Tag: statistics

Pediatr Allergy Immunol Pulmonol. 2023 Jul 11. doi: 10.1089/ped.2023.0024. Online ahead of print.

ABSTRACT

Background: Pediatric inflammatory multisystem syndrome temporarily associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PIMS-TS) is an acute complication of previous SARS-CoV-2 exposure. The relationship between inflammatory markers and anti-inflammatory medication in PIMS-TS is unknown. We retrospectively investigated the relationship between demographics, biomarkers, treatment, and length of stay (LOS) in this novel disease. Methods: We reviewed the case notes and blood tests of all patients who met the Royal College of Paediatrics and Child Health diagnostic criteria for PIMS-TS at a large tertiary center in the United Kingdom. Biomarker trajectories were modeled using log linear mixed effects, and factors affecting LOS in hospital were evaluated using multiple regression. Results: Between March 2020 and May 2022, a total of 56 patients attended Sheffield Children’s Hospital with PIMS-TS, 70% male. Mean age was 7.4 ± 3.7 years and mean LOS 8.7 ± 4.5 days with 50% requiring intensive care and 20% requiring inotropes. Older males had shorter LOS than younger males (P = 0.04), not seen in females. Treatment included intravenous glucocorticoids in 93%, intravenous immunoglobulins (IVIG) in 77%, Anakinra in 11%, and infliximab in 1.8%. Biomarkers correlated poorly with trajectories that peaked at different times. C-reactive protein peaked first after median 1.3 days postadmission; while LFT’s and neutrophils peaked after 3 days. Age had a large effect on some biomarkers, with older children having larger troponin and ferritin, and lower lymphocytes and platelets. Cumulative dose of glucocorticoids and IVIG had a statistically significant effect on some biomarkers, but effect size was small. Conclusions: The heterogenous nature of PIMS-TS highlights the importance of a multidisciplinary approach. Worse inflammatory markers in older children within our cohort may be an indication of a different disease process occurring at different ages. Future work to investigate the association between age and troponin and ferritin in hyperinflammatory states is warranted.

PMID:37433192 | DOI:10.1089/ped.2023.0024

Cornea. 2023 Jul 11. doi: 10.1097/ICO.0000000000003347. Online ahead of print.

ABSTRACT

PURPOSE: Residing in rural locations can be a barrier to health care access. This study investigated the impact of residing in rural and small town (RST) areas on Descemet stripping automated endothelial keratoplasty (DSAEK) indications and outcomes in Atlantic Canada.

METHODS: A retrospective cohort analysis examined consecutive DSAEKs performed in Nova Scotia between 2017 and 2020. Patient rurality was determined by the Statistical Area Classification system developed by Statistics Canada. Univariate and multivariate logistic regression models were used to assess for factors associated with DSAEK indication, including repeat keratoplasty, RST residence status, and travel time.

RESULTS: Of 271 DSAEKs during the study period, 87 (32.1%) were performed on the eyes of RST residents. The median postoperative follow-up time was 1.6 years. Undergoing DSAEK for a previous failed keratoplasty was not associated with a higher odds of RST residency (odds ratio [OR], 0.50; 95% confidence interval [CI], 0.19-1.16; P = 0.13) but was associated with travel time (OR, 0.78 for each increasing hour of travel; 95% CI, 0.61-0.99; P = 0.044). RST residency was not associated with the occurrence of graft failure (OR, 0.48; 95% CI, 0.17-1.17; P = 0.13).

CONCLUSIONS: Residing in a rural area in Atlantic Canada was not associated with DSAEK graft failure. Repeat endothelial keratoplasty was associated with shorter travel time for corneal surgery but not rural residency status. Further research in this field could inform regional health strategies aimed at improving equity and accessibility to ophthalmology subspecialist care.

PMID:37433174 | DOI:10.1097/ICO.0000000000003347

Cir Cir. 2023;91(3):432-436. doi: 10.24875/CIRU.21000783.

ABSTRACT

INTRODUCTION: Spigelian hernia is a rare entity, with higher improbability of acute appendicitis within it.

CASE REPORT: A 75-year-old female with a 30-year evolution hernia, abdominal pain, and fever of 1 week of onset, in whom was found an acute appendicitis within a Spigelian hernia.

DISCUSSION: Spigelian hernia comprises 0.12-2% of all abdominal hernias. Presurgical diagnosis is stablished only in 50% of cases, with an hernial ring less than 2 cm and hidden localization. There isn’t statistics of this complication because of the lack of case reports.

PMID:37433145 | DOI:10.24875/CIRU.21000783

G3 (Bethesda). 2023 Jul 12:jkad143. doi: 10.1093/g3journal/jkad143. Online ahead of print.

ABSTRACT

RNA-sequencing (RNA-seq) technology has led to a surge of neuroscience research using animal models to probe the complex molecular mechanisms underlying brain function and behavior, including substance use disorders (SUDs). However, findings from rodent studies often fail to be translated into clinical treatments. Here, we developed a novel pipeline for narrowing candidate genes from preclinical studies by translational potential and demonstrated its utility in two RNA-seq studies of rodent self-administration. This pipeline uses evolutionary conservation and preferential expression of genes across brain tissues to prioritize candidate genes, increasing the translational utility of RNA-seq in model organisms. Initially, we demonstrate the utility of our prioritization pipeline using an uncorrected p-value. However, we found no differentially-expressed genes (DEGs) in either dataset after correcting for multiple testing (FDR < 0.05 or < 0.1). This is likely due to low statistical power that is common across rodent behavioral studies, and therefore we additionally illustrate use of our pipeline on a third dataset with DEGs corrected for multiple testing (FDR < 0.05). We also advocate for improved RNA-seq data collection, statistical testing, and metadata reporting that will bolster the field’s ability to identify reliable candidate genes and improve the translational value of bioinformatics in rodent research.

PMID:37433118 | DOI:10.1093/g3journal/jkad143

J Natl Cancer Inst. 2023 Jul 11:djad115. doi: 10.1093/jnci/djad115. Online ahead of print.

ABSTRACT

BACKGROUND: Cancer is a leading cause of death by disease among children and adolescents in the United States. This study updates cancer incidence rates and trends using the most recent and comprehensive US cancer registry data available.

METHODS: We used data from US Cancer Statistics to evaluate counts, age-adjusted incidence rates, and trends among children and adolescents aged <20 years diagnosed with malignant tumors during 2003-2019. We calculated average annual percent change and annual percent change (APC) using joinpoint regression. Rates and trends were stratified by demographic and geographic characteristics and by cancer type.

RESULTS: With 248,749 cases reported during 2003-2019, the overall cancer incidence rate was 178.3 per 1 million; incidence rates were highest for leukemia (46.6), central nervous system (CNS) neoplasms (30.8), and lymphoma (27.3). Rates were highest for males, children aged 0-4 years, Non-Hispanic White children and adolescents, those in the Northeast census region, top 25% of counties by economic status, and metropolitan counties with population ≥1 million. While the overall incidence rate of pediatric cancer increased 0.5% per year on average during 2003-2019, the rate increased during 2003-2016 (APC = 1.1%) and then decreased during 2016-2019 (APC = -2.1%). During 2003-2019, rates of leukemia, lymphoma, hepatic tumors, bone tumors, and thyroid carcinomas increased, while melanoma rates decreased. CNS neoplasms rates increased until 2017 and then decreased. Other cancer types remained stable.

CONCLUSIONS: Incidence of pediatric cancer increased overall, although increases were limited to certain cancer types. These findings may guide future public health and research priorities.

PMID:37433078 | DOI:10.1093/jnci/djad115

Invest Radiol. 2023 Jul 12. doi: 10.1097/RLI.0000000000001000. Online ahead of print.

ABSTRACT

OBJECTIVES: The objective of this study is to validate the modulated acoustic radiation force (mARF)-based imaging method in the detection of abdominal aortic aneurysm (AAA) in murine models using vascular endothelial growth factor receptor 2 (VEGFR-2)-targeted microbubbles (MBs).

MATERIALS AND METHODS: The mouse AAA model was prepared using the subcutaneous angiotensin II (Ang II) infusion combined with the β-aminopropionitrile monofumarate solution dissolved in drinking water. The ultrasound imaging session was performed at 7 days, 14 days, 21 days, and 28 days after the osmotic pump implantation. For each imaging session, 10 C57BL/6 mice were implanted with Ang II-filled osmotic pumps, and 5 C57BL/6 mice received saline infusion only as the control group. Biotinylated lipid MBs conjugated to either anti-mouse VEGFR-2 antibody (targeted MBs) or isotype control antibody (control MBs) were prepared before each imaging session and were injected into mice via tail vein catheter. Two separate transducers were colocalized to image the AAA and apply ARF to translate MBs simultaneously. After each imaging session, tissue was harvested and the aortas were used for VEGFR-2 immunostaining analysis. From the collected ultrasound image data, the signal magnitude response of the adherent targeted MBs was analyzed, and a parameter, residual-to-saturation ratio (Rres – sat), was defined to measure the enhancement in the adherent targeted MBs signal after the cessation of ARF compared with the initial signal intensity. Statistical analysis was performed with the Welch t test and analysis of variance test.

RESULTS: The Rres – sat of abdominal aortic segments from Ang II-challenged mice was significantly higher compared with that in the saline-infused control group (P < 0.001) at all 4 time points after osmotic pump implantation (1 week to 4 weeks). In control mice, the Rres – sat values were 2.13%, 1.85%, 3.26%, and 4.85% at 1, 2, 3, and 4 weeks postimplantation, respectively. In stark contrast, the Rres – sat values for the mice with Ang II-induced AAA lesions were 9.20%, 20.6%, 22.7%, and 31.8%, respectively. It is worth noting that there was a significant difference between the Rres – sat for Ang II-infused mice at all 4 time points (P < 0.005), a finding not present in the saline-infused mice. Immunostaining results revealed the VEGFR-2 expression was increased in the abdominal aortic segments of Ang II-infused mice compared with the control group.

CONCLUSIONS: The mARF-based imaging technique was validated in vivo using a murine model of AAA and VEGFR-2-targeted MBs. Results in this study indicated that the mARF-based imaging technique has the ability to detect and assess AAA growth at early stages based on the signal intensity of adherent targeted MBs, which is correlated with the expression level of the desired molecular biomarker. The results may suggest, in very long term, a pathway toward eventual clinical implementation for an ultrasound molecular imaging-based approach to AAA risk assessment in asymptomatic patients.

PMID:37433074 | DOI:10.1097/RLI.0000000000001000

J Chem Inf Model. 2023 Jul 11. doi: 10.1021/acs.jcim.3c00408. Online ahead of print.

ABSTRACT

The complex network of water molecules within the binding pocket of a target protein undergoes alterations upon ligand binding, presenting a significant challenge for conventional molecular modeling methods to accurately characterize and compute the associated energy changes. We have previously developed an empirical method, HydraMap (J. Chem. Inf. Model. 2020, 60, 4359-4375), which employs statistical potentials to predict hydration sites and compute desolvation energy, achieving a reasonable balance between accuracy and speed. In this work, we present its improved version, namely, HydraMap v.2. We updated the statistical potentials for protein-water interactions through an analysis of 17 042 crystal protein structures. We also introduced a new feature to evaluate ligand-water interactions by incorporating statistical potentials derived from the solvated structures of 9878 small organic molecules produced by molecular dynamics simulations. By combining these potentials, HydraMap v.2 can predict and compare the hydration sites in a binding pocket before and after ligand binding, identifying key water molecules involved in the binding process, such as those forming bridging hydrogen bonds and unstable ones that can be replaced. We demonstrated the application of HydraMap v.2 in explaining the structure-activity relationship of a panel of MCL-1 inhibitors. The desolvation energies calculated by summing the energy change of each hydration site before and after ligand binding showed good correlation with known ligand binding affinities on six target proteins. In conclusion, HydraMap v.2 offers a cost-effective solution for estimating the desolvation energy during protein-ligand binding and also is practical in guiding lead optimization in structure-based drug discovery.

PMID:37433022 | DOI:10.1021/acs.jcim.3c00408

Mol Biol Evol. 2023 Jul 11:msad157. doi: 10.1093/molbev/msad157. Online ahead of print.

ABSTRACT

Natural selection leaves a spatial pattern along the genome, with a haplotype distribution distortion near the selected locus that fades with distance. Evaluating the spatial signal of a population-genetic summary statistic across the genome allows for patterns of natural selection to be distinguished from neutrality. Considering the genomic spatial distribution of multiple summary statistics is expected to aid in uncovering subtle signatures of selection. In recent years, numerous methods have been devised that consider genomic spatial distributions across summary statistics, utilizing both classical machine learning and deep learning architectures. However, better predictions may be attainable by improving the way in which features are extracted from these summary statistics. We apply wavelet transform, multitaper spectral analysis, and S-transform to summary statistic arrays to achieve this goal. Each analysis method converts one-dimensional summary statistic arrays to two-dimensional images of spectral analysis, allowing simultaneous temporal and spectral assessment. We feed these images into convolutional neural networks and consider combining models using ensemble stacking. Our modeling framework achieves high accuracy and power across a diverse set of evolutionary settings, including population size changes and test sets of varying sweep strength, softness, and timing. A scan of central European whole-genome sequences recapitulated well-established sweep candidates and predicted novel cancer-associated genes as sweeps with high support. Given that this modeling framework is also robust to missing genomic segments, we believe that it will represent a welcome addition to the population-genomic toolkit for learning about adaptive processes from genomic data.

PMID:37433019 | DOI:10.1093/molbev/msad157

Proc Natl Acad Sci U S A. 2023 Jul 18;120(29):e2303222120. doi: 10.1073/pnas.2303222120. Epub 2023 Jul 11.

ABSTRACT

Many systems in physics, chemistry, and biology exhibit oscillations with a pronounced random component. Such stochastic oscillations can emerge via different mechanisms, for example, linear dynamics of a stable focus with fluctuations, limit-cycle systems perturbed by noise, or excitable systems in which random inputs lead to a train of pulses. Despite their diverse origins, the phenomenology of random oscillations can be strikingly similar. Here, we introduce a nonlinear transformation of stochastic oscillators to a complex-valued function [Formula: see text](x) that greatly simplifies and unifies the mathematical description of the oscillator’s spontaneous activity, its response to an external time-dependent perturbation, and the correlation statistics of different oscillators that are weakly coupled. The function [Formula: see text] (x) is the eigenfunction of the Kolmogorov backward operator with the least negative (but nonvanishing) eigenvalue λ₁ = μ₁ + iω₁. The resulting power spectrum of the complex-valued function is exactly given by a Lorentz spectrum with peak frequency ω₁ and half-width μ₁; its susceptibility with respect to a weak external forcing is given by a simple one-pole filter, centered around ω₁; and the cross-spectrum between two coupled oscillators can be easily expressed by a combination of the spontaneous power spectra of the uncoupled systems and their susceptibilities. Our approach makes qualitatively different stochastic oscillators comparable, provides simple characteristics for the coherence of the random oscillation, and gives a framework for the description of weakly coupled oscillators.

PMID:37432992 | DOI:10.1073/pnas.2303222120

J Am Acad Orthop Surg. 2023 Jul 10. doi: 10.5435/JAAOS-D-23-00062. Online ahead of print.

ABSTRACT

INTRODUCTION: Patients with adolescent idiopathic scoliosis (AIS) are susceptible to high doses of radiation from radiographs. The purpose of this study was to examine the future cost of radiation-induced breast cancer in patients with AIS and its potential financial and mortality impact.

METHODS: A literature review identified articles relating radiation exposure in patients with AIS to increased risk for cancer. Based on population statistics and breast cancer treatment costs in the year 2020, the financial impact of radiation-induced breast cancer and the estimated number of additional deaths per year due to breast cancer for patients with AIS were calculated.

RESULTS: The US female population in 1970 was 205.1 million. Based on a prevalence of 3.0%, an estimated 3.1 million patients had AIS in 1970. With an incidence of breast cancer in the general population of 128.3/100,000 and a standardized incidence ratio of 1.82-2.4 for breast cancer in patients with scoliosis, there will be a 3,282 to 5,603 patient increase in radiation-induced breast cancer in patients with scoliosis over the general population. With a projected base cost of $34,979 per patient for the first year of breast cancer diagnosis in 2020, the cost of radiation-induced breast cancer will be 114.8 to 196.0 million dollars per year. Using a standardized mortality ratio of 1.68 for scoliosis radiation-induced breast cancer, there will be an expected increase in deaths of 420 patients due to breast cancer presumably secondary to radiation exposure in the evaluation and treatment of AIS.

CONCLUSION: The estimated radiation-induced breast cancer financial impact in 2020 will be between 114.8 and 196.0 million dollars per year, with an increase in deaths of 420 patients per year. Low-dose imaging systems reduce radiation exposure by up to 45 times while maintaining sufficient image quality. New low-dose radiography should be used whenever possible with patients with AIS.

LEVEL OF EVIDENCE: Level 5.

PMID:37432975 | DOI:10.5435/JAAOS-D-23-00062