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Colorectal cancer (CRC) screening has been demonstrated to reduce CRC incidence and mortality. However, besides such benefits, CRC screening is also associated with potential harmful effects. In an ideal world, screening would only be directed to the small proportion of the population that might potentially benefit. Risk-based screening can be seen as a first step towards this ideal world, by redistributing screening resources from low-risk to high-risk individuals. In theory, this should result in scarce resources being used in individuals who benefit most, while intensity of screening is reduced in individuals who benefit less, hence improving the benefit-harm ratio among all invitees. Available strategies that have been proposed for risk-based CRC screening include using information on age, sex, prior screening history, lifestyle and/or genetic information. Implementation of risk-based screening requires careful consideration of reliable risk prediction models, participation with screening and informed decision-making. While it is important to recognise the limitations of current approaches, available evidence suggests that it might be feasible to start planning the introduction of tailored strategies within screening programmes. Implementing risk-based screening based on age, sex and prior screening history alone would already represent a substantial improvement over current uniform screening approaches. We propose that it is time that screening programmes start there and continue striving towards more comprehensive approaches embedding primary prevention as an effective approach to lower risk for everyone.

There is a need for timely, accurate diagnosis, and personalised management in lung diseases. Exhaled breath reflects inflammatory and metabolic processes in the human body, especially in the lungs. The analysis of exhaled breath using electronic nose (eNose) technology has gained increasing attention in the past years. This technique has great potential to be used in clinical practice as a real-time non-invasive diagnostic tool, and for monitoring disease course and therapeutic effects. To date, multiple eNoses have been developed and evaluated in clinical studies across a wide spectrum of lung diseases, mainly for diagnostic purposes. Heterogeneity in study design, analysis techniques, and differences between eNose devices currently hamper generalization and comparison of study results. Moreover, many pilot studies have been performed, while validation and implementation studies are scarce. These studies are needed before implementation in clinical practice can be realised. This review summarises the technical aspects of available eNose devices and the available evidence for clinical application of eNose technology in different lung diseases. Furthermore, recommendations for future research to pave the way for clinical implementation of eNose technology are provided. Supplementary Information The online version contains supplementary material available at 10.1186/s12931-021-01835-4.

SummaryBackgroundImmersive virtual reality (iVR)-based digital therapeutics (DTx) are gaining clinical attention in the field of pain management. Based on known analogies between pain and dyspnea, we investigated the effects of visual-respiratory feedback, on persistent dyspnea in patients recovering from COVID-19 pneumonia.MethodsWe performed a controlled, randomized, single-blind, cross-over clinical study to evaluate an iVR-based intervention to alleviate dyspnea in patients recovering from COVID-19 pneumonia. Included patients reported persistent dyspnea (≥5 on a 10-point scale) and preserved cognitive function (MoCA>24). Assignment was random and concealed. Patients received synchronous (intervention) or asynchronous (control) feedback of their breathing, embodied via a gender-matched virtual body. Outcomes were assessed using questionnaires and breathing recordings. COVVR is registered with ClinicalTrials.gov (NCT04844567).FindingsStudy enrollment was open between November 2020 and April 2021. Twenty-six patients were enrolled (27% women; age: median=55, interquartile range (IQR)=18). Data were available for 24 of 26 patients. The median (IQR) rating on a 7-point Likert-scale of breathing comfort improved from 1(2) at baseline, to 2(1) for synchronous feedback, but remained unchanged at 1(1.5) for asynchronous feedback (pInterpretationBased on these findings, our iVR-based DTx presents a feasible and safe respiratory rehabilitation tool that improves breathing comfort in patients recovering from COVID-19 infection presenting with persistent dyspnea. Future research should investigate the DTx’s generalizability to persistent dyspnea with other etiologies and its potential for preventing chronification.FundingMarie Sklodowska-Curie Individual Fellowship (H2020-MSCA-IF-2019 894111/ RESPVR), Bertarelli Foundation

The landscape of cancer treatment has been transformed over the past decade by the success of immune-targeting therapies. However, despite sipuleucel-T being the first-ever approved vaccine for cancer and the first immunotherapy licensed for prostate cancer in 2010, immunotherapy has since seen limited success in the treatment of prostate cancer. The tumour microenvironment of prostate cancer presents particular barriers for immunotherapy. Moreover, prostate cancer is distinguished by being one of only two solid tumours where increased T cell-infiltration correlates with a poorer, rather than improved, outlook. Here, we discuss the specific aspects of the prostate cancer microenvironment that converge to create a challenging microenvironment, including myeloid-derived immune cells and cancer-associated fibroblasts. By exploring the immune microenvironment of defined molecular subgroups of prostate cancer, we propose an immunogenomic subtyping approach to single-agent and combination immune-targeting strategies that could lead to improved outcomes in prostate cancer treatment.

Biobanks play a crucial role in enabling biomedical research by facilitating scientific use of valuable human biomaterials. The PALGA foundation—a nationwide network and registry of histo- and cytopathology in the Netherlands—was established to promote the provision of data within and between pathology departments, and to make the resulting knowledge available for healthcare. Apart from the pathology data, we aimed to utilize PALGA’s nationwide network to find and access the rich wealth of Formalin-Fixed Paraffin-Embedded (FFPE) tissue samples for scientific use. We implemented the Dutch National TissueArchive Portal (DNTP) to utilize PALGA’s nationwide network for requesting FFPE tissue samples. The DNTP consists of (1) a centrally organized internet portal to improve the assessing, processing, harmonization, and monitoring of the procurement process, while (2) dedicated HUB-employees provide practical support at peripheral pathology departments. Since incorporation of the DNTP, both the number of filed requests for FFPE tissue samples and the amount of HUB-mediated support increased 55 and 29% respectively. In line, the sample procurement duration time decreased significantly (− 47%). These findings indicate that implementation of the DNTP improved the frequency, efficiency, and transparency of FFPE tissue sample procurement for research in the Netherlands. To conclude, the need for biological resources is growing persistently to enable precision medicine. Here, we access PALGA’s national, pathology network by implementation of the DNTP to allow for efficient, consistent, and transparent exchange of FFPE tissue samples for research across the Netherlands.

Introduction OncotypeDX© Recurrence Score (RS) is a multigene panel used to aid therapeutic decision making in early-stage, estrogen receptor positive (ER+)/human epidermal growth factor receptor-2 negative (HER2-) breast cancer. Aim To compare responses to neoadjuvant endocrine therapy (NET) in patients with ER+/HER2-breast cancer following substratification by RS testing. Methods This systematic review was performed in accordance to the PRISMA guidelines. Studies evaluating pathological complete response (pCR), partial response (PR), and successful conversion to breast conservation surgery (BCS) rates following NET guided by RS were retrieved. Dichotomous outcomes were reported as odds ratios (ORs) with 95% confidence intervals (CIs) following estimation by Mantel-Haenszel method. Results Eight prospective studies involving 691 patients were included. The mean age was 62.6 years (range 25–85) and the mean RS was 14.5 (range 0–68). Patients with RS 30 (OR: 1.27, 95% CI: 0.64–2.49, P = 0.490) respectively. Only 22 patients achieved pCR (2.8%) and RS group failed to predict pCR following NET (P = 0.850). Conclusion Estimations from this analysis indicate that those with low-intermediate RS on core biopsy are four times more likely to respond to NET than those with high-risk RS. Performing RS testing on diagnostic biopsy may be useful in guiding NET prescription., Highlights • Using the 21-gene assay (RS) on core biopsy is useful to guide neoadjuvant therapies. • Low-intermediate RS are four times as likely to respond to endocrine therapies. • Neoadjuvant endocrine therapy (NET) failed to increase breast conservation rates. • Following RS, NET is useful for treating early estrogen receptor positive cancers.

Background the aim of this study was to examine the cross-sectional and longitudinal associations of different multimorbidity patterns with physical frailty in older adults. Methods we used data from the Swedish National study on Aging and Care in Kungsholmen to generate a physical frailty measure, and clusters of participants with similar multimorbidity patterns were identified through fuzzy c-means cluster analyses. The cross-sectional association (n = 2,534) between multimorbidity clusters and physical frailty was measured through logistic regression analyses. Six- (n = 2,122) and 12-year (n = 2,140) longitudinal associations were determined through multinomial logistic regression analyses. Results six multimorbidity patterns were identified at baseline: psychiatric diseases; cardiovascular diseases, anaemia and dementia; sensory impairments and cancer; metabolic and sleep disorders; musculoskeletal, respiratory and gastrointestinal diseases; and an unspecific pattern lacking any overrepresented diseases. Cross-sectionally, each pattern was associated with physical frailty compared with the unspecific pattern. Over 6 years, the psychiatric diseases (relative risk ratio [RRR]: 3.04; 95% confidence intervals [CI]: 1.59–5.79); cardiovascular diseases, anaemia and dementia (RRR 2.25; 95% CI: 1.13–4.49) and metabolic and sleep disorders (RRR 1.99; 95% CI: 1.25–3.16) patterns were associated with incident physical frailty. The cardiovascular diseases, anaemia and dementia (RRR: 4.81; 95% CI: 1.59–14.60); psychiatric diseases (RRR 2.62; 95% CI: 1.45–4.72) and sensory impairments and cancer (RRR 1.87; 95% CI: 1.05–3.35) patterns were more associated with physical frailty, compared with the unspecific pattern, over 12 years. Conclusions we found that older adults with multimorbidity characterised by cardiovascular and neuropsychiatric disease patterns are most susceptible to developing physical frailty.

Governments are investing in precision medicine (PM) with the aim of improving healthcare through the use of genomic analyses and data analytics to develop tailored treatment approaches for individual patients. The success of PM is contingent upon clear public communications that engender trust and secure the social licence to collect and share large population-wide data sets because specific consent for each data re-use is impractical. Variation in the terminology used by different programmes used to describe PM may hinder clear communication and threaten trust. Language is used to create common understanding and expectations regarding precision medicine between researchers, clinicians and the volunteers. There is a need to better understand public interpretations of PM-related terminology. This paper reports on a qualitative study involving 24 focus group participants in the multi-lingual context of Singapore. The study explored how Singaporeans interpret and understand the terms ‘precision medicine’ and ‘personalised medicine’, and which term they felt more aptly communicates the concept and goals of PM. Results suggest that participants were unable to readily link the terms with this area of medicine and initially displayed preferences for the more familiar term of ‘personalised’. The use of visual aids to convey key concepts resonated with participants, some of whom then indicated preferences for the term ‘precision’ as being a more accurate description of PM research. These aids helped to facilitate dialogue around the ethical and social value, as well as the risks, of PM. Implications for programme developers and policy makers are discussed.

Graphical abstract The field of nanotechnology and personalised medicine is undergoing drastic changes in the approach and efficiency of experimentation. The COVID-19 pandemic has spiralled into mass stagnation of major laboratories around the globe and led to increased investment into remote systems for nanoparticle experiments. A significant number of laboratories now operate using automated systems; however, the extension to nanoparticle preparation and artificial intelligence–dependent databases holds great translational promise. The strive to combine automation with artificial intelligence (AI) grants the ability to optimise targeted therapeutic nanoparticles for unique cell types and patients. In this perspective, the current and future trends of automated approaches to nanomedicine synthesis are discussed and compared with traditional methods.

Objectives We sought to gain insight into the prevalence of COVID-19 and the impact stringent social distancing (shielding) has had on a large cohort of rheumatology (RD) follow-up patients from a single large UK centre. Methods We linked COVID-19-related deaths, screening and infection rates to our RD population (1.2.20–1.5.20) and audited active rheumatology follow-up patients through survey data communicated via a linked mobile phone SMS message. We assessed epidemiology, effect of stringent social distancing (shielding) and quality of life (HRQoL) by Short Form 12 (SF12). Results There were 10,387 active follow-up patients, 7911 had linked mobile numbers. 12/10,387 RD patients died from COVID-19 (0.12%); local population 4131/7,415,149 (0.12%). For patients with mobile phones, 1693/7911 (21%) responded and of these, 1605 completed the SF12. Inflammatory arthritis predominated 1174/1693 (69%); 792/1693 (47%) were shielding. Advice on shielding/distancing was followed by 1372/1693(81%). 61/1693 (4%) reported COVID-19 (24/61 shielding); medication distribution was similar in COVID and non-COVID patients. Mental SF12 (MCS) but not physical (PCS) component scores were lower in COVID (60) vs. non-COVID (1545), mean differences: MCS, − 3.3; 95% CI − 5.2 to − 1.4, P

Background In the presence of heterogeneous treatment effects, it is desirable to divide patients into subgroups based on their expected response to treatment. This is formalised via a personalised treatment recommendation: an algorithm that uses biomarker measurements to select treatments. It could be that multiple, rather than single, biomarkers better predict these subgroups. However, finding the optimal combination of multiple biomarkers can be a difficult prediction problem. Methods We described three parametric methods for finding the optimal combination of biomarkers in a personalised treatment recommendation, using randomised trial data: a regression approach that models outcome using treatment by biomarker interactions; an approach proposed by Kraemer that forms a combined measure from individual biomarker weights, calculated on all treated and control pairs; and a novel modification of Kraemer’s approach that utilises a prognostic score to sample matched treated and control subjects. Using Monte Carlo simulations under multiple data-generating models, we compare these approaches and draw conclusions based on a measure of improvement under a personalised treatment recommendation compared to a standard treatment. The three methods are applied to data from a randomised trial of home-delivered pragmatic rehabilitation versus treatment as usual for patients with chronic fatigue syndrome (the FINE trial). Prior analysis of this data indicated some treatment effect heterogeneity from multiple, correlated biomarkers. Results The regression approach outperformed Kraemer’s approach across all data-generating scenarios. The modification of Kraemer’s approach leads to improved treatment recommendations, except in the case where there was a strong unobserved prognostic biomarker. In the FINE example, the regression method indicated a weak improvement under its personalised treatment recommendation algorithm. Conclusions The method proposed by Kraemer does not perform better than a regression approach for combining multiple biomarkers. All methods are sensitive to misspecification of the parametric models.

Purpose This review provides an overview of the current challenges in oral targeted antineoplastic drug (OAD) dosing and outlines the unexploited value of therapeutic drug monitoring (TDM). Factors influencing the pharmacokinetic exposure in OAD therapy are depicted together with an overview of different TDM approaches. Finally, current evidence for TDM for all approved OADs is reviewed. Methods A comprehensive literature search (covering literature published until April 2020), including primary and secondary scientific literature on pharmacokinetics and dose individualisation strategies for OADs, together with US FDA Clinical Pharmacology and Biopharmaceutics Reviews and the Committee for Medicinal Products for Human Use European Public Assessment Reports was conducted. Results OADs are highly potent drugs, which have substantially changed treatment options for cancer patients. Nevertheless, high pharmacokinetic variability and low treatment adherence are risk factors for treatment failure. TDM is a powerful tool to individualise drug dosing, ensure drug concentrations within the therapeutic window and increase treatment success rates. After reviewing the literature for 71 approved OADs, we show that exposure-response and/or exposure-toxicity relationships have been established for the majority. Moreover, TDM has been proven to be feasible for individualised dosing of abiraterone, everolimus, imatinib, pazopanib, sunitinib and tamoxifen in prospective studies. There is a lack of experience in how to best implement TDM as part of clinical routine in OAD cancer therapy. Conclusion Sub-therapeutic concentrations and severe adverse events are current challenges in OAD treatment, which can both be addressed by the application of TDM-guided dosing, ensuring concentrations within the therapeutic window.

Broadband mid-infrared (B-MIR) thermography using fibre optic waveguides can be critical in real-time imaging in harsh environments such as additive manufacturing, personalised medical diagnosis and therapy. We investigate the polarisation effect on thermal measurements through poly-crystalline fibre bundle employing a simple broadband cross-polarisation configuration experimental set-up. Silver halide poly-crystalline fibres AgCl1−xBrx (0 ≤ x≤1) (AgClBr-PolyC) have very wide transmission bandwidth spanning over the spectral range from 1 µm up to 31 µm FWHM. Moreover, they are non-toxic, non-hygroscopic, with relatively good flexibility, which make them very adequate for spectroscopic and thermal measurements in medical and clinical fields. In this study, we used a fibre bundle composed of seven single AgClBr-PolyC fibres, each with a core diameter of about 300 µm, inserted between two broadband MIR polarisers.A silicon carbide filament source was placed at the entrance of the fibre bundle, while a FLIR thermal camera with a close-up lens was employed to measure the spatial temperature distribution over the fibre-bundle end. Indeed, polarisation dependence of temperature measurements has been clearly observed in which the orientation of temperature extrema (minima and maxima)vary from one fibre to another within the bundle. Moreover, these observations have enabled the classification of AgClBr-PolyC fibres following their polarisation sensitivities by which some fibres are relatively highly sensitive to polarisation with polarisation temperature difference (PTD) that can reach 22.1 ± 2.8 °C, whereas some others show very low PTD values down to 3.1 ± 2.8 °C. Many applications can readily be found based on the advantages of both extreme cases. © 2020, The Author(s). SM, AM, CS, JB and SAMT acknowledge European Commission Erasmus International Credit Mobility 2015–2020 between Ural Federal University named after the frst President of Russia B.N. Yeltsin, Yekaterinburg, Russia, and University of Limerick, Ireland, as well as Erasmus Bilateral Exchange between Wroclaw University of Science and Technology, Poland, and University of Limerick, Ireland, 2010–2020 for funding the work on imaging, characterisation and application development using MIR bundle fbres in medicine and manufacturing. JB acknowledges European Commission Erasmus+KA107 Inter-institutional Student and Staf Mobility Programme 2018–2020 between Wroclaw University of Science and Technology, Poland, and Ural Federal University, Yekaterinburg, Russia. SM and AM acknowledges Science Foundation Ireland (SFI) Centre for Medical Devices co-funded under the European Regional Development Fund (Grant Number 13/RC/2073) for characterising bundle fbre. EK, AK and LZ acknowledge Grant No. 18-73-10063 from the Russian Science Foundation for funding the fabrication of fbre bundles.

Background Clinical prediction models (CPMs) predict the risk of health outcomes for individual patients. The majority of existing CPMs only harness cross-sectional patient information. Incorporating repeated measurements, such as those stored in electronic health records, into CPMs may provide an opportunity to enhance their performance. However, the number and complexity of methodological approaches available could make it difficult for researchers to explore this opportunity. Our objective was to review the literature and summarise existing approaches for harnessing repeated measurements of predictor variables in CPMs, primarily to make this field more accessible for applied researchers. Methods MEDLINE, Embase and Web of Science were searched for articles reporting the development of a multivariable CPM for individual-level prediction of future binary or time-to-event outcomes and modelling repeated measurements of at least one predictor. Information was extracted on the following: the methodology used, its specific aim, reported advantages and limitations, and software available to apply the method. Results The search revealed 217 relevant articles. Seven methodological frameworks were identified: time-dependent covariate modelling, generalised estimating equations, landmark analysis, two-stage modelling, joint-modelling, trajectory classification and machine learning. Each of these frameworks satisfies at least one of three aims: to better represent the predictor-outcome relationship over time, to infer a covariate value at a pre-specified time and to account for the effect of covariate change. Conclusions The applicability of identified methods depends on the motivation for including longitudinal information and the method’s compatibility with the clinical context and available patient data, for both model development and risk estimation in practice.

Osteoarthritis (OA) is a multifactorial disease contributing to significant disability and economic burden in Western populations. The aetiology of OA remains poorly understood, but is thought to involve genetic, mechanical and environmental factors. Currently, the diagnosis of OA relies predominantly on clinical assessment and plain radiographic changes long after the disease has been initiated. Recent advances suggest that there are changes in joint fluid metabolites that are associated with OA development. If this is the case, biochemical and metabolic biomarkers of OA could help determine prognosis, monitor disease progression and identify potential therapeutic targets. Moreover, for focussed management and personalised medicine, novel biomarkers could sub-stratify patients into OA phenotypes, differentiating metabolic OA from post-traumatic, age-related and genetic OA. To date, OA biomarkers have concentrated on cytokine action and protein signalling with some progress. However, these remain to be adopted into routine clinical practice. In this review, we outline the emerging metabolic links to OA pathogenesis and how an elucidation of the metabolic changes in this condition may provide future, more descriptive biomarkers to differentiate OA subtypes.

The alarming increase in global diabetes, especially Type 2 diabetes mellitus (T2DM), is affecting diverse populations and leading to consequent burdens of morbidities, mortalities, and healthcare costs. Physical activity and nutritional approaches form the cornerstones of lifestyle T2DM prevention. Advances in understanding an individual's behaviour and biological responses to different exercise conditions are concurrent with new personalised exercise and nutritional and behavioural tools effective for preventing T2DM and associated chronic diseases. Targeted exercise and nutrition interventions can be personalised across diverse population groups and different settings. Such approaches can benefit from evolving technologies embedding genomics, metabolomics, proteomics, and transcriptomics, together with behavioural reduction strategies such as addressing sedentary behaviour. This narrative review focusses on describing personalised lifestyle prevention approaches, which address different population needs and environmental settings. These methods can be better directed towards translating T2DM interventions and laboratory trials into sustainable, healthy behaviours, and help form personalised lifestyle T2DM prevention guidelines.

Background A frequent problem in ageing patients, and thus in nursing home residents, is dysphagia, affecting the ability to swallow solid dosage forms. A promising and personalized drug delivery system for this patient group is the orodispersible film. Orodispersible films could be prepared extemporaneously in a (hospital) pharmacy setting or in specialty compounding community pharmacies using the solvent casting method. Little has been done to systematically investigate which medications should be chosen for orodispersible film formulation development. Objective In this study, the medication use of nursing home residents was examined to identify medications that are suitable for orodispersible film formulation development. Setting Nursing homes of three Northern provinces of Netherlands. Method Medication intake data from 427 nursing home residents from nine nursing homes from the three northern provinces of the Netherlands were used to identify candidates for orodispersible film formulation development. A stepwise approach, with exclusion steps, was used. Selection criteria included systemic use with a maximum amount of 100 mg per dose unit, no commercially available suitable dosage forms for administration in dysphagia, indication for diseases associated with dysphagia. Furthermore, the characteristics of the active pharmaceutical ingredient needed for the orodispersible film formulation development, such as water solubility and taste, were reviewed. Main outcome measure Active pharmaceutical ingredients suitable for orodispersible film formulation development. Results The nursing home residents used three hundred forty one different medications. Of those, 34 active pharmaceutical ingredients from six therapeutic groups were considered as candidates for orodispersible film formulation development. Most of these active pharmaceutical ingredients have a bitter taste and poor water solubility, which is a challenge for orodispersible film production. Conclusions The most suitable active pharmaceutical ingredient candidates for manufacturing of orodispersible films for the ageing patient population may be the combination of levodopa and carbidopa used to treat the symptoms of Parkinson’s disease, and baclofen used to treat spasticity.

Participants with a positive faecal immunochemical test (FIT) in screening programs for colorectal cancer (CRC) have a high risk for colorectal cancer and advanced adenomas. They are therefore recommended follow-up by colonoscopy. However, more than ten percent of positively screened persons do not adhere to this advice. To investigate FIT-positive individuals’ motives for non-adherence to colonoscopy advice in the Dutch CRC screening program. Non-adherent FIT-positive participants of the Dutch CRC screening program. We conducted semi structured in-depth interviews with 17 persons who did not undergo colonoscopy within 6 months after a positive FIT. Interviews were undertaken face-to-face and data were analysed thematically with open coding and constant comparison. All participants had multifactorial motives for non-adherence. A preference for more personalised care was described with the following themes: aversion against the design of the screening program, expectations of personalised care, emotions associated with experiences of impersonal care and a desire for counselling where options other than colonoscopy could be discussed. Furthermore, intrinsic motives were: having a perception of low risk for CRC (described by all participants), aversion and fear of colonoscopy, distrust, reluctant attitude to the treatment of cancer and cancer fatalism. Extrinsic motives were: having other health issues or priorities, practical barriers, advice from a general practitioner (GP) and financial reasons. Personalised screening counselling might have helped to improve the interviewees’ experiences with the screening program as well as their knowledge on CRC and CRC screening. Future studies should explore whether personalised screening counselling also has potential to increase adherence rates.Key pointsParticipants with a positive FIT in two-step colorectal cancer (CRC) screening programs are at high risk for colorectal cancer and advanced adenomas. Non-adherence after an unfavourable screening result happens in all CRC programs worldwide with the consequence that many of the participants do not undergo colonoscopy for the definitive assessment of the presence of colorectal cancer. Little qualitative research has been done to study the reasons why individuals participate in the first step of the screening but not in the second step. We found a preference for more personalised care, which was not reported in previous literature on this subject. Furthermore, intrinsic factors, such as a low risk perception and distrust, and extrinsic factors, such as the presence of other health issues and GP advice, may also play a role in non-adherence. A person-centred approach in the form of a screening counselling session may be beneficial for this group of CRC screening participants. Participants with a positive FIT in two-step colorectal cancer (CRC) screening programs are at high risk for colorectal cancer and advanced adenomas. Non-adherence after an unfavourable screening result happens in all CRC programs worldwide with the consequence that many of the participants do not undergo colonoscopy for the definitive assessment of the presence of colorectal cancer. Little qualitative research has been done to study the reasons why individuals participate in the first step of the screening but not in the second step. We found a preference for more personalised care, which was not reported in previous literature on this subject. Furthermore, intrinsic factors, such as a low risk perception and distrust, and extrinsic factors, such as the presence of other health issues and GP advice, may also play a role in non-adherence. A person-centred approach in the form of a screening counselling session may be beneficial for this group of CRC screening participants.

Objectives To identify, by a systematic literature review, predictors of clinical response to methotrexate treatment in rheumatoid arthritis patients, which would facilitate personalised treatment. Methods PubMed and Embase databases were searched for original articles. Additionally, congress abstracts of European League Against Rheumatism and American College of Rheumatology annual meetings of the past 2 years were screened. Articles describing predictors of clinical response to methotrexate after 3 to 6 months were included, since this reflects the time span used to determine treatment effectiveness and decide on treatment changes in treat-to-target recommendations. Results Thirty articles were included, containing 100 different predictors and 11 predictive models. Nineteen predictors and 2 predictive models were studied in multiple cohorts. Female gender was found to be a predictor of non-response in two studies (odds ratios 0.55 and 0.54), but these findings could not be replicated in two other studies. In two studies, smoking predicted non-response (adjusted odds ratios 0.35 and 0.60), although this was inconsistent over all response criteria assessed. Rheumatoid factor positivity predicted non-response in two studies (adjusted hazard ratio 0.61, adjusted odds ratio 0.4), but this was not found in three other studies. Heterogeneity in studies prohibited further comparison of predictive values between studies. Additionally, a validated epigenetic model was found (area under the curve 0.90 and 0.91). Conclusions No predictors were identified reliably predicting clinical response to methotrexate after 3 to 6 months in the individual patient: clinical predictors were weak. However, a promising epigenetic model was found that needs further validation.

The human microbiome can play key roles in disease, and diagnostic testing will soon have the ability to examine these roles in the context of clinical applications. Currently, most diagnostic testing in pathology applications focuses on a small number of disease‐causing microbes and dismisses the whole microbial community that causes or is modulated by disease. Microbiome modifications have already provided clinically relevant insights in gut and oral diseases, such as irritable bowel disease, but there are currently limitations when clinically examining microbiomes outside of these body sites. This is critical, as the majority of microbial samples used in pathology originate from body sites that contain low concentrations of microbial DNA, including skin, tissue, blood, and urine. These samples, also known as low microbial biomass samples, are difficult to examine without careful consideration and precautions to mitigate contamination and biases. Here, we present the limitations when analysing low microbial biomass samples using current protocols and techniques and highlight the advantages that microbiome testing can offer diagnostics in the future, if the proper precautions are implemented. Specifically, we discuss the sources of contamination and biases that may result in false assessments for these sample types. Finally, we provide recommendations to mitigate contamination and biases from low microbial biomass samples during diagnostic testing, which will be especially important to effectively diagnose and treat patients using microbiome analyses.

Over 90% of potential anti-cancer drug candidates results in translational failures in clinical trials. The main reason for this failure can be attributed to the non-accurate pre-clinical models that are being currently used for drug development and in personalised therapies. To ensure that the assessment of drug efficacy and their mechanism of action have clinical translatability, the complexity of the tumor microenvironment needs to be properly modelled. 3D culture models are emerging as a powerful research tool that recapitulatesin vivocharacteristics. Technological advancements in this field show promising application in improving drug discovery, pre-clinical validation, and precision medicine. In this review, we discuss the significance of the tumor microenvironment and its impact on therapy success, the current developments of 3D culture, and the opportunities that advancements thatin vitrotechnologies can provide to improve cancer therapeutics.

Immunosuppressive therapy is pivotal for sustained allograft and patient survival after renal transplantation. However, optimally balanced immunosuppressive therapy is challenged by between-patient and within-patient pharmacokinetic (PK) variability. This could warrant the application of personalised dosing strategies to optimise individual patient outcomes. Pharmacometrics, the science that investigates the xenobiotic-biotic interplay using computer-aided mathematical modelling, provides options to describe and quantify this PK variability and enables identification of patient characteristics affecting immunosuppressant PK and treatment outcomes. Here, we review and critically appraise the available pharmacometric model-informed dosing solutions for the typical immunosuppressants in modern renal transplantation, to guide their initial and subsequent dosing.

Background: Asthma is a heterogeneous disease with poorly defined phenotypes. Aim: To identify metabolic dysregulations associated with asthma severity and evaluate the effects of asthma medication upon observed metabotypes. Methods: Baseline urine was collected from healthy controls (HC, n=108), mild-to-moderate asthmatics (MMA, n=87) and severe asthmatics (SA, n=418) from the U-BIOPRED cohort. 12-18 month longitudinal samples were collected from the SA cohort (n=305). Metabolomic data were acquired using mass spectrometry and analyzed using multivariate statistics. Gene set variation analysis (GSVA) was performed on bronchial brushing transcriptomic data. Results: 90 metabolites were identified with 40 altered in asthma (FDR

Simple Summary Mucinous ovarian cancer (MOC) is a rare type of epithelial ovarian cancer, and current treatment regimens for late stage and recurrent disease are inadequate. The ‘gold standard’ treatments are based on large clinical trials that evaluated potential therapies for all ovarian cancer, but MOC was poorly represented in these studies. As such, what works for most cases may not work for MOC. In this review, we discuss the advances in MOC treatment and explore the concept of theranostics—using therapeutic and diagnostic radionuclides against single cell surface receptors expressed highly in MOC. Additionally, we highlight the previous literature that demonstrates the overexpression of certain targets, exploring their potential to be used as theranostic targets. Abstract MOC is a rare histotype of epithelial ovarian cancer, and current management options are inadequate for the treatment of late stage or recurrent disease. A shift towards personalised medicines in ovarian cancer is being observed, with trials targeting specific molecular pathways, however, MOC lags due to its rarity. Theranostics is a rapidly evolving category of personalised medicine, encompassing both a diagnostic and therapeutic approach by recognising targets that are expressed highly in tumour tissue in order to deliver a therapeutic payload. The present review evaluates the protein landscape of MOC in recent immunohistochemical- and proteomic-based research, aiming to identify potential candidates for theranostic application. Fourteen proteins were selected based on cell membrane localisation: HER2, EGFR, FOLR1, RAC1, GPR158, CEACAM6, MUC16, PD-L1, NHE1, CEACAM5, MUC1, ACE2, GP2, and PTPRH. Optimal proteins to target using theranostic agents must exhibit high membrane expression on cancerous tissue with low expression on healthy tissue to afford improved disease outcomes with minimal off-target effects and toxicities. We provide guidelines to consider in the selection of a theranostic target for MOC and suggest future directions in evaluating the results of this review.

Personalised medicine, in which clinical management is individualised to the genotypic and phenotypic data of patients, offers a promising means by which to enhance outcomes in the management of mycobacterial pulmonary infections. In this review, we provide an overview of how personalised medicine approaches may be utilised to identify patients at risk of developing tuberculosis (TB) or non-tuberculous mycobacterial pulmonary disease (NTM-PD), diagnose these conditions and guide effective treatment strategies. Despite recent technological and therapeutic advances, TB and NTM-PD remain challenging conditions to diagnose and treat. Studies have identified a range of genetic and immune factors that predispose patients to pulmonary mycobacterial infections. Molecular tests such as nucleic acid amplification assays and next generation sequencing provide a rapid means by which to identify mycobacterial isolates and their antibiotic resistance profiles, thus guiding selection of appropriate antimicrobials. Host-directed therapies and therapeutic drug monitoring offer ways of tailoring management to the clinical needs of patients at an individualised level. Biomarkers may hold promise in differentiating between latent and active TB, as well as in predicting mycobacterial disease progression and response to treatment.

Breast cancer is the most common malignancy diagnosed in women. Traditionally, radical surgical resection was the cornerstone of breast cancer management, with limited exceptions. In recent times, our enhanced appreciation of the biomolecular characteristics of breast cancer has transformed the treatment paradigm to include prescription of chemotherapeutical agents, radiotherapies, targeted therapies, as well as more refined surgical approaches. While treatments with such modalities have enhanced clinico-oncological outcomes for breast cancer patients, the efforts of oncological and translational research have concentrated on the identification of novel biomarkers which may successfully inform prognosis and response to therapies, improve current therapeutic strategies, and enhance prognostication. Mi(cro)RNAs are small, non-coding molecules which are known to play regulatory roles in governing gene expression and cellular activity. Measurement of miRNA expression profiles have been illustrated to inform the response to therapies, such as conventional chemotherapy, and are currently undergoing assessment as means of enhancing treatment strategies with these cytotoxic agents. Herein, this review outlines how chemotherapy prescription has revolutionised breast cancer treatment and illustrates the novel role of miRNAs as biomarkers capable of enhancing current therapeutic strategies using chemotherapy in patients being treated with curative intent for breast cancer.

Attention deficit hyperactivity disorder, or ADHD, is a common childhood disorder with a prevalence rate of 5–10%. There have been many theories proposed to explain ADHD, and one of them focuses on the deficiency of essential fatty acids (EFA), particularly omega-3 polyunsaturated fatty acids (n-3 PUFAs) including docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). Studies have shown that there is a positive correlation between EFA deficiency severity and ADHD symptoms, and a negative association between blood PUFAs levels and ADHD symptoms. Moreover, clinical studies have shown a promising effect of n-3 PUFAs in the treatment of both clinical and cognitive symptoms in children with ADHD. In addition, with the more relatively safe and tolerable properties of n-3 PUFAs when comparing with the standard pharmacotherapy, n-3 PUFAs may be a potential treatment option for children with ADHD. Of note, the association between n-3 PUFAs deficiency and ADHD has been suggested to involve several biological systems, including inflammation, dysregulation of the hypothalamus-pituitary-adrenal (HPA) axis and the autonomic nervous system (ANS), and an imbalanced gut-microbiota axis (GBA). Thus, the biomarkers from these biological systems may serve as possible treatment response predictors of n-3 PUFAs in children with ADHD., Highlights • Children with ADHD have lower levels of DHA, EPA and total n-3 PUFAs •N-3 PUFAs improved clinical and cognitive symptoms in children with ADHD •Inflammatory status and endogenous n-3 PUFAs levels may serve as treatment response predictors •N-3 PUFAs may be a treatment option for a subgroup of children with ADHD

The tumour-stroma ratio (TSR) and tumour budding (TB) are two high-risk factors with potential to be implemented in the next TNM classification. The aim of the current study was to evaluate the practical application of the two biomarkers based on reproducibility, independency and prognostic value. Patients diagnosed with stage II or III colon cancer who underwent surgery between 2005 and 2016 were included. Both TSR and TB were scored on haematoxylin and eosin-stained tissue sections. The TSR, based on the relative amount of stroma, was scored in increments of 10%. TB was scored following the consensus guidelines; a bud was defined as ≤ 4 tumour cells. For analysis, three categories were used. Cohen’s kappa was used for reproducibility. The prognostic value was determined with survival analysis. In total, 246 patients were included. The TSR distribution was N = 137 (56%) stroma-low and N = 109 (44%) stroma-high. The TB distribution was TB-low N = 194 (79%), TB-intermediate N = 35 (14%) and TB-high N = 17 (7%). The reproducibility of the TSR was good (interobserver agreement kappa = 0.83 and intraobserver agreement kappa = 0.82), whereas the inter- and intraobserver agreement for scoring TB was moderate (kappa 0.47 and 0.45, respectively). The survival analysis showed an independent prognostic value for disease-free survival for TSR (HR 1.57; 95% CI 1.01–2.44; p = 0.048) and for TB-high (HR 2.01; 95% CI 1.02–3.96; p = 0.043). Based on current results, we suggest the TSR is a more reliable parameter in daily practice due to better reproducibility and independent prognostic value for disease-free survival.

Simple Summary In breast cancer development, the expression of Ki-67 is strongly associated with cancer proliferation and is a known indicator of prognosis and outcome. Ki-67 expression levels are also useful to inform treatment decision making in some cases. As a result, routine measurement of Ki-67 is now widely performed during pathological tumour evaluation. However, the Ki-67 appraisal is not without its limitations and shortcomings—the aim of this study was to provide an overview of Ki-67 use in the clinical setting, the current challenges associated with its measurement, and the novel strategies that will hopefully enhance Ki-67 proliferation indices for prospective breast cancer patients. Abstract The advent of molecular medicine has transformed breast cancer management. Breast cancer is now recognised as a heterogenous disease with varied morphology, molecular features, tumour behaviour, and response to therapeutic strategies. These parameters are underpinned by a combination of genomic and immunohistochemical tumour factors, with estrogen receptor (ER) status, progesterone receptor (PgR) status, human epidermal growth factor receptor-2 (HER2) status, Ki-67 proliferation indices, and multigene panels all playing a contributive role in the substratification, prognostication and personalization of treatment modalities for each case. The expression of Ki-67 is strongly linked to tumour cell proliferation and growth and is routinely evaluated as a proliferation marker. This review will discuss the clinical utility, current pitfalls, and promising strategies to augment Ki-67 proliferation indices in future breast oncology.

Purpose of review \ud \ud Amyotrophic lateral sclerosis (ALS) is an archetypal complex disease wherein disease risk and severity are, for the majority of patients, the product of interaction between multiple genetic and environmental factors. We are in a period of unprecedented discovery with new large-scale genome-wide association study (GWAS) and accelerating discovery of risk genes. However, much of the observed heritability of ALS is undiscovered and we are not yet approaching elucidation of the total genetic architecture, which will be necessary for comprehensive disease subclassification.\ud \ud \ud \ud Recent findings \ud \ud We summarize recent developments and discuss the future. New machine learning models will help to address nonlinear genetic interactions. Statistical power for genetic discovery may be boosted by reducing the search-space using cell-specific epigenetic profiles and expanding our scope to include genetically correlated phenotypes. Structural variation, somatic heterogeneity and consideration of environmental modifiers represent significant challenges which will require integration of multiple technologies and a multidisciplinary approach, including clinicians, geneticists and pathologists.\ud \ud \ud \ud Summary \ud \ud The move away from fully penetrant Mendelian risk genes necessitates new experimental designs and new standards for validation. The challenges are significant, but the potential reward for successful disease subclassification is large-scale and effective personalized medicine.

Made available in DSpace on 2022-04-29T08:33:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-03-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Mammary tumours (MT) are one of the most prevalent malignancies in female dogs and women. Currently, molecular analyzes have shown that each tumour type presents its own genetic signature. In this context, liquid biopsy allows a comprehensive genetic characterisation of the tumour, enabling early diagnosis and personalised treatment of patients. In women, deleterious mutations inherited in BRCA2 gene are associated with an increased risk of breast cancer, resistance to therapies and worse prognosis. In female dogs, there are many divergent data on the involvement of BRCA2 gene with mammary carcinogenesis and what its pathogenic potential is. Therefore, the objective was to identify BRCA2 gene variants in 20 plasma DNA samples, from 10 newly diagnosed dogs with mammary cancer (RD), five control (CTR) and five mastectomized patients. Eleven single nucleotide polymorphisms (SNPs) were detected, most of them in the exon 11 and two indels (deletion/insertion) in the BRCA2 gene. However, there was no statistically significant difference in the SNPs/indels detected between the groups. In addition, only one SNP (p.T1425P) and one deletion (p.L2307del) were considered deleterious using in silico computational models. Interestingly, most common variants were present in the plasma of all groups, except for the Ile2614Thr, Ile2614Val, Thr1425Pro and p.L2307del variants. Thus, we observed that SNPs are common in the BRCA2 gene of female dogs with MT, with a similar condition identified in women with breast cancer. Liquid biopsy approach in dogs with MT is useful for genetic and therapeutic proposals. Department of Veterinary Clinic and Surgery School of Agricultural and Veterinarian Sciences Univ. Estadual Paulista Jaboticabal Department of Molecular Biology Cancer Molecular Research Laboratory (LIMC) FAMERP Department of Molecular Biology Molecular Markers and Bioinformatics Laboratory FAMERP Department of Anatomy-IBB/UNESP Institute of Biosciences of Botucatu Univ. Estadual Paulista Botucatu Luiz de Queiroz College of Agriculture (ESALQ) University of São Paulo Piracicaba Department of Molecular Biology FAMERP Collaborator in Program of Post-Graduate in Genetics UNESP/IBILCE Department of Veterinary Clinic and Surgery School of Agricultural and Veterinarian Sciences Univ. Estadual Paulista Jaboticabal Department of Anatomy-IBB/UNESP Institute of Biosciences of Botucatu Univ. Estadual Paulista Botucatu Collaborator in Program of Post-Graduate in Genetics UNESP/IBILCE FAPESP: 2017/15006-5

Background: Myocardial bridging is largely considered to be a benign, symptomless congenital anomaly of the coronary arteries in which the intramyocardial coronary course is partially 'tunnelled' and leads to vessel compression during ventricular systole. There are few data regarding children.Objective: To report on myocardial bridging observed in children seeking medical help in the paediatric emergency room.Case presentation: A series of four children aged 6-13 years with symptomatic myocardial bridging but no other underlying cardiac abnormalities is reported. They were admitted to the paediatric emergency department during 2013-2016, three with chest pain after physical activity and one with septic shock.Results: Heart computed tomography scan in the first three demonstrated myocardial bridging of the left anterior descendent coronary artery's branches; their 2-year follow-up was uneventful. The fourth patient presented with ventricular fibrillation 24 hours after admission and at autopsy there was an intramyocardial tract 4 cm long on the left anterior descendent coronary artery.Conclusions: This case series demonstrates that myocardial bridging can be symptomatic in children with no underlying cardiac disorders and should be included in the differential diagnosis of exertional chest pain and/or arrhythmias.Abbreviations: CRP, C-reactive protein; CT, computed tomography; D1, diagonal 1 artery; ECG, electrocardiogram; ED, emergency department; KD, Kawasaki disease; LAD, left anterior descending coronary artery; MB, myocardial bridging; RI, ramus intermedius artery; TN, troponin.

In the past decade, the emergence of machine learning (ML) applications has led to significant advances towards implementation of personalised medicine approaches for improved health care, due to the exceptional performance of ML models when utilising complex big data. The immune-mediated chronic inflammatory diseases are a group of complex disorders associated with dysregulated immune responses resulting in inflammation affecting various organs and systems. The heterogeneous nature of these diseases poses great challenges for tailored disease management and addressing unmet patient needs. Applying novel ML techniques to the clinical study of chronic inflammatory diseases shows promising results and great potential for precision medicine applications in clinical research and practice. In this review, we highlight the clinical applications of various ML techniques for prediction, diagnosis and prognosis of autoimmune rheumatic diseases, inflammatory bowel disease, autoimmune chronic kidney disease, and multiple sclerosis, as well as ML applications for patient stratification and treatment selection. We highlight the use of ML in drug development, including target identification, validation and drug repurposing, as well as challenges related to data interpretation and validation, and ethical concerns related to the use of artificial intelligence in clinical research.

(1) Background: Genomic precision medicine (PM) utilises people’s genomic data to inform the delivery of preventive and therapeutic health care. PM has not been well-established for use with people of Aboriginal and Torres Strait Islander ancestry due to the paucity of genomic data from these communities. We report the development of a new protocol using co-design methods to enhance the potential use of PM for Aboriginal Australians. (2) Methods: This iterative qualitative study consists of five main phases. Phase-I will ensure appropriate governance of the project and establishment of a Project Advisory Committee. Following an initial consultation with the Aboriginal community, Phase-II will invite community members to participate in co-design workshops. In Phase-III, the Chief Investigators will participate in co-design workshops and document generated ideas. The notes shall be analysed thematically in Phase-IV with Aboriginal community representatives, and the summary will be disseminated to the communities. In Phase-V, we will evaluate the co-design process and adapt our protocol for the use in partnership with other communities. (3) Discussion: This study protocol represents a crucial first step to ensure that PM research is relevant and acceptable to Aboriginal Australians. Without fair access to PM, the gap in health outcome between Aboriginal and non-Aboriginal Australians will continue to widen.

Over the last few decades, endoscopic ultrasound (EUS)-guided tissue acquisition has become the method of choice for the pathological diagnosis of solid pancreatic lesions. Due to its high diagnostic yield and low complication rate, EUS-guided tissue acquisition has surpassed percutaneous sampling techniques. For many years, EUS-guided fine-needle aspiration (EUS-FNA) was traditionally used to obtain cytological aspirates of solid pancreatic lesions, with sensitivity values ranging from 80 to 90% for the diagnosis of malignancy. Nevertheless, despite numerous technical advances, EUS-FNA still presents some limitations. Therefore, EUS-guided fine-needle biopsy (EUS-FNB) has been introduced to provide tissue core biopsies, allowing histological assessment. A newly developed generation of FNB needles has demonstrated an outstanding diagnostic accuracy of over 95% for solid pancreatic lesions and provides samples appropriate for ancillary testing, such as immunohistochemistry and tumour molecular profiling. As a result, EUS-FNB is rapidly replacing EUS-FNA and is now the recommended technique for EUS-guided tissue acquisition in pancreatic cancer. Furthermore, with the recent expansion of neoadjuvant treatment criteria and with the advent of novel and personalised anti-cancer therapies, EUS-FNB is gaining a pivotal role in pancreatic cancer management and might soon be generalised to all patients, independent of disease stage. In this article, the authors present an updated review of the role of EUS-guided tissue acquisition in pancreatic cancer. Current indications, several technical aspects and new applications of EUS-FNA and EUS-FNB are discussed., SCOPUS: re.j, info:eu-repo/semantics/published

Levothyroxine (LT4) therapy has a long history, a well-defined pharmacological profile and a favourable safety record in the alleviation of hypothyroidism. However, questions remain in defining the threshold for the requirement of treatment in patients with subclinical hypothyroidism, assessing the dose adequacy of the drug, and selecting the best treatment mode (LT4 monotherapy versus liothyronine [LT3]/LT4 combinations) for subpopulations with persisting complaints. Supplied as a prodrug, LT4 is enzymatically converted into the biologically more active thyroid hormone, triiodothyronine (T3). Importantly, tetraiodothyronine (T4) to T3 conversion efficiency may be impaired in patients receiving LT4, resulting in a loss of thyroid-stimulating hormone (TSH)-mediated feed-forward control of T3, alteration of the interlocking equilibria between serum concentrations of TSH, free thyroxine (FT4), and free triiodothyonine (FT3), and a decrease in FT3 to FT4 ratios. This downgrades the value of the TSH reference system derived in thyroid health for guiding the replacement dose in the treatment situation. Individualised conditionally defined setpoints may therefore provide appropriate biochemical targets to be clinically tested, together with a stronger focus on clinical presentation and future endpoint markers of tissue thyroid state. This cautionary note encompasses the use of aggregated statistical data from clinical trials which are not safely applicable to the individual level of patient care under these circumstances.

Inborn errors of metabolism cause disease because of accumulation of a metabolite before the blocked step or deficiency of an essential metabolite downstream of the block. Treatments can be directed at reducing the levels of a toxic metabolite or correcting a metabolite deficiency. Many disorders have been treated successfully first in a single patient because we can measure the metabolites and adjust treatment to get them as close as possible to the normal range. Examples are drawn from Komrower's description of treatment of homocystinuria and the author's trials of treatment in bile acid synthesis disorders (3β‐hydroxy‐Δ5‐C27‐steroid dehydrogenase deficiency and Δ4‐3‐oxosteroid 5β‐reductase deficiency), neurotransmitter amine disorders (aromatic L‐amino acid decarboxylase [AADC] and tyrosine hydroxylase deficiencies), and vitamin B6 disorders (pyridox(am)ine phosphate oxidase deficiency and pyridoxine‐dependent epilepsy [ALDH7A1 deficiency]). Sometimes follow‐up shows there are milder and more severe forms of the disease and even variable clinical manifestations but by measuring the metabolites we can adjust the treatment to get the metabolites into the normal range. Biochemical measurements are not subject to placebo effects and will also show if the disorder is improving spontaneously. The hypothesis that can then be tested for clinical outcome is whether getting metabolite(s) into a target range leads to an improvement in an outcome parameter such as abnormal liver function tests, hypokinesia, epilepsy control etc. The metabolite‐guided approach to treatment is an example of personalized medicine and is a better way of determining efficacy for disorders of variable severity than a randomized controlled clinical trial.

Multidrug-resistant TB (MDR-TB) is a major threat to global health security. In 2017, only 50% of patients with MDR-TB who received WHO-recommended treatment were cured. Most MDR-TB patients who recover continue to suffer from functional disability due to long-term lung damage. Whilst new MDR-TB treatment regimens are becoming available, conventional drug therapies need to be complemented with host-directed therapies (HDTs) to reduce tissue damage and improve functional treatment outcomes. This viewpoint highlights recent data on biomarkers, immune cells, circulating effector molecules and genetics which could be utilised for developing personalised HDTs. Novel technologies currently used for cancer therapy which could facilitate in-depth understanding of host genetics and the microbiome in patients with MDR-TB are discussed. Against this background, personalised cell-based HDTs for adjunct MDR-TB treatment to improve clinical outcomes are proposed as a possibility for complementing standard therapy and other HDT agents. Insights into the molecular biology of the mechanisms of action of cellular HDTs may also aid to devise non-cell-based therapies targeting defined inflammatory pathway (s) in Mtb-driven immunopathology. (c) 2019 Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Regenerative medicine is an exciting field of research, in which significant steps are being taken that are leading to the translation of the technique into clinical practice. In the near future, it is expected that clinicians will have the opportunity to bioprint tissues and organs that closely mimic native human tissues. To do so, imaging of patients must be translated to digital models and then fabricated in a layer-by-layer fashion. The main aim of this review is to elaborate on the possible mechanisms that support four-dimensional bioprinting, as well as provide examples of current and future applications of the technology. This technology, considering time as the fourth dimension, emerged with the aim to develop bioactive functional constructs with programmed stimuli responses. The main idea is to have three-dimensional-printed constructs that are responsive to preplanned stimuli. With this review, the authors aim to provoke creative thinking, highlighting several issues that need to be addressed when reproducing such a complex network as the human body. The authors envision that there are some key features that need to be studied in the near future: printed constructs should be able to respond to different types of stimuli in a timely manner, bioreactors must be developed combining different types of automated stimuli and aiming to replicate the in vivo ecology, and adequate testing procedures must be developed to obtain a proper assessment of the constructs. The effective development of a printed construct that supports tissue maturation according to the anticipated stimuli will significantly advance this promising approach to regenerative medicine. info:eu-repo/semantics/publishedVersion

Risk prediction modelling is important to better understand the determinants of the course and outcome of PBC and to inform the risk across the disease continuum in PBC enabling risk-stratified follow-up care and personalised therapy. Current prognostic models in PBC are based on treatment response to ursodeoxycholic acid because of the well-established relationship between alkaline phosphatase on treatment and long-term outcome. In addition, serum alkaline phosphatase correlates with ductular reaction and biliary metaplasia, which are hallmark of biliary injury. Considering the waiting time for treatment failure in high-risk patients is not inconsequential, efforts are focused on bringing forward risk stratification at diagnosis by predicting treatment response at onset. There is a need for better prognostic variables that are central to the disease process. We should take an integrative approach that incorporates multiple layers of information including genetic and environmental influences, host characteristics, clinical data, and molecular alterations for risk assessments. Biomarker discovery has an accelerated pace taking advantage of the emergence of large-scale omics platforms (genomics, epigenomics, transcriptomics, proteomics, metabolomics, and others) and whole-genome sequencing. In the digital era, applications of artificial intelligence, such as machine learning, can support the computing power required to analyse the vast amount of data produced by omics. The information is then used for the development of personalised risk prediction models that through clinical trials and hopefully industry partnerships can guide risk management strategies. We are facing an unprecedented opportunity for the integration of molecular diagnostics into the clinic, which promotes progress toward the personalised management of patients with PBC.

Background Human epidermal growth factor receptor-2 (HER2) is overexpressed in 20–25% of breast cancers. Complete eradication of disease following neoadjuvant therapies and chemotherapy has been referred to as pathological complete response (pCR). Aims To determine clinicopathological predictors of pCR to neoadjuvant therapies and to evaluate pCR as a surrogate to enhanced survival. Methods Consecutive female patients with HER2 positive (HER+) breast cancer managed surgically in a single institution between 2005 and 2015 were included. Descriptive statistics and binary logistic regression were used to determine predictors of pCR. Appraisal of pCR as a predictor of survival was performed using Kaplan-Meier curves and Cox regression analysis. Results 451 patients were included with a mean age of 56.6 ± 13.4 years (range 23–95). Disease-free (DFS) and overall survival (OS) was 82.3% (371/451) and 82.6% (376/451) respectively with a median follow-up of 108.0 months (range 3–184.0). 118 were treated in the neoadjuvant setting (26.2%): tumour size, Highlights • Clinicopathological data predict patients who achieve pCR in HER2+ breast cancer. • pCR is a sensitive biomarker of survival in HER2 positive breast cancer. • Patients achieving pCR have reduced risk of breast cancer recurrence and mortality. • pCR can aid patient prognostication in the era of personalised medicine.

Current practice in IBD is to classify patients based on clinical signs and symptoms and provide treatments accordingly. However, the response of IBD patients to available treatments is highly variable, highlighting clinically significant heterogeneity among patients. Thus, more accurate patient stratification is urgently needed to more effectively target therapeutic interventions to specific patients. Here we review the degree of heterogeneity in IBD, discussing how the microbiota, genetics, and immune system may contribute to the variation among patients. We highlight how molecular heterogeneity may relate to clinical phenotype, but in other situations may be independent of clinical phenotype, encouraging future studies to fill the gaps. Finally, we discuss novel stratification methodologies as a foundation for precision medicine, in particular a novel stratification strategy based on conserved genes across species. All of these dimensions of heterogeneity have potential to provide strategies for patient stratification and move IBD practice towards personalised medicine.

Background Type 2 diabetes is a syndrome defined by hyperglycaemia that is the result of various degrees of pancreatic β-cell failure and reduced insulin sensitivity. Although diabetes can be caused by multiple metabolic dysfunctions, most patients are defined as having either type 1 or type 2 diabetes. Recently, Ahlqvist and colleagues proposed a new method of classifying patients with adult-onset diabetes, considering the heterogenous metabolic phenotype of the disease. This new classification system could be useful for more personalised treatment based on the underlying metabolic disruption of the disease, although to date no prospective intervention studies have generated data to support such a claim. Scope of Review In this review, we first provide a short overview of the phenotype and pathogenesis of type 2 diabetes and discuss the current and new classification systems. We then review the effects of different anti-diabetic medication classes on insulin sensitivity and β-cell function and discuss future treatment strategies based on the subgroups proposed by Ahlqvist et al. Major Conclusions The proposed novel type 2 diabetes subgroups provide an interesting concept that could lead to a better understanding of the pathophysiology of the broad group of type 2 diabetes, paving the way for personalised treatment choices based on understanding the root cause of the disease. We conclude that the novel subgroups of adult-onset diabetes would benefit from anti-diabetic medications that take into account the main pathophysiology of the disease and thereby prevent end-organ damage. However, we are only beginning to address the personalised treatment of type 2 diabetes, and studies investigating the effects of current and novel drugs in subgroups with different metabolic phenotypes are needed to develop personalised treatment of the syndrome, Highlights • Novel subgroups of type 2 diabetes provide a concept that could lead to a better understanding of its pathophysiology. • Treatment strategies would benefit from anti-diabetic medications that influence the main pathophysiology of diabetes. • Here, we review different anti-diabetic medications classes affecting insulin sensitivity and β-cell function. • We suggest that future treatment strategies could benefit by taking into account subgroups provided by Ahlqvist et al.

Introduction: Oncologists have traditionally administered the maximum tolerated doses of drugs in chemotherapy. However, these toxicity-guided doses may lead to suboptimal efficacy. CURATE.AI is an indication-agnostic, mechanism-independent and efficacy-driven personalised dosing platform that may offer a more optimal solution. While CURATE.AI has already been applied in a variety of clinical settings, there are no prior randomised controlled trials (RCTs) on CURATE.AI-guided chemotherapy dosing for solid tumours. Therefore, we aim to assess the technical and logistical feasibility of a future RCT for CURATE.AI-guided solid tumour chemotherapy dosing. We will also collect exploratory data on efficacy and toxicity, which will inform RCT power calculations.Methods and analysis: This is an open-label, single-arm, two-centre, prospective pilot clinical trial, recruiting adults with metastatic solid tumours and raised baseline tumour marker levels who are planned for palliative-intent, capecitabine-based chemotherapy. As CURATE.AI is a small data platform, it will guide drug dosing for each participant based only on their own tumour marker levels and drug doses as input data. The primary outcome is the proportion of participants in whom CURATE.AI is successfully applied to provide efficacy-driven personalised dosing, as judged based on predefined considerations. Secondary outcomes include the timeliness of dose recommendations, participant and physician adherence to CURATE.AI-recommended doses, and the proportion of clinically significant dose changes. We aim to initially enrol 10 participants from two hospitals in Singapore, perform an interim analysis, and consider either cohort expansion or an RCT. Recruitment began in August 2020. This pilot clinical trial will provide key data for a future RCT of CURATE.AI-guided personalised dosing for precision oncology.Ethics and dissemination: The National Healthcare Group (NHG) Domain Specific Review Board has granted ethical approval for this study (DSRB 2020/00334). We will distribute our findings at scientific conferences and publish them in peer-reviewed journals.Trial registration number: NCT04522284

Background Every two years, German-speaking dermatologic specialist groups gather in Berlin to share the latest developments at Germanýs largest dermatologic conference, the Annual Meeting of the Germany Society of Dermatology (DDG). Because this conference has a lasting effect on dermatologic practice and research, understanding what is moving the specialist groups means understanding what is driving dermatology in Germany. Methods We used word network analysis to compile and visualize the information embedded in the contribution titles to the DDG Annual Meeting in 2019. We extracted words, contributing cities and inter-connections. The data was standardized, visualized using network graphs and analyzed using common network analysis parameters. Results A total of 5509 words were extracted from 1150 contribution titles. The most frequently used words were “therapy”, “patients”, and “psoriasis”. The highest number of contributions came from Hamburg, Berlin and Munich. High diversity in research topics was found, as well as a well-connected research network. Conclusions Focus of the well-connected German-speaking dermatology community meeting 2019 was patient and therapy centered and lies especially on the diseases psoriasis and melanoma. Network graph analysis can provide helpful insights and help planning future congresses. It can facilitate the choice which contributors to include as imbalances become apparent. Moreover, it can help distributing the topics more evenly across the whole dermatologic spectrum.

Pharmaceutical applications of 3D printing technologies are growing rapidly. Among these, vat photopolymerisation (VP) techniques, including Stereolithography (SLA) hold much promise for their potential to deliver personalised medicines on-demand. SLA 3D printing offers advantageous features for pharmaceutical production, such as operating at room temperature and offering an unrivaled printing resolution. However, since conventional SLA apparatus are designed to operate with large volumes of a single photopolymer resin, significant throughput limitations remain. This, coupled with the limited choice of biocompatible polymers and photoinitiators available, hold back the pharmaceutical development using such technologies. Hence, the aim of this work was to develop a novel SLA apparatus specifically designed to allow rapid and efficient screening of pharmaceutical photopolymer formulations. A commercially available SLA apparatus was modified by designing and fabricating a novel resin tank and build platform able to 3D print up to 12 different formulations at a single time, reducing the amount of sample resin required by 20-fold. The novel SLA apparatus was subsequently used to conduct a high throughput screening of 156 placebo photopolymer formulations. The efficiency of the equipment and formulation printability outcomes were evaluated. Improved time and cost efficiency by 91.66% and 94.99%, respectively, has been confirmed using the modified SLA apparatus to deliver high quality, highly printable outputs, thus evidencing that such modifications offer a robust and reliable tool to optimize the throughput and efficiency of vat photopolymerisation techniques in formulation development processes, which can, in turn, support future clinical applications.

Diabetic foot ulcers (DFUs) are a life-changing complication of diabetes that can lead to amputation. There is increasing evidence that long-term management with wearables can reduce incidence and recurrence of this condition. Temperature asymmetry measurements can alert to DFU development, but measurements of dynamic information, such as rate of temperature change, are under investigated. We present a new wearable device for temperature monitoring at the foot that is personalised to account for anatomical variations at the foot. We validate this device on 13 participants with diabetes (no neuropathy) (group name D) and 12 control participants (group name C), during sitting and standing. We extract dynamic temperature parameters from four sites on each foot to compare the rate of temperature change. During sitting the time constant of temperature rise after shoe donning was significantly (p &lt, 0.05) faster at the hallux (p = 0.032, 370.4 s (C), 279.1 s (D)) and 5th metatarsal head (p = 0.011, 481.9 s (C), 356.6 s (D)) in participants with diabetes compared to controls. No significant differences at the other sites or during standing were identified. These results suggest that temperature rise time is faster at parts of the foot in those who have developed diabetes. Elevated temperatures are known to be a risk factor of DFUs and measurement of time constants may provide information on their development. This work suggests that temperature rise time measured at the plantar surface may be an indicative biomarker for differences in soft tissue biomechanics and vascularisation during diabetes onset and progression.

International audience; The additive technology or 2D and 3D printing are increasingly used in various industrial fields, from aeronautics to mechanics but also in the fields of health such as dentistry or for bone reconstructions. These techniques have been studied for about fifteen years by the academic community in the pharmaceutical field (medical device and drug), and recently they have started to be applied to produce drugs in industry and in hospitals. Indeed, the Food and Drug Administration approved in August 2015 the marketing of the first drug printed by additive technique, then in 2018 the first clinical trial using 3D printed drugs was carried out in Great Britain by a hospital pharmacy. 2D-3D printing is presented as one of the tools of a more personalized medicine, the techniques of additive printing allowing the production of tabs containing several drugs in one tab (polypills) and the development of custom modified-releases drugs. This approach could allow better acceptance of the finished product and secure manufacturing. The objective of this work is to highlight relevant printing technologies for implementation in hospital pharmacies, and to see how these technologies could lead to a change in pharmaceutical practices, to improve patient care.

Gastrointestinal side effects (SEs) are frequently observed in patients with major depressive disorder (MDD) while taking antidepressants and may lead to treatment discontinuation. The aim of this meta-analysis is to provide quantitative measures on short-term rates of gastrointestinal SEs in MDD patients treated with second-generation antidepressants. An electronic search of the literature was conducted by using MEDLINE, ISI Web of Science – Web of Science Core Collection, and Cochrane Library databases. Eligible studies had to focus on the use of at least one of 15 antidepressants commonly used in MDD (i.e., agomelatine, bupropion, citalopram, desvenlafaxine, duloxetine, escitalopram, fluoxetine, fluvoxamine, levomilnacipran, mirtazapine, paroxetine, reboxetine, sertraline, venlafaxine, and vortioxetine) and report data on treatment-emergent gastrointestinal SEs (i.e. nausea/vomiting, diarrhoea, constipation, abdominal pain, dyspepsia, anorexia, increased appetite and dry mouth) within 12 weeks of treatment. Overall, 304 studies were included in the meta-analyses. All the considered antidepressants showed higher rates of gastrointestinal SEs than placebo. Escitalopram and sertraline were shown to be the least tolerated antidepressants on the gastrointestinal tract, being associated with all the considered SEs with the exception of constipation and increased appetite, while mirtazapine was shown to be the antidepressant with fewer side effects on the gut, being only associated with increased appetite. In conclusion, commonly used antidepressants showed different profiles of gastrointestinal SEs, possibly related to their mechanisms of action. The specific tolerability profile of each compound should be considered by clinicians when prescribing antidepressants in order to improve adherence to treatment and increase positive outcomes in patients with MDD.

Metabolomics encompasses the systematic identification and quantification of all metabolic products in the human body. This field could provide clinicians with novel sets of diagnostic biomarkers for disease states in addition to quantifying treatment response to medications at an individualized level. This literature review aims to highlight the technology underpinning metabolic profiling, identify potential applications of metabolomics in clinical practice, and discuss the translational challenges that the field faces. We searched PubMed, MEDLINE, and EMBASE for primary and secondary research articles regarding clinical applications of metabolomics. Metabolic profiling can be performed using mass spectrometry and nuclear magnetic resonance-based techniques using a variety of biological samples. This is carried out in vivo or in vitro following careful sample collection, preparation, and analysis. The potential clinical applications constitute disruptive innovations in their respective specialities, particularly oncology and metabolic medicine. Outstanding issues currently preventing widespread clinical use are scalability of data interpretation, standardization of sample handling practice, and e-infrastructure. Routine utilization of metabolomics at a patient and population level will constitute an integral part of future healthcare provision.