Nevin Manimala

Obesity (Silver Spring). 2023 Aug 9. doi: 10.1002/oby.23813. Online ahead of print.

ABSTRACT

OBJECTIVE: This review aimed to evaluate the association between childhood adiposity and depression and anxiety risk in adulthood.

METHODS: MEDLINE, PsychInfo, Embase, CINAHL, and Scopus were searched on June 6, 2022, to identify studies that investigated the association between childhood weight status (age ≤18 years) and outcomes of depression and/or anxiety in adulthood (age ≥19 years). Study quality was assessed using the Newcastle-Ottawa Scale and results were narratively synthesized.

RESULTS: Sixteen studies were eligible for inclusion, with heterogeneity in methods and follow-up durations complicating comparisons. Six out of eight studies found a statistically significant association between childhood adiposity and increased likelihood of depression in adulthood, particularly in females. However, overall evidence was of moderate quality and study limitations prevented causal conclusions. In contrast, limited evidence and mixed findings were reported for the associations between childhood adiposity and depressive symptom severity or anxiety outcomes in adulthood.

CONCLUSIONS: Evidence suggests that childhood adiposity is associated with greater vulnerability to depression in adulthood, particularly in females. However, further research is warranted to address the limitations discussed. Future research should also explore how changes in weight status from childhood to adulthood might differentially influence the likelihood of depression.

PMID:37555243 | DOI:10.1002/oby.23813

Arthritis Rheumatol. 2023 Aug 9. doi: 10.1002/art.42661. Online ahead of print.

ABSTRACT

OBJECTIVE: A simple, scalable tool that identifies psoriasis patients at high risk for developing psoriatic arthritis (PsA) could improve early diagnosis. We aimed to develop a risk prediction model for the development of PsA and to assess its performance among patients with psoriasis.

METHODS: We analyzed data from a prospective cohort of psoriasis patients without PsA at enrollment. Participants were assessed annually by a rheumatologist for the development of PsA. Information about their demographics, psoriasis characteristics, co-morbidities, medications, and musculoskeletal symptoms was used to develop prediction models for PsA. Penalized binary regression models were used for variable selection while adjusting for psoriasis duration. Risks of developing PsA over 1- and 5-year time periods were estimated. Model performance was assessed by the area under the curve (AUC) and calibration plots.

RESULTS: Among 635 psoriasis patients, 51 and 71 developed PsA during the 1-year and 5-year follow-up periods, respectively. The risk of developing PsA within 1 year was associated with younger age, male sex, family history of psoriasis, back stiffness, nail pitting, joint stiffness, use of biologic medications, patient global health, and pain severity (AUC 72.3). The risk of developing PsA within 5 years was associated with morning stiffness, psoriatic nail lesion, psoriasis severity, fatigue, pain, and use of systemic non-biologic medication or phototherapy (AUC 74.9). Calibration plots showed reasonable agreement between predicted and observed probabilities.

CONCLUSIONS: The development of PsA within clinically meaningful time frames can be predicted with reasonable accuracy for psoriasis patients using readily available clinical variables.

PMID:37555242 | DOI:10.1002/art.42661

J Appl Crystallogr. 2023 Jul 20;56(Pt 4):910-926. doi: 10.1107/S1600576723005344. eCollection 2023 Aug 1.

ABSTRACT

By providing predicted protein structures from nearly all known protein sequences, the artificial intelligence program AlphaFold (AF) is having a major impact on structural biology. While a stunning accuracy has been achieved for many folding units, predicted unstructured regions and the arrangement of potentially flexible linkers connecting structured domains present challenges. Focusing on single-chain structures without prosthetic groups, an earlier comparison of features derived from small-angle X-ray scattering (SAXS) data taken from the Small-Angle Scattering Biological Data Bank (SASBDB) is extended to those calculated using the corresponding AF-predicted structures. Selected SASBDB entries were carefully examined to ensure that they represented data from monodisperse protein solutions and had sufficient statistical precision and q resolution for reliable structural evaluation. Three examples were identified where there is clear evidence that the single AF-predicted structure cannot account for the experimental SAXS data. Instead, excellent agreement is found with ensemble models generated by allowing for flexible linkers between high-confidence predicted structured domains. A pool of representative structures was generated using a Monte Carlo method that adjusts backbone dihedral allowed angles along potentially flexible regions. A fast ensemble modelling method was employed that optimizes the fit of pair distance distribution functions [P(r) versus r] and intensity profiles [I(q) versus q] computed from the pool to their experimental counterparts. These results highlight the complementarity between AF prediction, solution SAXS and molecular dynamics/conformational sampling for structural modelling of proteins having both structured and flexible regions.

PMID:37555230 | PMC:PMC10405597 | DOI:10.1107/S1600576723005344

J Orthop. 2023 Jul 26;43:64-68. doi: 10.1016/j.jor.2023.07.029. eCollection 2023 Sep.

ABSTRACT

BACKGROUND: Cocaine use has surged in the past decade, with 4.8 million Americans (1.7% of the population greater than 12) reporting use in 2021, leading to a healthcare burden of 1.3 billion dollars. Cocaine users experience prolonged hospital stays, higher costs, worse surgical outcomes, increased risk of medical conditions, and inflammation-related osteoarthritis. The study aims to identify factors influencing length of stay, costs, and perioperative complications in cocaine users undergoing total hip arthroplasty (THA) to reduce these risks.

METHODS: This study utilized the NIS database, providing comprehensive information on patient demographics, length of stay, hospital costs, and complications. Statistical analyses were conducted using SPSS software, including propensity matching and significance testing, to compare outcomes between cocaine users (CU) and non-cocaine users (NCU) undergoing total hip arthroplasty.

RESULTS: After propensity matching, cocaine users had a significantly longer LOS (4.8 days) in comparison to non-cocaine users (2.6 days) (p < 0.001). Similarly, the CU group had a larger of care (87984.9) than the NCU group (69149.2) (p < 0.001). Cocaine users had significantly higher rates of blood loss anemia (OR: 3.24, 95% CI: 2.21, 4.73), blood loss anemia (OR: 1.59, 95% CI: 1.12, 2.24), blood transfusion (OR: 2.23, 95% CI: 1.04, 4.78), periprosthetic dislocation (OR: 6.57, 95% CI: 1.47, 29.32), and periprosthetic infection (OR: 4.59, 95% CI: 1.54, 13.68) than patients in the non-cocaine user’s group.

CONCLUSION: Cocaine users had a significantly longer length of stay, higher costs of care, and an increased number of post-operative complications compared to non-cocaine users. These data contribute to understanding the potential ramifications of cocaine users undergoing THA.

PMID:37555205 | PMC:PMC10404604 | DOI:10.1016/j.jor.2023.07.029

J Orthop. 2023 Jul 23;43:25-29. doi: 10.1016/j.jor.2023.07.011. eCollection 2023 Sep.

ABSTRACT

PURPOSE: Image-based Robotic Total knee Arthroplasty (RA-TKA)was developed with the purpose of enhancing the accuracy in determining the component sizes preoperatively and helping surgeons in minimizing errors and improve patient outcomes. The research aims to find the reliability of robotic-assisted TKR based on images in determining the correct component sizes using preoperative three-dimensional (3D) computer tomography.

METHOD: After ethical approval, we conducted a prospective study from March 2022 to December 2022. A total of 100 knees underwent image-based RA-TKA having grade 4 Osteoarthritis knee (Kellegren Lawrence classification). A single senior surgeon performed on all patients. Postoperative implant sizes and fit were assessed by five radiographic markers by an independent observer.

RESULTS: In our study, we found the mean age was (64.96 ± 7.3) years, with female to male ratio of 43:22. The preoperative 3D CT accuracy is 100% for femoral component sizing and 97% for the tibial component. There was a statistically significant improvement in varus deformity from preoperative 7.370 ± 3.70° to 1.24 0 ± 0.910° after surgery., p = 0.001. Improvement in flexion deformity correction was from preoperative 6.50 ± 6.30 to postoperative 1.640 ± 1.770, p = 0.001.

CONCLUSION: Our study concludes that the use of pre-operative 3D CT helps in predicting the component sizes, minimizes surgical time, and enhances implant position accuracy, as well as improves postoperative limb alignment in the coronal and sagittal planes.

PMID:37555200 | PMC:PMC10405159 | DOI:10.1016/j.jor.2023.07.011

Front Neuroimaging. 2022 Jun 23;1:879098. doi: 10.3389/fnimg.2022.879098. eCollection 2022.

ABSTRACT

BACKGROUND: Understanding the relationship between cerebrospinal fluid (CSF) dynamics and intrathecal drug delivery (ITDD) injection parameters is essential to improve treatment of central nervous system (CNS) disorders.

METHODS: An anatomically detailed in vitro model of the complete CSF system was constructed. Patient-specific cardiac- and respiratory-induced CSF oscillations were input to the model in the subarachnoid space and within the ventricles. CSF production was input at the lateral ventricles and CSF absorption at the superior sagittal sinus. A model small molecule simulated drug product containing fluorescein was imaged within the system over a period of 3-h post-lumbar ITDD injections and used to quantify the impact of (a) bolus injection volume and rate, (b) post-injection flush volume, rate, and timing, (c) injection location, and (d) type of injection device. For each experiment, neuraxial distribution of fluorescein in terms of spatial temporal concentration, area-under-the-curve (AUC), and percent of injected dose (%ID) to the brain was quantified at a time point 3-h post-injection.

RESULTS: For all experiments conducted with ITDD administration in the lumbar spine, %ID to the brain did not exceed 11.6% at a time point 3-h post-injection. Addition of a 12 mL flush slightly increased solute transport to the brain up to +3.9%ID compared to without a flush (p < 0.01). Implantation of a lumbar catheter with the tip at an equivalent location to the lumbar placed needle, but with rostral tip orientation, resulted in a small improvement of 1.5%ID to the brain (p < 0.05). An increase of bolus volume from 5 to 20 mL improved solute transport to the brain from 5.0 to 6.3%ID, but this improvement was not statistically significant. Increasing bolus injection rate from 5 to 13.3 mL/min lacked improvement of solute transport to the brain, with a value of 6.3 compared to 5.7%ID.

CONCLUSION: The in vitro modeling approach allowed precisely controlled and repeatable parametric investigation of ITDD injection protocols and devices. In combination, the results predict that parametric changes in lumbar spine ITDD-injection related parameters and devices can alter %ID to the brain and be tuned to optimize therapeutic benefit to CNS targets.

PMID:37555174 | PMC:PMC10406265 | DOI:10.3389/fnimg.2022.879098

Front Neuroimaging. 2023 Jan 10;1:1070151. doi: 10.3389/fnimg.2022.1070151. eCollection 2022.

ABSTRACT

Functional MRI (fMRI) has become a popular technique to study brain functions and their alterations in psychiatric and neurological conditions. The sample sizes for fMRI studies have been increasing steadily, and growing studies are sourced from open-access brain imaging repositories. Quality control becomes critical to ensure successful data processing and valid statistical results. Here, we outline a simple protocol for fMRI data pre-processing and quality control based on statistical parametric mapping (SPM) and MATLAB. The focus of this protocol is not only to identify and remove data with artifacts and anomalies, but also to ensure the processing has been performed properly. We apply this protocol to the data from fMRI Open quality control (QC) Project, and illustrate how each quality control step can help to identify potential issues. We also show that simple steps such as skull stripping can improve coregistration between the functional and anatomical images.

PMID:37555150 | PMC:PMC10406300 | DOI:10.3389/fnimg.2022.1070151

Front Neuroimaging. 2022 Oct 26;1:981642. doi: 10.3389/fnimg.2022.981642. eCollection 2022.

ABSTRACT

Methods for the analysis of neuroimaging data have advanced significantly since the beginning of neuroscience as a scientific discipline. Today, sophisticated statistical procedures allow us to examine complex multivariate patterns, however most of them are still constrained by assuming inherent linearity of neural processes. Here, we discuss a group of machine learning methods, called deep learning, which have drawn much attention in and outside the field of neuroscience in recent years and hold the potential to surpass the mentioned limitations. Firstly, we describe and explain the essential concepts in deep learning: the structure and the computational operations that allow deep models to learn. After that, we move to the most common applications of deep learning in neuroimaging data analysis: prediction of outcome, interpretation of internal representations, generation of synthetic data and segmentation. In the next section we present issues that deep learning poses, which concerns multidimensionality and multimodality of data, overfitting and computational cost, and propose possible solutions. Lastly, we discuss the current reach of DL usage in all the common applications in neuroimaging data analysis, where we consider the promise of multimodality, capability of processing raw data, and advanced visualization strategies. We identify research gaps, such as focusing on a limited number of criterion variables and the lack of a well-defined strategy for choosing architecture and hyperparameters. Furthermore, we talk about the possibility of conducting research with constructs that have been ignored so far or/and moving toward frameworks, such as RDoC, the potential of transfer learning and generation of synthetic data.

PMID:37555142 | PMC:PMC10406264 | DOI:10.3389/fnimg.2022.981642

Iran Biomed J. 2023 Apr 26. doi: 10.52547/ibj.3885. Online ahead of print.

ABSTRACT

BACKGROUND: The majority of insecticides target sodium channels. The increasing emergence of resistance to the current insecticides has persuaded researchers to search for alternative compounds. Scorpion venom gland as a reservoir of peptides or proteins, which selectively target insect sodium channels. These proteins would be an appropriate source for finding new suitable anti-insect components.

METHODS: Transcriptome of venom gland of scorpion M. eupeus was obtained by RNA extraction and cDNA library synthesis. The obtained transcriptome was blasted against protein databases to find insect toxins against sodium channel based on the statistically significant similarity in sequence. Physicochemical properties of the identified protein were calculated using bioinformatics software. The 3D structure of this protein was determined using homology modeling, and the final structure was assessed by MD simulation.

RESULTS: The sodium channel blocker found in the transcriptome of M. eupeus venom gland was submitted to the GenBank under the name of meuNa10, a stable hydrophilic protein consisting of 69 amino acids, with the molecular weight of 7721.77 g/mol and pI of 8.7. The tertiary structure of meuNa10 revealed a conserved CS-alpha/beta domain stabilized by eight cysteine residues. The meuNa10 is a member of the 3FP superfamily consisting of three finger-like beta strands.

CONCLUSION: This study identified meuNa10 as a small insect sodium channel-interacting protein with some physicochemical properties, including stability and water-solubility, which make it a good candidate for further in vivo and in vitro experiments in order to develop a new bioinsecticide.

PMID:37553755 | DOI:10.52547/ibj.3885

Nutr Rev. 2023 Aug 8:nuad096. doi: 10.1093/nutrit/nuad096. Online ahead of print.

ABSTRACT

CONTEXT: The metabolic response to stress can deplete the remaining thiamine stores, leading to thiamine deficiency.

OBJECTIVE: This study is the first meta-analysis of the effectiveness of thiamine supplementation on clinical and biochemical outcomes in adult patients admitted to the intensive care unit (ICU).

DATA SOURCES: Scopus, PubMed, and Cochrane databases were searched to select studies up to 20 November 2022.

STUDY SELECTION: Studies investigating the effect of thiamine supplementation on serum lactate and creatinine levels, the need for renal replacement therapy, length of ICU stay, and mortality rate in ICU patients were selected.

DATA EXTRACTION: After excluding studies based on title and abstract screening, 2 independent investigators reviewed the full texts of the remaining articles. In the next step, a third investigator resolved any discrepancy in the article selection process.

RESULTS: Of 1628 retrieved articles, 8 were selected for final analysis. This study showed that thiamine supplementation reduced the serum creatinine level (P = .03) compared with placebo. In addition, according to subgroup analysis, serum creatinine concentration was significantly lower in patients >60 years old (P < .00001). However, there was no statistically significant difference in the lactate level between the thiamine supplementation and placebo groups (P = .26). Thiamine supplementation did not decrease the risk of all-cause mortality (P = .71) or the need for renal replacement therapy (P = .14). The pooled results of eligible randomized controlled trials also showed that thiamine supplementation did not reduce the length of ICU stay in comparison to the placebo group (P = .39).

CONCLUSION: This meta-analysis provides evidence that thiamine supplementation has a protective effect against blood creatinine increase in ICU patients. However, further high-quality trials are needed to discover the effect of thiamine supplementation on clinical and biochemical outcomes in ICU patients.

SYSTEMATIC REVIEW REGISTRATION: PROSPERO no. CRD42023399710 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=399710).

PMID:37553224 | DOI:10.1093/nutrit/nuad096