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Somatic embryogenesis (SE) techniques have been established for micropropagation or basic research related to plant development in many conifer species. The frequent occurrence of non-embryogenic callus (NEC) during SE has impose constraints on the application of somatic embryogenesis SE in Larix kaempferi (Lamb.) Carr, but the potential regulatory mechanisms are poorly understood. In this study, integrated transcriptomic and metabolomic analyses were performed in embryogenic callus (EC) and NEC originating from a single immature zygotic embryo to better decipher the key molecular and metabolic mechanisms required for embryogenic potential maintenance. The results showed that a total of 13,842 differentially expressed genes (DEGs) were found in EC and NEC, among which many were enriched in plant hormone signal transduction, starch and sucrose metabolism, phenylpropanoid biosynthesis, flavonoid biosynthesis, and the biosynthesis of amino acids pathways. Metabolite profiling showed that 441 differentially accumulated metabolites (DAMs) were identified in EC and NEC. Both EC and NEC had vigorous primary metabolic activities, while most secondary metabolites were upregulated in NEC. Many totipotency-related transcription factor (TF) genes such as BBMs , WUSs , and LEC1 showed higher expression levels in EC compared with NEC, which may result in the higher accumulation of indole 3-acetic acid (IAA) in EC. NEC was characterized by upregulation of genes and metabolites associated with stress responses, such as DEGs involved in jasmonic acid (JA) and ethylene (ETH) biosynthesis and signal transduction pathways, and DEGs and DAMs related to phenylpropanoid and flavonoid biosynthesis. We predicted and analyzed TFs that could target several key co-expressed structural DEGs including two C4H genes, two CcoAOMT genes and three HCT genes involved in phenylpropanoid and flavonoid biosynthesis. Based on the targeted relationship and the co-expression network, two ERFs (Lk23436 and Lk458687), one MYB (Lk34626) and one C2C2-dof (Lk37167) may play an important role in regulating phenolic acid and flavonoid biosynthesis by transcriptionally regulating the expression of these structural genes. This study shows an approach involving integrated transcriptomic and metabolic analyses to obtain insights into molecular events underlying embryogenic potential maintenance and the biosynthesis mechanisms of key metabolites involving TF regulation, which provides valuable information for the improvement of SE efficiency in L. kaempferi .

Myricaria laxiflora is a rare and endangered shrub in China, and its wild populations are threatened by diverse abiotic stresses. Heat shock factors (HSFs) are essential for coping with environmental stresses, however, information about HSFs in M. laxiflora is limited. Currently, a total of 21 MlHSFs were systematically detected in the latest released genome of M. laxiflora . The MlHSFs were assigned into three subgroups (i.e., A, B and C) according to their conserved protein domains. All the MlHSFs were predicted to localize in nucleus with the conserved HSF-type DNA-binding domain, suggesting their potential roles as transcription factors. MlHSF proteins from the same subgroup shared similar conserved protein domains, the variable C-terminal domains of HSF proteins implied their functional diversity. A total of six gene duplication events from the same subgroup were detected among the HSF gene members, and all the duplication events belonged to segmental duplication. Furthermore, plenty of cis -elements were detected upstream of HSF gene members, these cis -elements could be primarily categorized into light response, as well as stress and hormone response. Transcriptomic analysis showed that most MlHSFs were significantly inhibited by cadmium and waterlogging stresses in most cases, however, MlHSFC1 was significantly stimulated by both cadmium and waterlogging stresses in M. laxiflora . A comprehensive co-expression network of MlHSFs has been established to reveal the potential roles of MlHSFs in photosynthesis, redox homeostasis and protein folding under abiotic stresses. The results obtained suggested the crucial roles of MlHSFs in adapting to environmental stresses in M. laxiflora .

As mainstream solvers for black-box optimization problems, evolutionary computation (EC) methods struggle with finding desired optima of lower attractiveness. Researchers have designed benchmark problems for simulating this scenario and proposed a large number of niching methods for solving those problems. However, factors causing the difference in attractiveness between local optima are often coupled in existing benchmark problems, which makes it hard to clarify the primary contributors. In addition, niching methods are carried out using a combination of several niching techniques and reproduction operators, which enhances the difficulty of identifying the essential effects of different niching techniques. To obtain an in-depth understanding of the above issue, thus offering actionable insights for optimization tasks challenged by the multimodality, this paper uses continuous optimization as an entry point and focuses on analyzing differential behaviors of EC methods across different basins of attraction. Specifically, we quantitatively investigate the independent impacts of three features of basins of attraction via corresponding benchmark scenarios generated by Free Peaks. The results show that the convergence biases induced by the difference in distribution only occur in EC methods with less uniform reproduction operators. On the other hand, convergence biases induced by differences in size and average fitness, both of which equate to the difference in size of superior region, pose a challenge to any EC method driven by objective functions. As niching methods limit survivor selection to specified neighborhoods to mitigate the latter biases, we abstract five niching techniques from these methods by their definitions of neighborhood for restricted competition, thus identifying key parameters that govern their efficacy. Experiments confirm these parameters’ critical roles in reducing convergence biases.

Background Picea species are distributed and planted world-wide due to their great ecological and economic values. It has been reported that Picea species vary widely in growth traits in a given environment, which reflects genetic and phenotypic differences among species. However, key physiological processes underlying tree growth and the influencing factors on them are still unknown. Results Here, we examined needle structures, needle chemical components, physiological characteristics and growth traits across five Picea species in a common garden in Tianshui, Gansu province in China: Picea glauca , P. mariana , P. likiangensis , P. koraiensis , and P. crassifolia , among which P. glauca and P. mariana were introduced from North America, P. likiangensis was from Lijiang, Yunan province in China, P. koraiensis was from Yichun, Heilongjiang province in China, and P. crassifolia was native to the experimental site. It was found that nearly all traits varied significantly among species. Tissue-level anatomical characteristics and leaf mass per area (LMA) were affected by needle size, but the variations of them were not associated with the variations in photosynthetic and biochemical capacity among species. Variations in area-based maximum photosynthesis (P nmax ) were affected by stomatal conductance (g s ), mesophyll conductance (g m ) and biochemical parameters including maximum carboxylation rate (V cmax ), and maximum electron transport rate (J max ). The fraction of N allocated to different photosynthetic apparatus displayed contrasting values among species, which contributed to the species variations in photosynthetic nitrogen use efficiency (PNUE) and P nmax . Additionally, all growth traits were positively correlated with P nmax and PNUE. Conclusion Needle structures are less important than needle biochemical parameters in determining the variations in photosynthetic capacity across the five Picea species. P nmax and PNUE are closedly associated with the fraction of N allocated to photosynthetic apparatus (P photo ) compared with leaf N content per area (N area ). The tremendous growth differences among the five Picea species were substantially related to the interspecies variation in P nmax and PNUE.

Optimization problems often feature local optima with a significant difference in the basin of attraction (BoA), making evolutionary computation methods prone to discarding solutions located in less-attractive BoAs, thereby posing challenges to the search for optima in these BoAs. To enhance the ability to find these optima, various niching methods have been proposed to restrict the competition scope of individuals to their specific neighborhoods. However, redundant searches in more-attractive BoAs as well as necessary searches in less-attractive BoAs can only be promoted simultaneously by these methods. To address this issue, we propose a general framework for niching methods named niching-driven divide-and-conquer hill exploration (NDDCHE). Through gradually learning BoAs from the search results of a niching method and dividing the problem into subproblems with a much smaller number of optima, NDDCHE aims to bring a more balanced distribution of searches in the BoAs of optima found so far, and thus enhance the niching method’s ability to find optima in less-attractive BoAs. Through experiments where niching methods with different categories of niching techniques are integrated with NDDCHE and tested on problems with significant differences in the size of the BoA, the effectiveness and the generalization ability of NDDCHE are proven.

BackgroundLaparoscopic lateral pelvic lymph node dissection (LPLND) in rectal cancer surgery requires considerable skill because the pelvic arteries, which need to be located to guide the dissection, are covered by other tissues and cannot be observed on laparoscopic views. Therefore, surgeons need to localize the pelvic arteries accurately before dissection, to prevent injury to these arteries.MethodsThis report proposes a surgical navigation system to facilitate artery localization in laparoscopic LPLND by combining ultrasonic imaging and laparoscopy. Specifically, free-hand laparoscopic ultrasound (LUS) is employed to capture the arteries intraoperatively in this approach, and a laparoscopic vision-based tracking system is utilized to track the LUS probe. To extract the artery contours from the two-dimensional ultrasound image sequences efficiently, an artery extraction framework based on local phase-based snakes was developed. After reconstructing the three-dimensional intraoperative artery model from ultrasound images, a high-resolution artery model segmented from preoperative computed tomography (CT) images was rigidly registered to the intraoperative artery model and overlaid onto the laparoscopic view to guide laparoscopic LPLND.ResultsExperiments were conducted to evaluate the performance of the vision-based tracking system, and the average reconstruction error of the proposed tracking system was found to be 2.4 mm. Then, the proposed navigation system was quantitatively evaluated on an artery phantom. The reconstruction time and average navigation error were 8 min and 2.3 mm, respectively. A navigation system was also successfully constructed to localize the pelvic arteries in laparoscopic and open surgeries of a swine. This demonstrated the feasibility of the proposed system in vivo. The construction times in the laparoscopic and open surgeries were 14 and 12 min, respectively.ConclusionsThe experimental results showed that the proposed navigation system can guide laparoscopic LPLND and requires a significantly shorter setting time than the state-of-the-art navigation systems do.

Background Segmentation of important structures in temporal bone CT is the basis of image-guided otologic surgery. Manual segmentation of temporal bone CT is time- consuming and laborious. We assessed the feasibility and generalization ability of a proposed deep learning model for automated segmentation of critical structures in temporal bone CT scans. Methods Thirty-nine temporal bone CT volumes including 58 ears were divided into normal (n = 20) and abnormal groups (n = 38). Ossicular chain disruption (n = 10), facial nerve covering vestibular window (n = 10), and Mondini dysplasia (n = 18) were included in abnormal group. All facial nerves, auditory ossicles, and labyrinths of the normal group were manually segmented. For the abnormal group, aberrant structures were manually segmented. Temporal bone CT data were imported into the network in unmarked form. The Dice coefficient (DC) and average symmetric surface distance (ASSD) were used to evaluate the accuracy of automatic segmentation. Results In the normal group, the mean values of DC and ASSD were respectively 0.703, and 0.250 mm for the facial nerve; 0.910, and 0.081 mm for the labyrinth; and 0.855, and 0.107 mm for the ossicles. In the abnormal group, the mean values of DC and ASSD were respectively 0.506, and 1.049 mm for the malformed facial nerve; 0.775, and 0.298 mm for the deformed labyrinth; and 0.698, and 1.385 mm for the aberrant ossicles. Conclusions The proposed model has good generalization ability, which highlights the promise of this approach for otologist education, disease diagnosis, and preoperative planning for image-guided otology surgery.

For a long time, there has been a gap between theoretical optimization research and real-world applications. A key challenge is that many real-world problems are black-box problems, making it difficult to identify their characteristics and, consequently, select the most effective algorithms to solve them. Fortunately, the Nearest-Better Network has emerged as an effective tool for analyzing the characteristics of problems, regardless of dimensionality. In this paper, we conduct an in-depth experimental analysis of real-world functions from the CEC 2022 and CEC 2011 competitions using the NBN. Our experiments reveal that real-world problems often exhibit characteristics such as unclear global structure, multiple attraction basins, vast neutral regions around the global optimum, and high levels of ill conditioning.

Lung cancer is among the most lethal malignancies with a high metastasis and recurrence rate. Recent studies indicate that tumors contain a subset of stem-like cancer cells that possess certain stem cell properties. Herein, we used Hoechst 33342 dye efflux assay and flow cytometry to isolate and characterize the side population (SP) cells from human lung cancer cell line NCI-H460 (H460). We show that the H460 SP cells harbor stem-like cells as they can readily form anchorage-independent floating spheres, possess great proliferative potential, and exhibit enhanced tumorigenicity. Importantly, the H460 SP cells were able to self-renew both in vitro and in vivo. Finally, we show that the H460 SP cells preferentially express ABCG2 as well as SMO, a critical mediator of the Hedgehog (HH) signaling, which seems to play an important role in H460 lung cancer cells as its blockage using Cyclopamine greatly inhibits cell-cycle progression. Collectively, our results lend further support to the existence of lung cancer stem cells and also implicate HH signaling in regulating large-cell lung cancer (stem) cells.

Background Phytohormones are the key factors regulating vascular development in plants, and they are also involved in tension wood (TW) formation. Although the theory of hormone distribution in TW formation is widely supported, the effects of endogenous hormones on TW formation have not yet been assessed. In this study, TW formation was induced in Catalpa bungei by artificial bending. The phytohormone content of TW, opposite wood (OW) and normal wood (NW) was determined using liquid chromatography-mass spectrometry (LC-MS), and transcriptome sequencing was performed. The hormone content and related gene expression data were comprehensively analyzed. Results The results of analyses of the plant hormone contents indicated significantly higher levels of cis-zeatin (cZ), indoleacetic acid (IAA) and abscisic acid (ABA) in TW than in OW. Genes involved in the IAA and ABA synthesis pathways, such as ALDH (evm.model.group5.1511) and UGT (evm.model.scaffold36.20), were significantly upregulated in TW. and the expression levels of ARF (evm.model.group5.1332), A-ARR (evm.model.group0.1600), and TCH4 (evm.model.group2.745), which participate in IAA, cZ and Brassinolide (BR) signal transduction, were significantly increased in TW. In particular, ARF expression may be regulated by long noncoding RNAs (lncRNAs) and the HD-ZIP transcription factor ATHB-15. Conclusions We constructed a multiple hormone-mediated network of C. bungei TW formation based on hormone levels and transcriptional expression profiles were identified during TW formation.