Identifying Key Genes and Functionally Enriched Pathways in Osteoporotic Patients by Weighted Gene Co-Expression Network Analysis

Osteoporosis is a systemic bone disease characterized by low bone mineral density and bone microstructure damage, resulting in increased bone fragility and fracture risk. The present study aimed to identify key genes and functionally enriched pathways in osteoporotic patients. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to microarray datasets of blood samples of osteoporotic patients from the Sao Paulo Ageing & Health [SPAH] study (26 osteoporotic samples and 31 normal samples) to construct co-expression networks and identify hub gene. The results showed that HDGF, AP2M1, DNAJC6, TMEM183B, MFSD2B, IGKV1-5, IGKV1-8, IGKV3-7, IGKV3D-11, and IGKV1D-42 are genes which were associated with the disease status of osteoporosis. Differentially expressed genes are enriched in proteasomal protein catabolic process, ubiquitin ligase complex, and ubiquitin-like protein transferase activity. Functional enrichment analysis demonstrated that genes in the tan module were enriched in immune-related functions, indicating that the immune system plays a critical role in osteoporosis. Validation assay demonstrated that the HDGF, AP2M1, TMEM183B, and MFSD2B levels were decreased in osteoporosis samples compared with healthy controls, while the levels of IGKV1-5, IGKV1-8, and IGKV1D-42 were increased in osteoporosis samples compared with healthy controls. In conclusion, our data identified and validated the association of HDGF, AP2M1, TMEM183B, MFSD2B, IGKV1-5, IGKV1-8, and IGKV1D-42 with osteoporosis in elderly women. These results suggest that these transcripts have potential clinical significance and may help to explain the molecular mechanisms and biological functions of osteoporosis.

Association of military-specific reaction time performance with physical fitness and visual skills

Background

The aim of the present study was to explore whether military-specific reaction time (RT) test performance is affected by individuals' physical and visual skills.

Method

In a single testing session, the military-specific Simple and Go, No-Go RT, aerobic power (20-m Multistage Shuttle Run test), maximal upper- and lower-body mechanical capacities (bench press and squat against different loads), and visual skills (multiple object tracking and dynamic visual acuity) of 30 young men (15 active-duty military personnel and 15 sport science students) were evaluated.

Results

The main findings revealed that the Simple RT and Go, No-Go RT presented (1) with aerobic power non-significant small correlations in military personnel (r = -0.39 and -0.35, respectively) and non-significant negligible correlations in sport science students (r = -0.10 and 0.06, respectively), (2) inconsistent and generally non-significant correlations with the maximal mechanical capacities of the upper- and lower-body muscles (r range = -0.10, 0.67 and -0.27, 0.48, respectively), (3) non-significant correlations with visual skills (r magnitude ≥ 0.58) with the only exception of the Go, No-Go RT that was significantly correlated to all visual variables in the group of students (i.e., students who achieved better results during visual tests had shorter RT; r magnitude ≥ 0.58), and (4) none of the physical and visual variables significantly predicted the Simple RT or Go, No-Go RT.

Conclusion

Altogether, these results indicate that military-specific RT performance is generally independent of physical and visual skills in both military personnel and active university students.

Easy as piadcs: A low-cost, ultra-high-resolution data acquisition system using a Raspberry Pi

PREMISE

High-precision data acquisition (DAQ) is essential for developing new methods in the plant sciences. Commercial high-resolution DAQ systems are cost prohibitive, whereas the less expensive systems that are currently available lack the resolution and precision required for many physiological measurements.

METHODS AND RESULTS

We developed the software libraries, called piadcs, and hardware design for a DAQ system based on an ultra-high-resolution analog-to-digital converter and a Raspberry Pi computer. We tested the system precision with and without a thermocouple attached and found the precision with the sensor to be better than ±0.01°C and the maximum possible system resolution to be 0.4 ppm.

CONCLUSIONS

The ultra-high-resolution DAQ system described here is inexpensive, flexible enough to be used with many different sensors, and can be built by researchers with rudimentary electronic and computer skills. This system is most applicable in the development of new measurement techniques and the improvement of existing methods.

AlphaFold - A Personal Perspective on the Impact of Machine Learning

I outline how over my career as a protein scientist Machine Learning has impacted my area of science and one of my pastimes, chess, where there are some interesting parallels. In 1968, modelling of three-dimensional structures was initiated based on a known structure as a template, the problem of the pathway of protein folding was posed and bets were taken in the emerging field of Machine Learning on whether computers could outplay humans at chess. Half a century later, Machine Learning has progressed from using computational power combined with human knowledge in solving problems to playing chess without human knowledge being used, where it has produced novel strategies. Protein structures are being solved by Machine Learning based on human-derived knowledge but without templates. There is much promise that programs like AlphaFold based on Machine Learning will be powerful tools for designing entirely novel protein folds and new activities. But, will they produce novel ideas on protein folding pathways and provide new insights into the principles that govern folds?

Cognitive Reflection and Theory of Mind of Go Players

Go is a classical Chinese mind game and a highly popular intellectual pursuit in East Asia. In a survey at two Go tournaments (one of them the largest in Europe), we measured cognitive reflection and decision in strategic games (using the classical "beauty contest" game) (N = 327). We found that Go players in our survey had outstanding average cognitive reflection test (CRT) scores: 2.51 among all participants and 2.80 among players of high master level (dan). This value easily outperforms previous measurements, for example, of undergraduates at top universities. The CRT score was closely related to the playing strength, but not to the frequency of playing. On the other hand, frequent players tended to have higher theory of mind, regardless of their playing strengths. However, selfreported patience was not statistically significantly correlated with Go strength or playing frequency.

[Go-induced epilepsy treatment with levetiracetam successfully prevented seizures]

There are only a few reports on Go-induced epilepsy. We hereby report a case of Go-induced epilepsy and its ictal electroencephalography (EEG) findings, and treatment. A 71-year-old man reported to our hospital for seizures that lasted for several minutes after he had played Go for approximately an hour. Ictal EEG showed focal to bilateral tonic-clonic seizures of right parietal origin. He was administered levetiracetam 500 mg before the games, and he participated without seizures for more than a year. Go-induced epilepsy is considered to have a focal onset, and it may be controlled with antiepileptic drugs before the games.

Comparing Ease of Programming in C++, Go, and Java for Implementing a Next-Generation Sequencing Tool

elPrep is an extensible multithreaded software framework for efficiently processing Sequence Alignment/Map (SAM)/Binary Alignment/Map (BAM) files in next-generation sequencing pipelines. Similar to other SAM/BAM tools, a key challenge in elPrep is memory management, as such programs need to manipulate large amounts of data. We therefore investigated 3 programming languages with support for assisted or automated memory management for implementing elPrep, namely C++, Go, and Java. We implemented a nontrivial subset of elPrep in all 3 programming languages and compared them by benchmarking their runtime performance and memory use to determine the best language in terms of computational performance. In a previous article, we motivated why, based on these results, we eventually selected Go as our implementation language. In this article, we discuss the difficulty of achieving the best performance in each language in terms of programming language constructs and standard library support. While benchmarks are easy to objectively measure and evaluate, this is less obvious for assessing ease of programming. However, because we expect elPrep to be regularly modified and extended, this is an equally important aspect. We illustrate representative examples of challenges in all 3 languages, and give our opinion why we think that Go is a reasonable choice also in this light.

A comparison of three programming languages for a full-fledged next-generation sequencing tool

BACKGROUND

elPrep is an established multi-threaded framework for preparing SAM and BAM files in sequencing pipelines. To achieve good performance, its software architecture makes only a single pass through a SAM/BAM file for multiple preparation steps, and keeps sequencing data as much as possible in main memory. Similar to other SAM/BAM tools, management of heap memory is a complex task in elPrep, and it became a serious productivity bottleneck in its original implementation language during recent further development of elPrep. We therefore investigated three alternative programming languages: Go and Java using a concurrent, parallel garbage collector on the one hand, and C++17 using reference counting on the other hand for handling large amounts of heap objects. We reimplemented elPrep in all three languages and benchmarked their runtime performance and memory use.

RESULTS

The Go implementation performs best, yielding the best balance between runtime performance and memory use. While the Java benchmarks report a somewhat faster runtime than the Go benchmarks, the memory use of the Java runs is significantly higher. The C++17 benchmarks run significantly slower than both Go and Java, while using somewhat more memory than the Go runs. Our analysis shows that concurrent, parallel garbage collection is better at managing a large heap of objects than reference counting in our case.

CONCLUSIONS

Based on our benchmark results, we selected Go as our new implementation language for elPrep, and recommend considering Go as a good candidate for developing other bioinformatics tools for processing SAM/BAM data as well.

Examining Second Graders' Healthy Food Choices: Through Literacy and Active Learning

The purpose of this study was to investigate the implementation of a nutrition module and activities (Go, Slow, Whoa) in a literacy environment through an active learning approach. Second graders (N = 85) from diverse socioeconomic status (SES) areas completed the 12-week program. The participants’ perceptions of healthy food choices were measured both pre- and post-intervention. Students met for 30 minutes twice a week, to complete 5-lessons from a Coordinated Approach to Child Health (CATCH) nutrition module and activities (Go, Slow, Whoa). Measures were taken both pre- and post-intervention (Food Fury Quiz) to distinguishing between healthy and unhealthy foods (images). There was a statistically significant improvement (t = 12.16, df =84, P = .000) from pretest (M = 19.06, SD = 3.13) and posttest (M = 23.34, SD = 0.48) scores. Administering a healthy food choice curriculum through literacy and active learning provides an alternative approach to improving health knowledge among second grade students.

SciPipe: A workflow library for agile development of complex and dynamic bioinformatics pipelines

BACKGROUND

The complex nature of biological data has driven the development of specialized software tools. Scientific workflow management systems simplify the assembly of such tools into pipelines, assist with job automation, and aid reproducibility of analyses. Many contemporary workflow tools are specialized or not designed for highly complex workflows, such as with nested loops, dynamic scheduling, and parametrization, which is common in, e.g., machine learning.

FINDINGS

SciPipe is a workflow programming library implemented in the programming language Go, for managing complex and dynamic pipelines in bioinformatics, cheminformatics, and other fields. SciPipe helps in particular with workflow constructs common in machine learning, such as extensive branching, parameter sweeps, and dynamic scheduling and parametrization of downstream tasks. SciPipe builds on flow-based programming principles to support agile development of workflows based on a library of self-contained, reusable components. It supports running subsets of workflows for improved iterative development and provides a data-centric audit logging feature that saves a full audit trace for every output file of a workflow, which can be converted to other formats such as HTML, TeX, and PDF on demand. The utility of SciPipe is demonstrated with a machine learning pipeline, a genomics, and a transcriptomics pipeline.

CONCLUSIONS

SciPipe provides a solution for agile development of complex and dynamic pipelines, especially in machine learning, through a flexible application programming interface suitable for scientists used to programming or scripting.

Special series on "effects of board games on health education and promotion" board games as a promising tool for health promotion: a review of recent literature

Board games are played by moving game pieces in particular ways on special boards marked with patterns. To clarify the possible roles of board game use in psychosomatic medicine, the present review evaluated studies that investigated the effects of this activity on health education and treatment. A literature search conducted between January 2012 and August 2018 identified 83 relevant articles; 56 (67%) targeted education or training for health-related problems, six (7%) examined basic brain mechanisms, five (6%) evaluated preventative measures for dementia or contributions to healthy aging, and three (4%) assessed social communication or public health policies. The results of several randomized controlled trials indicated that the playing of traditional board games (e.g., chess, Go, and Shogi) helps to improve cognitive impairment and depression, and that the playing of newly developed board games is beneficial for behavioral modifications, such as the promotion of healthy eating, smoking cessation, and safe sex. Although the number of studies that have evaluated board game use in terms of mental health remains limited, many studies have provided interesting findings regarding brain function, cognitive effects, and the modification of health-related lifestyle factors.

Comprehensive analysis of differentially expressed genes associated with PLK1 in bladder cancer

BACKGROUND

The significance of PLK1 (polo-like kinase 1) has become increasingly essential as both a biomarker and a target for cancer treatment. Here, we aimed to determine the downstream genes of PLK1 and their effects on the carcinogenesis and progression of bladder cancer.

METHODS

Specific siRNA was utilized to silence the target gene expression. The cell proliferation, invasion and migration of bladder cancer cells by MTT assay, BrdU assay and transwell assay. The differential expression genes were identified using Affymetrix HTA2.0 Array. The KEGG, GO and STRING analysis were used to analyze the signaling pathway and protein-protein interaction. Spearman analysis was used to analyze the correlation between protein and protein, between protein and clincopathologic characteristics.

RESULTS

PLK1 siRNA hindered the proliferation, invasion and migration of bladder cancer cells, as determined by the MTT, BrdU and transwell assays. A total of 561 differentially expressed genes were identified using an Affymetrix HTA2.0 Array in PLK1 knockdown T24 cells. According to KEGG, GO and STRING analysis, five key genes (BUB1B, CCNB1, CDC25A, FBXO5, NDC80) were determined to be involved in cell proliferation, invasion and migration. PLK1 knockdown decreased BUB1B, CCNB1, CDC25A and NDC80 expressions but increased FBXO5 expression. BUB1B, CCNB1, CDC25A and NDC80 were positively correlated with cell proliferation, invasion, migration and PLK1 expression in tissues, but FBXO5 was negatively correlated with each of those factors. The results showed that the five genes expressions were significantly correlation with the PLK1 expression in normal bladder tissues and bladder cancer tissues. Four of them (BUB1B, CCNB1, CDC25A, NDC80) were obviously positive correlations with pT stage and metastasis. But FBXO5 was negative correlated with pT stage and metastasis. Furthermore, significant correlations were found between CCNB1 or CDC25A or NDC80 and histological grade; between BUB1B or NDC80 and recurrence.

CONCLUSION

Five downstream genes of PLK1 were associated with the regulation of cell proliferation, invasion and migration in bladder cancer. Furthermore, these genes may play important roles in bladder cancer and become important biomarkers and targets for cancer treatment.

Higher extrinsic and lower intrinsic connectivity in resting state networks for professional Baduk (Go) players

INTRODUCTION

Dedication and training to a profession results in a certain level of expertise. This expertise, like any other skill obtained in our lifetime, is encoded in the brain and may be reflected in our brain's connectome. This property can be observed by mapping resting state connectivity. In this study, we examine the differences in resting state functional connectivity in four major networks between professional "Baduk" (Go) players and normal subjects.

METHODS

Resting state fMRI scans were acquired for professional "Baduk" (Go) players and normal controls. Major resting state networks were identified using independent component analysis and compared between the two groups. Networks which were compared include the default mode network, the left and right fronto-parietal network, and the salience network.

RESULTS

We found that normal subjects showed increased connectivity within certain areas of each target network. Professional players, however, showed higher connectivity to regions outside the traditional regions of each given network. Close examination of these regions revealed that regions shown to have higher connectivity in professional players have been revealed to be relevant in expertise for board games.

CONCLUSION

The findings in this study suggest that continuous training results in greater integration between regions and networks, which are necessary for high-level performance. The differences observed in our study between normal controls and professional players also shed light on the difference in brain connectivity which can arise through lifestyle and specialization in a specific field.

Emotional bias of cognitive control in adults with childhood attention-deficit/hyperactivity disorder

Affect recognition deficits found in individuals with attention-deficit/hyperactivity disorder (ADHD) across the lifespan may bias the development of cognitive control processes implicated in the pathophysiology of the disorder. This study aimed to determine the mechanism through which facial expressions influence cognitive control in young adults diagnosed with ADHD in childhood. Fourteen probands with childhood ADHD and 14 comparison subjects with no history of ADHD were scanned with functional magnetic resonance imaging while performing a face emotion go/no-go task. Event-related analyses contrasted activation and functional connectivity for cognitive control collapsed over face valence and tested for variations in activation for response execution and inhibition as a function of face valence. Probands with childhood ADHD made fewer correct responses and inhibitions overall than comparison subjects, but demonstrated comparable effects of face emotion on response execution and inhibition. The two groups showed similar frontotemporal activation for cognitive control collapsed across face valence, but differed in the functional connectivity of the right dorsolateral prefrontal cortex, with fewer interactions with the subgenual cingulate cortex, inferior frontal gyrus, and putamen in probands than in comparison subjects. Further, valence-dependent activation for response execution was seen in the amygdala, ventral striatum, subgenual cingulate cortex, and orbitofrontal cortex in comparison subjects but not in probands. The findings point to functional anomalies in limbic networks for both the valence-dependent biasing of cognitive control and the valence-independent cognitive control of face emotion processing in probands with childhood ADHD. This limbic dysfunction could impact cognitive control in emotional contexts and may contribute to the social and emotional problems associated with ADHD.

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We tested adult probands diagnosed with ADHD in childhood and comparison subjects.

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Emotional bias of cognitive control was modeled with a face emotion go/no-go task.

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Probands made fewer correct responses and correct inhibitions on the go/no-go task.

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Probands showed reduced prefrontal connectivity with limbic and paralimbic regions.

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Probands showed no valence-dependent limbic activation for cognitive control.

Baduk (the Game of Go) Improved Cognitive Function and Brain Activity in Children with Attention Deficit Hyperactivity Disorder

OBJECTIVE

Attention deficit hyperactivity disorder (ADHD) symptoms are associated with the deficit in executive functions. Playing Go involves many aspect of cognitive function and we hypothesized that it would be effective for children with ADHD.

METHODS

Seventeen drug naïve children with ADHD and seventeen age and sex matched comparison subjects were participated. Participants played Go under the instructor's education for 2 hours/day, 5 days/week. Before and at the end of Go period, clinical symptoms, cognitive functions, and brain EEG were assessed with Dupaul's ADHD scale (ARS), Child depression inventory (CDI), digit span, the Children's Color Trails Test (CCTT), and 8-channel QEEG system (LXE3208, Laxtha Inc., Daejeon, Korea).

RESULTS

There were significant improvements of ARS total score (z=2.93, p<0.01) and inattentive score (z=2.94, p<0.01) in children with ADHD. However, there was no significant change in hyperactivity score (z=1.33, p=0.18). There were improvement of digit total score (z=2.60, p<0.01; z=2.06, p=0.03), digit forward score (z=2.21, p=0.02; z=2.02, p=0.04) in both ADHD and healthy comparisons. In addition, ADHD children showed decreased time of CCTT-2 (z=2.21, p=0.03). The change of theta/beta right of prefrontal cortex during 16 weeks was greater in children with ADHD than in healthy comparisons (F=4.45, p=0.04). The change of right theta/beta in prefrontal cortex has a positive correlation with ARS-inattention score in children with ADHD (r=0.44, p=0.03).

CONCLUSION

We suggest that playing Go would be effective for children with ADHD by activating hypoarousal prefrontal function and enhancing executive function.

Go signaling in mushroom bodies regulates sleep in Drosophila

STUDY OBJECTIVES

Sleep is a fundamental physiological process and its biological mechanisms are poorly understood. In Drosophila melanogaster, heterotrimeric Go protein is abundantly expressed in the brain. However, its post-developmental function has not been extensively explored.

DESIGN

Locomotor activity was measured using the Drosophila Activity Monitoring System under a 12:12 LD cycle. Sleep was defined as periods of 5 min with no recorded activity.

RESULTS

Pan-neuronal elevation of Go signaling induced quiescence accompanied by an increased arousal threshold in flies. By screening region-specific GAL4 lines, we mapped the sleep-regulatory function of Go signaling to mushroom bodies (MBs), a central brain region which modulates memory, decision making, and sleep in Drosophila. Up-regulation of Go activity in these neurons consolidated sleep while inhibition of endogenous Go via expression of Go RNAi or pertussis toxin reduced and fragmented sleep, indicating that the Drosophila sleep requirement is affected by levels of Go activity in the MBs. Genetic interaction results showed that Go signaling serves as a neuronal transmission inhibitor in a cAMP-independent pathway.

CONCLUSION

Go signaling is a novel signaling pathway in MBs that regulates sleep in Drosophila.