Fibroblast growth factor 21 (FGF21) is a stress-inducible hormone that has important roles in regulating energy balance and glucose and lipid homeostasis through a heterodimeric receptor complex ...comprising FGF receptor 1 (FGFR1) and β-klotho. Administration of FGF21 to rodents or non-human primates causes considerable pharmacological benefits on a cluster of obesity-related metabolic complications, including a reduction in fat mass and alleviation of hyperglycaemia, insulin resistance, dyslipidaemia, cardiovascular disorders and non-alcoholic steatohepatitis (NASH). However, native FGF21 is unsuitable for clinical use owing to poor pharmacokinetic and biophysical properties. A large number of long-acting FGF21 analogues and agonistic monoclonal antibodies for the FGFR1-β-klotho receptor complexes have been developed. Several FGF21 analogues and mimetics have progressed to early phases of clinical trials in patients with obesity, type 2 diabetes mellitus and NASH. In these trials, the primary end points of glycaemic control have not been met, whereas substantial improvements were observed in dyslipidaemia, hepatic fat fractions and serum markers of liver fibrosis in patients with NASH. The complexity and divergence in pharmacology and pathophysiology of FGF21, interspecies variations in FGF21 biology, the possible existence of obesity-related FGF21 resistance and endogenous FGF21 inactivation enzymes represent major obstacles to clinical implementation of FGF21-based pharmacotherapies for metabolic diseases.
Iron deficiency, even in the absence of anemia, can be debilitating, and exacerbate any underlying chronic disease, leading to increased morbidity and mortality. Iron deficiency is frequently ...concomitant with chronic inflammatory disease; however, iron deficiency treatment is often overlooked, partially due to the heterogeneity among clinical practice guidelines. In the absence of consistent guidance across chronic heart failure, chronic kidney disease and inflammatory bowel disease, we provide practical recommendations for iron deficiency to treating physicians: definition, diagnosis, and disease-specific diagnostic algorithms. These recommendations should facilitate appropriate diagnosis and treatment of iron deficiency to improve quality of life and clinical outcomes.
•Malignant and benign tumor abstract patterns are explored by K-SVM respectively.•Similarities of tumors and abstract patterns is used for prediction model training.•K-SVM reduces feature space ...dimensions significantly.•Based on the WDBC dataset, the prediction model accuracy was at 97.38% by K-SVM.•K-SVM saves the training time dramatically without losing prediction accuracy.
With the development of clinical technologies, different tumor features have been collected for breast cancer diagnosis. Filtering all the pertinent feature information to support the clinical disease diagnosis is a challenging and time consuming task. The objective of this research is to diagnose breast cancer based on the extracted tumor features. Feature extraction and selection are critical to the quality of classifiers founded through data mining methods. To extract useful information and diagnose the tumor, a hybrid of K-means and support vector machine (K-SVM) algorithms is developed. The K-means algorithm is utilized to recognize the hidden patterns of the benign and malignant tumors separately. The membership of each tumor to these patterns is calculated and treated as a new feature in the training model. Then, a support vector machine (SVM) is used to obtain the new classifier to differentiate the incoming tumors. Based on 10-fold cross validation, the proposed methodology improves the accuracy to 97.38%, when tested on the Wisconsin Diagnostic Breast Cancer (WDBC) data set from the University of California – Irvine machine learning repository. Six abstract tumor features are extracted from the 32 original features for the training phase. The results not only illustrate the capability of the proposed approach on breast cancer diagnosis, but also shows time savings during the training phase. Physicians can also benefit from the mined abstract tumor features by better understanding the properties of different types of tumors.
Microplastic pollution in inland waters is receiving growing attentions. Reservoirs are suspected to be particularly vulnerable to microplastic pollution. However, very limited information is ...currently available on pollution characteristics of microplastics in reservoir ecosystems. This work studied the distribution and characteristics of microplastics in the backwater area of Xiangxi River, a typical tributary of the Three Gorges Reservoir. Microplastics were detected in both surface water and sediment with concentrations ranging from 0.55 × 105 to 342 × 105 items km–2 and 80 to 864 items m–2, respectively. Polyethylene, polypropylene, and polystyrene were identified in surface water, whereas polyethylene, polypropylene, and polyethylene terephthalate, and pigments were observed in sediment. In addition, microplastics were also detected in the digestion tracts of 25.7% of fish samples, and polyethylene and nylon were identified. Redundancy analysis indicates a weak correlation between microplastics and water quality variables but a negative correlation with water level of the reservoir and Secchi depth. Results from this study confirm the presence of high abundance microplastics in reservoir impacted tributaries, and suggest that water level regulated hydrodynamic condition and input of nonpoint sources are important regulators for microplastic accumulation and distribution in the backwater area of reservoir tributaries.
The design of synthetic routes by retrosynthetic logic is decisively influenced by the transformations available. Transition‐metal‐catalyzed C−H activation has emerged as a powerful strategy for C−C ...bond formation, with myriad methods developed for diverse substrates and coupling partners. However, its uptake in total synthesis has been tepid, partially due to their apparent synthetic intractability, as well as a lack of comprehensive guidelines for implementation. This Review addresses these issues and offers a guide to identify retrosynthetic opportunities to generate C−C bonds by C−H activation processes. By comparing total syntheses accomplished using traditional approaches and recent C−H activation methods, this Review demonstrates how C−H activation enabled C−C bond construction has led to more efficient retrosynthetic strategies, as well as the execution of previously unattainable tactical maneuvers. Finally, shortcomings of existing processes are highlighted; this Review illustrates how some highlighted total syntheses can be further economized by adopting next‐generation ligand‐enabled approaches.
The advent of new synthetic methods has historically motivated the evolution of retrosynthetic logic. A significant recent advance is C−C bond formation enabled by C−H activation, but it has only seen modest application in synthesis. This Review compares traditional synthetic routes towards complex targets with reconceptualized ones utilizing C−H activation, highlighting the strategic advantages of this powerful approach.
•The review covers plant and animal protein stabilised emulsions.•The review covers protein dynamics and affinity to the oil–water interface.•The review discusses mechanisms of emulsion ...instability.•The review discusses the effect of polysaccharides on protein-stabilised emulsions.
Proteins are of great interest due to their amphiphilic nature, which allows them to reduce the interfacial tension at the oil–water interface. The incorporation of proteins at the oil–water interface has allowed scientists to utilise them to form emulsions (O/W or W/O), which may be used in food formulations, drug and nutrient delivery. The systematic study of the proteins at the interface and the factors that affect their stability (i.e., conformation, pH, solvent conditions, and thermal treatment) has allowed for a broader use of these emulsions tailored for various applications. In this review, the factors affecting the stability of emulsions using food proteins will be discussed. The use of polysaccharides to complex with proteins will also be explored in relation to enhancing emulsion stability.
We develop a model in which cognitive and affective trust in the leader mediate the relationship between leader behavior and team psychological states that, in turn, drive team performance. The model ...is tested on a sample of 191 financial services teams in Hong Kong and the U.S. Servant leadership influenced team performance through affect-based trust and team psychological safety. Transformational leadership influenced team performance indirectly through cognition-based trust. Cognition-based trust directly influenced team potency and indirectly (through affect-based trust) influenced team psychological safety. The effects of leader behavior on team performance were fully mediated through the trust in leader variables and the team psychological states. Servant leadership explained an additional 10% of the variance in team performance beyond the effect of transformational leadership. We discuss implications of these results for research on the relationship between leader behavior and team performance, and for efforts to enhance leader development by combining knowledge from different leadership theories.
During the past 15 years, most large pharmaceutical companies have decreased the screening of natural products for drug discovery in favor of synthetic compound libraries. Main reasons for this ...include the incompatibility of natural product libraries with high-throughput screening and the marginal improvement in core technologies for natural product screening in the late 1980s and early 1990s. Recently, the development of new technologies has revolutionized the screening of natural products. Applying these technologies compensates for the inherent limitations of natural products and offers a unique opportunity to re-establish natural products as a major source for drug discovery. Examples of these new advances and technologies are described in this review.
While learning analytics (LA) practices have been shown to be practical and effective, most of them require a huge amount of data and effort. This paper reports a case study which demonstrates the ...feasibility of practising LA at a low cost for instructors to identify at-risk students in an undergraduate business quantitative methods course. Instead of using tracking data from a learning management system as predictive variables, this study utilised clicker responses as formative assessments, together with student demographic data and summative assessments. This LA practice makes use of free cloud services, Google Forms and Google Sheets in particular for collecting and analysing clicker data. Despite a small dataset being used, the LA implementation was effective in identifying at-risk students at an early stage. A systematic proactive advising approach is proposed as an intervention strategy based on students' at-risk probability estimated by a prediction model. The result shows that the intervention success rate increases correspondingly with the number of interventions and the intervention effects on peer groups are far more successful than on individual students. Overall, the students' pass rate in the study was 7% higher than that for the whole course. Practical recommendations and concerns about using linear regression and logistic regression for classification are also discussed.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NMLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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