Poor condyle position after mandibular reconstruction and a classification system for patients with "VSCU" based on computed tomography: a cross-sectional study with retrospective data collection.

Background: Although the application of vascularized free bone muscle flap to reconstruct the mandible has become a standardized approach for mandible reconstruction, the results of its reconstruction are not always satisfactory. The purpose of this study was to identify the types of mandibular and condylar defects by analyzing the unsatisfactory cases of mandibular reconstruction in clinical practice, and to provide some clinical experience of reconstruction. Methods: Our study retrospectively analyzed 364 patients who underwent mandibular resection and vascularized free bone flap reconstruction of the mandible and temporomandibular joint (TMJ). We innovatively proposed a "VSCU" classification system (V: vertical position, S: sagittal position, C: coronal position, U: condylar resection is not required) by analyzing computed tomography (CT) scans of mandibular branches and TMJs. Results: In all, 221 cases of free iliac muscle flap and 143 cases of fibula muscle flap were included in this study, of which 23 cases had unsatisfactory results after TMJ reconstruction. We classified 23 patients with unsatisfactory mandibular reconstruction according to the "VSCU" classification system. The most common type was U + V + SfC (n=8), followed by V - SfC + U + (n=4), V - s + C + U + (n=3), V - sbcou - (n=3), V - SBC + U + (n=2), V - s + C + U - (n=1). The most common classification was insufficient mandibular rami length, followed by condylar sagittal anteriorization. There was no significant change in the position of condyle on the healthy side during mandibular reconstruction involving condyle. P1 on the affected side was 52.28±4.17 mm before operation and 58.94±5.65 mm after operation, P<0.01; P2 was 12.83±3.49 mm before operation and 24.90±7.15 mm after operation. S2 was 4.54±2.84 mm before operation and 19.10±8.54 mm after operation. A2 was 11.46±3.35 mm before operation and 24.15±8.29 mm after operation. The P values were all less than 0.01, and the differences were statistically significant. Conclusions: We propose to use the "VSCU" classification system for accurate 3-dimensional (3D) analysis and positioning, and then obtain accurate models through computer-aided design and manufacturing (CAD/CAM), which can reduce the occurrence of poor reconstruction effect and unreasonable joint position, and is worthy of clinical promotion.

Dual-plasmonic CuS@Au heterojunctions synergistic enhanced photothermal and colorimetric dual signal for sensitive multiplexed LFIA.

Multiplexed immunodetection, which achieves qualitative and quantitative outcomes for multiple targets in a single-run process, provides more sufficient results to guarantee food safety. Especially, lateral flow immunoassay (LFIA), with the ability to offer multiple test lines for analytes and one control line for verification, is a forceful candidate in multiplexed immunodetection. Nevertheless, given that single-signal mode is incredibly vulnerable to interference, further efforts should be engrossed on the combination of multiplexed immunodetection and multiple signals. Photothermal signal has sparked significant excitement in designing immunosensors. In this work, by optimizing and comparing the amount of gold, CuS@Au heterojunctions (CuS@Au HJ) were synthesized. The dual-plasmonic metal-semiconductor hybrid heterojunction exhibits a synergistic photothermal performance by increasing light absorption and encouraging interfacial electron transfer. Meanwhile, the colorimetric property is synergistic enhanced, which is conducive to reduce the consumption of antibodies and then improve assay sensitivity. Therefore, CuS@Au HJ are suitable to be constructed in a dual signal and multiplexed LFIA (DSM-LFIA). T-2 toxin and deoxynivalenol (DON) were used as model targets for the simulated multiplex immunoassay. In contrast to colloidal gold-based immunoassay, the built-in sensor has increased sensitivity by ≈ 4.42 times (colorimetric mode) and ≈17.79 times (photothermal mode) for DON detection and by ≈ 1.75 times (colorimetric mode) and ≈13.09 times (photothermal mode) for T-2 detection. As a proof-of-concept application, this work provides a reference to the design of DSM-LFIA for food safety detection.

Clinical study of the posterior gastric artery and the lymph nodes around it in patients with gastric cancer.

OBJECTIVES: This study aims to gather and analyze the anatomical characteristics of the posterior gastric artery (PGA), investigate the presence and metastasis of lymph nodes around the PGA in patients with gastric cancer. Additionally, the study aims to analyze the relationship between the PGA and its surrounding lymph nodes and the clinicopathological features of patients with gastric cancer. METHODS: This study consisted of a cross-sectional analysis of data from 52 patients with gastric cancer who underwent total or proximal gastrectomy at the Department of Gastrointestinal Surgery, First Affiliated Hospital of Dalian Medical University, between January 2020 and November 2022. Intraoperative exploration was performed to determine the presence of the PGA, and patients with the PGA were assessed for relevant anatomical characteristics, including the length of the PGA and the distance from the root of the PGA to the celiac trunk. Dissection of lymph nodes around the PGA was also performed. Statistical methods were employed to describe and analyze the data regarding the presence of the PGA, as well as the presence and metastasis of the lymph nodes around the PGA. Additionally, the study identified clinicopathological factors associated with these conditions. RESULTS: The PGA was identified in 39 (75.0%) out of 52 patients with gastric cancer, exhibiting a mean PGA length of 3.5 ± 0.8 cm and a mean distance from the root of the PGA to the celiac trunk of 6.7 ± 1.7 cm. Among the 39 patients who underwent dissection of lymph nodes around the PGA, 36 lymph nodes around the PGA were detected in 20 patients. Analysis of factors associated with the presence of lymph nodes around the PGA revealed a significant correlation with the macroscopic type of the tumor and the total number of dissected lymph nodes (P = 0.007 and P = 0.022, respectively), with a larger number of total dissected lymph nodes being an independent factor (OR = 1.105, 95%CI: 1.019-1.199, P = 0.016). Furthermore, analysis of risk factors for metastasis of the lymph nodes around the PGA demonstrated that the total number of metastatic lymph nodes, No.3 lymph node metastasis, and No.11 lymph node metastasis were associated with metastasis of the lymph nodes around the PGA (P = 0.043, P = 0.028, and P = 0.020, respectively). CONCLUSION: The PGA exhibits a high incidence. It is essential to carefully identify the PGA during procedures involving the PGA and consider appropriate preservation or disconnection of this vessel. The presence of lymph nodes around the PGA is not an isolated occurrence. Gastric cancer can result in metastasis of the lymph nodes around the PGA. Although the overall risk of metastasis of the lymph nodes around the PGA is low in patients with gastric cancer, it increases in the presence of conditions such as No.3 lymph node metastasis, No.11 lymph node metastasis, advanced tumor stage, and extensive metastases in other regional lymph nodes.

Wireless Technologies in Flexible and Wearable Sensing: from Materials Design, System Integration to Applications.

Wireless and wearable sensors attract considerable interest in personalized healthcare by providing a unique approach for remote, non-contact, and continuous monitoring of various health-related signals without interference with daily life. Recent advances in wireless technologies and wearable sensors have promoted practical applications due to their significantly improved characteristics, such as reduction in size and thickness, enhancement in flexibility and stretchability, and improved conformability to the human body. Currently, most researches focus on active materials and structural designs for wearable sensors, with just a few exceptions reflecting on the technologies for wireless data transmission. This review provides a comprehensive overview of the state-of-the-art wireless technologies and related studies on empowering wearable sensors. The emerging functional nanomaterials utilized for designing unique wireless modules are highlighted, which include metals, carbons, and MXenes. Additionally, the review outlines the system-level integration of wireless modules with flexible sensors, spanning from novel design strategies for enhanced conformability to efficient transmitting data wirelessly. Furthermore, the review introduces representative applications for remote and non-invasive monitoring of physiological signals through on-skin and implantable wireless flexible sensing systems. Finally, the challenges, perspectives, and unprecedented opportunities for wireless and wearable sensors are discussed. This article is protected by copyright. All rights reserved.

Li Promoting Long Afterglow Organic Light-Emitting Transistor for Memory Optocoupler Module.

The artificial brain is conceived as advanced intelligence technology, capable to emulate in-memory processes occurring in the human brain by integrating synaptic devices. Within this context, improving the functionality of synaptic transistors to increase information processing density in neuromorphic chips is a major challenge in this field. In this article, Li-ion migration promoting long afterglow organic light-emitting transistors, which display exceptional postsynaptic brightness of 7000 cd m-2 under low operational voltages of 10 V is presented. The postsynaptic current of 0.1 mA operating as a built-in threshold switch is implemented as a firing point in these devices. The setting-condition-triggered long afterglow is employed to drive the photoisomerization process of photochromic molecules that mimic neurotransmitter transfer in the human brain for realizing a key memory rule, that is, the transition from long-term memory to permanent memory. The combination of setting-condition-triggered long afterglow with photodiode amplifiers is also processed to emulate the human responding action after the setting-training process. Overall, the successful integration in neuromorphic computing comprising stimulus judgment, photon emission, transition, and encoding,  to emulate the complicated decision tree of the human brain is demonstrated.

Creating augmented reality-based experiences for aviation weather training: Challenges, opportunities, and design implications for 3D authoring.

This paper examines opportunities and challenges of integrating augmented reality (AR) into education and investigates requirements to enable instructors to author AR educational experiences. Although AR technology is recognised for its potential in educational enhancement, it poses challenges for instructors creating AR-based experiences due to their limited digital skills and the complexity of 3D authoring tools. Semi-structured interviews with 17 aviation instructors identified current pedagogical approaches, gaps, and potential applications of AR in aviation weather education. Additionally, results highlighted the benefits of AR and obstacles to its integration into education, followed by outlining design priorities and user needs for educational AR authoring. For AR authoring toolkit development, this study recommended incorporating interactive AR lesson modules, early development of user requirements, and prebuilt AR modules. Findings will guide the development of a 3D authoring toolkit for non-technologist instructors, enabling wider AR use in aviation weather education and other educational fields.

Research interviews with aviation instructors were conducted to derive design implications of AR authoring toolkits for non-technologist instructors. Key findings highlighted gaps in aviation weather education, potential AR applications, and barriers to AR in education. Design recommendations emphasised incorporating interactive AR lesson modules, initial user requirements, and prebuilt AR modules.

Deep-learning-based super-resolution for accelerating chemical exchange saturation transfer MRI.

Chemical exchange saturation transfer (CEST) MRI is a molecular imaging tool that provides physiological information about tissues, making it an invaluable tool for disease diagnosis and guided treatment. Its clinical application requires the acquisition of high-resolution images capable of accurately identifying subtle regional changes in vivo, while simultaneously maintaining a high level of spectral resolution. However, the acquisition of such high-resolution images is time consuming, presenting a challenge for practical implementation in clinical settings. Among several techniques that have been explored to reduce the acquisition time in MRI, deep-learning-based super-resolution (DLSR) is a promising approach to address this problem due to its adaptability to any acquisition sequence and hardware. However, its translation to CEST MRI has been hindered by the lack of the large CEST datasets required for network development. Thus, we aim to develop a DLSR method, named DLSR-CEST, to reduce the acquisition time for CEST MRI by reconstructing high-resolution images from fast low-resolution acquisitions. This is achieved by first pretraining the DLSR-CEST on human brain T1w and T2w images to initialize the weights of the network and then training the network on very small human and mouse brain CEST datasets to fine-tune the weights. Using the trained DLSR-CEST network, the reconstructed CEST source images exhibited improved spatial resolution in both peak signal-to-noise ratio and structural similarity index measure metrics at all downsampling factors (2-8). Moreover, amide CEST and relayed nuclear Overhauser effect maps extrapolated from the DLSR-CEST source images exhibited high spatial resolution and low normalized root mean square error, indicating a negligible loss in Z-spectrum information. Therefore, our DLSR-CEST demonstrated a robust reconstruction of high-resolution CEST source images from fast low-resolution acquisitions, thereby improving the spatial resolution and preserving most Z-spectrum information.

Celecoxib attenuates hindlimb unloading-induced muscle atrophy via suppressing inflammation, oxidative stress and ER stress by inhibiting STAT3.

Improving inflammation may serve as useful therapeutic interventions for the hindlimb unloading-induced disuse muscle atrophy. Celecoxib is a selective non-steroidal anti-inflammatory drug. We aimed to determine the role and mechanism of celecoxib in hindlimb unloading-induced disuse muscle atrophy. Celecoxib significantly attenuated the decrease in soleus muscle mass, hindlimb muscle function and the shift from slow- to fast-twitch muscle fibers caused by hindlimb unloading in rats. Importantly, celecoxib inhibited the increased expression of inflammatory factors, macrophage infiltration in damaged soleus muscle. Mechanistically, Celecoxib could significantly reduce oxidative stress and endoplasmic reticulum stress in soleus muscle of unloaded rats. Furthermore, celecoxib inhibited muscle proteolysis by reducing the levels of MAFbx, MuRF1, and autophagy related proteins maybe by inhibiting the activation of pro-inflammatory STAT3 pathway in vivo and in vitro. This study is the first to demonstrate that celecoxib can attenuate disuse muscle atrophy caused by hindlimb unloading via suppressing inflammation, oxidative stress and endoplasmic reticulum stress probably, improving target muscle function and reversing the shift of muscle fiber types by inhibiting STAT3 pathways-mediated inflammatory cascade. This study not only enriches the potential molecular regulatory mechanisms, but also provides new potential therapeutic targets for disuse muscle atrophy.

Algorithms for classification of sequences and segmentation of prostate gland: an external validation study.

OBJECTIVES: The aim of the study was to externally validate two AI models for the classification of prostate mpMRI sequences and segmentation of the prostate gland on T2WI. MATERIALS AND METHODS: MpMRI data from 719 patients were retrospectively collected from two hospitals, utilizing nine MR scanners from four different vendors, over the period from February 2018 to May 2022. Med3D deep learning pretrained architecture was used to perform image classification,UNet-3D was used to segment the prostate gland. The images were classified into one of nine image types by the mode. The segmentation model was validated using T2WI images. The accuracy of the segmentation was evaluated by measuring the DSC, VS,AHD.Finally,efficacy of the models was compared for different MR field strengths and sequences. RESULTS: 20,551 image groups were obtained from 719 MR studies. The classification model accuracy is 99%, with a kappa of 0.932. The precision, recall, and F1 values for the nine image types had statistically significant differences, respectively (all P < 0.001). The accuracy for scanners 1.436 T, 1.5 T, and 3.0 T was 87%, 86%, and 98%, respectively (P < 0.001). For segmentation model, the median DSC was 0.942 to 0.955, the median VS was 0.974 to 0.982, and the median AHD was 5.55 to 6.49 mm,respectively.These values also had statistically significant differences for the three different magnetic field strengths (all P < 0.001). CONCLUSION: The AI models for mpMRI image classification and prostate segmentation demonstrated good performance during external validation, which could enhance efficiency in prostate volume measurement and cancer detection with mpMRI. CLINICAL RELEVANCE STATEMENT: These models can greatly improve the work efficiency in cancer detection, measurement of prostate volume and guided biopsies.

Hemodynamic Effects of Tortuosity and Stenosis in Superficial Temporal Artery-Middle Cerebral Artery Bypass for Moyamoya Disease.

BACKGROUND: Superficial temporal artery (STA)-middle cerebral artery (MCA) bypass surgery has been widely adopted in treating moyamoya disease (MMD). Geometric variations including high tortuosity and stenosis exist in many cases, but the hemodynamic effects have not been comprehensively evaluated. We aim to evaluate the hemodynamic effects of bypass geometry variations based on patient-specific data. METHODS: In total, 17 patients with MMD who underwent STA-MCA bypass surgery with highly tortuous bypass geometry were included. For each patient, the original 3-dimensional structure of STA-MCA bypass was reconstructed from clinical imaging data. The bypass structure was virtually improved by removing the tortuosity and stenosis. Computational fluid dynamics simulation was performed on both bypass structures under identical patient-specific condition. The simulated hemodynamic parameters of the bypass and its distal branches were compared between the original and virtually improved bypass geometries in all cases using paired t-test or Wilcoxon signed-rank test. The changes of hemodynamic parameters were compared between the cases with and without mild-to-moderate stenosis (44.0-70.3% in diameter) in the bypass using t-test or Mann-Whitney U test. RESULTS: The virtual improvement of bypass geometry significantly increased the flow rate of the bypass and its distal branches (P < 0.05) and decreased the transcranial flow resistance (P < 0.05). The hemodynamic changes in cases with stenosis removal were significantly greater than those without stenosis (P < 0.05). CONCLUSIONS: High tortuosity and stenosis can significantly change the hemodynamics of STA-MCA bypass, and the optimization of bypass geometry deserves further consideration.

Effect of Growth Stage on Nutrition, Fermentation Quality, and Microbial Community of Semidry Silage from Forage Soybean.

Soybean (Glycine max (Linn.) Merr.) is highly suitable as animal feed. The silage quality and microbial characteristics of soybean silage are still unclear. Forage soybean (HN389), at six different growth stages (R2-R7), were used as experimental materials to investigate the changes in fermentation, nutritional quality, and microbial characteristics of semidry silage after 0, 7, 14, 30, and 45 d. As the growth period extended, the content of crude protein (CP) and crude fat (EE) gradually increased, while the neutral detergent fiber (NDF) and the acid detergent fiber (ADF) content decreased. The pH value also decreased gradually with fermentation time, accompanied by increases in the proportion of ammonia-N and the content of lactic acid (LA) and acetic acid (AA). In addition, competitive inhibition was observed in the microbial fermentation. With the process of ensiling, Lactobacillus became the dominant bacterial species. The results indicate that the most active stage of fermentation during ensiling occurred within the first 7 days, the fermentation and nutritional quality of the soybean forage were improved, and the optimal mowing stage was the grain stage. Comparison of the microbial abundance showed that all microorganisms entered a stable stage at 30 days of silage. After storage, the dominant bacteria were Lactobacillus, Enterobacter, and Pantoea.

Deep learning-based radiomics model from pretreatment ADC to predict biochemical recurrence in advanced prostate cancer.

Purpose: To develop deep-learning radiomics model for predicting biochemical recurrence (BCR) of advanced prostate cancer (PCa) based on pretreatment apparent diffusion coefficient (ADC) maps. Methods: Data were collected retrospectively from 131 patients diagnosed with advanced PCa, randomly divided into training (n = 93) and test (n = 38) datasets. Pre-treatment ADC images were segmented using a pre-trained artificial intelligence (AI) model to identify suspicious PCa areas. Three models were constructed, including a clinical model, a conventional radiomics model and a deep-radiomics model. The receiver operating characteristic (ROC), precision-recall (PR) curve and decision curve analysis (DCA) were used to assess predictive performance in test dataset. The net reclassification index (NRI) and integrated discrimination improvement (IDI) were employed to compare the performance enhancement of the deep-radiomics model in relation to the other two models. Results: The deep-radiomics model exhibited a significantly higher area under the curve (AUC) of ROC than the other two (P = 0.033, 0.026), as well as PR curve (AUC difference 0.420, 0.432). The DCA curve demonstrated superior performance for the deep-radiomics model across all risk thresholds than the other two. Taking the clinical model as reference, the NRI and IDI was 0.508 and 0.679 for the deep-radiomics model with significant difference. Compared with the conventional radiomics model, the NRI and IDI was 0.149 and 0.164 for the deep-radiomics model without significant difference. Conclusion: The deep-radiomics model exhibits promising potential in predicting BCR in advanced PCa, compared to both the clinical model and the conventional radiomics model.

Added value of DCER-features to clinicopathologic model for predicting metachronous metastases in rectal cancer patients.

RATIONALE AND OBJECTIVES: The study aimed to investigate whether dynamic contrast-enhanced MRI parameters and preoperative radiological features (DCER-Features) add value to the clinicopathologic model for predicting metachronous metastases in rectal cancer patients. MATERIALS AND METHODS: From January 2014 to December 2020, 859 patients in the PACS system were retrospectively screened. Of the initial 722 patients with surgically confirmed rectal cancer and no synchronous metastases, 579 patients were excluded for various reasons such as lack of clinicopathological or radiological information. 143 patients were finally included in this study. And 73 Patients of them developed metachronous metastasis within five years. After stepwise multiple regression analyses, we constructed three distinct models. Model 1 was developed solely based on clinicopathological factors, and model 2 incorporated clinicopathological characteristics along with DCE-MRI parameters. Finally, model 3 was built on all available factors, including clinicopathological characteristics, DCE-MRI parameters, and radiological features based on rectal magnetic resonance imaging. The radiological features assessed in this study encompass tumor imaging staging, location, and circumferential resection margin (CRM) for primary tumors, as well as the number of visible lymph nodes and suspected metastatic lymph nodes. Receiver operating characteristic (ROC) and decision curve analysis (DCA) were conducted to evaluate whether the diagnostic efficiency was improved. RESULTS: The performance of model 3 (including clinicopathologic characteristics and DCER-Features) was the best (AUC: 0.856, 95% CI 0.778-0.886), whereas it was 0.796 (95% CI 0.720-0.828) for model 2 and 0.709 (95% CI 0.612-0.778) for model 1 (DeLong test: model 1 vs model 2, p = 0.004; model 2 vs model 3, p = 0.037; model 1 vs model 3, p < 0.001). The decision curves indicated that the net benefit of model 3 was higher than the other two models at each referral threshold. The calibration plot of the three models revealed an excellent predictive accuracy. CONCLUSION: This study suggests that DCER-Features have added value for the clinicopathological model to predict metachronous metastasis in patients with rectal cancers.

Elevated Plasma Lipoprotein(a) Level and Atherosclerotic Cardiovascular Disease Risks: A Large Clinical Retrospective Study.

Patients with well-controlled low-density lipoprotein cholesterol (LDL-C) levels still suffer from the progress of the atherosclerotic cardiovascular disease (ASCVD) and can develop adverse outcomes. We conducted this study to analyze the relationship between elevated lipoprotein(a) [Lp(a)] levels and ASCVD risk. We enrolled 8070 patients in the ASCVD group and 440 participants in the non-ASCVD group [median age of 60 years; 6376 (74.9%) were male]. Multivariate logistic regression models were used to identify the relationships between the lipids and ASCVD. These models showed that the Lp(a) level was a significant independent risk factor for ASCVD [odds ratio (OR) = 1.025, confidence interval (CI) = 1.020-1.029, P < .001]. The different categories analysis showed the OR of the high Lp(a)/low LDL-C group was 9.612 [CI = 6.206-14.887], P < .001. Our study demonstrated that elevated Lp(a) levels were associated with the increased ASCVD risk. Also, the patients with low LDL-C but high Lp(a) levels still had a higher risk of developing ASCVD than the low Lp(a)/high LDL-C group. In addition, elevated Lp(a) levels were associated with a higher ASCVD risk in males, hypertensive, and diabetic patients.

Quantitative measurement of the ureter on three-dimensional magnetic resonance urography images using deep learning.

BACKGROUND: Accurate measurement of ureteral diameters plays a pivotal role in diagnosing and monitoring urinary tract obstruction (UTO). While three-dimensional magnetic resonance urography (3D MRU) represents a significant advancement in imaging, the traditional manual methods for assessing ureteral diameters are characterized by labor-intensive procedures and inherent variability. In the realm of medical image analysis, deep learning has led to a paradigm shift, yet the development of a comprehensive automated tool for the precise segmentation and measurement of ureters in MR images is an unaddressed challenge. PURPOSE: The ureter was quantitatively measured on 3D MRU images using a deep learning model. METHODS: A retrospective cohort of 445 3D MRU scans (443 patients, 52 ± 18 years; 217 female patients) was collected and split into training, validation, and internal testing cohorts. A 3D V-Net model was trained for urinary tract segmentation, and a post-processing algorithm was developed for ureteral measurements. The accuracy of the segmentation was evaluated using the Dice similarity coefficient (DSC) and volume intraclass correlation coefficient (ICC), with ground truth segmentations provided by experienced radiologists. The external cohort comprised 50 scans (50 patients, 55 ± 21 years; 30 female patients), and the model-predicted ureteral diameter measurements were compared with manual measurements to assess system performance. The various diameter parameters of ureter among the different measurement methods (ground truth, auto-segmentation with automatic diameter extraction, and manual segmentation with automatic diameter extraction) were assessed with Friedman tests and post hoc Dunn test. The effectiveness of the UTO diagnosis was assessed by receiver operating characteristic (ROC) curves and their respective areas under the curve (AUC) between different methods. RESULTS: In both the internal test and external cohorts, the mean DSC values for bilateral ureters exceeded 0.70. The ICCs for the bilateral ureter volume obtained by comparing the model and manual segmentation were all greater than 0.96 (p  < â€¯0.05), except for the right ureter in the internal test cohort, for which the ICC was 0.773 (p  < â€¯0.05). The mean DSCs for interobserver and intraobserver reliability were all above 0.97. The maximum diameter of the ureter exhibited no statistically significant differences either in the dilated (p = 0.08) or in the non-dilated (p = 0.32) ureters across the three measurement methods. The AUCs of ground truth, auto-segmentation with automatic diameter extraction, and manual segmentation with automatic diameter extraction in diagnosing UTO were 0.988 (95% CI: 0.934, 1.000), 0.961 (95% CI: 0.893, 0.991), and 0.979 (95% CI: 0.919, 0.998), respectively. There was no statistical difference between AUCs of the different methods (p > 0.05). CONCLUSION: The proposed deep learning model and post-processing algorithm provide an effective means for the quantitative evaluation of urinary diseases using 3D MRU images.

Morphological Analyses and QTL Mapping of Mottled Leaf in Zucchini (Cucurbita pepo L.).

The mottled leaf is one of the agronomic traits of zucchini and can be applied as a marker trait in aggregation breeding. However, the genetic mechanism responsible for mottled leaf has yet to be elucidated. In the present study, we used two inbred lines (line '19': silver mottled leaf; line '113': normal leaf) as parents for the physiological and genetic analysis of mottled leaf. The synthesis and net photosynthetic rate of chlorophyll were not significantly affected in the mottled areas of leaves. However, we detected a large space between the palisade parenchyma in the leaf mottle area of line '19', which may have caused the mottled leaf phenotype. Light also plays an important role in the formation of mottled leaf, and receiving light during the early stages of leaf development is a necessary factor. Genetic analysis has previously demonstrated that mottled leaf is a quantitative trait that is controlled by multiple genes. Based on the strategy of quantitative trait locus sequencing (QTL-seq), two QTLs were identified on chromosomes 1 and 17, named CpML1.1 and CpML17.1, respectively. Two major loci were identified using R/qtl software version 1.66 under greenhouse conditions in April 2019 (2019A) and April 2020 (2020A) and under open cultivation conditions in May 2020 (2020M). The major QTL, CpML1.1, was located in a 925.2-kb interval on chromosome 1 and explained 10.51%-24.15% of the phenotypic variation. The CpML17.1 was located in a 719.7-kb interval on chromosome 17 and explained 16.25%-38.68% of the phenotypic variation. Based on gene annotation, gene sequence alignment, and qRT-PCR analysis, the Cp4.1LG01g23790 at the CpML1.1 locus encoding a protein of the TPX2 family (target protein of Xklp2) may be a candidate gene for mottled leaf in zucchini. Our findings may provide a theoretical basis for the formation of mottled leaf and provide a foundation for the fine mapping of genes associated with mottled leaf. Molecular markers closely linked to mottled leaf can be used in molecular-assisted selection for the zucchini mottled leaf breeding.

Pristine cobalt humic acid xerogels embedded with ultrafine cobalt sulfide for enhanced and stable lithium-ion storage.

The electrochemical performance of pristine metal-organic xerogels as anodes in lithium-ion batteries is reported for the first time. We propose a novel synthesis approach for the in situ generation of highly dispersed, ultrafine cobalt sulfide nanoparticles on humic acid gels (CoSHA). The CoS nanoparticles in CoSHA have an average diameter of approximately 3 nm. CoSHA electrodes demonstrate enhanced lithium storage capacity, delivering a capacity of 662 mAh g-1 at 0.1 A g-1. They also show stable long-term cycling performance, with no capacity decay after 900 cycles at 1.0 A g-1. Furthermore, our experiments indicate that the improved lithium-ion adsorption results from the oxygen-containing functional groups in humic acid and the ultrafine CoS active sites. This study offers a practical methodology for synthesizing ultrafine metal sulfides and new insights into using pristine gel-based electrodes for energy storage and conversion.

A review of lipid accumulation by oleaginous yeasts: Culture mode.

Microbial lipids have attracted considerable interest owing to their favorable environmental sustainability benefits. In laboratory-scale studies, the factors impacting lipid production in oleaginous yeasts, including culture conditions, nutrients, and low-cost substrates, have been extensively studied. However, there were several different modes of microbial lipid cultivation (batch culture, fed-batch culture, continuous culture, and other novel culture modes), making it difficult to comprehensively analyze impacting factors under different cultivation modes on a laboratory scale. And only few cases of microbial lipid production have been conducted at the pilot scale, which requires more technological reliability assessments and environmental benefit evaluations. Thus, this study summarized the different culture modes and cases of scale-up processes, highlighting the role of the nutrient element ratio in regulating culture mode selection and lipid accumulation. The cost distribution and environmental benefits of microbial lipid production by oleaginous yeasts were also investigated. Our results suggested that the continuous culture mode was recommended for the scale-up process because of its stable lipid accumulation. More importantly, exploring the continuous culture mode integrated with other efficient culture modes remained to be further investigated. In research on scale-up processes, low-cost substrate (organic waste) application and optimization of reactor operational parameters were key to increasing environmental benefits and reducing costs.

Registration study for the prevention and treatment of cerebral hemorrhage using naoxueshu oral liquid: Protocol for a research study.

BACKGROUND: Naoxueshu oral liquid is the only approved drug for acute treatment of cerebral hemorrhage in China. It has been used widely for the treatment of acute ischemic stroke and acute hemorrhagic stroke. However, safety and efficacy data on the early use of Naoxueshu oral liquid are lacking. The main purpose of this study is to observe the benefit and safety of early use of Naoxueshu oral liquid (< 72 h of cerebral hemorrhage) and offer evidence into the potential superiority of Naoxueshu oral liquid in patients with hemorrhagic stroke, and its healthcare costs. METHODS: This registration study for the prevention and treatment of cerebral hemorrhage using Naoxueshu oral liquid will be a quantitative, prospective, multicenter, observational clinical registry study. We aim to register 2000 patients with cerebral hemorrhage within 7 days of disease onset. This study will be an observational study and not interfere with the medication regimen of participants. Hence, we will not allocate patients. The main observation indicators will be the hematoma volume and the proportion of reduction 14 days post-cerebral hemorrhage (or at hospital discharge), onset of new stroke (ischemic stroke, hemorrhagic stroke) within 12 months of disease onset, independence in everyday life activities (modified Rankin Scale score ≤ 2), total cost during hospitalization, and treatment costs. CONCLUSION: This registration study will offer strong evidence for the efficacy and safety of Naoxueshu oral liquid for the prevention and treatment of cerebral hemorrhage, particularly with regard to early use (72 h after onset). It will offer evidence into the potential advantages of Naoxueshu oral liquid in patients with hemorrhagic stroke, including healthcare costs.