Hypothesis testing using R

Competencies in statistical data processing are becoming increasingly important for modern scientists. The apparent advantages of open-source software for statistical analysis are its accessibility and adaptability. The programming language and the corresponding software R, available as a minimalistic console interface or a complete development environment RStudio/Posit, have the widest possibilities among free solutions. We present a practical guide for comparing two groups using the software R. This study compares the effective doses of standard computed tomography with low-dose computed tomography for COVID-19 patients. The practical guide summarizes theoretical approaches to medical data processing and recommendations for correctly formulating research tasks and selecting optimal statistical analysis methods. The main goal of the practical guide is to introduce the reader to the Posit interface and the basic functionality of the R language by using a practical example of treating a real medical problem. The presented material can be useful as an introduction to statistical analysis using the programming language R

Volumetry versus linear diameter lung nodule measurement: an ultra-low-dose computed tomography lung cancer screening study

BACKGROUND: The DutchBelgian Randomized Lung Cancer Screening Trial (NELSON) used a volume-based protocol and significantly reduced the prevalence of false-positive results (2.1%). AIM: To compare the performance of manual linear diameter and semi-automated volumetric nodule measurement in the pilot project Moscow Lung Cancer Screening ultra-low-dose computed tomography pilot study. MATERIALS AND METHODS: The study included individuals with a lung nodule of at least 4 mm on baseline-computed tomography of the Moscow lung cancer screening between February 2017 and February 2018, without verified lung cancer diagnosis until 2020. The radiation dose was selected individually and did not exceed 1 mSv. All scans were assessed by three blinded readers to measure the maximum and minimum transversal nodule diameter and extrapolated volume. As a reference value of size and volume, the average value from the results of expert measurements was obtained. A false-positive nodule was defined as a nodule 6 mm/100 mm3 and a false-negative nodule as a nodule 6 mm/100 mm3. RESULTS: Overall, 293 patients were included (166 men; mean age, 64.6 5.3years); 199 lung nodules were 6 mm/100 mm3 and 94 were 6 mm/100 mm3. Regarding volumetric measurements, 32 [10.9%; 4 false-positive, 28 false-negative], 29 [9.9%; 17 false-positive, 12 false-negative], and 30 [10.2%; 6 false-positive, 24 false-negative] nodule discrepancies were reported by readers 1, 2, and 3 respectively. For linear diameter measurement, 92 [65.5%; 107 false-positive, 85 false-negative], 146 [49.8%; 58 false-positive, 88 false-negative], and 102 [34.8%; 23 false-positive, 79 false-negative] nodule discrepancies were reported by readers 1, 2, and 3 respectively. CONCLUSIONS: The use of lung nodule volumetry strongly reduces the number of false-positive and false-negative nodules compared with nodule diameter measurements, in an ultra-low-dose computed tomography lung cancer screening program

The Herschel Virgo Cluster Survey. IX. Dust-to-gas mass ratio and metallicity gradients in four Virgo spiral galaxies

Using Herschel data from the Open Time Key Project the Herschel Virgo Cluster Survey (HeViCS), we investigated the relationship between the metallicity gradients expressed by metal abundances in the gas phase as traced by the chemical composition of HII regions, and in the solid phase, as traced by the dust-to-gas mass ratio. We derived the radial gradient of the dust-to-gas mass ratio for all galaxies observed by HeViCS whose metallicity gradients are available in the literature. They are all late type Sbc galaxies, namely NGC4254, NGC4303, NGC4321, and NGC4501. We examined different dependencies on metallicity of the CO-to-H$_2$ conversion factor (\xco), used to transform the $^{12}$CO observations into the amount of molecular hydrogen. We found that in these galaxies the dust-to-gas mass ratio radial profile is extremely sensitive to choice of the \xco\ value, since the molecular gas is the dominant component in the inner parts. We found that for three galaxies of our sample, namely NGC4254, NGC4321, and NGC4501, the slopes of the oxygen and of the dust-to-gas radial gradients agree up to $\sim$0.6-0.7R$_{25}$ using \xco\ values in the range 1/3-1/2 Galactic \xco. For NGC4303 a lower value of \xco$\sim0.1\times$ 10$^{20}$ is necessary. We suggest that such low \xco\ values might be due to a metallicity dependence of \xco (from close to linear for NGC4254, NGC4321, and NGC4501 to superlinear for NGC4303), especially in the radial regions R$_G<$0.6-0.7R$_{25}$ where the molecular gas dominates. On the other hand, the outer regions, where the atomic gas component is dominant, are less affected by the choice of \xco, and thus we cannot put constraints on its value.Comment: 13 pages, 8 figures, A&A accepte

Cation binding to 15-TBA quadruplex DNA is a multiple-pathway cation-dependent process

A combination of explicit solvent molecular dynamics simulation (30 simulations reaching 4 µs in total), hybrid quantum mechanics/molecular mechanics approach and isothermal titration calorimetry was used to investigate the atomistic picture of ion binding to 15-mer thrombin-binding quadruplex DNA (G-DNA) aptamer. Binding of ions to G-DNA is complex multiple pathway process, which is strongly affected by the type of the cation. The individual ion-binding events are substantially modulated by the connecting loops of the aptamer, which play several roles. They stabilize the molecule during time periods when the bound ions are not present, they modulate the route of the ion into the stem and they also stabilize the internal ions by closing the gates through which the ions enter the quadruplex. Using our extensive simulations, we for the first time observed full spontaneous exchange of internal cation between quadruplex molecule and bulk solvent at atomistic resolution. The simulation suggests that expulsion of the internally bound ion is correlated with initial binding of the incoming ion. The incoming ion then readily replaces the bound ion while minimizing any destabilization of the solute molecule during the exchange

Artificial intelligence in the diagnosis of thoracic aortic aneurysms in a retrospective chest computed tomography scan analysis

BACKGROUND: Aortic aneurysms, known as silent killers, are frequently asymptomatic, leading to vessel rupture and death. Annual rates for ruptures, stratifications, and sudden deaths are up to 3.6%, 3.7%, and 10.8%, respectively. Timely diagnosis and early treatment save a patients life. The use of artificial intelligence (AI) technologies helps to detect aortic aneurysms, which significantly improves the quality of diagnosis and saves patients lives. AIM: To assess the efficiency of using AI technologies to detect thoracic aortic aneurysms on chest computed tomography (CT) and determining the possibility of using AI technologies as an assistant to the radiologist during the primary description of radiological images. METHODS: The study retrospectively assessed the results of AI technologies aimed at detecting thoracic aortic aneurysms on chest CT scans. No contrast enhancement was performed primarily. The sample consisted of 84,405 observations of patients over the age of 18 years; of these, 86 scans with thoracic aortic aneurysms were selected according to AI data. The selected examinations were retrospectively assessed by radiologists and vascular surgeons for the probable presence of a thoracic aortic aneurysm. In 44 cases, an aortic aneurysm was initially detected by the radiologist. In 31 cases, an aneurysm was not initially described by the radiologist, 6 were excluded from the sample (due to the absence of the radiologists report in the Unified Radiological Information Service), and 5 scans had false-positive results according to AI findings. RESULTS: The use of AI technologies allows detection and labeling of pathological changes in the aorta on the images. AI technologies increase the detectability of thoracic aortic aneurysms in the description of chest CT scans by 38.8%. The incidence of ascending aortic aneurysm was 0.3%, which corresponded to the literature data of 0.16%1.6%. According to the results, 22 surgical interventions for aortic stenting were performed. CONCLUSIONS: The use of AI in the primary chest CT description may help increase the detectability of clinically significant pathological conditions, such as thoracic aortic aneurysm. Further development of routing for this category of patients in the cito mode for surgical treatment is relevant. Expansion of retrospective screening by chest CT scans using AI systems will improve the quality of diagnosis of concomitant pathologies and prevent adverse outcomes for patients

Computed tomography in the diagnosis of fever of unknown origin: A case report

Fever of unknown origin can be a symptom of at least 200 diseases. Positron emission tomography-computed tomography, although highly informative, may not be readily available as an imaging tool. We present a clinical case of giant cell arteritis where computed tomography played a key role in arriving at a diagnosis. A 61-year-old woman presented to the hospital with a nocturnal fever up to 39.5°С, accompanied by chest and scapular pain, and substantial weight loss (10 kg over 3 months). Lymphoproliferative and infectious diseases were excluded. Baseline colonoscopy had revealed erosions in the colonic mucosa, leading to a preliminary diagnosis of ulcerative colitis, and subsequently, the patient was admitted to the gastroenterology department. Follow-up colonoscopy had excluded this diagnosis. Additional imaging via chest and abdominal computed tomography scan revealed wall thickening of aorta and its branches with subtle contrast enhancement. Conditions, such as tuberculous aortoarteritis and syphilitic aortitis, were excluded. The patient was diagnosed with giant cell arteritis involving brachiocephalic trunk, subclavian arteries, and celiac trunk. Prednisolone was administered with subsequent reduction in symptoms. Although computed tomography may not be regarded as the gold standard for the differential diagnosis of fever of unknown origin, this case underscores its valuable contribution in establishing a definitive diagnosis

Erratum in “Volumetry versus linear diameter lung nodule measurement: an ultra-low-dose computed tomography lung cancer screening study” (doi: 10.17816/DD117481)

In the article "Volumetry versus linear diameter lung nodule measurement: an ultra-low-dose computed tomography lung cancer screening study" published in Digital Diagnostics journal Volume 4 Issue 1 in 2023 (doi: 10.17816/DD117481) contained an error in the paragraph with data of funding sources for the study. At the request of the authors team, the error was eliminated, the original version of the published article and the information on the journals site was replaced with the corrected one. Correct text of the changed: This paper was prepared by a group of authors as part of the research work (USIS No. 123031400009-1) in accordance with the Order issued by the Moscow Health Care Department No. 1196 dated December 21, 2022. The authors and the publisher apologize to readers for the published error and express their confidence that this mistake could not significantly affect the perception and interpretation of the results of the study described in the text of the article

PeptoGrid—Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries

Peptides are promising drug candidates due to high specificity and standout safety. Identification of bioactive peptides de novo using molecular docking is a widely used approach. However, current scoring functions are poorly optimized for peptide ligands. In this work, we present a novel algorithm PeptoGrid that rescores poses predicted by AutoDock Vina according to frequency information of ligand atoms with particular properties appearing at different positions in the target protein&rsquo;s ligand binding site. We explored the relevance of PeptoGrid ranking with a virtual screening of peptide libraries using angiotensin-converting enzyme and GABAB receptor as targets. A reasonable agreement between the computational and experimental data suggests that PeptoGrid is suitable for discovering functional leads

Diagnostic Accuracy of AI for Opportunistic Screening of Abdominal Aortic Aneurysm in CT: A Systematic Review and Narrative Synthesis

In this review, we focused on the applicability of artificial intelligence (AI) for opportunistic abdominal aortic aneurysm (AAA) detection in computed tomography (CT). We used the academic search system PubMed as the primary source for the literature search and Google Scholar as a supplementary source of evidence. We searched through 2 February 2022. All studies on automated AAA detection or segmentation in noncontrast abdominal CT were included. For bias assessment, we developed and used an adapted version of the QUADAS-2 checklist. We included eight studies with 355 cases, of which 273 (77%) contained AAA. The highest risk of bias and level of applicability concerns were observed for the &ldquo;patient selection&rdquo; domain, due to the 100% pathology rate in the majority (75%) of the studies. The mean sensitivity value was 95% (95% CI 100&ndash;87%), the mean specificity value was 96.6% (95% CI 100&ndash;75.7%), and the mean accuracy value was 95.2% (95% CI 100&ndash;54.5%). Half of the included studies performed diagnostic accuracy estimation, with only one study having data on all diagnostic accuracy metrics. Therefore, we conducted a narrative synthesis. Our findings indicate high study heterogeneity, requiring further research with balanced noncontrast CT datasets and adherence to reporting standards in order to validate the high sensitivity value obtained