COVID-19-induced granulomatosis with polyangiitis: A case report of a 16-year-old East Asian and literature review.

OBJECTIVE: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is divided into granulomatosis with polyangiitis (GPA), microscopic polyangiitis, and eosinophilic GPA. It is one of the most severe and potentially fatal autoimmune inflammatory conditions. The etiology and pathology of AAV are complex and poorly understood. Since the onset of the Coronavirus Disease 2019 (COVID-19) pandemic, numerous reports have documented GPA cases following COVID-19, suggesting a potential link between COVID-19 and the development of GPA. This case report discusses a 16-year-old East Asian boy who developed GPA with diffuse alveolar hemorrhage after contracting COVID-19. Additionally, a literature review was conducted to gain a deeper understanding of this disorder. METHODS: The study involved a retrospective analysis of the data of a case of GPA post-COVID-19 infection, aiming to summarize the clinical characteristics of GPA post-COVID-19 infection through a search of databases (PubMed, Wanfang Data, and CNKI), supplemented by standard searches in Google Scholar, Cochrane, Scopus, and LitCovid, and to conduct a comprehensive analysis of the literature. RESULTS: A total of 12 cases were identified and, when combined with the present case, yielded 13 cases of GPA post-COVID-19 infection, comprising 5 males and 8 females with an average age of (40.6 ± 19.5) years. The interval between COVID-19 infection and the diagnosis of GPA varied from 1 day to 3 months across all cases. Mortality was reported at 7.7% (1/13). The most common clinical manifestations included cough (69.2%) and dyspnea (46.1%). Computed tomography scans revealed ground-glass opacities and multifocal pulmonary nodules. In all cases, positive findings for c-ANCA and protease 3-antibody were observed. Renal involvement was observed in more than half of the patients.

Arabidopsis thaliana YUC1 reduced fluoranthene accumulation by modulating IAA content and antioxidant enzyme activities.

Indole-3-acetic acid (IAA) can regulate plant growth and thus modulate the accumulation of polycyclic aromatic hydrocarbons (PAHs). However, the effect of endogenous IAA on PAHs accumulation and its influencing factors remains unclear. To unravel this, two different IAA expression genotypes of Arabidopsis thaliana, i.e., IAA-underproducing yucca1D [YUC1] mutant and wild type [WT]) were selected and treated with different fluoranthene (Flu) concentrations (0 mg/L [CK], 5 mg/L [Flu5], and 20 mg/L [Flu20]) to reveal the impact mechanism of endogenous IAA on Flu uptake by plants. The results indicated that under Flu5 treatment, the bioconcentration factors (BCF) and translocation factors (TF) of Flu in WT were 41.4 % and 14.3 % higher than those in YUC1. Similarly, under Flu20 treatment, the BCF and TF of Flu in WT were also 42.2 % and 8.2 % higher than those in YUC1. In addition, the BCF and TF were 72.5 % and 35.8 % higher under Flu5 treatment compared to Flu20 treatment for WT, and 73.4 % and 28.6 % higher respectively for YUC1. Moreover, WT exhibited higher plant growth (biomass, root morphology indicators [root length, root area and number of tips]) and IAA content compared to YUC1 under identical Flu treatments. Plant growth and IAA content declined with the increase of Flu concentration in both YUC1 and WT leaves compared with CK treatment. Conversely, in WT roots, root biomass and morphology indicators promoted followed by a decrease as the concentration of Flu increased. Additionally, the antioxidant enzyme activities (SOD, POD, and CAT) of WT were 11.1 %, 16.7 %, and 28.9 % higher than those of YUC1 under Flu5 treatment, and 13.6 %, 12.9 %, and 26.5 % higher under Flu20 treatment. Compared with CK treatment, SOD and POD activities promoted with increasing Flu concentration, whereas CAT activities decreased. Variability separation analysis revealed that level of IAA primarily influenced Flu accumulation in WT or under Flu5 treatments, whereas antioxidant enzyme activity primarily affected Flu accumulation in YUC1 or under Flu20 treatments. Exploring the relationship between the IAA synthesis gene YUCCA and IAA levels, alongside Flu accumulation, could yield novel insights into the regulation of PAH accumulation in plants.

Nanoceria-induced variations in leaf anatomy and cell wall composition drive the increase in mesophyll conductance of salt-stressed cotton leaves.

Nanomaterials as an emerging tool are being used to improve plant's net photosynthetic rate (AN) when suffering salt stress, but the underlying mechanisms remain unclear. To clarify this, a hydroponic experiment was conducted to study the effects of polyacrylic acid coated nanoceria (PNC) on the AN of salt-stressed cotton and related intrinsic mechanisms. Results showed that the PNC-induced AN enhancement of salt-stressed leaves was strongly facilitated by the mesophyll conductance to CO2 (gm). Further analysis showed that the PNC-induced improvement of gm was related to the increased chloroplast surface area exposed to intercellular airspaces, which was attribute to the increased mesophyll surface area exposed to intercellular airspaces and chloroplast number due to the increased K+ content and decreased reactive oxygen species level in salt-stressed leaves. Interestingly, our results also showed that PNC-induced variations in cell wall composition of salt-stressed cotton leaves strongly influenced gm, especially, hemicellulose and pectin. Moreover, the proportion of pectin in cell wall composition played a more important role in determining gm. Our study demonstrated for the first time that nanoceria, through alterations to anatomical traits and cell wall composition, drove gm enhancement, which ultimately increased AN of salt-stressed leaves.

Clinical Features and a Prediction Model for Early Prediction of Composite Outcome in Chlamydia psittaci Pneumonia: A Multi-Centre Retrospective Study in China.

Introduction: C. psittaci pneumonia has atypical clinical manifestations and is often ignored by clinicians. This study analyzed the clinical characteristics, explored the risk factors for composite outcome and established a prediction model for early prediction of composite outcome among C. psittaci pneumonia patients. Methods: A multicenter, retrospective, observational cohort study was conducted in ten Chinese tertiary hospitals. Patients diagnosed with C. psittaci pneumonia were included, and their clinical data were collected and analyzed. The composite outcome of C. psittaci pneumonia included death during hospitalization, ICU admission, and mechanical ventilation. Univariate and multivariable logistic regression analyses were conducted to determine the significant variables. A ten-fold cross-validation was performed to internally validate the model. The model performance was evaluated using various methods, including receiver operating characteristics (ROC), C-index, sensitivity, specificity, positive/negative predictive value (PPV/NPV), decision curve analysis (DCA), and clinical impact curve analysis (CICA). Results: In total, 83 patients comprised training cohorts and 36 patients comprised validation cohorts. CURB-65 was used to establish predictive Model 1. Multivariate logistic regression analysis identified three independent prognostic factors, including serum albumin, CURB-65, and white blood cells. These factors were employed to construct model 2. Model 2 had acceptable discrimination (AUC of 0.898 and 0.825 for the training and validation sets, respectively) and robust internal validity. The specificity, sensitivity, NPV, and PPV for predicting composite outcome in the nomogram model were 91.7%, 84.5%, 50.0%, and 98.4% in the training sets, and 100.0%, 64.7%, 14.2%, and 100.0% in the validation sets. DCA and CICA showed that the nomogram model was clinically practical. Conclusion: This study constructs a refined nomogram model for predicting the composite outcome in C. psittaci pneumonia patients. This nomogram model enables early and accurate C. psittaci pneumonia patients' evaluation, which may improve clinical outcomes.

Is postoperative adjuvant radiotherapy necessary for patients with esophageal cancer after neoadjuvant chemoradiotherapy? An analysis based on the SEER database.

OBJECTIVES: To evaluate the outcomes of adjuvant radiotherapy in patients with esophageal cancer (EC) who underwent esophagectomy following neoadjuvant chemoradiotherapy (NCRT). METHODS: The data of EC patients who received adjuvant therapy after NCRT between 2004 to 2019 was retrieved from the SEER database. The patients were split into the adjuvant radiotherapy with or without chemotherapy (RT±CT) and the adjuvant chemotherapy (CT) groups. The process of propensity score matching (PSM) was employed. RESULTS: Following PSM, 157 patients in total were recruited in each treatment group. There were no significant variations in either overall survival (OS) or cancer-specific survival (CSS) between the RT±CT and CT groups (median OS: 28 months versus. 51 months, p=0.063; median CSS: 31 months versus. 52 months, p=0.16). Within the CT group, patients with ypI/II or cI/II tumor stage, positive lymph node ratio (LNR) ≤0.1, and tumor size ≥50 mm (p<0.05) had higher OS compared to the RT±CT groups. Among patients with cT3-4 tumors in N-stage downstaging group, the OS and CSS were significantly greater for those underwent RT±CT as opposed to the CT group (5-year OS:56.6% versus 19.4%, p=0.042; 5-year CSS:67.9% versus. 19.4%, p=0.023). Multivariate Cox regression analysis identified the tumor histology grade as an independent prognostic factor of OS and CSS. CONCLUSION: Radiotherapy-based adjuvant therapy does not significantly improve the prognosis of EC patients after NCRT, although it may provide a survival benefit for patients with cT3-4 tumors in N-stage downstaging.

Computer vision based cargo boxes pose adjustment system for two-dimensional conveyor platform.

For enhancing the accuracy of cargo box position and angle recognition on the conveyor platform, this paper proposes a cargo box attitude detection and adjustment method based on instance segmentation and image processing. This approach involves generating Mask data through target detection of the cargo box using Mask R-CNN. Using image processing algorithms to generate a minimum rectangle according to the Mask data, and the minimum rectangle data is aligned with the Bbox data of Maks R-CNN. The position and angle of the cargo box are detected based on the minimum rectangular data, and the conveyor platform is adjusted to control the cargo box attitude using the Bbox data. Nine attitude acquisition and comparison experiments were conducted on the cargo box using an angle sensor, and the deviation of the method was consistently < 0 . 6 ∘ , with a relative error of 1.27% for the nine total changes. Importantly, the image processing technique in this study avoids external image processing, reducing ambient light impact and enhancing cargo box recognition and attitude feedback functionality on the conveyor platform. Throughout the entire cargo box adjustment experiment, the cargo box's can be stabilized to reach the set angle.

ASF-LKUNet: Adjacent-scale fusion U-Net with large kernel for multi-organ segmentation.

In the multi-organ segmentation task of medical images, there are some challenging issues such as the complex background, blurred boundaries between organs, and the larger scale difference in volume. Due to the local receptive fields of conventional convolution operations, it is difficult to obtain desirable results by directly using them for multi-organ segmentation. While Transformer-based models have global information, there is a significant dependency on hardware because of the high computational demands. Meanwhile, the depthwise convolution with large kernel can capture global information and have less computational requirements. Therefore, to leverage the large receptive field and reduce model complexity, we propose a novel CNN-based approach, namely adjacent-scale fusion U-Net with large kernel (ASF-LKUNet) for multi-organ segmentation. We utilize a u-shaped encoder-decoder as the base architecture of ASF-LKUNet. In the encoder path, we design the large kernel residual block, which combines the large and small kernels and can simultaneously capture the global and local features. Furthermore, for the first time, we propose an adjacent-scale fusion and large kernel GRN channel attention that incorporates the low-level details with the high-level semantics by the adjacent-scale feature and then adaptively focuses on the more global and meaningful channel information. Extensive experiments and interpretability analysis are made on the Synapse multi-organ dataset (Synapse) and the ACDC cardiac multi-structure dataset (ACDC). Our proposed ASF-LKUNet achieves 88.41% and 89.45% DSC scores on the Synapse and ACDC datasets, respectively, with 17.96M parameters and 29.14 GFLOPs. These results show that our method achieves superior performance with favorable lower complexity against ten competing approaches.ASF-LKUNet is superior to various competing methods and has less model complexity. Code and the trained models have been released on GitHub.

Infectious wrist arthritis complicating acute carpal tunnel syndrome in a child: A CARE-compliant case report.

INTRODUCTION: The objective of this case report is to provide clinical evidence that acute infectious wrist arthritis in children can lead to the rare condition of acute carpal tunnel syndrome (ACTS). This article discusses in detail the characteristics of infectious wrist arthritis complicating ACTS in children in terms of etiology, pathogenic bacteria, treatment modalities, and sequelae to improve the understanding of this disease. PATIENT CONCERNS: A 10-year-old male child presented with a 15-day history of swelling and pain in the left forearm, wrist, and hand. DIAGNOSES: Left-sided infected wrist arthritis complicating ACTS. INTERVENTIONS: The child received emergency surgery and anti-infective treatment combined with regular rehabilitation. OUTCOMES: During the treatment period, the child's wrist pain and swelling gradually improved, and wrist movement was restored compared with the preoperative period. At 6-month follow-up, the activities of the metacarpophalangeal joints of the left hand were close to normal, and the flexion of the left wrist joint was slightly limited. CONCLUSION: In infectious wrist arthritis in children, ACTS is a serious complication that requires aggressive surgical carpal tunnel release to avoid median nerve injury in addition to anti-infective therapy.

On the psychological effects of child-like space design on preschoolers under anesthesia: A qualitative study.

Background and Aims: In this study, a pediatric hospital was selected as the study setting, to investigate the effects of the environment of a pediatric operating room child-friendly space on preschool children under anesthesia. Methods: Interviews were conducted in pediatric hospitals through anesthesia of preschool children. This study randomizing children between the ages of 1 and 7 years (seven males, five females, mean age 3.8 years, standard deviation 0.7). Twelve participants took part in this interview, which was an in-depth interview of preschoolers' perceptions of anesthesia using generalized data analysis to assess young children's perceived preferences and sensitivity to the environment. Preschoolers' preferences for feeling under anesthesia are reflected in four main areas. Results: (1) Interesting and engaging environment. (2) Humanized design, free of fear and unfamiliarity. (3) Caring, patient, and compassionate care by healthcare professionals. (4) High cooperation of the child and good doctor-patient relationship. Conclusion: The key findings of this study may help designers and clinicians to design a toddler-friendly built environment where pediatric hospital child-friendly spaces are designed to benefit their health and maximize their cooperation and psychological recovery.

Influence of static cartoons combined with dynamic virtual environments on preoperative anxiety of preschool-aged children undergoing surgery.

BACKGROUND: Preschoolers become anxious when they are about to undergo anesthesia and surgery, warranting the development of more appropriate and effective interventions. AIM: To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery. METHODS: One hundred and sixteen preschool-aged children were selected and assigned to the drug (n = 37), intervention (n = 40), and control (n = 39) groups. All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation. The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments. The control group received no intervention. The modified Yale Preoperative Anxiety Scale was used to evaluate the children's anxiety level on the day before surgery (T0), before leaving the preoperative preparation room (T1), when entering the operating room (T2), and at anesthesia induction (T3). Compliance during anesthesia induction (T3) was evaluated using the Induction Compliance Checklist (ICC). Changes in mean arterial pressure (MAP), heart rate (HR), and respiratory rate (RR) were also recorded at each time point. RESULTS: The anxiety scores of the three groups increased variously at T1 and T2. At T3, both the drug and intervention groups had similar anxiety scores, both of which were lower than those in the control group. At T1 and T2, MAP, HR, and RR of the three groups increased. The drug and control groups had significantly higher MAP and RR than the intervention group at T2. At T3, the MAP, HR, and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group. Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction (T3), both of which were higher than those of the control group. CONCLUSION: Combining static cartoons with dynamic virtual environments as effective as medication, specifically midazolam, in reducing preoperative anxiety and fear in preschool-aged children. This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.

3D-Printed Stents Loaded with Panax notoginseng Saponin for Promoting Re-endothelialization and Reducing Local Inflammation in the Carotid Artery of Rabbits.

Endovascular treatment (EVT) using stents has become the primary option for severe cerebrovascular stenosis. However, considerable challenges remain to be addressed, such as in-stent restenosis (ISR) and late thrombosis. Many modified stents have been developed to inhibit the hyperproliferation of vascular smooth muscle cells (SMCs) and protect vascular endothelial cells (VECs), thereby reducing such complications. Some modified stents, such as those infused with rapamycin, have improved in preventing acute thrombosis. However, ISR and late thrombosis, which are long-term complications, remain unavoidable. Panax notoginseng saponin (PNS), a traditional Chinese medicine consisting of various compounds, is beneficial in promoting the proliferation and migration of VECs and inhibiting the proliferation of SMCs. Herein, a 3D-printed polycaprolactone (PCL) stent loaded with PNS (PNS-PCL stent) was developed based on a previous study. In vitro studies confirmed that PNS promotes the migration and proliferation of VECs, which were damaged, by increasing the expression levels of microRNA-126, p-AKT, and endothelial nitric oxide synthase. In vivo, the PNS-PCL stents maintained the patency of the carotid artery in rabbits for up to three months, outperforming the PCL stents. The PNS-PCL stents may present a new solution for the EVT of cerebrovascular atherosclerotic stenosis in the future.

Drought-induced cell wall degradation in the base of pedicel is associated with accelerated cotton square shedding.

Drought significantly impacts cotton square (flower buds with bracts) shedding, directly affecting yield. To address the internal physiological mechanisms of drought affecting cotton square shedding, a polyethylene glycol-simulated drought study was conducted with Dexiamian 1 and Yuzaomian 9110 to investigate cell wall degradation changes in the base of pedicel where the detachment of cotton square takes place, and its relationship with cotton square shedding. Results revealed significant decreases in cellulose, hemicellulose, and pectin contents in the base of square pedicel, leading to cell wall degradation and consequent square shedding. Furthermore, drought stress exacerbated the hydrolysis of cellulose and pectin in the base of pedicel, although not hemicellulose, resulting in more noticeable alterations in the morphology and structure of the base of pedicel, such as more significant degradation in the epidermis, cortex, and phloem. Regarding the cellulose hydrolysis, drought mainly increased the expression of genes ß-glucosidase (GhBG1) and endoglucanase (GhEG1), and the activity of ß-glucosidase and endoglucanase in the base of pedicel, promoting the conversion of cellulose to cellobiose, and eventually glucose. Regarding the pectin hydrolysis, drought significantly enhanced the expression of the gene pectin methylase (GhPE1), thereby accelerating pectin hydrolysis to generate polygalacturonic acid. Additionally, drought increased the expression of genes pectin lyase (GhPL1) and polygalacturonase (GhPG1), as well as the activity of pectin lyase, which further accelerated the hydrolysis of polygalacturonic acid into galacturonic acid. These findings suggest that drought mainly promotes cellulose and pectin hydrolysis in the base of pedicel, hastening cell wall degradation and final cotton square shedding.

SaE-GBLS: an effective self-adaptive evolutionary optimized graph-broad model for EEG-based automatic epileptic seizure detection.

Introduction: Epilepsy is a common neurological condition that affects a large number of individuals worldwide. One of the primary challenges in epilepsy is the accurate and timely detection of seizure. Recently, the graph regularized broad learning system (GBLS) has achieved superior performance improvement with its flat structure and less time-consuming training process compared to deep neural networks. Nevertheless, the number of feature and enhancement nodes in GBLS is predetermined. These node settings are also randomly selected and remain unchanged throughout the training process. The characteristic of randomness is thus more easier to make non-optimal nodes generate, which cannot contribute significantly to solving the optimization problem. Methods: To obtain more optimal nodes for optimization and achieve superior automatic detection performance, we propose a novel broad neural network named self-adaptive evolutionary graph regularized broad learning system (SaE-GBLS). Self-adaptive evolutionary algorithm, which can construct mutation strategies in the strategy pool based on the experience of producing solutions for selecting network parameters, is incorporated into SaE-GBLS model for optimizing the node parameters. The epilepsy seizure is automatic detected by our proposed SaE-GBLS model based on three publicly available EEG datasets and one private clinical EEG dataset. Results and discussion: The experimental results indicate that our suggested strategy has the potential to perform as well as current machine learning approaches.

The characterization of metabolic changes in adipose tissues and muscles due to different exercise intensities by Dixon in healthy young men.

PURPOSE: To delineate the alterations in adipose and muscle tissue composition and functionality among healthy young men across varying exercise intensities, which help to elucidate the impact of exercise intensity on weight management and inform fitness planning. METHOD: 3D Dixon MRI scans were performed on the neck and supraclavicular area in 10 high-intensity exercises (HIE) athletes, 20 moderate intensity exercises (MIE) athletes and 19 low-intensity exercises non-athlete male controls (NCM). Twelve imaging parameters, including the total volume of muscle, white adipose tissue (WAT), brown adipose tissue (BAT), and the mean fat-water fraction (FWF) within these tissues. Additionally, ratios of BAT or WAT to total fat (BATr or WATr) and the proportions of muscle, BAT, or WAT to total tissue volume (Musp, BATp, and WATp) were calculated. Parameters were compared across groups and correlated with Body Mass Index (BMI), waistline, and hipline. RESULTS: The HIE group exhibited the highest total muscle (totalMUS) and brown adipose tissue (totalBAT) volumes among the three groups. Conversely, the NCM group had significantly higher fwfFAT and fwfBAT values. The MUSp was higher in the HIE and MIE groups compared to NCM, while the BATp and WATp were lower. Furthermore, the BATr in HIE and MIE groups were higher than NCM group while the WATr were lower. Significant linear relationships were observed between totalBAT, totalWAT, MUSp, BATr, fwfFAT, and BMI, waistline (P < 0.05) across all groups. CONCLUSIONS: MIE is sufficient for the purpose of weight control, While HIE helps to further increase the muscle mass. All three physical indexes were significantly associated with the image parameters, with waistline emerging as the most effective indicator for detecting metabolic changes across all groups.

Reactive Oxygen Species Modulate Th17/Treg Balance in Chlamydia psittaci Pneumonia via NLRP3/IL-1ß/Caspase-1 Pathway Differentiation.

Chlamydia psittaci pneumonia (CPP) is a lung disease caused by the infection with the Chla-mydia psittaci bacterium, which can lead to severe acute respiratory distress syndrome and systemic symptoms. This study explored the specific mechanisms underlying the impact of reactive oxygen species (ROS) on the Th17/Treg balance in CPP. The levels of ROS and the differentiation ratio of Th17/Treg in the peripheral blood of healthy individuals and CPP patients were measured using ELISA and flow cytometry, respectively. The association between the ROS levels and Th17/Treg was assessed using Pearson correlation analysis. The ROS levels and the Th17/Treg ratio were measured in CD4+ T cells following H2O2 treatment and NLRP3 inhibition. The effects of H2O2 treatment and NLRP3 inhibition on the NLRP3/IL-1ß/caspase-1 pathway were observed using immunoblotting. Compared to the healthy group, the CPP group exhibited increased levels of ROS in the peripheral blood, an elevated ratio of Th17 differentiation, and a decreased ratio of Treg differentiation. ROS levels were positively correlated with the Th17 cell proportion but negatively correlated with the Treg cell proportion. The ROS levels and NLRP3/IL-1ß/caspase-1 expression were up-regulated in CD4+ T cells after H2O2 treatment. Furthermore, there was an increase in Th17 differentiation and a decrease in Treg differentiation. Conversely, the NLRP3/IL-1ß/caspase-1 pathway inhibition reversed the effects of H2O2 treatment, with no significant change in the ROS levels. ROS regulates the Th17/Treg balance in CPP, possibly through the NLRP3/IL-1ß/caspase-1 pathway. This study provides a new perspective on the development of immunotherapy for CPP.

Partial root-zone drying irrigation improves intrinsic water-use efficiency and maintains high photosynthesis by uncoupling stomatal and mesophyll conductance in cotton leaves.

Partial root-zone drying irrigation (PRD) can improve water-use efficiency (WUE) without reductions in photosynthesis; however, the mechanism by which this is attained is unclear. To amend that, PRD conditions were simulated by polyethylene glycol 6000 in a root-splitting system and the effects of PRD on cotton growth were studied. Results showed that PRD decreased stomatal conductance (gs) but increased mesophyll conductance (gm). Due to the contrasting effects on gs and gm, net photosynthetic rate (AN) remained unaffected, while the enhanced gm/gs ratio facilitated a larger intrinsic WUE. Further analyses indicated that PRD-induced reduction of gs was related to decreased stomatal size and stomatal pore area in adaxial and abaxial surface which was ascribed to lower pore length and width. PRD-induced variation of gm was ascribed to the reduced liquid-phase resistance, due to increases in chloroplast area facing to intercellular airspaces and the ratio of chloroplast surface area to total mesophyll cell area exposed to intercellular airspaces, as well as to decreases in the distance between cell wall and chloroplast, and between adjacent chloroplasts. The above results demonstrate that PRD, through alterations to stomatal and mesophyll structures, decoupled gs and gm responses, which ultimately increased intrinsic WUE and maintained AN.

Assessing the Influence of B-US, CDFI, SE, and Patient Age on Predicting Molecular Subtypes in Breast Lesions Using Deep Learning Algorithms.

OBJECTIVES: Our study aims to investigate the impact of B-mode ultrasound (B-US) imaging, color Doppler flow imaging (CDFI), strain elastography (SE), and patient age on the prediction of molecular subtypes in breast lesions. METHODS: Totally 2272 multimodal ultrasound imaging was collected from 198 patients. The ResNet-18 network was employed to predict four molecular subtypes from B-US imaging, CDFI, and SE of patients with different ages. All the images were split into training and testing datasets by the ratio of 80%:20%. The predictive performance on testing dataset was evaluated through 5 metrics including mean accuracy, precision, recall, F1-scores, and confusion matrix. RESULTS: Based on B-US imaging, the test mean accuracy is 74.50%, the precision is 74.84%, the recall is 72.48%, and the F1-scores is 0.73. By combining B-US imaging with CDFI, the results were increased to 85.41%, 85.03%, 85.05%, and 0.84, respectively. With the integration of B-US imaging and SE, the results were changed to 75.64%, 74.69%, 73.86%, and 0.74, respectively. Using images from patients under 40 years old, the results were 90.48%, 90.88%, 88.47%, and 0.89. When images from patients who are above 40 years old, they were changed to 81.96%, 83.12%, 80.5%, and 0.81, respectively. CONCLUSION: Multimodal ultrasound imaging can be used to accurately predict the molecular subtypes of breast lesions. In addition to B-US imaging, CDFI rather than SE contribute further to improve predictive performance. The predictive performance is notably better for patients under 40 years old compared with those who are 40 years old and above.

Oxygen-Independent Radiodynamic Therapy: Radiation-Boosted Chemodynamics for Reprogramming the Tumor Immune Environment and Enhancing Antitumor Immune Response.

Radiodynamic therapy (RDT) has emerged as a promising modality for cancer treatment, offering notable advantages such as deep tissue penetration and radiocatalytic generation of oxygen free radicals. However, the oxygen-dependent nature of RDT imposes limitations on its efficacy in hypoxic conditions, particularly in modulating and eliminating radioresistant immune suppression cells. A novel approach involving the creation of a "super" tetrahedron polyoxometalate (POM) cluster, Fe12-POM, has been developed for radiation boosted chemodynamic catalysis to enable oxygen-independent RDT in hypoxic conditions. This nanoscale cluster comprises four P2W15 units functioning as energy antennas, while the Fe3 core serves as an electron receptor and catalytic center. Under X-ray radiation, a metal-to-metal charge transfer phenomenon occurs between P2W15 and the Fe3 core, resulting in the valence transition of Fe3+ to Fe2+ and a remarkable 139-fold increase in hydroxyl radical generation compared to Fe12-POM alone. The rapid generation of hydroxyl radicals, in combination with PD-1 therapy, induces a reprogramming of the immune environment within tumors. This reprogramming is characterized by upregulation of CD80/86, downregulation of CD163 and FAP, as well as the release of interferon-γ and tumor necrosis factor-α. Consequently, the occurrence of abscopal effects is facilitated, leading to significant regression of both local and distant tumors in mice. The development of oxygen-independent RDT represents a promising approach to address cancer recurrence and improve treatment outcomes.

AMS-U-Net: automatic mass segmentation in digital breast tomosynthesis via U-Net.

Purpose: The objective of this study was to develop a fully automatic mass segmentation method called AMS-U-Net for digital breast tomosynthesis (DBT), a popular breast cancer screening imaging modality. The aim was to address the challenges posed by the increasing number of slices in DBT, which leads to higher mass contouring workload and decreased treatment efficiency. Approach: The study used 50 slices from different DBT volumes for evaluation. The AMS-U-Net approach consisted of four stages: image pre-processing, AMS-U-Net training, image segmentation, and post-processing. The model performance was evaluated by calculating the true positive ratio (TPR), false positive ratio (FPR), F-score, intersection over union (IoU), and 95% Hausdorff distance (pixels) as they are appropriate for datasets with class imbalance. Results: The model achieved 0.911, 0.003, 0.911, 0.900, 5.82 for TPR, FPR, F-score, IoU, and 95% Hausdorff distance, respectively. Conclusions: The AMS-U-Net model demonstrated impressive visual and quantitative results, achieving high accuracy in mass segmentation without the need for human interaction. This capability has the potential to significantly increase clinical efficiency and workflow in DBT for breast cancer screening.

Drought decreases cotton fiber strength by altering sucrose flow route.

The potential mechanisms by which drought restricts cotton fiber cell wall synthesis and fiber strength are still not fully understood. Herein, drought experiments were conducted using two cultivars of upland cotton (Gossypium hirsutum), Dexiamian 1 (drought-tolerant) and Yuzaomian 9110 (drought-sensitive). Results showed that drought notably reduced sucrose efflux from cottonseed coats to fibers by down-regulating the expression of GhSWEET10 and GhSWEET15 in outer cottonseed coats, leading to enhanced sucrose accumulation in cottonseed coats but decreased sucrose accumulation in fibers. Within cotton fibers, drought restricted the hydrolysis of sucrose to uridine-5'-diphosphoglucose by suppressing sucrose synthase activity, and drought favored the conversion of uridine-5'-diphosphoglucose to ß-1,3-glucan rather than cellulose by up-regulating GhCALS5. Hence, cellulose content was reduced, which was the main reason for the decreased fiber strength under drought. Moreover, drought promoted lignin synthesis by up-regulating the expression of Gh4CL4, GhPAL9, GhCCR5, GhCAD11, and GhCOMT6, which partly offset the negative influence of reduced cellulose content on fiber strength. Compared with Yuzaomian 9110, the drought-tolerance of Dexiamian 1 was evidenced by the following under drought conditions: (i) greater sucrose flow from seedcoat to fiber, (ii) less ß-1,3-glucan accumulation, and (iii) more lignin biosynthesis. Overall, this study provides new insights into the mechanism of reduced cotton fiber strength induced by drought.