几种椎间盘退变动物模型的建立和应用

椎间盘退变是一种年龄相关的退行性疾病,是引起下腰痛的主要因素,严重影响病人的生活质量,并显著增加家庭的经济负担。目前,缺少椎间盘退变的有效干预和治疗手段,部分原因是其发病机制尚未阐明。椎间盘退变动物模型的构建对于阐明该疾病的病理机制至关重要。椎间盘退变是一个复杂的过程,受机械应力、结构损伤、生物化学与基因表达等多种因素的影响。本文总结了应用异常机械应力、结构损伤、生物化学或化学诱导和基因敲除等方式构建的椎间盘退变动物模型。生物力学是维持椎间盘稳态的重要因素,异常的机械应力会导致椎间盘退变。同时,椎间盘退变常伴随结构性损伤,椎间盘结构破坏也会导致椎间盘发生退变。此外,生物化学或化学诱导和关键基因敲除也会导致椎间盘退变。本文按照造成异常机械应力的因素将机械应力模型分为加压模型和失稳模型;按照椎间盘结构将结构损伤模型分为髓核与纤维环损伤模型和软骨终板损伤模型。总结了生物化学或化学诱导模型以及新型的基因敲除模型。讨论了不同类型椎间盘退变动物模型的可能应用和局限性。     

福建省多花黄精生态适宜性区划研究

通过研究多花黄精(Polygonatum cyrtonema)的生态适宜性,为其野生资源保护及人工规范化栽培提供依据。收集237份多花黄精分布位置和55个生态因子,导入最大熵(MaxEnt)模型运算,结合地理信息系统(GIS)分析其适合生长区域。结果表明,影响多花黄精生态适宜性的主要生态因子是3月降水量、年均降水量、6月降水量、5月降水量、4月降水量、2月降水量和最冷季降水量,在福建省具有广泛适宜生长区域。模型预测结果可靠,可为多花黄精野生资源保护提供参考,并为其科学种植提供指导。     

Forecasting the potential distribution of Spodoptera exigua and S. littoralis (Lepidoptera,Noctuidae) in Iran

The beet armyworm, Spodoptera exigua (Hübner, 1808) and the Egyptian cotton leafworm, S. littoralis (Boisduval, 1833), are amongst the most notorious agricultural pest species in Iran. Spodoptera exigua is considered a serious pest of different crops, whereas S. littoralis is known as an important pest of cotton.In this paper, the potential distribution areas of these species in Iran and the important climatic factors affecting their distribution were predicted using the MaxEnt model and the ArcGIS. The results indicate that the main environmental variables contributing to S. exigua’s distribution were precipitation of the coldest quarter (bio19), average wind speed in April (wind4), and annual precipitation (bio12). Also, minimum temperature of the coldest month (bio6), mean temperature of coldest quarter (bio11), altitude and average wind speed in May (wind5) were dominant climatic factors that affected the potential distribution of S. littoralis. These species overlapped in most parts of coastal areas in the southern and northern parts of Iran, with an average overlapping range of 33.2%. Considering their preferred host plants in Iran, it is necessary to strengthen biosurveillance programes and management of these two species in their suitable areas to prevent further invasion, which endangers agricultural security.     

Population persistence under high mutation rate: From evolutionary rescue to lethal mutagenesis

Populations may genetically adapt to severe stress that would otherwise cause their extirpation. Recent theoretical work, combining stochastic demography with Fisher's geometric model of adaptation, has shown how evolutionary rescue becomes unlikely beyond some critical intensity of stress. Increasing mutation rates may however allow adaptation to more intense stress, raising concerns about the effectiveness of treatments against pathogens. This previous work assumes that populations are rescued by the rise of a single resistance mutation. However, even in asexual organisms, rescue can also stem from the accumulation of multiple mutations in a single genome. Here, we extend previous work to study the rescue process in an asexual population where the mutation rate is sufficiently high so that such events may be common. We predict both the ultimate extinction probability of the population and the distribution of extinction times. We compare the accuracy of different approximations covering a large range of mutation rates. Moderate increase in mutation rates favors evolutionary rescue. However, larger increase leads to extinction by the accumulation of a large mutation load, a process called lethal mutagenesis. We discuss how these results could help design “evolution‐proof” antipathogen treatments that even highly mutable strains could not overcome.     

Slip-induced fall-risk assessment based on regular gait pattern in older adults

Aging-associated fall-risk assessment is crucial for fall prevention. Thus, this study aimed to develop a prognostic model to predict fall-risk following an unexpected over-ground slip perturbation based on normal gait pattern in healthy older adults. 112 healthy older adults who experienced a novel slip in a safe laboratory environment were included. Their slip trial and natural walking trial immediately prior to it were analyzed. To identify the best fall-risk predictive model, gait related variables including step length, segment angles, center of mass state, and ground reaction force (GRF) were determined and inputted into a stepwise logistic regression. The optimal slip-induced fall prediction model was based on the right thigh angle at slipping foot touchdown (TD), the maximum GRF of the slipping limb after TD, and the momentum change from TD to recovery foot liftoff (LO), with an overall prediction accuracy of 75.9%, predicting 74.5% of falls (sensitivity) and 77.2% of recoveries (specificity). Conversely, a model based on clinical and demographic measures predicted 78.2% of falls and 47.4% of recoveries, resulting in a much lower overall accuracy of 62.5%. The fall-risk model based on normal gait pattern which was developed for slip-induced perturbations in healthy older adults was able to provide a high predictive accuracy. This information could provide insight about the ideal normal gait measures which could be used to contribute towards development of therapeutic strategies related to dynamic balance and fall prevention to enhance preventive interventions in populations with high-risk for slip-induced falls.     

Esophageal stress softening recovery is altered in STZ-induced diabetic rats

This study investigated stress softening recovery in intact, separated muscle and mucosa-submucosa esophageal tubes in streptozotocin-induced diabetic rats. Fifteen Wistar rats were made diabetic (DM group) by intraperitoneal injection of 50 mg kg⁻¹ streptozotocin and another 11 rats served as Sham group by injection of saline. All rats survived for 8-weeks. Three series of inflation-deflation loadings at luminal pressure levels of 0.5, 1.0 and 2.0 kPa were carried out on different esophageal tubes. Five distension cycles on each pressure level were done in Ca⁺⁺-free Krebs solution before and after KCl activation in Ca⁺⁺-containing Krebs solution. The wall stiffness and stored energy recovery were compared between two groups. The stiffness was biggest in the DM group for the intact tube at pressure 0.5 kPa (P < 0.01) and for the muscle tube at all pressure levels (P < 0.05). Energy recovery induced by stress softening and stiffness loss recovery were significantly smaller in the DM group than in the Sham group for the intact esophagus and separated tubes at all pressure levels (P < 0.05, P < 0.01). In conclusion, the reversible stress softening and passive stiffness recovery were altered in STZ-induced diabetic rats. This study fills a gap in the knowledge about diabetes-induced esophageal remodeling.     

A study on the protective effects of CpG oligodeoxynucleotide-induced mucosal immunity against lung injury in a mouse acute respiratory distress syndrome model

This study aims to determine the feasibility of using oligodeoxynucleotides with unmethylated cytosine-guanine dinucleotide sequences (CpG ODN) as an immunity protection strategy for a mouse model of acute respiratory distress syndrome (ARDS). This is a prospective laboratory animal investigation. Twenty-week-old BALB/c mice in Animal research laboratory were randomized into groups. An ARDS model was induced in mice using lipopolysaccharides (LPSs). CpG ODN was intranasally and transrectally immunized before or after the 3rd and 7th days of establishing the ARDS model. Mice were euthanized on Day 7 after the second immunization. Then, retroorbital bleeding was carried out and the chest was rapidly opened to collect the trachea and tissues from both lungs for testing. CpG ODN significantly improved the pathologic impairment in mice lung, especially after the intranasal administration of 50 μg. This resulted in the least severe lung tissue injury. Furthermore, interleukin-6 (IL-6) and IL-8 concentrations were lower, which was second to mice treated with the rectal administration of 20 µg CpG ODN. In contrast, the nasal and rectal administration of CpG ODN in BALB/c mice before LPS immunization did not appear to exhibit any significant protective effects. The intranasal administration of CpG ODN may be a potential treatment approach to ARDS. More studies are needed to further determine the protective mechanism of CpG ODN.     

Identification of esophageal cancer pathway deviation and construction of a diagnosis model using three kernel genes

The purpose of this study is to better understand the role of interleukin 35 (IL35) in esophageal carcinoma by comparing the mRNA level in Barrett's esophageal mucosa and in matched normal squamous mucosa and to understand how the diagnosis model works with two other genes: hepatocyte nuclear factor 1B (HNF1B) and cAMP responsive element binding protein 3-like 1 (CREB3L1). By comparing carcinoma tissue and normal tissue samples, we extracted all the differentially expressed mRNAs. The bioinformatics analysis resulted in the discovery of three prominent genes. Eventually, the three genes were utilized to train a deep-learning model. An additional wet experiment was conducted to validate the effect of IL35. All the differentially expressed genes were enriched into nine groups, each of which has specific biological functions. Given that the three significant genes HNF1B, CREB3L1, and IL35 as diagnostic features, a deep-learning model was constructed, reaching an accuracy of 93% in the training set and 87% in the test set. Our findings suggest that IL35, along with the other two signatures, can distinguish esophageal tumor samples from normal samples precisely.     

Factors associated with black bear density and implications for management

Wildlife density estimates are important to accurately formulate population management objectives and understand the relationship between habitat characteristics and a species’ abundance. Despite advances in density and abundance estimation methods, management of common game species continues to be challenged by a lack of reliable population estimates. In Washington, USA, statewide American black bear (Ursus americanus) abundance estimates are predicated on density estimates derived from research in the 1970s and are hypothesized to be a function of precipitation and vegetation, with higher densities in western Washington. To evaluate current black bear density and landscape relationships in Washington, we conducted a 4-year capture-recapture study in 2 areas of the North Cascade Mountains using 2 detection methods, non-invasive DNA collection and physical capture and deployment of global positioning system (GPS) collars. We integrated GPS telemetry from collared bears with spatial capture-recapture (SCR) data and created a SCR-resource selection model to estimate density as a function of spatial covariates and test the hypothesis that density is higher in areas with greater vegetative food resources. We captured and collared 118 bears 132 times and collected 7,863 hair samples at hair traps where we identified 537 bears from 1,237 detections via DNA. The most-supported model in the western North Cascades depicted a negative relationship between black bear density and an index of human development. We estimated bear density at 20.1 bears/100 km², but density varied from 13.5/100 km² to 27.8 bears/100 km² depending on degree of human development. The model best supported by the data in the eastern North Cascades estimated an average density of 19.2 bears/100 km², which was positively correlated with primary productivity, with resulting density estimates ranging from 7.1/100 km² to 33.6 bears/100 km². The hypothesis that greater precipitation and associated vegetative production in western Washington supports greater bear density compared to eastern Washington was not supported by our data. In western Washington, empirically derived average density estimates (including cubs) were nearly 50% lower than managers expected prior to our research. In eastern Washington average black bear density was predominantly as expected, but localized areas of high primary productivity supported greater than anticipated bear densities. Our findings underscore the importance that black bear density is not likely uniform and management risk may be increased if an average density is applied at too large a scale. Disparities between expected and empirically derived bear density illustrate the need for more rigorous monitoring to understand processes that affect population numbers throughout the jurisdiction, and suggest that management plans may need to be reevaluated to determine if current harvest strategies are achieving population objectives. © 2019 The Wildlife Society.     

Matching habitat choice promotes species persistence under climate change

Species may survive under contemporary climate change by either shifting their range or adapting locally to the warmer conditions. Theoretical and empirical studies recently underlined that dispersal, the central mechanism behind these responses, may depend on the match between an individuals’ phenotype and local environment. Such matching habitat choice is expected to induce an adaptive gene flow, but it now remains to be studied whether this local process could promote species’ responses to climate change. Here, we investigate this by developing an individual‐based model including either random dispersal or temperature‐dependent matching habitat choice. We monitored population composition and distribution through space and time under climate change. Relative to random dispersal, matching habitat choice induced an adaptive gene flow that lessened spatial range loss during climate warming by improving populations’ viability within the range (i.e. limiting range fragmentation) and by facilitating colonization of new habitats at the cold margin. The model even predicted range contraction under random dispersal but range expansion under optimal matching habitat choice. These benefits of matching habitat choice for population persistence mostly resulted from adaptive immigration decision and were greater for populations with larger dispersal distance and higher emigration probability. We also found that environmental stochasticity resulted in suboptimal matching habitat choice, decreasing the benefits of this dispersal mode under climate change. However population persistence was still better under suboptimal matching habitat choice than under random dispersal. Our results highlight the urgent need to implement more realistic mechanisms of dispersal such as matching habitat choice into models predicting the impacts of ongoing climate change on biodiversity.