Category: Nevin Manimala

Sci Rep. 2023 Apr 15;13(1):6143. doi: 10.1038/s41598-023-33298-6.

ABSTRACT

After graphene was first exfoliated in 2004, research worldwide has focused on discovering and exploiting its distinctive electronic, mechanical, and structural properties. Application of the efficacious methodology used to fabricate graphene, mechanical exfoliation followed by optical microscopy inspection, to other analogous bulk materials has resulted in many more two-dimensional (2D) atomic crystals. Despite their fascinating physical properties, manual identification of 2D atomic crystals has the clear drawback of low-throughput and hence is impractical for any scale-up applications of 2D samples. To combat this, recent integration of high-performance machine-learning techniques, usually deep learning algorithms because of their impressive object recognition abilities, with optical microscopy have been used to accelerate and automate this traditional flake identification process. However, deep learning methods require immense datasets and rely on uninterpretable and complicated algorithms for predictions. Conversely, tree-based machine-learning algorithms represent highly transparent and accessible models. We investigate these tree-based algorithms, with features that mimic color contrast, for automating the manual inspection process of exfoliated 2D materials (e.g., MoSe₂). We examine their performance in comparison to ResNet, a famous Convolutional Neural Network (CNN), in terms of accuracy and the physical nature of their decision-making process. We find that the decision trees, gradient boosted decision trees, and random forests utilize physical aspects of the images to successfully identify 2D atomic crystals without suffering from extreme overfitting and high training dataset demands. We also employ a post-hoc study that identifies the sub-regions CNNs rely on for classification and find that they regularly utilize physically insignificant image attributes when correctly identifying thin materials.

PMID:37061576 | DOI:10.1038/s41598-023-33298-6

Eur J Orthop Surg Traumatol. 2023 Apr 16. doi: 10.1007/s00590-023-03550-w. Online ahead of print.

ABSTRACT

BACKGROUND: Aseptic loosening is a feared complication following total elbow arthroplasty (TEA); however, literature regarding factors that may contribute to this complication is limited. The aims of this investigation were to: (1) compare baseline demographics of patients who developed aseptic loosening following primary TEA; and (2) identify patient-specific risk factors for the development of loosening.

METHODS: Retrospective analysis using a nationwide claims database was performed to identify patients who underwent primary TEA and developed aseptic loosening within 2 years (study n = 307, control n = 10,741). Multivariate regression analysis generated odds ratio (OR), 95% confidence interval (95% CI), and p-value of risk factors. p < 0.05 was considered statistically significant.

RESULTS: Patients who developed aseptic loosening had significant differences in numerous demographics, including age (p = 0.0001), sex (p = 0.0251), and various comorbid conditions such as obesity (15.96% vs. 8.36%, p < 0.0001). Furthermore, the risk factors most associated with aseptic loosening were obesity (OR 1.65, 95% CI 1.18-2.28, p = 0.002), male sex (OR 1.51, 95% CI 1.13-2.00, p = 0.004), and concomitant opioid use disorder (OR 1.58, 95% CI 1.14-2.15, p = 0.004).

DISCUSSION: This study is the first to identify demographics and patient-related risk factors associated with aseptic loosening following primary TEA. This evidence could be applied to the clinical setting in order to educate at-risk patients of this potential complication as well as inform their post-operative clinical management.

LEVEL OF EVIDENCE: Level III: Prognostic.

PMID:37061573 | DOI:10.1007/s00590-023-03550-w

Neurol Sci. 2023 Apr 15. doi: 10.1007/s10072-023-06801-0. Online ahead of print.

ABSTRACT

OBJECTIVES: We aimed to evaluate the available evidence on the efficacy and safety outcomes of intravenous tenecteplase (TNK) compared with intravenous alteplase(ALT) for patients with acute ischemic stroke (AIS) in randomized controlled trials (RCTs).

METHODS: The MEDLINE/PubMed, Embase, Springer, Web of Science, Cochrane Collaboration database, China National Knowledge Infrastructure (CNKI) database, and Wanfang database were comprehensively searched for RCTs regarding the effects of TNK versus ALT among AIS patients in these English and Chinese electronic databases from inception dates to August 1, 2022. This meta-analysis followed PRISMA guidelines. Two reviewers independently retrieved RCTs and extracted relevant information. The methodological quality of the included trials was estimated using the Cochrane risk of bias tool. The pooled analyses were performed using RevMan 5.3 software. The primary outcome was functional outcome on the modified Rankin Scale (mRS) (range 0 to 5) and mortality at 90 days. The secondary outcomes included successful recanalization, early neurologic improvement < 48 h, any intracranial hemorrhage (ICH), and symptomatic ICH. The follow-up time of all studies was at least 3 months.

RESULTS: A total of nine RCTs involving 1958 patients in TNK group and 1731 patients in ALT group were finally included. For the efficacy outcomes, there were no significant differences between the two groups in terms of mRS score 0 ~ 2 (RR 1.00; 95% CI 0.88-1.13; P = 0.96), mRS score 0 ~ 1 (RR 1.03; 95% CI 0.96-1.10; P = 0.36), successful recanalization (RR 1.25; 95% CI 0.88-1.76; P = 0.21), and early neurologic improvement < 48 h (RR 1.08; 95% CI 0.92-1.26; P = 0.37). Similar results were seen for the safety outcomes, which have no statistical differences in terms of any ICH (RR 1.01; 95% CI 0.72-1.41; P = 0.96), symptomatic ICH (RR 1.19; 95% CI 0.81-1.76; P = 0.37), and mortality at 90 days (RR 0.99; 95% CI 0.83-1.19; P = 0.94).

CONCLUSION: Overall, the efficacy and safety outcomes of intravenous thrombolysis with TNK versus ALT for AIS were not statistically different. However, TNK at a dose of 0.25 mg/kg may be a reasonable alternative to ALT for thrombolysis.

PMID:37061572 | DOI:10.1007/s10072-023-06801-0

Urolithiasis. 2023 Apr 15;51(1):70. doi: 10.1007/s00240-023-01439-1.

ABSTRACT

In 2018, the Endourology Disease Group for Excellence (EDGE) published a prospective trial comparing dusting versus basketing during ureteroscopy. One hundred fifty-nine patients were included in the original analysis, which found no difference in stone-free rate at 3 months. We report the intermediate and long-term outcomes of patients included in the original trial. Two analyses were performed. At 1-year, a retrospective chart review was performed, and data collected on stone episodes, Emergency Department (ED) visits, hospital admissions and surgical interventions. To obtain long-term outcomes, the four sites with the largest initial accrual were included in a second phase of data collection with updated analyses. The patients from those sites were contacted, re-consented, and data were collected on stone surgical interventions, stone episodes, stone recurrences on imaging, emergency department (ED) visits, and hospital admissions for stone-related care since their original procedure. One-year follow-up data were collected in 111 of the original 159 (69.8%) patients from the nine sites. There were no statistically significant differences in the number of painful episodes, ED visits, hospital admissions, or surgical interventions. 94 patients from four sites were included in the long-term analysis. There were no statistically significant differences in surgical interventions, painful stone episodes, stone recurrence on imaging, ED visits or hospitalizations for stone-related events between the two groups. Long-term outcomes of dusting versus basketing during ureteroscopy indicate that there are no significant differences in clinical outcomes between the two surgical modalities.

PMID:37061554 | DOI:10.1007/s00240-023-01439-1

Sci Rep. 2023 Apr 15;13(1):6157. doi: 10.1038/s41598-023-33098-y.

ABSTRACT

A deep learning model (LCP CNN) for the stratification of indeterminate pulmonary nodules (IPNs) demonstrated better discrimination than commonly used clinical prediction models. However, the LCP CNN score is based on a single timepoint that ignores longitudinal information when prior imaging studies are available. Clinically, IPNs are often followed over time and temporal trends in nodule size or morphology inform management. In this study we investigated whether the change in LCP CNN scores over time was different between benign and malignant nodules. This study used a prospective-specimen collection, retrospective-blinded-evaluation (PRoBE) design. Subjects with incidentally or screening detected IPNs 6-30 mm in diameter with at least 3 consecutive CT scans prior to diagnosis (slice thickness ≤ 1.5 mm) with the same nodule present were included. Disease outcome was adjudicated by biopsy-proven malignancy, biopsy-proven benign disease and absence of growth on at least 2-year imaging follow-up. Lung nodules were analyzed using the Optellum LCP CNN model. Investigators performing image analysis were blinded to all clinical data. The LCP CNN score was determined for 48 benign and 32 malignant nodules. There was no significant difference in the initial LCP CNN score between benign and malignant nodules. Overall, the LCP CNN scores of benign nodules remained relatively stable over time while that of malignant nodules continued to increase over time. The difference in these two trends was statistically significant. We also developed a joint model that incorporates longitudinal LCP CNN scores to predict future probability of cancer. Malignant and benign nodules appear to have distinctive trends in LCP CNN score over time. This suggests that longitudinal modeling may improve radiomic prediction of lung cancer over current models. Additional studies are needed to validate these early findings.

PMID:37061539 | DOI:10.1038/s41598-023-33098-y

Sci Rep. 2023 Apr 15;13(1):6158. doi: 10.1038/s41598-023-31314-3.

ABSTRACT

Decreasing the conventional sources of oil reservoirs attracts researchers’ attention to the tertiary recovery of oil reservoirs, such as in-situ catalytic upgrading. In this contribution, the response surface methodology (RSM) approach and multi-objective optimization were utilized to investigate the effect of reaction temperature and catalysts soaking time on the concentration distribution of upgraded oil samples. To this end, 22 sets of experimental oil upgrading over Ni-W-Mo catalyst were utilized for the statistical modeling. Then, optimization based on the minimum reaction temperature, catalysts soaking time, gas, and residue wt.% was performed. Also, correlations for the prediction of concentration of different fractions (residue, vacuum gas oil (VGO), distillate, naphtha, and gases) as a function of independent factors were developed. Statistical results revealed that RSM model is in good agreement with experimental data and high coefficients of determination (R² = 0.96, 0.945, 0.97, 0.996, 0.89) are the witness for this claim. Finally, based on multi-objective optimization, 378.81 °C and 17.31 h were obtained as the optimum upgrading condition. In this condition, the composition of residue, VGO, distillate, naphtha, and gases are 6.798%, 39.23%, 32.93%, 16.865%, and 2.896%, respectively, and the optimum condition is worthwhile for the pilot and industrial application of catalyst injection during in-situ oil upgrading.

PMID:37061521 | DOI:10.1038/s41598-023-31314-3

J Chem Phys. 2023 Apr 14;158(14):144114. doi: 10.1063/5.0140882.

ABSTRACT

Simulation datasets of proteins (e.g., those generated by molecular dynamics simulations) are filled with information about how a non-covalent interaction network within a protein regulates the conformation and, thus, function of the said protein. Most proteins contain thousands of non-covalent interactions, with most of these being largely irrelevant to any single conformational change. The ability to automatically process any protein simulation dataset to identify non-covalent interactions that are strongly associated with a single, defined conformational change would be a highly valuable tool for the community. Furthermore, the insights generated from this tool could be applied to basic research, in order to improve understanding of a mechanism of action, or for protein engineering, to identify candidate mutations to improve/alter the functionality of any given protein. The open-source Python package Key Interactions Finder (KIF) enables users to identify those non-covalent interactions that are strongly associated with any conformational change of interest for any protein simulated. KIF gives the user full control to define the conformational change of interest as either a continuous variable or categorical variable, and methods from statistics or machine learning can be applied to identify and rank the interactions and residues distributed throughout the protein, which are relevant to the conformational change. Finally, KIF has been applied to three diverse model systems (protein tyrosine phosphatase 1B, the PDZ3 domain, and the KE07 series of Kemp eliminases) in order to illustrate its power to identify key features that regulate functionally important conformational dynamics.

PMID:37061494 | DOI:10.1063/5.0140882

J Emerg Med. 2023 Mar 12:S0736-4679(23)00151-8. doi: 10.1016/j.jemermed.2023.03.052. Online ahead of print.

ABSTRACT

BACKGROUND: There have been recent reports of increased QT interval after head trauma in concussed athletes and adult patients. Ondansetron, which is widely used in treatment of nausea and vomiting symptoms in head injuries, was issued a safety warning from the U.S. Food and Drug Administration regarding QT prolongation and risk of fatal dysrhythmias.

OBJECTIVE: The purpose of this study was to evaluate the safety of ondansetron regarding QT prolongation for patients experiencing nausea or vomiting after head trauma.

METHODS: Patients aged 1-20 years presenting to a pediatric emergency department with head trauma and who required a dose of ondansetron for nausea or vomiting were enrolled in the study. Patients received a baseline 12-lead electrocardiogram (ECG) prior to administration of either oral or IV ondansetron. A second post-ondansetron 12-lead ECG was performed after administration of ondansetron. All ECGs were reviewed and the QTc calculated manually by a board-certified pediatric cardiologist.

RESULTS: Forty-two patients met enrollment criteria. Five patients received IV ondansetron and 37 received oral ondansetron. Mean QTc pre ondansetron was 387.5 ms and mean QTc post ondansetron was 400.9 ms (p = 0.120). We found no statistically significant difference in other ECG parameters pre and post ondansetron.

CONCLUSIONS: Ondansetron is safe in regard to QTc prolongation in patients with head trauma. Based on this research, ondansetron should continue to be used for the treatment of nausea and vomiting in emergency department patients who present with head injury.

PMID:37061459 | DOI:10.1016/j.jemermed.2023.03.052

Trends Biochem Sci. 2023 Apr 14:S0968-0004(23)00079-8. doi: 10.1016/j.tibs.2023.03.003. Online ahead of print.

ABSTRACT

Protein-protein interactions (PPIs) drive biological processes, and disruption of PPIs can cause disease. With recent breakthroughs in structure prediction and a deluge of genomic sequence data, computational methods to predict PPIs and model spatial structures of protein complexes are now approaching the accuracy of experimental approaches for permanent interactions and show promise for elucidating transient interactions. As we describe here, the key to this success is rich evolutionary information deciphered from thousands of homologous sequences that coevolve in interacting partners. This covariation signal, revealed by sophisticated statistical and machine learning (ML) algorithms, predicts physiological interactions. Accurate artificial intelligence (AI)-based modeling of protein structures promises to provide accurate 3D models of PPIs at a proteome-wide scale.

PMID:37061423 | DOI:10.1016/j.tibs.2023.03.003

Br J Oral Maxillofac Surg. 2023 Mar 28:S0266-4356(23)00082-7. doi: 10.1016/j.bjoms.2023.03.008. Online ahead of print.

ABSTRACT

The aim of this prospective study was to analyse if a delay in the time from injury to definitive surgical intervention of open reduction and internal fixation (ORIF) of compound mandibular fractures predisposed to an increase in postoperative infectious complications. ORIF beyond 72 hours from injury was considered to be delayed intervention. Postoperative surgical site infections (SSI) and non-infectious complications (NIC) were recorded. The Mann-Whitney U test was used to compare the delay in ORIF with SSI. The chi squared test/Fisher’s exact test was used to find the association of the infectious complication status with predetermined risk factors. Eighty-three patients underwent a delayed ORIF with a median (range) of 8 (4-19) days. SSI was documented in eight patients (9.6%) and could be managed as outpatient medical and surgical intervention. Two patients needed repeat surgical intervention due to non-union of the fracture. The median (range) time to ORIF was 6.5 (5-12) days in patients who developed SSI; the Mann-Whitney U test did not show a statistically significant association between delayed ORIF and SSI (p = 0.7). The univariate analysis did not establish a significant relationship between SSI and predetermined risk factors. The delay to definitive surgical intervention was not observed to be an independent attributing factor in postoperative infectious complications of compound mandibular fractures.

PMID:37061417 | DOI:10.1016/j.bjoms.2023.03.008