluate the ability of the Rat1 transfectants to degrade a quenched fluorescent protein substrate (DQ-green bovine serum albumin) embedded in a three-dimensional gelatin matrix. Cleavage of the substrate results in fluorescence, thus enabling one to image extracellular and intracellular proteolysis by living cells. The Rat1 transfectants accumulated degraded substrate intracellularly. V12rac1 increased accumulation of the fluorescent product in vesicles that also labeled with the lysosomal marker LysoTracker. Treatment of the V12rac1-transfected cells with membrane-permeable inhibitors of lysosomal cysteine proteases and a membrane-permeable selective inhibitor of the cysteine protease cathepsin B significantly reduced intracellular accumulation of degraded substrate, indicating that degradation occurred intracellularly. V12rac1 stimulated uptake of dextran 70 (a marker of macropinocytosis) and polystyrene beads (markers of phagocytosis) into vesicles that also labeled for cathepsin B. Thus, stimulation of the endocytic pathways of macropinocytosis and phagocytosis by activated Rac1 may be responsible for the increased internalization and subsequent degradation of extracellular proteins., (Copyright 2000 Academic Press.)

Background: Rac and Cdc42 are members of the Rho family of small GTPases. They modulate cell growth and polarity, and contribute to oncogenic transformation by Ras. The molecular mechanisms underlying these functions remain elusive, however., Results: We have identified a novel effector of Rac and Cdc42, hPar-6, which is the human homolog of a cell-polarity determinant in Caenorhabditis elegans. hPar-6 contains a PDZ domain and a Cdc42/Rac interactive binding (CRIB) motif, and interacts with Rac1 and Cdc42 in a GTP-dependent manner. hPar-6 also binds directly to an atypical protein kinase C isoform, PKCzeta, and forms a stable ternary complex with Rac1 or Cdc42 and PKCzeta. This association results in stimulation of PKCzeta kinase activity. Moreover, hPar-6 potentiates cell transformation by Rac1/Cdc42 and its interaction with Rac1/Cdc42 is essential for this effect. Cell transformation by hPar-6 involves a PKCzeta-dependent pathway distinct from the pathway mediated by Raf., Conclusions: These findings indicate that Rac/Cdc42 can regulate cell growth through Par-6 and PKCzeta, and suggest that deregulation of cell-polarity signaling can lead to cell transformation.

Directed cell migration is essential for a variety of important biological processes ranging from development and angiogenesis to metastasis. Ras plays a pivotal role in the signaling cascade that governs chemotaxis of fibroblasts toward platelet-derived growth factor-BB (PDGF-BB). Ras activates multiple downstream pathways, which include the extracellular signal-regulated kinase (ERK), Rac, and Ral signaling cascades. We therefore investigated the role of the Rac and ERK pathways in cell migration. We showed that migration of fibroblasts toward PDGF-BB is inhibited by expression of dominant negative Asn-17 Rac1. Blocking of the ERK pathway by either expression of dominant negative Ala-218/Ala-222-mitogen-activated protein kinase kinase (A218/A222-MEK1) or by a MEK-specific inhibitor did not inhibit migration toward PDGF-BB. In contrast, migration toward soluble fibronectin was suppressed by inhibition of the ERK pathway but not by Asn-17 Rac1 expression. These results indicate that directed cell migration mediated by different receptor classes in response to different ligands differentially utilizes the Rac and ERK pathways and suggest that Rac might play a critical role in pathological processes such as angiogenesis and metastasis.

The Rho family members Cdc42, Rac, and Rho play a central role in the organization of the actin cytoskeleton and regulate transcription. Whereas Rac and Rho have been implicated in transformation by oncogenic Ras, the role of Cdc42 in this process remains unknown. In this study, we found that Rat1 fibroblasts expressing constitutively active V12-Cdc42 were anchorage independent and proliferated in nude mice but failed to show enhanced growth in low serum. Similar to V12-Rac1-expressing Rat1 fibroblasts, V12-Cdc42 lines displayed a high frequency of multinucleated cells. Interestingly, coexpression of dominant negative N17-Rac1 blocked the V12-Cdc42-induced multinucleated phenotype but not growth in soft agar, indicating that Cdc42 controls anchorage independence in a Rac-independent fashion. We also showed that dominant negative N17-Cdc42 inhibited Ras focus formation and anchorage-independent growth and caused reversion of the transformed morphology, indicating that Cdc42 is necessary for Ras transformation. N17-Cdc42 caused only partial inhibition of Ras-induced low-serum growth, however. In contrast, whereas N17-Rac1 also effectively inhibited Ras-induced anchorage independence, it did not revert the morphology of Ras-transformed cells. N17-Rac1 strongly inhibited low-serum growth of Ras-transformed cells, however. Together, these data provide a novel function for Cdc42 in cell proliferation and indicate that Cdc42 and Rac play distinct roles in growth control and Ras transformation.

Glycerophosphoinositols are phosphoinositide metabolites whose levels are constitutively elevated in Ras-transformed cells. Here, we show that one of these compounds, glycerophosphoinositol-4-phosphate (GroPIns-4-P) responds acutely to the stimulation of the epidermal growth factor receptor, with a fast, massive and transient increase. The mechanism leading to GroPIns-4-P formation involves the activation of phosphoinositide-3 kinase and the small GTP-binding protein Rac, since GroPIns-4-P was neither formed in cells expressing the dominant negative form of Rac nor in cells treated with the phosphoinositide-3 kinase inhibitor wortmannin. GroPIns-4-P has been previously shown to inhibit adenylyl cyclase. Accordingly, epidermal growth factor also decreased the basal, cholera toxin-stimulated, and forskolin-stimulated cyclic AMP levels with kinetics similar to those of GroPIns-4-P formation, suggesting that GroPIns-4-P mediates this inhibitory effect. The hormone-induced formation of GroPIns-4-P was detected in several cell lines of various origin, suggesting that GroPIns-4-P is a novel intracellular messenger of the Ras pathway, possibly able to convey information from tyrosine kinase receptors to the cyclic AMP cascade.

Treatment of fibroblasts with growth factors results in activation of phospholipase D (PLD). In order to determine the role of the Rho family of small GTPases in growth factor-mediated PLD activation, we used cells transfected with wild type and mutant Rac1. In response to epidermal growth factor (EGF), PLD activity was greatly increased in Rat1 fibroblasts expressing wild type Rac1 (wtRac1), and completely abrogated in cells expressing dominant negative N17Rac1, consistent with Rac1 mediating the action of this growth factor. In contrast, in cells treated with platelet-derived growth factor (PDGF) or phorbol ester, the wtRac1 cells showed little or no enhancement of PLD activity, and the response was not affected in the N17Rac1 cells, implying that Rac1 played a minimal role in the activation of PLD by PDGF or protein kinase C. Both growth factors produced an attenuated PLD response in cells expressing constitutively active V12Rac1, but these cells showed other changes, including altered morphology, increased basal PLD, and decreased growth factor receptor autophosphorylation. The effects of EGF and PDGF on phosphoinositide phospholipase C activity were not enhanced in cells expressing wtRac1 or inhibited in those expressing N17Rac1. In cells expressing constitutively active V12Rac1, basal phosphoinositide phospholipase C was elevated, but there were no significant effects of EGF or PDGF. We used C3 transferase of Clostridium botulinum, which ADP-ribosylates and inactivates RhoA, to investigate the involvement of RhoA in the activation of PLD by PDGF. Cells expressing wtRac1 and N17Rac1 showed a decreased PLD in response to PDGF when treated with C3 transferase, indicating a role for RhoA. In summary, these data indicate a major role for Rac1 in the activation of PLD by EGF, but not PDGF or protein kinase C.

The Rho GTPase promotes proliferation and cytoskeletal rearrangements in mammalian cells. To understand the regulation of Rho, it is important to characterize guanine nucleotide exchange factors (GEFs), which stimulate the dissociation of GDP and subsequent binding of GTP. Using Rho as an affinity ligand, we have isolated a 115-kDa protein (p115-RhoGEF) that binds specifically to the nucleotide-depleted state. A full-length cDNA encoding p115-RhoGEF was isolated, and its protein product, which exhibited sequence homology to Dbl and Lbc, catalyzed the exchange of GDP for GTP specifically on Rho and not on the Rac, Cdc42, or Ras GTPases. p115-RhoGEF is capable of regulating cell proliferation, as determined by its ability to induce the transformation of NIH 3T3 cells. Northern and Western analysis suggests that p115-RhoGEF is ubiquitously expressed. These results indicate that p115-RhoGEF may be a general regulator of Rho and its associated cellular phenotypes.

We report that expressing interfering mutants of the small Ras-related GTPase Rac, using either recombinant vaccinia virus or stable DNA transfection, eliminates epidermal growth factor-induced Ca2+ signaling, without affecting Ca2+ mobilization or influx from G protein-coupled receptors. Platelet-derived growth factor-dependent Ca2+ influx, however, is only partly sensitive to dominant negative Rac proteins. Thus, whereas epidermal growth factor-induced Ca2+ influx is completely mediated by Rac proteins, platelet-derived growth factor-induced Ca2+ influx involves Rac-dependent and -independent signaling pathways.

The small GTP-binding proteins Rac and Rho are key elements in the signal-transduction pathways respectively controlling the formation of lamellipodia and stress fibers induced by growth factors or oncogenic Ras. We recently reported that Rac function is necessary for Ras transformation and that expression of constitutively activated Rac1 is sufficient to cause malignant transformation. We now show that, although expression of constitutively activated V14-RhoA in Rat 1 fibroblasts does not cause transformation on its own, it strongly cooperates with constitutively active RafCAAX in focus-formation assays in NIH 3T3 cells. Furthermore, dominant-negative N19-RhoA inhibits focus formation by V12-H-Ras and RafCAAX in NIH 3T3 cells, and stable coexpression of N19-RhoA and V12-H-Ras in Rat1 fibroblasts reverts Ras transformation. Interestingly, stress fiber formation is inhibited in V12-H-Ras lines and restored by coexpression of N19-RhoA. We conclude that Rho drives at least two separate pathways, one that induces stress fiber formation and another one that is important for transformation by oncogenic Ras.

Growth factor-induced stress fiber formation involves signal transduction through Rac and Rho proteins and production of leukotrienes from arachidonic acid metabolism. In exploring the relationship between these pathways, we found that Rac is essential for EGF-induced arachidonic acid production and subsequent generation of leukotrienes and that Rac V12, a constitutively activated mutant of Rac, generates leukotrienes in a growth factor-independent manner. Leukotrienes generated by EGF or Rac V12 are necessary and sufficient for stress fiber formation. Furthermore, leukotriene-dependent stress fiber formation requires Rho proteins. We have therefore identified elements of a pathway from growth factor receptors that includes Rac, arachidonic acid production, arachidonic acid metabolism to leukotrienes, and leukotriene-dependent Rho activation. This appears to be the major pathway by which Rac influences Rho-dependent cytoskeleton rearrangements.

Phospholipase D (PLD) activity that was stimulated by guanosine 5'-O-(3-thiotriphosphate) (GTP gamma S) was detected in cytosol and membranes of HL60 cells. GTP gamma S-stimulated PLD activity was detected in the membranes when exogenous labeled phosphatidylcholine was used in the presence of phosphatidylethanolamine and phosphatidylinositol 4,5-bisphosphate, but not when [3H]myristic acid-labeled endogenous substrate was used. Cytosolic PLD co-chromatographed with small GTP-binding proteins on anion-exchange columns, but subsequent chromatography separated these. Reconstitution studies demonstrated ADP ribosylation factor (ARF) as a regulator of cytosolic PLD, whereas the Rho proteins RhoA and CDC42Hs were ineffective. The cytosolic enzyme showed very little activity in the absence of GTP gamma S and was stimulated by 2 mM Ca2+, whereas the membrane enzyme had significant basal activity and was inhibited by Ca2+. Rho-specific GDP dissociation inhibitor inhibited GTP gamma S stimulation of membrane PLD activity in the presence and absence of cytosol. The stimulation in GDP dissociation inhibitor-treated membranes could be partially recovered by the addition of recombinant Rho proteins (RhoA, Rac1, CDC42Hs). RhoA and Rac1 were also stimulatory in untreated membranes. However, Western blot analysis of membranes showed the presence of RhoA, but not Rac1 or CDC42Hs, suggesting that RhoA was the endogenous small GTP-binding protein involved in GTP-dependent PLD activity in membranes in the absence of cytosol. ARF also stimulated the membrane PLD in the presence of GTP gamma S, and the combination of RhoA and ARF showed a synergistic effect. These results show the presence of ARF-dependent PLD activity in both cytosol and membranes. The membranes contain another PLD activity for which the endogenous regulator appears to be RhoA. The data suggest the existence of at least two different PLD isozymes in HL60 cells.

Background: Phosphoinositide 3-kinases (PI 3-kinases) are thought to play an important role in coordinating the responses elicited by a variety of growth factors, oncogene products and inflammatory stimuli. These responses include activation of membrane ruffling, chemotaxis, glucose transport, superoxide production, neurite outgrowth and pp70 S6 kinase. Some of these responses are also known to be regulated by Rac, a small GTP-binding protein related to Ras. Neither the transducing elements upstream of Rac, nor those downstream of PI 3-kinase, have been defined., Results: We show here that platelet-derived growth factor (PDGF) can stimulate an increase in the level of GTP-Rac by at least two distinct mechanisms: firstly, by increased guanine nucleotide exchange; and secondly, by inhibition of a Rac GTPase activity. The first of these mechanisms is essential for the activation of Rac, and we show that it is dependent upon PDGR-stimulated synthesis of phosphatidylinositol (3,4,5)-trisphosphate., Conclusions: These results suggest that Rac activation lies downstream of PI 3-kinase activation on a PDGF-stimulated signalling pathway. Furthermore, as Rac has been implicated in at least two diverse cellular responses that are also though to require activation of PI 3-kinase--a reorganization of the actin cytoskeleton known as membrane ruffling and the neutrophil oxidative burst--these results suggest that Rac may be a major effector protein for the PI 3-kinase signalling pathway in many cell types.

The GTPase Rac1 is a key component in the reorganization of the actin cytoskeleton that is induced by growth factors or oncogenic Ras1. Here we investigate the role of Rac1 in cell transformation and show that Rat1 fibroblasts expressing activated Val-12 Rac1 (Rac1 with valine at residue 12) display all the hallmarks of malignant transformation. In a focus-forming assay in NIH3T3 fibroblasts to measure the efficiency of transformation, we found that dominant-negative Asn-17 Rac1 inhibited focus formation by oncogenic Ras, but not by RafCAAX, a Raf kinase targeted to the plasma membrane by virtue of the addition of a carboxyterminal localization signal from K-Ras. This indicates that Rac is essential for transformation by Ras. In addition, Val-12 Rac1 synergizes strongly with RafCAAX in focus-formation assays, indicating that oncogenic Ras drives both the Rac and MAP-kinase pathways, which cooperate to cause transformation.

Stimulation of phospholipase D by guanosine 5'-O-(3-thiotriphosphate) (GTP gamma S) in rat liver plasma membranes indicates the involvement of GTP-binding proteins. We used RhoGDI, an inhibitor of GDP dissociation from small GTP-binding proteins of the Rho family, to determine the involvement of these proteins. Incubation, and subsequent washing, of plasma membranes with RhoGDI dose-dependently diminished GTP gamma S-stimulated phospholipase D activity, as determined by accumulation of phosphatidylethanol in the presence of ethanol. Incubation with RhoGDI also caused a rapid and dose-dependent appearance of RhoA in the wash, which was associated with the inhibition of phospholipase D. RhoGDI also rapidly extracted Cdc42 from membranes, but Rac1 was not extracted. Full reconstitution of GTP gamma S-stimulated phospholipase D in RhoGDI-washed membranes was achieved with recombinant RhoA. There was partial reconstitution with Rac1 and no enhancement with Cdc42 or ADP-ribosylation factor. The response to RhoA was dose-dependent (EC50 = 0.5 microM). ADP-ribosylation of RhoA by Clostridium botulinum C3 exoenzyme did not affect its ability to recover GTP gamma S-stimulated phospholipase D activity in RhoGDI-washed membranes. These findings support a role for GTP-binding proteins of the Rho family in the activation of membrane-associated phospholipase D and implicate RhoA as the major protein involved.

Murine B lymphocytes, adipocytes, and olfactory neurons contain a DNA-binding protein that participates in the regulation of genes encoding tissue-specific components of signal transduction. Purification and cloning of this protein, termed early B-cell factor (EBF), from murine B lymphocytes and independent cloning of a protein, termed Olf-1, from olfactory neuronal cells revealed virtual complete amino acid sequence identity between these proteins. As a first step towards identifying a human genetic disorder or mouse mutation for which EBF could be a candidate gene, we have chromosomally mapped the corresponding locus in both species. By Southern hybridization analyses of somatic cell hybrid panels with murine cDNA probe, fluorescence chromosomal in situ hybridization (FISH) of human genomic clones, and analysis of recombinant inbred mouse strains, we have found single sites for EBF homologous sequences on human Chromosome (Chr) 5, band q34, and on proximal mouse Chr 11, in an evolutionarily conserved region.

Factor access in chromatin has been proposed to be facilitated by transcriptional enhancers. With the aim of uncoupling factor access from transcriptional stimulation by protein-protein contacts, we analyzed the potential of enhancer fragments to confer accessibility upon a linked promoter for prokaryotic T7 RNA polymerase. Access to the T7 promoter in pre-B cells from transgenic mice was examined by transcribing chromatin of isolated nuclei with T7 RNA polymerase. A 95-bp immunoglobulin mu enhancer core element was necessary and sufficient to confer accessibility upon the T7 promoter independent of its chromosomal position. This enhancer-dependent factor access could be uncoupled from an active transcriptional state of the transgene and was not accompanied by the formation of pronounced DNase I hypersensitive sites. Additional mu enhancer sequences comprising previously identified matrix attachment regions and a cryptic promoter were required to induce DNase I hypersensitivity. Together, these data provide evidence that the 95-bp mu enhancer core can establish localized factor access in nuclear chromatin independent of detectable transcription by endogenous polymerases and suggest that multiple steps are involved in the alteration of chromatin structure.