Mid-treatment MRI-based tumor response assessment for tumor recurrence and patient survival in locally advanced adenocarcinoma of the cervix: A retrospective multicenter study of KROG 23-03.

OBJECTIVE: To evaluate the significance of response assessment with magnetic resonance imaging (MRI) during chemoradiotherapy (CRT) for outcomes of adenocarcinoma of the cervix. METHODS: A retrospective analysis of 102 patients diagnosed with FIGO 1B3-IVa cervical adenocarcinoma was conducted. Patients underwent definitive CRT and brachytherapy. Mid-treatment MRI-assessments were used to evaluate tumor response during radiotherapy, focusing on tumor volume reduction rate (TVRR), which was defined as an optimal reduction rate from initial tumor volume for tumor progression. Locoregional recurrence (LRR), distant metastasis (DM), progression-free survival (PFS) and overall survival (OS) rates according to the tumor response were analyzed. RESULTS: Forty-five (44.1 %) of 102 patients experienced tumor downstaging during CRT, with 72 (70.5 %) demonstrating a complete response on post-treatment MRI three months after radiotherapy. With a median follow-up of 35.5 months, the 3-year PFS and overall OS rates for all patients were 60.0 % and 84.0 %, respectively. LRR and DM rates at 3 years were 25.2 % and 23.3 %, respectively. Patients with TVRR≥81.8 % had significantly longer 3-year PFS (75.4 % vs. 36.2 %, P < 0.001) and OS (93.2 % vs. 69.0 %, P = 0.002) rates than the other patients with TVRR<81.8 %. LRR (10.6 % vs. 45.6 %, P = 0.003) and DM (14.6 % vs. 33.5 %, P = 0.008) rates at 3 years were significantly lower in TVRR≥81.8 % group compared to TVRR<81.8 % group. In the multivariate analysis, positive initial lymph node (hazard ratio [HR], 2.11; confidence interval [CI], 1.25-3.87; P = 0.02] and TVRR (HR, 0.42; CI, 0.19-0.93; P = 0.03) were significantly associated with PFS. CONCLUSION: Mid-treatment MRI assessment is crucial and higher rates of tumor volume reduction during radiotherapy indicates better prognosis for tumor recurrence and patient survival in cervical adenocarcinoma.

Korean Red Ginseng Extract Powder Mitigates Fasting And Postprandial Hyperglycemia in Type 2 Diabetic Mice.

Type 2 diabetes mellitus (T2DM) involves insulin resistance and elevated blood sugar levels, causing complications. Red ginseng extract powder (RGEP) from Panax ginseng Meyer shows promise for diabetes treatment. However, its efficacy in managing T2DM remains unclear. Therefore, this study aims to evaluate the effectiveness of RGEP in a mouse model of T2DM. The efficacy of RGEP in treating T2DM was assessed in db/db mice. Mice were divided into seven groups: control, db/db, metformin, and RGEP at 50, 100, 200, and 400 mg/kg. Administered orally for 9 weeks, RGEP effects on glucose regulation and insulin sensitivity were assessed through various metabolic parameters. In addition, mRNA expression levels of genes associated with hepatic gluconeogenesis and insulin sensitivity were examined. Fasting blood sugar showed a significant decrease in all RGEP concentration groups, but OGTT and insulin tolerance test showed a significant decrease at the RGEP concentration of 400 mg/kg, indicating enhanced glycemic control. Moreover, RGEP dose-dependently decreased serum glucose, HbA1c levels, and homeostatic model assessment of insulin resistance values, suggesting its effectiveness in reducing insulin resistance in db/db mice. Furthermore, RGEP downregulated mRNA expression of key components in the gluconeogenesis pathway (G6Pase, FOXO1, GLUT4, and PEPCK), insulin sensitivity (leptin, insulin1, PTP1B, GLP-1, and DPP-4), and mitochondria energy metabolism (PGC1) in either the liver or pancreas, while simultaneously upregulating GLP-1 expression. In conclusion, these findings highlight the potential of RGEP as a complementary therapy for T2DM, indicating therapeutic efficacy in managing diabetic complications through improved metabolic parameters.

Automated abdominal organ segmentation algorithms for non-enhanced CT for volumetry and 3D radiomics analysis.

PURPOSE: To develop fully-automated abdominal organ segmentation algorithms from non-enhanced abdominal CT and low-dose chest CT and assess their feasibility for automated CT volumetry and 3D radiomics analysis of abdominal solid organs. METHODS: Fully-automated nnU-Net-based models were developed to segment the liver, spleen, and both kidneys in non-enhanced abdominal CT, and the liver and spleen in low-dose chest CT. 105 abdominal CTs and 60 low-dose chest CTs were used for model development, and 55 abdominal CTs and 10 low-dose chest CTs for external testing. The segmentation performance for each organ was assessed using the Dice similarity coefficients, with manual segmentation results serving as the ground truth. Agreements between ground-truth measurements and model estimates of organ volume and 3D radiomics features were assessed using the Bland-Altman analysis and intraclass correlation coefficients (ICC). RESULTS: The models accurately segmented the liver, spleen, right kidney, and left kidney in abdominal CT and the liver and spleen in low-dose chest CT, showing mean Dice similarity coefficients in the external dataset of 0.968, 0.960, 0.952, and 0.958, respectively, in abdominal CT, and 0.969 and 0.960, respectively, in low-dose chest CT. The model-estimated and ground truth volumes of these organs exhibited mean differences between - 0.7% and 2.2%, with excellent agreements. The automatically extracted mean and median Hounsfield units (ICCs, 0.970-0.999 and 0.994-0.999, respectively), uniformity (ICCs, 0.985-0.998), entropy (ICCs, 0.931-0.993), elongation (ICCs, 0.978-0.992), and flatness (ICCs, 0.973-0.997) showed excellent agreement with ground truth measurements for each organ; however, skewness (ICCs, 0.210-0.831), kurtosis (ICCs, 0.053-0.933), and sphericity (ICCs, 0.368-0.819) displayed relatively low and inconsistent agreement. CONCLUSION: Our nnU-Net-based models accurately segmented abdominal solid organs in non-enhanced abdominal and low-dose chest CT, enabling reliable automated measurements of organ volume and specific 3D radiomics features.

Realization of Extremely High-Gain and Low-Power in nMOS Inverter Based on Monolayer WS2 Transistor Operating in Subthreshold Regime.

In this work, we report an n-type metal-oxide-semiconductor (nMOS) inverter using chemical vapor deposition (CVD)-grown monolayer WS2 field-effect transistors (FETs). Our large-area CVD-grown monolayer WS2 FETs exhibit outstanding electrical properties including a high on/off ratio, small subthreshold swing, and excellent drain-induced barrier lowering. These are achieved by n-type doping using AlOx/Al2O3 and a double-gate structure employing high-k dielectric HfO2. Due to the superior subthreshold characteristics, monolayer WS2 FETs show high transconductance and high output resistance in the subthreshold regime, resulting in significantly higher intrinsic gain compared to conventional Si MOSFETs. Therefore, we successfully realize subthreshold operating monolayer WS2 nMOS inverters with extremely high gains of 564 and 2056 at supply voltage (VDD) of 1 and 2 V, respectively, and low power consumption of ∼2.3 pW·µm-1 at VDD = 1 V. In addition, the monolayer WS2 nMOS inverter is further expanded to the demonstration of logic circuits such as AND, OR, NAND, NOR logic gates, and SRAM. These findings suggest the potential of monolayer WS2 for high-gain and low-power logic circuits and validate the practical application in large areas.

Comparison between head rotation and standard techniques for i-gel™ insertion: a randomized controlled trial.

BACKGROUND: This study evaluated the effect of head rotation on the first-attempt success rate of i-gel insertion, aiming to alleviate the effect of gravity on the tongue and reduce resistance between the device and the tongue. METHODS: Adult surgical patients were randomized to standard and head rotation technique groups. In the head rotation technique group, patients' heads were maximally rotated to the left before i-gel insertion. The primary endpoint was the first-attempt success rate. Secondary endpoints included the success rate within two attempts (using the allocated technique), time required for successful i-gel placement within two attempts, and success rate at the third attempt (using the opposite technique). RESULTS: Among 158 patients, the head rotation technique group showed a significantly higher first-attempt success rate (60/80, 75.0%) compared to the standard technique group (45/78, 57.7%; P = 0.021). The success rate within two attempts was similar between the groups (95.0% vs. 91.0%, P = 0.326). The time required for successful i-gel placement was significantly shorter in the head rotation technique (mean [SD], 13.4 [3.7] s vs. 16.3 [7.8] s; P = 0.030). When the head rotation technique failed, the standard technique also failed in all cases (n = 4), whereas the head rotation technique succeeded in five out of the seven patients where the standard technique failed. CONCLUSIONS: The head rotation technique significantly improved the first-attempt success rate and reduced the time required for successful i-gel insertion. It was effective when the standard technique failed. The head rotation technique may be an effective primary or alternative method for i-gel insertion. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (NCT05201339).

Zinc and copper isotope fractionation in metal leaching from hydrothermal ore deposits: Environmental implications for deep-sea mining.

Deep-sea mining can remobilize large amounts of inert metals from hydrothermal seafloor massive sulfides (SMSs) into bioavailable toxic forms that are dissolved in the water column, potentially impacting marine ecosystems. It is thus critical to assess the impacts of deep-sea mining on the reactivities and behaviors of crucial elements (e.g., Zn and Cu) and their isotopes during mineral leaching processes. To this end, we conducted leaching experiments using different SMS mineral types (CuFe rich, Fe rich, and ZnFe rich) to assess metal releases and the isotope fractionations of Zn and Cu. Significant correlations were observed between Ni, Cu, Zn, Cd, and Pb concentrations in leachates and the SMSs, suggesting that metal leaching into seawater depended on individual SMS metal content. The Zn and Cu concentrations in leachates varied greatly by both SMS type and the leaching time. Zn concentrations from ZnFe rich SMSs exceeded the recommended effluent limits set by the IFC World Bank and the USEPA. SMS ore leachates exhibited Cu and Zn isotope ratios distinct from those of Indian Ocean deep seawater. The isotope fractionation magnitude (Δore-seawater) of Cu was more pronounced than that of Zn, likely due to the redox process involved in the leaching processes. In contrast, the Zn isotope signatures in leachates conserve those of minerals, although slight isotope fractionations occurred in solution following the adsorption and precipitation processes of Fe-oxyhydroxides. Our findings confirm that leveraging the chemical and isotope signatures of toxic metals offers a valuable approach for assessing the extent of metal contamination of leachates and mine tailings stemming from deep-sea mining operations, concerning their influence on the surrounding water columns.

Clinical feasibility of deep learning based synthetic contrast enhanced abdominal CT in patients undergoing non enhanced CT scans.

Our objective was to develop and evaluate the clinical feasibility of deep-learning-based synthetic contrast-enhanced computed tomography (DL-SynCCT) in patients designated for nonenhanced CT (NECT). We proposed a weakly supervised learning with the utilization of virtual non-contrast CT (VNC) for the development of DL-SynCCT. Training and internal validations were performed with 2202 pairs of retrospectively collected contrast-enhanced CT (CECT) images with the corresponding VNC images acquired from dual-energy CT. Clinical validation was performed using an external validation set including 398 patients designated for true nonenhanced CT (NECT), from multiple vendors at three institutes. Detection of lesions was performed by three radiologists with only NECT in the first session and an additionally provided DL-SynCCT in the second session. The mean peak signal-to-noise ratio (PSNR) and structural similarity index map (SSIM) of the DL-SynCCT compared to CECT were 43.25 ± 0.41 and 0.92 ± 0.01, respectively. With DL-SynCCT, the pooled sensitivity for lesion detection (72.0% to 76.4%, P < 0.001) and level of diagnostic confidence (3.0 to 3.6, P < 0.001) significantly increased. In conclusion, DL-SynCCT generated by weakly supervised learning showed significant benefit in terms of sensitivity in detecting abnormal findings when added to NECT in patients designated for nonenhanced CT scans.

Development of a deep learning-based fully automated segmentation of rotator cuff muscles from clinical MR scans.

BACKGROUND: The fatty infiltration and atrophy in the muscle after a rotator cuff (RC) tear are important in surgical decision-making and are linked to poor clinical outcomes after rotator cuff repair. An accurate and reliable quantitative method should be developed to assess the entire RC muscles. PURPOSE: To develop a fully automated approach based on a deep neural network to segment RC muscles from clinical magnetic resonance imaging (MRI) scans. MATERIAL AND METHODS: In total, 94 shoulder MRI scans (mean age = 62.3 years) were utilized for the training and internal validation datasets, while an additional 20 MRI scans (mean age = 62.6 years) were collected from another institution for external validation. An orthopedic surgeon and a radiologist manually segmented muscles and bones as reference masks. Segmentation performance was evaluated using the Dice score, sensitivities, precision, and percent difference in muscle volume (%). In addition, the segmentation performance was assessed based on sex, age, and the presence of a RC tendon tear. RESULTS: The average Dice score, sensitivities, precision, and percentage difference in muscle volume of the developed algorithm were 0.920, 0.933, 0.912, and 4.58%, respectively, in external validation. There was no difference in the prediction of shoulder muscles, with the exception of teres minor, where significant prediction errors were observed (0.831, 0.854, 0.835, and 10.88%, respectively). The segmentation performance of the algorithm was generally unaffected by age, sex, and the presence of RC tears. CONCLUSION: We developed a fully automated deep neural network for RC muscle and bone segmentation with excellent performance from clinical MRI scans.

Recent advances in biosensors based on metal-oxide semiconductors system-integrated into bioelectronics.

Metal-oxide semiconductors (MOSs) have emerged as pivotal components in technology related to biosensors and bioelectronics. Detecting biomarkers in sweat provides a glimpse into an individual's metabolism without the need for sample preparation or collection steps. The distinctive attributes of this biosensing technology position it as an appealing option for biomedical applications beyond the scope of diagnosis and healthcare monitoring. This review encapsulates ongoing developments of cutting-edge biosensors based on MOSs. Recent advances in MOS-based biosensors for human sweat analyses are reviewed. Also discussed is the progress in sweat-based biosensing technologies to detect and monitor diseases. Next, system integration of biosensors is demonstrated ultimately to ensure the accurate and reliable detection and analysis of target biomarkers beyond individual devices. Finally, the challenges and opportunities related to advanced biosensors and bioelectronics for biomedical applications are discussed.

Perioperative urinary ketosis and metabolic acidosis in patients fasted for undergoing gynecologic surgery.

BACKGROUND: Our bodies have adaptive mechanisms to fasting, in which glycogen stored in the liver and muscle protein are broken down, but also lipid mobilisation is triggered. As a result, glycerol and fatty acids are released into the bloodstream, increasing the production of ketone bodies in liver. However, there are limited studies on the incidence of perioperative urinary ketosis, the intraoperative blood glucose changes and metabolic acidosis after fasting for surgery in non-diabetic adult patients. METHODS: We conducted a retrospective cohort study involving 1831 patients undergoing gynecologic surgery under general anesthesia from January to December 2022. Ketosis was assessed using a postoperative urine test, while blood glucose levels and acid-base status were collected from intraoperative arterial blood gas analyses. RESULTS: Of 1535 patients who underwent postoperative urinalysis, 912 (59.4%) patients had ketonuria. Patients with ketonuria were younger, had lower body mass index, and had fewer comorbidities than those without ketonuria. After adjustments, younger age, higher body mass index and surgery starting late afternoon were significant risk factors for postoperative ketonuria. Of the 929 patients assessed with intraoperative arterial blood gas analyses, 29.0% showed metabolic acidosis. Multivariable logistic regression revealed that perioperative ketonuria and prolonged surgery significantly increased the risk for moderate-to-severe metabolic acidosis. CONCLUSION: Perioperative urinary ketosis and intraoperative metabolic acidosis are common in patients undergoing gynecologic surgery, even with short-term preoperative fasting. The risks are notably higher in younger patients with lower body mass index. Optimization of preoperative fasting strategies including implementation of oral carbohydrate loading should be considered for reducing perioperative metabolic derangement due to ketosis.

Association of epicardial adipose tissue with metabolic risk factors on cardiovascular outcomes: serial coronary computed tomography angiography study.

BACKGROUND/AIMS: Epicardial adipose tissue (EAT) shares pathophysiological properties with other visceral fats and potentially triggers local inflammation. However, the association of EAT with cardiovascular disease (CVD) is still debatable. The study aimed to observe the changes and associations in EAT and risk factors over time, as well as to investigate whether EAT was associated with CVD. METHODS: A total of 762 participants from Seoul National University Hospital (SNUH) and SNUH Gangnam Center were included in this study. EAT was measured using coronary computed tomography angiography. RESULTS: Baseline EAT level was positively associated with body mass index (BMI), calcium score, atherosclerotic cardiovascular disease (ASCVD) 10-year risk score, glucose, triglycerides (TG)/high-density lipoprotein (HDL), but not with total cholesterol, low-density lipoprotein (LDL). At follow-up, EAT levels increased in all groups, with low EAT groups demonstrating a significant increase in EAT per year. Change in EAT was associated with a change in BMI, TG/HDL, and glucose, while changes in LDL, calcium score, and ASCVD 10-year risk score were not associated. Although calcium score and ASCVD 10-year risk score were associated with CVD events, baseline information of EAT, baseline EAT/body surface area, or EAT change was not available. CONCLUSION: Metabolic risks, e.g., BMI, TG/HDL, and glucose, were associated with EAT change per year, whereas classical CVD risks, e.g., LDL, calcium score, and ASCVD 10-year risk score, were not. The actual CVD event was not associated with EAT volume, warranting future studies combining qualitative assessments with quantitative ones.

Fully-automated multi-organ segmentation tool applicable to both non-contrast and post-contrast abdominal CT: deep learning algorithm developed using dual-energy CT images.

A novel 3D nnU-Net-based of algorithm was developed for fully-automated multi-organ segmentation in abdominal CT, applicable to both non-contrast and post-contrast images. The algorithm was trained using dual-energy CT (DECT)-obtained portal venous phase (PVP) and spatiotemporally-matched virtual non-contrast images, and tested using a single-energy (SE) CT dataset comprising PVP and true non-contrast (TNC) images. The algorithm showed robust accuracy in segmenting the liver, spleen, right kidney (RK), and left kidney (LK), with mean dice similarity coefficients (DSCs) exceeding 0.94 for each organ, regardless of contrast enhancement. However, pancreas segmentation demonstrated slightly lower performance with mean DSCs of around 0.8. In organ volume estimation, the algorithm demonstrated excellent agreement with ground-truth measurements for the liver, spleen, RK, and LK (intraclass correlation coefficients [ICCs] > 0.95); while the pancreas showed good agreements (ICC = 0.792 in SE-PVP, 0.840 in TNC). Accurate volume estimation within a 10% deviation from ground-truth was achieved in over 90% of cases involving the liver, spleen, RK, and LK. These findings indicate the efficacy of our 3D nnU-Net-based algorithm, developed using DECT images, which provides precise segmentation of the liver, spleen, and RK and LK in both non-contrast and post-contrast CT images, enabling reliable organ volumetry, albeit with relatively reduced performance for the pancreas.

Bioinspired nanoplatforms for human-machine interfaces: Recent progress in materials and device applications.

The panoramic characteristics of human-machine interfaces (HMIs) have prompted the needs to update the biotechnology community with the recent trends, developments, and future research direction toward next-generation bioelectronics. Bioinspired materials are promising for integrating various bioelectronic devices to realize HMIs. With the advancement of scientific biotechnology, state-of-the-art bioelectronic applications have been extensively investigated to improve the quality of life by developing and integrating bioinspired nanoplatforms in HMIs. This review highlights recent trends and developments in the field of biotechnology based on bioinspired nanoplatforms by demonstrating recently explored materials and cutting-edge device applications. Section 1 introduces the recent trends and developments of bioinspired nanomaterials for HMIs. Section 2 reviews various flexible, wearable, biocompatible, and biodegradable nanoplatforms for bioinspired applications. Section 3 furnishes recently explored substrates as carriers for advanced nanomaterials in developing HMIs. Section 4 addresses recently invented biomimetic neuroelectronic, nanointerfaces, biointerfaces, and nano/microfluidic wearable bioelectronic devices for various HMI applications, such as healthcare, biopotential monitoring, and body fluid monitoring. Section 5 outlines designing and engineering of bioinspired sensors for HMIs. Finally, the challenges and opportunities for next-generation bioinspired nanoplatforms in extending the potential on HMIs are discussed for a near-future scenario. We believe this review can stimulate the integration of bioinspired nanoplatforms into the HMIs in addition to wearable electronic skin and health-monitoring devices while addressing prevailing and future healthcare and material-related problems in biotechnologies.

Validation of real-time inside-out tracking and depth realization technologies for augmented reality-based neuronavigation.

PURPOSE: Concomitant with the significant advances in computing technology, the utilization of augmented reality-based navigation in clinical applications is being actively researched. In this light, we developed novel object tracking and depth realization technologies to apply augmented reality-based neuronavigation to brain surgery. METHODS: We developed real-time inside-out tracking based on visual inertial odometry and a visual inertial simultaneous localization and mapping algorithm. The cube quick response marker and depth data obtained from light detection and ranging sensors are used for continuous tracking. For depth realization, order-independent transparency, clipping, and annotation and measurement functions were developed. In this study, the augmented reality model of a brain tumor patient was applied to its life-size three-dimensional (3D) printed model. RESULTS: Using real-time inside-out tracking, we confirmed that the augmented reality model remained consistent with the 3D printed patient model without flutter, regardless of the movement of the visualization device. The coordination accuracy during real-time inside-out tracking was also validated. The average movement error of the X and Y axes was 0.34 ± 0.21 and 0.04 ± 0.08 mm, respectively. Further, the application of order-independent transparency with multilayer alpha blending and filtered alpha compositing improved the perception of overlapping internal brain structures. Clipping, and annotation and measurement functions were also developed to aid depth perception and worked perfectly during real-time coordination. We named this system METAMEDIP navigation. CONCLUSIONS: The results validate the efficacy of the real-time inside-out tracking and depth realization technology. With these novel technologies developed for continuous tracking and depth perception in augmented reality environments, we are able to overcome the critical obstacles in the development of clinically applicable augmented reality neuronavigation.

Decreased SMP30 Expression Is Related With EMT in the Kidneys of Two Siberian Tigers With CKD.

BACKGROUND/AIM: Chronic kidney disease (CKD) is one of the most common causes of mortality in wild non-domestic felidae. The molecular mechanism regulating renal fibrosis in nephropathy is not fully understood especially in the felidae. This study aimed to elucidate senescence marker protein 30 (SMP30) expression patterns and its relationship with epithelial-mesenchymal transition (EMT) by immunostaining in two necropsied Siberian tigers (Panthera tigris altaica) with CKD. MATERIALS AND METHODS: Two kidney samples from male Siberian tigers were fixed and tissue sections were stained for histopathological assay. RESULTS: In CKD, renal tubular epithelial cells lost their tubular structures surrounded by severe interstitial fibrosis and were detached from the basement membrane. These damaged cells resembled the morphology of mesenchymal cells and showed much lower SMP30 expression compared with intact tubular epithelial cells. These cells also expressed vimentin, which is specifically expressed by mesenchymal cells, and through double staining, it was observed that vimentin was expressed in the tubular epithelial cells where SMP30 was not expressed. In addition, double-positive expression of pan-cytokeratin (pan-CK) and vimentin was found in damaged epithelial cells with mesenchymal features. CONCLUSION: We demonstrated possible evidence to understand the role of SMP30 as a new pivotal factor and the possibility of decreased SMP30 as a potential indicator of EMT at the end stage of CKD.

Three-dimensional body composition parameters using automatic volumetric segmentation allow accurate prediction of colorectal cancer outcomes.

BACKGROUND: Parameters obtained from two-dimensional (2D) cross-sectional images have been used to determine body composition. However, data from three-dimensional (3D) volumetric body images reflect real body composition more accurately and may be better predictors of patient outcomes in cancer. This study aimed to assess the 3D parameters and determine the best predictive factors for patient prognosis. METHODS: Patients who underwent surgery for colorectal cancer (CRC) between 2010 and 2016 were included in this study. Preoperative computed tomography images were analysed using an automatic segmentation program. Body composition parameters for muscle, muscle adiposity, subcutaneous fat (SF) and abdominal visceral fat (AVF) were assessed using 2D images at the third lumbar (L3) level and 3D images of the abdominal waist (L1-L5). The cut-off points for each parameter were determined using X-tile software. A Cox proportional hazards regression model was used to identify the association between the parameters and the treatment outcomes, and the relative influence of each parameter was compared using a gradient boosting model. RESULTS: Overall, 499 patients were included in the study. At a median follow-up of 59 months, higher 3D parameters of the abdominal muscles and SF from the abdominal waist were found to be associated with longer overall survival (OS) and disease-free survival (all P < 0.001). Although the 3D parameters of AVF were not related to survival outcomes, patients with a high AVF volume and mass experienced higher rate of postoperative complications than those with low AVF volume (27.4% vs. 18.7%, P = 0.021, for mass; 27.1% vs. 19.0%, P = 0.028, for volume). Low muscle mass and volume (hazard ratio [HR] 1.959, P = 0.016; HR 2.093, P = 0.036, respectively) and low SF mass and volume (HR 1.968, P = 0.008; HR 2.561, P = 0.003, respectively), both in the abdominal waist, were identified as independent prognostic factors for worse OS. Along with muscle mass and volume, SF mass and volume in the abdominal waist were negatively correlated with mortality (all P < 0.001). Both AVF mass and volume in the abdominal waist were positively correlated with postoperative complications (P < 0.05); 3D muscle volume and SF at the abdominal waist were the most influential factors for OS. CONCLUSIONS: 3D volumetric parameters generated using an automatic segmentation program showed higher correlations with the short- and long-term outcomes of patients with CRC than conventional 2D parameters.

Expired Platelet Concentrate Up-Cycling: Growth Factor-Rich Bioproduct Preparation for FBS Substitute.

Due to the short storage period, large quantities of platelet concentrate (PC) are expiring. The expired PC cannot be injected into a blood vessel, but the activity of bioactive molecules, especially growth factors, is still preserved. In this paper, we organized a process to obtain a growth factor-rich bioproduct for use as a supplement in human cell culture by optimizing freezing, thawing, and sterilization conditions. Each unit of PC displayed visual differences, diverse biochemical values, and growth factor concentrations. To minimize lot-to-lot variation, we pooled a minimum of 10 PC units. The concentrations of growth factors were maximized through five freeze-thaw cycles for 12 h at -80 °C for freezing and for 5 min at 36 °C for thawing. We used a cell strainer with 40 µm pores, followed by a 0.45 µm filter and a 0.22 µm filter sequentially to sterilize the bioproduct with minimizing loss. The obtained growth factors remained stable for 4-6 h at room temperature (23 °C), 24 h at 4 °C, and 12 months at -80 °C. Cellular responses to the growth factor-rich bioproduct were tested with primary human renal proximal tubule epithelial cells. The cells exhibited a significantly increased growth rate, compared to the fetal bovine serum (FBS)-treated control group. The cells maintained their characteristic cuboidal shape, and stem cells and renal progenitor cells also preserved their genetic characteristics during culture. Therefore, the growth factor-rich bioproduct isolated from expired PC through our process can be used as a medium supplement to replace FBS in human cell culture for clinical application.

Comparison of Light-Sheet Fluorescence Microscopy and Fast-Confocal Microscopy for Three-Dimensional Imaging of Cleared Mouse Brain.

Whole-brain imaging is important for understanding brain functions through deciphering tissue structures, neuronal circuits, and single-neuron tracing. Thus, many clearing methods have been developed to acquire whole-brain images or images of three-dimensional thick tissues. However, there are several limitations to imaging whole-brain volumes, including long image acquisition times, large volumes of data, and a long post-image process. Based on these limitations, many researchers are unsure about which light microscopy is most suitable for imaging thick tissues. Here, we compared fast-confocal microscopy with light-sheet fluorescence microscopy for whole-brain three-dimensional imaging, which can acquire images the fastest. To compare the two types of microscopies for large-volume imaging, we performed tissue clearing of a whole mouse brain, and changed the sample chamber and low- magnification objective lens and modified the sample holder of a light-sheet fluorescence microscope. We found out that light-sheet fluorescence microscopy using a 2.5× objective lens possesses several advantages, including saving time, large-volume image acquisitions, and high Z-resolution, over fast-confocal microscopy, which uses a 4× objective lens. Therefore, we suggest that light-sheet fluorescence microscopy is suitable for whole mouse brain imaging and for obtaining high-resolution three-dimensional images.

Ultrafast MRI and T1 and T2 Radiomics for Predicting Invasive Components in Ductal Carcinoma in Situ Diagnosed With Percutaneous Needle Biopsy.

OBJECTIVE: This study aimed to investigate the feasibility of ultrafast magnetic resonance imaging (MRI) and radiomic features derived from breast MRI for predicting the upstaging of ductal carcinoma in situ (DCIS) diagnosed using percutaneous needle biopsy. MATERIALS AND METHODS: Between August 2018 and June 2020, 95 patients with 98 DCIS lesions who underwent preoperative breast MRI, including an ultrafast sequence, and subsequent surgery were included. Four ultrafast MRI parameters were analyzed: time-to-enhancement, maximum slope (MS), area under the curve for 60 s after enhancement, and time-to-peak enhancement. One hundred and seven radiomic features were extracted for the whole tumor on the first post-contrast T1WI and T2WI using PyRadiomics. Clinicopathological characteristics, ultrafast MRI findings, and radiomic features were compared between the pure DCIS and DCIS with invasion groups. Prediction models, incorporating clinicopathological, ultrafast MRI, and radiomic features, were developed. Receiver operating characteristic curve analysis and area under the curve (AUC) were used to evaluate model performance in distinguishing between the two groups using leave-one-out cross-validation. RESULTS: Thirty-six of the 98 lesions (36.7%) were confirmed to have invasive components after surgery. Compared to the pure DCIS group, the DCIS with invasion group had a higher nuclear grade (P < 0.001), larger mean lesion size (P = 0.038), larger mean MS (P = 0.002), and different radiomic-related characteristics, including a more extensive tumor volume; higher maximum gray-level intensity; coarser, more complex, and heterogeneous texture; and a greater concentration of high gray-level intensity. No significant differences in AUCs were found between the model incorporating nuclear grade and lesion size (0.687) and the models integrating additional ultrafast MRI and radiomic features (0.680-0.732). CONCLUSION: High nuclear grade, larger lesion size, larger MS, and multiple radiomic features were associated with DCIS upstaging. However, the addition of MS and radiomic features to the prediction model did not significantly improve the prediction performance.

Study protocol for prospective multi-institutional phase III trial of standard of care therapy with or without stereotactic ablative radiation therapy for recurrent ovarian cancer (SABR-ROC).

BACKGROUND: Efforts have been made to investigate the role of salvage radiotherapy (RT) in treating recurrent ovarian cancer (ROC). Stereotactic ablative radiation therapy (SABR) is a state-of-the-art therapy that uses intensity modulation to increase the fractional dose, decrease the number of fractions, and target tumors with high precision. METHODS: The SABR-ROC trial is a phase 3, multicenter, randomized, prospective study to evaluate whether the addition of SABR to the standard of care significantly improves the 3-year overall survival (OS) of patients with ROC. Patients who have completed the standard treatment for primary epithelial ovarian cancer are eligible. In addition, patients with number of metastases ≤ 10 and maximum diameter of each metastatic site of gross tumor ≤ 5 cm are allowed. Randomization will be stratified by (1) No. of the following clinical factors met, platinum sensitivity, absence of ascites, normal level of CA125, and ECOG performance status of 0-1; 0-3 vs. 4; (2) site of recurrence; with vs. without lymph nodes; and (3) PARP inhibitor; use vs. non-use. The target number of patients to be enrolled in this study is 270. Participants will be randomized in a 1:2 ratio. Participants in Arm 2 will receive SABR for recurrent lesions clearly identified in imaging tests as well as the standard of care (Arm 1) based on treatment guidelines and decisions made in multidisciplinary discussions. The RT fraction number can range from 1 to 10, and the accepted dose range is 16-45 Gy. The RT Quality Assurance (QA) program consists of a three-tiered system: general credentialing, trial-specific credentialing, and individual case reviews. DISCUSSION: SABR appears to be preferable as it does not interfere with the schedule of systemic treatment by minimizing the elapsed days of RT. The synergistic effect between systemic treatment and SABR is expected to reduce the tumor burden by eradicating gross tumors identified through imaging with SABR and controlling microscopic cancer with systemic treatment. It might also be beneficial for quality-of-life preservation in older adults or heavily treated patients. TRIAL REGISTRATION: This trial was registered at ClinicalTrials.gov (NCT05444270) on June 29th, 2022.