[Quality evaluation and grading standard discussion on Cinnamomi Ramulus].

This study explored the relationship between the appearance traits and internal components of Cinnamomi Ramulus pieces, so as to provide a reference for the quality evaluation and the formulation of grade standards. This study determined the appearance traits and index component contents of 41 batches of Cinnamomi Ramulus pieces in the core producing areas of Guangxi and Guangdongand established the HPLC characteristic map method. The weight of the pieces, the narrowest diameter, and the widest diameter of the tr ansverse section were used as the indices of appearance traits. The content of index components(cinnamic acid and cinnamalde hyde)was determined by the established content determination method. The chromatographic characteristics were determinedon a Waters XBridge C_(18)(4. 6 mm×250 mm, 5 µm) column with a mobile phase consisting of 0. 1% phosphoric acidacetonitrile and gradient elution at the flow rate of 1 mL ·min~(-1). The column temperature was 30 ℃, and the detection wavelength was 254 nm. Cluster analysis, principal component analysis, and other stoichiometric methods were used to analyze the correlation between theap pearance traits and the index/characteristic components of Cinnamomi Ramulus pieces and compare the qu ality differences of the piecesfrom different batches and plac es. The results showed that the larger weight, the narrowest diameter, andthe widest diameter of the tra nsverse section indicated lowercontent of main indexes/characteristic components, and there was a synergistic decreasing trend amongd ifferent components. The overall quality of Cinnamomi Ramulus pieces in Guangdong Province and Guangxi Province was similar, but there were still differences between different origins and different batches of the same origin. It is scientific and feasible to evaluatethe quality of Cinnamomi Ramulus pieces and establish grading standards based on the appearance traits and index/character istic components. The research provides a more scientific and comprehensive basis for the quality control evaluation and standardformulation of Cinnamomi Ramulus.

Genomics and resequencing of Fagopyrum dibotrys from different geographic regions reveals species evolution and genetic diversity.

Fagopyrum dibotrys, belonging to the family Polygonaceae and genus Fagopyrum, is used in traditional Chinese medicine and is rich in beneficial components, such as flavonoids. As its abundant medicinal value has become increasingly recognized, its excessive development poses a considerable challenge to wild germplasm resources, necessitating artificial cultivation and domestication. Considering these factors, a high-quality genome of F. dibotrys was assembled and the evolutionary relationships within Caryophyllales were compared, based on which 58 individual samples of F. dibotrys were re-sequenced. We found that the samples could be categorized into three purebred populations and regions distributed at distinct elevations. Our varieties were cultivated from the parental populations of the subpopulation in central Yunnan. F. dibotrys is speculated to have originated in the high-altitude Tibetan Plateau region, and that its combination with flavonoids can protect plants against ultraviolet radiation; this infers a subpopulation with a high accumulation of flavonoids. This study assembled a high-quality genome and provided a theoretical foundation for the future introduction, domestication, and development of cultivated varieties of F. dibotrys.

The prognostic value of sialylation-related long non-coding RNAs in lung adenocarcinoma.

There has been increasing interest in the role of epigenetic modification in cancers recently. Among the various modifications, sialylation has emerged as a dominant subtype implicated in tumor progression, metastasis, immune evasion, and chemoresistance. The prognostic significance of sialylation-related molecules has been demonstrated in colorectal cancer. However, the potential roles and regulatory mechanisms of sialylation in lung adenocarcinoma (LUAD) have not been thoroughly investigated. Through Pearson correlation, univariate Cox hazards proportional regression, and random survival forest model analyses, we identified several prognostic long non-coding RNAs (lncRNAs) associated with aberrant sialylation and tumor progression, including LINC00857, LINC00968, LINC00663, and ITGA9-AS1. Based on the signatures of four lncRNAs, we classified patients into two clusters with different landscapes using a non-negative matrix factorization approach. Collectively, patients in Cluster 1 (C1) exhibited worse prognoses than those in Cluster 2 (C2), as well as heavier tumor mutation burden. Functional enrichment analysis showed the enrichment of several pro-tumor pathways in C1, differing from the upregulated Longevity and programmed cell death pathways in C2. Moreover, we profiled immune infiltration levels of important immune cell lineages in two subgroups using MCPcounter scores and single sample gene set enrichment analysis scores, revealing a relatively immunosuppressive microenvironment in C1. Risk analysis indicated that LINC00857 may serve as a pro-tumor regulator, while the other three lncRNAs may be protective contributors. Consistently, we observed upregulated LINC00857 in C1, whereas increased expressive levels of LINC00968, LINC00663, and ITGA9-AS1 were observed in C2. Finally, drug sensitivity analysis suggested that patients in the two groups may benefit from different therapeutic strategies, contributing to precise treatment in LUAD. By integrating multi-omics data, we identified four core sialylation-related lncRNAs and successfully established a prognostic model to distinguish patients with different characterizations. These findings may provide some insights into the underlying mechanism of sialylation, and offer a new stratification way as well as clinical guidance in LUAD.

WW domains form a folded type of nuclear localization signal to guide YAP1 nuclear import.

The nuclear translocation of YAP1 is significantly implicated in the proliferation, stemness, and metastasis of cancer cells. Although the molecular basis underlying YAP1 subcellular distribution has been extensively explored, it remains to be elucidated how the nuclear localization signal guides YAP1 to pass through the nuclear pore complex. Here, we define a globular type of nuclear localization signal composed of folded WW domains, named as WW-NLS. It directs YAP1 nuclear import through the heterodimeric nuclear transport receptors KPNA-KPNB1, bypassing the canonical nuclear localization signal that has been well documented in KPNA/KPNB1-mediated nuclear import. Strikingly, competitive interference with the function of the WW-NLS significantly attenuates YAP1 nuclear translocation and damages stemness gene activation and sphere formation in malignant breast cancer cells. Our findings elucidate a novel globular type of nuclear localization signal to facilitate nuclear entry of WW-containing proteins including YAP1.

AS-NeSt: A Novel 3D Deep Learning Model for Radiation Therapy Dose Distribution Prediction in Esophageal Cancer Treatment With Multiple Prescriptions.

PURPOSE: Implementing artificial intelligence technologies allows for the accurate prediction of radiation therapy dose distributions, enhancing treatment planning efficiency. However, esophageal cancers present unique challenges because of tumor complexity and diverse prescription types. Additionally, limited data availability hampers the effectiveness of existing artificial intelligence models. This study developed a deep learning model, trained on a diverse data set of esophageal cancer prescriptions, to improve dose prediction accuracy. METHODS AND MATERIALS: We retrospectively collected data from 530 patients with esophageal cancer, including single-target and simultaneous integrated boost prescriptions, for model building. The proposed Asymmetric ResNeSt (AS-NeSt) model features novel 3-dimensional (3D) ResNeSt blocks and an asymmetrical architecture. We constructed a loss function targeting global and local doses and validated the model's performance against existing alternatives. Model-assisted experiments were used to validate its clinical benefits. RESULTS: The AS-NeSt model maintained an absolute prediction error below 5% for each dosimetric metric. The average Dice similarity coefficient for isodose volumes was 0.93. The model achieved an average relative prediction error of 2.02%, statistically lower than Hierarchically Densely Connected U-net (4.17%), DoseNet (2.35%), and Densely Connected Network (3.65%). It also demonstrated significantly fewer parameters and shorter prediction times. Clinically, the AS-NeSt model raised physicians' ability to accurately preassess appropriate treatment methods before planning from 95.24% to 100%, reduced planning time by over 61% for junior dosimetrists and 52% for senior dosimetrists, and decreased both inter- and intra-dosimetrist discrepancies by more than 50%. CONCLUSIONS: The AS-NeSt model, developed with innovative 3D ResNeSt blocks and an asymmetrical encoder-decoder structure, has been validated using clinical esophageal cancer patient data. It accurately predicts 3D dose distributions for various prescriptions, including simultaneous integrated boost, showing potential to improve the management of esophageal cancer treatment in a clinical setting.

Transforming Passive Employee Engagement Into Active Engagement: Supervisor Development Feedback Valences on Feedback-Seeking Behavior.

Employees' feedback-seeking behavior is an important way to develop and maintain self-awareness and interpersonal acuity, reduce uncertainty, boost creativity and improve innovative behavior and performance. Especially during the COVID-19 pandemic, working from home has become the new normal, supervisor feedback and employees feedback-seeking has an increasingly important impact on team creativity and team innovation performance.In the practice of organizational management, there is frequently a "feedback vacuum" between managers and employees. There is increasing research on feedback-seeking behavior in the field of OBHRM. This paper is the first to evaluate the impact of work meaning and positive attributions on workers' feedback-seeking behavior, and the cross-level effects of supervisor development feedback including variable valence. The paper analyzes supervisor-employee paired data from 158 supervisors and 659 employees using multi-source, multi-temporal data to draw the following conclusions: (1) Positive supervisor development feedback has a significant cross-level positive effect on employee feedback-seeking behavior, whereas negative supervisor development feedback does not affect employee feedback-seeking behavior; (2) Work meaningfulness mediates the cross-level relationship between positive supervisor development feedback and employees' feedback-seeking behaviors, whereas negative supervisor development feedback and employees' feedback-seeking behaviors do not; (3) Positive attributions positively moderate the relationship between positive supervisor development feedback and work meaningfulness; while positively moderating the relationship between negative supervisor development feedback and work meaningfulness; (4) Positive attributions have a moderating effect on supervisor development feedback that influences the indirect relationship to feedback-seeking behavior by work meaningfulness.

Conical diffractions of multilayered gratings modeled by Cartesian rigorous coupled-wave analysis.

Rigorous coupled-wave analysis (RCWA) has become one of the most efficient electromagnetic solvers to cope with the diffractions of large-scale periodic nanostructures. Conventional RCWAs focus on planar diffractions and their iterative stabilities. Conical diffractions, as more general incidence cases, are paid little attention in developing their universal and stable implementations for multilayered gratings. Here, we reformulate RCWA algorithms step by step for conical diffractions in a global Cartesian coordinate system. By applying some mathematics tricks, it is found that boundary conditions in conical diffractions can be reduced to the same forms as that of planar diffractions. Conventional stable algorithms including enhanced transmittance matrices and scattering matrices can be directly implemented to attain robust diffraction efficiencies as well as electromagnetic fields for multilayered gratings. An exemplary application in diffractive-waveguide-based augmented reality verified our algorithms.

Plasmonic metafibers electro-optic modulators.

Digitalizing optical signals through electric driving signals, electro-optic modulators (EOMs) are one of the cardinal elements in modern optical communications. Most of current EOM devices are targeting on-chip integrations, which routinely suffer from high coupling losses, complex optical alignments and single-band operations. In this study, we for the first time integrate a lumped EOM device on the endfaces of a single-mode optical fiber jumper for fast amplitude modulations. Profiting from ultrathin and high quality-factor plasmonic metasurfaces, nanofabrication-friendly and highly efficient EO polymers and coupling-free connections with fiber networks, our EOM is demonstrated to allow dual-band operations (telecom O band and S band) and high-speed modulations (~1 GHz at a bias voltage of ±9 V). This work offers an avenue to 'plug-and-play' implementations of EO devices and ultracompact "all-in-fibers" optical systems for communications, imaging, sensing and many others.

Novel in-house knowledge-based automated planning system for lung cancer treated with intensity-modulated radiotherapy.

PURPOSE: The goal of this study was to propose a knowledge-based planning system which could automatically design plans for lung cancer patients treated with intensity-modulated radiotherapy (IMRT). METHODS AND MATERIALS: From May 2018 to June 2020, 612 IMRT treatment plans of lung cancer patients were retrospectively selected to construct a planning database. Knowledge-based planning (KBP) architecture named αDiar was proposed in this study. It consisted of two parts separated by a firewall. One was the in-hospital workstation, and the other was the search engine in the cloud. Based on our previous study, A­Net in the in-hospital workstation was used to generate predicted virtual dose images. A search engine including a three-dimensional convolutional neural network (3D CNN) was constructed to derive the feature vectors of dose images. By comparing the similarity of the features between virtual dose images and the clinical dose images in the database, the most similar feature was found. The optimization parameters (OPs) of the treatment plan corresponding to the most similar feature were assigned to the new plan, and the design of a new treatment plan was automatically completed. After αDiar was developed, we performed two studies. The first retrospective study was conducted to validate whether this architecture was qualified for clinical practice and involved 96 patients. The second comparative study was performed to investigate whether αDiar could assist dosimetrists in improving the quality of planning for the patients. Two dosimetrists were involved and designed plans for only one trial with and without αDiar; 26 patients were involved in this study. RESULTS: The first study showed that about 54% (52/96) of the automatically generated plans would achieve the dosimetric constraints of the Radiation Therapy Oncology Group (RTOG) and about 93% (89/96) of the automatically generated plans would achieve the dosimetric constraints of the National Comprehensive Cancer Network (NCCN). The second study showed that the quality of treatment planning designed by junior dosimetrists was improved with the help of αDiar. CONCLUSIONS: Our results showed that αDiar was an effective tool to improve planning quality. Over half of the patients' plans could be designed automatically. For the remaining patients, although the automatically designed plans did not fully meet the clinical requirements, their quality was also better than that of manual plans.

Accurate luminance and chromaticity controls of digital colors using CIE-based RGBW algorithms.

Emerging high brightness of color displays and high signal-to-noise ratio of camera sensors require an addition of white (W) subpixels to ordinary red, green, and blue (RGB) subpixels. Conventional algorithms converting RGB signals to RGBW signals suffer from reduced chroma of highly saturated colors and complicated coordinate transformations between RGB color spaces and color spaces defined by the Commission internationale de l'éclairage (CIE). In this work, we developed a complete set of RGBW algorithms to digitally code a color in the CIE-based color spaces, making complicated processes including color space transformations and white balancing become largely unnecessary. The analytic three-dimensional gamut can be obtained so that the maximal hue and luminance of a digital frame could be simultaneously obtained. Exemplary applications in adaptive controls of the colors of an RGB display in accordance with the W component of background light validate our theory. The algorithm opens an avenue toward accurate manipulations of digital colors for RGBW sensors and displays.

Artificial intelligence with a deep learning network for the quantification and distinction of functional adrenal tumors based on contrast-enhanced CT images.

Background: Functional adrenal tumors (FATs) are mainly diagnosed by biochemical analysis. Traditional imaging tests have limitations and cannot be used alone to diagnose FATs. In this study, we aimed to establish an artificially intelligent diagnostic model based on computed tomography (CT) images to distinguish different types of FATs. Methods: A cohort study of 375 patients diagnosed with hyperaldosteronism (HA), Cushing's syndrome (CS), and pheochromocytoma in our center between March 2015 and June 2020 was conducted. Retrospectively, patients were randomly divided into three data sets: the training set (270 cases), the testing set (60 cases), and the retrospective trial set (45 cases). An artificially intelligent diagnostic model based on CT images was established by transferring data from the training set into the deep learning network. The testing set was then used to evaluate the accuracy of the model compared to that of physicians' judgments. The retrospective trial set was used to evaluate the quantification and distinction performance. Results: The deep learning model achieved an average area under the receiver operating characteristic (ROC) curve (AUC) of 0.915, and the AUCs in all three FAT types were greater than 0.882. The AUC of the model tested on the retrospective dataset reached above 0.849. In the quantitative evaluation of tumor lesion area recognition, the diagnostic model also obtained a segmentation Dice coefficient of 0.69. With the help of the proposed model, clinicians reached 92.5% accuracy in distinguishing FATs, compared to 80.6% accuracy when using only their judgment (P<0.05). Conclusions: The result of our study shows that the diagnostic model based on a deep learning network can distinguish and quantify three common FAT types based on texture features of contrast-enhanced CT images. The model can quantify and distinguish functional tumors without any endocrine tests and can assist clinicians in the diagnostic procedure.

Case Report: Differential lung ventilation with jet ventilation via a bronchial blocker for a patient with a large thoracogastric airway fistula after esophagectomy.

Background: A thoracogastric airway fistula (TGAF) is a rare and potentially fatal complication of esophagectomy for esophageal and cardia carcinomas. Isolation of the fistula and pulmonary separation is necessary during the surgical repair of a tracheal fistula. However, currently, the reported airway management techniques are not suitable for patients with a large TGAF. This case study presents an alternative technique for performing differential lung ventilation in a patient with a thoracogastric airway fistula. Case presentation: A 70-year-old man was diagnosed with a thoracogastric airway fistula situated above the carina after esophagectomy, and a thoracoscope-assisted repair of the fistula and pectoralis major myocutaneous flap transplantation were scheduled. The patient could not tolerate one-lung ventilation and the complex intubating operation due to aspiration pneumonia and the size (3.5 cm × 1.7 cm) of the fistula. We, therefore, performed differential lung ventilation in which an extended 6.5#single-lumen endotracheal tube was inserted into the left main bronchus and a 9Fr bronchial blocker was placed in the right main bronchus by using the video-flexible intubation scope. The right lung was selectively inflated with jet ventilation, while positive pressure ventilation was maintained through the left endotracheal tube. The value of SPO2 remained above 95% throughout the operation. Conclusion: For patients with a large thoracogastric airway fistula, differential lung ventilation of a combination of positive pressure ventilation and jet ventilation is useful. Inserting an extended single-lumen endotracheal tube into the left main bronchus and a bronchial blocker into the right main bronchus could be another way of providing differential ventilation for patients with a large thoracogastric airway fistula.

Icariside II suppressed tumorigenesis by epigenetically regulating the circß-catenin-Wnt/ß-catenin axis in colorectal cancer.

Icariside II, a flavonol glycoside, one of the major components of Traditional Chinese Medicine Herba epimedii. In the present study, we found that Icariside II suppressed the proliferation of CRC by inducing cell cycle arrest and apoptosis in vitro and inhibited tumor growth in vivo. The further mechanism investigation showed that Icariside II suppressed the expression of ß-catenin and led to the functional inactivation of Wnt/ß-catenin signaling. Circß-catenin was considered as a promising candidate for mediating the tumorigenesis and the activation of Wnt/ß-catenin signaling in CRC cells. Furthermore, Icariside II has been proven to suppress the biogenesis of circß-catenin via epigenetically targeting DNA methyltransferases (DNMTs) to decrease global DNA methylation levels in CRC cells. Taken together, our results indicated that Icariside II suppressed tumorigenesis by epigenetically silencing the activation of circß-catenin-Wnt/ß-catenin axis in colorectal cancer. More importantly, the information gained from this study suggest that Icariside II may have great potential to be developed as a therapeutic drug for CRC patients.

FNDC5/irisin facilitates muscle-adipose-bone connectivity through ubiquitination-dependent activation of runt-related transcriptional factors RUNX1/2.

In the past decade, the cleavage protein irisin derived from fibronectin type III domain-containing protein 5 (FNDC5) in exercise-stimulated skeletal muscle has increasingly become a biomarker associated with metabolic syndrome and osteoporosis in humans. However, it is unclear how this protein facilitates muscle-adipose-bone connectivity in metabolic and skeletal homeostasis. In this study, we unexpectedly observed that the FNDC5 gene can be markedly activated during the differentiation of brown adipocytes but not white adipocytes, and that FNDC5 is specifically expressed in mouse brown adipose tissues (BATs). But unlike it in the skeletal muscles, the expression of FNDC5/irisin in BAT is promoted by cold exposure rather than exercise in mice. Analysis of promoter activity and chromatin immunoprecipitation further showed that peroxisome proliferator-activated receptor γ coactivator-1α and thyroid hormone receptors cooperate on the FNDC5 gene promoter to induce its transcription. We found that FNDC5/irisin stimulates the runt-related transcriptional factors RUNX1/2 via a focal adhesion kinase-dependent pathway in both bone and subcutaneous white adipose tissues. Mechanistically, focal adhesion kinase is stimulated by FNDC5/irisin and then facilitates E3 ubiquitin-protein ligase WW domain-containing protein 2 to ubiquitinate and subsequently activate RUNX1/2, culminating in the activation of osteoblast-related or thermogenesis-related genes. Interestingly, the PR domain containing protein 16 that is crucial for subcutaneous white adipose "browning" and skeletal development was found to form a complex with RUNX1/2 in a WW domain-containing protein 2-dependent manner. These findings elucidate a signaling mechanism by which FNDC5/irisin supports the muscle-adipose-bone connectivity, especially BAT-bone connectivity.

Clinical findings and a DNA methylation signature in kindreds with alterations in ZNF711.

ZNF711 is one of eleven zinc-finger genes on the X chromosome that have been associated with X-linked intellectual disability. This association is confirmed by the clinical findings in 20 new cases in addition to 11 cases previously reported. No consistent growth aberrations, craniofacial dysmorphology, malformations or neurologic findings are associated with alterations in ZNF711. The intellectual disability is typically mild and coexisting autism occurs in half of the cases. Carrier females show no manifestations. A ZNF711-specific methylation signature has been identified which can assist in identifying new cases and in confirming the pathogenicity of variants in the gene.

Micro-scale opto-thermo-mechanical actuation in the dry adhesive regime.

Realizing optical manipulation of microscopic objects is crucial in the research fields of life science, condensed matter physics, and physical chemistry. In non-liquid environments, this task is commonly regarded as difficult due to strong adhesive surface force (~µN) attached to solid interfaces that makes tiny optical driven force (~pN) insignificant. Here, by recognizing the microscopic interaction mechanism between friction force-the parallel component of surface force on a contact surface-and thermoelastic waves induced by pulsed optical absorption, we establish a general principle enabling the actuation of micro-objects on dry frictional surfaces based on the opto-thermo-mechanical effects. Theoretically, we predict that nanosecond pulsed optical absorption with mW-scale peak power is sufficient to tame µN-scale friction force. Experimentally, we demonstrate the two-dimensional spiral motion of gold plates on micro-fibers driven by nanosecond laser pulses, and reveal the rules of motion control. Our results pave the way for the future development of micro-scale actuators in non-liquid environments.

Virtual Patient-Specific Quality Assurance of IMRT Using UNet++: Classification, Gamma Passing Rates Prediction, and Dose Difference Prediction.

The dose verification in radiotherapy quality assurance (QA) is time-consuming and places a heavy workload on medical physicists. To provide a clinical tool to perform patient specific QA accurately, the UNet++ is investigated to classify failed or pass fields (the GPR lower than 85% is considered "failed" while the GPR higher than 85% is considered "pass"), predict gamma passing rates (GPR) for different gamma criteria, and predict dose difference from virtual patient-specific quality assurance in radiotherapy. UNet++ was trained and validated with 473 fields and tested with 95 fields. All plans used Portal Dosimetry for dose verification pre-treatment. Planar dose distribution of each field was used as the input for UNet++, with QA classification results, gamma passing rates of different gamma criteria, and dose difference were used as the output. In the test set, the accuracy of the classification model was 95.79%. The mean absolute error (MAE) were 0.82, 0.88, 2.11, 2.52, and the root mean squared error (RMSE) were 1.38, 1.57, 3.33, 3.72 for 3%/3mm, 3%/2 mm, 2%/3 mm, 2%/2 mm, respectively. The trend and position of the predicted dose difference were consistent with the measured dose difference. In conclusion, the Virtual QA based on UNet++ can be used to classify the field passed or not, predict gamma pass rate for different gamma criteria, and predict dose difference. The results show that UNet++ based Virtual QA is promising in quality assurance for radiotherapy.