Category: Nevin Manimala

Rheumatol Ther. 2022 Nov 27. doi: 10.1007/s40744-022-00506-0. Online ahead of print.

ABSTRACT

A 2021 study described the development and validation of a blood-based precision medicine test called the molecular signature response classifier (MSRC) that uses 23 features to identify rheumatoid arthritis (RA) patients who are likely nonresponders to tumor necrosis factor-α inhibitor (TNFi) therapy. Both the gene expression features and clinical components (sex, body mass index, patient global assessment, and anti-cyclic citrullinated protein) included in the MSRC were statistically significant contributors to MSRC results. In response to continued inquiries on this topic, we write this letter to provide additional insights into the contribution of clinical components to the MSRC on the Network-004 validation cohort.

PMID:36441482 | DOI:10.1007/s40744-022-00506-0

Forensic Sci Med Pathol. 2022 Nov 28. doi: 10.1007/s12024-022-00560-8. Online ahead of print.

ABSTRACT

This paper presents the results of a study on the applicability of cerebrospinal fluid (CSF) collected from the spinal canal in the post-mortem determination of ethyl alcohol. The present study reviewed data of autopsy cases (n = 45), in which ethyl alcohol was detected in CSF using gas chromatography with a flame ionization detector (HS-GC-FID), to investigate ethyl alcohol concentrations in CSF, compared with blood. As a result of statistical analysis of the obtained data, a high positive correlation was found between blood ethanol concentration and cerebrospinal fluid collected from the spinal canal ethanol concentration. The Pearson correlation coefficient was statistically highly significant (p < 0.001) (r = 0.9503). The data obtained allowed us to conclude that cerebrospinal fluid collected from the spinal canal can be collected during an autopsy as an alternative biological specimen to assess the ethanol content. Cerebrospinal fluid collected from the spinal canal can corroborate and lend credibility to the results obtained for blood and, in special cases, when blood is drawn from putrefied bodies and may even be a superior specimen to blood for assessing ethyl alcohol intoxication status.

PMID:36441476 | DOI:10.1007/s12024-022-00560-8

J Epidemiol Glob Health. 2022 Nov 28. doi: 10.1007/s44197-022-00077-x. Online ahead of print.

ABSTRACT

BACKGROUND: In Benin, some riders of two-wheeled vehicles still do not wear helmets, the main protection against head injuries in road accidents. The objective of this study is to describe the characteristics of two-wheeled users, and to determine the factors influencing helmet use among this group.

METHODS: This is a prospective cross-sectional study of 977 two-wheeled road accident victims from a cohort. Proportions or means were calculated for the different variables. Statistical comparisons were made to test the association with helmet use. Logistic regression modelling was performed to identify factors associated with helmet use.

RESULTS: Among all subjects, 81.1% [CI_95% (78.5; 83.4)] wore a helmet. Factors explaining helmet use were female gender (OR = 2.8 [1.3-6.1]), purpose of trip (OR = 1.7 [1.1-2.6]), possession of health insurance (OR = 3.7 [1.3-10, 5]), having been driving for 15-20 years (OR = 2.6 [1.4-4.7]) or more than 20 years (OR = 3.4 [2.0-5.8]), good road conditions (OR = 3.1 [2.0-4.8]), and good visibility (OR = 1.9 [1.3-3.1]).

CONCLUSION: The factors influencing helmet use are gender, reason for travel, length of time as a driver, possession of health insurance, conditions, and visibility of the road on which the subject are driving. These factors are related to experience and appropriation of the notion of risk, but also related to the environment. To increase helmet use among two-wheelers, helmet awareness should take into account the individual factors found in this study. Enforcement actions should be strengthened, and the quality of the roads improved.

PMID:36441473 | DOI:10.1007/s44197-022-00077-x

Eur J Drug Metab Pharmacokinet. 2022 Nov 28. doi: 10.1007/s13318-022-00806-4. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVES: The Extended Clearance Classification System (ECCS) was established to facilitate the timely anticipation of clearance rate determination according to the physicochemical characteristics of a given compound and in vitro passive membrane permeability. Unfortunately, distinguishing between renal and hepatic uptake clearance mechanisms using ECCS class 3B is not possible. We determined the effects of plasma protein binding (PPB) on major hepatic organic anion transporting polypeptide (OATP) and renal organic anion transporter (OAT) substrates. A modified ECCS could predict when renal or hepatic uptake mechanisms were the main clearance rate determinants (accounting for ≥ 70% of total clearance).

METHODS: A dataset of 66 human OATP and 41 OAT substrates was analyzed to determine the effect of PPB. A total of 63 acidic and zwitterionic, and high-molecular-weight (MW > 400 Da) compounds, including 50 drugs in ECCS classes 1B and 3B, were reanalyzed considering their PPB.

RESULTS: Statistical analyses revealed that hepatic uptake transporter (OATP1B1 and OATP1B3) substrates possess a high PPB rate of ≥ 90%, whereas OAT1 and/or OAT3 substrates possess low PPB rates of < 90%. By analyzing the 63 drugs on the basis of their PPB, the active hepatic uptakes of acids and zwitterions were determined to be the main clearance mechanisms, with PPB ≥ 90%, whereas renally eliminated drugs exhibited limited PPB (< 90%).

CONCLUSIONS: Therefore, PPB is an effective parameter for defining clearance rate determination for acidic and zwitterionic drugs with high MWs. Using PPB as an additional parameter in ECCS, clearance mechanisms for class 1B and 3B compounds can be predicted, and OATP and OAT substrates may be readily distinguished.

PMID:36441468 | DOI:10.1007/s13318-022-00806-4

Methods Mol Biol. 2023;2595:225-237. doi: 10.1007/978-1-0716-2823-2_16.

ABSTRACT

The bioinformatics analysis of miRNA is a complicated task with multiple operations and steps involved from processing of raw sequence data to finally identifying accurate microRNAs associated with the phenotypes of interest. A complete analysis process demands a high level of technical expertise in programming, statistics, and data management. The goal of this chapter is to reduce the burden of technical expertise and provide readers the opportunity to understand crucial steps involved in the analysis of miRNA sequencing data.In this chapter, we describe methods and tools employed in processing of miRNA reads, quality control, alignment, quantification, and differential expression analysis.

PMID:36441466 | DOI:10.1007/978-1-0716-2823-2_16

Mol Divers. 2022 Nov 28. doi: 10.1007/s11030-022-10574-7. Online ahead of print.

ABSTRACT

Cytochrome P450-1B1 is a majorly overexpressed drug-metabolizing enzyme in tumors and is responsible for inactivation and subsequent resistance to a variety of anti-cancer drugs, i.e., docetaxel, tamoxifen, and cisplatin. In the present study, a 3D quantitative structure-activity relationship (3D-QSAR) model has been constructed for the identification, design, and optimization of novel CYP1B1 inhibitors. The model has been built using a set of 148 selective CYP1B1 inhibitors. The developed model was evaluated based on certain statistical parameters including q² and r² which showed the acceptable predictive and descriptive capability of the generated model. The developed 3D-QSAR model assisted in understanding the key molecular fields which were firmly related to the selective CYP1B1 inhibition. A theoretic approach for the generation of new lead compounds with optimized CYP1B1 receptor affinity has been performed utilizing bioisosteric replacement analysis. These generated molecules were subjected to a developed 3D-QSAR model to predict the inhibitory activity potentials. Furthermore, these compounds were scrutinized through the activity atlas model, molecular docking, electrostatic complementarity, molecular dynamics, and waterswap analysis. The final hits might act as selective CYP1B1 inhibitors which could address the issue of resistance. This 3D-QSAR includes several chemically diverse selective CYP1B1 receptor ligands and well accounts for the individual ligand’s inhibition affinities. These features of the developed 3D-QSAR model will ensure future prospective applications of the model to speed up the identification of new potent and selective CYP1B1 receptor ligands.

PMID:36441444 | DOI:10.1007/s11030-022-10574-7

Oral Radiol. 2022 Nov 28. doi: 10.1007/s11282-022-00665-4. Online ahead of print.

ABSTRACT

OBJECTIVES: To investigate the possible risk factors for mastoid cellulitis after treatment in patients with oral cancer.

METHODS: Patients with oral cancer who underwent preoperative and postoperative contrast-enhanced computed tomography (CECT) between January 2017 and March 2020 were retrospectively evaluated. Using an image reporting system, cases with reports containing the keyword “mastoid cellulitis” were registered in the mastoid cellulitis group. Fifty patients with oral cancer who did not develop mastoid cellulitis were randomly selected as the control group. Information concerning age, sex, location, and histopathological type of the primary tumor, presence or absence of cervical lymph node metastasis, and treatment methods were obtained from the hospital’s electronic medical records to investigate the association between these factors and the occurrence of mastoid cellulitis.

RESULTS: Statistically significant differences were observed in the following factors: age (p = 0.004), primary tumor site (p < 0.001), histopathological type (p = 0.032), radiotherapy (p < 0.001), and chemotherapy (p < 0.001). Logistic regression analysis revealed that maxillary tumors (p < 0.001), histopathological type (p = 0.047), and radiotherapy (p = 0.0301) were significantly associated with the occurrence of mastoid cellulitis.

CONCLUSIONS: In oral cancer, the risk of postoperative mastoid cellulitis was higher in patients with a maxillary tumor, histopathology other than squamous cell carcinoma, and history of radiotherapy.

PMID:36441420 | DOI:10.1007/s11282-022-00665-4

Oral Radiol. 2022 Nov 28. doi: 10.1007/s11282-022-00666-3. Online ahead of print.

ABSTRACT

OBJECTIVES: To evaluate the relationship between proximity of the root apices of healthy maxillary posterior teeth to the maxillary sinus floor (MSF) and mucosal thickening (MT) of the MSF using cone beam computed tomography (CBCT).

METHODS: Eighty-four CBCT images obtained from the patients, aged between 20 and 70 years with healthy and fully dentate maxillary posterior sextants, were included. The anatomical relationship between root apices of maxillary posterior teeth and MSF, was evaluated: (Type 1: no contact, Type 2: at least one root apex in contact, Type 3: at least one root apex protruding into MSF). Besides, MT of the MSF was measured from the thickest region. The patients were categorized into two groups based on the absence (≤ 2 mm) or the presence (2 < mm) of MT. Statistical significance was accepted at p < 0.05.

RESULTS: Intraexaminer consistency demonstrated an excellent agreement (p < 0.05). The prevalence of Type 1, 2, and 3 proximity were found as 26 (15.5%), 61 (36.3%), and 81 (48.2%); respectively. Overall, 62 (36.9%) maxillary sinuses demonstrated MT (2 < mm, mean: 8.6 ± 7.5 mm). The prevalence and mean values of MT (2 < mm) were not found to be statistically significantly different in terms of sex and proximity types (p > 0.05). Logistic regression analysis results were not found to be statistically significant (p > 0.05).

CONCLUSION: The proximity of healthy maxillary posterior teeth to the MSF was not found to be a contributing factor for the MT of the MSF. Further studies with larger samples, taking the other factors causing MT into consideration, are needed.

PMID:36441419 | DOI:10.1007/s11282-022-00666-3

J Robot Surg. 2022 Nov 28. doi: 10.1007/s11701-022-01495-6. Online ahead of print.

ABSTRACT

As the growing popularity of robotic-assisted laparoscopic procedures for the treatment of renal cancer increases, there exists a variation in surgical technique among institutions and surgeons alike. One variation that exists in robotics is the anatomical placement of the camera port (medial versus lateral camera port placement). The purpose of this study is to evaluate surgical complications and outcomes in comparison to site of camera port placement during nephron-sparing surgery in an academic setting. Over a three-year period, outcomes for all robotic surgeries for renal cancer were examined. A total of 229 cases were discovered. Patient demographics and comorbidities were analyzed along with perioperative surgical data including location of camera port, surgery length, warm ischemia time, blood loss, pathological tumor margins, tumor size, length of stay and laboratory data. 134 patients had surgery performed with lateral camera port placement versus 95 patients with medial camera port placement. Operative time was significantly lower with an average operative time of 165.8 min for the lateral group versus 209.1 min in the medial group (p < 0. 0001). Warm ischemia time was also less in the lateral group with an average of 11 min versus 15.5 min for the medial group (p < 0. 0001). Blood loss was less in the lateral camera port group with an average of 158.2 mL (± 196.5 mL) versus 248.6 mL in the medial group (± 252.6) (p = 0.0040). Drain use, positive surgical margin rate, transfusion rate, conversion to radical nephrectomy, change in pre-operative versus postoperative creatinine and glomerular filtration rate and length of hospital stay did not statistically differ. Lateral camera port placement is associated with decreased operative time and warm ischemia time in this series. There may be certain laparoscopic advantages through a better visualization of surgical anatomy, thus allowing for faster extirpation of renal lesions and decrease in surgical time. These advantages may result in better long-term renal function and decreased clinical sequela from chronic kidney disease.

PMID:36441417 | DOI:10.1007/s11701-022-01495-6

Metabolomics. 2022 Nov 28;18(12):99. doi: 10.1007/s11306-022-01959-8.

ABSTRACT

INTRODUCTION: Previous studies have explored prediction value of serum metabolites in neoadjuvant chemoradiation therapy (NCRT) response for rectal cancer. To date, limited literature is available for serum metabolome changes dynamically through NCRT.

OBJECTIVES: This study aimed to explore temporal change pattern of serum metabolites during NCRT, and potential metabolic biomarkers to predict the pathological response to NCRT in locally advanced rectal cancer (LARC) patients.

METHODS: Based on dynamic UHPLC-QTOF-MS untargeted metabolomics design, this study included 106 LARC patients treated with NCRT. Biological samples of the enrolled patients were collected in five consecutive time-points. Untargeted metabolomics was used to profile serum metabolic signatures from LARC patients. Then, we used fuzzy C-means clustering (FCM) to explore temporal change patterns in metabolites cluster and identify monotonously changing metabolites during NCRT. Repeated measure analysis of variance (RM-ANOVA) and multilevel partial least-squares discriminant analysis (ML-PLS-DA) were performed to select metabolic biomarkers. Finally, a panel of dynamic differential metabolites was used to build logistic regression prediction models.

RESULTS: Metabolite profiles showed a clearly tendency of separation between different follow-up panels. We identified two clusters of 155 serum metabolites with monotonously changing patterns during NCRT (74 decreased metabolites and 81 increased metabolites). Using RM-ANOVA and ML-PLS-DA, 8 metabolites (L-Norleucine, Betaine, Hypoxanthine, Acetylcholine, 1-Hexadecanoyl-sn-glycero-3-phosphocholine, Glycerophosphocholine, Alpha-ketoisovaleric acid, N-Acetyl-L-alanine) were further identified as dynamic differential biomarkers for predicting NCRT sensitivity. The area under the ROC curve (AUC) of prediction model combined with the baseline measurement was 0.54 (95%CI = 0.43 ~ 0.65). By incorporating the variability indexes of 8 dynamic differential metabolites, the prediction model showed better discrimination performance than baseline measurement, with AUC = 0.67 (95%CI 0.57 ~ 0.77), 0.64 (0.53 ~ 0.75), 0.60 (0.50 ~ 0.71), and 0.56 (0.45 ~ 0.67) for the variability index of difference, linear slope, ratio, and standard deviation, respectively.

CONCLUSION: This study identified eight metabolites as dynamic differential biomarkers to discriminate NCRT-sensitive and resistant patients. The changes of metabolite level during NCRT show better performance in predicting NCRT sensitivity. These findings highlight the clinical significance of metabolites variabilities in metabolomics analysis.

PMID:36441416 | DOI:10.1007/s11306-022-01959-8