Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

Co?N graphene encapsulated cobalt catalyst for H2O2 decomposition under acidic conditions

Hydrogen peroxide (H₂O₂) has been listed as one of the 100 most important chemicals in the world. However, huge amount of residual H₂O₂ is hard to timely decomposed into O₂ and H₂O under acidic condition, easily resulting in explosion hazard. Here, we reported a core–shell structure catalyst, that is graphene with Co N structure encapsulated Co nanoparticles. Co N graphene shell serves as the active site for the H₂O₂ decomposition, and Co core further enhance this decomposition. Benefiting from it, the H₂O₂ decomposition were close to 100% after 6 cycles without pH adjustment, which increased 6 orders of magnitude compared with no catalyst. At the same time, the O₂ generation reached 99.67% in 2 h with little metal leaching, and ·OH has been greatly inhibited to only 0.08%. This work can cleanly remove H₂O₂ with little deep oxidation and protect the process of H₂O₂ utilization to achieve a safer world.     

Identification of Novel Fragments Binding to the PDZ1-2 Domain of PSD-95

Inhibition of PSD-95 has emerged as a promising strategy for the treatment of ischemic stroke, as shown with peptide-based compounds that target the PDZ domains of PSD-95. In contrast, developing potent and drug-like small molecules against the PSD-95 PDZ domains has so far been unsuccessful. Here, we explore the druggability of the PSD-95 PDZ1-2 domain and use fragment screening to investigate if this protein is prone to binding small molecules. We screened 2500 fragments by fluorescence polarization (FP) and validated the hits by surface plasmon resonance (SPR), including an inhibition counter-test, and found four promising fragments. Three ligand efficient fragments were shown by ¹H,¹⁵N HSQC NMR to bind in the small hydrophobic P⁰ pockets of PDZ1-2, and one of them underwent structure-activity relationship (SAR) studies. Overall, we demonstrate that fragment screening can successfully be applied to PDZ1-2 of PSD-95 and disclose novel fragments that can serve as starting points for optimization towards small-molecule PDZ domain inhibitors.     

The Impact of the ‘Mis-Peptidome’ on HLA Class I-Mediated Diseases: Contribution of ERAP1 and ERAP2 and Effects on the Immune Response

The strong association with the Major Histocompatibility Complex (MHC) class I genes represents a shared trait for a group of autoimmune/autoinflammatory disorders having in common immunopathogenetic basis as well as clinical features. Accordingly, the main risk factors for Ankylosing Spondylitis (AS), prototype of the Spondyloarthropathies (SpA), the Behçet’s disease (BD), the Psoriasis (Ps) and the Birdshot Chorioretinopathy (BSCR) are HLA-B*27, HLA-B*51, HLA-C*06:02 and HLA-A*29:02, respectively. Despite the strength of the association, the HLA pathogenetic role in these diseases is far from being thoroughly understood. Furthermore, Genome-Wide Association Studies (GWAS) have highlighted other important susceptibility factors such as Endoplasmic Reticulum Aminopeptidase (ERAP) 1 and, less frequently, ERAP2 that refine the peptidome presented by HLA class I molecules to CD8⁺ T cells. Mass spectrometry analysis provided considerable knowledge of HLA-B*27, HLA-B*51, HLA-C*06:02 and HLA-A*29:02 immunopeptidome. However, the combined effect of several ERAP1 and ERAP2 allelic variants could generate an altered pool of peptides accounting for the “mis-immunopeptidome” that ranges from suboptimal to pathogenetic/harmful peptides able to induce non-canonical or autoreactive CD8⁺ T responses, activation of NK cells and/or garbling the classical functions of the HLA class I molecules. This review will focus on this class of epitopes as possible elicitors of atypical/harmful immune responses which can contribute to the pathogenesis of chronic inflammatory diseases.     

Activity of Riminophenazines against Mycobacterium tuberculosis: A Review of Studies that Might be Contenders for Use as Antituberculosis Agents

Tuberculosis is one of the leading cause of death in the world, mainly due to the increasing number of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) strains. Factors such as the HIV pandemic contribute further. Also, the ineffectiveness of the chemotherapy in current use increases the mortality rate. Therefore, new and repurposed antituberculosis drugs are urgently needed for the treatment of MDR-TB, and riminophenazines are among those drugs that are being reinvestigated for their potential in the treatment of TB. This review delivers a brief historical account of riminophenazines, their general synthesis, mechanisms of action, and their physicochemical properties. The discussion is limited to those studies that investigated the activity of these compounds as antituberculosis agents. Given their unique properties, this review will be of great significance in giving direction towards the design and development of new riminophenazine analogues.     

Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients

We define the emerging research field of applied data science as the knowledge discovery process in which analytic systems are designed and evaluated to improve the daily practices of domain experts. We investigate adaptive analytic systems as a novel research perspective of the three intertwining aspects within the knowledge discovery process in healthcare: domain and data understanding for physician- and patient-centric healthcare, data preprocessing and modelling using natural language processing and (big) data analytic techniques, and model evaluation and knowledge deployment through information infrastructures. We align these knowledge discovery aspects with the design science research steps of problem investigation, treatment design, and treatment validation, respectively. We note that the adaptive component in healthcare system prototypes may translate to data-driven personalisation aspects including personalised medicine. We explore how applied data science for patient-centric healthcare can thus empower physicians and patients to more effectively and efficiently improve healthcare. We propose meta-algorithmic modelling as a solution-oriented design science research framework in alignment with the knowledge discovery process to address the three key dilemmas in the emerging “post-algorithmic era” of data science: depth versus breadth, selection versus configuration, and accuracy versus transparency.     

基于声源定位的高校在线巡课系统设计与研究

随着网络建设以及信息化教学方法在高校教学过程中的应用普及,越来越多的高校使用在线巡课系统对教师的教学过程进行跟踪和管理,以便发现课堂教学中的亮点、问题和不足。文章提出的在线巡课系统,基于声源定位的技术,对传统的在线巡课系统做出了改进,解决了已有巡课系统中“只闻其声,不见其人”的问题,能够更直观地跟踪到教师的教学过程,包括教学行为以及师生互动过程,有效提升教务人员巡课效果和体验感受。     

Design,Synthesis, Radiosynthesis and Biological Evaluation of Fenretinide Analogues as Anticancer and Metabolic Syndrome-Preventive Agents

Fenretinide (4-HPR) is a synthetic derivative of all-trans-retinoic acid (ATRA) characterised by improved therapeutic properties and toxicological profile relative to ATRA. 4-HPR has been mostly investigated as an anti-cancer agent, but recent studies showed its promising therapeutic potential for preventing metabolic syndrome. Several biological targets are involved in 4-HPR's activity, leading to the potential use of this molecule for treating different pathologies. However, although 4-HPR displays quite well-understood multitarget promiscuity with regards to pharmacology, interpreting its precise physiological role remains challenging. In addition, despite promising results in vitro, the clinical efficacy of 4-HPR as a chemotherapeutic agent has not been satisfactory so far. Herein, we describe the preparation of a library of 4-HPR analogues, followed by the biological evaluation of their anti-cancer and anti-obesity/diabetic properties. The click-type analogue 3 b showed good capacity to reduce the amount of lipid accumulation in 3T3-L1 adipocytes during differentiation. Furthermore, it showed an IC₅₀ of 0.53±0.8 μM in cell viability tests on breast cancer cell line MCF-7, together with a good selectivity (SI=121) over noncancerous HEK293 cells. Thus, 3 b was selected as a potential PET tracer to study retinoids in vivo, and the radiosynthesis of [¹⁸F] 3b was successfully developed. Unfortunately, the stability of [¹⁸F] 3b turned out to be insufficient to pursue imaging studies.     

Weighted preliminary-summation-based principal component analysis for non-Gaussian processes

For industrial chemical process, preliminary-summation-based principal component analysis (PS-PCA), an amended PCA method was recently provided for coping with both Gaussian and non-Gaussian characteristics. By summing the training and monitoring data respectively, PS-PCA is capable of resolving the issue of non-Gaussian processes and achieves higher fault detection rate than the traditional PCA. However, in the PS-PCA summation operation, all data samples are regarded as the same weight, which results in the fault information of newly-samples may be diluted, leading to significant detection delays. To address this challenge, in this paper, we propose a novel weighted PS-PCA (WPS-PCA) method that employs an exponential weighting scheme to put more emphasis on recent information. Subsequently, a mathematical argument demonstrates that when the number of variables is enough plentiful, the obtained summation combined with the generalized central limit theorem conforms to approximately a Gaussian distribution. The kurtosis relationships indicate this conversion will bring out well-pleasing feasibility for conventional PCA. Ultimately, the proposed technique verifies detection performance using the Tennessee Eastman process, which is compared with the existing PCA and PS-PCA schemes, in terms of the fault detection time and fault detection rate. The simulation studies reveal that the proposed method is efficient and superior.