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Nevin Manimala Statistics

Atomically engineered cobaltite layers for robust ferromagnetism

Sci Adv. 2022 Oct 28;8(43):eabq3981. doi: 10.1126/sciadv.abq3981. Epub 2022 Oct 28.

ABSTRACT

Emergent phenomena at heterointerfaces are directly associated with the bonding geometry of adjacent layers. Effective control of accessible parameters, such as the bond length and bonding angles, offers an elegant method to tailor competing energies of the electronic and magnetic ground states. In this study, we construct unit-thick syntactic layers of cobaltites within a strongly tilted octahedral matrix via atomically precise synthesis. The octahedral tilt patterns of adjacent layers propagate into cobaltites, leading to a continuation of octahedral tilting while maintaining substantial misfit tensile strain. These effects induce severe rumpling within an atomic plane of neighboring layers, further triggering the electronic reconstruction between the splitting orbitals. First-principles calculations reveal that the cobalt ions transit to a higher spin state level upon octahedral tilting, resulting in robust ferromagnetism in ultrathin cobaltites. This work demonstrates a design methodology for fine-tuning the lattice and spin degrees of freedom in correlated quantum heterostructures by exploiting epitaxial geometric engineering.

PMID:36306366 | DOI:10.1126/sciadv.abq3981

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Nevin Manimala Statistics

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty

Proc Natl Acad Sci U S A. 2022 Nov;119(44):e2203150119. doi: 10.1073/pnas.2203150119. Epub 2022 Oct 28.

ABSTRACT

This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.

PMID:36306328 | DOI:10.1073/pnas.2203150119

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Nevin Manimala Statistics

Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia

PLoS One. 2022 Oct 28;17(10):e0276688. doi: 10.1371/journal.pone.0276688. eCollection 2022.

ABSTRACT

The objective of this study is to construct a new distribution known as the weighted Burr-Hatke distribution (WBHD). The PDF and CDF of the WBHD are derived in a closed form. Moments, incomplete moments, and the quantile function of the proposed distribution are derived mathematically. Eleven estimate techniques for estimating the distribution parameters are discussed, and numerical simulations are utilised to evaluate the various approaches using partial and overall rankings. According to the findings of this study, it is recommended that the maximum product of spacing (MPSE) estimator of the WBHD is the best estimator according to overall rank table. The actuarial measurements were derived to the suggested distribution. By contrasting the WBHD with other competitive distributions using two different actual data sets collected from the COVID-19 mortality rates, we show the importance and flexibility of the WBHD.

PMID:36306316 | DOI:10.1371/journal.pone.0276688

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Nevin Manimala Statistics

Correlation analysis of combined layers in multiplex networks based on entropy

PLoS One. 2022 Oct 28;17(10):e0276344. doi: 10.1371/journal.pone.0276344. eCollection 2022.

ABSTRACT

The interactions between layers of a multiplex network would generate new structural features, the most prominent feature being the existence of link overlaps between layers. How to capture the associations with the network behavior through the structural interaction between the combined layers of the multiplex network is a critical issue. In this paper, a new structure entropy is proposed by combining the overlapping links between the combined layers of a multiplex network. The correlation between layers is evaluated by structure entropy, and the results are consistent with the behaviors exhibited by the network. In addition, the validity and applicability of the proposed method were verified by conducting trials on four sets of real multiplex network data, which included the multiplex social network of a research department at Aarhus, tailor shop multiplex network, C. elegans multiplex network, and the network collected by Vickers from 29 seventh grade students in a school in Victoria.

PMID:36306315 | DOI:10.1371/journal.pone.0276344

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Nevin Manimala Statistics

Bayesian algorithms for joint estimation of brain activity and noise in electromagnetic imaging

IEEE Trans Med Imaging. 2022 Oct 28;PP. doi: 10.1109/TMI.2022.3218074. Online ahead of print.

ABSTRACT

Simultaneously estimating brain source activity and noise has long been a challenging task in electromagnetic brain imaging using magneto- and electroencephalography. The problem is challenging not only in terms of solving the NP-hard inverse problem of reconstructing unknown brain activity across thousands of voxels from a limited number of sensors, but also for the need to simultaneously estimate the noise and interference. We present a generative model with an augmented leadfield matrix to simultaneously estimate brain source activity and sensor noise statistics in electromagnetic brain imaging (EBI). We then derive three Bayesian inference algorithms for this generative model (expectation-maximization (EBI-EM), convex bounding (EBI-Convex) and fixed-point (EBI-Mackay)) to simultaneously estimate the hyperparameters of the prior distribution for brain source activity and sensor noise. A comprehensive performance evaluation for these three algorithms is performed. Simulations consistently show that the performance of EBI-Convex and EBI-Mackay updates is superior to that of EBI-EM. In contrast to the EBI-EM algorithm, both EBI-Convex and EBI-Mackay updates are quite robust to initialization, and are computationally efficient with fast convergence in the presence of both Gaussian and real brain noise. We also demonstrate that EBI-Convex and EBI-Mackay update algorithms can reconstruct complex brain activity with only a few trials of sensor data, and for resting-state data, achieving significant improvement in source reconstruction and noise learning for electromagnetic brain imaging.

PMID:36306311 | DOI:10.1109/TMI.2022.3218074

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Nevin Manimala Statistics

Diffusion Tensor and Kurtosis Imaging Findings the First Year Following Mild Traumatic Brain Injury

J Neurotrauma. 2022 Oct 28. doi: 10.1089/neu.2022.0206. Online ahead of print.

ABSTRACT

Despite enormous research interest in diffusion tensor and kurtosis imaging (DTI; DKI) following mild traumatic brain injury (MTBI), it remains unknown how diffusion in white matter evolves post-injury and relates to acute MTBI characteristics. This prospective cohort study aimed to characterize diffusion changes in white matter the first year after MTBI. Patients with MTBI (n=193) and matched controls (n=83) underwent 3T MRI within 72 hours and 3- and 12-months post-injury. Diffusion data were analyzed in three steps: (1) voxel-wise comparisons between the MTBI- and control group were performed with tract-based spatial statistics at each time point; (2) clusters of significant voxels identified in (1) were evaluated longitudinally with mixed effect models; (3) the MTBI group was divided into (A) complicated (with macrostructural findings on MRI) and uncomplicated MTBI, (B) long (1-24 hours) and short (< 1 hour) post-traumatic amnesia (PTA), and (C) other and no other concurrent injuries, to investigate if findings in (1) were driven mainly by aberrant diffusion in patients with a more severe injury. At 72 hours, voxel-wise comparisons revealed significantly lower fractional anisotropy (FA) in one tract and significantly lower mean kurtosis (Kmean) in 11 tracts in the MTBI- compared to control group. At 3 months, the MTBI group had significantly higher mean diffusivity in 8 tracts compared to controls. At 12 months, FA was significantly lower in 4 tracts and Kmean in 10 tracts in patients with MTBI compared to controls. There was considerable overlap in affected tracts across time, including the corpus callosum, corona radiata, internal and external capsule, and cerebellar peduncles. Longitudinal analyses revealed that the diffusion metrics remained relatively stable throughout the first year after MTBI. The significant group*time interactions identified were driven by changes in the control- rather than the MTBI group. Further, differences identified in step 1 did not result from greater diffusion abnormalities in patients with complicated MTBI, long PTA, or other concurrent injuries, as standardized mean differences in diffusion metrics between the groups were small (0.07±0.11) and non-significant. However, follow-up voxel-wise analyses revealed that other concurrent injuries had effects on diffusion metrics, but predominantly in other metrics, and at other time points, than the effects observed in the MTBI versus control group analysis. In conclusion, patients with MTBI differed from controls in white matter integrity already 72 hours after injury. Diffusion metrics remained relatively stable throughout the first year after MTBI and were not driven by deviating diffusion in patients with a more severe MTBI.

PMID:36305387 | DOI:10.1089/neu.2022.0206

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Nevin Manimala Statistics

The relationship between segmental trunk control and gross motor performance in low birth weight born infants

Physiother Theory Pract. 2022 Oct 28:1-8. doi: 10.1080/09593985.2022.2140023. Online ahead of print.

ABSTRACT

OBJECTIVE: Trunk control is associated with gross motor development. This study examines the relationship between segmental trunk control and gross motor performance in low birth weight (LBW) infants.

METHODS: A total of 42 LBW infants and 43 normal birth weight (NBW) infants aged 3-9 months were sampled for this cross-sectional study. All infants were evaluated one time by the Segmental Assessment Trunk Control (SATCo) and the Alberta Infant Motor Scale (AIMS).

RESULTS: Statistically high and significant correlations were found between gross motor performance and segmental trunk control in all sample populations (r = 0.835; p = .001). No statistically significant difference was found regarding the segmental trunk control between the groups (p = .119). The LBW infants with atypical motor development had poorer trunk control than the LBW infants with typical development (f = 5.480; p = .001).

CONCLUSION: Our results show that LBW infants with atypical motor development had poorer trunk control than LBW infants with typical motor development. It was found that the segmental trunk controls of LBW infants were 0.398 times lower than in NBW infants.

PMID:36305353 | DOI:10.1080/09593985.2022.2140023

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Nevin Manimala Statistics

Value of conventional ultrasound and shear wave elastography in assessing disease activity and prognosis in female patients with Sjögren’s syndrome

Clin Exp Rheumatol. 2022 Oct 24. doi: 10.55563/clinexprheumatol/20028h. Online ahead of print.

ABSTRACT

OBJECTIVES: This study aimed to assess the diagnostic value of labial salivary gland changes in female patients with Sjögren’s syndrome (SS) having different European League Against Rheumatism (EULAR) Sjögren’s syndrome disease activity index (ESSDAI) and serological markers using conventional ultrasound and shear wave elastography (SWE).

METHODS: A total of 82 female inpatients diagnosed with SS were retrospectively examined at the First Affiliated Hospital of Soochow University from July 2020 to December 2021. The patients were divided into two groups based on the ESSDAI score: remission group (ESSDAI <5) and active group (ESSDAI ≥5). The prognosis of patients was assessed using serological markers. The ultrasound examination of bilateral labial glands was performed in all patients to analyze the quantity and area of the largest single labial gland per unit detection range (Smax). The SWE of labial glands was performed in different groups.

RESULTS: The Smax and quantity of labial glands on both sides were correlated with patient age in 82 female patients with SS. Emin, Emean and Emax of remission group based on ESSDAI were significant lower than active group (p<0.001), and the areas under the receiver operating characteristic(ROC) curve for these three in diagnosing were 0.720, 0.728 and 0.734, respectively. The differences in Emean, Emin and Emax values of labial gland between the two groups of immunoglobulin G (IgG) <16g/L and IgG ≥16g/L were statistically significant differences (p<0.05), and the area under the ROC curve(AUC) for the three values were 0.825, 0.830, and 0.815, respectively. There were statistically significant differences (p < 0.05) in Emin, Emean, and Emax of labial glands between the hypocomplementemic and non-hypocomplementemic groups, and the AUC for the three values were 0.840, 0.843, and 0.819, respectively.

CONCLUSIONS: Conventional ultrasound and SWE of the labial gland can reflect the disease activity and prognosis of patients with SS, and more conveniently assess the progression in the patients and provide imaging evidence.

PMID:36305348 | DOI:10.55563/clinexprheumatol/20028h

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Nevin Manimala Statistics

Investigating predictors of treatment response in Dialectical Behavior Therapy for borderline personality disorder using LASSO regression

Psychother Res. 2022 Oct 28:1-13. doi: 10.1080/10503307.2022.2138790. Online ahead of print.

ABSTRACT

OBJECTIVE: Prior studies of Dialectical Behavior Therapy (DBT) for borderline personality disorder (BPD) have yielded heterogeneous findings on what factors differentiate individuals with or without sufficient treatment response, highlighting the need for further research.

METHOD: We investigated a sample of 105 individuals with BPD receiving a 6-month course of DBT. Participants were categorized as sufficient or insufficient responders using clinical and statistical change indices (based on emotion dysregulation, BPD symptom severity, utilization of DBT skills, and functional impairment). Sociodemographic, clinical severity, and treatment process factors were tested as potential predictors of treatment response using a machine learning approach (LASSO regression).

RESULTS: Two cross-validated LASSO regression models predicted treatment response (AUCs > .75). They suggested that higher homework completion rate, retention in treatment, and greater baseline severity were the most important predictors of DBT treatment response indicated by BPD symptom severity and utilization of DBT skills. Favorable effects of some aspects of therapeutic alliance during initial sessions were also found.

CONCLUSIONS: Future research may benefit from consolidating the criteria of treatment response, identifying clinically relevant variables, and testing the generalizability of findings to enhance knowledge of insufficient treatment response in DBT for BPD.

PMID:36305345 | DOI:10.1080/10503307.2022.2138790

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Nevin Manimala Statistics

Minced Autologous Chondral Fragments with Fibrin Glue as a Simple Promising One-Step Cartilage Repair Procedure: A Clinical and MRI Study at 12-Month Follow-Up

Cartilage. 2022 Oct 28:19476035221126343. doi: 10.1177/19476035221126343. Online ahead of print.

ABSTRACT

OBJECTIVE: The aim of this study was to investigate early radiological and clinical outcome of autologous minced cartilage treatment as a single-step treatment option in patients with a chondral or osteochondral lesion (OCL) in the knee.

DESIGN: Eighteen patients with an OCL in the knee were included. Cartilage from healthy-appearing loose bodies and/or the periphery of the defect were minced into small chips and sealed in the defect using fibrin glue. Preoperatively, and at 3 (n = 14) and 12 (n = 18) months follow-up, magnetic resonance imaging (MRI) was performed. The Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) 2.0 score was used to assess the cartilage repair tissue on MRI at 12 months. The International Knee Documentation Score, Knee Injury and Osteoarthritis Outcome Score, EuroQoL-5D, and Visual Analogue Scale pain were collected preoperatively and 12 months after surgery.

RESULTS: Three months postoperative, MRI showed complete defect filling in 11 out of 14 patients. Mean MOCART 2.0 score at 12 months was 65.0 ± 18.9 with higher scores for lateral femoral chondral lesions compared to medial femoral chondral lesions (75.8 ± 14.3, 52.5 ± 15.8 respectively, P = 0.02). Clinical and statistical significant improvements were observed in the patient-reported outcome measures at 12 months postoperatively compared to preoperatively.

CONCLUSION: Treatment of OCLs using the autologous minced cartilage procedure resulted in good cartilage repair measured by MOCART 2.0. Clinically relevant improvements were observed in the clinical scores. This study suggests autologous minced cartilage as a promising, single-step treatment for OCLs.

PMID:36305343 | DOI:10.1177/19476035221126343