Association between Vitamin D Deficiency and Prediabetes Phenotypes: A Population-Based Study in Henan, China.

The evidence remains inconsistent regarding whether vitamin D deficiency (VDD) increases the risk of prediabetes. This study aimed to examine whether there is sex-specific association between VDD and impaired fasting glucose (IFG) or impaired glucose tolerance (IGT) in Henan. The data were sourced from the survey of chronic diseases and nutrition in Henan. Multinomial logistic regression models based on complex sampling design and weight were developed to estimate the odds ratio (OR) and confidence interval (95%CI) for measuring the association between VDD and IFG/IGT. The prevalence rate of IGT in men was 20.1% in the VDD group, significantly higher than that in the non-VDD group (10.5%), but no significant difference was observed in women between the VDD and non-VDD groups; there were no significant differences in IFG prevalence between the VDD and non-VDD groups in either men or women. It was found that the association between VDD and IGT was statistically significant in men. The adjusted OR (95%CI) of VDD was 1.99 (1.24-3.19) for IGT in men and 14.84 (4.14-53.20) for IGT in men having a family history of DM. Thus, men with VDD were more likely to live with IGT than those without VDD, especially for men having a family history of diabetes.

Kimura's Disease in Unusual Anatomical Locations: Clinical and Radiological Characteristics.

Purpose: To explore the clinical and imaging features of rare site Kimura's disease (KD). Methods: Retrospective analysis was conducted on the clinical manifestations, laboratory examinations, and imaging features of five patients with rare site KD. All imaging data, including the location, quantity, size, uniformity, boundary, and enhanced appearance of the lesion were evaluated by two independent radiologists. Results: Of the five patients, four were asymptomatic, and one experienced localized skin itching. Four cases involved subcutaneous nodules in the upper arm, while one was in the inguinal region. The main manifestations were single (three cases) or multiple (two cases) subcutaneous nodules/masses, with three patients accompanied by local lymph node enlargement. Four patients exhibited elevated eosinophil counts in their peripheral blood. Four patients had lesions with vascular flow voids; in three of these, the lesions also showed prominent enhancement. Notably, the lesion in a 5-year-old did not show vascular flow voids but displayed significant enhancement. Additionally, two patients showed edema around the lesions. Conclusion: The presence of solitary or multiple subcutaneous nodules/masses in the upper arm or inguinal area, accompanied by lymph node enlargement, elevated eosinophils in the peripheral blood, and the observation of internal vascular within the lesion, can aid in the diagnosis of KD occurring in uncommon anatomical locations.

Differences of bacterioplankton communities between the source and upstream regions of the Yangtze River: microbial structure, co-occurrence pattern, and environmental influencing factors.

The source area of the Yangtze River is located in the hinterland of the Qinghai-Tibet Plateau, which is known as the "Earth's third pole." It is the water conservation area and the natural barrier of the ecosystem of the Yangtze River basin. It is also the most sensitive area of the natural ecosystem, and the ecological environment is very fragile. Microorganisms play key roles in the biogeochemical processes of water. In this paper, the bacterioplankton communities in the source and upstream regions of the Yangtze River were studied based on 16S rRNA high-throughput sequencing, and their environmental influencing factors were further analyzed. Results showed that the upstream region had higher richness and diversity than the source region. The predominant bacterial phyla in the source and upstream regions were Proteobacteria, Firmicutes, and Actinobacteriota. The bacterial phyla associated with municipal pollution and opportunistic pathogen, such as Firmicutes and Actinobacteriota, were more abundant in the upstream. By contrast, distinct planktonic bacterial genera associated with mining pollution, such as Acidiphilium and Acidithiobacillus, were more abundant in the source region. The co-occurrence network showed that the interaction of bacterioplankton community is more frequent in the upstream. The bacterioplankton community compositions, richness, and functional profiles were affected by the spatial heterogeneity. Moreover, variation partitioning analysis further confirmed that the amount of variation in the source region independently explained by variables of altitude was the largest, followed by water nutrient. This paper revealed the spatial distribution of planktonic bacterial communities in the source and upstream regions of the Yangtze River and its correlation with environmental factors, providing information support for ensuring the health and safety of aquatic ecosystems in the Yangtze River Basin.

Most suitable plant communities for the slope reclamation of the Zhengzhou-Xinxiang section of the Beijing-Hong Kong-Macao expressway.

The construction of expressways in China has produced diverse habitats along slopes characterized by steep gradients, uneven water distribution, poor soil conditions, and no routine maintenance. Manually planting beneficial species is an essential method of effectively improving slope soils to prevent soil erosion. However, few studies have evaluated the reclamation effects and plant community composition and structure used to restore slopes along expressways. This study focused on the Zhengzhou-Xinxiang section of the Beijing-Hong Kong-Macao Expressway. A total of 10 representative plant communities were evaluated using the analytic hierarchy process (AHP)-fuzzy integrated evaluation method. The sites were divided into four layers, namely, plant communities, soil nutrients, soil physical properties, and other ecological factors, and 14 indicators were assessed. The evaluation results showed that four of these plant communities (PCs) were excellent, three PCs were good, one PC was normal, two PCs were poor. The four excellent PCs had high Shannon-Wiener index, pielou index, richness index or community productivity. It is worth noting that most excellent plant community structures were tree + shrub + herb. Based on these results, we recommend that fill slopes should be restored using a combination of trees, herbs, and shrubs; also, the vegetation should include native plants, such as B. papyrifera, U. pumila, A. fruticosa, and Cynodon dactylon (L.). This study could provide ideas for plant community composition and structure of new highway slopes in similar climate environment, and provide theoretical support for plant community composition and structure and soil improvement for the existing slope.

Spatially explicit estimation of freshwater fish stock biomass with limited data: A case study of an endangered endemic fish on the Tibetan Plateau, China.

Accurate evaluation of fish stock biomass is essential for effective conservation management and targeted species enhancement efforts. However, this remains challenging owing to limited data availability. Therefore, we present an integrated modeling framework combining catch per unit effort with ensemble species distribution modeling called CPUESDM, which explicitly assesses and validates the spatial distribution of stock biomass for freshwater fish species with limited data, applied to Herzensteinia microcephalus. The core algorithm incorporates the Leslie regression model, ensemble species distribution modeling, and exploratory spatial interpolation techniques. We found that H. microcephalus biomass in the Yangtze River source area yielded an initial estimate of 113.52 tons. Our validation results demonstrate high accuracy with a Cohen's kappa coefficient of 0.78 and root mean square error of 0.05. Furthermore, our spatially-explicit, global, absolute biomass density map effectively identified areas with high and low concentrations of biomass distribution centers. Additionally, this study offers access to the source code, example raw data, and a step-by-step instruction manual for other researchers using field data to explore the application of this model. Our findings can help inform for future conservation efforts around fish stock biomass estimation, especially for endangered species.

First description study on molecular characterization of Hemiclepsis khankiana (Hirudinea: Glossiphoniidae) in China.

BACKGROUND: Leeches are an integral component of aquatic biocenosis and can be found in a wide range of ecosystems such as freshwater, saltwater, flowing, and still-water ecosystems. It especially plays an important role in the freshwater benthic community and is an important part of the food web. In this study, a leech species was found in the mantle cavity of wild freshwater mussels in Zigong City, Sichuan Province, China, and its identity was determined through morphological analysis and molecular biological analysis. RESULTS: The leech is Hemiclepsis khankiana, a new species of Hemiclepsis that has been discovered in Russia in recent years. Through morphological analysis, the current survey observed that the morphological characteristics of Hemiclepsis khankiana eyespots were significantly different from the first reported description. The first pair of eyespots on the leech were separated and clear, while it had been reduced to unclear shadows in the previous report. The phylogenetic tree based on the COI gene showed that the COI gene sequence obtained in this study was in the same evolutionary branch as Hemiclepsis khankiana (MN295420, MN295421). Genetically, it was most closely related to Hemiclepsis kasmiana (mean COI p-distance = 3.98%). CONCLUSIONS: The current study reported on the new distribution range of Hemiclepsis khankiana, which was initially discovered in China. This study indicates that the distribution range of the leech species has expanded, laying a foundation for further studies in China.

Case Report: Primary osteosarcoma of the kidney.

Extraosseous osteosarcoma is a rare malignant tumor, most commonly occurring in the thigh, upper limbs, and retroperitoneum. However, there are only a few reported cases of renal osteosarcoma. Herein, we present the case of a 54-year-old woman with malignant extraosseous osteosarcoma of the left kidney. CT and MR imaging revealed a soft tissue mass originating from the left kidney.

UV-Light-Induced Morphological Transformation of Spiropyran Assemblies from Irregular Sheet-like Structures to Nanospheres.

Studies on self-assembling systems with a controllable morphology responding to light stimulation are significant for revealing the process and mechanism of assembly. Here, a molecule of spiropyran derivative (SP) possessing photoresponsive assembly morphology is constructed. SP self-assembles into irregular sheet-like structures whose morphology can be significantly transformed into regular nanospheres under continuous ultraviolet light stimulation. The UV-vis absorption spectra indicate that 56% of SP are isomerized from closed-ring form (SPC) to open-ring form (SPO) with color changes from colorless to magenta. Furthermore, theoretical calculations demonstrate that SPO-SPO aggregates possess stronger van der Waals forces than do SPC-SPC aggregates and tend to form stable intermediates combined with SPO isomers. Therefore, the isomerization of SP from SPC to SPO and the differences in intermolecular interactions are important factors in the morphological transition. Our study provides an efficient strategy to modulate the assembled morphology, which holds great promise to be applied in the field of smart materials.

Identifying ureteral stent encrustation using machine learning based on CT radiomics features: a bicentric study.

Obstructive: To develop and validate radiomics and machine learning models for identifying encrusted stents and compare their recognition performance with multiple metrics. Methods: A total of 354 patients with ureteral stent placement were enrolled from two medical institutions and divided into the training cohort (n = 189), internal validation cohort (n = 81) and external validation cohort (n = 84). Based on features selected by Wilcoxon test, Spearman Correlation Analysis and least absolute shrinkage and selection operator (LASSO) regression algorithm, six machine learning models based on radiomics features were established with six classifiers (LR, DT, SVM, RF, XGBoost, KNN). After comparison with those models, the most robust model was selected. Considering its feature importance as radscore, the combined model and a nomogram were constructed by incorporating indwelling time. Accuracy, sensitivity, specificity, area under the curve (AUC), decision curve analysis (DCA) and calibration curve were used to evaluate the recognition performance of models. Results: 1,409 radiomics features were extracted from 641 volumes of interest (VOIs) and 20 significant radiomics features were selected. Considering the superior performance (AUC 0.810, 95%CI, 0.722-0.888) in the external validation cohort, feature importance of XGBoost was used as a radscore, constructing a combined model and a nomogram with indwelling time. The accuracy, sensitivity, specificity and AUC of the combined model were 98, 100, 97.3% and 0.999 for the training cohort, 83.3, 80, 84.5% and 0.867 for the internal cohort and 78.2, 76.3, 78.8% and 0.820 for the external cohort, respectively. DCA indicates the favorable clinical utility of models. Conclusion: Machine learning model based on radiomics features enables to identify ureteral stent encrustation with high accuracy.

Light-Modulated Morphological Transformation of Spiropyran Derivative from Nanosphere to Nanorod.

The construction of tunable morphological systems has important implications for understanding the mechanism of molecular self-assembly. In this study, a spiropyran derivative M1 is reported with light-responsive assembly morphology, which can be tuned from nanosphere to nanorod by ultraviolet light irradiation. The absorption spectra show that M1 molecules are transformed from closed-ring (SP) isomers into open-ring (MC) isomers and start to form H-aggregates with increasing irradiation time. Density functional theory calculations indicate that MC-MC isomers possess stronger binding energy than SP-SP isomers. The MC isomers may thus facilitate the dissociation of the SP-SP aggregates and promote the change of self-assembled morphology with the aid of stronger π-π stackings and dipole-dipole interactions. The research gives an effective method for modulating the morphology of assemblies, with great potential for applications in smart materials.

Evaluating AI rib fracture detections using follow-up CT scans.

PURPOSE: This study compares the results of Artificial Intelligence (AI) diagnosis of rib fractures using initial CT and follow-up CT as the final diagnostic criteria, and studies AI-assisted diagnosis in improving the detection rate of rib fractures. METHODS: A retrospective study was conducted on 113 patients who underwent initial and follow-up CT scans due to trauma. The initial and follow-up CT were used as diagnostic criteria, respectively. All images were transmitted to the AI software (V2.1.0, Huiying Medical Technology Co., Beijing, China) for rib fracture detection. The radiologist group (Group 1), AI group (Group 2), and Radiologist with AI group (Group 3) reviewed CT images at an interval of one month, recorded and compared the differences in the sensitivity and specificity for diagnosing rib fractures. RESULTS: 589 and 712 rib fractures were diagnosed by the initial and follow-up CT, respectively. The initial CT diagnosis failed to detect 127 rib fractures, resulting in a missed rate of 17.84%. In addition, four normal ribs were mistakenly identified as being fractured. The follow-up CT was regarded as the diagnostic standard for rib fractures. The sensitivity and specificity were 82.16% and 99.80% for Group 1, 79.35% and 84.90% for Group 2, and 91.57% and 99.70% for Group 3. The sensitivity of Group 3 was higher than that of Group 1 and Group 2 (p < 0.05). The specificity was lower for Group 2 compared with Group 1 and Group 3 (p < 0.05). CONCLUSION: AI-assisted diagnosis improved the detection rate of rib fractures, the follow-up CT should be used for the diagnosis standard of rib fractures, and AI misdiagnoses can be greatly reduced when a radiologist reviews the diagnosis.

Comparative Effectiveness of MRI, 4D-CT and Ultrasonography in Patients with Secondary Hyperparathyroidism.

Objective: Accurate preoperative localization of abnormal parathyroid glands is crucial for successful surgical management of secondary hyperparathyroidism (SHPT). This study was conducted to compare the effectiveness of preoperative MRI, 4D-CT, and ultrasonography (US) in localizing parathyroid lesions in patients with SHPT. Methods: We performed a retrospective review of prospectively collected data from a tertiary-care hospital and identified 52 patients who received preoperative MRI and/or 4D-CT and/or US and/or 99mTc-MIBI and subsequently underwent surgery for SHPT between May 2013 and March 2020. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of each imaging modality to accurately detect enlarged parathyroid glands were determined using histopathology as the criterion standard with confirmation using the postoperative biochemical response. Results: A total of 198 lesions were identified intraoperatively among the 52 patients included in this investigation. MRI outperformed 4D-CT and US in terms of sensitivity (P < 0.01), specificity (P = 0.455), PPV (P = 0.753), and NPV (P = 0.185). The sensitivity and specificity for MRI, 4D-CT, and US were 90.91%, 88.95%, and 66.23% and 58.33%, 63.64%, and 50.00%, respectively. The PPV of combined MRI and 4D-CT (96.52%) was the highest among the combined 2 modalities. The smallest diameter of the parathyroid gland precisely localized by MRI was 8×3 mm, 5×5 mm by 4D-CT, and 5×3 mm by US. Conclusion: MRI has superior diagnostic performance compared with other modalities as a first-line imaging study for patients undergoing renal hyperparathyroidism, especially for ectopic or small parathyroid lesions. We suggest performing US first for diagnosis and then MRI to make a precise localization, and MRI proved to be very helpful in achieving a high success rate in the surgical treatment of renal hyperparathyroidism in our own experience.

Identification of genetic loci associated with five agronomic traits in alfalfa using multi-environment trials.

KEY MESSAGE: The use of multi-environment trials to test yield-related traits in a diverse alfalfa panel allowed to find multiple molecular markers associated with complex agronomic traits. Yield is one of the most important target traits in alfalfa breeding; however, yield is a complex trait affected by genetic and environmental factors. In this study, we used multi-environment trials to test yield-related traits in a diverse panel composed of 200 alfalfa accessions and varieties. Phenotypic data of maturity stage measured as mean stage by count (MSC), dry matter content, plant height (PH), biomass yield (Yi), and fall dormancy (FD) were collected in three locations in Idaho, Oregon, and Washington from 2018 to 2020. Single-trial and stagewise analyses were used to obtain estimated trait means of entries by environment. The plants were genotyped using a genotyping by sequencing approach and obtained a genotypic matrix with 97,345 single nucleotide polymorphisms. Genome-wide association studies identified a total of 84 markers associated with the traits analyzed. Of those, 29 markers were in noncoding regions and 55 markers were in coding regions. Ten significant SNPs at the same locus were associated with FD and they were linked to a gene annotated as a nuclear fusion defective 4-like (NFD4). Additional SNPs associated with MSC, PH, and Yi were annotated as transcription factors such as Cysteine3Histidine (C3H), Hap3/NF-YB family, and serine/threonine-protein phosphatase 7 proteins, respectively. Our results provide insight into the genetic factors that influence alfalfa maturity, yield, and dormancy, which is helpful to speed up the genetic gain toward alfalfa yield improvement.

[Feasibility analysis of puncture robot technology for the application of acupuncture robot].

The difficulties such as how to accurately locate acupoints and safely insert needles are presented in acupuncture robot. The puncture robot with high technological similarity to acupuncture robot is getting mature, and a large number of human trials and animal experiments have been conducted for the development of puncture robot. Through comparing the similarities and differences between puncture robot and acupuncture robot in the aspects of through-skin puncture, needle insertion and needle removal, the valuable technology of puncture robot is analyzed for the development of acupuncture robot, and the crucial direction of technology migration is determined. ①Integrating the mechanical feedback and medical imaging technology and utilizing the multi-modal perception to achieve the safety of acupuncture operation. ②Emphasizing the integration of the existing designs of chest puncture robot to realize the acupuncture operation with inhalation and exhalation involved. ③Focusing on the development of relevant technology of automatic needle removal through conducting the actual scenario of treatment with acupuncture robot in patients under non-anaesthetic condition.

Automatic reorientation by deep learning to generate short-axis SPECT myocardial perfusion images.

BACKGROUND: Single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) can be displayed both in traditional short-axis (SA) cardiac planes and polar maps for interpretation and quantification. It is essential to reorient the reconstructed transaxial SPECT MPI into standard SA slices. This study is aimed to develop a deep-learning-based approach for automatic reorientation of MPI. METHODS: A total of 254 patients were enrolled, including 226 stress SPECT MPIs and 247 rest SPECT MPIs. Fivefold cross-validation with 180 stress and 201 rest MPIs was used for training and internal validation; the remaining images were used for testing. The rigid transformation parameters (translation and rotation) from manual reorientation were annotated by an experienced nuclear cardiologist and used as the reference standard. A convolutional neural network (CNN) was designed to predict the transformation parameters. Then, the derived transform was applied to the grid generator and sampler in spatial transformer network (STN) to generate the reoriented image. A loss function containing mean absolute errors for translation and mean square errors for rotation was employed. A three-stage optimization strategy was adopted for model optimization: (1) optimize the translation parameters while fixing the rotation parameters; (2) optimize rotation parameters while fixing the translation parameters; (3) optimize both translation and rotation parameters together. RESULTS: In the test set, the Spearman determination coefficients of the translation distances and rotation angles between the model prediction and the reference standard were 0.993 in X axis, 0.992 in Y axis, 0.994 in Z axis, 0.987 along X axis, 0.990 along Y axis and 0.996 along Z axis, respectively. For the 46 stress MPIs in the test set, the Spearman determination coefficients were 0.858 in percentage of profusion defect (PPD) and 0.858 in summed stress score (SSS); for the 46 rest MPIs in the test set, the Spearman determination coefficients were 0.9 in PPD and 0.9 in summed rest score (SRS). CONCLUSIONS: Our deep learning-based LV reorientation method is able to accurately generate the SA images. Technical validations and subsequent evaluations of measured clinical parameters show that it has great promise for clinical use.