Nevin Manimala

Am J Mens Health. 2022 Jul-Aug;16(4):15579883221108895. doi: 10.1177/15579883221108895.

ABSTRACT

There is a continuous worldwide increase in incidences of metabolic syndrome (MetS) reaching about a quarter of the world’s population. Thus, studies that allow for a robust diagnosis of MetS are of paramount importance from an economic and medical point of view. This study was carried out in a group of men diagnosed with MetS using consensus definition criteria that included the definitions of the International Diabetes Foundation and Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute. The control group consisted of men for whom the parameters that define the MetS were in the norm. This study analyzed statistical differences between MetS and healthy men and the correlations between the set of 14 potential markers of MetS, that is, between body mass index, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein, triglycerides, cortisol, adiponectin, monocyte chemotactic protein-1 (MCP-1), C-reactive protein (CRP), adipsin, leptin, resistin, and plasminogen activator inhibitor-1 (PAI)-1. This report revealed a significant difference between MetS and healthy men in most of the parameters studied. Furthermore, a strong positive correlation between cortisol levels and body mass index was demonstrated. Furthermore, MCP-1 levels in men with MetS were significantly higher than their levels in healthy men. Finally, a strong positive correlation was also observed between adiponectin and adipsin in Mets men. Thus, this study reveals the potential usefulness of adiponectin, MCP-1, adipsin, leptin, resistin, and PAI-1 as markers of MetS in adult men.

PMID:35962582 | DOI:10.1177/15579883221108895

Brain Behav. 2022 Aug 12:e2695. doi: 10.1002/brb3.2695. Online ahead of print.

ABSTRACT

BACKGROUND: Depression and overweight/obesity often cooccur but the underlying neural mechanisms for this bidirectional link are not well understood.

METHODS: In this functional magnetic resonance imaging study, we scanned 54 individuals diagnosed with depressive disorders (DD) and 48 healthy controls (HC) to examine how diagnostic status moderates the relationship between body mass index (BMI) and brain activation during anticipation and pleasantness rating of food versus nonfood stimuli.

RESULTS: We found a significant BMI-by-diagnosis interaction effect on activation in the right inferior frontal gyrus (RIFG) and anterior cingulate cortex (ACC) during food versus nonfood anticipation (p < .0125). Brain activation in these regions was greater in HC with higher BMI than in HC with lower BMI. Individuals with DD showed an opposite pattern of activation. Structural equation modeling revealed that the relationship between BMI, activation in the RIFG and ACC, and participants’ desire to eat food items shown in the experiment depended on the diagnostic status.

CONCLUSIONS: Considering that food anticipation is an important component of appetitive behavior and that the RIFG and ACC are involved in emotion regulation, response inhibition and conflict monitoring necessary to control this behavior, we propose that future clinical trials targeting weight loss in DD should investigate whether adequate mental preparation positively affects subsequent food consumption behaviors in these individuals.

PMID:35962573 | DOI:10.1002/brb3.2695

J Appl Clin Med Phys. 2022 Aug 12:e13749. doi: 10.1002/acm2.13749. Online ahead of print.

ABSTRACT

The purpose of this work is to objectively assess variability of intercampus plan quality for head-and-neck (HN) cancer and to test utility of a priori feasibility dose-volume histograms (FDVHs) as planning dose goals. In this study, 109 plans treated from 2017 to 2019 were selected, with 52 from the main campus and 57 from various regional centers. For each patient, the planning computed tomography images and contours were imported into a commercial program to generate FDVHs with a feasibility value (f-value) ranging from 0.0 to 0.5. For 10 selected organs-at-risk (OARs), we used the Dice similarity coefficient (DSC) to quantify the overlaps between FDVH and clinically achieved DVH of each OAR and determined the f-value associated with the maximum DSC (labeled as f-max). Subsequently, 10 HN plans from the regional centers were replanned with planning dose goals guided by FDVHs. The clinical and feasibility-guided auto-planning (FgAP) plans were evaluated using our institutional criteria. Among plans from the main campus and regional centers, the median f-max values were statistically significantly different (p < 0.05) for all OARs except for the left parotid (p = 0.622), oral cavity (p = 0.057), and mandible (p = 0.237). For the 10 FgAP plans, the median values of f-max were 0.21, compared to 0.37 from the clinical plans. With comparable dose coverage to the tumor volumes, the significant differences (p < 0.05) in the median f-max and corresponding dose reduction (shown in parenthesis) for the spinal cord, larynx, supraglottis, trachea, and esophagus were 0.27 (8.5 Gy), 0.3 (7.6 Gy), 0.19 (5.9 Gy), 0.19 (8.9 Gy), and 0.12 (4.0 Gy), respectively. In conclusion, the FDVH prediction is an objective quality assurance tool to evaluate the intercampus plan variability. This tool can also provide guideline in planning dose goals to further improve plan quality.

PMID:35962566 | DOI:10.1002/acm2.13749

Database (Oxford). 2022 Aug 13;2022:baac066. doi: 10.1093/database/baac066.

ABSTRACT

Large volumes of publications are being produced in biomedical sciences nowadays with ever-increasing speed. To deal with the large amount of unstructured text data, effective natural language processing (NLP) methods need to be developed for various tasks such as document classification and information extraction. BioCreative Challenge was established to evaluate the effectiveness of information extraction methods in biomedical domain and facilitate their development as a community-wide effort. In this paper, we summarize our work and what we have learned from the latest round, BioCreative Challenge VII, where we participated in all five tracks. Overall, we found three key components for achieving high performance across a variety of NLP tasks: (1) pre-trained NLP models; (2) data augmentation strategies and (3) ensemble modelling. These three strategies need to be tailored towards the specific tasks at hands to achieve high-performing baseline models, which are usually good enough for practical applications. When further combined with task-specific methods, additional improvements (usually rather small) can be achieved, which might be critical for winning competitions. Database URL: https://doi.org/10.1093/database/baac066.

PMID:35962559 | DOI:10.1093/database/baac066

J Obstet Gynaecol. 2022 Aug 12:1-8. doi: 10.1080/01443615.2022.2109139. Online ahead of print.

ABSTRACT

The aim of this study was primarily to evaluate the levels of progesterone, oestradiol and relaxin during different delivery modes and secondarily to assess specific traits and changes in maternal pelvic dimensions during pregnancy and childbirth, in correlation with foetal size and maternal hormonal profile. Nulliparous women (n = 448) were evaluated at three different stages, during first trimester, at the time of admission for childbirth and finally just before childbirth. Each examination included clinical internal pelvimetry, blood sample collection for defining the hormones levels in peripheral maternal circulation and ultrasonographic measurements of specific variables of the pubic symphysis and the foetus. We included 304 nulliparous women divided in three groups. According to our results, there was statistically significant difference at the mean progesterone, oestradiol and relaxin range during different modes of childbirth (p-value < .01). We also found significant correlation between the newborn’s weight and the changes in pubic symphysis dimensions. However, no significant association was noted between maternal hormones studied and the changes in pelvic dimensions.IMPACT STATEMENTWhat is already known on this subject? Mode of childbirth can be affected by various aspects, like maternal pelvic anatomy, foetal size and hormonal status at the time of labour. Hormonal fluctuations along with mechanical forces caused by the foetus are believed to lead to morphological alterations to promote natural vaginal childbirth.What do the results of this study add? Our results clearly showed that successful vaginal delivery is characterised by the prevalence of a hyperoestrogenic environment with higher values of intrapartum oestradiol range and significant increase in maternal serum relaxin levels. We also proved that progesterone levels do not decrease during vaginal childbirth, and we concluded that foetal size seems to be the most crucial factor causing alterations in maternal pelvis during parturition.What are the implications of these findings for clinical practice and further research? Our findings could form part of a set of key factors included in future algorithms or computerised biomechanical models for predicting potential childbirth mode. Larger multicenter studies should confirm our results and evaluate their clinical significance in the decision making to ensure safe childbirth and optimal maternal and perinatal outcomes.

PMID:35962554 | DOI:10.1080/01443615.2022.2109139

Musculoskeletal Care. 2022 Aug 12. doi: 10.1002/msc.1680. Online ahead of print.

ABSTRACT

OBJECTIVES: The aim of this evaluation was to review service outcomes for a spinal advanced practitioner physiotherapy (APP) triage service during COVID-19. The evaluation compares outcomes gathered against pre-pandemic data and evaluates the impact of the pandemic on service delivery.

DESIGN: Service-level data were extracted between 2019 and 2021 including: total referrals, new and follow-up appointments, telehealth consultation rates, discharges at first appointment, magnetic resonance imaging and injection request rates. Multidisciplinary-team (MDT) meeting notes with Spinal Surgeons were reviewed and surgical conversion calculated. Patient satisfaction data were collated using: Friends and Family test, specific questionnaires, individual and formal complaints and compliments, and telephone surveys. Analysis was performed by the lead author and results were compared between years using analysis of variance, as well as with previously reported data.

SETTING: ‘Nottingham University Hospitals’ National Health Services Trust is a secondary care spinal unit, using APPs to triage, assess and manage spinal conditions.

RESULTS: In 2020, 407 (22%; p = 0.02) less patients were referred to the service, however, there was a significant increase in the number of telehealth attendances (mean = 50% in 2020 from 2019, p = 0.005). Only 13% (n = 1342) patients were discussed at MDT, of which 8% (n = 808) were discussed for surgical consideration, and 36% (n = 268) were directly listed. High levels of patient satisfaction were reported by 89% (n = 1028 of 1160) patients.

CONCLUSION: This service evaluation demonstrates a statistically significant change in numbers of patients referred and telehealth attendances in the year of the pandemic (2020). Surgical conversion declined during the pandemic, and did not recover post-pandemic.

PMID:35962526 | DOI:10.1002/msc.1680

Int J Rheum Dis. 2022 Aug 12. doi: 10.1111/1756-185X.14417. Online ahead of print.

ABSTRACT

OBJECTIVE: To analyze the prevalence trend of Sjögren’s syndrome in the Department of Immunology and Rheumatology of Nanjing Zhongda Hospital from January 2015 to December 2019, and compare the application of SARIMA model and Holt-Winters model in predicting the number of cases of Sjögren’s syndrome.

METHODS: All of the data from the Department of Immunology and Rheumatology of Nanjing Zhongda Hospital were collected. The number of monthly cases from January 2015 to December 2019 was regarded as the training set, and it was used to establish the SARIMA model and Holt-Winters model. The number of monthly incidences from January 2020 to December 2020 was regarded as the test set, and it was used to check the model performance.

RESULTS: The optimal model of SARIMA is ARIMA (0,1,1) (2,1,1)₁₂ model, and the optimal model of Holt-Winters model is Holt-Winters addition model. It was found that the Holt-Winters addition model produced the smallest error.

CONCLUSION: Holt-Winters addition model produces better prediction accuracy of the model.

PMID:35962522 | DOI:10.1111/1756-185X.14417

Indian J Dermatol Venereol Leprol. 2022 Aug 1:1-6. doi: 10.25259/IJDVL_810_2021. Online ahead of print.

ABSTRACT

Background Leprosy (or Hansen’s disease) continues to present considerable challenges regarding containment and early diagnosis. Leprosy is considered to be primarily a neural disease that first affects the sensory function of small fibres. Although the condition is well described in terms of clinical manifestations and histology, few studies have been undertaken to detect damage done to small-fibre sensory nerves. In vivo confocal microscopy is a useful tool for conducting a detailed evaluation of these structures, although its use in individuals affected by leprosy has still not been explored. Objective To evaluate in vivo confocal microscopy findings in Hansen’s disease patients and their association with clinical variables relating to this disease. Method A cross-sectional case-series type study was carried out between October 2019 and May 2021, in Recife, Pernambuco, Brazil. Socio-demographic and clinical data were gathered from 21 patients with leprosy. The douleur neuropathique 4 neuropathic pain questionnaire was used to evaluate pain. In vivo confocal microscopy of the cornea was employed to evaluate the small-calibre fibres. Findings were compared with those for a control group of 23 healthy individuals. Results In relation to clinical parameters, 90.5% of the patients were classified as “multibacillary” according to the World Health Organization criteria, and 70% as dimorphic or borderline, in accordance with the Madrid classification. Around 52.4% had received a diagnosis after one year or less of living with the disease, while 95.2% presented alterations in small-fibre sensory function and 35% presented such alterations in the large fibre. Neuropathic pain was present in 81% of the patients. In vivo confocal microscopy found no statistically significant difference in mean age and distribution according to sex between the Hansen disease patients and the control group of healthy individuals. The median-of-means for dendritic cells and volume of sub-basal nerve fibres in the control group were used to test for normality. Both eyes of all leprosy patients examined contained higher number of dendritic cells than the median value and a volume of sub-basal nerve fibres lower than the mean. These differences were statistically significant (P < 0.001 and P < 0.001, respectively). Multibacillary individuals had a median number of dendritic cells two times that of paucibacillary individuals (P = 0.035). Limitations No association was found between the variables examined using in vivo confocal microscopy and clinical variables relating to small-fibre damage, the neuropathic pain questionnaire or alterations detected by the neurological examination. We believe, however, that Cochet-Bonnet esthesiometry of the cornea may have revealed such an association. Conclusion In vivo confocal microscopy is a useful diagnostic tool for detecting small fibre loss in individuals affected by leprosy and may constitute a useful addition to the range of tools available to help curb the effects of neuropathy in these patients.

PMID:35962495 | DOI:10.25259/IJDVL_810_2021

Cancer Imaging. 2022 Aug 12;22(1):39. doi: 10.1186/s40644-022-00476-0.

ABSTRACT

BACKGROUND: Current radiological assessments of ¹⁸fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging data in diffuse large B-cell lymphoma (DLBCL) can be time consuming, do not yield real-time information regarding disease burden and organ involvement, and hinder the use of FDG-PET to potentially limit the reliance on invasive procedures (e.g. bone marrow biopsy) for risk assessment.

METHODS: Our aim is to enable real-time assessment of imaging-based risk factors at a large scale and we propose a fully automatic artificial intelligence (AI)-based tool to rapidly extract FDG-PET imaging metrics in DLBCL. On availability of a scan, in combination with clinical data, our approach generates clinically informative risk scores with minimal resource requirements. Overall, 1268 patients with previously untreated DLBCL from the phase III GOYA trial (NCT01287741) were included in the analysis (training: n = 846; hold-out: n = 422).

RESULTS: Our AI-based model comprising imaging and clinical variables yielded a tangible prognostic improvement compared to clinical models without imaging metrics. We observed a risk increase for progression-free survival (PFS) with hazard ratios [HR] of 1.87 (95% CI: 1.31-2.67) vs 1.38 (95% CI: 0.98-1.96) (C-index: 0.59 vs 0.55), and a risk increase for overall survival (OS) (HR: 2.16 (95% CI: 1.37-3.40) vs 1.40 (95% CI: 0.90-2.17); C-index: 0.59 vs 0.55). The combined model defined a high-risk population with 35% and 42% increased odds of a 4-year PFS and OS event, respectively, versus the International Prognostic Index components alone. The method also identified a subpopulation with a 2-year Central Nervous System (CNS)-relapse probability of 17.1%.

CONCLUSION: Our tool enables an enhanced risk stratification compared with IPI, and the results indicate that imaging can be used to improve the prediction of central nervous system relapse in DLBCL. These findings support integration of clinically informative AI-generated imaging metrics into clinical workflows to improve identification of high-risk DLBCL patients.

TRIAL REGISTRATION: Registered clinicaltrials.gov number: NCT01287741.

PMID:35962459 | DOI:10.1186/s40644-022-00476-0

World J Surg Oncol. 2022 Aug 13;20(1):257. doi: 10.1186/s12957-022-02702-2.

ABSTRACT

BACKGROUND: The morbidity and mortality of colorectal cancer (CRC) remain high, posing a serious threat to human life and health. The early diagnosis and prognostic evaluation of CRC are two major challenges in clinical practice. MTUS1 is considered a tumour suppressor and can play an important role in inhibiting cell proliferation, migration, and tumour growth. Moreover, the expression of MTUS1 is decreased in different human cancers, including CRC. However, the biological functions and molecular mechanisms of MTUS1 in CRC remain unclear.

METHODS: In the present study, data from The Cancer Genome Atlas (TCGA) database were analysed using R statistical software (version 3.6.3.) to evaluate the expression of MTUS1 in tumour tissues and adjacent normal tissues using public databases such as the TIMER and Oncomine databases. Then, 38 clinical samples were collected, and qPCR was performed to verify MTUS1 expression. We also investigated the relationship between MTUS1 expression and clinicopathological characteristics and elucidated the diagnostic and prognostic value of MTUS1 in CRC. In addition, the correlation between MTUS1 expression and immune infiltration levels was identified using the TIMER and GEPIA databases. Furthermore, we constructed and analysed a PPI network and coexpression modules of MTUS1 to explore its molecular functions and mechanisms.

RESULTS: CRC tissues exhibited lower levels of MTUS1 than normal tissues. The logistic regression analysis indicated that the expression of MTUS1 was associated with N stage, TNM stage, and neoplasm type. Moreover, CRC patients with low MTUS1 expression had poor overall survival (OS). Multivariate analysis revealed that the downregulation of MTUS1 was an independent prognostic factor and was correlated with poor OS in CRC patients. MTUS1 expression had good diagnostic value based on ROC analysis. Furthermore, we identified a group of potential MTUS1-interacting proteins and coexpressed genes. GO and KEGG enrichment analyses showed that MTUS1 was involved in multiple cancer-related signalling pathways. Moreover, the expression of MTUS1 was significantly related to the infiltration levels of multiple cells. Finally, MTUS1 expression was strongly correlated with various immune marker sets.

CONCLUSIONS: Our results indicated that MTUS1 is a promising biomarker for predicting the diagnosis and prognosis of CRC patients. MTUS1 can also become a new molecular target for tumour immunotherapy.

PMID:35962436 | DOI:10.1186/s12957-022-02702-2