Photosynthetic physiological characteristics, growth performance, and element concentrations reveal the calcicole-calcifuge behaviors of three Camellia species

We grew three yellow Camellia species (the calcifuge C. nitidissima and C. tunghinensis, and the calcicole C. pubipetala) in acidic and calcareous soils for 7 months and assessed their photosynthetic physiological characteristics, growth performance, and element concentrations in this developmental context. The calcifuge C. nitidissima and C. tunghinensis species exhibited poor growth with leaf chlorosis, growth stagnation, and root disintegration in calcareous soils, and with their P n, G s, T r, F v/F m, ΦPSII, ETR, qP, leaf Chla, Chlb, and Chl(a + b) concentrations, and root, stem, leaf, and total biomass being significantly lower when grown in calcareous soils relative to in acidic soils. In contrast, the calcicole C. pubipetala grew well in both acidic and calcareous soils, with few differences in the above parameters between these two soil substrates. The absorption and/or transportation of nutrient elements such as N, K, Ca, Mg, and Fe by the two calcifuge Camellia species plants grown in calcareous soils were restrained. Soil type plays a major role in the failure of the two calcifuge Camellia species to establish themselves in calcareous soils, whereas other factors such as competition and human activity are likely more important limiting factors in the reverse case. This study furthers our understanding of the factors influencing the distribution of these rare and endangered yellow Camellia species, allowing for improved management of these species in conservation projects and horticultural production.

The structure and diversity of bacteria and fungi in the roots and rhizosphere soil of three different species of Geodorum

Shepherd's crook (Geodorum) is a genus of protected orchids that are valuable both medicinally and ornamentally. Geodorum eulophioides (GE) is an endangered and narrowly distributed species, and Geodorum densiflorum (GD) and Geodorum attenuatum (GA) are widespread species. The growth of orchids depend on microorganisms. However, there are few studies on the microbial structure in Geodorum, and little is known about the roles of microorganisms in the endangered mechanism of G. eulophioides. This study analyzed the structure and composition of bacterial and fungal communities in the roots and rhizosphere soil of GE, GD, and GA. The results showed that Delftia, Bordetella and norank_f_Xanthobacteraceae were the dominant bacteria in the roots of Geodorum, while norank_f_Xanthobacteraceae, Gaiella and norank_f_norank_o_Gaiellales were the dominant bacteria in the rhizosphere soil of Geodorum. In the roots, the proportion of Mycobacterium in GD_roadside was higher than that in GD_understory, on the contrary, the proportion of Fusarium, Delftia and Bordetella in GD_roadside was lower than that in GD_understory. Compared with the GD_understory, the roots of GD_roadside had lower microbial diversity. In the endangered species GE, Russula was the primary fungus in the roots and rhizosphere soil, with fungal diversity lower than in the more widespread species. Among the widespread species, the dominant fungal genera in the roots and rhizosphere soil were Neocosmospora, Fusarium and Coprinopsis. This study enhances our understanding of microbial composition and diversity, providing fundamental information for future research on microbial contributions to plant growth and ecosystem function in Geodorum.

AI's deep dive into complex pediatric inguinal hernia issues: a challenge to traditional guidelines?

OBJECTIVE

This study utilized ChatGPT, an artificial intelligence program based on large language models, to explore controversial issues in pediatric inguinal hernia surgery and compare its responses with the guidelines of the European Association of Pediatric Surgeons (EUPSA).

METHODS

Six contentious issues raised by EUPSA were submitted to ChatGPT 4.0 for analysis, for which two independent responses were generated for each issue. These generated answers were subsequently compared with systematic reviews and guidelines. To ensure content accuracy and reliability, a content analysis was conducted, and expert evaluations were solicited for validation. Content analysis evaluated the consistency or discrepancy between ChatGPT 4.0's responses and the guidelines. An expert scoring method assess the quality, reliability, and applicability of responses. The TF-IDF model tested the stability and consistency of the two responses.

RESULTS

The responses generated by ChatGPT 4.0 were mostly consistent with the guidelines. However, some differences and contradictions were noted. The average quality score was 3.33, reliability score was 2.75, and applicability score was 3.46 (out of 5). The average similarity between the two responses was 0.72 (out of 1), Content analysis and expert ratings yielded consistent conclusions, enhancing the credibility of our research.

CONCLUSION

ChatGPT can provide valuable responses to clinical questions, but it has limitations and requires further improvement. It is recommended to combine ChatGPT with other reliable data sources to improve clinical practice and decision-making.

[A semi-supervised network-based tissue-aware contrast enhancement method for CT images]

OBJECTIVE

To propose a tissue- aware contrast enhancement network (T- ACEnet) for CT image enhancement and validate its accuracy in CT image organ segmentation tasks.

METHODS

The original CT images were mapped to generate low dynamic grayscale images with lung and soft tissue window contrasts, and the supervised sub-network learned to recognize the optimal window width and level setting of the lung and abdominal soft tissues via the lung mask. The self-supervised sub-network then used the extreme value suppression loss function to preserve more organ edge structure information. The images generated by the T-ACEnet were fed into the segmentation network to segment multiple abdominal organs.

RESULTS

The images obtained by T-ACEnet were capable of providing more window setting information in a single image, which allowed the physicians to conduct preliminary screening of the lesions. Compared with the suboptimal methods, T-ACE images achieved improvements by 0.51, 0.26, 0.10, and 14.14 in SSIM, QABF, VIFF, and PSNR metrics, respectively, with a reduced MSE by an order of magnitude. When T-ACE images were used as input for segmentation networks, the organ segmentation accuracy could be effectively improved without changing the model as compared with the original CT images. All the 5 segmentation quantitative indices were improved, with the maximum improvement of 4.16%.

CONCLUSION

The T-ACEnet can perceptually improve the contrast of organ tissues and provide more comprehensive and continuous diagnostic information, and the T-ACE images generated using this method can significantly improve the performance of organ segmentation tasks.

[A semi-supervised material quantitative intelligent imaging algorithm for spectral CT based on prior information perception learning]

OBJECTIVE

To propose a semi-supervised material quantitative intelligent imaging algorithm based on prior information perception learning (SLMD-Net) to improve the quality and precision of spectral CT imaging.

METHODS

The algorithm includes a supervised and a self- supervised submodule. In the supervised submodule, the mapping relationship between low and high signal-to-noise ratio (SNR) data was constructed through mean square error loss function learning based on a small labeled dataset. In the self- supervised sub-module, an image recovery model was utilized to construct the loss function incorporating the prior information from a large unlabeled low SNR basic material image dataset, and the total variation (TV) model was used to to characterize the prior information of the images. The two submodules were combined to form the SLMD-Net method, and pre-clinical simulation data were used to validate the feasibility and effectiveness of the algorithm.

RESULTS

Compared with the traditional model-driven quantitative imaging methods (FBP-DI, PWLS-PCG, and E3DTV), data-driven supervised-learning-based quantitative imaging methods (SUMD-Net and BFCNN), a material quantitative imaging method based on unsupervised learning (UNTV-Net) and semi-supervised learning-based cycle consistent generative adversarial network (Semi-CycleGAN), the proposed SLMD-Net method had better performance in both visual and quantitative assessments. For quantitative imaging of water and bone materials, the SLMD-Net method had the highest PSNR index (31.82 and 29.06), the highest FSIM index (0.95 and 0.90), and the lowest RMSE index (0.03 and 0.02), respectively) and achieved significantly higher image quality scores than the other 7 material decomposition methods (P < 0.05). The material quantitative imaging performance of SLMD-Net was close to that of the supervised network SUMD-Net trained with labeled data with a doubled size.

CONCLUSIONS

A small labeled dataset and a large unlabeled low SNR material image dataset can be fully used to suppress noise amplification and artifacts in basic material decomposition in spectral CT and reduce the dependence on labeled data-driven network, which considers more realistic scenario in clinics.

Prediction of knee pain improvement over two years for knee osteoarthritis using a dynamic nomogram based on MRI-derived radiomics: a proof-of-concept study

OBJECTIVES

To develop and validate a nomogram to detect improved knee pain in osteoarthritis (OA) by integrating magnetic resonance imaging (MRI) radiomics signature of subchondral bone and clinical characteristics.

METHODS

Participants were selected from the Vitamin D Effects on Osteoarthritis (VIDEO) study. The primary outcome was 20% improvement of knee pain score over 2 years in participants administrated either vitamin D or placebo. Radiomics features of subchondral bone and clinical characteristics from 216 participants were extracted and analyzed. The participants were randomly split into the training and validation cohorts at a ratio of 8:2. Least absolute shrinkage and selection operator (LASSO) regression was used to select features and generate radiomics signatures. The optimal radiomics signature and clinical indicators were fitted into a nomogram using multivariable logistic regression model.

RESULTS

The nomogram showed favorable discrimination performance [AUC_training, 0.79 (95% CI: 0.72-0.79), AUC_validation, 0.83 (95% CI: 0.70-0.96)] as well as a good calibration. Additional contributing value of fusion radiomics signature to the nomogram was statistically significant (NRI, 0.23; IDI, 0.14, P < 0.001 in training cohort and NRI, 0.29; IDI, 0.18, P < 0.05 in validating cohort). Decision curve analysis confirmed the clinical usefulness of nomogram.

CONCLUSION

The radiomics-based nomogram comprising the MR radiomics signature and clinical variables achieves a favorable predictive efficacy and accuracy in differentiating improvement in knee pain among OA patients. This proof-of-concept study provides a promising way to predict clinically meaningful outcomes.

[Association analysis between genetic variants of matrix metalloproteinase enzyme 2 gene and the blood pressure of children and adolescents]

Objective: To explore the association between genetic variants of matrix metalloproteinase enzyme 2 (MMP2) gene and the blood pressure of children and adolescents. Methods: This cross-sectional study was performed in 2016 and included 4 155 children and adolescents in the urban area of Guangzhou. Physical examinations (including body height, weight, and blood pressure), questionnaires (including general characteristics, physical exercise, parental educational level, household income, etc.), and blood sampling were performed. Multivariable linear regression models were used to investigate the associations of MMP2 genetic variations (rs243865, rs7201) and the genetic risk score (GRS) level with standardized blood pressure. Mediating effect of standardized body mass index (BMI) was further assessed by process analysis in the association between GRS level and blood pressure, and potential additive interaction between physical activity and GRS level was analyzed using the product term in the regression model. Results: A total of 4 155 primary and secondary schoolchildren were finally included in the analysis, consisting of 1 401 (33.7%) second grade pupils of primary school, 1 422 (34.2%) first grade pupils of middle school, and 1 332 (32.1%) first-grade students of senior high school. After adjusting for age, sex, parental educational level, and family income, as compared to the rs243865 TT genotype, the CC/CT genotype increased diastolic blood pressure (DBP) by 0.461 standard deviations (SD) (β for dominant model=0.461, 95%CI 0.199-0.723). When compared to the rs7201 CC genotype, the AA/AC genotype showed 0.147 SD higher systolic blood pressure (SBP) (β for recessive model=0.147, 95%CI 0.014-0.279) and 0.171 SD increased DBP (β for recessive model=0.171, 95%CI 0.039-0.304). For each increment of GRS level, SBP and DBP increased by 0.151 SD (β for dominant model=0.151, 95%CI 0.029-0.272) and 0.242 SD (β=0.242, 95%CI 0.120-0.363), respectively. The mediating effect of BMI accounted for 28.3% and 12.6% of the total effect of GRS on SBP and DBP, respectively. After controlling BMI, the direct effect of GRS on DBP remained statistically significant (P<0.001). The insufficient moderate-to-vigorous physical activity (<0.5 h/d) showed a significant interaction with GRS on SBP under additive scale (β for interaction=0.518, 95%CI 0.088-0.949, P=0.018). Conclusions: rs243865 and rs7201 variants in MMP2 gene are associated with the elevated blood pressure of children and adolescents. Obesity may yield a mediation role in the associations, while insufficient physical activity may have a positively additive interaction with MMP2 genetic variants.

[Time-series analysis on the relationship between ambient PM2.5 and daily outpatient visits due to allergic conjunctivitis among children in Shenzhen]

Objective: To explore the short-term effects of ambient PM_2.5 on the outpatient visits of allergic conjunctivitis among children in Shenzhen. Methods: It was a ecological study. Data on daily visits including date of visit, sex and age from children with allergic conjunctivitis were collected from Shenzhen Eye Hospital and Shenzhen Children's Hospital in 2018. Related data on air pollution (PM_2.5, PM₁₀, SO₂, NO₂, CO and O₃) and meteorology (atmospheric pressure, temperature and relative humidity) were also collected. Pearson correlation analysis was used for normal distribution data and Spearman rank correlation analysis was used for non-normal distribution data. Generalized additive model was used to estimate the impact of PM_2.5 pollution on allergic conjunctivitis outpatients and the lagging effects. Results: In 2018, there were 16 133 allergic conjunctivitis outpatients in the two hospitals. The maximum age was 18 years and the minimum age was 2 months. Males accounted for 49.3%. The daily average concentration of PM_2.5 was 22 (15, 31) μg/m³. Changes of the concentration of PM_2.5 had a positive correlation with the amount of allergic conjunctivitis visits, and the Spearman correlation coefficient was 0.150 (P=0.004). The single pollutant model showed that the strongest effect appeared at 3 days (RR=1.111， 95%CI:1.071-1.152). A 10 μg/m³ increase of PM_2.5 would result in an excessive number of allergic conjunctivitis outpatients as much as 11.112% (95%CI：7.011%-15.212%). In the multiple air pollutants models, after the introduction of NO₂, O₃ and CO, the concentration of PM_2.5 showed an enhanced effect on the number of hospital visits due to allergic conjunctivitis on the same day, and the difference was statistically significant (P<0.05). Conclusion: Changes of the concentration of PM_{2.5 h}ad a positive correlation with daily outpatient visits of allergic conjunctivitis among children in Shenzhen. (Chin J Ophthalmol, 2020, 56: 608-614).

MicroRNA-374b accelerates the development of lung cancer through downregulating PTEN expression via activating PI3K/Akt pathway

OBJECTIVE

To elucidate whether microRNA-374b could participate in the development of lung cancer (LC) through downregulating PTEN (gene of phosphate and tensin homolog deleted on chromosome ten) expression via activating PI3K/Akt pathway.

PATIENTS AND METHODS

Expression levels of microRNA-374b and PTEN in LC tissues and adjacent normal tissues were detected by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). Moreover, the expression level of microRNA-374b in LC cell lines was detected as well. The microRNA-374b inhibitor was constructed and transfected to downregulate microRNA-374b expression in A549 and H358 cells. The regulatory effects of microRNA-374b on migratory and proliferative capacities of LC cells were explored by wound healing and cell counting kit-8 (CCK-8) assay, respectively. After co-transfection of microRNA-374b inhibitor and si-PTEN in LC cells, expression levels of PTEN/PI3K/Akt were determined by qRT-PCR and Western blot.

RESULTS

QRT-PCR results showed that microRNA-374b expression was higher, while PTEN expression was lower in LC tissues than adjacent tissues. Identically, microRNA-374b was also highly expressed in LC cell lines. PTEN expression was negatively correlated with microRNA-374b expression in LC. The downregulation of microRNA-374b in A549 and H358 cells inhibited their migratory and proliferative potentials. Subsequently, we verified that microRNA-374b could bind to PTEN through dual-luciferase reporter gene assay. MicroRNA-374b could inhibit PTEN expression and activate the PI3K/Akt pathway. Furthermore, PTEN knockdown enhanced migratory and proliferative abilities of LC cells, which were attenuated by co-transfection of microRNA-374b inhibitor.

CONCLUSIONS

MicroRNA-374b promotes the development of LC by downregulating PTEN expression through activating PI3K/Akt pathway.

1144 Actigraphy-defined Sleep And Neurocognitive Decline In Middle-age Hispanic/Latino Adults

Introduction

Few studies have evaluated objective sleep measures and longitudinal neurocognitive decline, particularly in middle-age or Hispanic/Latino adults. We evaluated prospective associations between actigraphy-defined sleep and 7-year neurocognitive change among Hispanic/Latino adults. We hypothesized that sleep duration would be associated with neurocognitive decline.

Methods

We analyzed data from 1,036 adults 45-64 years of age from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a multi-center prospective cohort study of diverse community-dwelling Hispanic/Latino adults. At Visit 1 (2008-2011), participants underwent neurocognitive assessments, 7-days of actigraphy, home sleep testing, and sleep questionnaires (including the Insomnia Severity Index). Seven years later, participants repeated neurocognitive assessments. The neurocognitive battery included the Six-Item Screener, Brief Spanish-English Verbal Learning Test, phonemic word fluency test, and Digit Symbol Subtest. Survey linear regression was used to evaluate prospective associations between actigraphy-defined or self-reported sleep variables and neurocognitive change. Final models adjusted for objectively-defined variables (age, body-mass index, Field Center, and time between neurocognitive assessments), and self-reported variables (sex, education, Hispanic/Latino background, alcohol consumption, physical activity, heart failure, cerebrovascular events, depression and anxiety symptoms, and antidepressant use).

Results

At Visit 1, the sample was 55% female and mean age was 54.9±2.2 years. The mean sleep duration was 402.6±27.6 minutes, mean sleep-onset latency was 11.3±9.7 minutes, mean number of days with naps of ≥ 15 minutes duration was 1.1±0.7, and mean sleep-time per nap was 51±14.1 minutes. Increased sleep-onset latency was associated with 7-year declines in global neurocognitive function (β=-0.0026, p&lt;0.01), verbal learning (β=-0.0028, p&lt;0.001) and verbal memory (β=-0.036, p&lt;0.05). Increased sleep-time per nap predicted better verbal memory (β=0.0038, p&lt;0.05). In contrast, sleep duration, sleep fragmentation, and self-reported sleep measures were not associated with neurocognitive change.

Conclusion

Among middle-age adults, sleep-onset latency and nap duration were associated with neurocognitive change. These findings may serve as targets for intervention of neurocognitive decline.

Support

This work is supported by the National Institute on Aging: R01AG048642, RF1AG054548, R01AG061022, R21AG056952, and R21HL140437 (AR).

Artificial light at night alter the impact of arsenic on microbial decomposers and leaf litter decomposition in streams

Artificial light at night (ALAN, also known as light pollution) has been proved to be a contributor to environmental change and a biodiversity threat worldwide, yet little is known about its potential interaction with different metal pollutants, such as arsenic (As), one of the largest threats to aquatic ecosystems. To narrow this gap, an indoor microcosm study was performed using an ALAN simulation device to examine whether ALAN exposure altered the impact of arsenic on plant litter decomposition and its associated fungi. Results revealed that microbial decomposers involved in the conversion of As(III) to As(V), and ALAN exposure enhanced this effect; ALAN or arsenic only exposure altered fungal community composition and the correlations between fungi species, as well as stimulated or inhibited litter decomposition, respectively. The negative effects of arsenic on the decomposition of Pterocarya stenoptera leaf litter was alleviated by ALAN resulting in the enhanced photodegradation of leaf litter lignin and microbiological oxidation of As(III) to As(V), the increased microbial biomass and CBH activity, as well as the enhanced correlations between CBH and litter decomposition rate. Overall, results expand our understanding of ALAN on environment and highlight the contribution of ALAN to the toxicity of arsenic in aquatic ecosystems.

Over-expression of both VEGF-C and Twist predicts poor prognosis in human breast cancer

BACKGROUND

Angiogenesis is an indispensable step in the growth and invasiveness of breast cancers involving a series of exquisite molecular steps. Pro-angiogenic factors, including vascular endothelial growth factor (VEGF), have been recognized as pivotal therapeutic targets in the treatment of breast cancer. More recently, a highly conserved transcription factor Twist has been reported to be involved in tumor angiogenesis and metastasis.

METHODS

The expression of VEGF-C and Twist was immunohistochemically determined in tissue samples of primary tumors from 408 patients undergoing curative surgical resection for breast cancer. The correlations of VEGF-C and Twist expressions with clinicopathologic parameters as well as survival outcomes were evaluated.

RESULTS

Of the 408 patients evaluated, approximately 70% had high expression of VEGF-C which was significantly associated with advanced tumor stages (P = 0.019). Similarly, VEGF-C expression was associated with the proliferation index Ki67, N3 lymph node metastasis, and D2-40-positive lymphatic vessel invasion (LVI) in a univariate analysis. Furthermore, patients with high expressions of VEGF-C and Twist (V + T+) had significantly increased lymph node metastasis, higher clinical stage, and worse disease-free survival, DFS (P = 0.001) and overall survival, OS (P = 0.011).

CONCLUSIONS

Our results suggested that co-expression of VEGF-C and Twist was associated with larger tumor size, higher numbers of lymph node involvement, D2-40-positive LVI, higher risk of distant metastasis, and worse DFS or OS in breast cancer patients.

Appropriate dose of Lactobacillus buchneri supplement improves intestinal microbiota and prevents diarrhoea in weaning Rex rabbits

This study examined the effects on intestinal microbiota and diarrhoea of Lactobacillus buchneri supplementation to the diet of weaning Rex rabbits. To this end, rabbits were treated with L. buchneri at two different doses (LC: 104 cfu/g diet and HC: 105 cfu/g diet) for 4 weeks. PCR-DGGE was used to determine the diversity of the intestinal microbiota, while real-time PCR permitted the detection of individual bacterial species. ELISA and real-time PCR allowed the identification of numerous cytokines in the intestinal tissues. Zonula occludens-1, polymeric immunoglobulin receptor and immunoglobulin A genes were examined to evaluate intestinal barriers. Results showed that the biodiversity of the intestinal microbiota of weaning Rex rabbits improved in the whole tract of the treated groups. The abundance of most detected bacterial species was highly increased in the duodenum, jejunum and ileum after L. buchneri administration. The species abundance in the HC group was more increased than in the LC group when compared to the control. Although the abundance of Enterobacteriaceae exhibited a different pattern, Escherichia coli was inhibited in all treatment groups. Toll-like receptor (TLR)2 and TLR4 genes were down-regulated in all intestinal tissues as the microbiota changed. In the LC group, the secretion of the inflammatory cytokine tumour necrosis factor-α was reduced, the gene expression of the anti-inflammatory cytokine interleukin (IL)-4 was up-regulated and the expression of intestinal-barrier-related genes was enhanced. Conversely, IL-4 expression was increased and the expression of other tested genes did not change in the HC group. The beneficial effects of LC were greater than those of HC or the control in terms of improving the daily weight gain and survival rate of weaning Rex rabbits and reducing their diarrhoea rate. Therefore, 104 cfu/g L. buchneri treatment improved the microbiota of weaning Rex rabbits and prevented diarrhoea in these animals.

Gene expression profiles for a prognostic immunoscore in gastric cancer

Background

Increasing evidence has indicated an association between immune infiltration in gastric cancer and clinical outcome. However, reliable prognostic signatures, based on systematic assessments of the immune landscape inferred from bulk tumour transcriptomes, have not been established. The aim was to develop an immune signature, based on the cellular composition of the immune infiltrate inferred from bulk tumour transcriptomes, to improve the prognostic predictions of gastric cancer.

Methods

Twenty‐two types of immune cell fraction were estimated based on large public gastric cancer cohorts from the Gene Expression Omnibus using CIBERSORT. An immunoscore based on the fraction of immune cell types was then constructed using a least absolute shrinkage and selection operator (LASSO) Cox regression model.

Results

Using the LASSO model, an immunoscore was established consisting of 11 types of immune cell fraction. In the training cohort (490 patients), significant differences were found between high‐ and low‐immunoscore groups in overall survival across and within subpopulations with an identical TNM stage. Multivariable analysis revealed that the immunoscore was an independent prognostic factor (hazard ratio 1·92, 95 per cent c.i. 1·54 to 2·40). The prognostic value of the immunoscore was also confirmed in the validation (210) and entire (700) cohorts.

Conclusion

The proposed immunoscore represents a promising signature for estimating overall survival in patients with gastric cancer.

Immunoscore predicts prognosis

Effects of cryopreservation on ultrastructural morphology of white shrimp (Litopenaeus vannamei) sperm

BACKGROUND

The structural integrity of a spermatozoon is very important for the processes of fertilization and embryo development.

OBJECTIVE

To provide valuable data for developing better cryopreservation techniques for shrimp sperm.

MATERIALS AND METHODS

Using scanning electron microscopy and transmission electron microscopy, we examined the morphological alteration of Litopenaeus vannamei sperm after cryopreservation with different concentrations of dimethylsulfoxide (DMSO).

RESULTS

We found that the damaged post-thaw sperm presented either vesiculated acrosomal contents, wrinkled membranes, perforated membranes, and loss of the acrosomal spike. The seriously damaged sperm showed missing acrosomal spikes, deformed nuclei, burst nuclear membranes, and vacuolated nuclei. In addition, we found that the post-thaw sperm stored with 5% DMSO had the highest viability rate and lowest DNA damage coefficient by eosin-nigrosin staining and comet assay.

CONCLUSION

Our results suggested that cryopreservation has deleterious effects on ultrastructural morphology of L. vannamei sperm, especially on acrosomal spikes and membranes.

Isolation and characterization of novel polymorphic microsatellite loci in large yellow croaker (Larimichthys crocea)

The large yellow croaker (Larimichthys crocea) is one of the largest marine net-cage cultured species in the oceans around China. In the present study, we isolated and characterized 13 polymorphic microsatellite markers from genomic libraries of L. crocea. Loci were screened for 10 wild specimens from 2 sites in southeast of China. All loci were polymorphic. The number of alleles per locus ranged from 2 to 21. The expected heterozygosity ranged from 0.233 to 0.838 and observed heterozygosity ranged from 0.527 to 0.935. Eleven loci were highly informative (polymorphic information content >0.5). Significant deviation from Hardy-Weinberg equilibrium was observed at 3 loci after Bonferroni's correction. The microsatellite loci may be valuable tools for studying the genetic diversity and genetic structure for conservation planning of the fish.

On random-effects meta-analysis

Meta-analysis is widely used to compare and combine the results of multiple independent studies. To account for between-study heterogeneity, investigators often employ random-effects models, under which the effect sizes of interest are assumed to follow a normal distribution. It is common to estimate the mean effect size by a weighted linear combination of study-specific estimators, with the weight for each study being inversely proportional to the sum of the variance of the effect-size estimator and the estimated variance component of the random-effects distribution. Because the estimator of the variance component involved in the weights is random and correlated with study-specific effect-size estimators, the commonly adopted asymptotic normal approximation to the meta-analysis estimator is grossly inaccurate unless the number of studies is large. When individual participant data are available, one can also estimate the mean effect size by maximizing the joint likelihood. We establish the asymptotic properties of the meta-analysis estimator and the joint maximum likelihood estimator when the number of studies is either fixed or increases at a slower rate than the study sizes and we discover a surprising result: the former estimator is always at least as efficient as the latter. We also develop a novel resampling technique that improves the accuracy of statistical inference. We demonstrate the benefits of the proposed inference procedures using simulated and empirical data.

Doubly Robust Learning for Estimating Individualized Treatment with Censored Data

Individualized treatment rules recommend treatments based on individual patient characteristics in order to maximize clinical benefit. When the clinical outcome of interest is survival time, estimation is often complicated by censoring. We develop nonparametric methods for estimating an optimal individualized treatment rule in the presence of censored data. To adjust for censoring, we propose a doubly robust estimator which requires correct specification of either the censoring model or survival model, but not both; the method is shown to be Fisher consistent when either model is correct. Furthermore, we establish the convergence rate of the expected survival under the estimated optimal individualized treatment rule to the expected survival under the optimal individualized treatment rule. We illustrate the proposed methods using simulation study and data from a Phase III clinical trial on non-small cell lung cancer.

A Likelihood-Based Framework for Association Analysis of Allele-Specific Copy Numbers

Copy number variants (CNVs) and single nucleotide polymorphisms (SNPs) co-exist throughout the human genome and jointly contribute to phenotypic variations. Thus, it is desirable to consider both types of variants, as characterized by allele-specific copy numbers (ASCNs), in association studies of complex human diseases. Current SNP genotyping technologies capture the CNV and SNP information simultaneously via fluorescent intensity measurements. The common practice of calling ASCNs from the intensity measurements and then using the ASCN calls in downstream association analysis has important limitations. First, the association tests are prone to false-positive findings when differential measurement errors between cases and controls arise from differences in DNA quality or handling. Second, the uncertainties in the ASCN calls are ignored. We present a general framework for the integrated analysis of CNVs and SNPs, including the analysis of total copy numbers as a special case. Our approach combines the ASCN calling and the association analysis into a single step while allowing for differential measurement errors. We construct likelihood functions that properly account for case-control sampling and measurement errors. We establish the asymptotic properties of the maximum likelihood estimators and develop EM algorithms to implement the corresponding inference procedures. The advantages of the proposed methods over the existing ones are demonstrated through realistic simulation studies and an application to a genome-wide association study of schizophrenia. Extensions to next-generation sequencing data are discussed.

Penalized Q-Learning for Dynamic Treatment Regimens

A dynamic treatment regimen incorporates both accrued information and long-term effects of treatment from specially designed clinical trials. As these trials become more and more popular in conjunction with longitudinal data from clinical studies, the development of statistical inference for optimal dynamic treatment regimens is a high priority. In this paper, we propose a new machine learning framework called penalized Q-learning, under which valid statistical inference is established. We also propose a new statistical procedure: individual selection and corresponding methods for incorporating individual selection within penalized Q-learning. Extensive numerical studies are presented which compare the proposed methods with existing methods, under a variety of scenarios, and demonstrate that the proposed approach is both inferentially and computationally superior. It is illustrated with a depression clinical trial study.

Short-term therapeutic drug monitoring of mycophenolic acid reduces infection: a prospective, single-center cohort study in Chinese living-related kidney transplantation

BACKGROUND

The role of therapeutic drug monitoring (TDM) of mycophenolic acid (MPA) in kidney transplant recipients (KTRs) is not clear. We performed a prospective cohort study to evaluate the efficiency of MPA TDM in the Chinese population.

METHODS

A total of 183 living-related KTRs were studied; 101 KTRs received controlled-dose mycophenolate mofetil (MMF) (the CD group), and 82 patients received fixed-dose MMF (the FD group). MPA exposure was measured at days 3, 7, 14, and 30 in the CD group, and at day 30 in the FD group. The primary endpoint was treatment failure (a composite of acute rejection, graft loss, death, or MMF discontinuation) at 12 months post transplantation.

RESULTS

In the CD group, with a starting MMF dose of 2 g/day, approximately 35% of patients had high MPA levels, which were >60 mg × h/L, and mean MPA levels were 59.17 mg × h/L and 61.38 mg × h/L for the CD and FD groups, respectively (P = 0.588). After adjusting MMF dose, MPA exposures in the CD group at day 30 were lower than those in the FD group at day 30 (54.06 vs. 61.38, P = 0.004). At month 12, the CD group had fewer infections (16.8% vs. 31.7%, P = 0.018) with no difference in treatment failure, acute rejection, diarrhea, or anemia.

CONCLUSIONS

KTRs can benefit from short-term TDM of MPA in reducing infection, without increasing acute rejection.

Long-term outcome of HLA-haploidentical hematopoietic SCT without in vitro T-cell depletion for adult severe aplastic anemia after modified conditioning and supportive therapy

HLA-haploidentical hematopoietic SCT (HSCT) is an option for severe aplastic anemia (SAA) patients. Here, we evaluated the outcomes of 26 adult-SAA patients who received HLA-haploidentical HSCT in five transplant centers in southwestern China. Most of the patients in this study failed prior therapy and were transfused heavily before the transplantation. The patients received fludarabine+cyclophosphamide+antithymocyte globulin as conditioning regimens and then unmanipulated peripheral blood plus marrow transplantation. Micafungin, i.v. Ig and recombinant human TPO were used for post-grafting infection prevention and supportive care. Of 26 patients, 25 achieved engraftment at a median of 13 days (range, 11-19 days) after HSCT. One of 25 patients experienced graft rejection and did not achieve sustained engraftment after second HSCT. Therefore, the final engraftment rate was 92.3%. Three of 25 (12%) patients developed acute GVHD, 10 of 25 (40%) patients developed chronic GVHD (9 with limited whereas the other with extensive). The OS rate was 84.6% and the average follow-up time was 1313.2 (738-2005) days for surviving patients. This encouraging result suggests that HLA-haploidentical HSCT is an effective therapeutic option for adults with acquired SAA if an HLA-identical donor is not available.

Role of monokine induced by interferon-γ in liver injury induced by hepatitis B virus in mice

The chemokine monokine induced by interferon-γ (Mig) is involved in the recruitment of inflammatory cells and liver injury during hepatitis B virus (HBV) infection. HBV protein X contributes to Mig expression in vitro by activation of nuclear factor (NF)-κB; however, the molecular mechanisms by which HBV induces Mig expression in vivo are unknown. In this paper, we established a mouse model for HBV study by tail vein injection of HBV genome-containing adenovirus vectors. Host immune response to the secreted hepatitis B surface antigen and e antigen was detected and serum alanine aminotransferase (ALT) was elevated at different time points. We also demonstrated that peripheral and intrahepatic Mig expression was increased after Ad-HBV infection. This was followed by inflammatory cell migration and formation of inflammatory foci in the liver. In addition, NF-κB p65 subunit translocated from the cytoplasm to the nucleus, and phosphoinositide 3-kinase/Akt, extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase (JNK) were to some extent phosphorylated after HBV injection. Following tail vein injection of Mig siRNA/in vivo-jetPEI-Gal complex, Mig expression was partially suppressed, inflammatory cell migration was inhibited, serum level of ALT were reduced. In conclusion, through NF-κB activation, HBV induced Mig expression in vivo, which recruited peripheral inflammatory cells to the liver and resulted in liver damage. Phosphorylation of phosphoinositide 3-kinase/Akt, ERK and JNK but not p38 might involved in the molecular mechanisms underlying HBV induced Mig expression in vivo.

Correcting for Population Stratification in Genomewide Association Studies

Genomewide association studies have become the primary tool for discovering the genetic basis of complex human diseases. Such studies are susceptible to the confounding effects of population stratification, in that the combination of allele-frequency heterogeneity with disease-risk heterogeneity among different ancestral subpopulations can induce spurious associations between genetic variants and disease. This article provides a statistically rigorous and computationally feasible solution to this challenging problem of unmeasured confounders. We show that the odds ratio of disease with a genetic variant is identifiable if and only if the genotype is independent of the unknown population substructure conditional on a set of observed ancestry-informative markers in the disease-free population. Under this condition, the odds ratio of interest can be estimated by fitting a semiparametric logistic regression model with an arbitrary function of a propensity score relating the genotype probability to ancestry-informative markers. Approximating the unknown function of the propensity score by B-splines, we derive a consistent and asymptotically normal estimator for the odds ratio of interest with a consistent variance estimator. Simulation studies demonstrate that the proposed inference procedures perform well in realistic settings. An application to the well-known Wellcome Trust Case-Control Study is presented. Supplemental materials are available online.

Effect of myofiber characteristics and thickness of perimysium and endomysium on meat tenderness of chickens

The objective of the present study was to evaluate the role of myofiber characteristics and the thickness of 2 major muscle membranes, perimysium and endomysium, in determining the breast meat tenderness of chickens. Birds from 2 breeds (White Leghorn and a line of broiler) were chosen. Chicks were sexed and wing-banded at hatch and were grown in separate cages in a single house. Sixty broilers and 60 White Leghorns were harvested at 6 wk of age, respectively, whereas another 60 White Leghorns were slaughtered at 18 wk of age. An equal number of males and females was maintained for each group. Body weight, breast muscle weight, pH, drip loss, cooking loss, Warner-Bratzler shear force value (SFV), total energy of shear force, fiber diameter, sarcomere length, myofiber density, and the thickness of endomysium and perimysium of the breast were determined for each bird. At 6 wk of age, histological examination indicated that the size of myofiber and thickness of endomysium and perimysium of broilers were larger than that those of White Leghorns (P < 0.01), whereas the SFV, drip loss, and cooking loss of broilers were smaller (P < 0.01). A comparison between the White Leghorns at 18 wk and the broilers at 6 wk, which were at similar BW but different ages, showed that the breast muscle weight of broilers was larger (P < 0.01) than that of White Leghorns. For breast muscle, the endomysium of broilers at 6 wk was thicker than that of White Leghorns at 18 wk (P < 0.01), whereas the perimysium was thinner (P < 0.01). The SFV, drip loss, and the cooking loss of broilers were smaller than those of White Leghorns at similar BW (P < 0.01). Meat tenderness was negatively correlated with myofiber density (-0.27) and the thickness of endomysium (-0.29) and positively correlated with the thickness of perimysium (0.20). It is suggested that muscle membrane should be considered in evaluating meat tenderness of the chicken.

On the relative efficiency of using summary statistics versus individual-level data in meta-analysis

Meta-analysis is widely used to synthesize the results of multiple studies. Although meta-analysis is traditionally carried out by combining the summary statistics of relevant studies, advances in technologies and communications have made it increasingly feasible to access the original data on individual participants. In the present paper, we investigate the relative efficiency of analyzing original data versus combining summary statistics. We show that, for all commonly used parametric and semiparametric models, there is no asymptotic efficiency gain by analyzing original data if the parameter of main interest has a common value across studies, the nuisance parameters have distinct values among studies, and the summary statistics are based on maximum likelihood. We also assess the relative efficiency of the two methods when the parameter of main interest has different values among studies or when there are common nuisance parameters across studies. We conduct simulation studies to confirm the theoretical results and provide empirical comparisons from a genetic association study.

A general framework for studying genetic effects and gene-environment interactions with missing data

Missing data arise in genetic association studies when genotypes are unknown or when haplotypes are of direct interest. We provide a general likelihood-based framework for making inference on genetic effects and gene-environment interactions with such missing data. We allow genetic and environmental variables to be correlated while leaving the distribution of environmental variables completely unspecified. We consider 3 major study designs-cross-sectional, case-control, and cohort designs-and construct appropriate likelihood functions for all common phenotypes (e.g. case-control status, quantitative traits, and potentially censored ages at onset of disease). The likelihood functions involve both finite- and infinite-dimensional parameters. The maximum likelihood estimators are shown to be consistent, asymptotically normal, and asymptotically efficient. Expectation-Maximization (EM) algorithms are developed to implement the corresponding inference procedures. Extensive simulation studies demonstrate that the proposed inferential and numerical methods perform well in practical settings. Illustration with a genome-wide association study of lung cancer is provided.

Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data

To identify genetic variants with modest effects on complex human diseases, a growing number of networks or consortia are created for sharing data from multiple genome-wide association studies on the same disease or related disorders. A central question in this enterprise is whether to obtain summary results or individual participant data from relevant studies. We show theoretically and numerically that meta-analysis of summary results is statistically as efficient as joint analysis of individual participant data (provided that both analyses are performed properly under the same modeling assumptions). We illustrate this equivalence with case-control data from the Finland-United States Investigation of NIDDM Genetics (FUSION) study. Collating only summary results will increase the number and representativeness of available studies, simplify data collection and analysis, reduce resource utilization, and accelerate discovery.

The effect of exercise on the cerebral vasculature of healthy aged subjects as visualized by MR angiography

BACKGROUND AND PURPOSE

Prior studies suggest that aerobic exercise may reduce both the brain atrophy and the decline in fractional anisotropy observed with advancing age. It is reasonable to hypothesize that exercise-induced changes to the vasculature may underlie these anatomic differences. The purpose of this blinded study was to compare high-activity and low-activity healthy elderly volunteers for differences in the cerebrovasculature as calculated from vessels extracted from noninvasive MR angiograms (MRAs).

MATERIALS AND METHODS

Fourteen healthy elderly subjects underwent MRA. Seven subjects reported a high level of aerobic activity (64 +/- 5 years of age; 5 men, 2 women) and 7, a low activity level (68 +/- 6 years of age; 5 women, 2 men). Following vessel segmentation from MRA by an individual blinded to subject activity level, quantitative measures of vessel number, radius, and tortuosity were calculated and histogram analysis of vessel number and radius was performed.

RESULTS

Aerobically active subjects exhibited statistically significant reductions in vessel tortuosity and an increased number of small vessels compared with less active subjects.

CONCLUSIONS

Aerobic activity in elderly subjects is associated with lower vessel tortuosity values and an increase in the number of small-caliber vessels. It is possible that an aerobic exercise program may contribute to healthy brain aging. MRA offers a noninvasive approach to visualizing the cerebral vasculature and may prove useful in future longitudinal investigations.

Proper analysis of secondary phenotype data in case-control association studies

Case-control association studies often collect extensive information on secondary phenotypes, which are quantitative or qualitative traits other than the case-control status. Exploring secondary phenotypes can yield valuable insights into biological pathways and identify genetic variants influencing phenotypes of direct interest. All publications on secondary phenotypes have used standard statistical methods, such as least-squares regression for quantitative traits. Because of unequal selection probabilities between cases and controls, the case-control sample is not a random sample from the general population. As a result, standard statistical analysis of secondary phenotype data can be extremely misleading. Although one may avoid the sampling bias by analyzing cases and controls separately or by including the case-control status as a covariate in the model, the associations between a secondary phenotype and a genetic variant in the case and control groups can be quite different from the association in the general population. In this article, we present novel statistical methods that properly reflect the case-control sampling in the analysis of secondary phenotype data. The new methods provide unbiased estimation of genetic effects and accurate control of false-positive rates while maximizing statistical power. We demonstrate the pitfalls of the standard methods and the advantages of the new methods both analytically and numerically. The relevant software is available at our website.

Cumulative life course and adult socioeconomic status and markers of inflammation in adulthood

OBJECTIVE

To examine the association between cumulative life course and adult socioeconomic status (SES) and adult levels of inflammatory risk markers (fibrinogen, white blood cell count (WBC), C-reactive protein (CRP), von Willebrand factor (vWF) and an overall inflammatory score).

DESIGN

Retrospective cohort study.

SETTING

12,681 white and African-American participants in the Atherosclerosis Risk in Communities (ARIC) study and two ancillary studies.

METHODS

Participants provided information on SES and place of residence in childhood and young (30-40 years) and mature (45+) adulthood. Residences were linked to census data for neighbourhood SES information. Multiple imputation (MI) was used for missing data. Linear regression and adjusted geometric means were used to estimate the effects of SES on inflammatory risk marker levels.

RESULTS

Graded, statistically significant associations were observed between greater cumulative life-course exposure to low education and social class and elevated levels of fibrinogen and WBC among white participants. Stronger graded, statistically significant associations were observed between low adult education, social class and neighbourhood SES and elevated inflammatory levels. Associations were weaker and less consistent in African-Americans. Covariate adjustment attenuated results but many associations remained strong.

CONCLUSIONS

Our results suggest that cumulative exposure to adverse SES conditions across the life course and low adult SES are associated with an elevated systemic inflammatory burden in adulthood. Chronic systemic inflammation may be one pathway linking low life-course SES and elevated cardiovascular disease risk.