Prediction of Three-Dimensional Arm Trajectories Based on ECoG Signals Recorded from Human Sensorimotor Cortex

Brain-machine interface techniques have been applied in a number of studies to control neuromotor prostheses and for neurorehabilitation in the hopes of providing a means to restore lost motor function. Electrocorticography (ECoG) has seen recent use in this regard because it offers a higher spatiotemporal resolution than non-invasive EEG and is less invasive than intracortical microelectrodes. Although several studies have already succeeded in the inference of computer cursor trajectories and finger flexions using human ECoG signals, precise three-dimensional (3D) trajectory reconstruction for a human limb from ECoG has not yet been achieved. In this study, we predicted 3D arm trajectories in time series from ECoG signals in humans using a novel preprocessing method and a sparse linear regression. Average Pearson’s correlation coefficients and normalized root-mean-square errors between predicted and actual trajectories were 0.44∼0.73 and 0.18∼0.42, respectively, confirming the feasibility of predicting 3D arm trajectories from ECoG. We foresee this method contributing to future advancements in neuroprosthesis and neurorehabilitation technology.     

Stability of Phase Relationships While Coordinating Arm Reaches with Whole Body Motion

The human movement repertoire is characterized by the smooth coordination of several body parts, including arm movements and whole body motion. The neural control of this coordination is quite complex because the various body parts have their own kinematic and dynamic properties. Behavioral inferences about the neural solution to the coordination problem could be obtained by examining the emerging phase relationship and its stability. Here, we studied the phase relationships that characterize the coordination of arm-reaching movements with passively-induced whole-body motion. Participants were laterally translated using a vestibular chair that oscillated at a fixed frequency of 0.83 Hz. They were instructed to reach between two targets that were aligned either parallel or orthogonal to the whole body motion. During the first cycles of body motion, a metronome entrained either an in-phase or an anti-phase relationship between hand and body motion, which was released at later cycles to test phase stability. Results suggest that inertial forces play an important role when coordinating reaches with cyclic whole-body motion. For parallel reaches, we found a stable in-phase and an unstable anti-phase relationship. When the latter was imposed, it readily transitioned or drifted back toward an in-phase relationship at cycles without metronomic entrainment. For orthogonal reaches, we did not find a clear difference in stability between in-phase and anti-phase relationships. Computer simulations further show that cost models that minimize energy expenditure (i.e. net torques) or endpoint variance of the reach cannot fully explain the observed coordination patterns. We discuss how predictive control and impedance control processes could be considered important mechanisms underlying the rhythmic coordination of arm reaches and body motion.     

人X染色体长臂(Xq)和短臂(Xp)基因组学比较分析

X染色体发生X染色体失活 ,但是Xp基因有 30 %表现为逃逸 ,而Xq仅不到 3%。为了研究X染色体基因失活和表达逃逸发生和维持的分子机制 ,比较了Xq和XpDNA序列的RNA模拟结合强度。X染色体的核苷酸序列被分为 5 0kb一段 ,对每一段DNA做 7碱基 (7nt)字符串组合分析 (共有 4 7=16 384种组合 ) ,记录每段 5 0kbDNA中每种 7nt字符串的频率。选择生发中心B细胞中的 12 0个高表达基因 ,计算这些基因的内含子 7nt字符串的出现频率 ,称为intron 7nt,以此作为RNAs(RNA群 ,模拟细胞中RNA在小片段的总和 )。已知一段DNA序列的 7nt频率值和intron 7nt,即可以计算该DNA段与intron 7nt的结合强度。每段 5 0kbDNA与intron 7nt的结合强度取决于该DNA段与intron 7nt互补核苷酸的频率 ,互补的核苷酸序列越多 ,结合强度就越大。DNA段与intron 7nt的模拟结合强度称为RNA结合强度 ,试图模拟该段DNA可以结合的RNA小片段的总量。之所以采用 7nt字符串组合分析是考虑到连续 7个核苷酸互补则可以形成相对稳定的结合。研究发现 :1)Xp各DNA段的RNA结合强度均值显著大于Xq (P <0 0 0 1) ;2 )Xp上高结合RNA的DNA段数目显著高于Xq (P <0 0 0 1) ;3)RNA高结合DNA段形成的簇与X染色体基因表达逃逸区关联。有证据表明 ,RNA可以通过改变染色质     

Characterizing and Diminishing Autofluorescence in Formalin-fixed Paraffin-embedded Human Respiratory Tissue

Tissue autofluorescence frequently hampers visualization of immunofluorescent markers in formalin-fixed paraffin-embedded respiratory tissues. We assessed nine treatments reported to have efficacy in reducing autofluorescence in other tissue types. The three most efficacious were Eriochrome black T, Sudan black B and sodium borohydride, as measured using white light laser confocal Λ² (multi-lambda) analysis. We also assessed the impact of steam antigen retrieval and serum application on human tracheal tissue autofluorescence. Functionally fitting this Λ² data to 2-dimensional Gaussian surfaces revealed that steam antigen retrieval and serum application contribute minimally to autofluorescence and that the three treatments are disparately efficacious. Together, these studies provide a set of guidelines for diminishing autofluorescence in formalin-fixed paraffin-embedded human respiratory tissue. Additionally, these characterization techniques are transferable to similar questions in other tissue types, as demonstrated on frozen human liver tissue and paraffin-embedded mouse lung tissue fixed in different fixatives.     

Three-Dimensional Structure of the Human Myeloma IgG2

Human immunoglobulin G, subclass 2 (hIgG2), plays an important role in immunity to bacterial pathogens and in numerous pathological conditions. However, there is a lack of information regarding the three-dimensional (3D) structure of the hIgG2 molecule. We used electron microscopy (EM), differential scanning microcalorimetry (DSC) and fluorescence for structural analysis of the hIgG2. DSC and fluorescence indicated two types of interaction between C_H1 domain of Fab (antigen-binding fragment/subunit) and C_H2 domain of Fc (complement fixation fragment/subunit) simultaneously present in the sample: close interaction, which increases the thermostability of both, C_H1 and C_H2 domains, and weak (or no) interaction, which is typical for most IgGs but not hIgG2. Thermodynamics could not determine if both types of interactions are present within a single molecule. To address this question, EM was used. We employed a single-particle reconstruction and negative staining approach to reveal the three-dimensional structure of the hIgG2. A three-dimensional model of hIgG2 was created at 1.78 nm resolution. The hIgG2 is asymmetrical: one Fab subunit is in close proximity to the upper portion of the Fc subunit (C_H2 domain) and the other Fab is distant from Fc. The plane of Fab subunits is nearly perpendicular to Fc. EM structure of the hIgG2 is in good agreement with thermodynamic data: a Fab distant from Fc should exhibit a lower melting temperature while a Fab interacting with Fc should exhibit a higher melting temperature. Both types of Fab subunits exist within one molecule resembling an A/B hIgG2 isoform introduced earlier on physicochemical level by Dillon et al. (2008). In such an arrangement, the access to the upper portion of Fc subunit is partially blocked by a Fab subunit. That might explain for instance why hIgG2 mildly activates complement and binds poorly to Fc receptors. Understanding of the three-dimensional structure of the hIgG2 should lead to better design of antibody-based therapeutics.     

Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments

Microorganisms have evolved to occupy certain environmental niches, and the metabolic genes essential for growth in these locations are retained in the genomes. Many microorganisms inhabit niches located in the human body, sometimes causing disease, and may retain genes essential for growth in locations such as the bloodstream and urinary tract, or growth during intracellular invasion of the hosts’ macrophage cells. Strains of Escherichia coli (E. coli) and Salmonella spp. are thought to have evolved over 100 million years from a common ancestor, and now cause disease in specific niches within humans. Here we have used a genome scale metabolic model representing the pangenome of E. coli which contains all metabolic reactions encoded by genes from 16 E. coli genomes, and have simulated environmental conditions found in the human bloodstream, urinary tract, and macrophage to determine essential metabolic genes needed for growth in each location. We compared the predicted essential genes for three E. coli strains and one Salmonella strain that cause disease in each host environment, and determined that essential gene retention could be accurately predicted using this approach. This project demonstrated that simulating human body environments such as the bloodstream can successfully lead to accurate computational predictions of essential/important genes.     

Characterizing the Major Structural Variant Alleles of the Human Genome

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Modulation of Arm Reaching Movements during Processing of Arm/Hand-Related Action Verbs with and without Emotional Connotation

The theory of embodied language states that language comprehension relies on an internal reenactment of the sensorimotor experience associated with the processed word or sentence. Most evidence in support of this hypothesis had been collected using linguistic material without any emotional connotation. For instance, it had been shown that processing of arm-related verbs, but not of those leg-related verbs, affects the planning and execution of reaching movements; however, at present it is unknown whether this effect is further modulated by verbs evoking an emotional experience. Showing such a modulation might shed light on a very debated issue, i.e. the way in which the emotional meaning of a word is processed. To this end, we assessed whether processing arm/hand-related verbs describing actions with negative connotations (e.g. to stab) affects reaching movements differently from arm/hand-related verbs describing actions with neutral connotation (e.g. to comb). We exploited a go/no-go paradigm in which healthy participants were required to perform arm-reaching movements toward a target when verbs expressing emotional hand actions, neutral hand actions or foot actions were shown, and to refrain from moving when no-effector-related verbs were presented. Reaction times and percentages of errors increased when the verb involved the same effector as used to give the response. However, we also found that the size of this interference decreased when the arm/hand-related verbs had a negative emotional connotation. Crucially, we show that such modulation only occurred when the verb semantics had to be retrieved. These results suggest that the comprehension of negatively valenced verbs might require the simultaneous reenactment of the neural circuitry associated with the processing of the emotion evoked by their meaning and of the neural circuitry associated with their motor features.     

Characterizing the Human Cone Photoreceptor Mosaic via Dynamic Photopigment Densitometry

Densitometry is a powerful tool for the biophysical assessment of the retina. Until recently, this was restricted to bulk spatial scales in living humans. The application of adaptive optics (AO) to the conventional fundus camera and scanning laser ophthalmoscope (SLO) has begun to translate these studies to cellular scales. Here, we employ an AOSLO to perform dynamic photopigment densitometry in order to characterize the optical properties and spectral types of the human cone photoreceptor mosaic. Cone-resolved estimates of optical density and photosensitivity agree well with bulk estimates, although show smaller variability than previously reported. Photopigment kinetics of individual cones derived from their selective bleaching allowed efficient mapping of cone sub-types in human retina. Estimated uncertainty in identifying a cone as long vs middle wavelength was less than 5%, and the total time taken per subject ranged from 3–9 hours. Short wavelength cones were delineated in every subject with high fidelity. The lack of a third cone-type was confirmed in a protanopic subject. In one color normal subject, cone assignments showed 91% correspondence against a previously reported cone-typing method from more than a decade ago. Combined with cone-targeted stimulation, this brings us closer in studying the visual percept arising from a specific cone type and its implication for color vision circuitry.     

MetaGeniE: Characterizing Human Clinical Samples Using Deep Metagenomic Sequencing

With the decreasing cost of next-generation sequencing, deep sequencing of clinical samples provides unique opportunities to understand host-associated microbial communities. Among the primary challenges of clinical metagenomic sequencing is the rapid filtering of human reads to survey for pathogens with high specificity and sensitivity. Metagenomes are inherently variable due to different microbes in the samples and their relative abundance, the size and architecture of genomes, and factors such as target DNA amounts in tissue samples (i.e. human DNA versus pathogen DNA concentration). This variation in metagenomes typically manifests in sequencing datasets as low pathogen abundance, a high number of host reads, and the presence of close relatives and complex microbial communities. In addition to these challenges posed by the composition of metagenomes, high numbers of reads generated from high-throughput deep sequencing pose immense computational challenges. Accurate identification of pathogens is confounded by individual reads mapping to multiple different reference genomes due to gene similarity in different taxa present in the community or close relatives in the reference database. Available global and local sequence aligners also vary in sensitivity, specificity, and speed of detection. The efficiency of detection of pathogens in clinical samples is largely dependent on the desired taxonomic resolution of the organisms. We have developed an efficient strategy that identifies “all against all” relationships between sequencing reads and reference genomes. Our approach allows for scaling to large reference databases and then genome reconstruction by aggregating global and local alignments, thus allowing genetic characterization of pathogens at higher taxonomic resolution. These results were consistent with strain level SNP genotyping and bacterial identification from laboratory culture.     

Quercetin-Induced Melanogenesis in a Reconstituted Three-Dimensional Human Epidermal Model

Quercetin (3,5,7,3',4'-pentahydroxyflavone) is one of the most abundant natural flavonoids. It is present in various common vegetables and fruits. In this report, we examined the effect of quercetin on melanogenesis using a three-dimensional reconstituted human epidermal culture model, MelanoDerm, which is a new commercially-available cultured human epidermis containing functional melanocytes. Treatment with 10 microM quercetin induced an increase of tyrosinase activity in cultured epidermis after 3-5 days in time-dependent manner. In the quercetin-treated epidermis, furthermore, melanin content and tyrosinase expression were markedly increased, as shown by immunohistochemistry after a 7-day culture period. Ultrastructural studies clearly indicated an accumulation of mature melanosomes (stages III and IV) inside the basal layer of the cultured epidermis after the quercetin treatment. In addition, the dendrites of melanocytes extended further towards the adjacent keratinocytes after quercetin treatment. These results suggest that quercetin has an effect on maturation of melanosomes and that quercetin has the potential to induced melanogenesis in human epidermis.     

Characterizing the Impact of Category Uncertainty on Human Auditory Categorization Behavior

Categorization is an important cognitive process. However, the correct categorization of a stimulus is often challenging because categories can have overlapping boundaries. Whereas perceptual categorization has been extensively studied in vision, the analogous phenomenon in audition has yet to be systematically explored. Here, we test whether and how human subjects learn to use category distributions and prior probabilities, as well as whether subjects employ an optimal decision strategy when making auditory-category decisions. We asked subjects to classify the frequency of a tone burst into one of two overlapping, uniform categories according to the perceived tone frequency. We systematically varied the prior probability of presenting a tone burst with a frequency originating from one versus the other category. Most subjects learned these changes in prior probabilities early in testing and used this information to influence categorization. We also measured each subject''s frequency-discrimination thresholds (i.e., their sensory uncertainty levels). We tested each subject''s average behavior against variations of a Bayesian model that either led to optimal or sub-optimal decision behavior (i.e. probability matching). In both predicting and fitting each subject''s average behavior, we found that probability matching provided a better account of human decision behavior. The model fits confirmed that subjects were able to learn category prior probabilities and approximate forms of the category distributions. Finally, we systematically explored the potential ways that additional noise sources could influence categorization behavior. We found that an optimal decision strategy can produce probability-matching behavior if it utilized non-stationary category distributions and prior probabilities formed over a short stimulus history. Our work extends previous findings into the auditory domain and reformulates the issue of categorization in a manner that can help to interpret the results of previous research within a generative framework.     

Characterizing Spatiotemporal Transcriptome of the Human Brain Via Low-Rank Tensor Decomposition

Statistics in Biosciences - Spatiotemporal gene expression data of the human brain offer insights on the spatial and temporal patterns of gene regulation during brain development. Most existing...     

Tracking and Predicting Human Somatic Cell Reprogramming Using Nuclear Characteristics

Reprogramming of human somatic cells to induced pluripotent stem cells (iPSCs) generates valuable resources for disease modeling, toxicology, cell therapy, and regenerative medicine. However, the reprogramming process can be stochastic and inefficient, creating many partially reprogrammed intermediates and non-reprogrammed cells in addition to fully reprogrammed iPSCs. Much of the work to identify, evaluate, and enrich for iPSCs during reprogramming relies on methods that fix, destroy, or singularize cell cultures, thereby disrupting each cell’s microenvironment. Here, we develop a micropatterned substrate that allows for dynamic live-cell microscopy of hundreds of cell subpopulations undergoing reprogramming while preserving many of the biophysical and biochemical cues within the cells’ microenvironment. On this substrate, we were able to both watch and physically confine cells into discrete islands during the reprogramming of human somatic cells from skin biopsies and blood draws obtained from healthy donors. Using high-content analysis, we identified a combination of eight nuclear characteristics that can be used to generate a computational model to predict the progression of reprogramming and distinguish partially reprogrammed cells from those that are fully reprogrammed. This approach to track reprogramming in situ using micropatterned substrates could aid in biomanufacturing of therapeutically relevant iPSCs and be used to elucidate multiscale cellular changes (cell-cell interactions as well as subcellular changes) that accompany human cell fate transitions.     

Predicting Human Age with Bloodstains by sjTREC Quantification

The age-related decline of signal joint T-cell receptor rearrangement excision circles (sjTRECs) in human peripheral blood has been demonstrated in our previous study and other reports. Until now, only a few studies on sjTREC detection in bloodstain samples were reported, which were based on a small sample of subjects of a limited age range, although bloodstains are much more frequently encountered in forensic practice. In this present study, we adopted the sensitive Taqman real-time quantitative polymerase chain reaction (qPCR) method to perform sjTREC quantification in bloodstains from individuals ranging from 0–86 years old (n = 264). The results revealed that sjTREC contents in human bloodstains were declined in an age-dependent manner (r = −0.8712). The formula of age estimation was Age  = −7.1815Y−42.458±9.42 (Y dCt_TBP-sjTREC; 9.42 standard error). Furthermore, we tested for the influence of short- or long- storage time by analyzing fresh and stored bloodstains from the same individuals. Remarkably, no statistically significant difference in sjTREC contents was found between the fresh and old DNA samples over a 4-week of storage time. However, significant loss (0.16–1.93 dCt) in sjTREC contents was detected after 1.5 years of storage in 31 samples. Moreover, preliminary sjTREC quantification from up to 20-year-old bloodstains showed that though the sjTREC contents were detectable in all samples and highly correlated with donor age, a time-dependent decrease in the correlation coefficient r was found, suggesting the predicting accuracy of this described assay would be deteriorated in aged samples. Our findings show that sjTREC quantification might be also suitable for age prediction in bloodstains, and future researches into the time-dependent or other potential impacts on sjTREC quantification might allow further improvement of the predicting accuracy.     

Predicting Human Genetic Interactions from Cancer Genome Evolution

Synthetic Lethal (SL) genetic interactions play a key role in various types of biological research, ranging from understanding genotype-phenotype relationships to identifying drug-targets against cancer. Despite recent advances in empirical measuring SL interactions in human cells, the human genetic interaction map is far from complete. Here, we present a novel approach to predict this map by exploiting patterns in cancer genome evolution. First, we show that empirically determined SL interactions are reflected in various gene presence, absence, and duplication patterns in hundreds of cancer genomes. The most evident pattern that we discovered is that when one member of an SL interaction gene pair is lost, the other gene tends not to be lost, i.e. the absence of co-loss. This observation is in line with expectation, because the loss of an SL interacting pair will be lethal to the cancer cell. SL interactions are also reflected in gene expression profiles, such as an under representation of cases where the genes in an SL pair are both under expressed, and an over representation of cases where one gene of an SL pair is under expressed, while the other one is over expressed. We integrated the various previously unknown cancer genome patterns and the gene expression patterns into a computational model to identify SL pairs. This simple, genome-wide model achieves a high prediction power (AUC = 0.75) for known genetic interactions. It allows us to present for the first time a comprehensive genome-wide list of SL interactions with a high estimated prediction precision, covering up to 591,000 gene pairs. This unique list can potentially be used in various application areas ranging from biotechnology to medical genetics.     

Reproducibility of In-Vivo OCT Measured Three-Dimensional Human Lamina Cribrosa Microarchitecture

Purpose

To determine the reproducibility of automated segmentation of the three-dimensional (3D) lamina cribrosa (LC) microarchitecture scanned in-vivo using optical coherence tomography (OCT).

Methods

Thirty-nine eyes (8 healthy, 19 glaucoma suspects and 12 glaucoma) from 49 subjects were scanned twice using swept-source (SS−) OCT in a 3.5×3.5×3.64 mm (400×400×896 pixels) volume centered on the optic nerve head, with the focus readjusted after each scan. The LC was automatically segmented and analyzed for microarchitectural parameters, including pore diameter, pore diameter standard deviation (SD), pore aspect ratio, pore area, beam thickness, beam thickness SD, and beam thickness to pore diameter ratio. Reproducibility of the parameters was assessed by computing the imprecision of the parameters between the scans.

Results

The automated segmentation demonstrated excellent reproducibility. All LC microarchitecture parameters had an imprecision of less or equal to 4.2%. There was little variability in imprecision with respect to diagnostic category, although the method tends to show higher imprecision amongst healthy subjects.

Conclusion

The proposed automated segmentation of the LC demonstrated high reproducibility for 3D LC parameters. This segmentation analysis tool will be useful for in-vivo studies of the LC.     

Predicting and Analyzing Interactions between Mycobacterium tuberculosis and Its Human Host

The outcome of infection by Mycobacterium tuberculosis (Mtb) depends greatly on how the host responds to the bacteria and how the bacteria manipulates the host, which is facilitated by protein–protein interactions. Thus, to understand this process, there is a need for elucidating protein interactions between human and Mtb, which may enable us to characterize specific molecular mechanisms allowing the bacteria to persist and survive under different environmental conditions. In this work, we used the interologs method based on experimentally verified intra-species and inter-species interactions to predict human-Mtb functional interactions. These interactions were further filtered using known human-Mtb interactions and genes that are differentially expressed during infection, producing 190 interactions. Further analysis of the subcellular location of proteins involved in these human-Mtb interactions confirms feasibility of these interactions. We also conducted functional analysis of human and Mtb proteins involved in these interactions, checking whether these proteins play a role in infection and/or disease, and enriching Mtb proteins in a previously predicted list of drug targets. We found that the biological processes of the human interacting proteins suggested their involvement in apoptosis and production of nitric oxide, whereas those of the Mtb interacting proteins were relevant to the intracellular environment of Mtb in the host. Mapping these proteins onto KEGG pathways highlighted proteins belonging to the tuberculosis pathway and also suggested that Mtb proteins might use the host to acquire nutrients, which is in agreement with the intracellular lifestyle of Mtb. This indicates that these interactions can shed light on the interplay between Mtb and its human host and thus, contribute to the process of designing novel drugs with new biological mechanisms of action.