Microsurgical Tool Detection and Characterization in Intra-operative Neurosurgical Videos.

Brain surgery is complex and has evolved as a separate surgical specialty. Surgical procedures on the brain are performed using dedicated micro-instruments which are designed specifically for the requirements of operating with finesse in a confined space. The usage of these microsurgical tools in an operating environment defines the surgical skill of a surgeon. Video recordings of micro-surgical procedures are a rich source of information to develop automated surgical assessment tools that can offer continuous feedback for surgeons to improve their skills, effectively increase the outcome of the surgery, and make a positive impact on their patients. This work presents a novel deep learning system based on the Yolov5 algorithm to automatically detect, localize and characterize microsurgical tools from recorded intra-operative neurosurgical videos. The tool detection achieves a high 93.2% mean average precision. The detected tools are then characterized by their on-off time, motion trajectory and usage time. Tool characterization from neurosurgical videos offers useful insight into the surgical methods employed by a surgeon and can aid in their improvement. Additionally, a new dataset of annotated neurosurgical videos is used to develop the robust model and is made available for the research community.Clinical relevance- Tool detection and characterization in neurosurgery has several online and offline applications including skill assessment and outcome of the surgery. The development of automated tool characterization systems for intra-operative neurosurgery is expected to not only improve the surgical skills of the surgeon, but also leverage in training the neurosurgical workforce. Additionally, dedicated neurosurgical video based datasets will, in general, aid the research community to explore more automation in this field.

Food Detection and Segmentation from Egocentric Camera Images.

Tracking an individual's food intake provides useful insight into their eating habits. Technological advancements in wearable sensors such as the automatic capture of food images from wearable cameras have made the tracking of food intake efficient and feasible. For accurate food intake monitoring, an automated food detection technique is needed to recognize foods from unstaged real-world images. This work presents a novel food detection and segmentation pipeline to detect the presence of food in images acquired from an egocentric wearable camera, and subsequently segment the food image. An ensemble of YOLOv5 detection networks is trained to detect and localize food items among other objects present in captured images. The model achieves an overall 80.6% mean average precision on four objects-Food, Beverage, Screen, and Person. Post object detection, the predicted food objects which are sufficiently sharp were considered for segmentation. The Normalized-Graph-Cut algorithm was used to segment the different parts of the food resulting in an average IoU of 82%.Clinical relevance- The automatic monitoring of food intake using wearable devices can play a pivotal role in the treatment and prevention of eating disorders, obesity, malnutrition and other related issues. It can aid in understanding the pattern of nutritional intake and make personalized adjustments to lead a healthy life.

The temperature and pH repertoire of the transglutaminase family is expanding.

Transglutaminases (TGs) play important roles in the food industry, pharmacology, and biotechnology, but as protein cross-linkers, their complexes are stable, resistant, immunogenic, and potentially pathogenic. Many TGs have been characterized, but they operate in narrow temperature and pH range limits. In a research article in this issue, Clemens Furnes and colleagues describe a novel cold-adapted TG from Atlantic cod, which expands the operating boundaries to a lower temperature and a wider pH. In this accompanying commentary, we discuss how this TG opens new applications in cold environments and can be deactivated by heating. New sources of TGs should be explored in hot environments like hot springs, in order to increase the temperature and widen the pH ranges for human and industrial benefits.

The Revival of the Battle between David and Goliath in the Enteric Viruses and Microbiota Struggle: Potential Implication for Celiac Disease.

The human gut is inhabited by overcrowded prokaryotic communities, a major component of which is the virome, comprised of viruses, bacteriophages, archaea, eukaryotes and bacteria. The virome is required for luminal homeostasis and, by their lytic or synergic capacities, they can regulate the microbial community structure and activity. Dysbiosis is associated with numerous chronic human diseases. Since the virome can impact microbial genetics and behavior, understanding its biology, composition, cellular cycle, regulation, mode of action and potential beneficial or hostile activities can change the present paradigm of the cross-talks in the luminal gut compartment. Celiac disease is a frequent autoimmune disease in which viruses can play a role in disease development. Based on the current knowledge on the enteric virome, in relation to celiac disease pathophysiological evolvement, the current review summarizes the potential interphases between the two. Exploring and understanding the role of the enteric virome in gluten-dependent enteropathy might bring new therapeutic strategies to change the luminal eco-event for the patient's benefit.

Serologic Diagnosis of Celiac Disease: New Biomarkers.

Most patients affected by celiac disease (CD) are asymptomatic or hyposymptomatic and undiagnosed, and are at risk of preventable complications. Therefore, early diagnosis is highly recommended. Multiple diagnostic antibodies are available; the most frequently used is IgA to tissue transglutaminase (IgA-tTg). It may yield false results and, alone, does not address IgA deficiency. Recently, a new generation of anti-neo-epitope tTg check (IgG + IgA) has become available. It is highly sensitive and specific, covers IgA-deficient patients with CD, reflects intestinal damage, and has predictive potential in the diagnosis of CD.

A variant in a cis-regulatory element enhances claudin-14 expression and is associated with pediatric-onset hypercalciuria and kidney stones.

The greatest risk factor for kidney stones is hypercalciuria, the etiology of which is largely unknown. A recent genome-wide association study (GWAS) linked hypercalciuria and kidney stones to a claudin-14 (CLDN14) risk haplotype. However, the underlying molecular mechanism was not delineated. Recently, renal CLDN14 expression was found to increase in response to increased plasma calcium, thereby inducing calciuria. We hypothesized therefore that some children with hypercalciuria and kidney stones harbor a CLDN14 variant that inappropriately increases gene expression. To test this hypothesis, we sequenced the CLDN14 risk haplotype in a cohort of children with idiopathic hypercalciuria and kidney stones. An intronic SNP was more frequent in affected children. Dual luciferase and cell-based assays demonstrated increased reporter or CLDN14 expression when this polymorphism was introduced. In silico studies predicted the SNP introduced a novel insulinoma-associated 1 (INSM1) transcription factor binding site. Consistent with this, repeating the dual luciferase assay in the presence of INSM1 further increased reporter expression. Our data suggest that children with the INSM1 binding site within the CLDN14 risk haplotype have a higher likelihood of hypercalciuria and kidney stones. Enhanced CLDN14 expression may play a role in the pathophysiology of their hypercalciuria.

A disulfide bond in the TIM23 complex is crucial for voltage gating and mitochondrial protein import.

Tim17 is a central, membrane-embedded subunit of the mitochondrial protein import machinery. In this study, we show that Tim17 contains a pair of highly conserved cysteine residues that form a structural disulfide bond exposed to the intermembrane space (IMS). This disulfide bond is critical for efficient protein translocation through the TIM23 complex and for dynamic gating of its preprotein-conducting channel. The disulfide bond in Tim17 is formed during insertion of the protein into the inner membrane. Whereas the import of Tim17 depends on the binding to the IMS protein Mia40, the oxidoreductase activity of Mia40 is surprisingly dispensable for Tim17 oxidation. Our observations suggest that Tim17 can be directly oxidized by the sulfhydryl oxidase Erv1. Thus, import and oxidation of Tim17 are mediated by the mitochondrial disulfide relay, though the mechanism by which the disulfide bond in Tim17 is formed differs considerably from that of soluble IMS proteins.

Import of proteins into isolated yeast mitochondria.

Mitochondria are essential organelles of eukaryotic cells. The vast majority of mitochondrial proteins is encoded within the nuclear genome and translocated into various mitochondrial compartments after translation in the cytosol as preproteins. Even in rather primitive eukaryotes like yeasts, there are 700-1,000 different proteins that need to be recognized in the cytosol, directed to the protein translocases in the two mitochondrial membranes and sorted to their appropriate mitochondrial subcompartment. In vitro reconstituted import systems have proved to be important tools to study these processes in detail. Using isolated mitochondria and radioactively labeled precursor proteins, it was possible to identify several import machineries and pathways consisting of a large number of components during the last few decades.