Physiologic Electrical Fields Direct Retinal Ganglion Cell Axon Growth In Vitro.

PurposeThe purpose of this study was to characterize the ability of applied electrical fields (EFs) to direct retinal ganglion cell (RGC) axon growth as well as to assess whether Rho GTPases play a role in translating electrical cues to directional cues.MethodsFull-thickness, early postnatal mouse retina was cultured in electrotaxis chambers and exposed to EFs of varying strengths (50-200 mV/mm). The direction of RGC axon growth was quantified from time-lapsed videos. The rate of axon growth and responsiveness to changes in EF polarity were also assessed. The effect of toxin B, a broad-spectrum inhibitor of Rho GTPase signaling, and Z62954982, a selective inhibitor of Rac1, on EF-directed growth was determined.ResultsIn the absence of an EF, RGC axons demonstrated indiscriminate directional growth from the explant edge. Retinal cultures exposed to an EF of 100 and 200 mV/mm showed markedly asymmetric growth, with 74.2% and 81.2% of axons oriented toward the cathode, respectively (P < 0.001). RGC axons responded to acute changes in EF polarity by redirecting their growth toward the "new" cathode. This galvanotropic effect was partially neutralized by toxin B and Rac1 inhibitor Z62954982.ConclusionsRGC axons exhibit cathode-directed growth in the presence of an EF. This effect is mediated in part by the Rho GTPase signaling cascade

Towards Integrated Traffic Control with Operating Decentralized Autonomous Organization

With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS that is capable of considering plentiful heterogeneous intelligent agents is desired. However, existing control methods based on the centralized or the decentralized scheme have not presented their competencies in considering the optimality and the scalability simultaneously. To address this issue, we propose an integrated control method based on the framework of Decentralized Autonomous Organization (DAO). The proposed method achieves a global consensus on energy consumption efficiency (ECE), meanwhile to optimize the local objectives of all involved intelligent agents, through a consensus and incentive mechanism. Furthermore, an operation algorithm is proposed regarding the issue of structural rigidity in DAO. Specifically, the proposed operation approach identifies critical agents to execute the smart contract in DAO, which ultimately extends the capability of DAO-based control. In addition, a numerical experiment is designed to examine the performance of the proposed method. The experiment results indicate that the controlled agents can achieve a consensus faster on the global objective with improved local objectives by the proposed method, compare to existing decentralized control methods. In general, the proposed method shows a great potential in developing an integrated control system in the ITSComment: 6 pages, 6 figures. To be published in 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC

Detection of various fusion genes by one-step RT-PCR and the association with clinicopathological features in 242 cases of soft tissue tumor

Introduction: Over the past decades, an increasing number of chromosomal translocations have been found in different STSs, which not only has value for clinical diagnosis but also suggests the pathogenesis of STS. Fusion genes can be detected by FISH, RT-PCR, and next-generation sequencing. One-step RT-PCR is a convenient method to detect fusion genes with higher sensitivity and lower cost.Method: In this study, 242 cases of soft tissue tumors were included, which were detected by one-step RT-PCR in multicenter with seven types of tumors: rhabdomyosarcoma (RMS), peripheral primitive neuroectodermal tumor (pPNET), synovial sarcoma (SS), myxoid liposarcomas (MLPS), alveolar soft part sarcoma (ASPS), dermatofibrosarcoma protuberans (DFSP), and soft tissue angiofibroma (AFST). 18 cases detected by one-step RT-PCR were further tested by FISH. One case with novel fusion gene detected by RNA-sequencing was further validated by one-step RT-PCR.Results: The total positive rate of fusion genes was 60% (133/213) in the 242 samples detected by one-step RT-PCR, in which 29 samples could not be evaluated because of poor RNA quality. The positive rate of PAX3–FOXO1 was 88.6% (31/35) in alveolar rhabdomyosarcoma, EWSR1–FLI1 was 63% (17/27) in pPNET, SYT–SSX was 95.4% in SS (62/65), ASPSCR1–TFE3 was 100% in ASPS (10/10), FUS–DDIT3 was 80% in MLPS (4/5), and COL1A1–PDGFB was 66.7% in DFSP (8/12). For clinicopathological parameters, fusion gene status was correlated with age and location in 213 cases. The PAX3–FOXO1 fusion gene status was correlated with lymph node metastasis and distant metastasis in RMS. Furthermore, RMS patients with positive PAX3–FOXO1 fusion gene had a significantly shorter overall survival time than those patients with the negative fusion gene. Among them, the FISH result of 18 cases was concordant with one-step RT-PCR. As detected as the most common fusion types of AHRR–NCOA2 in one case of AFST were detected as negative by one-step RT-PCR. RNA-sequencing was used to determine the fusion genes, and a novel fusion gene PTCH1–PLAG1 was found. Moreover, the fusion gene was confirmed by one-step RT-PCR.Conclusion: Our study indicates that one-step RT-PCR displays a reliable tool to detect fusion genes with the advantage of high accuracy and low cost. Moreover, it is a great tool to identify novel fusion genes. Overall, it provides useful information for molecular pathological diagnosis and improves the diagnosis rate of STSs

Stereotaxical Infusion of Rotenone: A Reliable Rodent Model for Parkinson's Disease

A clinically-related animal model of Parkinson's disease (PD) may enable the elucidation of the etiology of the disease and assist the development of medications. However, none of the current neurotoxin-based models recapitulates the main clinical features of the disease or the pathological hallmarks, such as dopamine (DA) neuron specificity of degeneration and Lewy body formation, which limits the use of these models in PD research. To overcome these limitations, we developed a rat model by stereotaxically (ST) infusing small doses of the mitochondrial complex-I inhibitor, rotenone, into two brain sites: the right ventral tegmental area and the substantia nigra. Four weeks after ST rotenone administration, tyrosine hydroxylase (TH) immunoreactivity in the infusion side decreased by 43.7%, in contrast to a 75.8% decrease observed in rats treated systemically with rotenone (SYS). The rotenone infusion also reduced the DA content, the glutathione and superoxide dismutase activities, and induced alpha-synuclein expression, when compared to the contralateral side. This ST model displays neither peripheral toxicity or mortality and has a high success rate. This rotenone-based ST model thus recapitulates the slow and specific loss of DA neurons and better mimics the clinical features of idiopathic PD, representing a reliable and more clinically-related model for PD research

Impact of cardiac arrest centers on the survival of patients with nontraumatic out‐of‐hospital cardiac arrest : a systematic review and meta‐analysis

Background The role of cardiac arrest centers (CACs) in out‐of‐hospital cardiac arrest care systems is continuously evolving. Interpretation of existing literature is limited by heterogeneity in CAC characteristics and types of patients transported to CACs. This study assesses the impact of CACs on survival in out‐of‐hospital cardiac arrest according to varying definitions of CAC and prespecified subgroups. Methods and Results Electronic databases were searched from inception to March 9, 2021 for relevant studies. Centers were considered CACs if self‐declared by study authors and capable of relevant interventions. Main outcomes were survival and neurologically favorable survival at hospital discharge or 30 days. Meta‐analyses were performed for adjusted odds ratio (aOR) and crude odds ratios. Thirty‐six studies were analyzed. Survival with favorable neurological outcome significantly improved with treatment at CACs (aOR, 1.85 [95% CI, 1.52–2.26]), even when including high‐volume centers (aOR, 1.50 [95% CI, 1.18–1.91]) or including improved‐care centers (aOR, 2.13 [95% CI, 1.75–2.59]) as CACs. Survival significantly increased with treatment at CACs (aOR, 1.92 [95% CI, 1.59–2.32]), even when including high‐volume centers (aOR, 1.74 [95% CI, 1.38–2.18]) or when including improved‐care centers (aOR, 1.97 [95% CI, 1.71–2.26]) as CACs. The treatment effect was more pronounced among patients with shockable rhythm ( P =0.006) and without prehospital return of spontaneous circulation ( P =0.005). Conclusions were robust to sensitivity analyses, with no publication bias detected. Conclusions Care at CACs was associated with improved survival and neurological outcomes for patients with nontraumatic out‐of‐hospital cardiac arrest regardless of varying CAC definitions. Patients with shockable rhythms and those without prehospital return of spontaneous circulation benefited more from CACs. Evidence for bypassing hospitals or interhospital transfer remains inconclusive

Rough-Number-Based Multiple-Criteria Group Decision-Making Method by Combining the BWM and Prospect Theory

Multicriteria group decision-making (MCGDM) problems have been a research hotspot in recent years, and prospect theory is introduced to cope with the risk and imprecision in the process of decision-making. To guarantee the effectiveness of information aggregation and extend the feasibility of prospect theory, this paper proposes a novel decision-making approach based on rough numbers and prospect theory to solve risky and uncertain MCGDM problems. Firstly by combining rough numbers and the best-worst method (BWM), we construct a linear programming model to calculate rough criteria weights, which are defined by lower limitations and upper limitations. Then for the imprecision of value function and weighting function in prospect theory, we propose a novel method with the aid of combining rough numbers and prospect theory to handle the risk in decision-making problems. Finally, a numerical example involving investment is introduced to illustrate the application and validity of the proposed method

Optimal Advertising Budget Allocation across Markets with Different Goals and Various Constraints

Advertising budget allocation across multiple markets has drawn considerable attention in recent years. To expand previous research and fill a gap in the current literature, this study proposes two decision models for optimal budget allocation decisions across multimarkets with different goals and various constraints. In addition to the market parameters proposed by the Vidale–Wolfe model, the present study incorporates market goals and advertising objectives into budget allocation decisions. Different types of markets are defined in terms of the goal set for market share or profit. Given the characteristics of different markets, two separate decision models are developed. Model I aims to maximize sales volume given a fixed advertising budget, while model II seeks to minimize the advertising budget given a total of targeted sales volume for all the markets. Solutions to the two models are discussed, and a numerical example is provided to demonstrate how to apply the models in making budget allocation decision