SARS-CoV-2 Omicron XBB lineage spike structures, conformations, antigenicity, and receptor recognition.

A recombinant lineage of the SARS-CoV-2 Omicron variant, named XBB, appeared in late 2022 and evolved descendants that successively swept local and global populations. XBB lineage members were noted for their improved immune evasion and transmissibility. Here, we determine cryo-EM structures of XBB.1.5, XBB.1.16, EG.5 and EG.5.1 spike (S) ectodomains to reveal reinforced 3-RBD-down receptor inaccessible closed states mediated by interprotomer receptor binding domain (RBD) interactions previously observed in BA.1 and BA.2. Improved XBB.1.5 and XBB.1.16 RBD stability compensated for stability loss caused by early Omicron mutations, while the F456L substitution reduced EG.5 RBD stability. S1 subunit mutations had long-range impacts on conformation and epitope presentation in the S2 subunit. Our results reveal continued S protein evolution via simultaneous optimization of multiple parameters including stability, receptor binding and immune evasion, and the dramatic effects of relatively few residue substitutions in altering the S protein conformational landscape.

Validation of bone mineral density measurement using quantitative CBCT image based on deep learning.

The bone mineral density (BMD) measurement is a direct method of estimating human bone mass for diagnosing osteoporosis, and performed to objectively evaluate bone quality before implant surgery in dental clinics. The objective of this study was to validate the accuracy and reliability of BMD measurements made using quantitative cone-beam CT (CBCT) image based on deep learning by applying the method to clinical data from actual patients. Datasets containing 7500 pairs of CT and CBCT axial slice images from 30 patients were used to train a previously developed deep-learning model (QCBCT-NET). We selected 36 volumes of interest in the CBCT images for each patient in the bone regions of potential implants sites on the maxilla and mandible. We compared the BMDs shown in the quantitative CBCT (QCBCT) images with those in the conventional CBCT (CAL_CBCT) images at the various bone sites of interest across the entire field of view (FOV) using the performance metrics of the MAE, RMSE, MAPE (mean absolute percentage error), R2 (coefficient of determination), and SEE (standard error of estimation). Compared with the ground truth (QCT) images, the accuracy of the BMD measurements from the QCBCT images showed an RMSE of 83.41 mg/cm3, MAE of 67.94 mg/cm3, and MAPE of 8.32% across all the bone sites of interest, whereas for the CAL_CBCT images, those values were 491.15 mg/cm3, 460.52 mg/cm3, and 54.29%, respectively. The linear regression between the QCBCT and QCT images showed a slope of 1.00 and a R2 of 0.85, whereas for the CAL_CBCT images, those values were 0.32 and 0.24, respectively. The overall SEE between the QCBCT images and QCT images was 81.06 mg/cm3, whereas the SEE for the CAL_CBCT images was 109.32 mg/cm3. The QCBCT images thus showed better accuracy, linearity, and uniformity than the CAL_CBCT images across the entire FOV. The BMD measurements from the quantitative CBCT images showed high accuracy, linearity, and uniformity regardless of the relative geometric positions of the bone in the potential implant site. When applied to actual patient CBCT images, the CBCT-based quantitative BMD measurement based on deep learning demonstrated high accuracy and reliability across the entire FOV.

Robust Energy Calibration Technique for Photon Counting Spectral Detectors.

This paper describes the implementation of a novel and robust threshold energy calibration method for photon counting detectors using polychromatic X-ray tubes. Methods often used for such energy calibration may require re-orientation of the detector or introduce calibration errors that are flux and acquisition time-dependent. Our newly proposed "differential intensity ratios" (DIR) method offers a practical and robust alternative to existing methods. We demonstrate this robustness against photon flux used in calibration, spectral errors such as pulse pile-up as well as the detector's inherent spectral resolution limits. The demonstrated significant insensitivity of the proposed DIR signature to detector spectral distortions and energy resolution is a key finding. The proposed DIR calibration method is demonstrated using Medipix3RX detectors with a CdTe sensor under varying flux conditions. A per pixel calibration using the DIR method has also been implemented to demonstrate an improvement over the global energy resolution of the PCD.

Feasibility of a New Desktop Motion Analysis System with a Video Game Console for Assessing Various Three-Dimensional Wrist Motions.

BACKGROUND: The restriction of wrist motion results in limited hand function, and the evaluation of the range of wrist motion is related to the evaluation of wrist function. To analyze and compare the wrist motion during four selected tasks, we developed a new desktop motion analysis system using the motion controller for a home video game console. METHODS: Eighteen healthy, right-handed subjects performed 15 trials of selective tasks (dart throwing, hammering, circumduction, and winding thread on a reel) with both wrists. The signals of light-emitting diode markers attached to the hand and forearm were detected by the optic receptor in the motion controller. We compared the results between both wrists and between motions with similar motion paths. RESULTS: The parameters (range of motion, offset, coupling, and orientations of the oblique plane) for wrist motion were not significantly different between both wrists, except for radioulnar deviation for hammering and the orientation for thread winding. In each wrist, the ranges for hammering were larger than those for dart throwing. The offsets and the orientations of the oblique plane were not significantly different between circumduction and thread winding. CONCLUSIONS: The results for the parameters of dart throwing, hammering, and circumduction of our motion analysis system using the motion controller were considerably similar to those of the previous studies with three-dimensional reconstruction with computed tomography, electrogoniometer, and motion capture system. Therefore, our system may be a cost-effective and simple method for wrist motion analysis.

Computerized Automated Quantification of Subcutaneous and Visceral Adipose Tissue From Computed Tomography Scans: Development and Validation Study.

BACKGROUND: Computed tomography (CT) is often viewed as one of the most accurate methods for measuring visceral adipose tissue (VAT). However, measuring VAT and subcutaneous adipose tissue (SAT) from CT is a time-consuming and tedious process. Thus, evaluating patients' obesity levels during clinical trials using CT scans is both cumbersome and limiting. OBJECTIVE: To describe an image-processing-based and automated method for measuring adipose tissue in the entire abdominal region. METHODS: The method detects SAT and VAT levels using a separation mask based on muscles of the human body. The separation mask is the region that minimizes the unnecessary space between a closed path and muscle area. In addition, a correction mask, based on bones, corrects the error in VAT. RESULTS: To validate the method, the volume of total adipose tissue (TAT), SAT, and VAT were measured for a total of 100 CTs using the automated method, and the results compared with those from manual measurements obtained by 2 experts. Dice's similarity coefficients (DSCs) between the first manual measurement and the automated result for TAT, SAT, and VAT are 0.99, 0.98, and 0.97, respectively. The DSCs between the second manual measurement and the automated result for TAT, SAT, and VAT are 0.98, 0.98, and 0.97, respectively. Moreover, intraclass correlation coefficients (ICCs) between the automated method and the results of the manual measurements indicate high reliability as the ICCs for the items are all .99 (P<.001). CONCLUSIONS: The results described in this paper confirm the accuracy and reliability of the proposed method. The method is expected to be both convenient and useful in the clinical evaluation and study of obesity in patients who require SAT and VAT measurements.

Clinical Application of Solid Model Based on Trabecular Tibia Bone CT Images Created by 3D Printer.

OBJECTIVES: The aim of this work is to use a 3D solid model to predict the mechanical loads of human bone fracture risk associated with bone disease conditions according to biomechanical engineering parameters. METHODS: We used special image processing tools for image segmentation and three-dimensional (3D) reconstruction to generate meshes, which are necessary for the production of a solid model with a 3D printer from computed tomography (CT) images of the human tibia's trabecular and cortical bones. We examined the defects of the mechanism for the tibia's trabecular bones. RESULTS: Image processing tools and segmentation techniques were used to analyze bone structures and produce a solid model with a 3D printer. CONCLUSIONS: These days, bio-imaging (CT and magnetic resonance imaging) devices are able to display and reconstruct 3D anatomical details, and diagnostics are becoming increasingly vital to the quality of patient treatment planning and clinical treatment. Furthermore, radiographic images are being used to study biomechanical systems with several aims, namely, to describe and simulate the mechanical behavior of certain anatomical systems, to analyze pathological bone conditions, to study tissues structure and properties, and to create a solid model using a 3D printer to support surgical planning and reduce experimental costs. These days, research using image processing tools and segmentation techniques to analyze bone structures to produce a solid model with a 3D printer is rapidly becoming very important.

A quantitative evaluation of abdominal aorta aneurysm by CT images.

An abdominal aorta aneurysm (AAA) is a disease that aortic vessel inflates abnormally. The aorta blows up continuously, which may lead to the rupture of the aorta. The mortality of rupturing the aorta is between 75 and 90% to properly treat this disease, we need to accurate measure about variation of AAA size. our team performed that AAA is reconstructed as three dimensional (3D) images by computer tomography (CT), and analyzed the elements of inflation through a geometric parameter measurement . Subjects (seven males) who undergo an AAA are enrolled for the analysis. The authors used CT images as a primary source, and obtained secondary CT images 12 months later. By means of these data, the authors constructed 3D images of AAA and performed examinations using a geometric analysis that calculates geometric parameter such as the tortuosity, diameter, saccular and so on based on volume, area of the segmented region of the CT slices that is set up by the centroids and 8 points around it. The result of the severity biomechanical factor shows increased AAA tortuosity ratio (4.9%), AAA diameter expansion ratio [cm/year] (6.8%), AAA total diameter ratio (4.7%), AAA saccular ratio (2.4%) than 12-month before. Through these results, We can plan to endovascular repair surgery to undergoing AAA patients and possible diagnosis estimation of AAA.

Ambient vibration testing for story stiffness estimation of a heritage timber building.

This paper investigates dynamic characteristics of a historic wooden structure by ambient vibration testing, presenting a novel estimation methodology of story stiffness for the purpose of vibration-based structural health monitoring. As for the ambient vibration testing, measured structural responses are analyzed by two output-only system identification methods (i.e., frequency domain decomposition and stochastic subspace identification) to estimate modal parameters. The proposed methodology of story stiffness is estimation based on an eigenvalue problem derived from a vibratory rigid body model. Using the identified natural frequencies, the eigenvalue problem is efficiently solved and uniquely yields story stiffness. It is noteworthy that application of the proposed methodology is not necessarily confined to the wooden structure exampled in the paper.

Preoperative serum sex hormone-binding globulin as a predictive marker for extraprostatic extension of tumor in patients with clinically localized prostate cancer.

OBJECTIVES: We investigated the relationships of serum sex hormone-binding globulin (SHBG) level with known prognostic factors for prostate cancer in men who received radical retropubic prostatectomy (RRP) for clinically localized prostate cancer. METHODS: Preoperative serum levels of SHBG were analyzed in 288 consecutive patients who were scheduled to undergo RRP for clinically localized prostate cancer. We investigated the potential associations of preoperative serum SHBG level with various clinical and pathological factors. Accuracy of variables in predicting adverse pathological features was assessed via receiver operator characteristics (ROC) curves. RESULTS: In univariate analysis, preoperative serum SHBG level was observed to be significantly associated with extraprostatic extension of a tumor (p=0.019) and with pathological Gleason score (p=0.001). In multivariate analysis, serum SHBG level (p=0.039) along with serum PSA (p<0.001) level, biopsy Gleason score (p<0.001), and clinical stage (p=0.004) was observed to be an independent predictor of the extraprostatic extension of prostate cancer. The area under ROC curve that demonstrated the performance of a multivariate logistic regression model (MLRM), which included serum SHBG level and other preoperative variables, in predicting extraprostatic extension of tumor was larger than that of MLRM without SHBG (0.797 vs. 0.758, p=0.121). Meanwhile, serum SHBG level was not observed to be significantly associated with pathological Gleason score in multivariate analysis (p=0.303). CONCLUSIONS: Our data showed that serum SHBG level is an independent predictive factor for extraprostatic extension of tumor in patients with clinically localized prostate cancer.

Utilization of the recombinant human beta-carotene-15,15'-monooxygenase gene in Escherichia coli and mammalian cells.

In animals, beta-carotene 15,15'-monooxygenase (BCMO) is the key enzyme involved in the metabolism of plant beta-carotene to retinal. In the present study, we utilized beta-carotene-producing Escherichia coli to screen for mutants with higher BCMO activity which was monitored by color changes derived from beta-carotene cleavage. Recombinant wild-type and T381L mutant BCMO proteins were purified to near homogeneity in E. coli, and their enzymatic activities were determined by HPLC analysis. The catalytic efficiency for beta-carotene and retinal production of the mutant were 1.5-fold and 1.7-fold higher than those of wild-type, respectively. Further BCMO function in mammalian cells was analyzed by a retinoic acid receptor reporter assay, which responds to the metabolic conversion of beta-carotene to retinoic acid in vivo. Overall, these tools can be used to screen more active BCMO for the industrial and pharmacological purpose of retinal production from beta-carotene.