Analysis of the Human Kinome and Phosphatome by Mass Cytometry Reveals Overexpression-Induced Effects on Cancer-Related Signaling.

Kinase and phosphatase overexpression drives tumorigenesis and drug resistance. We previously developed a mass-cytometry-based single-cell proteomics approach that enables quantitative assessment of overexpression effects on cell signaling. Here, we applied this approach in a human kinome- and phosphatome-wide study to assess how 649 individually overexpressed proteins modulated cancer-related signaling in HEK293T cells in an abundance-dependent manner. Based on these data, we expanded the functional classification of human kinases and phosphatases and showed that the overexpression effects include non-catalytic roles. We detected 208 previously unreported signaling relationships. The signaling dynamics analysis indicated that the overexpression of ERK-specific phosphatases sustains proliferative signaling. This suggests a phosphatase-driven mechanism of cancer progression. Moreover, our analysis revealed a drug-resistant mechanism through which overexpression of tyrosine kinases, including SRC, FES, YES1, and BLK, induced MEK-independent ERK activation in melanoma A375 cells. These proteins could predict drug sensitivity to BRAF-MEK concurrent inhibition in cells carrying BRAF mutations.

Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.

High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an extensible framework with two new deep learning models (i.e., FunTrans and FunRep), structured databases, and supporting resources for achieving highly accurate (Accuracy > 0.99, F1-score > 0.97) and fine-grained classification of antibiotic resistance genes (ARGs) and virulence factor genes. Using an experimentally confirmed dataset of ARGs comprising remote homologous sequences as the test set, our framework achieves by-far-the-best performance in the discovery of new ARGs from human gut (F1-score: 0.6948), wastewater (0.6072), and soil (0.5445) microbiomes, beating the state-of-the-art bioinformatics tools and sequence alignment-based (F1-score: 0.0556-0.5065) and domain-based (F1-score: 0.2630-0.5224) annotation approaches. Furthermore, our framework is implemented as a lightweight, privacy-preserving, and plug-and-play neural network module, facilitating its versatility and accessibility to developers and users worldwide. We anticipate widespread utilization of FunGeneTyper (https://github.com/emblab-westlake/FunGeneTyper) for precise classification of protein-coding gene functions and the discovery of numerous valuable enzymes. This advancement will have a significant impact on various fields, including microbiome research, biotechnology, metagenomics, and bioinformatics.

Tandem mass tag (TMT)-based quantitative proteomics analysis reveals the different responses of contrasting alfalfa varieties to drought stress.

BACKGROUND: Drought stress restricts the growth, distribution and productivity of alfalfa (Medicago sativa L.). In order to study the response differences of alfalfa cultivars to drought stress, we previously carried out physiological and molecular comparative analysis on two alfalfa varieties with contrasting drought resistance (relatively drought-tolerant Longdong and drought-sensitive Algonquin). However, the differences in proteomic factors of the two varieties in response to drought stress still need to be further studied. Therefore, TMT-based quantitative proteomic analysis was performed using leaf tissues of the two alfalfa cultivars to identify and uncover differentially abundant proteins (DAPs). RESULTS: In total, 677 DAPs were identified in Algonquin and 277 in Longdong under drought stress. Subsequently, we conducted various bioinformatics analysis on these DAPs, including subcellular location, functional classification and biological pathway enrichment. The first two main COG functional categories of DAPs in both alfalfa varieties after drought stress were 'Translation, ribosomal structure and biogenesis' and 'Posttranslational modification, protein turnover, chaperones'. According to KEGG database, the DAPs of the two alfalfa cultivars after drought treatment were differentially enriched in different biological pathways. The DAPs from Algonquin were enriched in 'photosynthesis' and 'ribosome'. The pathways of 'linoleic acid metabolism', 'protein processing in endoplasmic reticulum' and 'RNA transport' in Longdong were significantly enriched. Finally, we found significant differences in DAP enrichment and expression patterns between Longdong and Algonquin in glycolysis/glycogenesis, TCA cycle, photosynthesis, protein biosynthesis, flavonoid and isoflavonoid biosynthesis, and plant-pathogen interaction pathway after drought treatment. CONCLUSIONS: The differences of DAPs involved in various metabolic pathways may explain the differences in the resistance of the two varieties to drought stress. These DAPs can be used as candidate proteins for molecular breeding of alfalfa to cultivate new germplasm with more drought tolerance to adapt to unfavorable environments.

Interpretable discriminant analysis for functional data supported on random nonlinear domains with an application to Alzheimer's disease.

We introduce a novel framework for the classification of functional data supported on nonlinear, and possibly random, manifold domains. The motivating application is the identification of subjects with Alzheimer's disease from their cortical surface geometry and associated cortical thickness map. The proposed model is based upon a reformulation of the classification problem as a regularized multivariate functional linear regression model. This allows us to adopt a direct approach to the estimation of the most discriminant direction while controlling for its complexity with appropriate differential regularization. Our approach does not require prior estimation of the covariance structure of the functional predictors, which is computationally prohibitive in our application setting. We provide a theoretical analysis of the out-of-sample prediction error of the proposed model and explore the finite sample performance in a simulation setting. We apply the proposed method to a pooled dataset from Alzheimer's Disease Neuroimaging Initiative and Parkinson's Progression Markers Initiative. Through this application, we identify discriminant directions that capture both cortical geometric and thickness predictive features of Alzheimer's disease that are consistent with the existing neuroscience literature.

Restriction of C1-inhibitor activity in hereditary angioedema by dominant-negative effects of disease-associated SERPING1 gene variants.

BACKGROUND: Patients with hereditary angioedema experience recurrent, sometimes life-threatening, attacks of edema. It is a rare genetic disorder characterized by genetic and clinical heterogenicity. Most cases are caused by genetic variants in the SERPING1 gene leading to plasma deficiency of the encoded protein C1 inhibitor (C1INH). More than 500 different hereditary angioedema-causing variants have been identified in the SERPING1 gene, but the disease mechanisms by which they result in pathologically low C1INH plasma levels remain largely unknown. OBJECTIVES: The aim was to describe trans-inhibitory effects of full-length or near full-length C1INH encoded by 28 disease-associated SERPING1 variants. METHODS: HeLa cells were transfected with expression constructs encoding the studied SERPING1 variants. Extensive and comparative studies of C1INH expression, secretion, functionality, and intracellular localization were carried out. RESULTS: Our findings characterized functional properties of a subset of SERPING1 variants allowing the examined variants to be subdivided into 5 different clusters, each containing variants sharing specific molecular characteristics. For all variants except 2, we found that coexpression of mutant and normal C1INH negatively affected the overall capacity to target proteases. Strikingly, for a subset of variants, intracellular formation of C1INH foci was detectable only in heterozygous configurations enabling simultaneous expression of normal and mutant C1INH. CONCLUSIONS: We provide a functional classification of SERPING1 gene variants suggesting that different SERPING1 variants drive the pathogenicity through different and in some cases overlapping molecular disease mechanisms. For a subset of gene variants, our data define some types of hereditary angioedema with C1INH deficiency as serpinopathies driven by dominant-negative disease mechanisms.

Differences in nonlinearities determine retinal cell types.

Classifying neurons in different types is still an open challenge. In the retina, recent works have taken advantage of the ability to record from a large number of cells to classify ganglion cells into different types based on functional information. Although the first attempts in this direction used the receptive field properties of each cell to classify them, more recent approaches have proposed to cluster ganglion cells directly based on their response to stimuli. These two approaches have not been compared directly. Here, we recorded the responses of a large number of ganglion cells and compared two methods for classifying them into functional groups, one based on the receptive field properties, and the other one using directly their responses to stimuli with various temporal frequencies. We show that the response-based approach allows separation of more types than the receptive field-based method, leading to a better classification. This better granularity is due to the fact that the response-based method takes into account not only the linear part of ganglion cell function but also some of the nonlinearities. A careful characterization of nonlinear processing is thus key to allowing functional classification of sensory neurons.NEW & NOTEWORTHY In the retina, ganglion cells can be classified based on their response to visual stimuli. Although some methods are based on the modeling of receptive fields, others rely on responses to characteristic stimuli. We compared these two classes of methods and show that the latter provides a higher discrimination performance. We also show that this gain arises from the ability to account for the nonlinear behavior of neurons.

Multiple Profile Models Extract Features from Protein Sequence Data and Resolve Functional Diversity of Very Different Protein Families.

Functional classification of proteins from sequences alone has become a critical bottleneck in understanding the myriad of protein sequences that accumulate in our databases. The great diversity of homologous sequences hides, in many cases, a variety of functional activities that cannot be anticipated. Their identification appears critical for a fundamental understanding of the evolution of living organisms and for biotechnological applications. ProfileView is a sequence-based computational method, designed to functionally classify sets of homologous sequences. It relies on two main ideas: the use of multiple profile models whose construction explores evolutionary information in available databases, and a novel definition of a representation space in which to analyze sequences with multiple profile models combined together. ProfileView classifies protein families by enriching known functional groups with new sequences and discovering new groups and subgroups. We validate ProfileView on seven classes of widespread proteins involved in the interaction with nucleic acids, amino acids and small molecules, and in a large variety of functions and enzymatic reactions. ProfileView agrees with the large set of functional data collected for these proteins from the literature regarding the organization into functional subgroups and residues that characterize the functions. In addition, ProfileView resolves undefined functional classifications and extracts the molecular determinants underlying protein functional diversity, showing its potential to select sequences towards accurate experimental design and discovery of novel biological functions. On protein families with complex domain architecture, ProfileView functional classification reconciles domain combinations, unlike phylogenetic reconstruction. ProfileView proves to outperform the functional classification approach PANTHER, the two k-mer-based methods CUPP and eCAMI and a neural network approach based on Restricted Boltzmann Machines. It overcomes time complexity limitations of the latter.

Correlation of Serum Laminin Levels with Cardiac Function and In-Hospital Prognosis in Patients with Atrial Fibrillation.

We aimed to investigate the correlation between serum laminin (LN) levels and cardiac function in patients with atrial fibrillation (AF) and its predictive value for in-hospital prognosis. This study included 295 patients with AF who were admitted to the Second Affiliated Hospital of Nantong University from January 2019 to January 2021. The patients were divided into three groups according to the New York Heart Association (NYHA) functional classification (I-II, III, and IV); the LN levels increased with increasing NYHA class (P < 0.05). Spearman's correlation analysis revealed a positive correlation between LN and NT-proBNP (r = 0.527, P < 0.001). Of the patients, 36 had in-hospital major adverse cardiac events (MACEs), of whom 30 had acute heart failure, 5 had malignant arrhythmias, and one had stroke. The area under the ROC curve for predicting the in-hospital MACEs by LN was 0.815 (95% CI: 0.740-0.890, P < 0.001). Multivariate logistic regression analysis revealed that LN could be an independent predictor of in-hospital MACEs (odds ratio: 1.009, 95% confidence interval: 1.004-1.015, P = 0.001). In conclusion, LN may serve as a potential biomarker to evaluate the severity of cardiac function and predict in-hospital prognosis in AF patients.

The Research Progress of Bioactive Peptides Derived from Traditional Natural Products in China.

Traditional natural products in China have a long history and a vast pharmacological repertoire that has garnered significant attention due to their safety and efficacy in disease prevention and treatment. Among the bioactive components of traditional natural products in China, bioactive peptides (BPs) are specific protein fragments that have beneficial effects on human health. Despite many of the traditional natural products in China ingredients being rich in protein, BPs have not received sufficient attention as a critical factor influencing overall therapeutic efficacy. Therefore, the purpose of this review is to provide a comprehensive summary of the current methodologies for the preparation, isolation, and identification of BPs from traditional natural products in China and to classify the functions of discovered BPs. Insights from this review are expected to facilitate the development of targeted drugs and functional foods derived from traditional natural products in China in the future.

Crystal structure of chloroplast fructose-1,6-bisphosphate aldolase from the green alga Chlamydomonas reinhardtii.

The Calvin-Benson cycle fixes carbon dioxide into organic triosephosphates through the collective action of eleven conserved enzymes. Regeneration of ribulose-1,5-bisphosphate, the substrate of Rubisco-mediated carboxylation, requires two lyase reactions catalyzed by fructose-1,6-bisphosphate aldolase (FBA). While cytoplasmic FBA has been extensively studied in non-photosynthetic organisms, functional and structural details are limited for chloroplast FBA encoded by oxygenic phototrophs. Here we determined the crystal structure of plastidial FBA from the unicellular green alga Chlamydomonas reinhardtii (Cr). We confirm that CrFBA folds as a TIM barrel, describe its catalytic pocket and homo-tetrameric state. Multiple sequence profiling classified the photosynthetic paralogs of FBA in a distinct group from non-photosynthetic paralogs. We mapped the sites of thiol- and phospho-based post-translational modifications known from photosynthetic organisms and predict their effects on enzyme catalysis.

Pooling random forest and functional data analysis for biomedical signals supervised classification: Theory and application to electrocardiogram data.

Scientific progress has contributed to creating many devices to gather vast amounts of biomedical data over time. The goal of these devices is generally to monitor people's health conditions, diagnose, and prevent patients' diseases, for example, to discover cardiovascular disorders or predict epileptic seizures. A common way of investigating these data is classification, but these instruments generate signals often characterized by high dimensionality. Learning from these data is definitely a challenging task due to many issues, for example, the trade-off between complexity and accuracy and the course of dimensionality. This study proposes a supervised classification method based on the joint use of functional data analysis, classification trees, and random forest to deal with massive biomedical data recorded over time. For this purpose, this research suggests different original tools to extract features and train functional classifiers, interpret the classification rules, assess leaves' quality and composition, avoid the classical drawbacks due to the COD, and improve the accuracy of the functional classifiers. Focusing on ECG data as a possible example, the final purpose of this study is to offer an original approach to identify and classify patients at risk using different types of biomedical signals. The results confirm that this line of research is exciting; indeed, the interpretative tools show evidence to be very useful for understanding classification rules. Furthermore, the performance of the proposed functional classifier, in terms of accuracy, is excellent because the latter breaks the previous classification record regarding a well-known ECG dataset.

Using a microprocessor knee (C-Leg) with appropriate foot transitioned individuals with dysvascular transfemoral amputations to higher performance levels: a longitudinal randomized clinical trial.

BACKGROUND: Individuals with transfemoral amputations who are considered to be limited community ambulators are classified as Medicare functional classification (MFCL) level K2. These individuals are usually prescribed a non-microprocessor controlled knee (NMPK) with an appropriate foot for simple walking functions. However, existing research suggests that these individuals can benefit from using a microprocessor controlled knee (MPK) and appropriate foot for their ambulation, but cannot obtain one due to insurance policy restrictions. With a steady increase in older adults with amputations due to vascular conditions, it is critical to evaluate whether advanced prostheses can provide better safety and performance capabilities to maintain and improve quality of life in individuals who are predominantly designated MFCL level K2. To decipher this we conducted a 13 month longitudinal clinical trial to determine the benefits of using a C-Leg and 1M10 foot in individuals at K2 level with transfemoral amputation due to vascular disease. This longitudinal clinical trial incorporated recommendations prescribed by the lower limb prosthesis workgroup to design a study that can add evidence to improve reimbursement policy through clinical outcomes using an MPK in K2 level individuals with transfemoral amputation who were using an NMPK for everyday use. METHODS: Ten individuals (mean age: 63 ± 9 years) with unilateral transfemoral amputation due to vascular conditions designated as MFCL K2 participated in this longitudinal crossover randomized clinical trial. Baseline outcomes were collected with their current prosthesis. Participants were then randomized to one of two groups, either an intervention with the MPK with a standardized 1M10 foot or their predicate NMPK with a standardized 1M10 foot. On completion of the first intervention, participants crossed over to the next group to complete the study. Each intervention lasted for 6 months (3 months of acclimation and 3 months of take-home trial to monitor home use). At the end of each intervention, clinical outcomes and self-reported outcomes were collected to compare with their baseline performance. A generalized linear model ANOVA was used to compare the performance of each intervention with respect to their own baseline. RESULTS: Statistically significant and clinically meaningful improvements were observed in gait performance, safety, and participant-reported measures when using the MPK C-Leg + 1M10 foot. Most participants were able to achieve higher clinical scores in gait speed, balance, self-reported mobility, and fall safety, while using the MPK + 1M10 combination. The improvement in scores were within range of scores achieved by individuals with K3 functional level as reported in previous studies. CONCLUSIONS: Individuals with transfemoral amputation from dysvascular conditions designated MFCL level K2 benefited from using an MPK + appropriate foot. The inference and evidence from this longitudinal clinical trial will add to the knowledgebase related to reimbursement policy-making. Trial registration This study is registered on clinical trials.gov with the study title "Functional outcomes in dysvascular transfemoral amputees" and the associated ClinicalTrials.gov Identifier: NCT01537211. The trial was retroactively registered on February 7, 2012 after the first participant was enrolled.

Seasonal dynamics of phytoplankton community and functional groups in a tropical river.

Functional classification of phytoplankton could be a valuable tool in water quality monitoring in the eutrophic riverine ecosystems. This study is novel from the Bangladeshi perspective. In this study, phytoplankton cell density and diversity were studied with particular reference to the functional groups (FGs) approach during pre-monsoon, monsoon, and post-monsoon at four sampling stations in Karatoya River, Bangladesh. A total of 54 phytoplankton species were recorded under four classes, viz. Chlorophyceae (21 species) Cyanophyceae (16 species), Bacillariophyceae (15 species), and Euglenophyceae (2 species). A significantly higher total cell density of phytoplankton was detected during the pre-monsoon season (24.20 × 103 cells/l), while the lowest in monsoon (9.43 × 103 cells/l). The Shannon-Wiener diversity index varied significantly (F = 16.109, P = 000), with the highest value recorded during the post-monsoon season. Analysis of similarity (ANOSIM) identified significant variations among the three seasons (P < 0.0001, R = 0.9518). The similarity percentage (SIMPER) analysis pinpointed Ulothrix spp. (Melosira granulate and Cymbella spp.) as the most contributory species are causing such a noticeable difference. Fifty-four phytoplankton species recorded during the study period were classified into 20 functional groups, whereas D/J/M/MP/X1 was considered the most abundant FG in the Karatoya River. FGs of the Karatoya River were influenced mainly by the nutrients (PO4-P and NO3-N) enrichments. As a novel investigation on FGs of phytoplankton in Bangladesh, this study recommends additional surveys in other rivers and floodplains to improve our understanding of phytoplankton diversity and functional groups.

Correlation of plasma TSG-6 with cardiac function, myocardial fibrosis, and prognosis in dilated cardiomyopathy patients with heart failure. / 血浆TSG-6æ°´å¹³ä¸Žæ‰©å¼ åž‹å¿ƒè‚Œç— å¿ƒåŠ›è¡°ç«­æ‚£è€ å¿ƒåŠŸèƒ½ã€å¿ƒè‚Œçº¤ç»´åŒ–åŠé¢„åŽçš„ç›¸å ³æ€§.

OBJECTIVES: Tumor necrosis factor α stimulated gene 6 (TSG-6) protein is an inflammation-inducing protein. In recent years, TSG-6 protein has been found to play an anti-inflammatory and anti-fibrosis role in a variety of disease models. The level of TSG-6 protein in circulating blood is considered to be a biological indicator for the evaluation of acute coronary syndrome, severe infection, and other diseases, and it is closely related to the prognosis. The clinical correlation between TSG-6 protein and dilated cardiomyopathy (DCM) patients with heart failure has not been reported. This study aims to investigate the changes of plasma TSG-6 protein levels in cardiomyopathy patients with heart failure and its correlation with cardiac function, myocardial fibrosis, and prognosis. METHODS: Based on the prospective studies, a number of 90 DCM patients with heart failure were selected as a DCM heart failure group from Dec.1, 2019 to Sept.1, 2020. Thirty-nine healthy people were served as a control group. Plasma TSG-6, Collagen Ⅰ, Collagen III, and α-smooth muscle actin (α-SMA) were measured with ELISA test. Echocardiography was used to evaluate the structure and function of the heart. DCM patients with heart failure were followed up for 3 months. The patients were assigned into 2 groups according to whether they had major adverse cardiovascular events (MACE). The general clinical data, plasma TSG-6, Collagen Ⅰ, Collagen III, and α-SMA protein levels were compared between the control group and the DCM heart failure group. At the same time, the correlation between plasma TSG-6 protein level and cardiac function grade, myocardial fibrosis or prognosis of patients in the DCM heart failure group was analyzed. RESULTS: Compared with the control group, the heart rate, TSG-6, Collagen Ⅰ, Collage III, α-SMA, hemoglobin, atrial natriuretic peptide (NT-proBNP), hypersensitive C-reactive protein, aspartate aminotransferase, serum creatinine, lactate dehydrogenase, and left ventricular end diastolic diameter (LVEDD) increased significantly (all P<0.001). High-density lipoprotein, left ventricular short axis shortening rate (LVFS), and left ventricular ejection fraction (LVEF) decreased significantly in the DCM heart failure group (all P<0.001). Plasma levels of TSG-6 were positively correlated with NT-proBNP, Collagen Ⅰ, Collagen III, α-SMA, and LVEDD (all P<0.001), while they were negatively correlated with LVFS and LVEF (all P<0.001). With the increase of NYHA heart function classification, plasma levels of TSG-6, Collagen Ⅰ, Collagen III, and α-SMA increased significantly (all P<0.001). The increases in plasma levels of NT-proBNP and TSG-6 was associated with poor prognosis in DCM patients with heart failure (all P<0.05). The sensitivity and specificity of plasma NT-proBNP for evaluating the prognosis of DCM heart failure were 76.2% and 68.1%, respectively. The sensitivity and specificity of plasma TSG-6 for evaluating the prognosis of DCM heart failure were 95.2% and 66.7%, respectively. The sensitivity and specificity of plasma TSG-6 combined with NT-proBNP for prognostic evaluation of DCM heart failure were 85.7% and 81.2%, respectively. The specificity of plasma TSG-6 combined with NT-proBNP for the prognosis of heart failure was better than that of NT-proBNP or TSG-6 alone (P<0.001). CONCLUSIONS: The plasma levels TSG-6 in DCM patients with heart failure increase significantly, and the plasma levels TSG-6 could be used as a new predictor for cardiac function, myocardial fibrosis, and prognosis.

FUNCTIONAL CLASSIFICATION OF CHILDREN WITH CEREBRAL PALSY IN KRAPINA-ZAGORJE COUNTY.

The aim was to study functional abilities and to create functional classification of children with cerebral palsy (CP) in Krapina-Zagorje County, based on the classification of gross and fine motor skills and associated impairments. Classification was performed according to the SCPE (Surveillance of Cerebral Palsy in Europe) criteria. We used standardized and complementary functional classification systems for cerebral palsy to create a functional profile. Research included 44 children with CP in the age range of 4 to 18 years. The results showed that the majority of children had bilateral spastic CP (63.6%), followed by unilateral spastic (22.7%) while the representation of dyskinetic CP was 9.09% and ataxic CP 4.55%. Based on the classification of gross and fine motor skills, 43.2% of children had the ability to walk, 11% of children could walk with assistive mobility devices, while 45.4% of children had a low functional level. The study also analyzed the associated impairments where higher classification score of motor impairment correlated with the severity of impairment. The results showed that children with dyskinetic CP and severe motor impairment could have mild cognitive impairment. We systematically present the neuropsychological and functional profile according to the CP type.

Which Functional Classification Scale is Optimal for Children with Pulmonary Hypertension (PAH)?

Functional status assessed by the WHO-FC scale derived from adults is a known prognostic factor for pulmonary hypertension. Data on the usefulness of the Panama-FC scale in assessing children with pulmonary hypertension are limited. The study was performed to compare functional status results (WHO-FC and Panama-FC) and to assess the usefulness of these scales in various clinical situations. The reliability of the Panama-FC questionnaire method for facilitating patient evaluation was also examined. 26 functional status assessments (7 in disease progression/after treatment intensification) in both scales were analyzed in 19 patients with PAH confirmed in RHC. WHO-FC, Panama-FC scales, and questionnaire-based on Panama-FC were conducted independently by three different physicians. Results of assessments were compared with each other and with 6MWD, NTproBNP level, and echo parameters (TAPSE, RV/LV ratio). The Panama-FC scale results obtained using the medical interview method and questionnaire did not differ. Both WHO-FC and Panama-FC classes well-reflected disease advancement confirmed by non-invasive parameters (NTproBNP, 6MWD, TAPSE, RV/LV ratio). Differences between grading the class in both scales were observed: 5pts were classified to II (Panama-FC) vs I (WHO-FC), 2pts were in lower risk group in WHO-FC (II) vs Panama (IIIa). Worsening or improvement after treatment intensification in functional status in both scales was connected with the significant change of NTproBNP level. The 6-min walking distance did not change. TAPSE, RV/LV ratio changed significantly in 3pts with IPAH, accordingly to change in WHO-FC and Panama-FC. WHO-FC and Panama-FC well reflect the disease advancement. The questionnaire method simplified the use of the Panama-FC scale. The Panama-FC scale appears to be better for assessing functional status during long-term follow-up, while the WHO-FC scale was more useful in short-term treatment monitoring.

Qualitative analysis and functional classification of the uterine proteome of mares in oestrus and dioestrus.

Quantitative analysis of the uterine flush fluid proteome of mares in oestrus and dioestrus has been previously reported. The objectives of this study were to: a) evaluate qualitative differences in the uterine flush fluid proteome between mares in oestrus and mares in dioestrus and b) perform a functional classification of proteins either unique to each stage or common between the two stages. Uterine flush fluid samples were collected from 8 light breed mares in either oestrus (n = 5) or dioestrus (n = 3). Proteomic analysis of the samples was conducted using liquid chromatography-tandem mass spectrometry. Proteins exclusively detected in oestrus or dioestrus and those common to both stages were identified using the Scaffold software (version 4.4.8, Proteome Software Inc., Portland, OR). The identified proteins were classified into gene ontology (GO) categories (cellular component [CC], molecular function [MF] and biological process [BP]) using the PANTHER (www.pantherdb.org) classification system version 14.0. Of 172 proteins identified, 51 and 28 were exclusively detected in mares in oestrus and dioestrus, respectively, and 93 proteins were common to both stages. The most represented terms in various GO categories were similar among the three subsets of proteins. The most represented CC terms were extracellular region and cell, the most represented MF terms were catalytic activity and binding, and the most represented BP terms were metabolic process and cellular process. In conclusion, proteomic analysis of the uterine flush fluid enabled the identification of subsets of proteins unique to oestrus or dioestrus, or common to both stages. The results of this study can serve as a baseline for future research focused on finding stage-specific protein markers or evaluating differences in the uterine flush fluid proteome between normal mares and those with uterine disease.

Residue Cluster Classes: A Unified Protein Representation for Efficient Structural and Functional Classification.

Proteins are characterized by their structures and functions, and these two fundamental aspects of proteins are assumed to be related. To model such a relationship, a single representation to model both protein structure and function would be convenient, yet so far, the most effective models for protein structure or function classification do not rely on the same protein representation. Here we provide a computationally efficient implementation for large datasets to calculate residue cluster classes (RCCs) from protein three-dimensional structures and show that such representations enable a random forest algorithm to effectively learn the structural and functional classifications of proteins, according to the CATH and Gene Ontology criteria, respectively. RCCs are derived from residue contact maps built from different distance criteria, and we show that 7 or 8 Å with or without amino acid side-chain atoms rendered the best classification models. The potential use of a unified representation of proteins is discussed and possible future areas for improvement and exploration are presented.

Prognostic value of cranial ultrasonography in comparison with magnetic resonance imaging in children with cerebral palsy: a population-based study.

The aim of this population-based study was to evaluate the characteristics of cerebral palsy (CP) in relation to the predominant pattern of the Magnetic Resonance Imaging Classification System (MRICS) that was analogously applied to the neonatal/early infant cranial ultrasound (CUS). The study included children born during the 2004-2007 period from the Croatian part (C28 RCP-HR) of the Surveillance of Cerebral Palsy in Europe (SCPE) CP register. Motor functions, accompanying impairments and brain MRI were evaluated in 227 children, 185 of which also had CUS. Concerning CP types, 56% of children had bilateral spastic, 34% unilateral spastic, 9% dyskinetic and 1% ataxic CP type. Gross Motor Function Classification System (GMFCS) revealed that 62.05% had mild (GMFCS I-III) and 37.85% had severe motor impairment (GMFCS IV-V). CUS showed white matter injury in 60%, gray matter injury in 12%, maldevelopments in 8%, miscellaneous changes in 14%, while 6% were normal; MRI showed significant agreement (κ=0.675, p<0.001). Neuroimaging findings of maldevelopments and predominant gray matter injury were associated with more severe CP, but 7% of children with CP had normal MRI. As we found very good agreement between CUS and MRI findings, CUS is recommended in children at an increased risk of CP if MRI is not available.

Evolution and functional classification of mammalian copper amine oxidases.

Mammalian copper-containing amine oxidases (CAOs), encoded by four genes (AOC1-4) and catalyzing the oxidation of primary amines to aldehydes, regulate many biological processes and are linked to various diseases including inflammatory conditions and histamine intolerance. Despite the known differences in their substrate preferences, CAOs are currently classified based on their preference for either primary monoamines (EC 1.4.3.21) or diamines (EC 1.4.3.22). Here, we present the first extensive phylogenetic study of CAOs that, combined with structural analyses of the CAO active sites, provides in-depth knowledge of their relationships and guidelines for classification of mammalian CAOs into AOC1-4 sub-families. The phylogenetic results show that CAOs can be classified based on two residues, X1 and X2, from the active site motif: T/S-X1-X2-N-Y-D. Residue X2 discriminates among the AOC1 (Tyr), AOC2 (Gly), and AOC3/AOC4 (Leu) proteins, while residue X1 further classifies the AOC3 (Leu) and AOC4 (Met) proteins that so far have been poorly identified and annotated. Residues X1 and X2 conserved within each sub-family and located in the catalytic site seem to be the key determinants for the unique substrate preference of each CAO sub-family. Furthermore, one residue located at 10 Šdistance from the catalytic site is different between the sub-families but highly conserved within each sub-family (Asp in AOC1, His in AOC2, Thr in AOC3 and Asn in AOC4) and likely contributes to substrate selectivity. Altogether, our results will benefit the design of new sub-family specific inhibitors and the design of in vitro tests to detect individual CAO levels for diagnostic purposes.