Role of primary tumor volume and metastatic lymph node volume in response to curative effect of definitive radiotherapy for locally advanced head and neck cancer.

BACKGROUND: Studies have shown mixed results concerning the role of primary tumor volume (TV) and metastatic lymph node (NV) volume in response to the curative effect of definitive radiotherapy for locally advanced head and neck squamous cell carcinoma (LAHNSCC). OBJECTIVE: We aimed to evaluate the impact of TV and NV on the efficacy of radical radiotherapy in LAHNSCC patients, with the goal of guiding individualized therapy. PATIENTS AND METHODS: Patients with LAHNSCC who received radical radiation therapy and were reexamined within 6 months post-therapy from January 2012 to December 2021 were selected. The volumes of the primary tumors and metastatic lymph nodes were calculated by software and then were divided into a large TV group vs small TV group and a large NV group vs small NV group according to the relationship with the median. Additionally, patients who received concurrent chemoradiotherapy (CCRT) or not were divided into the CCRT group and the radiotherapy (RT) group. Patients with lymph node metastasis were divided into node concurrent chemotherapy (N-CCRT) group and a node metastatic chemotherapy (N-RT) group according to whether they received concurrent chemotherapy or not. The volume shrinkage rate (VSR), objective response rate (ORR), local control rate (LCR) and overall survival (OS) were recorded and analyzed. RESULTS: 96 patients were included in the primary tumor volume group, and 73 patients were included in the metastatic lymph node group. Receiver operating characteristic (ROC) curves were constructed for objective remission (OR) endpoints, and a volume threshold was defined for TV and NV patients. The threshold primary tumor volume was 32.45 cm3, and the threshold metastatic lymph node volume was 6.05 cm3.The primary TV shrinkage rates of the small TV and the large TV groups were basically the same, P = 0.801. Similarly, the ORR and LCR were not significantly different between the small TV group and the large TV group (PORR = 0.118, PLCR = 0.315). Additionally, the TV shrinkage rate did not significantly differ between the CCRT group and the RT group, P = 0.133. Additionally, there was no significant difference in ORR or LCR in CCRT group (PORR = 0.057, PLCR = 0.088). However, the metastatic lymph node volume shrinkage rate in the small NV group was significantly greater than that in the large NV group (P = 0.001). The ORR and LCR of the small NV subgroup were significantly greater than those of the large NV subgroup (PORR = 0.002, PLCR = 0.037). Moreover, compared with that of the N-RT group, the NV shrinkage rate of the N-CCRT group was 84.10 ± s3.11%, and the shrinkage rate was 70.76 ± s5.77% (P = 0.047). For the ORR and LCR, the N-CCRT group and N-RT group were significantly different (PORR = 0.030, PLCR = 0.037). The median OS of the whole group was 26 months. However, neither TV/NV nor concurrent chemotherapy seemed to influence OS. CONCLUSION: Primary tumor volume is not a prognostic factor for the response to curative effect radiotherapy in LAHNSCC patients. Nevertheless, metastatic lymph nodes are a prognostic factor for the response to curative effect radiotherapy in LAHNSCC patients. Patients with smaller lymph nodes have better local control.

Genome-Wide Network Analysis of Above- and Below-Ground Co-growth in Populus euphratica.

Tree growth is the consequence of developmental interactions between above- and below-ground compartments. However, a comprehensive view of the genetic architecture of growth as a cohesive whole is poorly understood. We propose a systems biology approach for mapping growth trajectories in genome-wide association studies viewing growth as a complex (phenotypic) system in which above- and below-ground components (or traits) interact with each other to mediate systems behavior. We further assume that trait-trait interactions are controlled by a genetic system composed of many different interactive genes and integrate the Lotka-Volterra predator-prey model to dissect phenotypic and genetic systems into pleiotropic and epistatic interaction components by which the detailed genetic mechanism of above- and below-ground co-growth can be charted. We apply the approach to analyze linkage mapping data of Populus euphratica, which is the only tree species that can grow in the desert, and characterize several loci that govern how above- and below-ground growth is cooperated or competed over development. We reconstruct multilayer and multiplex genetic interactome networks for the developmental trajectories of each trait and their developmental covariation. Many significant loci and epistatic effects detected can be annotated to candidate genes for growth and developmental processes. The results from our model may potentially be useful for marker-assisted selection and genetic editing in applied tree breeding programs. The model provides a general tool to characterize a complete picture of pleiotropic and epistatic genetic architecture in growth traits in forest trees and any other organisms.

Computational dissection of genetic variation modulating the response of multiple photosynthetic phenotypes to the light environment.

BACKGROUND: The expression of biological traits is modulated by genetics as well as the environment, and the level of influence exerted by the latter may vary across characteristics. Photosynthetic traits in plants are complex quantitative traits that are regulated by both endogenous genetic factors and external environmental factors such as light intensity and CO2 concentration. The specific processes impacted occur dynamically and continuously as the growth of plants changes. Although studies have been conducted to explore the genetic regulatory mechanisms of individual photosynthetic traits or to evaluate the effects of certain environmental variables on photosynthetic traits, the systematic impact of environmental variables on the dynamic process of integrated plant growth and development has not been fully elucidated. RESULTS: In this paper, we proposed a research framework to investigate the genetic mechanism of high-dimensional complex photosynthetic traits in response to the light environment at the genome level. We established a set of high-dimensional equations incorporating environmental regulators to integrate functional mapping and dynamic screening of gene‒environment complex systems to elucidate the process and pattern of intrinsic genetic regulatory mechanisms of three types of photosynthetic phenotypes of Populus simonii that varied with light intensity. Furthermore, a network structure was established to elucidate the crosstalk among significant QTLs that regulate photosynthetic phenotypic systems. Additionally, the detection of key QTLs governing the response of multiple phenotypes to the light environment, coupled with the intrinsic differences in genotype expression, provides valuable insights into the regulatory mechanisms that drive the transition of photosynthetic activity and photoprotection in the face of varying light intensity gradients. CONCLUSIONS: This paper offers a comprehensive approach to unraveling the genetic architecture of multidimensional variations in photosynthetic phenotypes, considering the combined impact of integrated environmental factors from multiple perspectives.

Neuron Contact Detection Based on Pipette Precise Positioning for Robotic Brain-Slice Patch Clamps.

A patch clamp is the "gold standard" method for studying ion-channel biophysics and pharmacology. Due to the complexity of the operation and the heavy reliance on experimenter experience, more and more researchers are focusing on patch-clamp automation. The existing automated patch-clamp system focuses on the process of completing the experiment; the detection method in each step is relatively simple, and the robustness of the complex brain film environment is lacking, which will increase the detection error in the microscopic environment, affecting the success rate of the automated patch clamp. To address these problems, we propose a method that is suitable for the contact between pipette tips and neuronal cells in automated patch-clamp systems. It mainly includes two key steps: precise positioning of pipettes and contact judgment. First, to obtain the precise coordinates of the tip of the pipette, we use the Mixture of Gaussian (MOG) algorithm for motion detection to focus on the tip area under the microscope. We use the object detection model to eliminate the encirclement frame of the pipette tip to reduce the influence of different shaped tips, and then use the sweeping line algorithm to accurately locate the pipette tip. We also use the object detection model to obtain a three-dimensional bounding frame of neuronal cells. When the microscope focuses on the maximum plane of the cell, which is the height in the middle of the enclosing frame, we detect the focus of the tip of the pipette to determine whether the contact between the tip and the cell is successful, because the cell and the pipette will be at the same height at this time. We propose a multitasking network CU-net that can judge the focus of pipette tips in complex contexts. Finally, we design an automated contact sensing process in combination with resistance constraints and apply it to our automated patch-clamp system. The experimental results show that our method can increase the success rate of pipette contact with cells in patch-clamp experiments.

Interactive Effects of Flooding Duration and Sediment Texture on the Growth and Adaptation of Three Plant Species in the Poyang Lake Wetland.

Flooding duration and sediment texture play vital roles in the growth and adaptation of wetland plants. However, there is a lack of research on the interactive effects of flooding duration and sediments on wetland plants. A two-factor experiment with flooding duration and sediment texture was designed in the study, involving three plant species commonly found in the Poyang Lake wetland (i.e., Carex cinerascens, Phalaris arundinacea, and Polygonum criopolitanum). Our findings were as follows: (i) Sediments play a crucial role in the growth and adaptation of hygrophilous plants, but they exhibited a weaker effect than flooding. (ii) Sediment texture mediates flooding to affect the stressing responses of wetland plant functional traits, including the leaf chlorophyll content, the plant height, and the number of leaves and ramets. (iii) Sediment texture forms interactive effects with flooding duration and directly influences hygrophilous plants. The results of this study help provide theoretical insights from a more scientific perspective for the prediction of hygrophilous plant dynamics and to facilitate the formulation of wetland management.

The genetic architecture of trait covariation in Populus euphratica, a desert tree.

Introduction: The cooperative strategy of phenotypic traits during the growth of plants reflects how plants allocate photosynthesis products, which is the most favorable decision for them to optimize growth, survival, and reproduction response to changing environment. Up to now, we still know little about why plants make such decision from the perspective of biological genetic mechanisms. Methods: In this study, we construct an analytical mapping framework to explore the genetic mechanism regulating the interaction of two complex traits. The framework describes the dynamic growth of two traits and their interaction as Differential Interaction Regulatory Equations (DIRE), then DIRE is embedded into QTL mapping model to identify the key quantitative trait loci (QTLs) that regulate this interaction and clarify the genetic effect, genetic contribution and genetic network structure of these key QTLs. Computer simulation experiment proves the reliability and practicability of our framework. Results: In order to verify that our framework is universal and flexible, we applied it to two sets of data from Populus euphratica, namely, aboveground stem length - underground taproot length, underground root number - underground root length, which represent relationships of phenotypic traits in two spatial dimensions of plant architecture. The analytical result shows that our model is well applicable to datasets of two dimensions. Discussion: Our model helps to better illustrate the cooperation-competition patterns between phenotypic traits, and understand the decisions that plants make in a specific environment that are most conducive to their growth from the genetic perspective.

A Multilayer Interactome Network Constructed in a Forest Poplar Population Mediates the Pleiotropic Control of Complex Traits.

The effects of genes on physiological and biochemical processes are interrelated and interdependent; it is common for genes to express pleiotropic control of complex traits. However, the study of gene expression and participating pathways in vivo at the whole-genome level is challenging. Here, we develop a coupled regulatory interaction differential equation to assess overall and independent genetic effects on trait growth. Based on evolutionary game theory and developmental modularity theory, we constructed multilayer, omnigenic networks of bidirectional, weighted, and positive or negative epistatic interactions using a forest poplar tree mapping population, which were organized into metagalactic, intergalactic, and local interstellar networks that describe layers of structure between modules, submodules, and individual single nucleotide polymorphisms, respectively. These multilayer interactomes enable the exploration of complex interactions between genes, and the analysis of not only differential expression of quantitative trait loci but also previously uncharacterized determinant SNPs, which are negatively regulated by other SNPs, based on the deconstruction of genetic effects to their component parts. Our research framework provides a tool to comprehend the pleiotropic control of complex traits and explores the inherent directional connections between genes in the structure of omnigenic networks.

A Holling Functional Response Model for Mapping QTLs Governing Interspecific Interactions.

Genes play an important role in community ecology and evolution, but how to identify the genes that affect community dynamics at the whole genome level is very challenging. Here, we develop a Holling type II functional response model for mapping quantitative trait loci (QTLs) that govern interspecific interactions. The model, integrated with generalized Lotka-Volterra differential dynamic equations, shows a better capacity to reveal the dynamic complexity of inter-species interactions than classic competition models. By applying the new model to a published mapping data from a competition experiment of two microbial species, we identify a set of previously uncharacterized QTLs that are specifically responsible for microbial cooperation and competition. The model can not only characterize how these QTLs affect microbial interactions, but also address how change in ecological interactions activates the genetic effects of the QTLs. This model provides a quantitative means of predicting the genetic architecture that shapes the dynamic behavior of ecological communities.

Genetic Architecture of Multiphasic Growth Covariation as Revealed by a Nonlinear Mixed Mapping Framework.

Trait covariation during multiphasic growth is of crucial significance to optimal survival and reproduction during the entire life cycle. However, current analyses are mainly focused on the study of individual traits, but exploring how genes determine trait interdependence spanning multiphasic growth processes remains challenging. In this study, we constructed a nonlinear mixed mapping framework to explore the genetic mechanisms that regulate multiphasic growth changes between two complex traits and used this framework to study stem diameter and stem height in forest trees. The multiphasic nonlinear mixed mapping framework was implemented in system mapping, by which several key quantitative trait loci were found to interpret the process and pattern of stem wood growth by regulating the ecological interactions of stem apical and lateral growth. We quantified the timing and pattern of the vegetative phase transition between independently regulated, temporally coordinated processes. Furthermore, we visualized the genetic machinery of significant loci, including genetic effects, genetic contribution analysis, and the regulatory relationship between these markers in the network structure. We validated the utility of the new mapping framework experimentally via computer simulations. The results may improve our understanding of the evolution of development in changing environments.

Spermidine-Activated Satellite Cells Are Associated with Hypoacetylation in ACVR2B and Smad3 Binding to Myogenic Genes in Mice.

Spermidine is an acetyltransferase inhibitor and a specific inducer of autophagy. Recently, spermidine is identified as a potential therapeutic agent for age-related muscle atrophy and inherited myopathies. However, the effect of spermidine on nonpathological skeletal muscle remains unclear. In this study, long-term spermidine administration in mice lowered the mean cross-sectional area of the gastrocnemius muscle and reduced the expression of myosin heavy chain isoforms in the muscle, which was associated with ubiquitination. Moreover, spermidine supplementation induced autophagy in satellite cells and enhanced satellite cell proliferation. ChIP assay revealed that spermidine repressed H3K56ac in the promoter of ACVR2B and lowered the binding affinity of Smad3 to the promoters of Myf5 and MyoD. Altogether, our results indicate that long-term administration of spermidine can activate satellite cells, as well as enhance autophagy, eventually resulting in muscle atrophy. In addition, H3K56ac and Smad3 emerged as key determinants of satellite cell activation.

On-column refolding and purification of recombinant human interleukin-1 receptor antagonist (rHuIL-1ra) expressed as inclusion body in Escherichia coli.

Recombinant human interleukin-1 receptor antagonist (rHuIL-1ra) was produced in E. coli as an inclusion body. rHuIL-1ra was purified to Over 98% purity by anion exchange chromatography after on-column refolding. The optimized processes produced more than 2 g pure refolded rHuIL-1ra per 1 l culture, corresponding to a 44% recovery, without an intermediate dialysis step. Refolded rHuIL-1ra had full biological activity with the MTT assay. An intramolecular disulfide linkage in the oxidized recombinant protein was suggested by data from HPLC and non-reducing SDS-PAGE.

Purification and characterization of recombinant truncated human interleukin-11 expressed as fusion protein in Escherichia coli.

Mature human interleukin-11 (HuIL-11) is a cytokine consisting of 178 amino acid residues that results from scission of the N-terminal signal peptide, consisting of 21 amino acid residaues, from the corresponding nascent polypeptide. A DNA fragment encoding a truncated HuIL-11 (trHuIL-11), with an additional 5 amino acid residues removed from the N-terminus, was cloned into vector pGEX-2T between the BamHI site and the EcoRI site. Upon transformation with Escherichia coli BL21, the construct over-produced a glutathione S-transferase (GST)-fused protein in a soluble form after IPTG induction. The fusion protein was initially fractionated with butyl-Sepharose 4 fast flow column and by affinity chromatography using a GSH-Sepharose 4B column. On-site enzymatic release with thrombin gave the target protein at 96% purity as judged by SDS-PAGE and HPLC. Expression of the interleukin as a GST-fused protein thus greatly improved downstream processing. Subsequent biological activity assay suggested that trHuIL-11 had similar activity profile to the naturally produced sample and may be a promising candidate for further development as biopharmaceutical.