Category: Nevin Manimala

IEEE Trans Pattern Anal Mach Intell. 2023 Feb 16;PP. doi: 10.1109/TPAMI.2023.3245886. Online ahead of print.

ABSTRACT

The study of languages’ structure and their organization in a set of well-defined relation schemes is a delicate matter. In the last decades, the convergence of traditional conflicting views by linguists is supported by an interdisciplinary approach that involves not only genetics or bio-archelogy but nowadays even the science of complexity. In light of this new and useful approach, this study proposes an in-depth analysis of the complexity underlying the morphological organization, in terms of multifractality and long-range correlations, of several modern and ancient texts pertaining to various linguistic strains (including ancient Greek, Arabic, Coptic, Neo-Latin and Germanic languages). The methodology is grounded on the mapping procedure between lexical categories belonging to text excerpts and time series, which is based on the rank of the frequency occurrence. Through the well-known MFDFA technique and a specific multifractal formalism, several multifractal indexes are then extracted for characterizing texts and the multifractal signature has been adopted for characterizing several language families, such as Indo-European, Semitic and Hamito-Semitic. The regularities and differences in the linguistic strains are assessed within a multivariate statistical framework and corroborated with a Machine Learning approach that is dedicated, in turn, to investigate the predictive power of the multifractal signature pertinent to text excerpts. The obtained results show a strong presence of persistence, i.e., memory, in the morphological structure of analyzed texts and we claim that this property has a role in characterizing the studied linguistic families. In fact, for example, the proposed analysis framework – grounded on complexity indexes – is able to easily distinguish ancient Greek texts from Arabic ones, as they belong to different language strains, i.e. indo-European and Semitic, respectively. The proposed approach has been proven effective and can be adopted for further comparative studies and for designing new informetrics for further advances in the fields of information retrieval and Artificial Intelligence.

PMID:37027765 | DOI:10.1109/TPAMI.2023.3245886

IEEE/ACM Trans Comput Biol Bioinform. 2023 Feb 28;PP. doi: 10.1109/TCBB.2023.3247957. Online ahead of print.

ABSTRACT

Cellular microscopy imaging is a common form of data acquisition for biological experimentation. Observation of gray-level morphological features allows for the inference of useful biological information such as cellular health and growth status. Cellular colonies can contain multiple cell types, making colony level classification very difficult. Additionally, cell types growing in a hierarchical, downstream fashion, can often look visually similar, although biologically distinct. In this paper, it is determined empirically that traditional deep Convolutional Neural Networks (CNN) and classical object recognition techniques are not sufficient to distinguish between these subtle visual differences, resulting in misclassifications. Instead, Triplet-net CNN learning is employed in a hierarchical classification scheme to improve the ability of the model to discern distinct, fine-grain features of two commonly confused morphological image-patch classes, namely Dense and Spread colonies. The Triplet-net method improves classification accuracy over a four-class deep neural network by 3 %, a value that was determined to be statistically significant, as well as existing state-of-the-art image patch classification approaches and standard template matching. These findings allow for the accurate classification of multi-class cell colonies with contiguous boundaries, and increased reliability and efficiency of automated, high-throughput experimental quantification using non-invasive microscopy.

PMID:37027755 | DOI:10.1109/TCBB.2023.3247957

IEEE Trans Med Imaging. 2023 Feb 22;PP. doi: 10.1109/TMI.2023.3247941. Online ahead of print.

ABSTRACT

We present an unsupervised domain adaptation method for image segmentation which aligns high-order statistics, computed for the source and target domains, encoding domain-invariant spatial relationships between segmentation classes. Our method first estimates the joint distribution of predictions for pair of pixels whose relative position corresponds to a given spatial displacement. Domain adaptation is then achieved by aligning the joint distributions of source and target images, computed for a set of displacements. Two enhancements of this method are proposed. The first one uses an efficient multi-scale strategy that enables capturing long-range relationships in the statistics. The second one extends the joint distribution alignment loss to features in intermediate layers of the network by computing their cross-correlation. We test our method on the task of unpaired multi-modal cardiac segmentation using the Multi-Modality Whole Heart Segmentation Challenge dataset and prostate segmentation task where images from two datasets are taken as data in different domains. Our results show the advantages of our method compared to recent approaches for cross-domain image segmentation. Code is available at https://github.com/WangPing521/Domain_adaptation_shape_prior.

PMID:37027662 | DOI:10.1109/TMI.2023.3247941

Curr Cancer Drug Targets. 2023 Apr 7. doi: 10.2174/1568009623666230407101128. Online ahead of print.

ABSTRACT

BACKGROUND: The optimal second-line therapy for hormone receptor-positive (HR+)/ human epidermal growth factor receptor 2 negative (HER2-) advanced or metastatic breast cancer is yet to be established. Therefore, we conducted a network meta-analysis (NMA) of marketed drugs to compare their efficacy.

METHODS: We searched the literature in PubMed, Embase, Web of Science databases, and the main international conferences in the past 5 years to find phase III clinical trials on drugs available in the market. Network meta-analysis of progression-free survival (PFS), overall survival (OS), and the objective response rate (ORR) was performed using R software. The efficiency of treatment options was compared using hazard ratios and 95% credibility intervals.

RESULTS: Overall, 12 studies with 6120 patients were included in the analysis. In an indirect comparison of the five regimens, cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) plus 500 mg fulvestrant (Ful500) gave the best PFS results; palbociclib ranked first with a surface under the cumulative ranking (SUCRA) of 94.99%, followed by mammalian target of rapamycin inhibitor (mTORi) plus everolimus (SUCRA=73.07%), phosphoinositide 3-kinase inhibitor (PI3Ki) plus Ful500 (SUCRA=66.73%), Ful500 alone (SUCRA=44.55%), and histone deacetylase inhibitor (HDACi) plus exemestane (SUCRA=43.49%). However, no significant difference was found in the PFS rates of CDK4/6i, mTORi, and PI3Ki. For OS, CDK4/6i plus Ful500 ranked first; the SUCRA of ribociclib, abemaciclib, and palbociclib were 86.20%, 83.98%, and 78.52%, respectively. Alpelisib plus Ful500 (SUCRA=66.91%) ranked second but was not statistically different from CDK4/6i. The mTORi plus everolimus group had the best ORR (SUCRA=88.73%). In terms of safety, 81.56% of patients in the tucidinostat plus exemestane regimen developed neutropenia, suggesting strong hematological toxicity; 13.40% of patients developed grade 3-4 diarrhea after using abemaciclib plus Ful500.

CONCLUSION: For second-line endocrine therapy in HR+/HER2- advanced/metastatic breast cancer, CDK4/6i is a better choice than mTORi, PI3Ki, HDACi, and Ful; it shows good PFS and OS outcomes and a low probability for serious adverse events.

PMID:37026492 | DOI:10.2174/1568009623666230407101128

Pediatr Blood Cancer. 2023 Apr 7:e30346. doi: 10.1002/pbc.30346. Online ahead of print.

ABSTRACT

BACKGROUND: Youth with sickle cell disease (SCD) experience increased rates of neurocognitive and emotional difficulties. Cross-sectional studies suggest neurocognitive and emotional functioning are associated with health outcomes in SCD. We investigated whether neurocognitive and emotional factors predicted future pain-related healthcare utilization in children with SCD.

PROCEDURE: Total 112 youth with SCD between ages 7 and 16 years reported sociodemographics and completed measures of neurocognitive functioning and emotional well-being. The number of emergency department (ED) visits and hospitalizations for pain 1 and 3 years after enrollment were determined by chart review.

RESULTS: The mean age of participants was 10.61 years (standard deviation = 2.91), with most being female (n = 65; 58%). Eighty-three (74%) participants had either HbSS or HbSβ⁰ thalassemia. Regression analyses showed that attention significantly predicted ED visits and hospitalizations for pain at 1 and 3 years after enrollment (all p-values ≤ .017), such that poorer attention was associated with higher healthcare utilization. Lower emotional quality of life also predicted more ED visits for pain at 3 years (b = -.009, p = .013) and hospitalizations for pain at 3 years (b = -.008, p = .020).

CONCLUSIONS: Neurocognitive and emotional factors are associated with subsequent healthcare use in youth with SCD. Poor attentional control might limit implementation of strategies to distract from pain or could make disease self-management behaviors more challenging. Results also highlight the potential impact of stress on pain onset, perception, and management. Clinicians should consider neurocognitive and emotional factors when developing strategies to optimize pain-related outcomes in SCD.

PMID:37026487 | DOI:10.1002/pbc.30346

Stroke. 2023 Apr 7. doi: 10.1161/STROKEAHA.122.040529. Online ahead of print.

ABSTRACT

BACKGROUND: Anti-inflammatory therapies reduce recurrent vascular events in coronary disease. Existing studies have reported highly conflicting findings for the association of blood inflammatory markers with vascular recurrence after stroke leading to uncertainty about the potential of anti-inflammatory therapies after stroke and no consensus about the utility of measurement of inflammatory markers in current guidelines.

METHODS: We investigated the association between hsCRP (high-sensitivity C-reactive protein), IL-6 (interluekin-6), and recurrent major adverse cardiovascular events (MACE), and stroke from individual participant data from 8420 patients with ischemic stroke/transient ischemic attack from 10 prospective studies. We did within-study multivariable regression analyses and then combined adjusted risk ratio (RR) by random-effects meta-analysis.

RESULTS: During 18 920 person-years of follow-up, 1407 (16.7% [95% CI, 15.9-17.5]) patients had MACE and 1191 (14.1% [95% CI, 13.4-14.9]) patients had recurrent stroke. On bivariate analysis, baseline IL-6 was associated with MACE (RR, 1.26 [95% CI, 1.10-1.43]) and recurrent stroke (RR, 1.18 [95% CI, 1.05-1.32]), per unit increase log_eIL-6. Similar associations were observed for hsCRP (MACE RR, 1.19 [95% CI, 1.09-1.29]; recurrent stroke RR, 1.12 [95% CI, 1.04-1.21], per unit increase log_ehsCRP). After adjustment for vascular risk factors and treatment, independent associations remained with MACE (IL-6, RR, 1.12 [95% CI, 1.04-1.21]; hsCRP, RR, 1.09 [95% CI, 1.04-1.15]) and recurrent stroke (IL-6, RR, 1.09 [95% CI, 1.00-1.19]; hsCRP, RR, 1.05 [95% CI, 1.00-1.11]). Comparing the top with the bottom quarters (Q4 versus Q1), IL-6 (RR, 1.35 [95% CI, 1.09-1.67]) and hsCRP (RR, 1.31 [95% CI, 1.07-1.61]) were associated with MACE after adjustment. Similar results were observed for recurrent stroke for IL-6 (RR, 1.33 [95% CI, 1.08-1.65]) but not hsCRP (RR, 1.16 [95% CI, 0.93-1.43]).

CONCLUSIONS: Blood markers of inflammation were independently associated with vascular recurrence after stroke, strengthening the rationale for randomized trials of anti-inflammatory therapies for secondary prevention after ischemic stroke/TIA.

PMID:37026458 | DOI:10.1161/STROKEAHA.122.040529

J Magn Reson Imaging. 2023 Apr 7. doi: 10.1002/jmri.28698. Online ahead of print.

ABSTRACT

BACKGROUND: Preventing sepsis-associated acute kidney injury (S-AKI) can be challenging because it develops rapidly and is often asymptomatic. Probability assessment of disease progression for therapeutic follow-up and outcome are important to intervene and prevent further damage.

PURPOSE: To establish a noninvasive multiparametric MRI (mpMRI) tool, including T₁ , T₂ , and perfusion mapping, for probability assessment of the outcome of S-AKI.

STUDY TYPE: Preclinical randomized prospective study.

ANIMAL MODEL: One hundred and forty adult female SD rats (65 control and 75 sepsis).

FIELD STRENGTH/SEQUENCE: 9.4T; T₁ and perfusion map (FAIR-EPI) and T₂ map (multiecho RARE).

ASSESSMENT: Experiment 1: To identify renal injury in relation to sepsis severity, serum creatinine levels were determined (31 control and 35 sepsis). Experiment 2: Animals underwent mpMRI (T₁ , T₂ , perfusion) 18 hours postsepsis. A subgroup of animals was immediately sacrificed for histology examination (nine control and seven sepsis). Result of mpMRI in follow-up subgroup (25 control and 33 sepsis) was used to predict survival outcomes at 96 hours.

STATISTICAL TESTS: Mann-Whitney U test, Spearman/Pearson correlation (r), P < 0.05 was considered statistically significant.

RESULTS: Severely ill septic animals exhibited significantly increased serum creatinine levels compared to controls (70 ± 30 vs. 34 ± 9 μmol/L, P < 0.0001). Cortical perfusion (480 ± 80 vs. 330 ± 140 mL/100 g tissue/min, P < 0.005), and cortical and medullary T₂ relaxation time constants were significantly reduced compared to controls (41 ± 4 vs. 37 ± 5 msec in cortex, P < 0.05, 52 ± 7 vs. 45 ± 6 msec in medulla, P < 0.05). The combination of cortical T₂ relaxation time constants and perfusion results at 18 hours could predict survival outcomes at 96 hours with high sensitivity (80%) and specificity (73%) (area under curve of ROC = 0.8, J_max = 0.52).

DATA CONCLUSION: This preclinical study suggests combined T₂ relaxation time and perfusion mapping as first line diagnostic tool for treatment planning.

LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

PMID:37026419 | DOI:10.1002/jmri.28698

J Dermatolog Treat. 2023 Apr 7:1-27. doi: 10.1080/09546634.2023.2200570. Online ahead of print.

ABSTRACT

BACKGROUND: Topical medication is the mainstay for treatment of mild psoriasis. However, dissatisfaction with topicals is common and rates of non-adherence are high. Assessing patients’ perspectives can help to identify unmet needs.

OBJECTIVE: Our aim was to investigate satisfaction of patients with psoriasis with topical therapy and to determine influencing factors.

METHODS: Patients were recruited from the Department of Dermatology, University Medical Center Mannheim, Germany. Satisfaction was assessed using the Treatment Satisfaction Questionnaire for Medication version 1.4 with the domains effectiveness, side effects, convenience, and global satisfaction (scale 0-100 each). The impact of sociodemographic and disease characteristics was determined by multivariate regression.

RESULTS: Averaged across the cohort (n = 122, mean age 52.5 years, 58.2% male), the side effects domain had the highest mean satisfaction score (89.7), followed by convenience (72.5), global satisfaction (60.8) and effectiveness (55.0). Comparing specific medications, combinations of corticosteroids and vitamin D analogues were rated best in effectiveness. Treatment satisfaction was influenced by age, partnership, ability to apply topicals independently, disease-related quality-of-life impairment, sole or adjunctive use of topicals and pruritus.

CONCLUSIONS: Participants were particularly satisfied with safety but rather dissatisfied with effectiveness of topicals. Topical therapy should be adapted to individual needs with special attention to effectiveness.

PMID:37026416 | DOI:10.1080/09546634.2023.2200570

Disabil Rehabil. 2023 Apr 7:1-6. doi: 10.1080/09638288.2023.2194682. Online ahead of print.

ABSTRACT

PURPOSE: Translate, investigate reliability, and construct validity of the Brazilian Early Activity Scale for Endurance (EASE).

MATERIALS AND METHODS: Translation followed the international guidelines. Test-retest reliability was tested by 100 parents of children with cerebral palsy (CP): 18 months-5 years and 6-11 years. To determine construct validity, 94 parents of typically children completed the EASE. Statistical analysis included Bland-Altman, Intraclass Correlation Coefficient (ICC), Internal Consistency, and Floor and Ceiling Effect.

RESULTS: The majority of the sample consisted of children with CP in GMFCS (IV-V). EASE showed good test-retest reliability for younger (ICC = 0.8) and excellent test-retest reliability for older children with CP (ICC = 0.9), and good internal consistency of 0.7 and 0.8 for the young and older group, respectively. Bland-Altman showed the bias close to zero, with no ceiling or floor effect. Regarding construct validity, younger children showed lower scores when compared to the older children. Endurance differed significantly between children with CP who were walking and those who were not walking and also for age groups. Children with CP showed lower endurance compared to typically participants in the same age group.

CONCLUSIONS: Brazilian EASE is reliable and valid to estimate endurance in children with CP. Results provide evidence of construct validity.

PMID:37026412 | DOI:10.1080/09638288.2023.2194682

Am J Epidemiol. 2023 Apr 7:kwad081. doi: 10.1093/aje/kwad081. Online ahead of print.

ABSTRACT

Monitoring morbidity and mortality in resurgences of respiratory infections has been underpinned with the epidemic of COVID-19 and poses significant challenges. For example, case fatality rates and deaths attributed to specific respiratory pathogens are known to suffer from significant biases undermining their comparability through time and space. As a result, it is difficult to evaluate the protective effect of public health interventions or quantify the impact of a resurgence to the general population through direct recording of COVID-19 related deaths. To overcome these limitations, it has been proposed that more robust less biased metrics, such as the all-cause deaths, can be used to monitor the effect of an epidemic over a population and over time. More specifically, metrics of excess mortality over time, which have been used for influenza surveillance in the past, are increasingly considered important for COVID-19 surveillance. Here, we discuss excess mortality surveillance focusing on standardised single-point and standardised cumulative metrics that allow comparability of excess mortality through space and time. We explain why z-score allows for comparison of excess mortality between countries and different periods, while cumulative z-score allows assessment of excess mortality over long periods. Our commentary re-iterates the importance of standardised statistics of excess mortality for COVID-19 surveillance as we move towards co-existence with SARS-CoV-2 that will allow drawing conclusions from best practices in different health systems and different periods.

PMID:37026399 | DOI:10.1093/aje/kwad081