INAUGURAL ARTICLE by a Recently Elected Academy Member:Functional redundancy of type I and type II receptors in the regulation of skeletal muscle growth by myostatin and activin A

Myostatin (MSTN) is a transforming growth factor-β (TGF-β) family member that normally acts to limit muscle growth. The function of MSTN is partially redundant with that of another TGF-β family member, activin A. MSTN and activin A are capable of signaling through a complex of type II and type I receptors. Here, we investigated the roles of two type II receptors (ACVR2 and ACVR2B) and two type I receptors (ALK4 and ALK5) in the regulation of muscle mass by these ligands by genetically targeting these receptors either alone or in combination specifically in myofibers in mice. We show that targeting signaling in myofibers is sufficient to cause significant increases in muscle mass, showing that myofibers are the direct target for signaling by these ligands in the regulation of muscle growth. Moreover, we show that there is functional redundancy between the two type II receptors as well as between the two type I receptors and that all four type II/type I receptor combinations are utilized in vivo. Targeting signaling specifically in myofibers also led to reductions in overall body fat content and improved glucose metabolism in mice fed either regular chow or a high-fat diet, demonstrating that these metabolic effects are the result of enhanced muscling. We observed no effect, however, on either bone density or muscle regeneration in mice in which signaling was targeted in myofibers. The latter finding implies that MSTN likely signals to other cells, such as satellite cells, in addition to myofibers to regulate muscle homeostasis.

Myostatin (MSTN) is a secreted signaling molecule that normally acts to limit skeletal muscle growth (for review, see ref. 1). Mice lacking MSTN exhibit dramatic increases in muscle mass throughout the body, with individual muscles growing to about twice the normal size (2). MSTN appears to play two distinct roles in regulating muscle size, one to regulate the number of muscle fibers that are formed during development and a second to regulate the growth of those fibers postnatally. The sequence of MSTN has been highly conserved through evolution, with the mature MSTN peptide being identical in species as divergent as humans and turkeys (3). The function of MSTN has also been conserved, and targeted or naturally occurring mutations in MSTN have been shown to cause increased muscling in numerous species, including cattle (3–5), sheep (6), dogs (7), rabbits (8), rats (9), swine (10), goats (11), and humans (12). Numerous pharmaceutical and biotechnology companies have developed biologic agents capable of blocking MSTN activity, and these have been tested in clinical trials for a wide range of indications, including Duchenne and facioscapulohumeral muscular dystrophy, inclusion body myositis, muscle atrophy following falls and hip fracture surgery, age-related sarcopenia, Charcot–Marie–Tooth disease, and cachexia due to chronic obstructive pulmonary disease, end-stage kidney disease, and cancer.The finding that certain inhibitors of MSTN signaling can increase muscle mass even in Mstn^−/− mice revealed that the function of MSTN as a negative regulator of muscle mass is partially redundant with at least one other TGF-β family member (13, 14), and subsequent studies have identified activin A as one of these cooperating ligands (15, 16). MSTN and activin A share many key regulatory and signaling components. For example, the activities of both MSTN and activin A can be modulated extracellularly by naturally occurring inhibitory binding proteins, including follistatin (17, 18) and the follistatin-related protein, FSTL-3 or FLRG (19, 20). Moreover, MSTN and activin A also appear to share receptor components. Based on in vitro studies, MSTN is capable of binding initially to the activin type II receptors, ACVR2 and ACVR2B (also called ActRIIA and ActRIIB) (18) followed by engagement of the type I receptors, ALK4 and ALK5 (21). In previous studies, we presented genetic evidence supporting a role for both ACVR2 and ACVR2B in mediating MSTN signaling and regulating muscle mass in vivo. Specifically, we showed that mice expressing a truncated, dominant-negative form of ACVR2B in skeletal muscle (18) or carrying deletion mutations in Acvr2 and/or Acvr2b (13) have significantly increased muscle mass. One limitation of the latter study, however, was that we could not examine the consequence of complete loss of both receptors using the deletion alleles, as double homozygous mutants die early during embryogenesis (22). Moreover, the roles that the two type I receptors, ALK4 and ALK5, play in regulating MSTN and activin A signaling in muscle in vivo have not yet been documented using genetic approaches. Here, we present the results of studies in which we used floxed alleles for each of the type II and type I receptor genes in order to target these receptors alone and in combination in muscle fibers. We show that these receptors are functionally redundant and that signaling through each of these receptors contributes to the overall control of muscle mass.     

Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning

Conservation laws are considered to be fundamental laws of nature. It has broad applications in many fields, including physics, chemistry, biology, geology, and engineering. Solving the differential equations associated with conservation laws is a major branch in computational mathematics. The recent success of machine learning, especially deep learning in areas such as computer vision and natural language processing, has attracted a lot of attention from the community of computational mathematics and inspired many intriguing works in combining machine learning with traditional methods. In this paper, we are the first to view numerical PDE solvers as an MDP and to use (deep) RL to learn new solvers. As proof of concept, we focus on 1-dimensional scalar conservation laws. We deploy the machinery of deep reinforcement learning to train a policy network that can decide on how the numerical solutions should be approximated in a sequential and spatial-temporal adaptive manner. We will show that the problem of solving conservation laws can be naturally viewed as a sequential decision-making process, and the numerical schemes learned in such a way can easily enforce long-term accuracy. Furthermore, the learned policy network is carefully designed to determine a good local discrete approximation based on the current state of the solution, which essentially makes the proposed method a meta-learning approach. In other words, the proposed method is capable of learning how to discretize for a given situation mimicking human experts. Finally, we will provide details on how the policy network is trained, how well it performs compared with some state-of-the-art numerical solvers such as WENO schemes, and supervised learning based approach L3D and PINN, and how well it generalizes.     

铜绿假单胞菌噬菌体PaP3生物学特性的研究

目的测定铜绿假单胞菌噬菌体PaP3的最佳感染复数、一步生长曲线和吸附K值及交叉吸附K值等基本生物学特性。方法按照感染复数（MOI）分别为0．0001、0．001、0．01、0．1、1和10加入噬菌体纯培养液和宿主菌，充分裂解细菌后，测定噬菌体滴度；以MOI=10的比例加入噬菌体及宿主菌，进行一步生长实验；纯化PaP3颗粒，免疫家兔，获得抗血清，通过中和反应实验测定PaP3和其抗血清之间的吸附反应常数K值。同时，利用抗血清交叉中和试验确定本室分离的三株噬菌体之间的血清学关系。结果当MOI=0．001时PaP3感染其宿主菌产生的子代噬菌体滴度最高；根据一步生长实验结果绘制一步生长曲线；通过血清交叉中和反应得出不同的吸附常数。结论PaP3最佳感染复数为0．001，感染宿主菌的潜伏期是20min，爆发期是60min，平均爆发量约为31，其抗血清反应的吸附常数K值为262。     

影响颅脑外伤术后颅内感染的危险因素分析

目的探讨影响颅脑外伤开颅术后颅内感染的危险因素。方法采用回顾性研究比较分析了912例颅脑损伤术后出现颅内感染与未出现颅内感染组间的差异因素。结果非感染 770例,颅内感染142例(15．6％)。感染类型有无菌性脑膜炎、细菌性脑膜炎、脑室炎及脑室积脓、脑脓肿、硬膜下腔积脓、术区皮下或(和)骨瓣下化脓或合并骨髓炎、切口感染。细菌检出率占感染的27．5％。颅脑外伤术后感染与高温季节、高龄、重度以上损伤、短期内两次以上手术、连续两侧开颅术、长时间 (>5 h)手术、显微外科手术、颅底与后颅凹手术、脑室外引流、皮下或硬膜外积液以及急诊手术等因素相关(P<0．05)。结论对具有上述危险冈素的易感患者应给予更密切的关注和预防性的处理。     

医学摄影用光

根据医学摄影不同拍摄对象,结合各种光源特点,介绍了用光的一般方法和掌握的基本原则,对物体的反光控制、透明物体内部结构与质感的表现等难点问题进行了研讨,并对荧光摄影作了简要介绍。     

Correction of frequency and phase variations induced by eddy currents in localized spectroscopy with multiple echo times.

As a consequence of the time-varying magnetic field induced by eddy currents, frequency drifting occurs when the sampling window of localized spectroscopy continuously shifts. The frequency drifting and the concomitant phase variations can severely affect spectroscopy results when data are acquired with multiple echo times (TEs), such as in the measurement of glutamate (Glu) concentration using the TE-averaged method. Specifically, the averaged spectra are further broadened and distorted in the presence of residual eddy currents, and editing of the coupled spins of Glu C4 protons is affected, resulting in errors in the measured relative intensity ratio. Postacquisition correction using unsuppressed water as reference can effectively minimize this detrimental effect, as manifested by the significantly enhanced signal intensity. Also, it is demonstrated that the methyl signals of creatine (Cr) at 3.0 ppm and choline (Cho) at 3.2 ppm can be used as internal references in finding frequency and phase disparities between different TEs.     

主动呼吸控制技术(ABC)在肺癌放射治疗中的应用

目的：使用主动呼吸控制技术（aetive brething control,ABC）治疗非小细胞肺癌患者，评价呼吸运动时肺部肿瘤动度的影响及ABC技术的优势和可行性，并评价近期疗效和急性放射反应。方法：选择9例使用ABC技术联合三维造型放疗技术治疗的非小细胞系癌患者进行分析。CT定位扫描时分别采集ABC和自由呼吸（free breath.FB）状态下的图像，评价呼吸运动对肺部肿瘤动度和PTV边界的影响唾弃；并比较两种计划的DVH，放疗剂量为54-60Gy/18-20次。3Gy/次，1次/天，5天/周，定期随访，评价近期疗效及急性放射反应。结果：应用ABC技术后，隔肌的平均位移从FB时的43.5mm（20.0-32.0mm）降低为3.6mm（0.5-72.mm）,胸壁的侧方位移从FB时的3.2mm（2.8-4.0mm）降低为1.2mm（0.5-1.6mm）.PTV边界可以从FB时的1.5mm减少为0.75cm;肺的V20从21.8%降低为15.0%,减少了30.6%.中位随访6个月时,9例患者中有6例CR,3例PR.急性放射副反应都很轻微,仅为I-II.结论：在肺癌的精确放射治疗中,呼吸动度的影响不可忽视.而ABC系统可以有效的降低呼吸运动时治疗的影响,提高放疗的精确性,减少副反应.,但该系统使用较为复杂,延长了治疗的时间,个别患者不能忍受.