Mitochondrial Genome of Strophopteryx fasciata (Plecoptera: Taeniopterygidae), with a Phylogenetic Analysis of Nemouroidea.

Taeniopterygidae is a medium-sized family of stoneflies. The phylogeny of Taeniopterygidae was widely accepted based on the morphological analyses. However, there are different opinions based on molecular data. To date, only two taeniopterygid mitochondrial genomes (mitogenomes) were available, and more sampling is needed to obtain precise phylogenetic relationships. In this research, the Strophopteryx fasciata mitogenome was sequenced and analyzed. The complete mitogenome of S. fasciata was 15,527 bp in length and contained 37 genes and a non-coding control region. Among taeniopterygid mitogenomes, the length variation was minimal in protein-coding genes (PCGs), transfer RNA genes (tRNAs) and ribosomal RNA genes (rRNAs), but very different in the control region. Similar to mitogenomes of other taeniopterygid species, the S. fasciata mitogenome was consistently AT biased and displayed positive AT- and negative GC-skews of the whole mitogenome. Most PCGs used ATN as the start codon and TAA/TAG as the stop codon. The stop codons were far less variable than the start codons in taeniopterygid mitogenomes. All Ka/Ks ratios were less than 1, indicating the presence of purifying selection in these genes. The secondary structures of transfer and ribosomal RNA genes of S. fasciata mitogenome are highly conserved with other taeniopterygid species. In the control region of the S. fasciata mitogenome, some essential elements (tandem repeats, stem-loop structures, and poly-N stretch, etc.) were observed. Two phylogenetic trees were inferred from Bayesian inference (BI) and Maximum Likelihood (ML) methods generated the identical topology across the PCGR dataset. The relationships of five families in Nemouroidea were recovered as Leuctridae + ((Capniidae + Taeniopterygidae) + (Nemouridae + Notonemouridae)). These results will help us understand the mitogenome structure of taeniopterygid species and the evolutionary relationship within Plecoptera.

Estimation of Time-Frequency Muscle Synergy in Wrist Movements.

Muscle synergy analysis is a kind of modularized decomposition of muscles during exercise controlled by the central nervous system (CNS). It can not only extract the synergistic muscles in exercise, but also obtain the activation states of muscles to reflect the coordination and control relationship between muscles. However, previous studies have mainly focused on the time-domain synergy without considering the frequency-specific characteristics within synergy structures. Therefore, this study proposes a novel method, named time-frequency non-negative matrix factorization (TF-NMF), to explore the time-varying regularity of muscle synergy characteristics of multi-channel surface electromyogram (sEMG) signals at different frequency bands. In this method, the wavelet packet transform (WPT) is used to transform the time-scale signals into time-frequency dimension. Then, the NMF method is calculated in each time-frequency window to extract the synergy modules. Finally, this method is used to analyze the sEMG signals recorded from 8 muscles during the conversion between wrist flexion (WF stage) and wrist extension (WE stage) movements in 12 healthy people. The experimental results show that the number of synergy modules in wrist flexion transmission to wrist extension (Motion Conversion, MC stage) is more than that in the WF stage and WE stage. Furthermore, the number of flexor and extensor muscle synergies in the frequency band of 0-125 Hz during the MC stage is more than that in the frequency band of 125-250 Hz. Further analysis shows that the flexion muscle synergies mostly exist in the frequency band of 140.625-156.25 Hz during the WF stage, and the extension muscle synergies appear in the frequency band of 125-156.25 Hz during the WE stage. These results can help to better understand the time-frequency features of muscle synergy, and expand study perspective related to motor control in nervous system.

Muscle activation patterns and muscle synergies reflect different modes of coordination during upper extremity movement.

A core issue in motor control is how the central nervous system generates and selects the muscle activation patterns necessary to achieve a variety of behaviors and movements. Extensive studies have verified that it is the foundation to induce a complex movement by the modular combinations of several muscles with a synergetic relationship. However, a few studies focus on the synergetic similarity and dissimilarity among different types of movements, especially for the upper extremity movements. In this study, we introduced the non-negative matrix factorization (NMF) method to explore the muscle activation patterns and synergy structure under 6 types of movements, involving the hand open (HO), hand close (HC), wrist flexion (WF), wrist extension (WE), supination (SU), and pronation (PR). For this, we enrolled 10 healthy subjects to record the electromyography signal for NMF calculation. The results showed a highly modular similarity of the muscle synergy among subjects under the same movement. Furthermore, Spearman's correlation analysis indicated significant similarities among HO-WE, HO-SU, and WE-SU (p < 0.001). Additionally, we also found shared synergy and special synergy in activation patterns among different movements. This study confirmed the theory of modular structure in the central nervous system, which yields a stable synergetic pattern under the same movement. Our findings on muscle synergy will be of great significance to motor control and even to clinical assessment techniques.

Mitochondrial genome of Arcynopteryx dichroa (McLachlan, 1872) (Plecoptera: Perlodidae) and phylogenetic analysis.

To better understand the diversity and phylogeny of Perlodidae, we sequenced and annotated the complete mitochondrial genome (mitogenome) of Arcynopteryx dichroa. This mitogenome was 16,215 bp long and encoded 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), 2 ribosomal RNA unit genes (rRNAs), and a control region like other plecopteran. The nucleotide composition of A. dichroa mitochondrial genome obviously biases toward A and T. The A + T content of the whole mitochondrial genome, the PCGs, tRNAs, rRNAs, and the control region were: 69.3%, 67.6%, 69.8%, 71.3%, and 78.7%. Phylogenetic relationship based on the concatenated sequences of 13 PCGs and two ribosomal RNAs showed that the family Perlodidae and Chloroperlidae are sister relationship, family Perlidae being the sister group to the clade (Perlodidae + Chloroperlidae). The monophyly of the family Perlodidae is well supported but the subfamily Perlodinae and Isoperlinae are not monophyletic groups.

[Therapeutic effects and prognostic factors for the limited-stage small cell lung cancer treated with multidisciplinary therapy].

OBJECTIVE: To study the differences of objective response rate (ORR), side effects and survival among patients with limited-stage small cell lung cancer (LD-SCLC), who received concurrent chemoradiotherapy, sequential chemoradiotherapy or chemotherapy alone, and to analyze the influencing factors on their survival. METHODS: One hundred and sixty-six patients diagnosed as LD-SCLC in Peking Union Medical College Hospital from January 2000 to December 2009 were included in this study. The differences of objective response rates, side effects and survival rates were analyzed by χ2 test. Kaplan-Meier test was used to calculate the overall survival (OS) and progress-free survival (PFS). Cox regression was used to detect the influencing factors on survival time of the patients. RESULTS: The patients were divided into three groups: concurrent chemoradiotherapy (49 cases), sequential chemoradiotherapy (62 cases) and chemotherapy alone (55 cases). The chemotherapy was based on CE/EP regimen, with an average cycle of 5.2. Radiotherapy was of a common or 3-dimensional conformal technology, for regular segmentation irradiation with an average dose of 49.6 Gy. The total ORR was 73.4%, OS and PFS were 22.9 months and 10.8 months, 1, 3, 5-year survival rates were 82.7%, 31.8%, 18.6%, respectively. For the concurrent group, sequential group and chemotherapy alone group, the ORR was 89.4%, 67.2% and 66.0%, respectively. Compared the chemotherapy alone group and concurrent group with the sequential group, there were significant differences (P<0.05). For the concurrent group, sequential group and chemotherapy alone group, the median OS was 29.7 months, 22.6 months, and 19.5 months; the median PFS was 12.7 months, 10.8 months, and 9.8 months, respectively, with a non-significant difference between each two groups (P>0.05). For the concurrent group, sequential group and chemotherapy alone group, the 1-year survival rates were 91.1%, 86.3%, and 65.6%, the 3-year survival rates were 44.2%, 28.3% and 22.8%, and the 5-year survival rates were 24.2%, 21.4% and 11.1%, respectively, with significant differences among them (P<0.05). The major side effects were myelosuppression, gastrointestinal reactions, radiation pneumonia and radiation esophagitis. For the concurrent group, sequential group and chemotherapy alone group, the incidence of myelosuppression were 84.4%, 76.8% and 60.0%, respectively, with a significant difference (P=0.008) between the concurrent group and chemotherapy alone group. For the concurrent group and sequential group, the incidences of radiation pneumonia were 22.2% and 22.9%, with a non-significant difference (P=0.940). The incidences of radiation esophagitis were 47.2% and 16.7%, respectively, with a significant difference (P=0.002). Multivariate analysis showed that OS was significantly associated with gender (P=0.018) and ECOG score (P=0.009), and PFS was significantly associated with gender (P=0.050). CONCLUSIONS: For LD-SCLC, concurrent chemoradiotherapy can significantly increase the objective response rate. Concurrent chemoradiotherapy and sequential chemoradiotherapy compared with chemotherapy alone can extend survival, and concurrent chemoradiotherapy is better, but the differences among the three regimens are not significant. Gender and ECOG score are important influencing factors of survival.