New prophylaxis regimen for SARS-CoV-2 infection in health professionals with low doses of hydroxychloroquine and bromhexine: a randomised, double-blind placebo clinical trial (ELEVATE Trial).

INTRODUCTION: SARS-CoV-2 infection in Mexico has caused ~2.7 million confirmed cases; around 20%-25% of health workers will be infected by the virus at their workplace, with approximately 4.4% of mortality. High infectivity of SARS-CoV-2 is related with cell entry mechanism, through the ACE receptor. SARS-CoV-2 requires transmembrane protease serine 2 to cleave its spike glycoprotein and ensure fusion of host cell and virus membrane. We propose studying prophylactic treatment with hydroxychloroquine (HCQ) and bromhexine (BHH), which have been shown to be effective in preventing SARS-CoV-2 infection progression when administered in early stages. The aim of this study is to assess the efficacy of HCQ and BHH as prophylactic treatments for SARS-CoV-2 infection in healthy health workers exposed to the virus. METHODS AND ANALYSIS: Double-blind randomised clinical trial, with parallel allocation at a 1:1 ratio with placebo, of low doses of HCQ plus BHH, for 60 days. Study groups will be defined as follows: (1) HCQ 200 mg/day+BHH 8 mg/8 hours versus (2) HCQ placebo plus BHH placebo. Primary endpoint will be efficacy of both interventions for the prevention of SARS-CoV-2 infection, determined by the risk ratio of infected personnel and the absolute risk. At least a 16% reduction in absolute risk is expected between the intervention and placebo groups; a minimum of 20% infection is expected in the placebo group. The sample size calculation estimated a total of 214 patients assigned: two groups of 107 participants each. ETHICS AND DISSEMINATION: This protocol has been approved by the local Medical Ethics Committee (National Institute of Rehabilitation 'Luis Guillermo Ibarra Ibarra', approval number INRLGII/25/20) and by the Federal Commission for Protection against Sanitary Risks (COFEPRIS, approval number 203 300 410A0058/2020). The results of the study will be submitted for publication in peer-reviewed journals and disseminated through conferences. TRIAL REGISTRATION NUMBER: NCT04340349.

Improved Surface-Based Registration of CT and Intraoperative 3D Ultrasound of Bones.

The intraoperative registration of preoperative CT volumes is a key process of most computer-assisted orthopedic surgery (CAOS) systems. In this work, is reported a new method for automatic registration of long bones, based on the segmentation of the bone cortical in intraoperative 3D ultrasound images. A bone classifier was developed based on features, obtained from the principal component analysis of the Hessian matrix, of every voxel in an intraoperative ultrasound volume. 3D freehand ultrasound was used for the acquisition of the intraoperative ultrasound volumes. Corresponding bone surface segmentations in ultrasound and preoperative CT imaging were used for the intraoperative registration. Validation on a phantom of the tibia produced encouraging results, with a maximum mean segmentation error of 0.34⁡mm (SD=0.26⁡mm) and a registration accuracy error of 0.64⁡mm (SD=0.49⁡mm).

Molecular and clinical analysis in a series of patients with Pyknodysostosis reveals some uncommon phenotypic findings.

Pyknodysostosis is a rare autosomal recessive skeletal dysplasia characterized by short stature, deformity of the skull, osteosclerosis, hypoplasia of the clavicle, and bone fragility. Radiographs show increased bone density, osteosclerosis, and acroosteolysis of the terminal phalanges. The pycnodysostosis gene is located on chromosome 1q21 and encodes an enzyme called Cathepsin K. Cathepsin K is a cysteine protease lysosomal protein associated with the degradation of bone and cartilage. In the current study, the authors described the clinical, radiological and molecular features of a group of six Mexican patients, including two familial and two sporadic cases, with Pyknodysostosis. One of the patients presented hypoacusia, an unusual finding in this disease.

Computer assisted biopsy of breast tumors.

In this paper we report our preliminary results of the development of a computer assisted system for breast biopsy. The system is based on tracked ultrasound images of the breast. A three dimensional ultrasound volume is constructed from a set of tracked B-scan images acquired with a calibrated probe. The system has been designed to assist a radiologist during breast biopsy, and also as a training system for radiology residents. A semiautomatic classification algorithm was implemented to assist the user with the annotation of the tumor on an ultrasound volume. We report the development of the system prototype, tested on a physical phantom of a breast with a tumor, made of polivinil alcohol.