Egzosomni faktor miR-433 regulira izlučivanje upalnih faktora u epitelnim stanicama endometrija mliječnih krava s endometritisom

Endometritis is a common postpartum reproductive system disease, which causes reproductive disorders and even infertility in dairy cows. High-throughput sequencing revealed that exosomal miR-433 is differentially expressed in the peripheral blood of dairy cows with endometritis. However, the specific roles of miR-433 in the occurrence and development of endometritis in dairy cows are still unclear. Therefore, a miR-433-labeled probe was used initially and found that miR-433 is mainly located in uterine cavity epithelial cells and stromal cells. The fluorescence expression of miR-433 in the uterine cavity epithelium and stromal tissues of dairy cows with endometritis is significantly weaker than that in the healthy tissues. The qRT-PCR results showed that the expressions of miR-433 in the uterine tissues of dairy cows with endometritis, LPS stimulated endometrial epithelial cells (EECs), and their derived exosomes were significantly lower than those in the uterine tissues of healthy dairy cows, EECs and their derived exosomes. Exosomal miR-433 derived from EECs transports into neighboring LPS-stimulated EECs by exosome vesicles fusion, regulating the secretion of inflammatory factors within the endometrial epithelium of dairy cows with endometritis, further influencing the development of endometritis. In conclusion, the intensity of miR-433 expression decreased in the epithelial and stromal cells of the uterine lumen and exosomes derived from endometrial epithelium in dairy cows during the occurrence of endometritis, which to some extent promotes the development and progression of endometritis in dairy cows.Endometritis je česta poslijeporođajna bolest reproduktivnog sustava, koja uzrokuje poremećaje, pa čak i neplodnost u mliječnih krava. Sekvenciranje visoke propusnosti otkrilo je da je u perifernoj krvi mliječnih krava s endometritisom egzosomni miR-433 diferencijalno eksprimiran. Još uvijek, međutim, nisu razjašnjene specifične uloge miR-433 u nastanku i razvoju endometritisa u mliječnih krava. S obzirom na to, inicijalno je upotrijebljena sonda označena kao miR-433 te je ustanovljeno da se miR-433 uglavnom nalazi u epitelnim i stromalnim stanicama maternične šupljine. Ekspresija miR-433 dobivena metodom fluorescencije iz epitela i stromalnog tkiva maternične šupljine mliječnih krava s endometritisom znakovito je manja nego u zdravim tkivima. Rezultati dobiveni qRT-PCR-om pokazali su da su ekspresija molekule miR-433 u materničnom tkivu mliječnih krava s endometritisom, endometrijske epitelne stanice (EEC) stimulirane lipopolisaharidom (LPS) i njihovi egzomi bili znakovito niži od onih u materničnom tkivu zdravih mliječnih krava. Egzosomni miR-433 dobiven iz EEC-a prevodi se u susjedne EEC-ove stimulirane LPS-om fuzijom egzosomskih vezikula, čime se regulira izlučivanje upalnih čimbenika u epitelu endometrija mliječnih krava s endometritisom, što dodatno utječe na razvoj endometritisa. Zaključno, intenzitet ekspresije miR-433 smanjio se u epitelnim i stromalnim stanicama maternične šupljine i egzomima dobivenim iz epitela endometrija u mliječnih krava s endometritisom, što u određenoj mjeri potiče razvoj i progresiju endometritisa u mliječnih krava

Striking Isotopologue-Dependent Photodissociation Dynamics of Water Molecules:The Signature of an Accidental Resonance

Investigations of the photofragmentation patterns of both light and heavy water at the state-to-state level are a prerequisite for any thorough understanding of chemical processing and isotope heterogeneity in the interstellar medium. Here we reveal dynamical features of the dissociation of water molecules following excitation to the (C) over tilde (010) state using a tunable vacuum ultraviolet source in combination with the high-resolution H(D)-atom Rydberg tagging time-of-flight technique. The action spectra for forming H(D) atoms and the OH(OD) product state distributions resulting from excitation to the (C) over tilde (010) states of H2O and D2O both show striking differences, which are attributable to the effects of an isotopologue-specific accidental resonance. Such accidental-resonance-induced state mixing may contribute to the D/H isotope heterogeneity in the solar system. The present study provides an excellent example of competitive state-to-state nonadiabatic decay pathways involving at least five electronic states

Оценка воздействия техногенных вод предприятия железорудной промышленности на систему водных объектов северной Карелии с учетом природных условий

Цель работы заключалась в оценке влияния предприятий железорудной промышленности на водную среду с учетом природных и техногенных факторов формирования вод и в разработке нормативов допустимого сброса техногенных вод на примере Костомукшского ГОК (Республика Карелия)

Ultraviolet photochemistry of ethane:implications for the atmospheric chemistry of the gas giants

Chemical processing in the stratospheres of the gas giants is driven by incident vacuum ultraviolet (VUV) light. Ethane is an important constituent in the atmospheres of the gas giants in our solar system. The present work describes translational spectroscopy studies of the VUV photochemistry of ethane using tuneable radiation in the wavelength range 112 ≤ λ ≤ 126 nm from a free electron laser and event-triggered, fast-framing, multi-mass imaging detection methods. Contributions from at least five primary photofragmentation pathways yielding CH(2), CH(3) and/or H atom products are demonstrated and interpreted in terms of unimolecular decay following rapid non-adiabatic coupling to the ground state potential energy surface. These data serve to highlight parallels with methane photochemistry and limitations in contemporary models of the photoinduced stratospheric chemistry of the gas giants. The work identifies additional photochemical reactions that require incorporation into next generation extraterrestrial atmospheric chemistry models which should help rationalise hitherto unexplained aspects of the atmospheric ethane/acetylene ratios revealed by the Cassini–Huygens fly-by of Jupiter

Rotational and Nuclear-Spin Level Dependent Photodissociation Dynamics of H₂S

The photodissociation dynamics of small molecules in the vacuum ultraviolet range can have key implications for astrochemical modelling, but revealing such dynamical details is a challenging task. Here the authors, combining high resolution experimental techniques, provide a detailed description of the fragmentation dynamics of selected rotational levels of a predissociated Rydberg state of H2S

Hydroxyl super rotors from vacuum ultraviolet photodissociation of water

Free electron lasers provide a state-of-the-art tool to investigate the photochemistry of water. Here, the authors show that highly rotationally excited hydroxyl radicals, so-called “super rotors” existing above the bond dissociation energy, are observed from the photodissociation of water, which may have implications for understanding the interstellar medium

A Multi-Task Learning and Knowledge Selection Strategy for Environment-Induced Color-Distorted Image Restoration

Existing methods for restoring color-distorted images in specific environments typically focus on a singular type of distortion, making it challenging to generalize their application across various types of color-distorted images. If it were possible to leverage the intrinsic connections between different types of color-distorted images and coordinate their interactions during model training, it would simultaneously enhance generalization, address potential overfitting and underfitting issues during data fitting, and consequently lead to a positive performance boost. In this paper, our approach primarily addresses three distinct types of color-distorted images, namely dust-laden images, hazy images, and underwater images. By thoroughly exploiting the unique characteristics and interrelationships of these types, we achieve the objective of multitask processing. Within this endeavor, identifying appropriate correlations is pivotal. To this end, we propose a knowledge selection and allocation strategy that optimally distributes the features and correlations acquired by the network from the images to different tasks, enabling a more refined task differentiation. Moreover, given the challenge of difficult dataset pairing, we employ unsupervised learning techniques and introduce novel Transformer blocks, feedforward networks, and hybrid modules to enhance context relevance. Through extensive experimentation, we demonstrate that our proposed method significantly enhances the performance of color-distorted image restoration