Notes

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To increase vanadium recovery, it is critical to understand the intrinsic phase evolution during vanadium slag roasting. This work proposes the novel concept of `atomic atmosphere' to effectively evaluate and recognize the microscopic state of the vanadium atom in vanadium slag before and after roasting. Atomic atmosphere includes the chemical state, chemical environment and spatial environment of the atom, and provides a universal way to explore the microscopic phase evolution mechanism during the metal-extraction process from minerals.The diamond-anvil cell (DAC) was invented 60 years ago, ushering in a new era for material sciences, extending research into the dimension of pressure. Most structural determinations and chemical research have been conducted at ambient pressure, i.e. the atmospheric pressure on Earth. However, modern experimental techniques are capable of generating pressure and temperature higher than those at the centre of Earth. Such extreme conditions can be used for obtaining unprecedented chemical compounds, but, most importantly, all fundamental phenomena can be viewed and understood from a broader perspective. This knowledge, in turn, is necessary for designing new generations of materials and applications, for example in the pharmaceutical industry or for obtaining super-hard materials. The high-pressure chambers in the DAC are already used for a considerable variety of experiments, such as chemical reactions, crystallizations, measurements of electric, dielectric and magnetic properties, transformations of biological materials as well as experiments on living tissue. Undoubtedly, more applications involving elevated pressure will follow. High-pressure methods become increasingly attractive, because they can reduce the sample volume and compress the intermolecular contacts to values unattainable by other methods, many times stronger than at low temperature. The compressed materials reveal new information about intermolecular interactions and new phases of single- and multi-component compounds can be obtained. At the same time, high-pressure techniques, and particularly those of X-ray diffraction using the DAC, have been considerably improved and many innovative developments implemented. Increasingly more equipment of in-house laboratories, as well as the instrumentation of beamlines at synchrotrons and thermal neutron sources are dedicated to high-pressure research.Comprehensive genomic profiling using next-generation sequencing (NGS) enables the identification of multiple genomic biomarkers established in advanced gastrointestinal (GI) cancers. However, tissue-based NGS has limitations, such as long turnaround time and failure to detect tumour heterogeneity. Recently, the analysis of circulating tumour DNA (ctDNA) using polymerase chain reaction-based or NGS-based methods has demonstrated the capability to detect genomic alterations with high accuracy compared with tumour tissue analysis with short turnaround time and identify heterogeneous resistance mechanisms. Furthermore, ctDNA analysis can be repeatedly performed on disease progression to clarify resistant clones. Clinical trials that test the outcome of a selected targeted therapy based on a ctDNA result are ongoing to prospectively evaluate the clinical utility of ctDNA analysis. Furthermore, the improvement of ctDNA analysis beyond current technical limits of mutation-based ctDNA detection methods has expanded the potential for detecting the presence of tumours in patients with no clinically evident disease, such as minimal residual disease and early cancer. Although a careful understanding of the advantages and limitations are required and further prospective studies are needed, the ctDNA analysis has the potential to overcome several challenges in the treatment of various types of cancers at all stages, including GI cancers.
Most existing machine learning methods for coronary angiography analysis are limited to a single aspect. We aimed to achieve an automatic and multimodal analysis to recognize and quantify coronary angiography, integrating multiple aspects, including the identification of coronary artery segments and the recognition of lesion morphology.

A dataset of 20,612 angiograms were retrospectively collected, among which 13,373 angiograms were labeled with coronary artery segments, 7,239 were labeled with special lesion morphology. Trained and optimized by these labeled data, one network recognized 20 different segments of coronary arteries, while the other detected lesion morphology, including measures of lesion diameter stenosis as well as calcification, thrombosis, total occlusion, and dissection detections in an input angiogram. For segment prediction, the recognition accuracy was 98.4%,the recognition sensitivity was 85.2%. For detecting lesion morphologies including stenotic lesion, total occlusion, calcification, thrombosis, and dissection, the F1-scores were 0.829, 0.810, 0.802, 0.823, and 0.854 respectively. Only 2 seconds were needed for the automatic recognition.

Our deep learning architecture automatically provides a coronary diagnostic map by integrating multiple aspects, which helps cardiologists to flag and diagnose lesion severity and morphology during the intervention.
Our deep learning architecture automatically provides a coronary diagnostic map by integrating multiple aspects, which helps cardiologists to flag and diagnose lesion severity and morphology during the intervention.
We sought to assess the proportion of patients eligible for the ISCHEMIA trial and to compare the characteristics and outcomes of these patients with those without ISCHEMIA inclusion or with ISCHEMIA exclusion criteria in a contemporary, nationwide cohort of patients with stable coronary artery disease (CAD).

Among the 5,070 consecutive patients enrolled in the START registry, 4,295 (84.7%) did not fulfil the inclusion criteria (ISCHEMIA-Not Included or ISCHEMIA-Unclassifiable), 582 (11.5%) had exclusion criteria (ISCHEMIA-Excluded), and the remaining 193 (3.8%) were classified as ISCHEMIA-Like. At one year, the incidence of the primary outcome, a composite of death from cardiovascular (CV) causes, myocardial infarction (MI), or hospitalisation for unstable angina and heart failure, was 0.5% in the ISCHEMIA-Like versus 3.3% in other patients (p=0.03). The composite secondary outcome of CV mortality and MI occurred in 0.5% of the ISCHEMIA-Like patients and in 1.4% of the remaining patients (p=0.1).

In a contemporary real-world cohort of stable CAD patients, only 4% resulted in being eligible for the ISCHEMIA trial. These patients presented an extremely low annual risk of adverse events, especially when compared with other groups of stable CAD patients. Visual summary. Proportion of patients with stable CAD enrolled in the START registry with or without ISCHEMIA criteria and their rate of MACE at 1 year.
In a contemporary real-world cohort of stable CAD patients, only 4% resulted in being eligible for the ISCHEMIA trial. These patients presented an extremely low annual risk of adverse events, especially when compared with other groups of stable CAD patients. Visual summary. Proportion of patients with stable CAD enrolled in the START registry with or without ISCHEMIA criteria and their rate of MACE at 1 year.
To model the safety and effectiveness of drug-coated stents (DCS) vs. bare-metal stents (BMS) in high bleeding risk (HBR) patients according to the Academic Research Criteria (ARC) criteria.

Participants from the LEADERS FREE (LF) and LEADERS FREE (LFII) studies were pooled into one dataset. Participants were treated with 30 days of DAPT. The primary safety (composite of cardiac death, myocardial infarction, or stent thrombosis) and effectiveness (target-lesion revascularization) endpoints were compared between DCS and BMS in the subgroup of patients satisfying the ARC-HBR definition using propensity-score modelling. From the 3,635 participants included in the combined LF & LFII dataset, 2,898 (79.7%) satisfied the ARC-HBR criteria (DCS 1,923; BMS 975). The primary safety endpoint occurred in 184 (9.8%) and in 132 (13.8%) participants in the DCS and BMS groups, respectively (adjusted HR 0.72; 95% CI 0.57-0.91; p=0.006). The risk of the primary effectiveness endpoint was also significantly lower with DCS (6.2%) vs. BMS (8.8%) (adjusted HR 0.70; 95% CI 0.52-0.94; p=0.016). Safety and effectiveness of DCS vs. BMS were consistent according to ARC-HBR status (p interaction = 0.206 and 0.260, respectively).

DCS are safer and more effective than BMS in an ARC-defined HBR population.
DCS are safer and more effective than BMS in an ARC-defined HBR population.The SARS-CoV-2 virus has emerged and rapidly evolved into a current global pandemic. Although bacterial and fungal coinfections have been associated with COVID-19, little is known about parasitic infection. We report a case of a COVID-19 patient who developed disseminated strongyloidiasis following treatment with high-dose corticosteroids and tocilizumab. Screening for Strongyloides infection should be pursued in individuals with COVID-19 who originate from endemic regions before initiating immunosuppressive therapy.We conducted a comparative cross-sectional study to examine the potential effects of a community-led total sanitation (CLTS) intervention on sanitation and hygiene in Pallisa district in Uganda. Quantitative data were collected from households using a semi-structured questionnaire and an observation checklist, entered and analyzed using univariate, bivariate, and multivariate analyses. Overall, knowledge on sanitation and hygiene was significantly higher (64.5%; 129/200) among households in the CLTS intervention than among those in the nonintervention subcounties (54.0%; 108/200) (P = 0.033). Latrine quality was rated as fair in a majority (73.3%; 143/195) of the CLTS intervention households compared with 50.8% (93/183) in the non-CLTS households (P less then 0.001). Latrine cleanliness was rated as good in more than a half (51.3%; 100/195) of households in the intervention area, whereas only 13.7% (25/183) for the nonintervention area (P less then 0.001). In this study, 35.0% (70/200) of the households in the intervention subcounty had attained open defecation-free (ODF) status compared with only 6.0% (12/200) in the nonintervention subcounty (P less then 0.001). Level of knowledge on hygiene and sanitation (adjusted odd ratio [AOR] 2.23; 95% CI 1.24-4.03) and CLTS status (AOR 8.89; 95% CI 4.26-18.56) were significantly associated with achievement of ODF status in the multivariate analysis. The mean cases of diarrhea were significantly lower in CLTS implementing (subcounty (0.42 [SD ± 1.03]) than in the non-CLTS implementing subcounty (0.98 [SD ± 1.39]; t = -4.6; P less then 0.001). Sanitation and hygiene outcomes were better in the CLTS intervention subcounty than in the non-CLTS intervention subcounty, suggesting that scaling up CLTS could reduce ODF and the burden of diarrheal diseases.Sequence data were combined with morphological analyses to identify two lepocreadiid trematode species from jellyfishes and fishes. Three species of jellyfish were captured within Port Phillip Bay, Australia, and three species of fish that feed on jellyfish were obtained from Moreton Bay (Queensland) and Port Phillip Bay and Portland (Victoria). The digeneans were distributed throughout most parts of the jellyfish. Opechona cf. kahawai Bray & Cribb, 2003 parasitized the scyphozoan jellyfish Aequorea eurodina and the scombrid fish Scomber australasicus. Cephalolepidapedon warehou Bray & Cribb, 2003 parasitized the scyphozoans Pseudorhiza haeckeli and Cyanea annaskala, and the centrolophid fishes Seriolella brama and Seriolella punctata. Intensities ranged from four to 96 in the jellyfish, and one to 30 in the fish. For both trematode species, internal transcribed spacer 2 of ribosomal DNA sequences from mature adults in the fishes matched those from metacercariae from the jellyfish. This is the first record of larval stages of C.
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