Tag: nevin manimala

J Arthroplasty. 2023 Aug 25:S0883-5403(23)00865-3. doi: 10.1016/j.arth.2023.08.055. Online ahead of print.

ABSTRACT

BACKGROUND: The use of antibiotic-impregnated cement during two-stage revision arthroplasty for periprosthetic joint infection poses a risk of renal complications following spacer insertion. This systematic review aimed to investigate the rate of acute kidney injury (AKI) following antibiotic-loaded spacer insertion and to identify risk factors associated with this complication.

METHODS: A systematic review was performed using PubMed, Cochrane Central, and Scopus databases. All clinical studies that documented renal complications following antibiotic-loaded spacer insertion for periprosthetic knee (TKA) or hip (THA) infection were included. Articles that combined THA and TKA outcomes were also included and labeled ‘THA+TKA.’ Descriptive statistics were analyzed when data were available.

RESULTS: There were 24 studies (9 THA, 7 TKA, 8 THA+TKA) included. Mean incidences of spacer-related AKI across THA, TKA, and THA+TKA cohorts were 4.2 (range, 0 to 10%), 14 (range, 0 to 19%), and 27% (range, 0 to 35%), respectively. The most common patient-related risk factors for AKI were underlying CKD or high baseline creatinine, low preoperative hemoglobin, and blood transfusion requirement. Spacer-related risk factors included high antibiotic dosage (>3.6 g/cement batch) and antibiotic type. While most recovered without complication, select patients required hemodialysis for acute management (2 THA, 18 THA+TKA) and/or developed chronic kidney disease (CKD) (8 TKA, 8 THA).

CONCLUSION: The rate of AKI following spacer insertion was high and likely under-reported in the literature. Surgeons should be cognizant of this devastating complication and should closely monitor at-risk patients for AKI following antibiotic-loaded spacer insertion.

PMID:37634877 | DOI:10.1016/j.arth.2023.08.055

J Pharm Sci. 2023 Aug 25:S0022-3549(23)00337-4. doi: 10.1016/j.xphs.2023.08.018. Online ahead of print.

ABSTRACT

In-vitro models are available in the literature for predicting the volume of distribution at steady-state (Vd_ss) of drugs. The mechanistic model refers to the tissue composition-based model (TCM), which includes important factors that govern Vd_ss such as drug physiochemistry and physiological data. The recognized TCM published by Rodgers and Rowland (TCM-RR) and a subsequent adjustment made by Simulations Plus Inc. (TCM-SP) have been shown to be generally less accurate with neutral compared to ionized drugs. Therefore, improving these models for neutral drugs becomes necessary. The objective of this study was to propose a new TCM for improving the prediction of Vd_ss for neutral drugs. The new TCM included two modifications of the published models (i) accentuate the effect of the blood-to-plasma ratio (BPR) that should cover permeated molecules across the biomembranes, which is lacking in these models for neutral compounds, and (ii) use a different approach to estimate the binding in tissues. The new TCM was validated with a large dataset of 202 commercial and proprietary compounds including preclinical and clinical data. All scenario datasets were predicted more accurately with the TCM-New, whereas all statistical parameters indicate that the TCM-New showed significant improvements in terms of accuracy over the TCM-RR and TCM-SP. Predictions of Vd_ss were frequently more accurate for the TCM-new with 83% within twofold error versus only 50% for the TCM-RR. Overall, the new TCM incorporating BPR significantly improved the Vd_ss predictions in animals and humans for neutral drugs, and, hence, has the potential to better support the drug discovery and facilitate the first-in-human predictions.

PMID:37634869 | DOI:10.1016/j.xphs.2023.08.018

Adv Nutr. 2023 Aug 25:S2161-8313(23)01358-3. doi: 10.1016/j.advnut.2023.08.009. Online ahead of print.

ABSTRACT

BACKGROUND: Vitamin A deficiency (VAD) increases risk for morbidity and mortality. Food-based approaches offer one strategy to improve vitamin A status.

OBJECTIVE: This systematic review assessed evidence of the effects of food-based approaches on the vitamin A status of women and children under five years.

METHODS: VAD was defined as clinical ocular symptoms, such as loss of vision, and/or retinol plasma or serum concentration <0.70 μmol/L. Searches on food-based approaches to improve vitamin A status were conducted for the period 2011-2022 on PubMed, CINHAL, Web of Science, and Google Scholar using PRISMA guidelines. English language publications were included. Case studies, unpublished dissertations, and non-peer-reviewed studies were excluded.

RESULTS: This review comprises 24 of 27,322 identified studies; 23 included studies focused on provitamin A carotenoids. There were 17, 214 participants across the 24 studies with sample sizes ranging from 8 to 3571 individuals. Intervention studies spanned from three weeks to two years. Fifteen (63%) studies were randomized control trials, seven were cross-sectional, and two were longitudinal studies. Most studies (N = 21) used biochemical measurements, e.g. serum retinol, to assess vitamin A status; other studies used clinical symptoms (e.g. xerophtalmia) or dietary intake. Thirteen (54%) studies reported a statistically significant effect of food-based interventions (N = 8) or an association of diet (N= 5) on vitamin A status.

CONCLUSIONS: This systematic review indicated that some food-based interventions improved vitamin A status, thus offering a safe and effective delivery mechanism for vitamin A. There appeared to be significant association between vitamin A status and consumption of foods with high concentrations of preformed vitamin A and provitamin A carotenoids. Differences across studies in regard to the period of evaluation, food approaches used, and statistical power may explain the lack of effectiveness of food-based approaches on vitamin A status in some studies.

PMID:37634852 | DOI:10.1016/j.advnut.2023.08.009

J Vasc Interv Radiol. 2023 Aug 25:S1051-0443(23)00635-8. doi: 10.1016/j.jvir.2023.08.024. Online ahead of print.

ABSTRACT

PURPOSE: To compare the mechanistic effects and hypertrophy outcomes using two different PVE regimens in normal and cirrhotic livers in a large animal model.

METHODS AND MATERIALS: The Institutional Animal Care and Use Committee (IACUC) approved all conducted experiments. Fourteen female Yorkshire pigs were separated into a cirrhotic (CG, n=7) and non-cirrhotic group (NCG, n=7); further subgrouped into using microspheres and coils (MC, n=3) or n-butyl-cyanoacrylate (NBCA, n=3) and their corresponding controls (each n=1). A 3:1 ethiodized-oil and ethanol-mixture was administered intraarterially in the CG to induce cirrhosis four-weeks before PVE. Animals received baseline-CT, PVE including pre- and post-PVE pressure-measurements and CT-imaging two and four-weeks post-PVE. Immunofluorescence staining’s for CD3, CD16, Ki-67 and Caspase-3 were conducted to assess immune-cell infiltration, hepatocyte-proliferation and apoptosis. Statistical significance was tested using Student’s t-test.

RESULTS: Four-weeks post-PVE, the FLR% increased by 18.82% (SD:3.55%) vs. 10.93% (SD:0.95% (p<0.01) in the NCG vs. CG. Control baseline sFLR% was 41.59% vs. 43.57%. Seperated by the embolic-agents the standardized FLR% (sFLR%) two-weeks post-PVE was 58.43% (SD:3.66%) and 52.24% (SD:0.88%) (p<0.01) for MC in the NCG vs. CG and 46.02% (SD:2.24%) and 47.24% (SD:0.40%) for NBCA, respectively. sFLR% four-weeks post-PVE was 60.48% (SD:3.88%) and 54.85% (SD:0.83%) (p<0.01), and 60.35% (SD:3.45%) and 54.15% (SD:0.95%) (p<0.01), respectively. Ki-67 signal intensity was increased in the embolized lobe both in the CG and NCG (p<0.01).

CONCLUSIONS: This pre-clinical study demonstratess that MC could be the preferred embolic of choice compared to NBCA when a substantial and rapid FLR increase is needed for resection, both in cirrhotic and non-cirrhotic liver.

PMID:37634850 | DOI:10.1016/j.jvir.2023.08.024

J Affect Disord. 2023 Aug 25:S0165-0327(23)01099-6. doi: 10.1016/j.jad.2023.08.120. Online ahead of print.

ABSTRACT

BACKGROUND: Serum insulin levels and insulin sensitivity can impact mental disorders. This study investigates the association of the insulinemic potential of diet calculated using the empirical dietary indices for insulin resistance (EDIR) and hyperinsulinemia (EDIH) with psychological disorders, including depression, anxiety, and stress.

METHODS: This cross-sectional study was undertaken on 5405 individuals, aged 20-70, from the Yazd Health Study (YaHS). The food frequency questionnaire (FFQ) was used to collect dietary intakes. EDIR and EDIH were calculated from the FFQ data. Psychological disorders were assessed by an Iranian-validated version of the depression, anxiety, and stress scale questionnaire 21 (DASS 21). Multivariable logistic regression analysis was performed and odds ratio (OR) and 95 % confidence interval (CI) were reported.

RESULTS: The mean ± SD of EDIR and EDIH were 0.32 ± 0.17 and 0.11 ± 0.08 in the total population, respectively. In the final adjusted model, participants in the highest versus the lowest quartile of EDIR had statistically higher odds of depression (OR: 1.28; 95 % CI: 1.01-1.62, P-trend = 0.032). However, no statistically significant association was observed between the EDIH score and depression. Also, EDIR and EDIH scores were not significantly associated with the odds of anxiety and stress.

LIMITATIONS: The cross-sectional design of the study prevented the inference of causality.

CONCLUSIONS: Higher adherence to EDIR was positively associated with depression, but there was no significant association between EDIH and depression. EDIR and EDIH were also not significantly related to anxiety or stress.

PMID:37634820 | DOI:10.1016/j.jad.2023.08.120

J Affect Disord. 2023 Aug 25:S0165-0327(23)01101-1. doi: 10.1016/j.jad.2023.08.121. Online ahead of print.

ABSTRACT

BACKGROUND: Osteomyelitis and major depressive disorder (MDD) are significant health concerns with potential interconnections. However, the underlying mechanisms linking these conditions remain unknown. This study aimed to investigate the potential mediating role of non-steroidal anti-inflammatory drug (NSAID) medication in the association between MDD and the risk of osteomyelitis.

METHODS: We utilized summary data from large-scale genome-wide association studies (GWAS) to perform Mendelian randomization (MR) mediation analysis. Instrumental variables were selected based on genome-wide significance, and instrumental strength was assessed using F-statistics. Univariable and multivariable MR analyses were conducted to estimate causal effects and proportions mediated by NSAID medication.

RESULTS: The univariable MR analysis revealed significant associations between MDD and osteomyelitis (odds ratio [OR] = 1.44, 95 % confidence interval [CI]: 1.18-1.874) and between MDD and NSAID medication (OR = 1.36, 95 % CI 1.24-1.49). In the multivariable MR analysis, the direct effect of MDD on osteomyelitis was OR 1.35 (95 % CI: 1.09, 1.67) after adjusting for NSAID medication. The proportion of mediation by NSAID medication was 23 % (95 % CI: 0.05 %, 38.6 %).

CONCLUSION: This MR study provides evidence for a genetically predicted causal association between MDD, NSAID medication, and osteomyelitis. The findings emphasize the need for a comprehensive approach in managing individuals with comorbid depression and osteomyelitis, considering the potential risks and benefits of NSAID medication. Future research should address limitations and explore additional mediators and confounding factors to enhance understanding of this complex relationship.

PMID:37634817 | DOI:10.1016/j.jad.2023.08.121

J Am Coll Radiol. 2023 Aug 25:S1546-1440(23)00628-2. doi: 10.1016/j.jacr.2023.02.037. Online ahead of print.

ABSTRACT

OBJECTIVE: With social media becoming a vibrant hub for the radiology community, highlighting expert leaders and trustful conduits of information in the virtual field is proving crucial. This study aimed to identify and describe the most prominent and influential figures and organizational accounts to follow in radiology.

METHODS: Influence scores for the topic “Radiology” on Twitter were computed using Right Relevance machine learning service. Top influencers were classified according to gender, geography, physician degree, areas of influence, sub-specialization, influence score, title, affiliated institution, dual degree, medical school origin, content type, and research activity. Statistical analysis was performed assessing variable correlations.

RESULTS: In the top quartile of influential figures, 87% were physicians, 60% males, and 93% located in the United States. Prevalent backgrounds included: neuroradiology (21%), abdominal imaging (12%), and artificial intelligence (11%). Of the top 100 figures, 81% were US graduates, 97% holding medical degrees, and 28% with dual degrees. 58% provided educational content. A majority held leadership positions (58%) and academic professorship titles (70%). Median h-index, publication, and citation numbers were 14, 49, and 881, respectively. No significant correlation was noted between influence score and academic rank or research output.

DISCUSSION: Virtual presence is becoming integral to our healthcare professions and academic spheres, unfolding great potential for enhancing the sense of belonging, advocacy, recruitment, and fostering new relationships. Having a core of influential leaders and organizations to follow can serve as a resource for the community members and aspiring students building a positive connected basis for radiology’s thriving future.

PMID:37634801 | DOI:10.1016/j.jacr.2023.02.037

Radiother Oncol. 2023 Aug 25:109870. doi: 10.1016/j.radonc.2023.109870. Online ahead of print.

ABSTRACT

PURPOSE: To investigate the performance of 4 atlas-based (multi-ABAS) and 2 deep learning (DL) solutions for head-and-neck (HN) elective nodes (CTVn) automatic segmentation (AS) on CT images.

MATERIAL AND METHODS: Bilateral CTVn levels of 69 HN cancer patients were delineated on contrast-enhanced planning CT. Ten and 49 patients were used for atlas library and for training a mono-centric DL model, respectively. The remaining 20 patients were used for testing. Additionally, three commercial multi-ABAS methods and one commercial multi-centric DL solution were investigated. Quantitative evaluation was assessed using volumetric Dice Similarity Coefficient (DSC) and 95-percentile Hausdorff distance (HD_95%). Blind evaluation was performed for 3 solutions by 4 physicians. One recorded the time needed for manual corrections. A dosimetric study was finally conducted using automated planning.

RESULTS: Overall DL solutions had better DSC and HD_95% results than multi-ABAS methods. No statistically significant difference was found between the 2 DL solutions. However, the contours provided by multi-centric DL solution were preferred by all physicians and were also faster to correct (1.1min vs 4.17min, on average). Manual corrections for multi-ABAS contours took on average 6.52min Overall, decreased contour accuracy was observed from CTVn2 to CTVn3 and to CTVn4. Using the AS contours in treatment planning resulted in underdosage of the elective target volume.

CONCLUSION: Among all methods, the multi-centric DL method showed the highest delineation accuracy and was better rated by experts. Manual corrections remain necessary to avoid elective target underdosage. Finally, AS contours help reducing the workload of manual delineation task.

PMID:37634765 | DOI:10.1016/j.radonc.2023.109870

Mol Cell Neurosci. 2023 Aug 25:103895. doi: 10.1016/j.mcn.2023.103895. Online ahead of print.

ABSTRACT

In the last two decades of Genome-wide association studies (GWAS), nicotine-dependence-related genetic loci (e.g., nicotinic acetylcholine receptor – nAChR subunit genes) are among the most replicable genetic findings. Although GWAS results have reported tens of thousands of SNPs within these loci, further analysis (e.g., fine-mapping) is required to identify the causal variants. However, it is computationally challenging for existing fine-mapping methods to reliably identify causal variants from thousands of candidate SNPs based on the posterior inclusion probability. To address this challenge, we propose a new method to select SNPs by jointly modeling the SNP-wise inference results and the underlying structured network patterns of the linkage disequilibrium (LD) matrix. We use adaptive dense subgraph extraction method to recognize the latent network patterns of the LD matrix and then apply group LASSO to select causal variant candidates. We applied this new method to the UK biobank data to identify the causal variant candidates for nicotine addiction. Eighty-one nicotine addiction-related SNPs (i.e.,-log(p) > 50) of nAChR were selected, which are highly correlated (average r²>0.8) although they are physically distant (e.g., >200 kilobase away) and from various genes. These findings revealed that distant SNPs from different genes can show higher LD r² than their neighboring SNPs, and jointly contribute to a complex trait like nicotine addiction.

PMID:37634742 | DOI:10.1016/j.mcn.2023.103895

Sci Total Environ. 2023 Aug 25:166504. doi: 10.1016/j.scitotenv.2023.166504. Online ahead of print.

ABSTRACT

Since the Geostationary Ocean Color Imager (GOCI) was successfully launched in 2010, the GOCI Yonsei aerosol retrieval (YAER) algorithm has been continuously updated to retrieve hourly aerosol optical properties. GOCI-II has 4 more channels including UV, finer spatial resolution (250 m), and daily full disk coverage as compared to GOCI, and was launched in February 2020, onboard the GEO-KOMPSAT-2B (GK-2B) satellite. In this study, we extended the YAER algorithm to GOCI-II data based on its improved performance in many aspects and present the first results of aerosol optical properties retrieved from GOCI-II data. Utilizing the overlapping period between the GOCI-II and GOCI in geostationary Earth orbit, we present GOCI-II aerosol retrievals for high aerosol-loading cases over East Asia and show that these have a consistent spatial distribution with those from GOCI. Furthermore, GOCI-II provides AOD at an even higher spatial resolution, revealing finer changes in aerosol concentrations. Validation results for one year data show that the GOCI-II AOD has a correlation coefficient of 0.83 and a ratio within the expected error (EE) of 59.4 % when compared with the aerosol robotic network (AERONET) data. We compared statistical metrics for the GOCI and GOCI-II AODs to assess the consistency between the two datasets. In addition, it was found that there is a strong correlation between the two datasets from the comparison of gridded GOCI and GOCI-II AOD products. It is expected that data from GOCI-II will continue long-term aerosol records with high accuracy that can be used to address air-quality issues over East Asia.

PMID:37634717 | DOI:10.1016/j.scitotenv.2023.166504