Category: Nevin Manimala

Methods Mol Biol. 2023;2553:325-393. doi: 10.1007/978-1-0716-2617-7_16.

ABSTRACT

Breast cancer is one of the most common cancers in women worldwide, which causes an enormous number of deaths annually. However, early diagnosis of breast cancer can improve survival outcomes enabling simpler and more cost-effective treatments. The recent increase in data availability provides unprecedented opportunities to apply data-driven and machine learning methods to identify early-detection prognostic factors capable of predicting the expected survival and potential sensitivity to treatment of patients, with the final aim of enhancing clinical outcomes. This tutorial presents a protocol for applying machine learning models in survival analysis for both clinical and transcriptomic data. We show that integrating clinical and mRNA expression data is essential to explain the multiple biological processes driving cancer progression. Our results reveal that machine-learning-based models such as random survival forests, gradient boosted survival model, and survival support vector machine can outperform the traditional statistical methods, i.e., Cox proportional hazard model. The highest C-index among the machine learning models was recorded when using survival support vector machine, with a value 0.688, whereas the C-index recorded using the Cox model was 0.677. Shapley Additive Explanation (SHAP) values were also applied to identify the feature importance of the models and their impact on the prediction outcomes.

PMID:36227551 | DOI:10.1007/978-1-0716-2617-7_16

Methods Mol Biol. 2023;2553:221-263. doi: 10.1007/978-1-0716-2617-7_12.

ABSTRACT

Research in synthetic biology and metabolic engineering require a deep understanding on the function and regulation of complex pathway genes. This can be achieved through gene expression profiling which quantifies the transcriptome-wide expression under any condition, such as a cell development stage, mutant, disease, or treatment with a drug. The expression profiling is usually done using high-throughput techniques such as RNA sequencing (RNA-Seq) or microarray. Although both methods are based on different technical approaches, they provide quantitative measures of the expression levels of thousands of genes. The expression levels of the genes are compared under different conditions to identify the differentially expressed genes (DEGs), the genes with different expression levels under different conditions. DEGs, usually involving thousands in number, are then investigated using bioinformatics and data analytic tools to infer and compare their functional roles between conditions. Dealing with such large datasets, therefore, requires intensive data processing and analyses to ensure its quality and produce results that are statistically sound. Thus, there is a need for deep statistical and bioinformatics knowledge to deal with high-throughput gene expression data. This represents a barrier for wet biologists with limited computational, programming, and data analytic skills that prevent them from getting the full potential of the data. In this chapter, we present a step-by-step protocol to perform transcriptome analysis using GeneCloudOmics, a cloud-based web server that provides an end-to-end platform for high-throughput gene expression analysis.

PMID:36227547 | DOI:10.1007/978-1-0716-2617-7_12

Methods Mol Biol. 2023;2553:41-56. doi: 10.1007/978-1-0716-2617-7_3.

ABSTRACT

Machine learning is revolutionizing molecular biology and bioengineering by providing powerful insights and predictions. Massively parallel reporter assays (MPRAs) have emerged as a particularly valuable class of high-throughput technique to support such algorithms. MPRAs enable the simultaneous characterization of thousands or even millions of genetic constructs and provide the large amounts of data needed to train models. However, while the scale of this approach is impressive, the design of effective MPRA experiments is challenging due to the many factors that can be varied and the difficulty in predicting how these will impact the quality and quantity of data obtained. Here, we present a computational tool called FORECAST, which can simulate MPRA experiments based on fluorescence-activated cell sorting and subsequent sequencing (commonly referred to as Flow-seq or Sort-seq experiments), as well as carry out rigorous statistical estimation of construct performance from this type of experimental data. FORECAST can be used to develop workflows to aid the design of MPRA experiments and reanalyze existing MPRA data sets.

PMID:36227538 | DOI:10.1007/978-1-0716-2617-7_3

Lasers Med Sci. 2022 Oct 13. doi: 10.1007/s10103-022-03652-7. Online ahead of print.

ABSTRACT

The effect of near infrared (NIR) laser irradiation on proliferation and osteogenic differentiation of buccal fat pad-derived stem cells and the role of transient receptor potential (TRP) channels was investigated in the current research. After stem cell isolation, a 940 nm laser with 0.1 W, 3 J/cm² was used in pulsed and continuous mode for irradiation in 3 sessions once every 48 h. The cells were cultured in the following groups: non-osteogenic differentiation medium/primary medium (PM) and osteogenic medium (OM) groups with laser-irradiated (L +), without irradiation (L -), laser treated + Capsazepine inhibitor (L + Cap), and laser treated + Skf96365 inhibitor (L + Skf). Alizarin Red staining and RT-PCR were used to assess osteogenic differentiation and evaluate RUNX2, Osterix, and ALP gene expression levels. The pulsed setting showed the best viability results (P < 0.05) and was used for osteogenic differentiation evaluations. The results of Alizarin red staining were not statistically different between the four groups. Osterix and ALP expression increased in the (L +) group. This upregulation abrogated in the presence of Capsazepine, TRPV1 inhibitor (L + Cap); however, no significant effect was observed with Skf96365 (L + Skf).

PMID:36227520 | DOI:10.1007/s10103-022-03652-7

Hepatol Int. 2022 Oct 13. doi: 10.1007/s12072-022-10426-4. Online ahead of print.

ABSTRACT

BACKGROUND: Dynamic assessment of critically ill patients with cirrhosis (CICs) is required for accurate prognostication.

OBJECTIVE: Development of a dynamic model for prediction of mortality and decision on futility of care in CICs.

DESIGN AND SETTING: In a prospective cohort study, we developed the PIRO-CIC model (predisposition, injury, response, organ failure for critically ill cirrhotics)] in a derivative cohort (n = 360) and validated it (n = 240) for patients admitted to the Liver ICU.

PATIENTS: Decompensated cirrhosis admitted to ICU. The model was developed using Cox-regression analysis, and futility was performed by decision-curve analysis.

RESULTS: CICs aged 48 ± 11.5 years, 87% males, majority being alcoholics, were enrolled, of which 73.5% were alive at one month. Factors significant for P component were INR [hazard ratio 1.12, 95% confidence interval 1.07-1.18] and CystatinC [2.25, 1.70-2.97]; for I component were sepsis [4.69, 1.90-11.57], arterial lactate[1.40, 1.02-1.93] and alcohol as etiology [2.78, 1.85-4.18]; for R component-systemic inflammatory response syndrome [1.97, 1.14-3.42] and urine neutrophil-gelatinase-associated lipocalin [HR 2.37, 1.59-3.53]; for O component-low PaO2/FiO2 ratio and need of mechanical ventilation [7.41, 4.63-11.86]. The PIRO-CIC model predicted one-month mortality with a C-index of 0.83 in the derivation and 0.80 in the validation cohorts. It predicted futility of care better than other prognostic scores. The immediate risk of mortality increased by 39% with each unit increase in PIRO-CIC score.

LIMITATIONS: Not applicable for acute-on-chronic liver failure and patients requiring emergency liver transplant.

CONCLUSIONS: Assessment and stratification of CICs with the dynamic PIRO-CIC model could determine one-month mortality and futility in the first week. Targeted and aggressive management of coagulation, kidneys, sepsis, and severe systemic inflammation may improve outcomes of CICs.

PMID:36227516 | DOI:10.1007/s12072-022-10426-4

Phys Eng Sci Med. 2022 Oct 13. doi: 10.1007/s13246-022-01184-6. Online ahead of print.

ABSTRACT

This work details the clinical pilot study methodology used at Wellington Blood and Cancer Centre (WBCC) before the clinical release of in vivo dosimetry (IVD) system EPIgray™ for head and neck (H&N) volumetric modulated arc therapy (VMAT) treatments. Clinical pilot studies make it possible to select appropriate, department-specific tolerance ranges for the treatment type and site under investigation. An IVD clinical pilot study of H&N VMAT treatments was conducted over 3 months at WBCC using EPIgray™ dose reconstruction software and included 12 patients and 32 individual treatment fractions. Statistical analysis of the dose deviations between the treatment planning system (TPS) dose and EPIgray™ reconstructed dose confirmed that a deviation tolerance range of ± 7.0% was an appropriate choice for H&N VMAT at WBCC.

PMID:36227496 | DOI:10.1007/s13246-022-01184-6

J Ultrasound. 2022 Oct 13. doi: 10.1007/s40477-022-00724-w. Online ahead of print.

ABSTRACT

BACKGROUND: To show the effectiveness of plane wave HighFrame-Rate CEUS (HiFR-CEUS) compared with “conventional” (plane wave) CEUS (C-CEUS) in the characterization of small (< 2 cm) focal liver lesions (FLLs) not easily detected by CT in cirrhotic patients. HiFR-CEUS exploit an ultra-wideband nonlinear process to combine fundamental, second and higher-order harmonic signals generated by ultrasound contrast agents to increase the frame rate. C-CEUS is limited by the transmission principle, and its frame-rate is around 10 FPS. With HiFR-CEUS (Shenzhen Mindray Bio-Medical Electronics Co., China), the frame-rate reached 60 FPS.

MATERIAL AND METHODS: Ultrasound detected small FLLs (< 2 cm) in 63 cirrhotic patients during follow-up (June 2019-February 2020); (7 nodules < 1 cm and were not evaluable by spiral CT). Final diagnosis was obtained with MRI (47) or fine needle aspiration (16 cases) C-CEUS was performed and HiFR-CEUS was repeated after 5 min; 0.8-1.2 ml of contrast media (SonoVue, Bracco, Italy) was used. 57 nodules were better evaluable with HiFR-CEUS; 6 nodules were equally evaluable by both techniques; final diagnosis was: 44 benign lesions (29 hemangiomas, 1 amartoma, 2 hepatic cysts; 2 focal nodular hyperplasias, 3 regenerative macronodules, 3 AV-shunts, 3 hepatic sparing areas and 1 focal steatosis) and 19 malignant one (17 HCCs, 1 cholangioca, 1 metastasis); statistical evaluation for better diagnosis with X² test (SPSS vers. 26); we used LI-RADS classification for evaluating sensitivity, specificity PPV, NPV and diagnostic accuracy of C- and HFR-CEUS. Corrispective AU-ROC were calculated.

RESULTS: C-CEUS and HiFR-CEUS reached the same diagnosis in 29 nodules (13 nodules > 1 < 1.5 cm; 16 nodules > 1.5 < 2 cm); HiFR-CEUS reached a correct diagnosis in 32 nodules where C-CEUS was not diagnostic (6 nodules < 1 cm; 17 nodules > 1 < 1.5 cm; 9 nodules > 1.5 < 2 cm); C-CEUS was better in 2 nodules (1 < 1 cm and 1 > 1 < 1.5 cm). Some patient’s (sex, BMI, age) and nodule’s characteristics (liver segment, type of diagnosis, nodule’s dimensions (p = 0.65)) were not correlated with better diagnosis (p ns); only better visualization (p 0.004) was correlated; C-CEUS obtained the following LI-RADS: type-1: 18 Nodules, type-2: 21; type-3: 7, type-4: 7; type-5: 8; type-M: 2; HiFR-CEUS: type-1: 38 Nodules, type-2: 2; type-3:4, type-4: 2; type-5: 15; type-M: 2; In comparison with final diagnosis: C-CEUS: TP: 17; TN: 39; FP: 5; FN:2; HIFR-CEUS: TP: 18; TN: 41; FP: 3; FN:1; C-CEUS: sens: 89.5%; Spec: 88.6%, PPV: 77.3%; NPV: 95.1%; Diagn Acc: 88.6% (AU-ROC: 0.994 ± SE_AUC: 0.127; CI: 0.969-1.019); HiHFR CEUS: sens: 94.7%; Spec: 93.2%, PPV: 85.7%; NPV: 97.6%; Diagn Acc: 93.2% (AU-ROC: 0.9958 ± SE_AUC: 0.106; CI: 0.975-1.017) FLL vascularization in the arterial phase was more visible with HiFR-CEUS than with C-CEUS, capturing the perfusion details in the arterial phase due to a better temporal resolution. With a better temporal resolution, the late phase could be evaluated longer with HiFR-CEUS (4 min C-CEUS vs. 5 min HiFR-CEUS).

CONCLUSION: Both C-CEUS and HIFR-CEUS are good non invasive imaging system for the characterization of small lesions detected during follow up of cirrhotic patients. HiFR-CEUS allowed better FLL characterization in cirrhotic patients with better temporal and spatial resolution capturing the perfusion details that cannot be easily observed with C-CEUS.

PMID:36227456 | DOI:10.1007/s40477-022-00724-w

J Racial Ethn Health Disparities. 2022 Oct 13. doi: 10.1007/s40615-022-01428-x. Online ahead of print.

ABSTRACT

The COVID-19 pandemic has brought new urgency to a longstanding problem: the US health system is not well-equipped to accommodate the country’s large limited English proficient (LEP) population in times of national emergency. We examined the landscape of Spanish-language COVID-19 website information compared to information in English provided by health departments of the top 10 cities by population in the USA. For each city, coders evaluated three score measures (amount of information, presentation quality, and ease of navigation) for six content types (general information, symptoms, testing, prevention, vaccines, and live statistics) across six delivery modes (print resources, website text, videos, external links, data visualization, and media toolkits). We then calculated a grand average, combining all cities’ values per score measure for each content type-delivery mode combination, to understand the landscape of Spanish-language information across the country. Overall, we found that, for all cities combined, nearly all content types and delivery modes in Spanish were inferior or non-existent compared to English resources. Our findings also showed much variability and spread concerning content type and delivery mode of information. Finally, our findings uncovered three main clusters of content type and delivery mode combinations for Spanish-language information, ranging from similar to worse, compared to information in English. Our findings suggest that COVID-19 information was not equivalently provided in Spanish, despite federal guidance regarding language access during times of national emergency. These results can inform ongoing and future emergency communication plans for Spanish-preferring LEP and other LEP populations in the USA.

PMID:36227453 | DOI:10.1007/s40615-022-01428-x

Int J Bipolar Disord. 2022 Oct 13;10(1):23. doi: 10.1186/s40345-022-00267-3.

ABSTRACT

BACKGROUND: In the 1970 s, scientific research on psychiatric nosology was summarized in Research Diagnostic Criteria (RDC), based solely on empirical data, an important source for the third revision of the official nomenclature of the American Psychiatric Association in 1980, the Diagnostic and Statistical Manual, Third Edition (DSM-III). The intervening years, especially with the fourth edition in 1994, saw a shift to a more overtly “pragmatic” approach to diagnostic definitions, which were constructed for many purposes, with research evidence being only one consideration. The latest editions have been criticized as failing to be useful for research. Biological and clinical research rests on the validity of diagnostic definitions that are supported by firm empirical foundations, but critics note that DSM criteria have failed to prioritize research data in favor of “pragmatic” considerations.

RESULTS: Based on prior work of the International Society for Bipolar Diagnostic Guidelines Task Force, we propose here Clinical Research Diagnostic Criteria for Bipolar Illness (CRDC-BP) for use in research studies, with the hope that these criteria may lead to further refinement of diagnostic definitions for other major mental illnesses in the future. New proposals are provided for mixed states, mood temperaments, and duration of episodes.

CONCLUSIONS: A new CRDC could provide guidance toward an empirically-based, scientific psychiatric nosology, and provide an alternative clinical diagnostic approach to the DSM system.

PMID:36227452 | DOI:10.1186/s40345-022-00267-3

Pediatr Nephrol. 2022 Oct 13. doi: 10.1007/s00467-022-05747-3. Online ahead of print.

ABSTRACT

BACKGROUND: Children with immunoglobulin A vasculitis (IgAV Henoch-Schönlein purpura) frequently encounter nephritis (IgAV-N) with 1-2% risk of kidney failure. The pathophysiology of IgAV-N is not fully understood with speculation that complement may contribute. The aim of this study was to identify whether urinary complement proteins are increased in children with IgAV-N.

METHODS: A cross-sectional prospective cohort of children with IgAV were recruited together with controls including healthy children and children with systemic lupus erythematosus (SLE). Patients were subdivided according to the presence of nephritis. Urinary C3, C4, C5, and C5a were measured by enzyme-linked immunosorbent assay (ELISA) and corrected for urinary creatinine.

RESULTS: The study included 103 children; 47 with IgAV (37 IgAV without nephritis, IgAVwoN; 10 IgAV-N), 30 SLE and 26 healthy children. Urinary complement C3, C4, and C5 were all statistically significantly increased in all children with IgAV compared to SLE patients (all p < 0.05). In patients with IgAV-N, urinary complement C3, C4, C5, C5a were all statistically significantly increased compared to IgAVwoN (C3 14.65 μg/mmol [2.26-20.21] vs. 2.26 μg/mmol [0.15-3.14], p = 0.007; C4 6.52 μg/mmol [1.30-9.72] vs. 1.37 μg/mmol [0.38-2.43], p = 0.04; C5 1.36 μg/mmol [0.65-2.85] vs. 0.38 μg/mmol [0.03-0.72], p = 0.005; C5a 101.9 ng/mmol [15.36-230.0] vs. 18.33 ng/mmol [4.27-33.30], p = 0.01). Using logistic regression, the urinary complement components produced an outstanding ability to discriminate between patients with and without nephritis in IgAV (AUC 0.92, p < 0.001).

CONCLUSIONS: Children with IgAV-N have evidence of increased complement proteins present in their urine that may indicate a pathological role and may allow treatment stratification. A higher resolution version of the Graphical abstract is available as Supplementary information.

PMID:36227437 | DOI:10.1007/s00467-022-05747-3