Detection and Analysis of Low Energy Electrons in a Scanning Electron Microscope using a novel detector design based on the Bessel Box Energy Analyser

Advancements in the field of scanning electron microscopy have been one of the major nano technology enablers. A scanning electron microscope (SEM) generates a magnified image of the sample by bombarding it with an electron beam and detecting the electrons that scatter off the surface along with the electrons that are generated in the sample. In conventional SEMs, the generated or secondary electrons are detected by the famous Everhart Thornley detector via positively biased input-grid. However, in doing so, it loses energy and angular information of the electrons. This information is crucial to interpret the SEM image of the sample under study. What is needed is a small and compact detector that can detect electrons and furnish energy information inside an SEM chamber. The detector designed to achieve these aims is able to detect low energy electrons at the same time able to take the geometrical constraints of the SEM into account. This study presents a design and implementation of a novel secondary electron detector based on the Bessel Box (BB) energy analyser for SEM Simulations were carried out for the design in SIMION 8.1 ray tracing software. An energy resolution of 0.4% has been numerically calculated and experimentally tested in an ultra-high-vacuum chamber. This was followed by the integration of the BB detector to a conventional scanning electron microscope. The device described would be appealing to the electron microscopy and spectroscopy at large. The detector has been successfully demonstrated for electron spectroscopy applications: Auger and secondary electron. It has also been demonstrated for secondary electron microscopy, all obtained by as-designed BB detector

Characterization of a Miniature Electron Energy Analyzer for Scanning Electron Microscopes

We report the design and experimental characterisation of a miniature detector for the scanning electron microscope based on the Bessel Box (BB) electron energy analyser which has a simple cylindrical geometry. We report on the simulation and operation of a prototype BB. The energy resolution of a single BB has been numerically calculated and experimentally characterised to be < 1%. This miniature electron detector is designed to be used close to the sample, alleviating the effects of the ambient electrostatic and magnetic fields

Prognostic Stratification of GBMs Using Combinatorial Assessment of IDH1 Mutation, MGMT Promoter Methylation, and TERT Mutation Status: Experience from a Tertiary Care Center in India

AbstractThis study aims to establish the best and simplified panel of molecular markers for prognostic stratification of glioblastomas (GBMs). One hundred fourteen cases of GBMs were studied for IDH1, TP53, and TERT mutation by Sanger sequencing; EGFR and PDGFRA amplification by fluorescence in situ hybridization; NF1expression by quantitative real time polymerase chain reaction (qRT-PCR); and MGMT promoter methylation by methylation-specific PCR. IDH1 mutant cases had significantly longer progression-free survival (PFS) and overall survival (OS) as compared to IDH1 wild-type cases. Combinatorial assessment of MGMT and TERT emerged as independent prognostic markers, especially in the IDH1 wild-type GBMs. Thus, within the IDH1 wild-type group, cases with only MGMT methylation (group 1) had the best outcome (median PFS: 83.3 weeks; OS: not reached), whereas GBMs with only TERT mutation (group 3) had the worst outcome (PFS: 19.7 weeks; OS: 32.8 weeks). Cases with both or none of these alterations (group 2) had intermediate prognosis (PFS: 47.6 weeks; OS: 89.2 weeks). Majority of the IDH1 mutant GBMs belonged to group 1 (75%), whereas only 18.7% and 6.2% showed group 2 and 3 signatures, respectively. Interestingly, none of the other genetic alterations were significantly associated with survival in IDH1 mutant or wild-type GBMs.Based on above findings, we recommend assessment of three markers, viz., IDH1, MGMT, and TERT, for GBM prognostication in routine practice. We show for the first time that IDH1 wild-type GBMs which constitute majority of the GBMs can be effectively stratified into three distinct prognostic subgroups based on MGMT and TERT status, irrespective of other genetic alterations

From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments

Minimally invasive surgeries and related applications demand surgical tool classification and segmentation at the instance level. Surgical tools are similar in appearance and are long, thin, and handled at an angle. The fine-tuning of state-of-the-art (SOTA) instance segmentation models trained on natural images for instrument segmentation has difficulty discriminating instrument classes. Our research demonstrates that while the bounding box and segmentation mask are often accurate, the classification head mis-classifies the class label of the surgical instrument. We present a new neural network framework that adds a classification module as a new stage to existing instance segmentation models. This module specializes in improving the classification of instrument masks generated by the existing model. The module comprises multi-scale mask attention, which attends to the instrument region and masks the distracting background features. We propose training our classifier module using metric learning with arc loss to handle low inter-class variance of surgical instruments. We conduct exhaustive experiments on the benchmark datasets EndoVis2017 and EndoVis2018. We demonstrate that our method outperforms all (more than 18) SOTA methods compared with, and improves the SOTA performance by at least 12 points (20%) on the EndoVis2017 benchmark challenge and generalizes effectively across the datasets.Comment: WACV 202

Validation of a noninvasive aMMP-8 point-of-care diagnostic methodology in COVID-19 patients with periodontal disease

Objectives: The aim of this study was to validate an active matrix metalloproteinase (MMP-8) point-of-care diagnostic tool in COVID-19 patients with periodontal disease. Subjects, Materials, and Methods: Seventy-two COVID-19-positive and 30 COVID-19-negative subjects were enrolled in the study. Demographic data were recorded, periodontal examination carried out, and chairside tests run for evaluating the expression of active MMP-8 (aMMP-8) in the site with maximum periodontal breakdown via gingival crevicular fluid sampling as well as via a mouth rinse-based kit for general disease activity. In COVID-19-positive patients, the kits were run again once the patients turned COVID-19 negative. Results: The overall (n = 102) sensitivity/specificity of the mouthrinse-based kits to detect periodontal disease was 79.41%136.76% and that of site-specific kits was 64.71%/55.88% while adjusting for age, gender, and smoking status increased the sensitivity and specificity (82.35%/76.47% and 73.53%/88.24, respectively). Receiver operating characteristic (ROC) analysis for the adjusted model revealed very good area under the ROC curve 0.746-0.869 (p < .001) and 0.740-0.872 (p < .001) (the aMMP-8 mouth rinse and site-specific kits, respectively). No statistically significant difference was observed in the distribution of results of aMMP-8 mouth rinse test (p = .302) and aMMP-8 site-specific test (p = .189) once the subjects recovered from COVID-19. Conclusions: The findings of the present study support the aMMP-8 point-of-care testing (PoCT) kits as screening tools for periodontitis in COVID-19 patients. The overall screening accuracy can be further increased by utilizing adjunctively risk factors of periodontitis. The reported noninvasive, user-friendly, and objective PoCT diagnostic methodology may provide a way of stratifying risk groups, deciding upon referrals, and in the institution of diligent oral hygiene regimens.Peer reviewe

A definition of flare in low back pain (LBP): A multiphase process involving perspectives of individuals with LBP and expert consensus

Low back pain (LBP) varies over time. Consumers, clinicians and researchers use various terms to describe fluctuations of LBP symptoms. Although "flare" is commonly used to describe symptom fluctuation, there is no consensus on how it is defined. This study aimed to obtain consensus for a LBP flare definition using a mixed-method approach. Step 1 involved derivation of a preliminary candidate flare definition based on thematic analysis of consumers' views in consultation with an expert consumer writer. In Step 2, a workshop was conducted to incorporate perspectives of LBP experts into the preliminary flare definition, which resulted in two alternative LBP flare definitions. Step 3 refined the definition using a two-round Delphi consensus process with experts in musculoskeletal conditions. The definition favoured by experts was further tested with individuals with LBP in Step 4, using the definition in three scenarios. This multiphase study produced a LBP flare definition that distinguishes it from other LBP fluctuations, represents views of consumers, involves expert consensus, and is understandable by consumers in clinical and research contexts: "A flare-up is a worsening of your condition that lasts from hours to weeks that is difficult to tolerate and generally impacts your usual activities and/or emotions". Perspective: A multiphase processes produced a low back pain (LBP) flare definition that distinguishes it from other LBP fluctuations, involves expert consensus and represents consumers' views

Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm: A Review

Cardiovascular disease (CVD) related mortality and morbidity heavily strain society. The relationship between external risk factors and our genetics have not been well established. It is widely acknowledged that environmental influence and individual behaviours play a significant role in CVD vulnerability, leading to the development of polygenic risk scores (PRS). We employed the PRISMA search method to locate pertinent research and literature to extensively review artificial intelligence (AI)-based PRS models for CVD risk prediction. Furthermore, we analyzed and compared conventional vs. AI-based solutions for PRS. We summarized the recent advances in our understanding of the use of AI-based PRS for risk prediction of CVD. Our study proposes three hypotheses: i) Multiple genetic variations and risk factors can be incorporated into AI-based PRS to improve the accuracy of CVD risk predicting. ii) AI-based PRS for CVD circumvents the drawbacks of conventional PRS calculators by incorporating a larger variety of genetic and non-genetic components, allowing for more precise and individualised risk estimations. iii) Using AI approaches, it is possible to significantly reduce the dimensionality of huge genomic datasets, resulting in more accurate and effective disease risk prediction models. Our study highlighted that the AI-PRS model outperformed traditional PRS calculators in predicting CVD risk. Furthermore, using AI-based methods to calculate PRS may increase the precision of risk predictions for CVD and have significant ramifications for individualized prevention and treatment plans

In Memoriam: A Memoir for Our Fallen "Heroes"

This article is made available for unrestricted research re-use and secondary analysis in any form or be any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Even though neurosurgeons exercise these enormous and versatile skills, the COVID-19 pandemic has shaken the fabrics of the global neurosurgical family, jeopardizing human lives, and forcing the entire world to be locked down. We stand on the shoulders of the giants and will not forget their examples and their teachings. We will work to the best of our ability to honor their memory. Professor Harvey Cushing said: “When to take great risks; when to withdraw in the face of unexpected difficulties; whether to force an attempted enucleation of a pathologically favorable tumor to its completion with the prospect of an operative fatality, or to abandon the procedure short of completeness with the certainty that after months or years even greater risks may have to be faced at a subsequent session—all these require surgical judgment which is a matter of long experience.” It is up to us, therefore, to keep on the noble path that we have decided to undertake, to accumulate the surgical experience that these icons have shown us, the fruit of sacrifice and obstinacy. Our tribute goes to them; we will always remember their excellent work and their brilliant careers that will continue to enlighten all of us. This memorial is intended to commemorate our colleagues who succumbed during the first 4 months

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research