Medical Research Research Articles

Patients as knowledge partners in the context of complex chronic conditions

This article conveys how taking patient knowledge seriously can improve patient experience and further medical science. In clinical contexts related to infection-associated chronic conditions and other complex chronic illnesses, patient...

Role of Non-coding RNAs in the Response of Glioblastoma to Temozolomide.

Chemotherapy and radiotherapy are widely used in clinical practice across the globe as cancer treatments. Intrinsic or acquired chemoresistance poses a significant problem for medical practitioners and researchers, causing tumor recurrence and metastasis. The most dangerous kind of malignant brain tumor is called glioblastoma multiforme (GBM) that often recurs following surgery. The most often used medication for treating GBM is temozolomide chemotherapy; however, most patients eventually become resistant. Researchers are studying preclinical models that accurately reflect human disease and can be used to speed up drug development to overcome chemoresistance in GBM. Non-coding RNAs (ncRNAs) have been shown to be substantial in regulating tumor development and facilitating treatment resistance in several cancers, such as GBM. In this work, we mentioned the mechanisms of how different ncRNAs (microRNAs, long non-coding RNAs, circular RNAs) can regulate temozolomide chemosensitivity in GBM. We also address the role of these ncRNAs encapsulated inside secreted exosomes.

Medical School Regulatory Compliance Burdens for the Physician-Scientist.

Medical school research faculty is increasingly required to complete more comprehensive and time consuming compliance steps for regulatory oversight. These relate to animal studies, information technology, biosafety, and human resources. For physician-scientists, the additional role in clinical care adds to these research areas with regulatory compliance in patient care and ever-growing web trainings. The sum of all these compliance regimes is a considerable time and cost burden, diminished research performance, and disengagement of faculty from colleagues, collaborations, and institutions. Many research and clinical compliance processes were put in place, often using legacy systems, in well-meaning attempts to address straightforward regulations in humane animal care, safe use of biological agents, and medical care delivery. However, their accumulation and negative impact on faculty performance demand time, energy, and resources that impact academic productivity. There are solutions to a relentlessly increasing regulatory load for research faculty, which involve vertical integration, convergence, and performance assessment in medical school and health system compliance regimes. ANN NEUROL 2024.

Development and cross-sectional morphology of the recurrent laryngeal nerves in human fetuses.

The recurrent laryngeal nerve is a bilateral branch of the vagus nerve that is mainly associated with the motor innervation of the intrinsic muscles of the larynx. Despite its bilateral distribution, the right and left recurrent laryngeal nerves display unequal length due to embryological processes related to the development of the aortic arches. This length asymmetry leads to theories about morphological compensations to provide symmetrical functions to the intrinsic muscles of the larynx. In this study we investigated the developmental and cross-sectional morphometrics of the recurrent laryngeal nerves in human fetuses. Fifteen stillbirth fetuses donated to anatomical and medical research were used for investigation. Fetuses had intrauterine age ranging from 30 to 40 weeks estimated by biometry methods. Specialized anatomical dissection of the visceral block of the neck was performed to prepare histological samples of the recurrent laryngeal nerves in its point of contact with the larynx, and morpho-quantitative techniques were applied to evaluate the epineurium and perineural space of the recurrent laryngeal nerves. No statistical difference in the cross-sectional morphology of the epineurium and perineural space between right and left recurrent laryngeal nerves intra-individually was confirmed, however, we found evidence that these structures are under greater development in the left recurrent laryngeal nerve during 30 to 40 weeks of intrauterine life. Our data suggest that the nerves are under morphological development that possibly set the stage for accommodation of larger diameter and myelinization of the left recurrent laryngeal nerve during post-natal life.

Resolution limits for radiation-induced acoustic imaging for in vivo radiation dosimetry.

Radiation-induced acoustic (RA) computed tomographic (RACT) imaging is being thoroughly explored for radiation dosimetry. It is essential to understand how key machine parameters like beam pulse, size, and energy deposition affect image quality in RACT. We investigate the intricate interplay of these parameters and how these factors influence dose map resolution in RACT. We first conduct an analytical assessment of time-domain RA signals and their corresponding frequency spectra for certain testcases, and computationally validate these analyses. Subsequently, we simulated a series of X-ray-based RACT (XACT) experiments and compared the simulations with experimental measurements. In-silico reconstruction studies have also been conducted to demonstrate the resolution limits imposed by the temporal pulse profiles on RACT. XACT experiments were performed using clinical machines and the reconstructions were analyzed for resolution capabilities. Our paper establishes the theory for predicting the time- and frequency-domain behavior of RA signals. We illustrate that the frequency content of RA signal is not solely dependent on the spatial energy deposition characteristics but also on the temporal features of radiation. The same spatial energy deposition through a Gaussian pulse and a rectangular pulse of equal pulsewidths results in different frequency spectra of the RA signals. RA signals corresponding to the rectangular pulse exhibit more high-frequency content than their Gaussian pulse counterparts and hence provide better resolution in the reconstructions. XACT experiments with ~3.2 us and ~4 us rectangular radiation pulses were performed, and the reconstruction results were found to correlate well with the in-silico results. Here, we discuss the inherent resolution limits for RACT-based radiation dosimetric systems. While our study is relevant to the broader community engaged in research on photoacoustics, X-ray-acoustics, and proto/ionoacoustics, it holds particular significance for medical physics researchers aiming to set up RACT for dosimetry and radiography using clinical radiation machines.

Sex differences in alcohol use: is it all about hormones?

Risky alcohol use and alcohol use disorders (AUD) are a rising problem in women, yet a major disparity in our understanding of what drives alcohol consumption in women remains. Historically biomedical research has focused on male subjects, however, recent increases in reporting of females, have highlighted major differences between the sexes. Here we review the current literature of the impact of gonadal steroid hormones (estrogens, androgens and progestins), neurosteriods and neurobiological factors on alcohol use in clinical and preclinical studies of both sexes. Further, we briefly discuss how fundamental sex differences in genetics, metabolism, neuroimmune and stress responses may influence sex differences in alcohol intake. Comparing the sexes could aid in the discovery of novel therapeutics to treat AUD, and implementation of current treatment options in women.

Neural interval‐censored survival regression with feature selection

AbstractSurvival analysis is a fundamental area of focus in biomedical research, particularly in the context of personalized medicine. This prominence is due to the increasing prevalence of large and high‐dimensional datasets, such as omics and medical image data. However, the literature on nonlinear regression algorithms and variable selection techniques for interval‐censoring is either limited or nonexistent, particularly in the context of neural networks. Our objective is to introduce a novel predictive framework tailored for interval‐censored regression tasks, rooted in Accelerated Failure Time (AFT) models. Our strategy comprises two key components: (i) a variable selection phase leveraging recent advances on sparse neural network architectures; (ii) a regression model targeting prediction of the interval‐censored response. To assess the performance of our novel algorithm, we conducted a comprehensive evaluation through both numerical experiments and real‐world applications that encompass scenarios related to diabetes and physical activity. Our results outperform traditional AFT algorithms, particularly in scenarios featuring nonlinear relationships.

Liver cirrhosis: current status and treatment options using western or traditional Chinese medicine

Liver cirrhosis arises from liver fibrosis and necroinflammation caused by various mechanisms of hepatic injury. It is a prevalent condition in clinical practice characterized by hepatocellular dysfunction, portal hypertension, and associated complications. Despite its common occurrence, the etiology and pathogenesis of liver cirrhosis remain incompletely understood, posing a significant health threat. Effective prevention of its onset and progression is paramount in medical research. Symptoms often include discomfort in the liver area, while complications such as sarcopenia, hepatic encephalopathy, ascites, upper gastrointestinal bleeding, and infection can arise. While the efficacy of Western medicine in treating liver cirrhosis is uncertain, Chinese medicine offers distinct advantages. This review explores advancements in liver cirrhosis treatment encompassing non-pharmacological and pharmacological modalities. Chinese medicine interventions, including Chinese medicine decoctions, Chinese patent medicines, and acupuncture, exhibit notable efficacy in cirrhosis reversal and offer improved prognoses. Nowadays, the combination of Chinese and Western medicine in the treatment of liver cirrhosis also has considerable advantages, which is worthy of further research and clinical promotion. Standardized treatment protocols based on these findings hold significant clinical implications.

The evolving role of biostatistics in medical research

The evolving role of biostatistics in medical research

Statistical Analysis of Features for Detecting Leukemia

In this age of digital microscopy, image processing, statistical analysis, categorization, and systems for decision-making have become essential tools for medical diagnostics research. By visualizing and analyzing images, clinicians can identify anomalies in intracellular structure. Leukemia is a cancerous condition marked by an unregulated increase in aberrant white blood cells (WBCs). Recognizing acute leukemia tumor cells in blood smear images (BSI) is a challenging assignment. Image segmentation is regarded as the most significant step in the automated identification of this disease. The innovative concavity-based segmentation algorithm is employed in this study to segment WBC in sub-images from the ALLIDB2 database. The concave endpoints and elliptical features are used in the segmentation step of convex-shaped cell images. The procedure involves the extraction of contour evidence, which detects the visible section of each object, and contour estimation, which corresponds to the final object’s contours. Following the identification of the cells and their internal structure by concavity-based segmentation, the cells are categorized based on their morphological and statistical features. The method was evaluated using a public dataset meant to test classification and segmentation approaches. The statistical tool SPSS is used to independently check the significance of derived features. For classification, significant features are passed into machine learning techniques such as support vector machines (SVM), k-nearest neighbor (KNN), neural networks (NN), decision trees (DT), and Nave Bayes (NB). With an AUC of 98.9% and a total accuracy of 95%, the neural network model performed better. We advocate using the neural network model to identify acute leukemia cells based on its accuracy.

American registry of ambulatory and acute decompensated heart failure (AMERICCAASS registry): Rationale and design.

Heart failure (HF) is a highly prevalent and progressive condition associated with significant morbidity and mortality rates. Acute decompensated HF precipitates millions of hospitalizations each year. Despite therapeutic advances, the overall prognosis of HF is poor. The varying clinical courses and outcomes of patients with this disease may be due to region-specific gaps and since most HF studies are conducted in developed countries, the participation of Latin American and Caribbean countries is low. Considering this, the American Registry of Ambulatory and Acute Decompensated Heart Failure (AMERICCAASS) aims to characterize the population with ambulatory and acute decompensated HF in the American continent and to determine rehospitalization and survival outcomes during the 12months of follow-up. AMERICCAASS Registry is an observational, prospective, and hospital-based registry recruiting patients with ambulatory or acute decompensated HF. The registry plans to include between two and four institutions per country from at least 20 countries in the Americas, and at least 60 patients recruited from each participant institution regardless of their ambulatory or acutely decompensated condition. Ambulatory patients with confirmed HF diagnosis or inpatients presenting with acute decompensated HF will be included. Follow-up will be performed at 12months in ambulatory patients or 1, 6, and 12months after hospital discharge in acutely decompensated HF patients. This ongoing study began on 1 April 2022, with recruitment scheduled to end on 30 November 2023, and follow-up on 31 January 2025. Ethics approval was obtained from the Biomedical Research Ethics Committee of Fundación Valle del Lili. Data collected in the AMERICCAASS registry is being stored on the electronic platform REDCap (Research Electronic Data Capture), which allows different forms for patient groups to enable unbiased analyses. For quantitative variables comparison, we will use the Student's t-test or non-parametric tests accordingly. Categorical variables will be presented as proportions, and groups will be compared with Fisher's exact test. The significance level will be <0.05 for comparisons. Readmissions and post-discharge mortality will be calculated as proportions at 1, 6, and 12months, with a survival analysis by conditional probability and the Kaplan-Meier method. AMERICCAASS Registry is intended to be the most important registry of the continent for obtaining important information about demographics, aetiology, co-morbidities, and treatment received, either ambulatory or hospitalized. This registry may contribute to the optimization of national and regional evidence and public policies for the diagnosis and treatment of HF disease.

Anti-inflammatory therapy with nebulized dornase alfa for severe COVID-19 pneumonia: a randomized unblinded trial.

Prinflammatory extracellular chromatin from neutrophil extracellular traps (NETs) and other cellular sources is found in COVID-19 patients and may promote pathology. We determined whether pulmonary administration of the endonuclease dornase alfa reduced systemic inflammation by clearing extracellular chromatin. Eligible patients were randomized (3:1) to the best available care including dexamethasone (R-BAC) or to BAC with twice-daily nebulized dornase alfa (R-BAC + DA) for seven days or until discharge. A 2:1 ratio of matched contemporary controls (CC-BAC) provided additional comparators. The primary endpoint was the improvement in C-reactive protein (CRP) over time, analyzed using a repeated-measures mixed model, adjusted for baseline factors. We recruited 39 evaluable participants: 30 randomized to dornase alfa (R-BAC +DA), 9 randomized to BAC (R-BAC), and included 60 CC-BAC participants. Dornase alfa was well tolerated and reduced CRP by 33% compared to the combined BAC groups (T-BAC). Least squares (LS) mean post-dexamethasone CRP fell from 101.9 mg/L to 23.23 mg/L in R-BAC +DA participants versus a 99.5 mg/L to 34.82 mg/L reduction in the T-BAC group at 7 days; p=0.01. The anti-inflammatory effect of dornase alfa was further confirmed with subgroup and sensitivity analyses on randomised participants only, mitigating potential biases associated with the use of CC-BAC participants. Dornase alfa increased live discharge rates by 63% (HR 1.63, 95% CI 1.01-2.61, p=0.03), increased lymphocyte counts (LS mean: 1.08 vs 0.87, p=0.02) and reduced circulating cf-DNA and the coagulopathy marker D-dimer (LS mean: 570.78 vs 1656.96 μg/mL, p=0.004). Dornase alfa reduces pathogenic inflammation in COVID-19 pneumonia, demonstrating the benefit of cost-effective therapies that target extracellular chromatin. LifeArc, Breathing Matters, The Francis Crick Institute (CRUK, Medical Research Council, Wellcome Trust). NCT04359654.

Exploring subjective quality-of-life indicators in long-term care facilities: a mixed-methods research protocol.

Improving quality of life has become a priority in the long-term care (LTC) sector internationally. With development and implementation guidance, standardised quality-of-life monitoring tools based on valid, self-report surveys could be used more effectively to benefit LTC residents, families and organisations. This research will explore the potential for subjective quality-of-life indicators in the interRAI Self-Reported Quality of Life Survey for Long-Term Care Facilities (QoL-LTCF). Guided by the Medical Research Council Framework, this research will entail a (1) modified Delphi study, (2) feasibility study and (3) realist synthesis. In study 1, we will evaluate the importance of statements and scales in the QoL-LTCF by administering Delphi surveys and focus groups to purposively recruited resident and family advisors, researchers, and LTC clinicians, staff, and leadership from international quality improvement organisations. In study 2, we will critically examine the feasibility and implications of risk-adjusting subjective quality-of-life indicators. Specifically, we will collect expert stakeholder perspectives with interviews and apply a risk-adjustment methodology to QoL-LTCF data. In study 3, we will iteratively review and synthesise literature, and consult with expert stakeholders to explore the implementation of quality-of-life indicators. This study has received approval through a University of Waterloo Research Ethics Board and the Social and Societal Ethics Committee of KU Leuven. We will disseminate our findings in conferences, journal article publications and presentations for a variety of stakeholders.

Anti-inflammatory therapy with nebulized dornase alfa for severe COVID-19 pneumonia: a randomized unblinded trial

Background:Prinflammatory extracellular chromatin from neutrophil extracellular traps (NETs) and other cellular sources is found in COVID-19 patients and may promote pathology. We determined whether pulmonary administration of the endonuclease dornase alfa reduced systemic inflammation by clearing extracellular chromatin.Methods:Eligible patients were randomized (3:1) to the best available care including dexamethasone (R-BAC) or to BAC with twice-daily nebulized dornase alfa (R-BAC + DA) for seven days or until discharge. A 2:1 ratio of matched contemporary controls (CC-BAC) provided additional comparators. The primary endpoint was the improvement in C-reactive protein (CRP) over time, analyzed using a repeated-measures mixed model, adjusted for baseline factors.Results:We recruited 39 evaluable participants: 30 randomized to dornase alfa (R-BAC +DA), 9 randomized to BAC (R-BAC), and included 60 CC-BAC participants. Dornase alfa was well tolerated and reduced CRP by 33% compared to the combined BAC groups (T-BAC). Least squares (LS) mean post-dexamethasone CRP fell from 101.9 mg/L to 23.23 mg/L in R-BAC +DA participants versus a 99.5 mg/L to 34.82 mg/L reduction in the T-BAC group at 7 days; p=0.01. The anti-inflammatory effect of dornase alfa was further confirmed with subgroup and sensitivity analyses on randomised participants only, mitigating potential biases associated with the use of CC-BAC participants. Dornase alfa increased live discharge rates by 63% (HR 1.63, 95% CI 1.01–2.61, p=0.03), increased lymphocyte counts (LS mean: 1.08 vs 0.87, p=0.02) and reduced circulating cf-DNA and the coagulopathy marker D-dimer (LS mean: 570.78 vs 1656.96 μg/mL, p=0.004).Conclusions:Dornase alfa reduces pathogenic inflammation in COVID-19 pneumonia, demonstrating the benefit of cost-effective therapies that target extracellular chromatin.Funding:LifeArc, Breathing Matters, The Francis Crick Institute (CRUK, Medical Research Council, Wellcome Trust).Clinical trial number:NCT04359654.

Navigating Bias When Using AI in Oncology

OPTIMISING patient care and survival with AI is a rapidly advancing field of medical research. During the 2024 American Society of Clinical Oncology (ASCO) Annual Meeting, a symposium titled “Using ‘Artificial’ Intelligence to Achieve ‘Real’ Improvements in Cancer Care” explored the use of innovative AI algorithms in oncology. Experts presented breakthroughs in diagnostic and predictive AI, whilst increasing awareness of inherent bias in AI models that can perpetuate into clinical outcomes.

Misconducts in research and methods to uphold research integrity.

Research misconduct refers to deliberate or accidental manipulation or misrepresentation of research data, findings, or processes. It can take many forms, such as fabricating data, plagiarism, or failing to disclose conflicts of interest. Data falsification is a serious problem in the field of medical research, as it can lead to the promotion of false or misleading information. Researchers might engage in p-hacking - the practice of using someone else's research results or ideas without giving them proper attribution. Conflict of interest (COI) occurs when an individual's personal, financial, or professional interests could potentially influence their judgment or actions in relation to their research. Nondisclosure of COI can be considered research misconduct and can damage the reputation of the authors and institutions. Hypothesis after results are known can lead to the promotion of false or misleading information. Cherry-picking data is the practice of focusing attention on certain data points or results that support a particular hypothesis, while ignoring or downplaying results that do not. Researchers should be transparent about their methods and report their findings honestly and accurately. Research institutions should have clear and stringent policies in place to address scientific misconduct. This knowledge must become widespread, so that researchers and readers understand what approaches to statistical analysis and reporting amount to scientific misconduct. It is imperative that readers and researchers alike are aware of the methods of statistical analysis and reporting that constitute scientific misconduct.

First Australian estimates of incidence and prevalence of uterine fibroids: a data linkage cohort study 2000-2022.

What is the estimated prevalence and incidence of uterine fibroids diagnosed in Australian women of reproductive age? An estimated 7.3% of Australian women had a diagnosis of uterine fibroids by the age of 45-49 years, with age-specific incidence highest in women aged 40-44 years (5.0 cases per 1000 person-years). Uterine fibroids are associated with a high symptom burden and may affect overall health and quality of life. Studies in different countries show a wide variation in both the prevalence (4.5-68%) and incidence (2.2-37.5 per 1000 person-years) of uterine fibroids, which may be partly explained by the type of investigation, method of case ascertainment, or the age range of the study population, necessitating the reporting of country-specific estimates. This observational prospective cohort study using self-report survey and linked administrative data (2000-2022) included 8066 women, born between 1973 and 1978, in the Australian Longitudinal Study on Women's Health. A combination of self-report survey and linked administrative health data (hospital, emergency department, the Medicare Benefits Schedule, and the Pharmaceutical Benefits Scheme) were used to identify women with a report of a diagnosis of uterine fibroids between 2000 and 2022. Of the 8066 Australian women followed for 22 years, an estimated 7.3% of women (95% CI 6.9, 7.6) had a diagnosis of uterine fibroids by the age of 45-49 years. The incidence increased with age and was highest in women aged 40-44 years (5.0 cases per 1000 person-years, 95% CI 4.3, 5.7 cases per 1000 person-years). Women with uterine fibroids were more likely to experience heavy or painful periods. They were also more likely to report low iron levels, endometriosis, and poor self-rated health and to have two or more annual visits to their general practitioner. Our estimates are based on self-report of doctor diagnosis or treatment for fibroids and/or data linked to treatment and procedure administrative records. This predominantly captures women with symptomatic fibroids, but has the potential for misclassification of asymptomatic women and an underestimate of overall prevalence and incidence. In addition, questions on fibroids were only asked in surveys when women were 37-42 years of age to 43-48 years of age, so cases at younger ages may have been underestimated (particularly in women with less severe symptoms) as these were only ascertained through data linkage. These are the first population-based estimates of the prevalence and incidence of uterine fibroids in women of reproductive age in Australia. Establishing these first estimates will help inform health policy and health care provision in the Australian context. The ALSWH is funded by the Australian Government Department of Health and Aged Care. L.FW. was supported by an Australian National Health and Medical Research Council (NHMRC) Centres for Research Excellence grant (APP1153420) and G.D.M. was supported by an NHMRC Leadership Fellowship (APP2009577). The funding bodies played no role in the design, the collection, analysis or interpretation of data, the writing of the manuscript, or the decision to submit the manuscript for publication. There are no competing interests. N/A.

Granulosa cell metabolism at ovulation correlates with oocyte competence and is disrupted by obesity and aging.

Is oocyte developmental competence associated with changes in granulosa cell (GC) metabolism? GC metabolism is regulated by the LH surge, altered by obesity and reproductive aging, and, in women, specific metabolic profiles are associated with failed fertilization versus increased blastocyst development. The cellular environment in which an oocyte matures is critical to its future developmental competence. Metabolism is emerging as a potentially important factor; however, relative energy production profiles between GCs and cumulus cells and their use of differential substrates under normal in vivo ovulatory conditions are not well understood. This study identified metabolic and substrate utilization profiles within ovarian cells in response to the LH surge, using mouse models and GCs of women undergoing gonadotropin-induced oocyte aspiration followed by IVF/ICSI. To comprehensively assess follicular energy metabolism, we used real-time metabolic analysis (Seahorse XFe96) to map energy metabolism dynamics (mitochondrial respiration, glycolysis, and fatty acid oxidation) in mouse GCs and cumulus-oocyte complexes (COCs) across a detailed time course in the lead up to ovulation. In parallel, the metabolic profile of GCs was measured in a cohort of 85 women undergoing IVF/ICSI (n = 21 with normal ovarian function; n = 64 with ovarian infertility) and correlated with clinical parameters and cycle outcomes. Our study reveals dynamic changes in GC energy metabolism in response to ovulatory LH, with mitochondrial respiration and glycolysis differentially affected by obesity versus aging, in both mice and women. High respiration in GCs is associated with failed fertilization (P < 0.05) in a subset of women, while glycolytic reserve and mitochondrial ATP production are correlated with on-time development at Day 3 (P < 0.05) and blastocyst formation (P < 0.01) respectively. These data provide new insights into the cellular mechanisms of infertility, by uncovering significant associations between metabolism within the ovarian follicle and oocyte developmental competence. A larger prospective study is needed before the metabolic markers that were positively and negatively associated with oocyte quality can be used clinically to predict embryo outcomes. This study offers new insights into the importance of GC metabolism for subsequent embryonic development and highlights the potential for therapeutic strategies focused on optimizing mitochondrial metabolism to support embryonic development. National Health and Medical Research Council (Australia). The authors have no competing interests. N/A.

Theory of change for addressing sex and gender bias, invisibility and exclusion in Australian health and medical research, policy and practice

Sex and gender are inadequately considered in health and medical research, policy and practice, leading to preventable disparities in health and wellbeing. Several global institutions, journals, and funding bodies have developed policies and guidelines to improve the inclusion of diverse participants and consideration of sex and gender in research design and reporting and the delivery of clinical care. However, according to recent evaluations, these policies have had limited impact on the inclusion of diverse research participants, adequate reporting of sex and gender data and reducing preventable inequities in access to, and quality provision of, healthcare. In Australia, the Sex and Gender Policies in Medical Research (SGPMR) project aims to address sex and gender bias in health and medical research by (i) examining how sex and gender are currently considered in Australian research policy and practice; (ii) working with stakeholders to develop policy interventions; and (iii) understanding the wider impacts, including economic, of improved sex and gender consideration in Australian health and medical research. In this paper we describe the development of a theory of change (ToC) for the SGPMR project. The ToC evolved from a two-stage process consisting of key stakeholder interviews and a consultation event. The ToC aims to identify the pathways to impact from improved consideration of sex and gender in health and medical research, policy and practice, and highlight how key activities and policy levers can lead to improvements in clinical practice and health outcomes. In describing the development of the ToC, we present an entirely novel framework for outlining how sex and gender can be appropriately considered within the confines of health and medical research, policy and practice.

Estimation of biological variance in coherent Raman microscopy data of two cell lines using chemometrics.

Broadband Coherent Anti-Stokes Raman Scattering (BCARS) is a valuable spectroscopic imaging tool for visualizing cellular structures and lipid distributions in biomedical applications. However, the inevitable biological changes in the samples (cells/tissues/lipids) introduce spectral variations in BCARS data and make analysis challenging. In this work, we conducted a systematic study to estimate the biological variance in BCARS data of two commonly used cell lines (HEK293 and HepG2) in biomedical research. The BCARS data were acquired from two different experimental setups (Leibniz Institute of Photonics Technology (IPHT) in Jena and Politecnico di Milano (POLIMI) in Milano) to evaluate the reproducibility of results. Also, spontaneous Raman data were independently acquired at POLIMI to validate those results. First, Kramers-Kronig (KK) algorithm was utilized to retrieve Raman-like signals from the BCARS data, and a pre-processing pipeline was subsequently used to standardize the data. Principal component analysis - Linear discriminant analysis (PCA-LDA) was performed using two cross-validation (CV) methods: batch-out CV and 10-fold CV. Additionally, the analysis was repeated, considering different spectral regions of the data as input to the PCA-LDA. Finally, the classification accuracies of the two BCARS datasets were compared with the results of spontaneous Raman data. The results demonstrated that the CH band region (2770-3070 cm-1) and spectral data in the 1500-1800 cm-1 region have significantly contributed to the classification. A maximum of 100% balanced accuracies were obtained for the 10-fold CV for both BCARS setups. However, in the case of batch-out CV, it is 92.4% for the IPHT dataset and 98.8% for the POLIMI dataset. This study offers a comprehensive overview for estimating biological variance in biomedical applications. The insights gained from this analysis hold promise for improving the reliability of BCARS measurements in biomedical applications, paving the way for more accurate and meaningful spectroscopic analyses in the study of biological systems.