Computer-aided superimposition of the frontal sinus via 3D reconstruction for comparative forensic identification.

The anatomical uniqueness of the frontal sinus morphology has been widely used for comparative forensic identification using various techniques, mostly including 2D X-rays or one fixed slice of an axial computed tomography (CT) scan image. However, computer-aided 3D automatic graphical comparison techniques can provide accurate comparisons between two 3D models that allow users to comply with even the strictest deviation standards, avoiding error-prone identification of frontal sinuses with similar morphologies. The study proposes the use of a computer-aided comparative paradigm based on the 3D-3D frontal sinus model superimposition process and further assesses the anatomical uniqueness of frontal sinuses using a large Chinese Han sample. Three hundred thirty-six patients older than 20 years with two multi-slice CT scans were collected. Frontal sinus 3D models were semi-automatically segmented through Dolphin Imaging software. Automatic pairwise comparisons of 336 matched pairs from the same person and 340 mismatched pairs from different individuals with an analysis of average root mean square (RMS) point-to-point distance were performed using Geomagic Studio Qualify software. RMS ranged between 0.005 and 1.032 (mean RMS 0.390 ± 0.25 mm) in the group of matches and between 1.107 and 19.363 (mean RMS 4.49 ± 2.69 mm) in the group of mismatches. On average, the RMS value was over ten-fold greater in mismatches than in matches. Statistically significant differences in RMS between the group of matches and mismatches were assessed using the Mann-Whitney U test (p < 0.05). This study supports the value of the frontal sinus with a 3D computer-aided superimposition method for human identification with large samples when DNA, fingerprints, and dental materials are not accessible.

An up-to-date view of paclitaxel-induced peripheral neuropathy.

Chemotherapy-induced peripheral neuropathy (CIPN),referring to the damage to the peripheral nerves caused by exposure to a neurotoxic chemotherapeutic agent, is a common side effect amongst patients undergoing chemotherapy. Paclitaxel-induced peripheral neuropathy (PIPN) can lead to dose reduction or early cessation of chemotherapy, which is not conducive to patients'survival. Even after treatment is discontinued, PIPN symptoms carried a greater risk of worsening and plagued the patient's life, leading to long-term morbidity in survivors. Here, we summarize the research progress for clinical manifestations, risk factors, pathogenesis, prevention and treatment of PIPN, so as to embark on the path of preventing PIPN with prolongation of patient's life quality on a long-term basis.

A fully automated sex estimation for proximal femur X-ray images through deep learning detection and classification.

PURPOSE: To develop a fully automated deep learning pipeline using digital radiographs to detect the proximal femur region for accurate automated sex estimation. METHOD: Radiograph predictive features from 2122 Chinese Han clinical pelvic with ages ranging from 18 to 26 years were collected retrospectively to train and test the sex prediction model using deep machine learning's convolutional neural networks (CNN). Model performance was assessed using a Chinese Han population with 361 samples and a white population with 50 samples. The average accuracy of the sex estimation of the two test datasets was determined. RESULTS: For the Chinese Han population test dataset, the sex estimation accuracy was 94.6% (males: 93.9% and females: 94.7%). For the white population samples, the accuracy of sex estimation was 82.9% (males: 80.9% and females: 88.6%). The accuracy of CNN tested in the Chinese population was significantly higher than that tested in the White population (p < 0.001) CONCLUSIONS: The model based on convolutional neural networks has an accuracy similar to that of current state-of-the-art mathematical functions using manually extracted features for the Chinese Han population samples, proving to be a reliable choice for the human sex estimation.

Microfluidic devices with disposable enzyme electrode for electrochemical monitoring of glucose concentrations.

This article describes the fabrication of tube-like microchannels made of UV curable polymer on a glass substrate and the device assembling with a disposable enzyme-working electrode for high-sensitivity electrochemical detection. While both reference and counter electrodes are patterned on the surface of the glass substrate, the working electrode is flipped on the top of the channel with an open access, providing a face-to-face probing configuration. When the enzyme electrode is contaminated or degraded, it can be easily replaced by a new one, keeping the main body of the device and the detection schema unchanged. Using glucose oxidase-coated gold electrodes, we were able to determine a linear amperometry response to the glucose concentrations in the range of 2-16 mM. By replacing the as-prepared working electrode by the one after thermal treatments, we showed a much more degraded enzyme electrode activity, enabling efficient determination of the electrode quality as well as the whole process optimization.