Physics-Informed Explainable Continual Learning on Graphs.

Temporal graph learning has attracted great attention with its ability to deal with dynamic graphs. Although current methods are reasonably accurate, most of them are unexplainable due to their black-box nature. It remains a challenge to explain how temporal graph learning models adapt to information evolution. Furthermore, with the increasing application of artificial intelligence in various scientific domains, such as chemistry and biomedicine, the importance of delivering not only precise outcomes but also offering explanations regarding the learning models becomes paramount. This transparency aids users in comprehending the decision-making procedures and instills greater confidence in the generated models. To address this issue, this article proposes a novel physics-informed explainable continual learning (PiECL), focusing on temporal graphs. Our proposed method utilizes physical and mathematical algorithms to quantify the disturbance of new data to previous knowledge for obtaining changed information over time. As the proposed model is based on theories in physics, it can provide a transparent underlying mechanism for information evolution detection, thus enhancing explainability. The experimental results on three real-world datasets demonstrate that PiECL can explain the learning process, and the generated model outperforms other state-of-the-art methods. PiECL shows tremendous potential for explaining temporal graph learning in various scientific contexts.

The predictive accuracy of Barrett toric calculator using measured posterior corneal astigmatism derived from swept source-OCT and Scheimpflug camera.

PURPOSE: To compare the performance of Barrett toric calculator incorporated with measured posterior corneal astigmatism (PCA) derived from IOL Master 700 and Pentacam HR versus predicted PCA. METHODS: The predicted residual astigmatism using Barrett toric IOL calculator with predicted PCA, measured PCA from IOL Master 700 and measured PCA from Pentacam were calculated with the preoperative keratometry and intended IOL axis with modification. The vector analysis was performed to calculate the mean absolute prediction error (MAE), the centroid of the prediction error and the percentage of eyes with a prediction error within ±0.50 D, ±0.75 D, and ±1.00 D. RESULTS: In 57 eyes of 57 patients with mean age of 70.42 ± 10.75 years, the MAE among the three calculation methods were 0.59 ± 0.38 D (Predicted PCA), 0.60 ± 0.38 D (Measured PCA from IOL Master 700) and 0.60 ± 0.36 D (Measured PCA from Pentacam) with no significant difference, either in the whole sample, the WTR eyes and the ATR eyes (F = 0.078, 0.306 and 0.083, p = 0.925, 0.739 and 0.920, respectively). Measured PCA obtained from IOL Master 700 resulted in one level reduction (from Tn to Tn-1) in 49.12% eyes in cylindrical model selection, while measured PCA obtained from Pentacam resulted in one level reduction of toric model selection in 18.18% eyes. CONCLUSION: The present study suggested that the incorporation of measured PCA values derived from IOL Master 700 and Pentacam produce comparable clinical outcome with the predicted PCA mode in Barrett toric calculator.

The impact of posterior corneal astigmatism on the surgical planning of toric multifocal intraocular lens implantation.

Purpose: To investigate the influence of posterior corneal astigmatism on the prediction accuracy of toric multifocal intraocular lens (IOL) calculation. Methods: The keratometric astigmatism measured by Lenstar LS 900 (KCAL), keratometric astigmatism (KCAP) and total corneal astigmatism (TCA) measured by Scheimpflug camera (Pentacam HR) were documented and analyzed accordingly. Three deduction models using different parameters were compared. Model 1: KCAL â€‹+ â€‹keratometric corneal surgically induced astigmatism (KCSIA, 0.30 D @ 50°); Model 2: KCAP â€‹+ â€‹KCSIA); Model 3: TCA â€‹+ â€‹total CSIA (TCSIA, 0.23 D @ 50°). The prediction errors of each model as the difference vector between the actual and the intended residual astigmatism were compared. Results: Seventy-six eyes implanted with toric multifocal IOLs were included in this study. The vector differences of the actual KCSIA and TCSIA were statistically significant in the total sample and against-the-rule (ATR) subgroup (both P â€‹< â€‹0.05). Model 1 deduced the smallest mean values of prediction error, while that of Model 3 were smaller than that of Model 2, both in the total sample and the ATR subgroups (all P â€‹< â€‹0.05). Meanwhile, in the total sample and ATR subgroups, the centroid vector magnitudes of Model 3 were smaller than that of Model 1 (0.31 â€‹± â€‹0.76 D and 0.39 â€‹± â€‹0.76 D). Conclusions: The calculation of toric multifocal IOL should be individualized especially in the ATR eyes for the impact of PCA on the estimation of the preoperative corneal astigmatism and the CSIA.

Plasmin-Induced Lens Epithelial Cells Detachment for the Reduction of Posterior Capsular Opacification.

Purpose: We sought to evaluate the efficacy and safety of plasmin injection in the capsular bag during the cataract operation for the prevention of posterior capsule opacification. Methods: Thirty-seven anterior capsular flaps taken from phacoemulsification surgery were immersed in either 1 µg/mL plasmin (plasmin group, n = 27) or phosphate-buffered saline (control group, n = 10) for 2 minutes and photographed after fixation and nuclear staining to compare the numbers of residual lens epithelial cells. In the animal experiments, the plasmin solution was injected into the capsular bag and remained for 5 minutes during hydrodissection or after lens extraction. The degree of posterior capsular opacity of the rabbits at 2 months were photographed by slit lamp biomicroscopy. In HLE-B3 cell culture, the cell detachment rate, proliferation, and apoptosis after the plasmin digestion were analyzed. Results: The residual lens epithelial cell numbers on the capsule after plasmin treatment were 168 ± 190.7/mm2 in the 1 µg/mL plasmin group, which was significantly lower than that of the control (1012 ± 798.8/mm2; P < 0.0001). In a rabbit model, the treatment of plasmin resulted in a significantly clearer posterior capsule compared with that of the control group at 2 months postoperatively. Conclusions: This study suggested that plasmin injection can induce effective lens epithelial cell detachment, which could be a promising adjunctive treatment to further improve the success rate in posterior capsule opacification prevention. Translational Relevance: Plasmin injection for lens epithelial cell detachment could significantly decrease the number of residual lens epithelial cells. This approach could be a promising treatment incorporating the current treatment approach to further improve the success rate in posterior capsule opacification prevention.

miR-638 suppresses proliferation by negatively regulating high mobility group A1 in ovarian cancer cells.

Ovarian cancer is one of the most common gynecological diseases with high mortality rates. Previous studies have shown that microRNA (miR)-638 is associated with tumorigenesis. The present study aimed to assess the role and underlying mechanisms of miR-638 in ovarian cancer. miR-638 expression was detected in ovarian cancer tissues and miR-638 was overexpressed or knocked down in ovarian cancer OVCAR-3 and Caov-3 cells. The clinical results revealed that miR-638 expression was downregulated in ovarian cancer tissues compared with in adjacent normal tissues. miR-638 expression was also found to be relatively low in OVCAR-3 cells whilst being relatively high in Caov-3 cells among the five ovarian cancer cell lines tested. miR-638 overexpression inhibited cell viability, arrested the cell cycle at the G1 phase and promoted apoptosis in OVCAR-3 cells. By contrast, miR-638 knockdown increased Caov-3 cell viability, facilitated cell cycle progression and inhibited apoptosis. miR-638 reduced the expression of high mobility group A1 (HMGA1) by directly targeting its 3' untranslated region. HMGA1 overexpression reversed the inhibition of proliferation induced by miR-638 overexpression in OVCAR-3 cells. These results suggest that miR-638 may serve to be a suppressor of ovarian cancer by regulating HMGA1, which may provide a potential therapeutic target for ovarian cancer.

Educational Anomaly Analytics: Features, Methods, and Challenges.

Anomalies in education affect the personal careers of students and universities' retention rates. Understanding the laws behind educational anomalies promotes the development of individual students and improves the overall quality of education. However, the inaccessibility of educational data hinders the development of the field. Previous research in this field used questionnaires, which are time- and cost-consuming and hardly applicable to large-scale student cohorts. With the popularity of educational management systems and the rise of online education during the prevalence of COVID-19, a large amount of educational data is available online and offline, providing an unprecedented opportunity to explore educational anomalies from a data-driven perspective. As an emerging field, educational anomaly analytics rapidly attracts scholars from a variety of fields, including education, psychology, sociology, and computer science. This paper intends to provide a comprehensive review of data-driven analytics of educational anomalies from a methodological standpoint. We focus on the following five types of research that received the most attention: course failure prediction, dropout prediction, mental health problems detection, prediction of difficulty in graduation, and prediction of difficulty in employment. Then, we discuss the challenges of current related research. This study aims to provide references for educational policymaking while promoting the development of educational anomaly analytics as a growing field.

Source identification of antibiotic resistance genes in a peri-urban river using novel crAssphage marker genes and metagenomic signatures.

Antimicrobial resistance is a growing public health concern, and environment is regarded as an important reservoir and dissemination route for antibiotic resistance genes (ARGs). To prevent and control ARG pollution, it is essential to correctly disentangle source-sink relationship of ARGs in the environment. However, accurately apportioning sources of ARGs is still a big challenge due to the complex interaction of multiple sources and contaminants in the environment with changing dynamics. In this study, we addressed this problem and focused on identifying the potential sources of ARGs in a peri-urban river by jointly utilizing two novel microbial source tracking methods. To attain the objective, sediment/water samples were collected from the peri-urban river and four ARG-associated ecotypes including effluents of sewage treatment plants (STPs), STP influent, chicken manures and pig manures. The high-throughput profilings of ARGs and microbial taxa in the river sediments and the four ecotypes were comprehensively characterized in combination of shotgun sequencing and metagenomic assembly analysis. CrAssphage, a recently-discovered DNA bacteriophage, was employed to track the impact of human fecal pollution on ARGs in the river sediments. Further, SourceTracker, a machine-learning classification tool, was used for quantifying the contributions of potential sources to ARGs in the river sediments based on the metagenomic signatures of ARGs and microbial taxa. In total, 888 ARG subtypes belonging to 29 ARG types were detected across all samples, including mcr-1 and a range of carbapenemases types. Statistical analyses suggested different ecotypes generally had distinct profiles of both ARGs and microbial taxa, while the ARG compositions were significantly correlated with the microbial community. Source tracking with crAssphage showed the presence of ARGs in the river sediments might be largely impacted by the extent of human fecal pollution, which was also confirmed by the analyses of SourceTracker that the discharge from STPs was the largest contributor of ARGs (81.6-92.1%) and microbes (49.3-68.1%) in the river sediments. Results of the study can help us to better understand the characterization of ARGs in the peri-urban ecosystem and to design effective prevention and control strategies for reducing ARG dissemination.

Characterization and source-tracking of antibiotic resistomes in the sediments of a peri-urban river.

The peri-urban rivers are one of the critical interfaces between urban-rural symbiotic ecosystems and appear to be a reservoir of antibiotic resistance genes (ARGs) in the environment. To prevent the transmission risks of ARGs between peri-urban river and human, it is essential to explore the prevalence and source of ARGs in the environment for designing potential mitigation strategies. In this study, we focused on the characterization and source-tracking of ARGs in the sediments of a typical peri-urban river in Beijing, Chaobai River. Twenty-seven ARGs frequently reported in the environment, and two integrons (intI1 and intI2) were detected using high-throughput quantitative PCR. The profile of bacterial community was determined by performing 16S rRNA gene sequencing. Meanwhile, crAssphage, a novel recently-discovered DNA bacteriophage, was employed for tracking the contribution of human fecal pollution to the prevalence of ARGs. Results showed that the targeted ARGs were detected widely in the sediments of Chaobai River. Relatively, the abundances of ARGs in downstream were higher than those in the upstream, likely suggesting a gradient impact of anthropogenic activities along the river. Remarkably, the int1 gene was correlated significantly with most of the ARGs and might be the key factor influencing the shaping of ARGs in the river sediments. However, no significant correlations were observed between the ARGs and selective pressure factors, including antibiotics and metals. Of the identified 1039 genera, Escherichia-Shigella, Bacteroides, Arcobacter, Dechloromonas and Pseudomonas were the top most abundant organisms. Microbial source tracking based on the crAssphage annotation suggested that human sewage might be one of the potential sources of resistance bacteria in the river sediments. The study can advance our knowledge about ARGs in the peri-urban river and provides a management reference for ARG pollution control.

Characterization of antibiotic resistance genes in the sediments of an urban river revealed by comparative metagenomics analysis.

The over-use of antibiotics causes growing concerns about human health risks induced by increasing rates of antimicrobial resistance. Riverine systems are considered generally as a natural reservoir of antibiotic resistance genes (ARGs). In this study, several methods including high-throughput sequencing-based metagenomics approach, statistical analysis and network analysis were applied jointly to characterize the wide-spectrum profile of ARGs in the sediments of an urban river in Beijing. Furthermore, contribution of human activities for the presence of ARGs was identified through comparative studies on the metagenomic profiling of ARGs between the river sediments and pristine niches (remote Antarctic soils and deep sea sediments). In total, 442 ARG subtypes belonging to 22 ARG types were detected in the human-impacted river sediments with an abundance range of 1.1 × 10-1-8.1 × 10-1 copy of ARG per copy of 16S-rRNA gene. The most abundant and diverse ARGs were commonly associated with antibiotics that have been extensively used in that area, likely indicating the spread of ARGs in river environments because of the selective pressure resulting from antibiotic use. As a whole, anthropogenic activities were the dominant contributor of major ARG types, for example, occupying 100% for sulfonamide-ARGs, 97% for beta-lactam-ARGs, 94% for aminoglycoside-ARGs and 64% for tetracycline-ARGs. This study provides insights into the role of human activities in accelerating the dissemination and proliferation of ARGs in urban river environment and draws attention to controlling the use and discharge of antibiotics for protection of public health.

Skill ranking of researchers via hypergraph.

Researchers use various skills in their works, such as writing, data analysis and experiments design. These research skills have greatly influenced the quality of their research outputs, as well as their scientific impact. Although many indicators have been proposed to quantify the impact of researchers, studies of evaluating their scientific research skills are very rare. In this paper, we analyze the factors affecting researchers' skill ranking and propose a new model based on hypergraph theory to evaluate the scientific research skills. To validate our skill ranking model, we perform experiments on the PLOS ONE dataset and compare the rank of researchers' skills with their papers' citation counts and h-index. Finally, we analyze the patterns about how researchers' skill ranking increased over time. Our studies also show the change patterns of researchers between different skills.

A metagenomic analysis framework for characterization of antibiotic resistomes in river environment: Application to an urban river in Beijing.

River is considered generally as a natural reservoir of antibiotic resistance genes (ARGs) in environments. For the prevention and control of ARG risks, it is critical to comprehensively characterize the antibiotic resistomes and their associations in riverine systems. In this study, we proposed a metagenomic framework for identifying antibiotic resistomes in river sediments from multiple categories, including ARG potential, ARG hosts, pathogenicity potential, co-selection potential and gene transfer potential, and applied it to understand the presence, hosts, and co-occurrence of ARGs in the sediments of an urban river in Beijing. Results showed that a total of 203 ARG subtypes belonging to 21 ARG types were detected in the river sediments with an abundance range of 107.7-1004.1×/Gb, dominated by multidrug, macrolide-lincosamide-streptogramin, bacitracin, quinolone and sulfonamide resistance genes. Host-tracking analysis identified Dechloromonas, Pseudoxanthomonas, Arenimonas, Lysobacter and Pseudomonas as the major hosts of ARGs. A number of ARG-carrying contigs (ACCs) were annotated as fragments of pathogenic bacteria and carried multiple multidrug-ARGs. In addition, various biocide/metal resistance genes (B/MRGs) and mobile genetic elements (MGEs), including prophages, plasmids, integrons and transposons, were detected in the river sediments. More importantly, the co-occurrence analysis via ACCs showed a strong association of ARGs with B/MRGs and MGEs, indicating high potential of co-selection and active horizontal transmission for ARGs in the river environment, likely driven by the frequent impact of anthropogenic activities in that area.

L-3-n-butylphthalide attenuates cognitive deficits in db/db diabetic mice.

Numerous epidemiological studies have shown that diabetes mellitus (DM) is associated with dementia and cognition decline. However, there is currently no effective treatment for diabetes-induced cognitive dysfunction. The neuroprotective effect of L-3-n-butylphthalide (L-NBP) has been demonstrated in vascular dementia animal models. The purpose of this study was to determine whether L-NBP can ameliorate cognitive deficits in db/db mice, a model of obesity and type 2 diabetes. The mice were administered with vehicle or L-NBP (120 mg/kg) by gavage daily for 6 weeks. Then, Morris water maze tasks were performed, and hippocampal LTP was recorded in vivo. Next, the synaptic structure of the CA1 hippocampus region was investigated via electron microscopy. Finally, the expression levels of MDA, SOD, 8-OHdG, and NADPH oxidase subunits gp91 and p67, as well as the expression of NF-κB p65, TNF-α, IL-1ß and caspase-3 were measured by Western blot, RT-PCR and ELISA. Treatment with L-NBP significantly attenuated the learning and memory deficits in db/db mice. Concomitantly, L-NBP also increased hippocampus synaptic plasticity, characterized by an enhanced in vivo LTP, and suppressed oxidative stress, as indicated by increased SOD activity and decreased MDA, 8-OHdG, and NADPH oxidase subunits p67 and gp91. L-NBP also significantly decreased NF-κB p65, TNF-α, IL-1ßand caspase-3 levels in the hippocampus. L-NBP significantly ameliorated cognitive decline in type 2 diabetic mice, and this effect was accompanied by an improvement in hippocampal plasticity and an amelioration of oxidative stress, inflammation and apoptosis cascades. Thus, L-NBP may be a promising therapeutic agent against DM-mediated cognitive dysfunction.

Quantifying the impact of scholarly papers based on higher-order weighted citations.

Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical.

Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact.

Evaluating the impact of a scholarly article is of great significance and has attracted great attentions. Although citation-based evaluation approaches have been widely used, these approaches face limitations e.g. in identifying anomalous citations patterns. This negligence would inevitably cause unfairness and inaccuracy to the article impact evaluation. In this study, in order to discover the anomalous citations and ensure the fairness and accuracy of research outcome evaluation, we investigate the citation relationships between articles using the following factors: collaboration times, the time span of collaboration, citing times and the time span of citing to weaken the relationship of Conflict of Interest (COI) in the citation network. Meanwhile, we study a special kind of COI, namely suspected COI relationship. Based on the COI relationship, we further bring forward the COIRank algorithm, an innovative scheme for accurately assessing the impact of an article. Our method distinguishes the citation strength, and utilizes PageRank and HITS algorithms to rank scholarly articles comprehensively. The experiments are conducted on the American Physical Society (APS) dataset. We find that about 80.88% articles contain contributed citations by co-authors in 26,366 articles and 75.55% articles among these articles are cited by the authors belonging to the same affiliation, indicating COI and suspected COI should not be ignored for evaluating impact of scientific papers objectively. Moreover, our experimental results demonstrate COIRank algorithm significantly outperforms the state-of-art solutions. The validity of our approach is verified by using the probability of Recommendation Intensity.

Influence analysis of Github repositories.

With the support of cloud computing techniques, social coding platforms have changed the style of software development. Github is now the most popular social coding platform and project hosting service. Software developers of various levels keep entering Github, and use Github to save their public and private software projects. The large amounts of software developers and software repositories on Github are posing new challenges to the world of software engineering. This paper tries to tackle one of the important problems: analyzing the importance and influence of Github repositories. We proposed a HITS based influence analysis on graphs that represent the star relationship between Github users and repositories. A weighted version of HITS is applied to the overall star graph, and generates a different set of top influential repositories other than the results from standard version of HITS algorithm. We also conduct the influential analysis on per-month star graph, and study the monthly influence ranking of top repositories.

Evaluating sustainability of cropland use in Yuanzhou county of the Loess plateau, China using an emergy-based ecological footprint.

Evaluating the sustainability of cropland use is essential for guaranteeing a secure food supply and accomplishing agriculture sustainable development. This study was conducted in the ecologically vulnerable Loess Plateau region of China to evaluate the sustainability of cropland use based on an ecological footprint model that integrates emergy analysis. One modified method proposed in 2005 is known as the emergetic ecological footprint (EEF). We enhanced the method by accounting for both the surface soil energy in the carrying capacity calculation and the net topsoil loss for human consumption in the EF calculation. This paper evaluates whether the cropland of the study area was overloaded or sustainably managed during the period from 1981 to 2009. Toward this end, the final results obtained from EEF were compared to conventional EF and previous methods. The results showed that the cropland of Yuanzhou County has not been used sustainably since 1983, and the conventional EF analysis provided similar results. In contrast, a deficit did not appear during this time period when previous calculation methods of others were used. Additionally, the ecological sustainable index (ESI) from three models indicated that the recently used cropland system is unlikely to be unsustainable.

Preparation of a novel porous poly (trimethylol propane triacrylate-co-ethylene dimethacrylate) monolithic column for highly efficient HPLC separations of small molecules.

A novel poly (trimethylol propane triacrylate-co-ethylene dimethacrylate) [poly (TMPTA-co-EDMA)] monolith was prepared by in situ free-radical polymerization in a 50 mm × 4.6mm i.d. stainless steel column and was investigated for high performance liquid chromatography (HPLC). The porous structure of monolith was optimized by changing the conditions of polymerization. The chemical group of the monolithic column was confirmed by a Fourier transform infrared spectroscopy (FT-IR) method and the morphology of column structure was characterized by scanning electron microscopy (SEM). The mechanical strength and permeability were also studied. Finally, a series of low-molecular-weight organic compounds were utilized to evaluate the retention behaviors of the monolithic column. The result demonstrated that the prepared column exhibited an RP-chromatographic behavior and good separation performance. The method reproducibility was obtained by evaluating the run-to-run and column-to-column with relative standard deviations (RSDs) less than 0.7% (n=6) and 2.9% (n=6), respectively, which indicated that prepared monolithic columns had good reproducibility and stability.

High-performance liquid chromatography separation of small molecules on a porous poly (trimethylol propane triacrylate-co-N-isopropylacrylamide-co-ethylene dimethacrylate) monolithic column.

A porous monolith was prepared by in situ free-radical polymerization using N-isopropylacrylamide (NIPAAm) and trimethylol propane triacrylate (TMPTA) as functional monomers, ethylene dimethacrylate (EDMA) as crosslinking agent. The chemical group of the monolith was assayed by a Fourier transform infrared spectroscopy (FT-IR) method and the morphology of optimized monolithic column was characterized by scanning electron microscopy (SEM). The mechanical strength and permeability have been studied in detail as well. The run-to-run and column-to-column reproducibility of the retention times were less than 0.9% and 3.0%, respectively. Furthermore, the influence of temperature and mobile phase composition on the separation of aromatic compounds was investigated. The results indicated that poly (trimethylol propane triacrylate-co-N-isopropylacrylamide-co-ethylenedimethacrylate) (TMPTA-co-NIPAAm-co-EDMA) monolithic column not only had high porosity and strong rigidity, but also was a promising tool for analyzing small molecule compounds with a short analysis time by controlling the column temperature.

Rational optimization of a bispecific ligand trap targeting EGF receptor family ligands.

The human epidermal growth factor (EGF) receptor (HER) family members cooperate in malignancy. Of this family, HER2 does not bind growth factors and HER3 does not encode an active tyrosine kinase. This diversity creates difficulty in creating pan-specific therapeutic HER family inhibitors. We have identified single amino acid changes in epidermal growth factor receptor (EGFR) and HER3 which create high affinity sequestration of the cognate ligands, and may be used as receptor decoys to downregulate aberrant HER family activity. In silico modeling and high throughput mutagenesis were utilized to identify receptor mutants with very high ligand binding activity. A single mutation (T15S; EGFR subdomain I) enhanced affinity for EGF (two-fold), TGF-alpha (twenty-six-fold), and heparin-binding (HB)-EGF (six-fold). This indicates that T15 is an important, previously undescribed, negative regulatory amino acid for EGFR ligand binding. Another mutation (Y246A; HER 3 subdomain II) enhanced neuregulin (NRG)1-beta binding eight-fold, probably by interfering with subdomain II-IV interactions. Further work revealed that the HER3 subunit of an EGFR:HER3 heterodimer suppresses EGFR ligand binding. Optimization required reversing this suppression by mutation of the EGFR tether domain (G564A; subdomain IV). This mutation resulted in enhanced ligand binding (EGF, ten-fold; TGF-alpha, thirty-four-fold; HB-EGF, seventeen-fold; NRG1-beta, thirty-one-fold). This increased ligand binding was reflected in improved inhibition of in vitro tumor cell proliferation and tumor suppression in a human non-small cell lung cancer xenograft model. In conclusion, amino acid substitutions were identified in the EGFR and HER3 ECDs that enhance ligand affinity, potentially enabling a pan-specific therapeutic approach for downregulating the HER family in cancer.

Functional UDP-xylose transport across the endoplasmic reticulum/Golgi membrane in a Chinese hamster ovary cell mutant defective in UDP-xylose Synthase.

In mammals, xylose is found as the first sugar residue of the tetrasaccharide GlcAbeta1-3Galbeta1-3Galbeta1-4Xylbeta1-O-Ser, initiating the formation of the glycosaminoglycans heparin/heparan sulfate and chondroitin/dermatan sulfate. It is also found in the trisaccharide Xylalpha1-3Xylalpha1-3Glcbeta1-O-Ser on epidermal growth factor repeats of proteins, such as Notch. UDP-xylose synthase (UXS), which catalyzes the formation of the UDP-xylose substrate for the different xylosyltransferases through decarboxylation of UDP-glucuronic acid, resides in the endoplasmic reticulum and/or Golgi lumen. Since xylosylation takes place in these organelles, no obvious requirement exists for membrane transport of UDP-xylose. However, UDP-xylose transport across isolated Golgi membranes has been documented, and we recently succeeded with the cloning of a human UDP-xylose transporter (SLC25B4). Here we provide new evidence for a functional role of UDP-xylose transport by characterization of a new Chinese hamster ovary cell mutant, designated pgsI-208, that lacks UXS activity. The mutant fails to initiate glycosaminoglycan synthesis and is not capable of xylosylating Notch. Complementation was achieved by expression of a cytoplasmic variant of UXS, which proves the existence of a functional Golgi UDP-xylose transporter. A approximately 200 fold increase of UDP-glucuronic acid occurred in pgsI-208 cells, demonstrating a lack of UDP-xylose-mediated control of the cytoplasmically localized UDP-glucose dehydrogenase in the mutant. The data presented in this study suggest the bidirectional transport of UDP-xylose across endoplasmic reticulum/Golgi membranes and its role in controlling homeostasis of UDP-glucuronic acid and UDP-xylose production.