Biology subjects

Lai, X.

Publications and source records attributed to Lai, X..

6 recordsLinked to original sources

bioRxiv2018

Multiple modulation synthesis with high spatial resolution for noninvasive deep neurostimulation

Noninvasive neurostimulation plays a pivotal role in direct control of neural circuit and modulating neuronal function. However, it is difficult to balance both spatial focality and depth of penetration in stimulating deep neurons. Here, we designed time-division, frequency & polarity modulation synthesis (TMFPMS) for stimulating deep neurons noninvasively with low-frequency envelope. We demonstrated its spatial resolution: mm-level via computational simulation including finite element analysis and Hodgkin-Huxley action potential model. Taken together, the results of this study indicate that TMFPMS neurostimulation with high spatial resolution is steerable and may replace traditional implanted electrode.

neuroscience↗

bioRxiv2018

Niacin fine-tunes energy homeostasis through canonical GPR109A signaling

Niacin has long been considered as a high-potency drug for beneficially treating lipid abnormalities, however, its anti-atherosclerotic effects have been challenged by recent studies. Here, we demonstrated that oral supplementation of niacin resulted in a significant reduction in body weight and fat mass without affecting food intake in high-fat diet-fed wild-type mice, but not in GPR109A-defeicient mice. Further investigation showed that niacin challenge led to a remarkable inhibition of hepatic lipogenesis via a GPR109A-dependent ERK1/2/AMPK pathway. Additionally, we demonstrated that niacin treatment stimulated thermogenesis in brown adipose tissue by induction of thermogenic genes via GPR109A. Moreover, we observed that mice exposed to niacin exhibited a dramatic decrease in intestinal absorption of fatty acids. Together, our data demonstrate that acting on GPR109A, niacin shows the potential to maintain energy homeostasis by fine-tuning hepatic lipogenesis, BAT/beige thermogenesis and intestinal fat absorption, representing a potential approach to the treatment of lipid abnormalities.

cell biology↗

bioRxiv2018

Towards personalized computer simulation of breast cancer treatment: a multi-scale pharmacokinetic and pharmacodynamic model informed by multi-type patient data

Mathematical modeling and simulation have emerged as a potentially powerful, time and cost effective approach to personalized cancer treatment. The usefulness of mechanistic models to disentangle complex multi-scale cancer processes such as treatment response has been widely acknowledged. However, a major barrier for multi-scale models to predict the outcomes of therapeutic regimens in a particular patient lies in their initialization and parameterization which need to reflect individual cancer characteristics accurately. In this study we use multi-type routinely acquired measurements on a single breast tumor, including histopathology, magnetic resonance imaging, and molecular profiling to personalize parts of a complex multi-scale model of breast cancer treated with chemotherapeutic and anti-angiogenic agents. We model the dynamics of drugs in tissue (pharmacokinetics) and the corresponding effects on their targets (pharmacodynamics). We developed a open-source computer program that simulates cross-sections of tumors under 12-week therapy regimes and use it to individually reproduce and elucidate treatment outcomes of four patients. For two of the tumors that did not respond to therapy, we used model simulations to suggest alternative regimes, depending on their individual characteristics, with improved outcomes. We found that more frequent doses of chemothereapy reduce tumor burden in a low proliferative tumor while lower doses of anti-angiogenic agents improve drug penetration in a poorly perfused tumor. In addition to bridge multi-type clinical data to shed light on individual treatment outcomes, our approach identified a few tumor-related aspects that need to be clinically portraited better to allow for future model-driven personalized cancer therapy.

cancer biology↗

bioRxiv2017

Parallels between artificial selection in temperate maize and natural selection in the cold-adapted crop-wild relative Tripsacum

Artificial selection has produced varieties of domesticated maize which thrive in temperate climates around the world. However, the direct progenitor of maize, teosinte, is indigenous only to a relatively small range of tropical and sub-tropical latitudes and grows poorly or not at all outside of this region. Tripsacum, a sister genus to maize and teosinte, is naturally endemic to the majority of areas in the western hemisphere where maize is cultivated. A full-length reference transcriptome for Tripsacum dactyloides generated using long-read isoseq data was used to characterize independent adaptation to temperate climates in this clade. Genes related to phospholipid biosynthesis, a critical component of cold acclimation on other cold adapted plant lineages, were enriched among those genes experiencing more rapid rates of protein sequence evolution in T. dactyloides. In contrast with previous studies of parallel selection, we find that there is a significant overlap between the genes which were targets of artificial selection during the adaptation of maize to temperate climates and those which were targets of natural selection in temperate adapted T. dactyloides. This overlap between the targets of natural and artificial selection suggests genetic changes in crop-wild relatives associated with adaptation to new environments may be useful guides for identifying genetic targets for breeding efforts aimed at adapting crops to a changing climate.

plant biology↗

bioRxiv2017

Largely unlinked gene sets targeted by selection for domestication syndrome phenotypes in maize and sorghum

The domestication of diverse grain crops from wild grasses resulted from artificial selection for a suite of overlapping traits producing changes referred to in aggregate as \"domestication syndrome\". Parallel phenotypic change can be accomplished by either selection on orthologous genes, or selection on non-orthologous genes with parallel phenotypic effects. To determine how often artificial selection for domestication traits in the grasses targeted orthologous genes, we employed resequencing data from wild and domesticated accessions of Zea (maize) and Sorghum (sorghum). Many \"classic\" domestication genes identified through QTL mapping in populations resulting from wild/domesticated crosses indeed show signatures of parallel selection in both maize and sorghum. However, the overall number of genes showing signatures of parallel selection in both species is not significantly different from that expected by chance. This suggests that, while a small number of genes will extremely large phenotypic effects have been targeted repeatedly by artificial selection during domestication, the optimization portion of domestication targeted small and largely non-overlapping subsets of all possible genes which could produce equivalent phenotypic alterations.

plant biology↗

bioRxiv2017

STAG-CNS: An Order-Aware Conserved Non-coding Sequences Discovery Tool For Arbitrary Numbers of Species

One method for identifying noncoding regulatory regions of a genome is to quantify rates of divergence between related species, as functional sequence will generally diverge more slowly. Most approaches to identifying these conserved noncoding sequences (CNS) based on alignment have had relatively large minimum sequence lengths ([>=]15 base pair) compared to the average length of known transcription factor binding sites. To circumvent this constraint, STAG-CNS integrates data from the promoters of conserved orthologous genes in three or more species simultaneously. Using data from up to six grass species made it possible to identify conserved sequences as short at 9 base pairs with FDP [<=] 0.05. These CNS exhibit greater overlap with open chromatin regions identified using DNase I hypersensitivity, and are enriched in the promoters of genes involved in transcriptional regulation. STAG-CNS was further employed to characterize loss of conserved noncoding sequences associated with retained duplicate genes from the ancient maize polyploidy. Genes with fewer retained CNS show lower overall expression, although this bias is more apparent in samples of complex organ systems containing many cell types, suggesting CNS loss may correspond to a reduced number of expression contexts rather than lower expression levels across the entire ancestral expression domain.

bioinformatics↗