Low temperature exposure influences nitrogen metabolism resulting in decreased Cry1Ac insecticidal endotoxin content in cotton seeds.

BACKGROUND: Sudden temperature drops, resulting from extreme weather events, often occur during the boll-setting period of cotton in Xinjiang, China, causing decreased expression of Bacillus thuringiensis (Bt) insecticidal proteins in cotton bolls. The precise threshold temperatures and durations that lead to significant changes in Cry1Ac endotoxin levels under low temperatures remain unclear. To address this, we investigated the effects of different temperatures and stress durations on Cry1Ac endotoxin levels in cotton bolls. In 2020-2021, two Bt transgenic cotton varieties, conventional Sikang1 and hybrid Sikang3, were selected as experimental materials. Various low temperatures (ranging from 16 to 20 °C) with different durations (12 h, 24 h and 48 h) were applied during the peak boll-setting period. RESULTS: As the temperature decreased, the Cry1Ac endotoxin content in the boll shell, fiber, and seed exhibited a declining trend. Moreover, the threshold temperature which caused a significant reduction in Cry1Ac endotoxin content increased with the prolonged duration of low-temperature stress. Among the components of cotton bolls, seeds were most affected by low-temperature stress, with the threshold temperature for a significant reduction in Cry1Ac endotoxin content ranging from 17 °C to 19 °C. Correlation analysis indicated that low temperatures led to a decrease in protein synthesis capacity and an increase in degradation ability, resulting in reduced Cry1Ac endotoxin content. Pathway analysis revealed that both free amino acid and peptidase had significant negative effects on Cry1Ac endotoxin content. CONCLUSION: In summary, when the daily average temperature was ≤ 19 °C, implementing cultural practices to reduce free amino acid content and peptidase activity could serve as effective cold defense strategies for Bt cotton production.

Type 17 mucosal-associated invariant T cells contribute to neutrophilic inflammation in patients with nasal polyps.

BACKGROUND: Immune regulation in chronic rhinosinusitis with nasal polyps (CRSwNP) with a neutrophilic endotype remains unclear. Mucosal-associated invariant T (MAIT) cells are tissue-resident innate T lymphocytes that respond quickly to pathogens and promote chronic mucosal inflammation. OBJECTIVE: We aimed to investigate the roles of MAIT cells in neutrophilic CRSwNP. METHODS: Nasal tissues were obtained from 113 patients with CRSwNP and 29 control subjects. Peripheral and tissue MAIT cells and their subsets were analyzed by flow cytometry. Polyp-derived MAIT cells were analyzed by RNA sequencing to study their effects on neutrophils. RESULTS: Endotypes of CRSwNP were classified as paucigranulocytic (n = 21), eosinophilic (n = 29), neutrophilic (n = 39), and mixed granulocytic (n = 24). Frequencies of MAIT cells were significantly higher in neutrophilic (3.62%) and mixed granulocytic (3.60%) polyps than in control mucosa (1.78%). MAIT cell percentages positively correlated with local neutrophil counts. MAIT cells were more enriched in tissues than in matched PBMCs. The frequencies of MAIT1 subset or IFN-γ+ MAIT cells were comparable among control tissues and CRSwNP subtypes. The proportions of MAIT17 subset or IL-17A+ MAIT cells were significantly increased in neutrophilic or mixed granulocytic polyps compared with controls. RNA sequencing revealed type 17 and pro-neutrophil profiles in neutrophilic polyp-derived MAIT cells. In patients with neutrophilic CRSwNP, the proportions of MAIT and MAIT17 cells were positively correlated with local proinflammatory cytokines and symptom severity. In vitro experiments demonstrated that neutrophilic polyp-derived MAIT cells promoted neutrophil migration, survival, and activation. CONCLUSIONS: MAIT cells from neutrophilic CRSwNP demonstrate type 17 functional properties and promote neutrophil infiltration in nasal mucosa.

Mesenchymal stromal cells-derived small extracellular vesicles modulate DC function to suppress Th2 responses via IL-10 in patients with allergic rhinitis.

Mesenchymal stromal cells (MSCs) are well known for their immunoregulatory roles on allergic inflammation particularly by acting on T cells, B cells, and dendritic cells (DCs). MSC-derived small extracellular vesicles (MSC-sEV) are increasingly considered as one of the main factors for the effects of MSCs on immune responses. However, the effects of MSC-sEV on DCs in allergic diseases remain unclear. MSC-sEV were prepared from the induced pluripotent stem cells (iPSC)-MSCs by anion-exchange chromatography, and were characterized with the size, morphology, and specific markers. Human monocyte-derived DCs were generated and cultured in the presence of MSC-sEV to differentiate the so-called sEV-immature DCs (sEV-iDCs) and sEV-mature DCs (sEV-mDCs), respectively. The phenotypes and the phagocytic ability of sEV-iDCs were analyzed by flow cytometry. sEV-mDCs were co-cultured with isolated CD4+ T cells or peripheral blood mononuclear cells (PBMCs) from patients with allergic rhinitis. The levels of Th1 and Th2 cytokines produced by T cells were examined by ELISA and intracellular flow staining. And the following mechanisms were further investigated. We demonstrated that MSC-sEV inhibited the differentiation of human monocytes to iDCs with downregulation of the expression of CD40, CD80, CD86, and HLA-DR, but had no effects on mDCs with these markers. However, MSC-sEV treatment enhanced the phagocytic ability of mDCs. More importantly, using anti-IL-10 monoclonal antibody or IL-10Rα blocking antibody, we identified that sEV-mDCs suppressed the Th2 immune response by reducing the production of IL-4, IL-9, and IL-13 via IL-10. Furthermore, sEV-mDCs increased the level of Treg cells. Our study identified that mDCs treated with MSC-sEV inhibited the Th2 responses, providing novel evidence of the potential cell-free therapy acting on DCs in allergic airway diseases.

Prediction of coronary heart disease based on combined reinforcement multitask progressive time-series networks.

Coronary heart disease is the first killer of human health. At present, the most widely used approach of coronary heart disease diagnosis is coronary angiography, a surgery that could potentially cause some physical damage to the patients, together with some complications and adverse reactions. Furthermore, coronary angiography is expensive thus cannot be widely used in under development country. On the other hand, the heart color Doppler echocardiography report, blood biochemical indicators and personal information, such as gender, age and diabetes, can reflect the degree of heart damage in patients to some extent. This paper proposes a combined reinforcement multitask progressive time-series networks (CRMPTN) model to predict the grade of coronary heart disease through heart color Doppler echocardiography report, blood biochemical indicators and ten basic body information items about the patients. In this model, the first step is to perform deep reinforcement learning (DRL) pre-training through asynchronous advantage actor-critic (A3C). Training data is adopted to optimize the recurrent neural network (RNN) that parameterizes the stochastic policy. In the second step, soft parameter sharing module, hard parameter sharing module and progressive time-series networks are used to predict the status of coronary heart disease. The experimental results show that after DRL pre-training, the multiple tasks in the model interact with each other and learn together to achieve satisfactory results and outperform other state-of-the-art methods.

A method for extracting tumor events from clinical CT examination reports.

Accurate and efficient extraction of key information related to diseases from medical examination reports, such as X-ray and ultrasound images, CT scans, and others, is crucial for accurate diagnosis and treatment. These reports provide a detailed record of a patient's health condition and are an important part of the clinical examination process. By organizing this information in a structured way, doctors can more easily review and analyze the data, leading to better patient care. In this paper, we introduce a new technique for extracting useful information from unstructured clinical text examination reports, which we refer to as a medical event extraction (EE) task. Our approach is based on Machine Reading Comprehension (MRC) and involves two sub-tasks: Question Answerability Judgment (QAJ) and Span Selection (SS). We use BERT to build a question answerability discriminator (Judger) that determines whether a reading comprehension question can be answered or not, thereby avoiding the extraction of arguments from unanswerable questions. The SS sub-task first obtains the encoding of each word in the medical text from the final layer of BERT's Transformer, then utilizes the attention mechanism to identify important information related to the answer from these word encodings. This information is then input into a bidirectional LSTM (BiLSTM) module to obtain a global representation of the text, which is used, along with the softmax function, to predict the span of the answer (i.e., the start and end positions of the answer in the text report). We use interpretable methods to calculate the Jensen-Shannon Divergence (JSD) score between various layers of the network and confirm that our model has strong word representation capabilities, enabling it to effectively extract contextual information from medical reports. Our experiments demonstrate that our method outperforms existing medical event extraction methods, achieving state-of-the-art results with a notable F1 score.

Apparent Diffusion Coefficient in the Differentiation of Common Pediatric Brain Tumors in the Posterior Fossa: Different Region-of-Interest Selection Methods for Time Efficiency, Measurement Reproducibility, and Diagnostic Utility.

OBJECTIVES: This study aimed to explore the diagnostic ability of apparent diffusion coefficient (ADC) values obtained from different region of interest (ROI) measurements in tumor parenchyma for differentiating posterior fossa tumors (PFTs) and the correlations between ADC values and Ki-67. METHODS: Seventy-three pediatric patients with PFTs who underwent conventional diffusion-weighted imaging were recruited in this study. Five different ROIs were manually drawn by 2 radiologists (ROI-polygon, ROI-3 sections, ROI-3-5 ovals, ROI-more ovals, and ROI-whole). The interreader/intrareader repeatability, time required, diagnostic ability, and Ki-67 correlation analysis of the ADC values based on these ROI strategies were calculated. RESULTS: Both interreader and intrareader reliabilities were excellent for ADC values among the different ROI strategies (intraclass correlation coefficient, 0.899-0.992). There were statistically significant differences in time consumption among the 5 ROI selection methods ( P < 0.001). The time required for the ROI-3-5 ovals was the shortest (32.23 ± 5.14 seconds), whereas the time required for the ROI-whole was the longest (204.52 ± 92.34 seconds). The diagnostic efficiency of the ADC values showed no significant differences among the different ROI measurements ( P > 0.05). The ADC value was negatively correlated with Ki-67 ( r = -0.745 to -0.798, all P < 0.0001). CONCLUSIONS: The ROI-3-5 ovals method has the best interobserver repeatability, the shortest amount of time spent, and the best diagnostic ability. Thus, it is considered an effective measurement to produce ADC values in the evaluation of pediatric PFTs.

Sensitive dynamics of brain cognitive networks and its resource constraints.

It is well known that brain functions are closely related to the synchronization of brain networks, but the underlying mechanisms are still not completely understood. To study this problem, we here focus on the synchronization of cognitive networks, in contrast to that of a global brain network, as individual brain functions are in fact performed by different cognitive networks but not the global network. In detail, we consider four different levels of brain networks and two approaches, i.e., either with or without resource constraints. For the case of without resource constraints, we find that global brain networks have fundamentally different behaviors from that of the cognitive networks; i.e., the former has a continuous synchronization transition, while the latter shows a novel transition of oscillatory synchronization. This feature of oscillation comes from the sparse links among the communities of cognitive networks, resulting in coupling sensitive dynamics of brain cognitive networks. While for the case of resource constraints, we find that at the global level, the synchronization transition becomes explosive, in contrast to the continuous synchronization for the case of without resource constraints. At the level of cognitive networks, the transition also becomes explosive and the coupling sensitivity is significantly reduced, thus guaranteeing the robustness and fast switch of brain functions. Moreover, a brief theoretical analysis is provided.

Mesenchymal stem cells regulate type 2 innate lymphoid cells via regulatory T cells through ICOS-ICOSL interaction.

Group 2 innate lymphoid cells (ILC2s) are recognized as key controllers and effectors of type 2 inflammation. Mesenchymal stem cells (MSCs) have been shown to alleviate type 2 inflammation by modulating T lymphocyte subsets and decreasing TH 2 cytokine levels. However, the effects of MSCs on ILC2s have not been investigated. In this study, we investigated the potential immunomodulatory effects of MSCs on ILC2s in peripheral blood mononuclear cells (PBMCs) from allergic rhinitis patients and healthy subjects. We further investigated the mechanisms involved in the MSC modulation using isolated lineage negative (Lin- ) cells. PBMCs and Lin- cells were cocultured with induced pluripotent stem cell-derived MSCs (iPSC-MSCs) under the stimulation of epithelial cytokines IL-25 and IL-33. And the ILC2 levels and functions were examined and the possible mechanisms were investigated based on regulatory T (Treg) cells and ICOS-ICOSL pathway. iPSC-MSCs successfully decreased the high levels of IL-13, IL-9, and IL-5 in PBMCs in response to IL-25, IL-33, and the high percentages of IL-13+ ILC2s and IL-9+ ILC2s in response to epithelial cytokines were significantly reversed after the treatment of iPSC-MSCs. However, iPSC-MSCs were found directly to enhance ILC2 levels and functions via ICOS-ICOSL interaction in Lin- cells and pure ILC2s. iPSC-MSCs exerted their inhibitory effects on ILC2s via activating Treg cells through ICOS-ICOSL interaction. The MSC-induced Treg cells then suppressed ILC2s by secreting IL-10 in the coculture system. This study revealed that human MSCs suppressed ILC2s via Treg cells through ICOS-ICOSL interaction, which provides further insight to regulate ILC2s in inflammatory disorders.

Estimation of Mycophenolic Acid Exposure in Chinese Renal Transplant Patients by a Joint Deep Learning Model.

BACKGROUND: To predict mycophenolic acid (MPA) exposure in renal transplant recipients using a deep learning model based on a convolutional neural network with bilateral long short-term memory and attention methods. METHODS: A total of 172 Chinese renal transplant patients were enrolled in this study. The patients were divided into a training group (n = 138, Ruijin Hospital) and a validation group (n = 34, Zhongshan Hospital). Fourteen days after renal transplantation, rich blood samples were collected 0-12 hours after MPA administration. The plasma concentration of total MPA was measured using an enzyme-multiplied immunoassay technique. A limited sampling strategy based on a convolutional neural network-long short-term memory with attention (CALS) model for the prediction of the area under the concentration curve (AUC) of MPA was established. The established model was verified using the data from the validation group. The model performance was compared with that obtained from multiple linear regression (MLR) and maximum a posteriori (MAP) methods. RESULTS: The MPA AUC 0-12 of the training and validation groups was 54.28 ± 18.42 and 41.25 ± 14.53 µg·ml -1 ·h, respectively. MPA plasma concentration after 2 (C 2 ), 6 (C 6 ), and 8 (C 8 ) hours of administration was the most significant factor for MPA AUC 0-12 . The predictive performance of AUC 0-12 estimated using the CALS model of the validation group was better than the MLR and MAP methods in previous studies (r 2 = 0.71, mean prediction error = 4.79, and mean absolute prediction error = 14.60). CONCLUSIONS: The CALS model established in this study was reliable for predicting MPA AUC 0-12 in Chinese renal transplant patients administered mycophenolate mofetil and enteric-coated mycophenolic acid sodium and may have good generalization ability for application in other data sets.

Phase frustration induced remote synchronization.

Remote synchronization (RS) may take an important role in brain functioning and its study has attracted much attention in recent years. So far, most studies of RS are focused on the Stuart-Landau oscillators with mean-field coupling. However, realistic cases may have more complicated couplings and behaviors, such as the brain networks. To make the study of RS a substantial progress toward realistic situations, we here present a model of RS with phase frustration and show that RS can be induced for those systems where no RS exists when there is no phase frustration. By numerical simulations on both the Stuart-Landau and Kuramoto oscillators, we find that the optimal range of RS depends on the match of phase frustrations between the hub and leaf nodes and a fixed relationship of this match is figured out. While for the non-optimal range of RS, we find that RS exists only in a linear band between the phase frustrations of the hub and leaf nodes. A brief theoretical analysis is provided to explain these results.

Percutaneous endovenous intervention without vena cava filter for acute proximal deep vein thrombosis secondary to iliac vein compression syndrome: preliminary outcomes.

The aim is to report the preliminary outcomes of percutaneous endovenous intervention (PEVI) for acute proximal deep vein thrombosis (DVT) secondary to iliac vein compression syndrome (IVCS) without inferior vena cava filter (IVCF) placement. Acute DVT patients who underwent PEVI without IVCF were analyzed retrospectively. PEVI consisted of catheter-directed thrombolysis, manual aspiration thrombectomy, balloon angioplasty and stenting. CT was used to evaluate the left common iliac vein (LCIV). Sixty-two consecutive patients (17 men and 45 women, mean age, 59.4 ± 15.2 years) were enrolled. The compression percentage of the LCIV ranged from 51.7% to 95.2% (median 83.2%). Iliac DVT was present in 7 patients; iliofemoral, in 30 patients; and iliofemoropopliteal, in 25 patients. Complete technical success and clinical improvement were obtained in all subjects without the occurrence of symptomatic pulmonary embolism (PE). Five patients experienced recurrent thrombosis. The primary patency rates at 12 and 24 months were 93.8% and 91.4%, respectively, which remained stable at 36, 48 and 60 months. The secondary patency rates at 12 and 24 months were 95.7% and 93.3%, respectively, and there was no change at 60 months. Although limited, our preliminary results suggested that PEVI without IVCF placement seemed to be safe and effective for acute proximal DVT secondary to IVCS without inferior vena cava thrombosis or symptomatic PE.

Epigenetic Modification of Enhancer of Zeste Homolog 2 Modulates the Activation of Dendritic Cells in Allergen Immunotherapy.

BACKGROUND: Allergen immunotherapy (AIT) is the only etiological and potentially curative therapy for allergic rhinitis (AR). OBJECTIVES: We sought to investigate the role of epigenetic regulator enhancer of zeste homolog 2 (EZH2) in the activation of dendritic cells (DCs) in AIT. METHOD: In this study, EZH2 expression in circulating myeloid DCs (mDCs) and plasmacytoid DCs (pDCs) were evaluated using flow cytometry. Clinical information from 56 AR patients receiving AIT was collected, including 30 subjects with subcutaneous immunotherapy (SCIT) and 26 subjects with sublingual immunotherapy (SLIT). In vitro, the effect of EZH2 inhibitor, 3 Deazaneplanocin A (DZNep), on the phenotypic and functional activation of monocyte-derived DCs (moDCs) was evaluated. RESULTS: EZH2 expression in circulating mDCs and pDCs were both negatively correlated to treatment time of AIT (r = -0.39, p = 0.003 and r = -0.47, p = 0.0002, respectively). Furthermore, there was a higher correlation between EZH2 expression and AIT treatment time in the SCIT group compared to that of the SLIT group in mDCs (r = -0.42, p = 0.02 vs. r = -0.23, p = 0.26)and pDCs (r = -0.52, p = 0.003 vs. r = -0.33, p = 0.10). In vitro, the co-stimulatory molecules on moDCs, such as CD80, CD86, and CD83, were significantly inhibited by DZNep in a dose-dependent manner. The -DC-driven T-cell proliferation was suppressed by DZNep (MD = 22.88, 95% CI 7.809-37.96, p < 0.05). CONCLUSIONS: Our study shows that EZH2, which is required in the activation of DCs, mediates the epigenetic modification in AIT and stresses the importance of patient adherence during AIT.

A Hydrodynamic Model for Measuring Fluid Density and Viscosity by Using Quartz Tuning Forks.

A hydrodynamic model of using quartz tuning forks (QTFs) for density and viscosity sensing, by measuring the resonance frequency and quality factor, has been established based on the cantilever beam theory applied to the atomic force microscope (AFM). Two examples are presented to verify the usability of this model. Then, the Sobol index method is chosen for explaining quantitatively how the resonance frequency and quality factor of the QTFs are affected by the fluid density and viscosity, respectively. The results show that the relative mean square error in viscosity of the eight solutions evaluated by the hydrodynamic model is reduced by an order of magnitude comparing with Butterworth-Van Dyke equivalent circuit method. When the measured resonance frequency and quality factor of the QTFs vary from 25,800-26,100 Hz and 28-41, the sensitivities of the quality factor affected by the fluid density increase. This model provides an idea for improving the accuracy of fluid component recognition in real time, and lays a foundation for the application of miniaturized and cost-effective downhole fluid density and viscosity sensors.

Increased innate type 2 immune response in house dust mite-allergic patients with allergic rhinitis.

Group 2 innate lymphoid cells (ILC2s) are essential in initiating and driving allergic immune responses. However, there were inconsistent findings of the ILC2 levels in allergic rhinitis (AR) patients. This study investigated the ILC2 levels in the peripheral blood of house dust mite (HDM)-sensitized AR patients and their ability to secrete type 2 cytokines. The levels of ILC2s with phenotypic ILC2 characteristics were increased in the HDM-AR patients. The AR patients' symptom score and IL-13 levels were positively associated with the ILC2s in HDM-AR patients. The epithelial cytokine stimulation induced dramatic production of IL-5 and IL-13 in PBMCs of AR patients. We successfully sorted ILC2s from AR patients and identified their ability of type 2 cytokines production. The number of ILC2s increased in the HDM-AR patients and ILC2s produced the amount of TH2 cytokines in the presence of epithelial cytokines, which suggested the important role of ILC2 in AR patients.

Telomerase-mediated telomere elongation from human blastocysts to embryonic stem cells.

High telomerase activity is a characteristic of human embryonic stem cells (hESCs), however, the regulation and maintenance of correct telomere length in hESCs is unclear. In this study we investigated telomere elongation in hESCs in vitro and found that telomeres lengthened from their derivation in blastocysts through early expansion, but stabilized at later passages. We report that the core unit of telomerase, hTERT, was highly expressed in hESCs in blastocysts and throughout long-term culture; furthermore, this was regulated in a Wnt-ß-catenin-signaling-dependent manner. Our observations that the alternative lengthening of telomeres (ALT) pathway was suppressed in hESCs and that hTERT knockdown partially inhibited telomere elongation, demonstrated that high telomerase activity was required for telomere elongation. We observed that chromatin modification through trimethylation of H3K9 and H4K20 at telomeric regions decreased during early culture. This was concurrent with telomere elongation, suggesting that epigenetic regulation of telomeric chromatin may influence telomerase function. By measuring telomere length in 96 hESC lines, we were able to establish that telomere length remained relatively stable at 12.02 ± 1.01 kb during later passages (15-95). In contrast, telomere length varied in hESCs with genomic instability and hESC-derived teratomas. In summary, we propose that correct, stable telomere length may serve as a potential biomarker for genetically stable hESCs.

Immune responses to different patterns of exposure to ovalbumin in a mouse model of allergic rhinitis.

Allergic rhinitis (AR) has been a significant healthcare burden on individuals and society. However, the detailed effect of different patterns of allergen exposure on the development of AR remains controversial. A mouse model of AR was established to address the complex relationships between allergen exposure and the development of AR. Allergic symptom, OVA-specific IgE in serum and nasal lavage fluid, allergic inflammation in nasal tissues were evaluated after intranasal sensitization and challenge of ovalbumin (OVA) in mice treated with two different doses of allergen for different sensitized durations. Exposure to different doses and sensitized durations of OVA were capable of inducing allergic nasal response. Repetitive OVA exposure in the sensitization phase induced the recruitment of eosinophils and goblet cell hyperplasia. The level of OVA-specific IgE in serum depended on OVA exposure and was mediated in a duration-related manner. In addition, mice treated with low-dose OVA for prolonged duration manifested the major features of human local allergic rhinitis. There were dose- and duration-related effects of allergen exposure on the development of AR. LAR was associated with repetitive exposure to low-dose allergen. Thus, allergen avoidance should be an important aim of AR management.

Functional characterization of motif sequences under purifying selection.

Diverse life forms are driven by the evolution of gene regulatory programs including changes in regulator proteins and cis-regulatory elements. Alterations of cis-regulatory elements are likely to dominate the evolution of the gene regulatory networks, as they are subjected to smaller selective constraints compared with proteins and hence may evolve quickly to adapt the environment. Prior studies on cis-regulatory element evolution focus primarily on sequence substitutions of known transcription factor-binding motifs. However, evolutionary models for the dynamics of motif occurrence are relatively rare, and comprehensive characterization of the evolution of all possible motif sequences has not been pursued. In the present study, we propose an algorithm to estimate the strength of purifying selection of a motif sequence based on an evolutionary model capturing the birth and death of motif occurrences on promoters. We term this measure as the 'evolutionary retention coefficient', as it is related yet distinct from the canonical definition of selection coefficient in population genetics. Using this algorithm, we estimate and report the evolutionary retention coefficients of all possible 10-nucleotide sequences from the aligned promoter sequences of 27 748. orthologous gene families in 34 mammalian species. Intriguingly, the evolutionary retention coefficients of motifs are intimately associated with their functional relevance. Top-ranking motifs (sorted by evolutionary retention coefficients) are significantly enriched with transcription factor-binding sequences according to the curated knowledge from the TRANSFAC database and the ChIP-seq data generated from the ENCODE Consortium. Moreover, genes harbouring high-scoring motifs on their promoters retain significantly coherent expression profiles, and those genes are over-represented in the functional classes involved in gene regulation. The validation results reveal the dependencies between natural selection and functions of cis-regulatory elements and shed light on the evolution of gene regulatory networks.

Optical design of a street lamp based on dual-module chip-on-board LED arrays.

We design and propose a compact street lamp based on dual-module chip-on-board LED. The street lamp is composed of six faceted reflectors. It can direct the luminous flux and form uniform illumination on the target area, and it effectively reduces power consumption. We have conducted both simulations and prototype measurements. The test results show good optical performance in that the uniformity of luminance reaches 0.58 for LED lamp zigzag arrangements and 0.60 for LED lamp double-side arrangements. The average luminance can fulfill the requirements in Chinese road lighting Standard CJJ45-2006.

Generating lymphoma ultrasound image description with transformer model.

Lymphoma, the most prevalent hematologic tumor originating from the lymphatic hematopoietic system, can be accurately diagnosed using high-resolution ultrasound. Microscopic ultrasound performance enables clinicians to identify suspected tumors and subsequently obtain a definitive pathological diagnosis through puncture biopsy. However, the complex and diverse ultrasonographic manifestations of lymphoma pose challenges for accurate characterization by sonographers. To address these issues, this study proposes a Transformer-based model for generating descriptive ultrasound images of lymphoma, aiming to provide auxiliary guidance for ultrasound doctors during screening procedures. Specifically, deep stable learning is integrated into the model to eliminate feature dependencies by training sample weights. Additionally, a memory module is incorporated into the model decoder to enhance semantic information modeling in descriptions and utilize learned semantic tree branch structures for more detailed image depiction. Experimental results on an ultrasonic diagnosis dataset from Shanghai Ruijin Hospital demonstrate that our proposed model outperforms relevant methods in terms of prediction performance.

Multi-transcriptomics analysis of microvascular invasion-related malignant cells and development of a machine learning-based prognostic model in hepatocellular carcinoma.

Background: Microvascular invasion (MVI) stands as a pivotal pathological hallmark of hepatocellular carcinoma (HCC), closely linked to unfavorable prognosis, early recurrence, and metastatic progression. However, the precise mechanistic underpinnings governing its onset and advancement remain elusive. Methods: In this research, we downloaded bulk RNA-seq data from the TCGA and HCCDB repositories, single-cell RNA-seq data from the GEO database, and spatial transcriptomics data from the CNCB database. Leveraging the Scissor algorithm, we delineated prognosis-related cell subpopulations and discerned a distinct MVI-related malignant cell subtype. A comprehensive exploration of these malignant cell subpopulations was undertaken through pseudotime analysis and cell-cell communication scrutiny. Furthermore, we engineered a prognostic model grounded in MVI-related genes, employing 101 algorithm combinations integrated by 10 machine-learning algorithms on the TCGA training set. Rigorous evaluation ensued on internal testing sets and external validation sets, employing C-index, calibration curves, and decision curve analysis (DCA). Results: Pseudotime analysis indicated that malignant cells, showing a positive correlation with MVI, were primarily concentrated in the early to middle stages of differentiation, correlating with an unfavorable prognosis. Importantly, these cells showed significant enrichment in the MYC pathway and were involved in extensive interactions with diverse cell types via the MIF signaling pathway. The association of malignant cells with the MVI phenotype was corroborated through validation in spatial transcriptomics data. The prognostic model we devised demonstrated exceptional sensitivity and specificity, surpassing the performance of most previously published models. Calibration curves and DCA underscored the clinical utility of this model. Conclusions: Through integrated multi-transcriptomics analysis, we delineated MVI-related malignant cells and elucidated their biological functions. This study provided novel insights for managing HCC, with the constructed prognostic model offering valuable support for clinical decision-making.