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Abstract Career planning consists of a series of decisions that will significantly impact one’s life. However, current recommendation systems have serious limitations, including the lack of effective artificial intelligence algorithms for long-term career planning, and the lack of efficient reinforcement learning (RL) methods for dynamic systems. To improve the long-term recommendation, this work proposes an intelligent sequential career planning system featuring a career path rating mechanism and a new RL method coined as the stochastic subsampling reinforcement learning (SSRL) framework. After proving the effectiveness of this new recommendation system theoretically, we evaluate it computationally by gauging it against several benchmarks under different scenarios representing different user preferences in career planning. Numerical results have demonstrated that our system is superior to other benchmarks in locating promising optimal career paths for users in long-term planning. Case studies have further revealed that our SSRL career path recommendation system would encourage people to gradually improve their career paths to maximize long-term benefits. Moreover, we have shown that the initial state (i.e., the first job) can have a significant impact, positively or negatively, on one’s career, while in the long-term view, a carefully planned career path following our recommendation system may mitigate the negative impact of a lackluster beginning in one’s career life.

Abstract Several reports have presented that balanced chromosomal rearrangements (BCRs) carriers with normal phenotypes may be carriers of complex rearrangements. However, the incidence and PGT clinical outcomes of cryptic complex chromosome rearrangements (CCCRs) in individuals with BCRs is remain unknown. We recruited a cohort of 1,264 individuals with BCR carriers from 2016 to 2021 at the Reproductive and Genetic Hospital of CITIC Xiangya. Peripheral blood was collected for karyotyping and genomic DNA extraction and the PGT-SR clinical outcomes of CCCRs carriers were analyzed and compared with those of BCR carriers. Our findings revealed that 3.6% (45/1,264) of BCR carriers had CCCRs, involving 3–25 breakpoints on 1–3 chromosomes. Furthermore, when mate-pair sequencing was employed, 63.3% (19/30) of CCCR carriers were found to have chromosome rearrangements that were different from those identified by the MicroSeq technique. And the transferable embryo rate of CCCR carriers with 3 chromosomes was significantly lower than that of CCCR carriers with only 1–2 chromosomes. In this research, we revealed that some of the BCR carriers were actually CCCR carriers, and the prognosis of PGT in CCCR carriers with one or two chromosomes is better than that of CCCR carriers with three chromosomes.

Abstract The hippocampus is a critical component of the brain and is associated with many neurological disorders. It can be further subdivided into several subfields, and accurate segmentation of these subfields is of great significance for diagnosis and research. However, the structures of hippocampal subfields are irregular and have complex boundaries, and their voxel values are close to surrounding brain tissues, making the segmentation task highly challenging. Currently, many automatic segmentation tools exist for hippocampal subfield segmentation, but they suffer from high time costs and low segmentation accuracy. In this paper, we propose a new dual-branch segmentation network structure (DSnet) based on deep learning for hippocampal subfield segmentation. While traditional convolutional neural network-based methods are effective in capturing hierarchical structures, they struggle to establish long-term dependencies. The DSnet integrates the Transformer architecture and a hybrid attention mechanism, enhancing the network’s global perceptual capabilities. Moreover, the dual-branch structure of DSnet leverages the segmentation results of the hippocampal region to facilitate the segmentation of its subfields. We validate the efficacy of our algorithm on the public Kulaga-Yoskovitz dataset. Experimental results indicate that our method is more effective in segmenting hippocampal subfields than conventional single-branch network structures. Compared to the classic 3D U-Net, our proposed DSnet improves the average Dice accuracy of hippocampal subfield segmentation by 0.57%.

JAK2/STAT signaling participates in the Ph-negative myeloproliferative neoplasms (MPN) pathophysiology and has been targeted by ruxolitinib, a JAK1/2 inhibitor. In the present study, the impact of ruxolitinib treatment on cytoskeleton-related genes expression was explored. In SET2 cells, AURKA and AURKB expression/activity were downregulated in a dose- and time-dependent manner by ruxolitinib. Reversine, a multikinase inhibitor selective for aurora kinases, reduced cell viability in a dose- and/or time-dependent manner in JAK2V617F cells. Reversine significantly increased apoptosis and mitotic catastrophe, and reduced cell proliferation and clonogenic capacity in SET2 and HEL cells. In the molecular scenario, reversine induced DNA damage and apoptosis markers, as well as, reduced AURKA and AURKB expression/activity. In SET2 cells, reversine modulated the expression of 32 out of 84 apoptosis-related genes investigated, including downregulation of antiapoptotic (BCL2, BCL2L1, and BIRC5) and upregulation of proapoptotic (BIK, BINP3, and BNIP3L) genes. Synergism experiments indicated that low dose of reversine had a potentiating effect under ruxolitinib treatment at low doses in SET2 cells. In summary, our exploratory study establishes new targets, related to the regulation of the cellular cytoskeleton, for potential pharmacological intervention in MPN. These findings indicate that AURKA and AURKB participate in the JAK2/STAT signaling pathway and contribute to the MPN phenotype. [ABSTRACT FROM AUTHOR]

Abstract Single image dehazing has received a lot of concern and achieved great success with the help of deep-learning models. Yet, the performance is limited by the local limitation of convolution. To address such a limitation, we design a novel deep learning dehazing model by combining the transformer and guided filter, which is called as Deep Guided Transformer Dehazing Network. Specially, we address the limitation of convolution via a transformer-based subnetwork, which can capture long dependency. Haze is dependent on the depth, which needs global information to compute the density of haze, and removes haze from the input images correctly. To restore the details of dehazed result, we proposed a CNN sub-network to capture the local information. To overcome the slow speed of the transformer-based subnetwork, we improve the dehazing speed via a guided filter. Extensive experimental results show consistent improvement over the state-of-the-art dehazing on natural haze and simulated haze images.

Abstract A self-organized phenomenon in postural coordination is essential for understanding the auto-switching mechanism of in-phase and anti-phase postural coordination modes during standing and related supra-postural activities. Previously, a model-based approach was proposed to reproduce such self-organized phenomenon. However, if we set this problem including the process of how we establish the internal predictive model in our central nervous system, the learning process is critical to be considered for establishing a neural network for managing adaptive postural control. Particularly when body characteristics may change due to growth or aging or are initially unknown for infants, a learning capability can improve the hyper-adaptivity of human motor control for maintaining postural stability and saving energy in daily living. This study attempted to generate a self-organizing neural network that can adaptively coordinate the postural mode without assuming a prior body model regarding body dynamics and kinematics. Postural coordination modes are reproduced in head-target tracking tasks through a deep reinforcement learning algorithm. The transitions between the postural coordination types, i.e. in-phase and anti-phase coordination modes, could be reproduced by changing the task condition of the head tracking target, by changing the frequencies of the moving target. These modes are considered emergent phenomena existing in human head tracking tasks. Various evaluation indices, such as correlation, and relative phase of hip and ankle joint, are analyzed to verify the self-organizing neural network performance to produce the postural coordination transition between the in-phase and anti-phase modes. In addition, after learning, the neural network can also adapt to continuous task condition changes and even to unlearned body mass conditions keeping consistent in-phase and anti-phase mode alternation.

Abstract LncRNAs represent a class of RNA transcripts of more than 200 nucleotides (nt) in length without discernible protein-coding potential. The expression levels of lncRNAs are significantly affected by stress or developmental cues. Recent studies have shown that lncRNAs participate in fruit development and ripening processes in tomato and strawberry; however, in other fleshy fruits, the association between lncRNAs and fruit ripening remains largely elusive. Here, we constructed 9 ssRNA-Seq libraries from three different peach (Prunus persica) fruit developmental stages comprising the first and second exponential stages and the fruit-ripening stage. In total, 1500 confident lncRNAs from 887 loci were obtained according to the bioinformatics analysis. The lncRNAs identified in peach fruits showed distinct characteristics compared with protein-coding mRNAs, including lower expression levels, lower complexity of alternative splicing, shorter isoforms and smaller numbers of exons. Expression analysis identified 575 differentially expressed lncRNAs (DELs) classified into 6 clusters, among which members of Clusters 1, 2, 4 and 5 were putatively associated with fruit development and ripening processes. Quantitative real-time PCR revealed that the DELs indeed had stage-specific expression patterns in peach fruits. GO and KEGG enrichment analysis revealed that DELs might be associated with fruit-ripening-related physiological and metabolic changes, such as flavonoid biosynthesis, fruit texture softening, chlorophyll breakdown and aroma compound accumulation. Finally, the similarity analysis of lncRNAs within different plant species indicated the low sequence conservation of lncRNAs. Our study reports a large number of fruit-expressed lncRNAs and identifies fruit development phase-specific expressed lncRNA members, which highlights their potential functions in fruit development and ripening processes and lays the foundations for future functional research.

Abstract Mitochondrial topoisomerase I (TOP1MT) is a type IB topoisomerase encoded in the nucleus of vertebrate cells. In contrast to the other five human topoisomerases, TOP1MT possesses two high frequency single nucleotide variants (SNVs), rs11544484 (V256I, Minor Allele Frequency = 0.27) and rs2293925 (R525W, MAF = 0.45), which tend to be mutually exclusive across different human ethnic groups and even more clearly in a cohort of 129 US patients with breast cancer and in the NCI-60 cancer cell lines. We expressed these two TOP1MT variants and the double-variant (V256I-R525W) as recombinant proteins, as well as a less common variant E168G (rs200673353, MAF = 0.001), and studied their biochemical properties by magnetic tweezers-based supercoil relaxation and classical DNA relaxation assays. Variants showed reduced DNA relaxation activities, especially the V256I variant towards positively supercoiled DNA. We also found that the V256I variant was enriched to MAF = 0.64 in NCI-60 lung carcinoma cell lines, whereas the TOP1MT R525W was enriched to MAF = 0.65 in the NCI-60 melanoma cell lines. Moreover, TOP1MT expression correlated with the 256 variants in the NCI-60 lung carcinoma cell lines, valine with high expression and isoleucine with low expression. Our results are discussed in the context of evolution between the nuclear and mitochondrial topoisomerases and potential cancer predisposition.

Abstract Tungsten-doped VO2 thin films have been synthesized by a modified sol–gel process and followed by a post annealing. Vanadium pentoxide and tungstic acid as raw materials with the addition of hydrogen peroxide, concentrated hydrochloric acid (catalyst) and oxalic acid used as reducing agent were reacted in isobutanol. Finally, the uniform sol of vanadyl oxalate in isobutanol solvent was obtained as precursor. Detailed study suggested that W doped in VO2 introduces additional electron carriers and induces the formation of V3+. Post annealing under vacuum promotes the releasing of chemical stress and generates oxygen vacancies in the samples. Temperature dependent transmittance study revealed that the releasing of chemical stress and deliberately introducing oxygen vacancies in W-doped VO2 films have positive effects on enhancing its switching ability in the infrared transmittance as the metal-insulator transition (MIT) occurs. The largest switching of transmittance was obtained about 48% in the infrared range at 43 °C in 1.5%W doped VO2 films, which is significantly larger than the reported ones. The findings in this work open a new way to synthesize the novel and thermochromic W doped VO2 films with facility and low cost. Therefore, it has extensive application to construct smart windows and electronic devices.

Abstract In vitro induced human regulatory T cells (iTregs) have demonstrated in vivo therapeutic utility, but pathways regulating their function have not been elucidated. Here, we report that human iTregs generated in vitro from naïve cord blood cells preferentially recruit Disc large homolog 1 (Dlgh1) and exclude protein kinase C (PKC)-θ from immunological synapses formed on supported lipid bilayers with laterally mobile ICAM-1 and anti-CD3 mAb. Also, iTregs display elevated Dlgh1 overall and Dlgh1-dependent p38 phosphorylation, higher levels of phosphatase and tensin homolog (PTEN), and diminished Akt phosphorylation. Pharmacological interruption of PKC-θ increases and Dlgh1 silencing decreases the ability of iTregs to suppress interferon-γ production by CD4+CD25− effector T cells (Teff). Comparison with expanded cord blood-derived CD4+CD25hi tTreg and expanded Teffs from the same donors indicate that iTreg are intermediate between expanded CD4+CD25hi tTregs and Teffs, whereas modulation of suppressive activities by PKC-θ and Dlgh1 signaling pathways are shared.

Abstract The genetic etiology and the contribution of rare genetic variation in multiple sclerosis (MS) has not yet been elucidated. Although familial forms of MS have been described, no convincing rare and penetrant variants have been reported to date. We aimed to characterize the contribution of rare genetic variation in familial and sporadic MS and have identified a family with two sibs affected by concomitant MS and malignant melanoma (MM). We performed whole exome sequencing in this primary family and 38 multiplex MS families and 44 sporadic MS cases and performed transcriptional and immunologic assessment of the identified variants. We identified a potentially causative homozygous missense variant in NLRP1 gene (Gly587Ser) in the primary family. Further possibly pathogenic NLRP1 variants were identified in the expanded cohort of patients. Stimulation of peripheral blood mononuclear cells from MS patients with putatively pathogenic NLRP1 variants showed an increase in IL-1B gene expression and active cytokine IL-1β production, as well as global activation of NLRP1-driven immunologic pathways. We report a novel familial association of MS and MM, and propose a possible underlying genetic basis in NLRP1 gene. Furthermore, we provide initial evidence of the broader implications of NLRP1-related pathway dysfunction in MS.

Abstract Trans-endothelial migration (TEM) is essential for leukocyte circulation. While much is known about trans-blood endothelial migration, far less is known about trans-lymphatic endothelial migration. We established an in vitro system to evaluate lymphatic TEM for various cell types across primary mouse and human lymphatic endothelial cells (LEC), and validated the model for the murine LEC cell line SVEC4-10. T cells exhibited enhanced unidirectional migration from the basal (abluminal) to the apical (luminal) surface across LEC, whereas for blood endothelial cells (BEC) they migrated similarly in both directions. This preferential, vectorial migration was chemotactic toward many different chemoattractants and dose-dependent. Stromal protein fibers, interstitial type fluid flow, distribution of chemokines in the stromal layer, and inflammatory cytokines influenced LEC phenotype and leukocyte TEM. Activated and memory CD4 T cells, macrophages, and dendritic cell (DC) showed chemoattractantΔdriven vectorial migration, while CD8 T cell migration across LEC was not. The system was further validated for studying cancer cell transmigration across lymphatic endothelium. This model for lymphatic TEM for various migrating and endothelial cell types possesses the capacity to be high-throughput, highly reproducible and integrate the complexities of lymphatic biology, stromal variability, chemoattractant distribution, and fluid flow.