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Particulate Al2O3 matrix nanocomposites containing 1 vol.%Ni were prepared by the heterogeneous precipitation method and the addition of 5 vol.% ZrO2 (ANZ) or 1 vol.% Cr2O3 (ANC). The prepared samples were subjected to the low energy drop weight impact tests to compare the behaviour of the composites under low energy impact and to investigate the damage mechanisms. The pure Al2O3, Al2O3/Ni, Al2O3/ZrO2 and Al2O3/Cr2O3 compositions with the same additive ratios were also produced to make the comparison systematically. Also, the Vickers hardness measurements were carried out and a significant increase in hardness was attained for both ANZ and ANC composites. The average hardness value around 24.8±1.0GPa was measured for the ANZ and ANC composites which means ~15% improvement compared to the pure Al2O3. Between all the compositions, the maximum force (Fmax) value was obtained for the ANZ (for 12 J impact energy level Fmax = 26617N) according to the low energy drop weight impact test results. Tensile radial crack network formation, cone formation, fracture and crushing of the cone structure were observed as damage mechanisms for all compositions. The volume of conical frustum structure was evaluated for each composition and the effect of microstructure on possible ballistic performance was also discussed.

Objective: Our aim was to predict these stages of hepatic fibrosis and necroinflammation using measurements from two-dimensional shear wave elastography (2D-SWE), transient elastography (Fibroscan, TE), and shear wave dispersion (SWD)., Materials and Methods: In this prospectively designed study, chronic liver patients with nonspecific etiology whose biopsy was performed for up to 1 week were included. Two-dimensional SWE, SWD, and TE measurements were performed. The METAVIR and F-ISHAK classification was used for histopathological evaluation., Results: Two-dimensional SWE and TE were considered significant for detecting hepatic fibrosis. In distinguishing ≥F2, for 2D-SWE, area under the receiver operating characteristics (AUROC) was 0.86 (confidence interval [CI], 0.75-0.96) for the cutoff value of 8.05 kPa ( P = 0.003); for TE, AUROC was 0.79 (CI, 0.65-0.94) for the cutoff value of 10.4 kPa ( P < 0.001). No significance was found for TE in distinguishing ≥F3 ( P = 0.132). However, for 2D-SWE, a cutoff value of 10.45 kPa ( P < 0.001), with AUROC = 0.87 (CI, 0.78-0.97) was determined for ≥F3. Shear wave dispersion was able to determine the presence of necroinflammation ( P = 0.016) and a cutoff value of 15.25 (meter/second)/kiloHertz ([m/s]/kHz) ( P = 0.006) and AUROC of 0.71 (CI, 0.57-0.85) were calculated for distinguishing ≥A2. In addition, a cutoff value of 17.25 (m/s)/kHz ( P = 0.023) and AUROC = 0.72 (CI, 0.51-0.93) were found to detect severe necroinflammation. The cutoff value for SWD was 15.25 (m/s)/kHz ( P = 0.013) for detecting ≥A2 in the reversible stage of fibrosis (F0, F1, and F2), and AUROC = 0.72 (CI, 0.56-0.88)., Conclusions: Two-dimensional SWE and TE measurements were significant in detecting the irreversible stage and the stage that should be treated in hepatic fibrosis noninvasively. Shear wave dispersion measurements were significant in detecting necroinflammation noninvasively., Competing Interests: The authors declare no conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Introduction: The aim of the study was to develop deep-learning neural networks to guide treatment decisions and for the accurate evaluation of tumor response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer using magnetic resonance (MR) images., Methods: Fifty-nine tumors with stage 2 or 3 rectal cancer that received nCRT were retrospectively evaluated. Pathological tumor regression grading was carried out using the Dworak (Dw-TRG) guidelines and served as the ground truth for response predictions. Imaging-based tumor regression grading was performed according to the MERCURY group guidelines from pre-treatment and post-treatment para-axial T2-weighted MR images (MR-TRG). Tumor signal intensity signatures were extracted by segmenting the tumors volumetrically on the images. Normalized histograms of the signatures were used as input to a deep neural network (DNN) housing long short-term memory (LSTM) units. The output of the network was the tumor regression grading prediction, DNN-TRG., Results: In predicting complete or good response, DNN-TRG demonstrated modest agreement with Dw-TRG (Cohen's kappa= 0.79) and achieved 84.6% sensitivity, 93.9% specificity, and 89.8% accuracy. MR-TRG revealed 46.2% sensitivity, 100% specificity, and 76.3% accuracy. In predicting a complete response, DNN-TRG showed slight agreement with Dw-TRG (Cohen's kappa= 0.75) with 71.4% sensitivity, 97.8% specificity, and 91.5% accuracy. MR-TRG provided 42.9% sensitivity, 100% specificity, and 86.4% accuracy. DNN-TRG benefited from higher sensitivity but lower specificity, leading to higher accuracy than MR-TRG in predicting tumor response., Conclusion: The use of deep LSTM neural networks is a promising approach for evaluating the tumor response to nCRT in rectal cancer.

Mandibular fractures are one of the most frequently observed injuries within craniofacial region mostly due to tumor-related problems and traumatic events, often related to non-linear effects like impact loading. Therefore, a validated digital twin of the mandible is required to develop the best possible patient-specific treatment. However, there is a need to obtain a fully compatible numerical model that can reflect the patients' characteristics, be available and accessible quickly, require an acceptable level of modeling efforts and knowledge to provide accurate, robust and fast results at the same time under highly non-linear effects. In this study, a validated simulation methodology is suggested to develop a digital twin of mandible, capable of predicting the non-linear response of the biomechanical system under impact loading, which then can be utilized to design treatment strategies even for multiple fractures of the mandibular system. Using Computed Tomography data containing cranial (skull) images of a patient, a 3-dimensional mandibular model, which consists cortical and cancellous bones, disks and fossa is obtained with high accuracy that is compatible with anatomical boundaries. A Finite Element Model (FEM) of the biomechanical system is then developed for a three-level validation procedure including (A) modal analysis, (B) dynamic loading and (C) impact loading. For the modal analysis stage: Free-free vibration modes and frequencies of the system are validated against cadaver test results. For the dynamic loading stage: Two different regions of the mandible are loaded, and maximum stress levels of the system are validated against finite element analyses (FEA) results, where the first loading condition (i) transfers a 2000 N force acting on the symphysis region and, the second loading condition (ii) transfers a 2000 N force acting on the left body region. In both cases, equivalent muscle forces dependent on time are applied. For the impact loading stage: Thirteen different human mandibular models with various tooth deficiencies are used under the effects of traumatic impact forces that are generated by using an impact hammer with different initial velocities to transfer the impulse and momentum, where contact forces and fracture patterns are validated against cadaver tests. Five different anatomical regions are selected as the impact site. The results of the analyzes (modal, dynamic and impact) performed to validate the digital twin model are compared with the similar FEA and cadaver test results published in the literature and the results are found to be compatible. It has been evaluated that the digital twin model and numerical models are quite realistic and perform well in terms of predicting the biomechanical behavior of the mandible. The three-level validation methodology that is suggested in this research by utilizing non-linear FEA has provided a reliable road map to develop a digital twin of a biomechanical system with enough confidence that it can be utilized for similar structures to offer patient-specific treatments and can help develop custom or tailor-made implants or prosthesis for best compliance with the patient even considering the most catastrophic effects of impact related trauma., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Objective: Lung adenocarcinomas are divided into acinar, lepidic, papillary, micropapillary, and solid predominant subtypes according to the current World Health Organization (WHO) classification. We designed this retrospective study to demonstrate profiles of MUC expression (MUC1, MUC2, MUC5AC, and MUC6) of different histologic patterns within the same tumor among pulmonary adenocarcinomas and investigate correlations of MUC expression with clinicopathologic features., Material and Method: We analyzed the expression of mucins (MUC1, MUC2, MUC5AC, and MUC6) in a series of 99 resected lung adenocarcinomas, which included a total of 193 patterns (71 acinar, 30 lepidic, 25 papillary, 20 micropapillary, 34 solid and 13 mucinous) and calculated a final immune reactivity score (FIRS) per tumor., Results: MUC1 IRS scores were significantly higher in lepidic and solid patterns compared with mucinous patterns (p=0.013). MUC2 expression was seen only in three cases (1 acinar, 2 mucinous). MUC5AC and MUC2 expression was more common in mucinous patterns (p < 0.001 and p=0.028, respectively). MUC6 expression was only detected in seven patterns and the expression was weak. No significant difference was seen among histologic patterns for the staining scores of MUC6. Mucinous adenocarcinoma differed from other histologic subtypes regarding MUC1 and MUC5AC expression. Mucinous adenocarcinoma showed less MUC1 expression with lower IRS scores and higher MUC5AC expression. Tumor size (p=0.006), lymphatic invasion (p=0.018), vascular invasion (p=0.025), perineural invasion (p=0.019), MUC1 IRS scores (p=0.018), and MUC1 IRS scores > 8.5 (p=0.018) were significant predictors for lymph node metastasis., Conclusion: An alternative scoring for MUC1 can be used as a predictor for lymph node metastasis regardless of the histologic subtype.

Objective: To document and analyze diagnostic accuracy of renal core biopsy (RCB), its diagnostic correlation with resection specimens, and to question the need for immunohistochemistry (IHC) in the preoperative diagnosis of renal masses., Material and Method: RCBs performed at a reference center between 2007 and 2017 were included. Pathological, clinical, and radiological data were obtained from medical records., Results: Among 302 biopsies included in this study, 274 (90.7%) were diagnostic. Two hundred sixty-six were neoplastic and 179 were of primary renal origin. The most common secondary neoplasms were hematolymphoid (n = 35) and metastatic (n = 17). Sixty-nine tumors were classified as small renal masses (SRMs) (≤4 cm in diameter) and 53 of them were malignant. Nephrectomy was performed in 58 patients. Overall diagnostic accuracy between resections and RCBs was 88.7%. IHC was performed in 160 (53%) cases. In 15 of those, a definite diagnosis could not be rendered. Renal cell origin and subtype were determined by histomorphology alone in 81 and 75 cases, respectively. Sixty primary neoplasms of renal cell origin required IHC for diagnosis., Conclusion: RCB is a safe and highly accurate method for the diagnosis of both primary and secondary renal neoplasms. IHC is mostly required for the diagnosis of secondary tumors. Histomorphology is still the primary diagnostic tool, highly dependent on the experience of the surgical pathologist., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Abstract: Surgical resection is an unavoidable part of the current treatment options for Crohn's disease (CD), and more than half of patients develop recurrence. The aim of this study was to investigate the predictors for recurrence in the long-term follow-up of CD patients after surgery.Medical records of consecutive CD patients who were operated on between January 2003 and January 2015 were retrospectively analyzed. Data including demographic and clinical characteristics of the patients were recorded. Recurrence was evaluated based on the Crohn's Disease Activity Index or endoscopic findings.The majority of 112 patients were males (n = 64, 57.1%), and 61 (54.4%) of them were active smokers. The median follow-up was 113 (range: 61-197) months. Disease recurrence occurred in 16 (14.3%) patients at a median of 13.5 months. The endoscopic recurrence rate was 8% (n = 9) at 1 year, 12.5% (n = 14) at 5 years, and 13.4% (n = 15) at 10 years. One (0.9%) patient underwent colonoscopic balloon dilatation at 1 year, and 7 (6.3%) patients needed re-resection at a median of 36 months. The age of the patient at the time of diagnosis (P = .033), penetrating disease behavior (P = .011), intra-abdominal abscess (P = 0.040) and, concomitant fistula and intra-abdominal abscess (P = .017) were associated with disease recurrence.Our study results suggest that the patients' age at the time of diagnosis, penetrating disease, intra-abdominal abscess, and concomitant fistula and abscess are the risk factors for CD recurrence after surgery., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.)

Objectives: This study aims to improve the diagnosis of gastrointestinal (GI) cytomegalovirus (CMV) disease. It presents the results of a novel study in which CMV blood viral load (BVL), tissue viral load (TVL) determined by PCR and hematoxylin-eosin (HE)/immunohistochemistry (IHC) results of GI biopsies are examined comparatively., Methods: CMV DNA was investigated by quantitative real-time PCR in blood and GI biopsy specimens of 76 patients suspected of CMV disease. Biopsies were also performed HE/IHC stainings in the pathology laboratory., Results: This study included 76 patients whose median age was 34.5 years and 58% (44) were male. Tissue CMV PCR positivity was detected in the highest colon (40/53;75.5%) samples. HE, IHC, blood and tissue CMV PCR positivity rates of all samples were 15.8, 25, 50 and 71.1%, respectively. When IHC was used as the gold standard test for ROC analysis, the optimal cutoff values for the maximum sensitivity and specificity for BVL and TVL were 1.91 log10 copies/ml and 3.82 log10 copies/mg, respectively. Sensitivity and specificity for the cutoff value of tissue CMV DNA were 78.9 and 74.3%, respectively (P < 0.001)., Conclusion: In this study, CMV DNA was detected in 71.1% of the tissue samples of the cases by PCR. Since the sensitivity of the histopathological examinations accepted as the gold standard is low, simultaneous with the histopathological examinations, determination of BVL, TVL and the identification of optimal cutoff values have been shown to support the diagnosis of GI CMV disease.