Cryptic diversity and gene introgression of Moinidae (Crustacea: Cladocera) in Nigeria

The distribution and species/lineage diversity of freshwater invertebrate zooplankton is understudied in Sub-Saharan Africa. In the present study, we explored the lineage diversity and regional distribution of Moinidae (Crustacea: Cladocera) species in Southeast Nigeria. Three species of Moinidae were identified, based on morphology, in 11 of 32 Nigerian lakes examined. Their phylogenetic relationships were investigated based on mitochondrial dna sequences (cytochrome oxidase c subunit I gene; coi) and two nuclear internal transcribed spacer regions (its-1 and its-2). Three coi lineages were detected, corresponding to the morphological species. Two of the coi lineages are newly reported, but one coi lineage (and the haplotype found) is globally distributed, suggesting an ability of moinids to disperse over long distances. Interestingly, two individuals that were morphologically M. cf. macrocopa and had its alleles typical of that species had mtDNA sequences typical of M. cf. micrura. Additionally, one individual that corresponded morphologically to M. cf. macrocopa (and also had a mitochondrial sequence typical of M. cf. micrura) had one its-2 allele typical of that species and one typical of M. cf. micrura. This discordance between mtDNA and nuclear phylogenies suggests gene introgression and/or hybridization between different species within the genus. Our data shows the lineage distribution/diversity and the presence of gene introgression/interspecific hybridization among moinid species from a tropical region

Effect of Parental Migration on the Intellectual and Physical Development of Early School-Aged Children in Rural China

Abstract OBJECTIVE: The purpose of this study is to estimate the effect of parent migration on intellectual and physical development of early school-aged children in rural China. DESIGN: setting and participants: The present cross-sectional study participants were a subset from a controlled, cluster-randomized, double-blind trial. From October 2012 to September 2013, the offspring of women who participated in a large trial were examined in the present study. Wechsler intelligence scale for children (WISC-IV) in which validity and reliability were shown to be satisfactory was used to measure the intellectual function and trained anthropometrists measured weight and height of children using standard procedures. RESULTS: The mean difference of FSIQ scores between non-migration and both-parent migration groups was -3.68 (95%CI: -5.49, -1.87). After adjusting for the confounders, the mean difference of full-scale IQ between non-migration and both-parent migration group was -1.97 (95%CI: -3.92, -0.01), the mean differences of perceptual reasoning index and processing speed index were -2.41 (95%CI: -4.50, -0.31) and -2.39 (95%CI: -4.42, -0.35) between two groups respectively. CONCLUSION: Our results emphasized the impairment of both-parental migration in intellectual function (FSIQ, PRI, PSI) of children. These findings have important policy implications for the Chinese government to prevent the impairment of left-behind children. Further research is required to clarify the mechanisms by which both-parental migration influence the impairment in intellectual function of children

Correlation between Insulin Resistance and Thyroid Nodule in Type 2 Diabetes Mellitus

Objective. The present study explored the association between insulin resistance (IR) and the clinical characteristics of thyroid nodules in patients with type 2 diabetes mellitus (T2DM). Methods. All the patients were newly diagnosed with T2DM. 201 patients with thyroid nodule disease and 308 patients without the nodular thyroid disease. The participants were evaluated by relevant examination. Correlation analyses and regression analyses were performed to examine the relationships between the two groups. Results. HOMA-IR values, serum FT4 (free thyroxine) levels, and age were higher in the thyroid nodule group than in the control group. The proportion of women in the thyroid nodule group is greater than the proportion of women in the control group. Logistic regression analysis showed that age, sex, FT4, and HOMA-IR were positive factors for thyroid nodule. The volume and size of the thyroid nodule were positively correlated with HOMA-IR, irrespective of gender. The thyroid nodule volume and size and the TSH (thyroid stimulating hormone) were greater in females than in males, whereas FT3 (free triiodothyronine) was lower in females. Conclusion. IR might be a risk factor for thyroid nodule. Whether alleviating the IR might slow the growth, or diminish the volume and size of the thyroid nodules, is yet to be elucidated

Disease Burden and Indirect Economic Burden Due to Lung Cancer from 1981 to 2020 in Kunshan, Jiangsu Province, China

Objective To identify the disease burden and indirect economic burden caused by lung cancer in Kunshan City, Jiangsu Province, from 1981 to 2020. Methods The incidence and death cases of lung cancer were obtained from cancer registry and death cause monitoring data. The disability adjusted life years (DALY) was used as the evaluation index for burden posed by lung cancer on health, and the indirect economic burden was calculated by a human capital method. Results From 1981 to 2020, a total of 9272 deaths due to lung cancer were reported in Kunshan, of which 7106 were males and 2166 were females. The DALY caused by lung cancer in the whole population were 3.81, 4.14, 4.38, and 9.46 in 1981–1990, 1991–2000, 2001–2010, and 2011–2020, respectively. The indirect economic burden caused by lung cancer was 10.515, 141.657, 813.794, and 6659.149 million yuan. From 2011 to 2020, the ratios of years of life lost due to premature mortality to DALY in males, females, and the general population were 92.42%, 95.15%, and 93.60%, respectively. Conclusion The health burden and indirect economic burden for lung cancer are substantial in the Kunshan City. Moreover, age-specific DALY and indirect economic burden are not exactly symmetrical, suggesting that an effective control strategy to lower cost is urgently needed, especially for individuals aged 40-59

Association of adiponectin with peripheral arterial disease and mortality in nondiabetic hemodialysis patients: Long-term follow-up data of 7 years

Background: The relationships between adiponectin and clinical outcomes in hemodialysis (HD) patients remain highly controversial. Meanwhile, the association between adiponectin and the peripheral artery disease (PAD) has not been well studied in HD patients without diabetic mellitus. Materials and Methods: The ankle-brachial index was measured in HD patients. Adiponectin levels in 105 HD patients were measured by Enzyme-Linked Immunosorbant Assay. Results: 105 HD patients were enrolled; 14 (13%) patients had PAD. Using receiver-operating-characteristic (ROC) curve analysis for PAD, adiponectin (area under the curve [AUC] 0.935, 95% confidence interval [CI]: 0.848–0.981, P < 0.001) showed significantly positive predictive value. During follow-up (mean 63 ± 30 months), 34 deaths (32%) occurred. Kaplan–Meier analysis found those patients lower median adiponectin had a significantly poor outcome (P < 0.05), and Cox analysis further confirmed that adiponectin was an independent predictor of overall mortality (hazard ratio [HR], 0.832, 95% CI: 0.696–0.995, P < 0.05). The ROC curve of overall mortality showed that the AUC of adiponectin was 0.719 (95% CI: 0.586–0.813, P < 0.05). In HD patients with PAD, the univariate analysis showed that adiponectin (HR, 0.649, 95% CI: 0.527–0.800, P < 0.001) was also associated with overall mortality. Conclusion: Decreasing levels of adiponectin were associated with a significant increase in the risk of PAD in HD patients without diabetic mellitus. Furthermore, as the results of our observation period (maximum of 7 years) showed, adiponectin was a predictor of all-cause mortality in HD patients

Functional analysis of apple stem pitting virus coat protein variants

Abstract Background Although the canonical function of viral coat protein (CP) is to encapsidate the viral genome, they have come to be recognized as multifunctional proteins, involved in almost every stage of the viral infection cycle. However, CP functions of Apple stem pitting virus (ASPV) has not been comprehensively documented. This study aimed to characterize the functions of ASPV CP and any functional diversification caused by sequence diversity of six ASPV CP variants and studied their biological, serological, pathogenic and viral suppressor of RNA silencing (VSR) functions. Methods Six ASPV CP variants that have previously been shown to belong to different subgroups were selected here to study their diversity functions. Agrobacterium mediated infiltration (Agroinfiltration) was used to express YFP-ASPV-CPs in Nicotiana. benthamiana and infect Nicotiana. occidental with PVX-ASPV-CPs in. Confocal microscopy was used to detect YFP-ASPV-CPs florescence. CPs expressed in Escherichia coli BL21 (DE3) were induced by IPTG. Results In this study, we showed that recombinant CPs expressed in Escherichia coli BL21 (DE3) had different levels of serological reactivity to three anti-ASPV antibodies used to detect ASPV. Furthermore, fusion CPs with YFP (YFP-CPs) expressed in N. benthamiana cells differed in their ability to form aggregates. We also showed that ASPV isolates that harbour these CPs induced different biological symptoms on its herbaceous host N. occidentalis. At the same time, we found that all six CPs when expressed in PVX vector showed similar VSR activity and produced similar symptoms in N. occidentalis, despite their differences in amino acids. Conclusions Different ASPV isolates induced different symptoms in N. occidentalis, however, ASPV CP variants expressed in PVX vector showed the same symptoms in N. occidentalis plants. Also, we showed that ASPV CP variants has the same level of VSR activity, but they have different abilities to aggregate in N. benthamiana

New lineages and old species: lineage diversity and regional distribution of Moina (Crustacea: Cladocera) in China

The distribution and genetic diversity of freshwater zooplankton is understudied in the Eastern Palearctic. Here, we explored the lineage diversity and regional distribution of the genus Moina in China. Members of this genus are often keystone components of freshwater ecosystems and have been frequently subjected to toxicological and physiological studies. Four species of Moina were identified, based on morphology, in 50 of 113 Chinese water bodies examined, and their phylogenetic position was analyzed using both a mitochondrial (mitochondrial cytochrome c oxidase subunit I; COI) and a nuclear marker (the nuclear internal transcribed spacer; ITS-1). Both molecular markers identified four clades corresponding broadly to the morphological species. Mitochondrial DNA analysis showed the presence of four species complexes with eleven lineages across China, five of which were new. However, some lineages (and even individual haplotypes) were widespread in Eurasia, suggesting an ability to disperse over long distances. In contrast, a few lineages exhibited restricted distributions. The nuclear phylogeny also recognized four species of Moina within China and seven very distinct clades. Interestingly, one specimen possessing Moina cf. micrura mtDNA had ITS-1 alleles of the M. cf. brachiata clade. This discordance between mtDNA and nuclear ITS-1 phylogenies is indicative of interspecific introgression and hybridization. Additionally, our COI phylogeny showed apparent paraphyly in two Moina species groups, suggesting introgression of their mitochondrial genomes. Our data shows the regional distribution/diversity of the Moina species complex in a Eurasian context

Transfer Learning for Leaf Small Dataset Using Improved ResNet50 Network with Mixed Activation Functions

Taxonomic studies of leaves are one of the most effective means of correctly identifying plant species. In this paper, mixed activation function is used to improve the ResNet50 network in order to further improve the accuracy of leaf recognition. Firstly, leaf images of 15 common tree species in northern China were collected from the Urban Forestry Demonstration Base of Northeast Forestry University (45°43′–45°44′ N, 126°37′–126°38′ E, forest type was artificial forest), and a small leaf dataset was established. After that, seven commonly used activation functions were selected to improve the ResNet50 network structure, and the improved network was applied to the transfer learning research of the leaf small dataset. On this basis, five activation functions with better performance were selected for the study of mixed activation functions in deep learning. Two of these five activation functions are arbitrarily selected for combination, and a total of twenty combinations are obtained. Further, the first activation function was used in each combination to replace the first ReLU function after all addition operations in the ResNet50 network residual block structure, and another activation function was used to replace the other position ReLU functions. The experimental results show that in the transfer learning of the leaf small dataset using the ResNet50 deep residual network, the appropriate combination of mixed activation functions can increase the performance of the improved network to a certain extent. Among them, the ELU-Swish1 combination has the most significant improvement effect on the network performance, whose final effective validation accuracy reaches 98.17%. Furthermore, the comparison with GoogLeNet and VGG-16 also demonstrates the excellent performance of the improved ELU-Swish1 ResNet50 (ES-ResNet50) network architecture. Finally, tests on the other two small leaf datasets, Flavia and Swedish, also demonstrate the performance improvement of ES-ResNet50. The validation accuracy of the improved ES-Resnet 50 algorithm on these two datasets reaches 99.30% and 99.39%, respectively. All these experiments prove that the recognition performance of leaf transfer learning using the ES-ResNet50 network is indeed improved, which may be caused by the complementarity of the e-exponential gradient of ELU and Swish1 activation functions in the negative region

Transfer Learning for Leaf Small Dataset Using Improved ResNet50 Network with Mixed Activation Functions

Taxonomic studies of leaves are one of the most effective means of correctly identifying plant species. In this paper, mixed activation function is used to improve the ResNet50 network in order to further improve the accuracy of leaf recognition. Firstly, leaf images of 15 common tree species in northern China were collected from the Urban Forestry Demonstration Base of Northeast Forestry University (45&deg;43&prime;&ndash;45&deg;44&prime; N, 126&deg;37&prime;&ndash;126&deg;38&prime; E, forest type was artificial forest), and a small leaf dataset was established. After that, seven commonly used activation functions were selected to improve the ResNet50 network structure, and the improved network was applied to the transfer learning research of the leaf small dataset. On this basis, five activation functions with better performance were selected for the study of mixed activation functions in deep learning. Two of these five activation functions are arbitrarily selected for combination, and a total of twenty combinations are obtained. Further, the first activation function was used in each combination to replace the first ReLU function after all addition operations in the ResNet50 network residual block structure, and another activation function was used to replace the other position ReLU functions. The experimental results show that in the transfer learning of the leaf small dataset using the ResNet50 deep residual network, the appropriate combination of mixed activation functions can increase the performance of the improved network to a certain extent. Among them, the ELU-Swish1 combination has the most significant improvement effect on the network performance, whose final effective validation accuracy reaches 98.17%. Furthermore, the comparison with GoogLeNet and VGG-16 also demonstrates the excellent performance of the improved ELU-Swish1 ResNet50 (ES-ResNet50) network architecture. Finally, tests on the other two small leaf datasets, Flavia and Swedish, also demonstrate the performance improvement of ES-ResNet50. The validation accuracy of the improved ES-Resnet 50 algorithm on these two datasets reaches 99.30% and 99.39%, respectively. All these experiments prove that the recognition performance of leaf transfer learning using the ES-ResNet50 network is indeed improved, which may be caused by the complementarity of the e-exponential gradient of ELU and Swish1 activation functions in the negative region