Short communication: Validation of a novel milk progesterone-based tool to monitor luteolysis in dairy cows using cost-effective,on-farm measured data

The progesterone (P4) monitoring algorithm using synergistic control (PMASC) uses luteal dynamics to identify fertility events in dairy cows. This algorithm employs a combination of mathematical functions describing the increasing and decreasing P4 concentrations during the development and regression of the corpus luteum and a statistical control chart that allows identification of luteolysis. The mathematical model combines sigmoidal functions from which the cycle characteristics can be calculated. Both the moment at which luteolysis is detected and confirmed by PMASC, as well as the model features themselves, can be used to inform the farmer on the fertility status of the cows.     

Loliolide,a New Therapeutic Option for Neurological Diseases? In Vitro Neuroprotective and Anti-Inflammatory Activities of a Monoterpenoid Lactone Isolated from Codium tomentosum

Parkinsons Disease (PD) is the second most common neurodegenerative disease worldwide, and is characterized by a progressive degeneration of dopaminergic neurons. Without an effective treatment, it is crucial to find new therapeutic options to fight the neurodegenerative process, which may arise from marine resources. Accordingly, the goal of the present work was to evaluate the ability of the monoterpenoid lactone Loliolide, isolated from the green seaweed Codium tomentosum, to prevent neurological cell death mediated by the neurotoxin 6-hydroxydopamine (6-OHDA) on SH-SY5Y cells and their anti-inflammatory effects in RAW 264.7 macrophages. Loliolide was obtained from the diethyl ether extract, purified through column chromatography and identified by NMR spectroscopy. The neuroprotective effects were evaluated by the MTT method. Cells’ exposure to 6-OHDA in the presence of Loliolide led to an increase of cells’ viability in 40%, and this effect was mediated by mitochondrial protection, reduction of oxidative stress condition and apoptosis, and inhibition of the NF-kB pathway. Additionally, Loliolide also suppressed nitric oxide production and inhibited the production of TNF-α and IL-6 pro-inflammatory cytokines. The results suggest that Loliolide can inspire the development of new neuroprotective therapeutic agents and thus, more detailed studies should be considered to validate its pharmacological potential.     

An improved machine learning technique based on downsized KPCA for Alzheimer's disease classification

Alzheimer's disease (AD), a neurodegenerative disorder, is a very serious illness that cannot be cured, but the early diagnosis allows precautionary measures to be taken. The current used methods to detect Alzheimer's disease are based on tests of cognitive impairment, which does not provide an exact diagnosis before the patient passes a moderate stage of AD. In this article, a novel classifier of brain magnetic resonance images (MRI) based on the new downsized kernel principal component analysis (DKPCA) and multiclass support vector machine (SVM) is proposed. The suggested scheme classifies AD MRIs. First, a multiobjective optimization technique is used to determine the optimal parameter of the kernel function in order to ensure good classification results and to minimize the number of retained principle components simultaneously. The optimal parameter is used to build the optimized DKPCA model. Second, DKPCA is applied to normalized features. Downsized features are then fed to the classifier to output the prediction. To validate the effectiveness of the proposed method, DKPCA was tested using synthetic data to demonstrate its efficiency on dimensionality reduction, then the DKPCA based technique was tested on the OASIS MRI database and the results were satisfactory compared to conventional approaches.     

Spatial Charge Separation as the Origin of Anomalous Stark Effect in Fluorous 2D Hybrid Perovskites

2D hybrid perovskites (2DP) are versatile materials, whose electronic and optical properties can be tuned through the nature of the organic cations (even when those are seemingly electronically inert). Here, it is demonstrated that fluorination of the organic ligands yields glassy 2DP materials featuring long‐lived correlated electron–hole pairs. Such states have a marked charge‐transfer character, as revealed by the persistent Stark effect in the form of a second derivative in electroabsorption. Modeling shows that electrostatic effects associated with fluorination, combined with the steric hindrance due to the bulky side groups, drive the formation of spatially dislocated charge pairs with reduced recombination rates. This work enriches and broadens the current knowledge of the photophysics of 2DP, which will hopefully guide synthesis efforts toward novel materials with improved functionalities.     

Nanomotion Detection Method for Testing Antibiotic Resistance and Susceptibility of Slow‐Growing Bacteria

Infectious diseases are caused by pathogenic microorganisms and are often severe. Time to fully characterize an infectious agent after sampling and to find the right antibiotic and dose are important factors in the overall success of a patient's treatment. Previous results suggest that a nanomotion detection method could be a convenient tool for reducing antibiotic sensitivity characterization time to several hours. Here, the application of the method for slow‐growing bacteria is demonstrated, taking Bordetella pertussis strains as a model. A low‐cost nanomotion device is able to characterize B. pertussis sensitivity against specific antibiotics within several hours, instead of days, as it is still the case with conventional growth‐based techniques. It can discriminate between resistant and susceptible B. pertussis strains, based on the changes of the sensor's signal before and after the antibiotic addition. Furthermore, minimum inhibitory and bactericidal concentrations of clinically applied antibiotics are compared using both techniques and the suggested similarity is discussed.     

Image and video denoising by combining unsupervised bounded generalized gaussian mixture modeling and spatial information

Multimedia Tools and Applications - In recent years, a great deal of effort has been expended on developing robust solutions for images quality degradation caused mainly by noise. In this paper, we...     

Genomic structure,cloning and expression of two phospholipase D isoenzymes from white cabbage

Phospholipase D (PLD) from cabbage is interesting as biocatalyst in phospholipid transformation. To provide the basis for genetic engineering of the enzyme, gene cloning and sequencing were carried out. We have recently identified two isoenzymes, PLD1 and PLD2, on the basis of their cDNAs, here we describe their genomic structure consisting of 3404 and 3614 bp, respectively. Based on their sequence, PLD1 and PLD2 can be assigned to the α‐type of plant PLDs, they contain two HKD motifs and the C2 domain with a phosphatidylinositol 4,5‐bisphosphate (PIP₂) binding motif. Starting from pld1 cDNA, expression studies were carried out. Whereas expression using constructs with StrepTactin or Glutathion S‐transferase tags was not successful, soluble active enzyme was produced from constructs without tag. pld2 was expressed accordingly. Both enzymes were purified by Ca²⁺‐mediated hydrophobic interaction chromatography to high purity. N‐terminal sequencing of PLD1 and PLD2 revealed that the Met‐free N‐termini of both enzymes correspond to sequences derived from the coding region of the pld1 and pld2 genes, respectively. Both recombinant enzymes showed highest hydrolytic activities at pH 5.5 to 5.6, independent of Ca²⁺ concentration (10—100 mM). The optimum Ca²⁺ concentration was 45 mM for PLD1 and PLD2. Both enzymes showed comparable activities in hydrolysis and transphosphatidylation of phospholipids.