冷型小麦旗叶衰老和活性氧代谢特性研究

以典型的冷型小麦和暖型小麦为试验材料,研究了同一环境背景下不同温度型小麦开花后的旗叶衰老和活性氧代谢特性。结果表明,与暖型小麦相比,冷型小麦籽料灌浆期旗叶叶绿素和可溶性蛋白质含量下降缓慢、含量高,整个业粒形成和灌浆期ＭＤＡ积累速度慢、含量低,籽粒灌浆期防御活性氧伤害的关键性保护酶（ＳＯＤ、ＣＡＴ和ＰＯＤ）活性下隆幅度小,灌浆中后期活性水平高。由此认为,小麦旗叶衰老和活性氧代谢特性与其温度型的归属关     

Operant Procedures for Assessing Behavioral Flexibility in Rats

Executive functions consist of multiple high-level cognitive processes that drive rule generation and behavioral selection. An emergent property of these processes is the ability to adjust behavior in response to changes in one’s environment (i.e., behavioral flexibility). These processes are essential to normal human behavior, and may be disrupted in diverse neuropsychiatric conditions, including schizophrenia, alcoholism, depression, stroke, and Alzheimer’s disease. Understanding of the neurobiology of executive functions has been greatly advanced by the availability of animal tasks for assessing discrete components of behavioral flexibility, particularly strategy shifting and reversal learning. While several types of tasks have been developed, most are non-automated, labor intensive, and allow testing of only one animal at a time. The recent development of automated, operant-based tasks for assessing behavioral flexibility streamlines testing, standardizes stimulus presentation and data recording, and dramatically improves throughput. Here, we describe automated strategy shifting and reversal tasks, using operant chambers controlled by custom written software programs. Using these tasks, we have shown that the medial prefrontal cortex governs strategy shifting but not reversal learning in the rat, similar to the dissociation observed in humans. Moreover, animals with a neonatal hippocampal lesion, a neurodevelopmental model of schizophrenia, are selectively impaired on the strategy shifting task but not the reversal task. The strategy shifting task also allows the identification of separate types of performance errors, each of which is attributable to distinct neural substrates. The availability of these automated tasks, and the evidence supporting the dissociable contributions of separate prefrontal areas, makes them particularly well-suited assays for the investigation of basic neurobiological processes as well as drug discovery and screening in disease models.     

植酶Q9对大田遮阴夏玉米产量和衰老特性的调控作用

黄淮海夏季太阳辐射量降低以及种植密度增加引起了夏玉米冠层光照不足,产量大幅降低。本试验选用夏玉米品种‘登海605'(DH605)为试验材料,设置3个遮阴处理:花粒期遮阴(S₁)、穗期遮阴(S₂)和全生育期遮阴(S₃),以大田自然光照为对照(CK),并选用化控试剂植酶Q9(原液稀释100倍)对遮阴处理和CK进行外源调控,即花粒期遮阴-植酶Q9(S₁Q)、穗期遮阴-植酶Q9(S₂Q)、全生育期遮阴-植酶Q9(S₃Q)及大田自然光照-植酶Q9(CKQ),化控处理以同时期喷施清水为对照,探讨植酶Q9对大田遮阴夏玉米衰老特性的调控作用。结果表明: 遮阴显著降低了夏玉米的叶面积指数(LAI)、功能叶片叶绿素相对含量值(SPAD值)和净光合速率,进而显著降低了夏玉米产量。同时,遮阴夏玉米穗位叶的超氧物歧化酶(SOD)、过氧化物酶(POD)、过氧化氢酶(CAT)活性显著降低,丙二醛(MDA)、游离脯氨酸含量显著增加,可溶性蛋白含量显著降低。喷施植酶Q9后,S₃Q和S₂Q的LAI、功能叶片SPAD值和净光合速率显著提高;S₃Q、S₂Q、S₁Q的MDA和游离脯氨酸含量显著降低,可溶性蛋白含量和POD活性显著提高,S₂Q、S₃Q各时期的SOD和CAT活性显著提高;S₃Q、S₂Q、S₁Q的产量分别较S₃、S₂、S₁平均提高19%、8%、7%,CKQ与CK间无显著差异。因此,喷施植酶Q9通过提高弱光胁迫下夏玉米的光合能力,延缓叶片的衰老,增加产量,可有效缓解弱光胁迫导致的减产危害。     

The JAK1/2 inhibitor ruxolitinib delays premature aging phenotypes

Hutchinson–Gilford progeria syndrome (HGPS) is caused by an LMNA mutation that results in the production of the abnormal progerin protein. Children with HGPS display phenotypes of premature aging and have an average lifespan of 13 years. We found earlier that the targeting of the transmembrane protein PLA2R1 overcomes senescence and improves phenotypes in a mouse model of progeria. PLA2R1 is regulating the JAK/STAT signaling, but we do not yet know whether targeting this pathway directly would influence cellular and in vivo progeria phenotypes. Here, we show that JAK1/2 inhibition with ruxolitinib rescues progerin‐induced cell cycle arrest, cellular senescence, and misshapen nuclei in human normal fibroblasts expressing progerin. Moreover, ruxolitinib administration reduces several premature aging phenotypes: bone fractures, bone mineral content, grip strength, and a trend to increase survival in a mouse model of progeria. Thus, we propose that ruxolitinib, an FDA‐approved drug, should be further evaluated as a drug candidate in HGPS therapy.     

Cellular senescence in osteoarthritis pathology

Cellular senescence is a state of stable proliferation arrest of cells. The senescence pathway has many beneficial effects and is seen to be activated in damaged/stressed cells, as well as during embryonic development and wound healing. However, the persistence and accumulation of senescent cells in various tissues can also impair function and have been implicated in the pathogenesis of many age‐related diseases. Osteoarthritis (OA), a severely debilitating chronic condition characterized by progressive tissue remodeling and loss of joint function, is the most prevalent disease of the synovial joints, and increasing age is the primary OA risk factor. The profile of inflammatory and catabolic mediators present during the pathogenesis of OA is strikingly similar to the secretory profile observed in ‘classical’ senescent cells. During OA, chondrocytes (the sole cell type present within articular cartilage) exhibit increased levels of various senescence markers, such as senescence‐associated beta‐galactosidase (SAβGal) activity, telomere attrition, and accumulation of p16ink4a. This suggests the hypothesis that senescence of cells within joint tissues may play a pathological role in the causation of OA. In this review, we discuss the mechanisms by which senescent cells may predispose synovial joints to the development and/or progression of OA, as well as touching upon various epigenetic alterations associated with both OA and senescence.     

A hidden Markov movement model for rapidly identifying behavioral states from animal tracks

Electronic telemetry is frequently used to document animal movement through time. Methods that can identify underlying behaviors driving specific movement patterns can help us understand how and why animals use available space, thereby aiding conservation and management efforts. For aquatic animal tracking data with significant measurement error, a Bayesian state‐space model called the first‐Difference Correlated Random Walk with Switching (DCRWS) has often been used for this purpose. However, for aquatic animals, highly accurate tracking data are now becoming more common. We developed a new hidden Markov model (HMM) for identifying behavioral states from animal tracks with negligible error, called the hidden Markov movement model (HMMM). We implemented as the basis for the HMMM the process equation of the DCRWS, but we used the method of maximum likelihood and the R package TMB for rapid model fitting. The HMMM was compared to a modified version of the DCRWS for highly accurate tracks, the DCRWS, and to a common HMM for animal tracks fitted with the R package moveHMM. We show that the HMMM is both accurate and suitable for multiple species by fitting it to real tracks from a grey seal, lake trout, and blue shark, as well as to simulated data. The HMMM is a fast and reliable tool for making meaningful inference from animal movement data that is ideally suited for ecologists who want to use the popular DCRWS implementation and have highly accurate tracking data. It additionally provides a groundwork for development of more complex modeling of animal movement with TMB. To facilitate its uptake, we make it available through the R package swim.