Quantifying personal exposure to air pollution from smartphone‐based location data

Personal exposure assessment is a challenging task that requires both measurements of the state of the environment as well as the individual's movements. In this paper, we show how location data collected by smartphone applications can be exploited to quantify the personal exposure of a large group of people to air pollution. A Bayesian approach that blends air quality monitoring data with individual location data is proposed to assess the individual exposure over time, under uncertainty of both the pollutant level and the individual location. A comparison with personal exposure obtained assuming fixed locations for the individuals is also provided. Location data collected by the Earthquake Network research project are employed to quantify the dynamic personal exposure to fine particulate matter of around 2500 people living in Santiago (Chile) over a 4‐month period. For around 30% of individuals, the personal exposure based on people movements emerges significantly different over the static exposure. On the basis of this result and thanks to a simulation study, we claim that even when the individual location is known with nonnegligible error, this helps to better assess personal exposure to air pollution. The approach is flexible and can be adopted to quantify the personal exposure based on any location‐aware smartphone application.     

内固定与关节置换手术治疗骨质疏松性髋部骨折的临床效果及术后并发症的影响因素分析

目的:分析内固定与关节置换手术治疗骨质疏松性髋部骨折的临床效果及其术后并发症的影响因素。方法:将2017年4月至2018年5月因骨质疏松性髋部骨折于我院进行手术治疗的78例患者作为研究对象,参考患者自身意愿按照采取手术方案的不同将所有患者分为内固定组与关节置换组。内固定组主要采用动力髋螺钉内固定治疗;关节置换组采用全髋关节置换术治疗。对比分析两组治疗后并发症的发生情况及关节功能恢复程度。结果:关节置换组手术治疗后关节功能的恢复情况显著优于内固定组(P0.05),术后并发症发生率低于内固定组(P0.05);患者术后并发症发生的主要影响因素包括:术前存在合并症、手术时机≥2h、采用内固定手术。结论:与内固定术相比,关节置换手术治疗骨质疏松性髋部骨折患者的疗效和安全性均更高,但采用该手术治疗时需注意手术操作的规范性及手术时机。     

A critical evaluation of the conformational requirements of fusogenic peptides in membranes

It is generally assumed that fusogenic peptides would require a certain conformation, which triggers or participates in the rate-determining step of membrane fusion. Previous structure analyses of the viral fusion peptide from gp41 of HIV-1 have yielded contradictory results, showing either an α-helical or a β-stranded conformation under different conditions. To find out whether either of these conformations is relevant in the actual fusion process, we have placed sterically demanding substitutions into the fusion peptide FP23 to prevent or partially inhibit folding and self-assembly. A single substitution of either D- or L-CF₃-phenylglycine was introduced in different positions of the sequence, and the capability of these peptide analogues to fuse large unilamellar vesicles was monitored by lipid mixing and dynamic light scattering. If fusion proceeds via a β-stranded oligomer, then the D- and L-epimers are expected to differ systematically in their activity, since the D-epimers should be unable to form β-structures due to sterical hindrance. If an α-helical conformation is relevant for fusion, then the D-epimers would be slightly disfavoured compared to the L-forms, hence a small systematic difference in fusion activity should be observed. Interestingly, we find that (1) all D- and L-epimers are fusogenically active, though to different extents compared to the wild type, and – most importantly – (ii) there is no systematic preference for either the D- or L-forms. We therefore suggest that a well-structured α-helical peptide conformation or a β-stranded oligomeric assembly can be excluded as the rate-determining state. Instead, fusion appears to involve conformationally disordered peptides with a pronounced structural plasticity. Dedicated to Prof. K. Arnold on the occasion of this 65th birthday.     

Novel two-stage processes for optimal chemical production in microbes

Microbial metabolism can be harnessed to produce a broad range of industrially important chemicals. Often, three key process variables: Titer, Rate and Yield (TRY) are the target of metabolic engineering efforts to improve microbial hosts toward industrial production. Previous research into improving the TRY metrics have examined the efficacy of having distinct growth and production stages to achieve enhanced productivity. However, these studies assumed a switch from a maximum growth to a maximum production phenotype. Hence, phenotypes with intermediate growth and chemical production in each of the growth and production stages of two-stage processes are yet to be explored. The impact of reduced growth rates on substrate uptake adds to the need for intelligent choice of operating points while designing two-stage processes. In this work, we develop a computational framework that scans the phenotypic space of microbial metabolism to identify ideal growth and production phenotypic targets, to achieve optimal TRY targets. Using this framework, with Escherichia coli as a model organism, we compare two-stage processes that use dynamic pathway regulation, with one-stage processes that use static intervention strategies, for different bioprocess objectives. Our results indicate that two-stage processes with intermediate growth during the production stage always result in optimal TRY values even in cases where substrate uptake is limited due to reduced growth during chemical production. By analyzing the flux distributions for the production enhancing strategies, we identify key reactions and reaction subsystems that require perturbation to achieve a production phenotype for a wide range of metabolites in E. coli. Interestingly, flux perturbations that increase phosphoenolpyruvate and NADPH availability are enriched among these production phenotypes. Furthermore, reactions in the pentose phosphate pathway emerge as key control nodes that function together to increase the availability of precursors to most products in E. coli. The inherently modular nature of microbial metabolism results in common reactions and reaction subsystems that need to be regulated to modify microbes from their target of growth to the production of a diverse range of metabolites. Due to the presence of these common patterns in the flux perturbations, we propose the possibility of a universal production strain.     

Modeling of dynamical systems through deep learning

This review presents a modern perspective on dynamical systems in the context of current goals and open challenges. In particular, our review focuses on the key challenges of discovering dynamics from data and finding data-driven representations that make nonlinear systems amenable to linear analysis. We explore various challenges in modern dynamical systems, along with emerging techniques in data science and machine learning to tackle them. The two chief challenges are (1) nonlinear dynamics and (2) unknown or partially known dynamics. Machine learning is providing new and powerful techniques for both challenges. Dimensionality reduction methods are used for projecting dynamical methods in reduced form, and these methods perform computational efficiency on real-world data. Data-driven models drive to discover the governing equations and give laws of physics. The identification of dynamical systems through deep learning techniques succeeds in inferring physical systems. Machine learning provides advanced new and powerful algorithms for nonlinear dynamics. Advanced deep learning methods like autoencoders, recurrent neural networks, convolutional neural networks, and reinforcement learning are used in modeling of dynamical systems.     

Evolución clínica y funcional de los pacientes que ingresan en residencias tras una fractura de cadera. Implementación de un programa de intervención multinivel

Background and objectiveThe aim of this study was to determine the clinical and functional outcomes of patients discharged to nursing homes after a hip fracture.MethodsThe study included all patients admitted to a group of nursing homes after a hip fracture in 2016. A geriatric assessment protocol was applied, and patients were treated with a specific protocol for 90 days. They were assessed for nutritional status (Mini-Nutritional Assessment and Body Mass Index), pain (Visual Analogue Scale, and the PAINAD Scale), the presence of pressure ulcers, blood test (D vitamin, haemoglobin, proteins), and functional status (Barthel index and Functional Assessment Categories).ResultsOut of a total of 175 patients, 116 (75%) met the inclusion criteria. The mean age was 84.9 years old (±6.7 SD), and 91 (78.4%) were women. At admission, 73.8% of 65 residents had anaemia, 76.7% hypovitaminosis D, 88% malnutrition or «at risk of malnutrition», and 15.3% had pressure ulcers. After 90 days, the moderate-severe functional status (Barthel index < 60) was reduced from 90.4 to 39.6%, dependence due to gait from 97.3 to 36.1%, and moderate-severe pain from 88.9 to 14.4%. Most of the pressure ulcers healed (94.4%).ConclusionsPatients admitted to nursing homes after a hip fracture had poor clinical and functional status. This study shows that after 90 days from admission these patients had positive outcomes in terms of functionality, gait, pain control, and pressure ulcers healing.     

A label-free nanoparticle aggregation assay for protein complex/aggregate detection and study

The detection, analysis, and understanding of protein complexes/aggregates and their formation process are extremely important for biomolecular research, diagnosis, and biopharmaceutical development. Unfortunately, techniques that can be used conveniently for protein complex/aggregate detection and analysis are very limited. Using gold nanoparticle immunoprobes coupled with dynamic light scattering (DLS), we developed a label-free nanoparticle aggregation immunoassay (NanoDLSay) for protein aggregate detection and study. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), a protein target used routinely in Western blot as a loading control, is demonstrated here as an example. Through this study, we discovered that GAPDH has a strong tendency to form large aggregates in certain buffer solutions at a concentration range of 10-25 μg/ml. The strong light scattering property of gold nanoparticles immunoprobes greatly enhanced the sensitivity of the dynamic light scattering for protein complex/aggregate detection. In contrast to fluorescence techniques for protein complex and aggregation study, the protein targets do not need to be labeled with fluorescent probe molecules in NanoDLSay. NanoDLSay is a very convenient and sensitive tool for protein complex/aggregate detection and study.     

Crystal structure of a carbohydrate induced homodimer of phospholipase A2 from Bungarus caeruleus at 2.1A resolution

This is the first crystal structure of a carbohydrate induced dimer of phospholipase A(2) (PLA(2)). This is an endogenous complex formed between two PLA(2) molecules and two mannoses. It was isolated from Krait venom (Bungarus caeruleus) and crystallized as such. The complete amino acid sequence of PLA(2) was determined using cDNA method. Three-dimensional structure of the complex has been solved with molecular replacement method and refined to a final R-factor of 0.192 for all the data in the resolution range 20.0-2.1A. The presence of mannose molecules in the protein crystals was confirmed using dinitrosalicylic acid test and the molecular weight of the dimer was verified with MALDI-TOF. As indicated by dynamic light scattering and analytical ultracentrifugation the dimer was also stable in solution. The good quality non-protein electron density at the interface of two PLA(2) molecules enabled us to model two mannoses. The mannoses are involved extensively in interactions with protein atoms of both PLA(2) molecules. Some of the critical amino acid residues such as Asp 49 and Tyr 31, which are part of the substrate-binding site, are found facing the interface and interacting with mannoses. The structure of the complex clearly shows that the dimerization is caused by mannoses and it results in the loss of enzymatic activity.     

Mathematical modeling of cell growth in a 3D scaffold and validation of static and dynamic cultures

Tissue engineering, an immensely important field in contemporary clinical practices, aims at the repair or replacement of damaged tissues. The mathematical model proposed herein shows the distribution and growth of cells in their characteristic time in a 3D scaffold model. This study contributes to the progress of simulation techniques in static and dynamic cultures of bone tissue. Brinkman, nutrient transport, and cell growth equations are brought together to quantify the growth behavior of cells. However, when a static culture is being studied, the Brinkman equation is eliminated. The model was validated by experimental cell culture using 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay and scanning electron microscopy. Then, static and dynamic cultures were compared to assess the cell density and cell distribution in the scaffold. Cell counting after 21 days of cell culture showed that the number of cells increased 42‐fold in static and 53.5‐fold in dynamic cultures, which was in good agreement with our model estimations (37‐fold increase in the number of cells in static and 49‐fold increase in dynamic cultures). In conclusion, our mathematical model could predict cell distribution and growth in the scaffold.     

切开与闭合复位空心钉内固定对移位股骨颈骨折患者骨折复位质量和髋关节功能的影响

摘要 目的：探讨切开与闭合复位空心钉内固定对移位股骨颈骨折患者骨折复位质量和髋关节功能的影响。方法：本研究为回顾性研究,选取98例移位股骨颈骨折患者的临床资料,根据手术方式的不同将患者分为A组（n=50,切开复位）和B组（n=48,闭合复位）,比较两组患者优良率、骨折复位质量、髋关节功能、围术期指标、术后并发症发生率和二次手术发生率。结果：A组患者术后6个月的优良率为78.00%（39/50）,高于B组的58.33%（28/48）（P<0.05）。两组术后负重下地时间、术中透视时间比较无差异（P>0.05）;B组手术时间、住院时间短于A组,术中出血量少于A组（P<0.05）。两组患者术后1个月、术后3个月、术后6个月髋关节功能Harris评分均较术前升高,且A组高于B组（P<0.05）。两组二次手术及并发症发生率比较无差异（P>0.05）。A组Ⅰ型、Ⅱ型的例数均多于B组,Ⅲ型例数少于B组（P<0.05）。结论：与闭合复位空心钉内固定相比,切开复位空心钉内固定虽损伤较大,但其术后骨折复位质量和髋关节功能改善效果更佳,且不增加并发症发生率和二次手术发生率。