Palmitoylation prevents sustained inflammation by limiting NLRP3 inflammasome activation through chaperone-mediated autophagy.

As a key component of the inflammasome, NLRP3 is a critical intracellular danger sensor emerging as an important clinical target in inflammatory diseases. However, little is known about the mechanisms that determine the kinetics of NLRP3 inflammasome stability and activity to ensure effective and controllable inflammatory responses. Here, we show that S-palmitoylation acts as a brake to turn NLRP3 inflammasome off. zDHHC12 is identified as the S-acyltransferase for NLRP3 palmitoylation, which promotes its degradation through the chaperone-mediated autophagy pathway. Zdhhc12 deficiency in mice enhances inflammatory symptoms and lethality following alum-induced peritonitis and LPS-induced endotoxic shock. Notably, several disease-associated mutations in NLRP3 are associated with defective palmitoylation, resulting in overt NLRP3 inflammasome activation. Thus, our findings identify zDHHC12 as a repressor of NLRP3 inflammasome activation and uncover a previously unknown regulatory mechanism by which the inflammasome pathway is tightly controlled by the dynamic palmitoylation of NLRP3.

Semantic encoding during language comprehension at single-cell resolution.

From sequences of speech sounds1,2 or letters3, humans can extract rich and nuanced meaning through language. This capacity is essential for human communication. Yet, despite a growing understanding of the brain areas that support linguistic and semantic processing4-12, the derivation of linguistic meaning in neural tissue at the cellular level and over the timescale of action potentials remains largely unknown. Here we recorded from single cells in the left language-dominant prefrontal cortex as participants listened to semantically diverse sentences and naturalistic stories. By tracking their activities during natural speech processing, we discover a fine-scale cortical representation of semantic information by individual neurons. These neurons responded selectively to specific word meanings and reliably distinguished words from nonwords. Moreover, rather than responding to the words as fixed memory representations, their activities were highly dynamic, reflecting the words' meanings based on their specific sentence contexts and independent of their phonetic form. Collectively, we show how these cell ensembles accurately predicted the broad semantic categories of the words as they were heard in real time during speech and how they tracked the sentences in which they appeared. We also show how they encoded the hierarchical structure of these meaning representations and how these representations mapped onto the cell population. Together, these findings reveal a finely detailed cortical organization of semantic representations at the neuron scale in humans and begin to illuminate the cellular-level processing of meaning during language comprehension.

Single-neuronal elements of speech production in humans.

Humans are capable of generating extraordinarily diverse articulatory movement combinations to produce meaningful speech. This ability to orchestrate specific phonetic sequences, and their syllabification and inflection over subsecond timescales allows us to produce thousands of word sounds and is a core component of language1,2. The fundamental cellular units and constructs by which we plan and produce words during speech, however, remain largely unknown. Here, using acute ultrahigh-density Neuropixels recordings capable of sampling across the cortical column in humans, we discover neurons in the language-dominant prefrontal cortex that encoded detailed information about the phonetic arrangement and composition of planned words during the production of natural speech. These neurons represented the specific order and structure of articulatory events before utterance and reflected the segmentation of phonetic sequences into distinct syllables. They also accurately predicted the phonetic, syllabic and morphological components of upcoming words and showed a temporally ordered dynamic. Collectively, we show how these mixtures of cells are broadly organized along the cortical column and how their activity patterns transition from articulation planning to production. We also demonstrate how these cells reliably track the detailed composition of consonant and vowel sounds during perception and how they distinguish processes specifically related to speaking from those related to listening. Together, these findings reveal a remarkably structured organization and encoding cascade of phonetic representations by prefrontal neurons in humans and demonstrate a cellular process that can support the production of speech.

YAP-VGLL4 antagonism defines the major physiological function of the Hippo signaling effector YAP.

The Hippo-YAP signaling pathway plays a critical role in development, homeostasis, regeneration, and tumorigenesis by converging on YAP, a coactivator for the TEAD family DNA-binding transcription factors, to regulate downstream transcription programs. Given its pivotal role as the nuclear effector of the Hippo pathway, YAP is indispensable in multiple developmental and tissue contexts. Here we report that the essentiality of YAP in liver and lung development can be genetically bypassed by simultaneous inactivation of the TEAD corepressor VGLL4. This striking antagonistic epistasis suggests that the major physiological function of YAP is to antagonize VGLL4. We further show that the YAP-VGLL4 antagonism plays a widespread role in regulating Hippo pathway output beyond normal development, as inactivation of Vgll4 dramatically enhanced intrahepatic cholangiocarcinoma formation in Nf2-deficient livers and ameliorated CCl4-induced damage in normal livers. Interestingly, Vgll4 expression is temporally regulated in development and regeneration and, in certain contexts, provides a better indication of overall Hippo pathway output than YAP phosphorylation. Together, these findings highlight the central importance of VGLL4-mediated transcriptional repression in Hippo pathway regulation and inform potential strategies to modulate Hippo signaling in cancer and regenerative medicine.

WWTR1(TAZ)-CAMTA1 reprograms endothelial cells to drive epithelioid hemangioendothelioma.

Epithelioid hemangioendothelioma (EHE) is a poorly understood and devastating vascular cancer. Sequencing of EHE has revealed a unique gene fusion between the Hippo pathway nuclear effector TAZ (WWTR1) and the brain-enriched transcription factor CAMTA1 in ∼90% of cases. However, it remains unclear whether the TAZ-CAMTA1 gene fusion is a driver of EHE, and potential targeted therapies are unknown. Here, we show that TAZ-CAMTA1 expression in endothelial cells is sufficient to drive the formation of vascular tumors with the distinctive features of EHE, and inhibition of TAZ-CAMTA1 results in the regression of these vascular tumors. We further show that activated TAZ resembles TAZ-CAMTA1 in driving the formation of EHE-like vascular tumors, suggesting that constitutive activation of TAZ underlies the pathological features of EHE. We show that TAZ-CAMTA1 initiates an angiogenic and regenerative-like transcriptional program in endothelial cells, and disruption of the TAZ-CAMTA1-TEAD interaction or ectopic expression of a dominant negative TEAD in vivo inhibits TAZ-CAMTA1-mediated transformation. Our study provides the first genetic model of a TAZ fusion oncoprotein driving its associated human cancer, pinpointing TAZ-CAMTA1 as the key driver and a valid therapeutic target of EHE.

Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals.

The ongoing outbreak of coronavirus disease 2019 (COVID-19) has spread rapidly on a global scale. Although it is clear that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted through human respiratory droplets and direct contact, the potential for aerosol transmission is poorly understood1-3. Here we investigated the aerodynamic nature of SARS-CoV-2 by measuring viral RNA in aerosols in different areas of two Wuhan hospitals during the outbreak of COVID-19 in February and March 2020. The concentration of SARS-CoV-2 RNA in aerosols that was detected in isolation wards and ventilated patient rooms was very low, but it was higher in the toilet areas used by the patients. Levels of airborne SARS-CoV-2 RNA in the most public areas was undetectable, except in two areas that were prone to crowding; this increase was possibly due to individuals infected with SARS-CoV-2 in the crowd. We found that some medical staff areas initially had high concentrations of viral RNA with aerosol size distributions that showed peaks in the submicrometre and/or supermicrometre regions; however, these levels were reduced to undetectable levels after implementation of rigorous sanitization procedures. Although we have not established the infectivity of the virus detected in these hospital areas, we propose that SARS-CoV-2 may have the potential to be transmitted through aerosols. Our results indicate that room ventilation, open space, sanitization of protective apparel, and proper use and disinfection of toilet areas can effectively limit the concentration of SARS-CoV-2 RNA in aerosols. Future work should explore the infectivity of aerosolized virus.

A RhoA-YAP-c-Myc signaling axis promotes the development of polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is an inherited disorder caused by mutations in PKD1 or PKD2 and affects one in 500-1000 humans. Limited treatment is currently available for ADPKD. Here we identify the Hippo signaling effector YAP and its transcriptional target, c-Myc, as promoters of cystic kidney pathogenesis. While transgenic overexpression of YAP promotes proliferation and tubule dilation in mouse kidneys, loss of YAP/TAZ or c-Myc suppresses cystogenesis in a mouse ADPKD model resulting from Pkd1 deficiency. Through a comprehensive kinase inhibitor screen based on a novel three-dimensional (3D) culture of Pkd1 mutant mouse kidney cells, we identified a signaling pathway involving the RhoGEF (guanine nucleotide exchange factor) LARG, the small GTPase RhoA, and the RhoA effector Rho-associated kinase (ROCK) as a critical signaling module between PKD1 and YAP. Further corroborating its physiological importance, inhibition of RhoA signaling suppresses cystogenesis in 3D culture of Pkd1 mutant kidney cells as well as Pkd1 mutant mouse kidneys in vivo. Taken together, our findings implicate the RhoA-YAP-c-Myc signaling axis as a critical mediator and potential drug target in ADPKD.

Glutamine metabolism prognostic index predicts tumour microenvironment characteristics and therapeutic efficacy in ovarian cancer.

Mounting evidence has highlighted the multifunctional characteristics of glutamine metabolism (GM) in cancer initiation, progression and therapeutic regimens. However, the overall role of GM in the tumour microenvironment (TME), clinical stratification and therapeutic efficacy in patients with ovarian cancer (OC) has not been fully elucidated. Here, three distinct GM clusters were identified and exhibited different prognostic values, biological functions and immune infiltration in TME. Subsequently, glutamine metabolism prognostic index (GMPI) was constructed as a new scoring model to quantify the GM subtypes and was verified as an independent predictor of OC. Patients with low-GMPI exhibited favourable survival outcomes, lower enrichment of several oncogenic pathways, less immunosuppressive cell infiltration and better immunotherapy responses. Single-cell sequencing analysis revealed a unique evolutionary trajectory of OC cells from high-GMPI to low-GMPI, and OC cells with different GMPI might communicate with distinct cell populations through ligand-receptor interactions. Critically, the therapeutic efficacy of several drug candidates was validated based on patient-derived organoids (PDOs). The proposed GMPI could serve as a reliable signature for predicting patient prognosis and contribute to optimising therapeutic strategies for OC.

Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity.

BACKGROUND: Early prediction of pathological complete response (pCR) is important for deciding appropriate treatment strategies for patients. In this study, we aimed to quantify the dynamic characteristics of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) and investigate its value to improve pCR prediction as well as its association with tumor heterogeneity in breast cancer patients. METHODS: The DCE-MRI, clinicopathologic record, and full transcriptomic data of 785 breast cancer patients receiving neoadjuvant chemotherapy were retrospectively included from a public dataset. Dynamic features of DCE-MRI were computed from extracted phase-varying radiomic feature series using 22 CAnonical Time-sereis CHaracteristics. Dynamic model and radiomic model were developed by logistic regression using dynamic features and traditional radiomic features respectively. Various combined models with clinical factors were also developed to find the optimal combination and the significance of each components was evaluated. All the models were evaluated in independent test set in terms of area under receiver operating characteristic curve (AUC). To explore the potential underlying biological mechanisms, radiogenomic analysis was implemented on patient subgroups stratified by dynamic model to identify differentially expressed genes (DEGs) and enriched pathways. RESULTS: A 10-feature dynamic model and a 4-feature radiomic model were developed (AUC = 0.688, 95%CI: 0.635-0.741 and AUC = 0.650, 95%CI: 0.595-0.705) and tested (AUC = 0.686, 95%CI: 0.594-0.778 and AUC = 0.626, 95%CI: 0.529-0.722), with the dynamic model showing slightly higher AUC (train p = 0.181, test p = 0.222). The combined model of clinical, radiomic, and dynamic achieved the highest AUC in pCR prediction (train: 0.769, 95%CI: 0.722-0.816 and test: 0.762, 95%CI: 0.679-0.845). Compared with clinical-radiomic combined model (train AUC = 0.716, 95%CI: 0.665-0.767 and test AUC = 0.695, 95%CI: 0.656-0.714), adding the dynamic component brought significant improvement in model performance (train p < 0.001 and test p = 0.005). Radiogenomic analysis identified 297 DEGs, including CXCL9, CCL18, and HLA-DPB1 which are known to be associated with breast cancer prognosis or angiogenesis. Gene set enrichment analysis further revealed enrichment of gene ontology terms and pathways related to immune system. CONCLUSION: Dynamic characteristics of DCE-MRI were quantified and used to develop dynamic model for improving pCR prediction in breast cancer patients. The dynamic model was associated with tumor heterogeniety in prognostic-related gene expression and immune-related pathways.

An Integrated Inertial-Magnetophoresis Microfluidic Chip Online-Coupled with ICP-MS for Rapid Separation and Precise Detection of Circulating Tumor Cells.

Circulating tumor cells (CTCs) are recognized as promising targets for liquid biopsy, which play an important role in early diagnosis and efficacy monitoring of cancer. However, due to the extreme scarcity of CTCs and partial size overlap between CTCs and white blood cells (WBCs), the separation and detection of CTCs from blood remain a big challenge. To address this issue, we fabricated a microfluidic chip by integrating a passive contraction-expansion array (CEA) inertial sorting zone and an active magnetophoresis zone with the trapezoidal groove and online coupled it with inductively coupled plasma mass spectrometry (ICP-MS) for rapid separation and precise detection of MCF-7 cells (as a model CTC) in blood samples. In the integrated microfluidic chip, most of the small-sized WBCs can be rapidly removed in the circular CEA inertial sorter, while the rest of the magnetically labeled WBCs can be further captured in the trapezoidal groove under the magnetic field. As a result, the rapid separation of MCF-7 cells from blood samples was achieved with an average recovery of 91.6% at a sample flow rate of 200 µL min-1. The developed online integrated inertial-magnetophoresis microfluidic chip-ICP-MS system has been applied for the detection of CTCs in real clinical blood samples with a fast analysis speed (5 min per 1 mL blood). CTCs were detected in all 24 blood samples from patients with different types of cancer, exhibiting excellent application potential in clinical diagnosis.

S-palmitoylation regulates innate immune signaling pathways: molecular mechanisms and targeted therapies.

S-palmitoylation is a reversible posttranslational lipid modification that targets cysteine residues of proteins and plays critical roles in regulating the biological processes of substrate proteins. The innate immune system serves as the first line of defense against pathogenic invaders and participates in the maintenance of tissue homeostasis. Emerging studies have uncovered the functions of S-palmitoylation in modulating innate immune responses. In this review, we focus on the reversible palmitoylation of innate immune signaling proteins, with particular emphasis on its roles in the regulation of protein localization, protein stability, and protein-protein interactions. We also highlight the potential and challenge of developing therapies that target S-palmitoylation or de-palmitoylation for various diseases.

The complete plastomes of thirteen Libanotis (Apiaceae, Apioideae) plants: comparative and phylogenetic analyses provide insights into the plastome evolution and taxonomy of Libanotis.

BACKGROUND: The genus Libanotis Haller ex Zinn, nom. cons., a contentious member of Apiaceae, encompasses numerous economically and medicinally significant plants, comprising approximately 30 species distributed across Eurasia. Despite many previous taxonomic insights into it, phylogenetic studies of the genus are still lacking. And the establishment of a robust phylogenetic framework remains elusive, impeding advancements and revisions in the taxonomic system for this genus. Plastomes with greater variability in their genetic characteristics hold promise for building a more robust Libanotis phylogeny. RESULTS: During our research, we sequenced, assembled, and annotated complete plastomes for twelve Libanotis species belong to three sections and two closely related taxa. We conducted a comprehensive comparative analysis through totally thirteen Libanotis plastomes for the genus, including an additional plastome that had been published. Our results suggested that Libanotis plastome was highly conserved between different subclades, while the coding regions were more conserved than the non-coding regions, and the IR regions were more conserved than the single copy regions. Nevertheless, eight mutation hotspot regions were identified among plastomes, which can be considered as candidate DNA barcodes for accurate species identification in Libanotis. The phylogenetic analyses generated a robustly framework for Libanotis and revealed that Libanotis was not a monophyletic group and their all three sections were polygenetic. Libanotis schrenkiana was sister to L. sibirica, type species of this genus, but the remainders scattered within Selineae. CONCLUSION: The plastomes of Libanotis exhibited a high degree of conservation and was effective in enhancing the support and resolution of phylogenetic analyses within this genus. Based on evidence from both phylogeny and morphology, we propose the recognition of "Libanotis sensu stricto" and provide taxonomic recommendations for other taxa that previously belonged to Libanotis. In conclusion, our study not only revealed the phylogenetic position and plastid evolution of Libanotis, but also provided new insights into the phylogeny of the family Apiaceae and phylogenetic relationships within the tribe Selineae.

Solution-Processed 1D Wurtzite ZnS Nanostructures with Controlled Crystallographic Orientation and Tunable Band-Edge Emission.

1D compound semiconductor nanomaterials possess unique physicochemical properties that strongly depend on their size, composition, and structures. ZnS has been widely investigated as one of the most important semiconductors, and the control of crystallographic orientation of 1D ZnS nanostructures is still challenging and crucial to exploring their anisotropic properties. Herein, a solution-processed strategy is developed to synthesize 1D wurtzite (w-)ZnS nanostructures with the specific <002> and <210> orientations by co-decomposing the copper dibutyldithiocarbamate {[(C4 H9 )2 NCS2 ]2 Cu, i.e., R2 Cu} and zinc dibutyldithiocarbamate (R2 Zn) precursors in the mixed solvents of oleylamine and 1-dodecanethoil. A solution-solid-solid (SSS)-Oriented growth mechanism is proposed, which includes oriented nucleation dominated and SSS growth dominated stages. The crystallographic orientation mainly depends on the interfacial energy and ligand effect. The 1D w-ZnS nanostructures with controlled crystallographic orientation display unique morphologies, i.e., <002>-oriented w-ZnS nanorod enclosed with {110} facets while <210>-oriented w-ZnS nanobelt enclosed with wide (002) and narrow (110) facets. The bandgap of 1D w-ZnS nanostructures can be tuned from 3.94 to 3.82 eV with the crystallographic growth direction varied from <002> to <210>, thus leading to the tunable band-edge emission from ≈338 to ≈345 nm.

Klotho accelerates the progression of polycystic ovary syndrome through promoting granulosa cell apoptosis and inflammation†.

The morbidity of polycystic ovary syndrome (PCOS) is in highly increasing rate nowadays. PCOS not only affects the fertility in women, but also threatens the health of whole life. Hence, to find the prognostic risk factors is of great value. However, the effective predictors in clinical practice of PCOS are still in blackness. In this study, we found Klotho (KL) was increased in follicular fluid (FF) and primary luteinized granulosa cells (GCs) from PCOS patients with hyperandrogenism. Furthermore, we found follicular KL was negatively correlated with numbers of mature oocytes, and positively correlated with serum testosterone, LH, and LH/FSH levels menstrual cycle and number of total antral follicles in PCOS patients. In primary luteinized GCs, the increased KL was accompanied with upregulation of cell apoptosis and inflammation-related genes. In ovaries of PCOS mice and cultured human KGN cell line, KL was up-regulated and accompanied by apoptosis, inflammation, and mitochondrial dysfunction. Therefore, our findings suggest new mechanisms for granulosa cell injury and revealed to target inhibit KL maybe a new therapeutic strategy for treatment of PCOS.

ITGA7 loss drives the differentiation of adipose-derived mesenchymal stem cells to cancer-associated fibroblasts.

Cancer-associated fibroblasts (CAFs) represent a major cellular component of the tumor (pre-)metastatic niche and play an essential role in omental dissemination of ovarian cancer. The omentum is rich in adipose, and adipose-derived mesenchymal stem cells (ADSCs) have been identified as a source of CAFs. However, the molecular events driving the phenotype shift of ADSCs remain largely unexplored. In this research, we focus on integrins, transmembrane receptors that have been widely involved in cellular plasticity. We found that integrin α7 (ITGA7) was the only member of the integrin family that positively correlated with both overall survival and progression-free survival in ovarian cancer through GEPIA2. The immunohistochemistry signal of ITGA7 was apparent in the tumor stroma, and a lower omental ITGA7 level was associated with metastasis. Primary ADSCs were isolated from the omentum of patients with ovarian cancer and identified by cellular morphology, biomarkers, and multilineage differentiation. The conditional medium of ovarian cancer cells induced ITGA7 expression decrease and phenotypic changes in ADSCs. Downregulation of ITGA7 in primary omental ADSCs led to decrease in stemness properties and emerge of characteristic morphology and biomarkers of CAFs. Moreover, the conditioned medium of ADSCs with ITGA7 depletion exhibited enhanced abilities to improve the migration and invasion of ovarian cancer cells in vitro. Overall, these findings indicate that loss of ITGA7 may induce the differentiation of ADSCs to CAFs that contribute to a tumor-supportive niche.

The unique sweet potato NAC transcription factor IbNAC3 modulates combined salt and drought stresses.

Plants often simultaneously experience combined stresses rather than a single stress, causing more serious damage, but the underlying mechanisms remain unknown. Here, we identified the stress-induced IbNAC3 from sweet potato (Ipomoea batatas) as a nucleus-localized transcription activator. IbNAC3 contains a unique activation domain whose MKD sequence confers transactivation activities to multiple other TFs and is essential for the activated expression of downstream target genes. Ectopic expression of IbNAC3 conferred tolerance to single and combined salt and drought stresses in Arabidopsis (Arabidopsis thaliana), and a group of NAM, ATAF1/2, and CUC2 (NAC) TFs, including ANAC011, ANAC072, ANAC083, ANAC100, and NAP, interacted with IbNAC3, and the specific domains responsible for each interaction varied. Intriguingly, IbNAC3 repressed the interaction among the five NACs, and knockout or mutation of ANAC011 and ANAC072 dramatically impaired combined stress tolerance. IbNAC3-ANAC072 and IbNAC3-NAP modules synergistically activated the MICROTUBULE-RELATED E3 LIGASE57 (MREL57) gene. Consistently, mutation of MREL57 and overexpression of WAVE-DAM-PENED2-LIKE7, encoding a target protein of MREL57, both remarkably impaired combined stress tolerance. Moreover, transgenic plants displayed abscisic acid (ABA) hyposensitivity by directly promoting the transcription of ENHANCED RESPONSE TO ABA 1, a key negative regulator of ABA signaling. The data unravel the unique IbNAC3 TF functions as a pivotal component in combined stress tolerance by integrating multiple regulatory events and ubiquitin pathways, which is essential for developing high-tolerant plants in natural environments.

FIONA1-mediated mRNA m6 A methylation regulates the response of Arabidopsis to salt stress.

N6 -methyladenosine (m6 A) is an mRNA modification widely found in eukaryotes and plays a crucial role in plant development and stress responses. FIONA1 (FIO1) is a recently identified m6 A methyltransferase that regulates Arabidopsis (Arabidopsis thaliana) floral transition; however, its role in stress response remains unknown. In this study, we demonstrate that FIO1-mediated m6 A methylation plays a vital role in salt stress response in Arabidopsis. The loss-of-function fio1 mutant was sensitive to salt stress. Importantly, the complementation lines expressing the wild-type FIO1 exhibited the wild-type phenotype, whereas the complementation lines expressing the mutant FIO1m , in which two critical amino acid residues essential for methyltransferase activity were mutated, did not recover the wild-type phenotype under salt stress, indicating that the salt sensitivity is associated with FIO1 methyltransferase activity. Furthermore, FIO1-mediated m6 A methylation regulated ROS production and affected the transcript level of several salt stress-responsive genes via modulating their mRNA stability in an m6 A-dependent manner in response to salt stress. Importantly, FIO1 is associated with salt stress response by specifically targeting and differentially modulating several salt stress-responsive genes compared with other m6 A writer. Collectively, our findings highlight the molecular mechanism of FIO1-mediated m6 A methylation in the salt stress adaptation.

Productive Poplar Genotypes Exhibited Temporally Stable Low Stem Embolism Resistance and Hydraulic Resistance Segmentation at the Stem-Leaf Transition.

Breeding tree genotypes that are both productive and drought-resistant is a primary goal in forestry. However, the relationships between plant hydraulics and yield at the genotype level, and their temporal stabilities, remain unclear. We selected six poplar genotypes from I-101 (Populus alba) × 84 K (P. alba × Popolus tremula var. glandulosa) for experiments in the first and fourth years after planting in a common garden. Measurements included stem embolism resistance, shoot hydraulic resistance and its partitioning between stems and leaves, vessel- and pit-level anatomy, leaf carbon acquisition capacity, carbon allocation to leaves, and aboveground biomass (yield proxy). Significant genetic variations in hydraulic properties and yield were found among genotypes in both years. Productive genotypes had wide vessels, large thin pit membranes, small pit apertures, and shallow pit chambers. Hydraulic resistance was negatively correlated with yield, enabling high stomatal conductance and assimilation rates. Productive genotypes allocated less aboveground carbon and hydraulic resistance to leaves. Temporally stable trade-offs between stem embolism resistance and yield, and between hydraulic segmentation and yield, were identified. These findings highlight the tight link between hydraulic function and yield and suggest that stable trade-offs may challenge breeding poplar genotypes that are both productive and drought-resistant.

Optical design and fabrication of a multi-channel imaging spectrometer for combustion flame monitoring.

We design and construct a broadband integrated multi-channel imaging spectrometer (MCIS) from visible light to near-infrared. This system can directly obtain spectral images that conform to the consistent visual habits of the human eyes through a single exposure of the detector. The genetic algorithm is used to calculate system parameters to minimize pixel waste between spectral channels, achieving nearly 100% utilization of detector pixels. The field stop suppresses stray light in the system. This device is used for imaging an optical-resolution target, an object, and a furnace to verify the basic principles of the system. The results indicate that the system can effectively utilize detectors to monitor high-temperature objects in the visible to near-infrared wavelength range.

Quantitative texture analysis using machine learning for predicting interpretable pulmonary perfusion from non-contrast computed tomography in pulmonary embolism patients.

BACKGROUND: Pulmonary embolism (PE) is life-threatening and requires timely and accurate diagnosis, yet current imaging methods, like computed tomography pulmonary angiography, present limitations, particularly for patients with contraindications to iodinated contrast agents. We aimed to develop a quantitative texture analysis pipeline using machine learning (ML) based on non-contrast thoracic computed tomography (CT) scans to discover intensity and textural features correlated with regional lung perfusion (Q) physiology and pathology and synthesize voxel-wise Q surrogates to assist in PE diagnosis. METHODS: We retrospectively collected 99mTc-labeled macroaggregated albumin Q-SPECT/CT scans from patients suspected of PE, including an internal dataset of 76 patients (64 for training, 12 for testing) and an external testing dataset of 49 patients. Quantitative CT features were extracted from segmented lung subregions and underwent a two-stage feature selection pipeline. The prior-knowledge-driven preselection stage screened for robust and non-redundant perfusion-correlated features, while the data-driven selection stage further filtered features by fitting ML models for classification. The final classification model, trained with the highest-performing PE-associated feature combination, was evaluated in the testing cohorts based on the Area Under the Curve (AUC) for subregion-level predictability. The voxel-wise Q surrogate was then synthesized using the final selected feature maps (FMs) and model score maps (MSMs) to investigate spatial distributions. The Spearman correlation coefficient (SCC) and Dice similarity coefficient (DSC) were used to assess the spatial consistency between FMs or MSMs and Q-SPECT scans. RESULTS: The optimal model performance achieved an AUC of 0.863 during internal testing and 0.828 on the external testing cohort. The model identified a combination containing 14 intensity and textural features that were non-redundant, robust, and capable of distinguishing between high- and low-functional lung regions. Spatial consistency assessment in the internal testing cohort showed moderate-to-high agreement between MSMs and reference Q-SPECT scans, with median SCC of 0.66, median DSCs of 0.86 and 0.64 for high- and low-functional regions, respectively. CONCLUSIONS: This study validated the feasibility of using quantitative texture analysis and a data-driven ML pipeline to generate voxel-wise lung perfusion surrogates, providing a radiation-free, widely accessible alternative to functional lung imaging in managing pulmonary vascular diseases. CLINICAL TRIAL NUMBER: Not applicable.