In the last decade, our understanding of rice domestication has improved by new archaeological findings using advanced analytical techniques such as morphological and morphometric analyses on rice grains, spikelet bases and phytoliths, and ancient DNA analysis on rice remains. Previous studies have considered the size of rice bulliform phytoliths as a proxy for tracking the domestication process. These phytoliths are often abundant and well preserved in sediments, and their shape is under the control of numerous genes, which may shift toward larger sizes by genetic mutation in domestication. Therefore, it has been assumed that the bulliforms of domesticated rice are usually larger than those of wild ones; however, morphometric data supporting this assumption are lacking in the literature, thereby requiring additional evidence to test its veracity. In this study, the vertical and horizonal lengths of bulliform phytoliths were measured in four rice species (domesticated Oryza sativa and wild Oryza rufipogon, Oryza officinalis, and Oryza meyeriana) from different regions of southern China. We found that the bulliform morphometric data of wild and domesticated rice overlapped and that there was no statistically significant difference between them. Therefore, bulliform size could not be used as a diagnostic indicator to distinguish domesticated rice from wild species and is a supporting rather than conclusive proxy for determining the domesticated status of rice in archaeological research. We further found that larger rice bulliform sizes likely occurred at the locations with higher temperature, precipitation, and water levels, indicating hydrothermal environment is an alternative factor influencing the size of rice bulliform phytoliths. For further archaeological use of an increasing size trend of bulliform phytoliths to reveal the process of rice domestication, we present some suggestions for controlling the influence of hydrothermal factors. Even so, the combination of bulliform phytolith size with other established criteria is strongly suggested to provide precise identification of wild and domesticated rice in future research.

Fusaric acid (FA) is an important secondary metabolite of many Fusarium species and involved in the wilt symptoms caused in banana by Fusarium oxysporum f. sp. cubense (Foc). To investigate the evolution characteristics of the 12 Foc FA biosynthetic genes (FUB), coding sequences of the 12 FUB genes and three housekeeping genes, EF-1α/RPB1/RPB2 (translation elongation factor-1α/RNA polymerase II subunit I/RNA polymerase II subunit II), were subjected to genetic diversity analysis, phylogenetic analysis, recombination detection, and selective pressure analysis. The results of selective pressure analysis showed that the 15 genes were mainly subjected to negative selection. However, a significantly higher number of silent mutations, which could not be simply explained by selective pressure difference, were observed in the 12 FUB genes in Foc than in the three housekeeping genes. Infraspecies phylogeny and recombination detection analysis showed that significantly more horizontal gene transfer (HGT) events (normalized) had occurred in the FUB genes than in the three housekeeping genes. In addition, many of these events involved outgroup isolates and significantly increased the genetic diversity of FUB genes in Foc. The infraspecies phylogenetic analysis suggested that the polyphyletic phylogeny proposed for Foc requires further discussion, and the divergence of race 1, race 4, and the common ancestor of several F. oxysporum (Fo) isolates pathogenic to nonbanana plants should have diverged over a short period. Finally, our results suggest that the FUB genes in Fo should have benefited from HGT to gain a relatively high genetic diversity to respond to different host plants and environments despite mainly being subject to negative selection.

Lipid remodeling plays an important role in the adaptation of plants to environmental factors, but the mechanism by which lipid remodeling mediates salt stress response remains unclear. In this study, we compared the root and leaf lipidome profiles of salt-tolerant and salt-sensitive sweet potato cultivars (Xu 22 and Xu 32, respectively) under salinity stress. After salt treatment, the leaf lipidome showed more significant remodeling than the root lipidome in both cultivars. Compared with Xu 32 leaves, Xu 22 leaves generally maintained higher abundance of phospholipids, glycolipids, sphingolipids, sterol derivatives, and diacylglycerol under salinity conditions. Interestingly, salinity stress significantly increased phosphatidylserine (PS) abundance in Xu 22 leaves by predominantly triggering the increase of PS (20:5/22:6). Furthermore, Xu 32 leaves accumulated higher triacylglycerol (TG) level than Xu 22 leaves under salinity conditions. The exogenous application of PS delayed salt-induced leaf senescence in Xu 32 by reducing salt-induced K+ efflux and upregulating plasma membrane H+-ATPase activity. However, the inhibition of TG mobilization in salinized-Xu 22 leaves disturbed energy and K+/Na+ homeostasis, as well as plasma membrane H+-ATPase activity. These results demonstrate alterations in the leaf lipidome of sweet potato under salinity condition, underscoring the importance of PS and TG in mediating salt-defensive responses in sweet potato leaves.

Genetic diversity studies are essential in characterization of populations and species conservation. Alosa braschnikowi is a commercially valuable species native to the Caspian Sea. It is thought to have eight to nine subspecies, but the genetics of these populations remains to be investigated. The present study was performed to evaluate the genetic population structures of Caspian marine shad (Alosa braschnikowi) in the southern coast of the Caspian Sea using six pairs of SSR markers. A total of Alosa braschnikowi 140 specimens through five locations across the southern coast of the Caspian Sea were genotyped and 130 alleles were identified. The overall mean values of Ho and He were 0.58 and 0.87, respectively, with the highest and minimum value of Ho observed in Sari (0.67 ± 0.08) and Miankaleh (0.50 ± 0.04), respectively. The overall mean value of allelic richness was 12.6. The data suggest that there was a high rate of migration between populations of Alosa braschnikowi (overall mean of Nm = 13.57), with the highest value (19.07) between Gomishan and Mahmodabad locations. AMOVA results showed that 96% of variation was related to within populations and only 4% belonged to between populations. The mean Fst value of 0.019 indicates a low level of population differentiation. Our data suggest that there may be two genetically separate populations of Alosa braschnikowi across the southern coast of the Caspian Sea and a high rate of migration is likely to limit genetic diversity between them.

Endometriosis is a complex and common gynecological disorder yet a poorly understood disease affecting about 176 million women worldwide and causing significant impact on their quality of life and economic burden. Neither a definitive clinical symptom nor a minimally invasive diagnostic method is available, thus leading to an average of 4 to 11 years of diagnostic latency. Discovery of relevant biological patterns from microarray expression or next generation sequencing (NGS) data has been advanced over the last several decades by applying various machine learning tools. We performed machine learning analysis using 38 RNA-seq and 80 enrichment-based DNA methylation (MBD-seq) datasets. We experimented how well various supervised machine learning methods such as decision tree, partial least squares discriminant analysis (PLSDA), support vector machine, and random forest perform in classifying endometriosis from the control samples trained on both transcriptomics and methylomics data. The assessment was done from two different perspectives for improving classification performances: a) implication of three different normalization techniques and b) implication of differential analysis using the generalized linear model (GLM). Several candidate biomarker genes were identified by multiple machine learning experiments including NOTCH3, SNAPC2, B4GALNT1, SMAP2, DDB2, GTF3C5, and PTOV1 from the transcriptomics data analysis and TRPM6, RASSF2, TNIP2, RP3-522J7.6, FGD3, and MFSD14B from the methylomics data analysis. We concluded that an appropriate machine learning diagnostic pipeline for endometriosis should use TMM normalization for transcriptomics data, and quantile or voom normalization for methylomics data, GLM for feature space reduction and classification performance maximization.

Lactobacillus johnsonii ZLJ010 is a probiotic strain isolated from the feces of a healthy sow and has putative health-promoting properties. To determine the molecular basis underlying the probiotic potential of ZLJ010 and the genes involved in the same, complete genome sequencing and comparative genome analysis with L. johnsonii ZLJ010 were performed. The ZLJ010 genome was found to contain a single circular chromosome of 1,999,879 bp with a guanine-cytosine (GC) content of 34.91% and encoded 18 ribosomal RNA (rRNA) genes and 77 transfer RNA (tRNA) genes. From among the 1,959 protein coding sequences (CDSs), genes known to confer probiotic properties were identified, including genes related to stress adaptation, biosynthesis, metabolism, transport of amino acid, secretion, and the defense machinery. ZLJ010 lacked complete or partial biosynthetic pathways for amino acids but was predicted to compensate for this with an enhanced transport system and some unique amino acid permeases and peptidases that allow it to acquire amino acids and other precursors exogenously. The comparative genomic analysis of L. johnsonii ZLP001 and seven other available L. johnsonii strains, including L. johnsonii NCC533, FI9785, DPC6026, N6.2, BS15, UMNLJ22, and PF01, revealed 2,732 pan-genome orthologous gene clusters and 1,324 core-genome orthologous gene clusters. Phylogenomic analysis based on 1,288 single copy genes showed that ZLJ010 had a closer relationship with the BS15 from yogurt and DPC6026 from the porcine intestinal tract but was located on a relatively standalone branch. The number of clusters of unique, strain-specific genes ranged from 42 to 185. A total of 219 unique genes present in the genome of L. johnsonii ZLJ010 primarily encoded proteins that are putatively involved in replication, recombination and repair, defense mechanisms, transcription, amino acid transport and metabolism, and carbohydrate transport and metabolism. Two unique prophages were predicted in the ZLJ010 genome. The present study helps us understand the ability of L. johnsonii ZLJ010 to better adapt to the gut environment and also its probiotic functionalities.

Enterococcus faecalis is a commensal organism as well as an important nosocomial pathogen, and its infections are typically linked to biofilm formation. Nearly 25% of the E. faecalis OG1RF genome encodes hypothetical genes or genes of unknown function. Elucidating their function and how these gene products influence biofilm formation is critical for understanding E. faecalis biology. To identify uncharacterized early biofilm determinants, we performed a genetic screen using an arrayed transposon (Tn) library containing ~2000 mutants in hypothetical genes/intergenic regions and identified eight uncharacterized predicted protein-coding genes required for biofilm formation. We demonstrate that OG1RF_10435 encodes a phosphatase that modulates global protein expression and arginine catabolism and propose renaming this gene bph (biofilm phosphatase). We present a workflow for combining phenotype-driven experimental and computational evaluation of hypothetical gene products in E. faecalis, which can be used to study hypothetical genes required for biofilm formation and other phenotypes of diverse bacteria.

Annexin A1 (AnxA1) modulates neutrophil life span and bone marrow/blood cell trafficking thorough activation of formyl-peptide receptors (FPRs). Here, we investigated the effect of exogenous AnxA1 on haematopoiesis in the mouse. Treatment of C57BL/6 mice with recombinant AnxA1 (rAnxA1) reduced the granulocyte-macrophage progenitor (GMP) population in the bone marrow, enhanced the number of mature granulocytes Gr-1+Mac-1+ in the bone marrow as well as peripheral granulocytic neutrophils and increased expression of mitotic cyclin B1 on hematopoietic stem cells (HSCs)/progenitor cells (Lin-Sca-1+c-Kit+: LSK). These effects were abolished by simultaneous treatment with Boc-2, an FPR pan-antagonist. In in vitro studies, rAnxA1 reduced both HSC (LSKCD90lowFLK-2-) and GMP populations while enhancing mature cells (Gr1+Mac1+). Moreover, rAnxA1 induced LSK cell proliferation (Ki67+), increasing the percentage of cells in the S/G2/M cell cycle phases and reducing Notch-1 expression. Simultaneous treatment with WRW4, a selective FPR2 antagonist, reversed the in vitro effects elicited by rAnxA1. Treatment of LSK cells with rAnxA1 led to phosphorylation of PCLγ2, PKC, RAS, MEK, and ERK1/2 with increased expression of NFAT2. In long-term bone marrow cultures, rAnxA1 did not alter the percentage of LSK cells but enhanced the Gr-1+Mac-1+ population; treatment with a PLC (U73122), but not with a PKC (GF109203), inhibitor reduced rAnxA1-induced phosphorylation of ERK1/2 and Elk1. Therefore, we identify here rAnxA1 as an inducer of HSC/progenitor cell differentiation, favouring differentiation of the myeloid/granulocytic lineage, via Ca2+/MAPK signalling transduction pathways.

Systematic review and case series.

Alternative splicing (AS) has a critical role in tumor progression and prognosis. Our study aimed to investigate pancreatic cancer-specific AS events using RNA-seq data, gaining systematic insights into potential prognostic predictors. We downloaded 10,623 genes with 45,313 pancreatic cancer-specific AS events from the Cancer Genome Atlas (TCGA) and SpliceSeq database. Cox univariate analyses of overall survival suggested there was a remarkable association between 6,711 AS events and overall survival in pancreatic cancer patients (P < 0.05). The area under the curves (AUC) of the receiver operator characteristic curves (ROC) of risk score was 0.89 for final prognostic predictor. Results indicated that AS events of DAZAP1, RBM4, ESRP1, QKI, and SF1 were significantly associated with overall survival. The results of FunRich showed that transcription factors KLF7, GABPA, and SP1 were the most highly related to survival-associated AS genes. Furthermore, using DriverDBv2, we identified 13 driver genes associated with survival-associated AS events, including TP53 and CDC27. Thus, we concluded that the aberrant AS patterns in pancreatic cancer patients might serve as prognostic predictors.

High-dose chemotherapy (HDT) followed by autologous hematopoietic stem cell transplantation (ASCT) is widely used in patients with malignant lymphomas. In Europe over 8,000 ASCTs for lymphoma were performed out of a total of 40,000 transplants according to the European Bone Marrow Transplant (EBMT) activity survey in 2017. ASCT is considered the standard treatment for eligible patients failing to achieve remission after first line chemotherapy or patients with relapsed or refractory lymphomas, including classical Hodkin's lymphoma, diffuse large B-cell lymphoma, mantle cell lymphoma, and follicular lymphoma, as well as consolidation therapy in first remission in mantle cell lymphoma. BEAM (BCNU/carmustine, etoposide, cytarabine, and melphalan) is the most commonly used conditioning regimen for ASCT in patients with relapsed/refractory (R/R) lymphomas in Europe, whereas the CBV (cyclophosphamide, BCNU, and etoposide) regimen is also widely used in North America. Recently, concerns regarding BCNU toxicity as well as restricted availability of BCNU and melphalan has determined an increasing number of transplant centers to use alternative conditioning regimens. Currently, only a few comparative studies, most of them retrospective, between different conditioning protocols regarding efficacy and toxicity have been published. Thus, in the current manuscript, we report the experience of 2 transplant centers in ASCT in R/R lymphomas with three types of conditioning: BEAM, CLV (cyclophosphamide, lomustine, etoposide) and LEAM (lomustine, etoposide, cytarabine, and melphalan), with the aim to evaluate the results of alternative conditioning regimens using lomustine (LEAM and CLV) and compare them with the standard BEAM regarding early toxicity, engraftment, and transplant related mortality (TRM). All patients developed grade IV neutropenia, anemia with/without transfusion necessity. Severe thrombocytopenia with transfusion requirements is reported in most cases. Median time to platelet engraftment and neutrophil engraftment was 13 days (range) and 10 days (range), respectively. Gastrointestinal toxicity was the most common non-hematologic toxicity after all three conditioning regimens. Oral mucositis in various grades from I to IV was diagnosed in most cases. Other side effects include vomiting, diarrhea, colitis, and skin rash but with low severity grades. For the LEAM arm, one patient died after transplant, before engrafting, one patient didn't achieve platelet engraftment in day 100, one patient developed grade 3 upper gastrointestinal bleeding, one patient died (grade 5 toxicity) with acute renal failure, one patient developed hypoxic events up to grade 4 acute respiratory failure and one patient developed grade 3 itchy skin rash. For the CLV arm, one patient died after transplant, before engrafting, one patient developed grade 3 colitis, one patient with grade 3 hepatic cytolysis, one patient with cardiac toxicity followed by death (grade 5) caused by an acute myocardial infarction with ST elevation and one patient with pulmonary toxicity clinically manifested with grade 3 pleurisy. For the BEAM arm, one patient developed grade 3 cardiac toxicity with sinus bradycardia and afterwards grade 4 with acute pulmonary edema, three patients presented a grade 3 pruritic skin rash and two patients developed grade 3 seizures. In the present study we presented the differences that were observed between BEAM, LEAM, and CLV conditioning regimens offering clinical arguments for an SCT practitioner choice in the ideal situation, but also of choice for alternative regimens in the case that one regimen cannot be used.

Carbapenem-resistant, hypervirulent Klebsiella pneumoniae (CR-hvKP) has recently emerged as a significant threat to public health. In this study, 29 K. pneumoniae isolates were isolated from eight patients admitted to the intensive care unit (ICU) of a comprehensive teaching hospital located in China from March 2017 to January 2018. Clinical information of patients was the basis for the further analyses of the isolates including antimicrobial susceptibility tests, identification of antibiotic resistance and virulence gene determinants, multilocus sequence typing (MLST), XbaI-macrorestriction by pulsed-field gel electrophoresis (PFGE). Selected isolates representing distinct resistance profiles and virulence phenotypes were screened for hypervirulence in a Galleria mellonella larvae infection model. In the course of the outbreak, the overall mortality rate of patients was 100% (n = 8) attributed to complications arising from CR-hvKP infections. All isolates except one (28/29, 96.6%) were resistant to multiple antimicrobial agents, and harbored diverse resistance determinants that included the globally prevalent carbapenemase bla KPC-2. Most isolates had hypervirulent genotypes being positive for 19 virulence-associated genes, including iutA (25/29, 86.2%), rmpA (27/29, 93.1%), ybtA (27/29, 93.1%), entB (29/29, 100%), fimH (29/29, 100%), and mrkD (29/29, 100%). MLST revealed ST11 for the majority of isolates (26/29, 89,7%). Infection assays demonstrated high mortality in the Galleria mellonella model with the highest LD50 values for three isolates (<105 CFU/mL) demonstrating the degree of hypervirulence of these CR-hvKP isolates, and is discussed relative to previous outbreaks of CR-hvKP.

The recent advancements in rapid and affordable DNA sequencing technologies have revolutionized diagnostic microbiology and microbial surveillance. The availability of bioinformatics tools and online accessible databases has been a prerequisite for this. We conducted a scientific literature review and here we present a description of examples of available tools and databases for antimicrobial resistance (AMR) detection and provide future perspectives and recommendations. At least 47 freely accessible bioinformatics resources for detection of AMR determinants in DNA or amino acid sequence data have been developed to date. These include, among others but not limited to, ARG-ANNOT, CARD, SRST2, MEGARes, Genefinder, ARIBA, KmerResistance, AMRFinder, and ResFinder. Bioinformatics resources differ for several parameters including type of accepted input data, presence/absence of software for search within a database of AMR determinants that can be specific to a tool or cloned from other resources, and for the search approach employed, which can be based on mapping or on alignment. As a consequence, each tool has strengths and limitations in sensitivity and specificity of detection of AMR determinants and in application, which for some of the tools have been highlighted in benchmarking exercises and scientific articles. The identified tools are either available at public genome data centers, from GitHub or can be run locally. NCBI and European Nucleotide Archive (ENA) provide possibilities for online submission of both sequencing and accompanying phenotypic antimicrobial susceptibility data, allowing for other researchers to further analyze data, and develop and test new tools. The advancement in whole genome sequencing and the application of online tools for real-time detection of AMR determinants are essential to identify control and prevention strategies to combat the increasing threat of AMR. Accessible tools and DNA sequence data are expanding, which will allow establishing global pathogen surveillance and AMR tracking based on genomics. There is however, a need for standardization of pipelines and databases as well as phenotypic predictions based on the data.

The most frequently diagnosed cancers in women are the estrogen receptor (ER)-positive breast cancer subtypes, which are characterized by estrogen dependency for their growth. The mainstay of clinical treatment for this tumor relies on the modulation of ERα action or on the suppression of estrogen biosynthesis via the administration of Selective ERα Modulators/Down-regulators (SERMs/SERDs) or aromatase inhibitors, respectively. Nevertheless, de novo and acquired resistance to these therapies frequently occurs and represents a major clinical concern for patient survival. Recently, somatic mutations affecting the hormone-binding domain of ERα (i.e., Y537S, Y537N, D538G) have been associated with endocrine resistance, disease relapse and increased mortality rates. Hence, devising novel therapies against these ERα isoforms represents a daunting challenge. Here, we identified five molecules active on recurrent Y537S ERα polymorphism by employing in silico virtual screening on commercial databases of molecules, complemented by ER-transactivation and MTT assays in MCF7 and MDA-MB-231 breast cancer cells expressing wild type or mutated ERα. Among them, one molecule selectively targets Y537S ERα without inducing any cytotoxicity in breast cell lines. Multi-microseconds (4.5 μs) of biased and unbiased molecular dynamics provided an atomic-level picture of the structural, thermodynamics (i.e., binding free energies) and the kinetic (i.e., dissociation free energy barriers) of these active ligands as compared to clinically used SERM/SERDs upon binding to wild type and distinct ERα variants (Y537S, Y537N, D538G). This study contributes to a dissection of the key molecular traits needed by drug-candidates to hamper the agonist (active)-like conformation of ERα, normally selected by those polymorphic variants. This information can be useful to discover mutant specific drug-candidates, enabling to move a step forward toward tailored approaches for breast cancer treatment.

In guided bone tissue engineering, successful ingrowth of MSCs depends primarily on the nature of the scaffold. It is well-known that only seconds after implantation, biomaterials are coated by a layer of adsorbed proteins/peptides which modulates the subsequent cell/scaffold interactions, especially at early times after implantation. In this work, nanohydroxyapatite and collagen based composite materials (Coll/nanoHA) were modified with phosphorylated amino acid (O-phospho-L-serine-OPS) to mimic bone tissue, and induce cell differentiation. The choice for this phosphorylated amino acid is due to the fact that osteopontin is a serine-rich glycol-phosphoprotein and has been associated to the early stages of bone formation, and regeneration. Several concentrations of OPS were added to the Coll/nanoHA scaffold and physico-chemical, mechanical, and in vitro cell behavior were evaluated. Afterwards, the composite scaffold with stronger mechanical and best cellular behavior was tested in vivo, with or without previous in vitro culture of human MSC's (bone tissue engineering). The OPS signaling of the biocomposite scaffolds showed similar cellular adhesion and proliferation, but higher ALP enzyme activity (HBMSC). In vivo bone ectopic formation studies allowed for a thorough evaluation of the materials for MSC's osteogenic differentiation. The OPS-scaffolds results showed that the material could modulated mesenchymal cells behavior in favor of osteogenic differentiation into late osteoblasts that gave raised to their ECM with human bone proteins (osteopontin) and calcium deposits. Finally, OPS-modified scaffolds enhanced cell survival, engraftment, migration, and spatial distribution within the 3D matrix that could be used as a cell-loaded scaffold for tissue engineering applications and accelerate bone regeneration processes.

Chitosan is a natural polymer revealing an increased potential to be used in different biomedical applications, including drug delivery systems, and tissue engineering. It implies the evaluation of the organism response to the biomaterial implantation. Low-molecular degradation products, the chito-oligomers, are resulting mainly from the influence of enzymes, which are found in the organism fluids. Within this study, we have performed the computational assessment of pharmacological profiles and toxicological effects on human health of small chito-oligomers with distinct molecular weights, deacetylation degrees, and acetylation patterns. Our approach is based on the fact that regulatory agencies and researchers in the drug development field rely on the use of modeling to predict biological effects and to guide decision making. To be considered as valid for regulatory purposes, every model that is used for predictions should be associated with a defined toxicological endpoint and has appropriate robustness and predictivity. Within this context, we have used FAF-Drugs4, SwissADME, and PreADMET tools to predict the oral bioavailability of chito-oligomers and SwissADME, PreADMET, and admetSAR2.0 tools to predict their pharmacokinetic profiles. The organs and genomic toxicities have been assessed using admetSAR2.0 and PreADMET tools but specific computational facilities have been also used for predicting different toxicological endpoints: Pred-Skin for skin sensitization, CarcinoPred-EL for carcinogenicity, Pred-hERG for cardiotoxicity, ENDOCRINE DISRUPTOME for endocrine disruption potential and Toxtree for carcinogenicity and mutagenicity. Our computational assessment showed that investigated chito-oligomers reflect promising pharmacological profiles and limited toxicological effects on humans, regardless of molecular weight, deacetylation degree, and acetylation pattern. According to our results, there is a possible inhibition of the organic anion transporting peptides OATP1B1 and/or OATP1B3, a weak potential of cardiotoxicity, a minor probability of affecting the androgen receptor, and phospholipidosis. Consequently, these results may be used to guide or to complement the existing in vitro and in vivo toxicity tests, to optimize biomaterials properties and to contribute to the selection of prototypes for nanocarriers.

To gain insight into the malfunction of the Golgi apparatus and its relationship to various genetic and neurodegenerative diseases, the identification of sub-Golgi proteins, both cis-Golgi and trans-Golgi proteins, is of great significance. In this study, a state-of-art random forests sub-Golgi protein classifier, rfGPT, was developed. The rfGPT used 2-gap dipeptide and split amino acid composition for the feature vectors and was combined with the synthetic minority over-sampling technique (SMOTE) and an analysis of variance (ANOVA) feature selection method. The rfGPT was trained on a sub-Golgi protein sequence data set (137 sequences), with sequence identity less than 25%. For the optimal rfGPT classifier with 93 features, the accuracy (ACC) was 90.5%; the Matthews correlation coefficient (MCC) was 0.811; the sensitivity (Sn) was 92.6%; and the specificity (Sp) was 88.4%. The independent testing scores for the rfGPT were ACC = 90.6%; MCC = 0.696; Sn = 96.1%; and Sp = 69.2%. Although the independent testing accuracy was 4.4% lower than that for the best reported sub-Golgi classifier trained on a data set with 40% sequence identity (304 sequences), the rfGPT is currently the top sub-Golgi protein predictor utilizing feature vectors without any position-specific scoring matrix and its derivative features. Therefore, the rfGPT is a more practical tool, because no sequence alignment is required with tens of millions of protein sequences. To date, the rfGPT is the Golgi classifier with the best independent testing scores, optimized by training on smaller benchmark data sets. Feature importance analysis proves that the non-polar and aliphatic residues composition, the (aromatic residues) + (non-polar, aliphatic residues) dipeptide and aromatic residues composition between NH2-termial and COOH-terminal of protein sequences are the three top biological features for distinguishing the sub-Golgi proteins.

Here we report a novel approach, the DelPhiForce Molecular Dynamics (DFMD) method, for steered molecular dynamics simulations to model receptor-ligand association involving charged species. The main purpose of developing DFMD is to simulate ligand's trajectory toward the receptor and thus to predict the "entrance" of the binding pocket and conformational changes associated with the binding. We demonstrate that the DFMD is superior compared with molecular dynamics simulations applying standard cut-offs, provides correct binding forces, allows for modeling the ligand approach at long distances and thus guides the ligand toward the correct binding spot, and it is very fast (frequently the binding is completed in <1 ns). The DFMD is applied to model the binding of two ligands to a receptor (spermine synthase) and it is demonstrated that it guides the ligands toward the corresponding pockets despite of the initial ligand's position with respect to the receptor. Predicted conformational changes and the order of ligand binding are experimentally verified.

Background: Canine chronic enteropathies (CE) are a group of intestinal diseases that can be categorized based on treatment response into diet- or food- responsive enteropathy (FRD), antibiotic-responsive enteropathy, steroid-responsive enteropathy, and non-responsive enteropathy. CE can often be associated with intestinal dysbiosis and thus administration of probiotic or synbiotic products may provide a useful tool for the management of some of these patients. Enterococcus faecium (EF) is a probiotic strain included in a commercially available synbiotic for small animals, however its impact on the microbial communities in dogs with FRD has not yet been evaluated. Hypothesis/Objectives: The administration of a synbiotic will lead to a significant difference of the fecal microbial composition and/or diversity in dogs with FRD, and these changes are not attributable to diet change alone. Animals/Samples: Twelve dogs with FRD fed a hydrolyzed protein diet received either a synbiotic (EF, fructooligosaccharides, gum Arabic) or placebo. Fecal samples were taken before and 6 weeks into treatment. Fecal samples were also acquired from 8 healthy dogs before and 6 weeks after being switched to the same hydrolyzed protein diet as their sole food. Methods: Bacterial DNA was extracted from fecal samples and next generation sequencing based on the 16S rRNA genes was performed. Microbial composition and diversity between groups were compared using QIIME. Results: There was a small increase in species diversity in the feces of dogs with FRD treated with synbiotics. However, there were no significant differences in microbial community composition before and after 6 weeks in either the synbiotic or placebo treated dogs with FRD or the healthy dogs. In all groups, large individual variations were observed. Conclusions: No changes in microbial composition were observed in diseased or healthy dogs with diet change alone. However, administration of a synbiotic increased bacterial richness in both groups.

Oxyclozanide is an effective anthelmintic and has shown good properties in other ways including anti-adenovirus, anti-biofilm, antifungal, and antibacterial activity. This study aimed to investigate the acute and subacute 28-days repeated dose oral toxicity of an oxyclozanide suspension in Wistar rats. A high oral lethal dose (LD50) of 3,707 mg/kg was observed in the acute toxicity test. During the 28-days time period, no obvious adverse effects or death were detected. Histopathological changes were observed in the heart, liver, and kidney of animals treated with high dose of oxyclozanide. Based on the hematological parameters, there were no statistical differences between the oxyclozanide-treated group and the control group. For biochemistry assays, ALP, AST, GLU, TBIL, GLO, TG, BUN, UA, LDH, and CK were statistically changed in the treatment groups. These data suggested that the LD50 of oxyclozanide was ~3,707 mg/kg body weight (BW), and the lowest observed adverse effect level (LOAEL) of oxyclozanide was at a dose of 74 mg/kg in rats.