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Chemical exchange between silicate magmas and carbonate rocks has major implications for igneous fractionation, atmospheric CO2 flux, and formation of mineral deposits. However, this process is only partly understood, and long-standing questions of whether, where, and how carbonate rocks can be digested by silicate melts remain controversial. We describe evidence for pervasive chemical exchange between silicate melt and carbonate rock in a shallow porphyry setting driven by limestone assimilation. Melt inclusions in endoskarn from the Chating Cu-Au deposit in eastern China reveal that the calc-silicate assemblage (diopside + andradite ± wollastonite ± epidote) was molten at the time of skarn formation and coexisted with CO2 vapor as well as sulfate- and chloride-salt melts. Hence, we argue that endoskarn at Chating formed by crystallization of an immiscible calc-silicate melt produced by assimilation of carbonate rock, aided by the presence of sulfate and other fluxes, which in turn promoted desilication of the intruding magma and drove vigorous CO2 release.

Cisplatin is one of the most effective chemotherapy drugs and is widely used for cancer treatment. However, its clinical use is limited by nephrotoxicity. Emerging findings suggested that both ferroptosis and mitochondrial dysfunction mediate cisplatin-induced nephrotoxicity. In the current study, a novel 3-phenylglutaric acid derivative 5-[[2-(4-methoxyphenoxy)-5-(trifluoromethyl)phenyl]amino]-5-oxo-3-phenylpentanoic acid (referred to as 84-B10) was found to play a protective role in cisplatin-induced acute kidney injury with no tumor promoting effects. A genome-wide transcriptome analysis indicated that the protective effect of 84-B10 might be dependent on antagonizing ferroptosis. In accordance, lipid peroxide accumulation and downregulation of key ferroptosis suppressors were reversed using 84-B10 treatment both in vivo and in vitro. In addition, 84-B10 inhibited cisplatin-induced mitochondrial damage and mitochondrial reactive oxygen species (mtROS) production and restored superoxide dismutases (SODs). Furthermore, 84-B10 showed similar therapeutic effects to MnTBAP (a cell-permeable SOD mimetic) in eliminating mtROS, restoring mitochondrial homeostasis, and inhibiting ferroptosis under cisplatin challenge. Comparable effects of 84-B10 and liproxstatin-1 in ameliorating cisplatin-induced ferroptosis were observed. However, liproxstatin-1 failed to prevent mitochondrial dysfunction. These data indicated that mtROS might act upstream of cisplatin-induced tubular ferroptosis. Taken together, the novel 3-phenylglutaric acid derivative 84-B10 showed therapeutic potential against cisplatin-induced nephrotoxicity possibly by restoring mitochondria homeostasis and inhibiting mtROS-induced ferroptosis, which suggests the potential use of 84-B10 in preventing and treating cisplatin-nephrotoxicity.

Anion substitution is a valid strategy to modulate the active sites of the transition metal dichalcogenides (TMDs). Herein, a series of cobalt sulfoselenide nanomeshes (CoS

Enzymatic interesterification (EIE) of beef tallow (BT) blended with soybean oil (SO), peanut oil (PO) and canola oil (CO) in different proportions were analyzed in terms of the fatty acid compositions, thermal properties (melting and crystallization behaviors), rheological properties, hardness, crystal, and microstructure to achieve their sufficient utilization. The content of saturated fatty acids in all interesterified oils (IOs) decreased gradually with the increase of plant oil content in base stock. The higher the proportion of plant oil in the base stock, the lower the enthalpy of IOs. All IOs were in the solid-like state, and the hardness of all IOs met the requirements of traditional plastic oil. All IOs were mainly in α and β′ crystal forms and can be used as basic stock for special oils.

Vibrio choleraeis an aquatic bacterium that primarily infects the gastrointestinal tract, causing the severe and potentially deadly diarrheal disease, cholera. Despite the impact ofVibrioon global health, our understanding of host mucosal responses to the pathogen at the site of infection remains limited, highlighting a critical gap in our knowledge that must be addressed to develop more effective prevention and treatment strategies. Using a natural infection model, we combined physiological and single-cell transcriptomic studies to characterize adult zebrafish guts raised under conventional conditions and after a challenge withVibrio. We discovered thatVibriocaused a mild inflammatory response characterized by T cell activation and enhanced antigen capture in the epithelium. Additionally, we discovered thatVibriosuppresses host interferon signaling, and that ectopic activation of interferon significantly increases shedding of live pathogen by the host. Notably, we also found that the adult zebrafish gut shares many similarities with mammalian counterparts, including the presence of previously undescribed Best4+ cells, tuft cells, and transit amplifying cells. These discoveries provide important insights into host-pathogen interactions and emphasize the utility of zebrafish as a natural model ofVibrioinfection.

Background: Renal diseases remain an increasing public health issue affecting millions of people. The kidney is a highly energetic organ that is rich in mitochondria. Numerous studies have demonstrated the important role of mitochondria in maintaining normal kidney function and in the pathogenesis of various renal diseases, including acute kidney injuries (AKI) and chronic kidney diseases (CKD). Summary: Under physiological conditions, fine-tuning mitochondrial energy balance, mitochondrial dynamics (fission and fusion processes), mitophagy, and biogenesis maintain mitochondrial fitness. While under AKI and CKD conditions, disruption of mitochondrial energy metabolism leads to increased oxidative stress. In addition, mitochondrial dynamics shift to excessive mitochondrial fission, mitochondrial autophagy is impaired, and mitochondrial biogenesis is also compromised. These mitochondrial injuries regulate renal cellular functions either directly or indirectly. Mitochondria-targeted approaches, containing genetic (microRNAs) and pharmaceutical methods (mitochondria-targeting antioxidants, mitochondrial permeability pore inhibitors, mitochondrial fission inhibitors, and biogenesis activators) are emerging as important therapeutic strategies for AKI and CKD. Key messages: Mitochondria play a critical role in the pathogenesis of AKI and CKD. This review provides an updated overview of mitochondrial homeostasis under physiological conditions and the involvement of mitochondrial dysfunction in renal diseases. Finally, we summarize the current status of mitochondria-targeted strategies in attenuating renal diseases.

Additional details on geologic background, methods, and results, and Figures S1–S6.

Using 8-benzyloxyisoquinolines as the guests and polymethyl methacrylate as the host, the resultant doped materials show obvious room-temperature phosphorescence activities.

Mycobacterium tuberculosis possesses a dynamic cell envelope, which consists of a peptidoglycan layer, a mycolic acid layer, and an arabinogalactan polysaccharide. This envelope possesses a highly complex and unique structure representing a barrier that protects and assists the growth of M. tuberculosis and allows its adaptation to the host. It regulates the immune response of the host cells, causing their damage. Therefore, the cell envelope of M. tuberculosis is an attractive target for vaccine and drug development. The emergence of multidrug-resistant as well as extensively drug resistant tuberculosis and co-infection with HIV prevented an effective control of this disease. Thus, the discovery and development of new drugs is a major keystone for TB treatment and control. This review mainly summarizes the development of drug enzymes involved in the biosynthesis of the cell wall in M. tuberculosis, and other potential drug targets in this pathway, to provide more effective strategies for the development of new drugs.

This paper proposes a diffusive predator–prey model with Allee effect, time delay and anti-predator behavior. First, the existence and stability of all equilibria are analyzed and the conditions for the appearance of the Hopf bifurcation are studied. Using the normal form and center manifold theory, the formulas which can determine the direction, period and stability of Hopf bifurcation are obtained. Numerical simulations show that the Allee effect can determine the survival abundance of the prey and predator populations, and anti-predator behavior can greatly improve the stability of the coexisting equilibrium.

A host–guest system is constructed using quaternary ammonium salts as the hosts. It is the guest-activated hosts that emit room temperature phosphorescence, rather than the host-assisted guests in traditional doped systems.

Purpose During rush hours, many passengers find it difficult to board the first train due to the insufficient capacity of metro vehicles, namely, left behind phenomenon. In this paper, a data-driven approach is presented to estimate left-behind patterns using automatic fare collection (AFC) data and train timetable data. Design/methodology/approach First, a data preprocessing method is introduced to obtain the waiting time of passengers at the target station. Second, a hierarchical Bayesian (HB) model is proposed to describe the left behind phenomenon, in which the waiting time is expressed as a Gaussian mixture model. Then a sampling algorithm based on Markov Chain Monte Carlo (MCMC) is developed to estimate the parameters in the model. Third, a case of Beijing metro system is taken as an application of the proposed method. Findings The comparison result shows that the proposed method performs better in estimating left behind patterns than the existing Maximum Likelihood Estimation. Finally, three main reasons for left behind phenomenon are summarized to make relevant strategies for metro managers. Originality/value First, an HB model is constructed to describe the left behind phenomenon in a target station and in the target direction on the basis of AFC data and train timetable data. Second, a MCMC-based sampling method Metropolis–Hasting algorithm is proposed to estimate the model parameters and obtain the quantitative results of left behind patterns. Third, a case of Beijing metro is presented as an application to test the applicability and accuracy of the proposed method.

Herein, we present the divergent syntheses of α-arylacylamides and oxindoles via mechanoredox chemistry by using easily accessible α-bromo N-sulfonyl amides as starting materials. Our system consists of a catalytic amount of Cu

Through describing the confusing misdiagnosis process of Liddle syndrome, we try to reveal the importance of accurate aldosterone-renin detection and a genetic test for Liddle syndrome.We found a family of hypertension and hypokalaemia with the proband of a 21-year-old female who had been misdiagnosed as primary aldosteronism (PA). She presented with high aldosterone and low renin levels. Aldosterone is not suppressed in the saline infusion test and captopril challenge test. However, treatment with a standard dose of spironolactone has no blood pressure improvement effect. A heterozygous variant ofThe two kits had nearly opposite results. Among those Liddle syndrome patients confirmed by a genetic test, for Test kit A all ARR were screened positive while for test kit B negative. It seems Test kit B is consistent with the diagnosis while test kit A misleads the diagnosis. A novelinaccurate ARR detection might misdiagnose Liddle syndrome. A Gene test is an important method for the diagnosis of Liddle syndrome. A novel

Tuberculosis (TB) is a life-threatening infectious disease caused by Mycobacterium tuberculosis (M. tuberculosis). Timely diagnosis and effective treatment are essential in the control of TB. Conventional smear microscopy still has low sensitivity and is unable to reveal the drug resistance of this bacterium. The traditional culture-based diagnosis is time-consuming, since usually the results are available after 3–4 weeks. Molecular biology methods fail to differentiate live from dead M. tuberculosis, while diagnostic immunology methods fail to distinguish active from latent TB. In view of these limitations of the existing detection techniques, in addition to the continuous emergence of multidrug-resistant and extensively drug-resistant TB, in recent years there has been an increase in the demand for simple, rapid, accurate and economical point-of-care approaches. This review describes the development, evaluation, and implementation of conventional diagnostic methods for TB and the rapid new approaches for the detection of M. tuberculosis.

Bile acid metabolites have been increasingly recognized as pleiotropic signaling molecules that regulate cardiovascular functions, but their role in mesenchymal stromal cells (MSC)-based therapy has never been investigated. It is found that overexpression of farnesoid X receptor (FXR), a main receptor for bile acids, improves the retention and cardioprotection of adipose tissue-derived MSC (ADSC) administered by intramyocardial injection in mice with myocardial infarction (MI), which shows enhanced antiapoptotic, proangiogenic, and antifibrotic effects. RNA sequencing, LC-MS/MS, and loss-of-function studies reveal that FXR overexpression promotes ADSC paracrine angiogenesis via Angptl4. FXR overexpression improves ADSC survival in vivo but fails in vitro. By performing bile acid-targeted metabolomics using ischemic heart tissue, 19 bile acids are identified. Among them, cholic acid and deoxycholic acid significantly increase Angptl4 secretion from ADSC overexpressing FXR and further improve their proangiogenic capability. Moreover, ADSC overexpressing FXR shows significantly lower apoptosis by upregulating Nqo-1 expression only in the presence of FXR ligands. Retinoid X receptor α is identified as a coactivator of FXR. It is first demonstrated that there is a bile acid pool in the myocardial microenvironment. Targeting the bile acid-FXR axis may be a novel strategy for improving the curative effect of MSC-based therapy for MI.

Visual data stories shown in the form of narrative visualizations such as a poster or a data video, are frequently used in data-oriented storytelling to facilitate the understanding and memorization of the story content. Although useful, technique barriers, such as data analysis, visualization, and scripting, make the generation of a visual data story difficult. Existing authoring tools rely on users' skills and experiences, which are usually inefficient and still difficult. In this paper, we introduce a novel visual data story generating system, Calliope, which creates visual data stories from an input spreadsheet through an automatic process and facilities the easy revision of the generated story based on an online story editor. Particularly, Calliope incorporates a new logic-oriented Monte Carlo tree search algorithm that explores the data space given by the input spreadsheet to progressively generate story pieces (i.e., data facts) and organize them in a logical order. The importance of data facts is measured based on information theory, and each data fact is visualized in a chart and captioned by an automatically generated description. We evaluate the proposed technique through three example stories, two controlled experiments, and a series of interviews with 10 domain experts. Our evaluation shows that Calliope is beneficial to efficient visual data story generation.

The automated detection of distress such as cracks or potholes is a key basis for assessing the condition of pavements and deciding on their maintenance. A fine-grained pavement distress-detection algorithm based on integrated data using a digital twin is proposed to solve the challenges of the insufficiency of high-quality negative samples in specific scenarios An asphalt pavement background model is created based on UAV-captured images, and a lightweight physical engine is used to randomly render 5 types of distress and 3 specific scenarios to the background model, generating a digital twin model that can provide virtual distress data. The virtual data are combined with real data in different virtual-to-real ratios (0:1 to 5:1) to form an integrated dataset and used to fully train deep object detection networks for fine-grained detection. The results show that the YOLOv5 network with the virtual-to-real ratio of 3:1 achieves the best average precision for 5 types of distress (asphalt pavement MAP: 75.40%), with a 2-fold and 1.5-fold improvement compared to models developed without virtual data and with traditional data augmentation, respectively, and achieves over 40% recall in shadow, occlusion and blur. The proposed approach could provide a more reliable and refined automated method for pavement analysis in complex scenarios.

The digital economy is fundamentally altering human productivity and lifestyles, gradually becoming a new engine that drives energy technology transformation and optimizes the energy consumption structure. This paper examines the impact of the digital economy on upgrading the energy consumption structure using panel data from 30 Chinese provinces from 2013 to 2019. The empirical findings indicate that the digital economy’s development can help to improve energy consumption structure, and this impact can have a threshold effect. Heterogeneity analysis reveals that upgrading the energy consumption structure affected by the digital economy is more significant in lower digital divide regions, the eastern and central regions, and provinces with high economic development levels. Moreover, the findings of a mechanism analysis demonstrate that the digital economy primarily influences green technology innovation, and government environmental regulation affects the major upgrades of the energy consumption structure.

At present, the existing dynamic OD estimation methods in an urban rail transit network still need to be improved in the factors of the time-dependent characteristics of the system and the estimation accuracy of the results. This study focuses on predicting the dynamic OD demand for a time of period in the future for an urban rail transit system. We propose a nonlinear programming model to predict the dynamic OD matrix based on historic automatic fare collection (AFC) data. This model assigns the passenger flow to the hierarchical flow network, which can be calibrated by backpropagation of the first-order gradients and reassignment of the passenger flow with the updated weights between different layers. The proposed model can predict the time-varying OD matrix, the number of passengers departing at each time, and the travel time spent by passengers, of which the results are shown in the case study. Finally, the results indicate that the proposed model can effectively obtain a relatively accurate estimation result. The proposed model can integrate more traffic characteristics than traditional methods and provides an effective and hierarchical passenger flow estimation framework. This study can provide a rich set of passenger demand for advanced transit planning and management applications, for instance, passenger flow control, adaptive travel demand management, and real-time train scheduling.