Precision medicine--personalized, problematic, and promising

Precision Medicine in Acute Coronary Syndromes

Nowadays, current guidelines on acute coronary syndrome (ACS) provide recommendations mainly based on the clinical presentation. However, greater attention is being directed to the specific pathophysiology underlying ACS, considering that plaque destabilization and rupture leading to luminal thrombotic obstruction is not the only pathway involved, albeit the most recognized. In this review, we discuss how intracoronary imaging and biomarkers allow the identification of specific ACS endotypes, leading to the recognition of different prognostic implications, tailored management strategies, and new potential therapeutic targets. Furthermore, different strategies can be applied on a personalized basis regarding antithrombotic therapy, non-culprit lesion revascularization, and microvascular obstruction (MVO). With respect to myocardial infarction with non-obstructive coronary arteries (MINOCA), we will present a precision medicine approach, suggested by current guidelines as the mainstay of the diagnostic process and with relevant therapeutic implications. Moreover, we aim at illustrating the clinical implications of targeted strategies for ACS secondary prevention, which may lower residual risk in selected patients.

The way towards ethical anesthesia care: no aim - no game - no fame or blame?

PURPOSE OF REVIEW

This review explores the intricacies of ethical anesthesia, exploring the necessity for precision anesthesia and its impact on patient-reported outcomes. The primary objective is to advocate for a defined aim, promoting the implementation of rules and feedback systems. The ultimate goal is to enhance precision anesthesia care, ensuring patient safety through the implementation of a teamwork and the integration of feedback mechanisms.

RECENT FINDINGS

Recent strategies in the field of anesthesia have evolved from intraoperative monitorization to a wider perioperative patient-centered precision care. Nonetheless, implementing this approach encounters significant obstacles. The article explores the evidence supporting the need for a defined aim and applicable rules for precision anesthesia's effectiveness. The implementation of the safety culture is underlined. The review delves into the teamwork description with structured feedback systems.

SUMMARY

Anesthesia is a multifaceted discipline that involves various stakeholders. The primary focus is delivering personalized precision care. This review underscores the importance of establishing clear aims, defined rules, and fostering effective and well tolerated teamwork with accurate feedback for improving patient-reported outcomes. The Safe Brain Initiative approach, emphasizing algorithmic monitoring and systematic follow-up, is crucial in implementing a fundamental and standardized reporting approach within patient-centered anesthesia care practice.

Amadori and Heyns rearrangement products of bioactive peptides as potential new ligands of galectin-3

Non-enzymatic cascade reactions between amines and reducing sugars are known as Maillard reaction. The late phase of these reactions consists of advanced glycation end products (AGEs), which have been implicated in the pathogenesis of numerous human diseases. Recent evidence suggests that galectin-3 acts as a receptor for AGEs and some early products of the Maillard reaction. The early phase of the Maillard reaction, which consists of 1-amino-1-deoxyketoses (Amadori compounds) and 2-amino-2-deoxyaldoses (Heyns compounds), was the subject of our study. The binding interactions between galectin-3 and the Amadori and Heyns compounds of leucine-enkephalin (YGGFL), leucine-enkephalin methyl ester (YGGFL-OMe), truncated enkephalin (YGG and Y) and tetrapeptide (LSKL) were measured using the AlphaScreen competitive binding assay. The affinity of galectin-3 for Amadori and Heyns compounds depends on both the sugar moiety and the amino acid sequence of the model compounds. The best results were obtained with Leu-enkephalin derivatives of Amadori (IC50 = 6.06 μm) and Heyns (IC50 = 8.6 μm) compound, respectively.

Design, construction, and validation of obstetric risk classification systems to predict intensive care unit admission

INTRODUCTION

To develop and validate a support tool for healthcare providers, enabling them to make precise and critical decisions regarding intensive care unit (ICU) admissions for high-risk pregnant women, thus enhancing maternal outcomes.

METHODS

This retrospective study involves secondary data analysis of information gathered from 9550 pregnant women, who had severe maternal morbidity (any unexpected complication during labor and delivery that leads to substantial short-term or long-term health issues for the mother), collected between 2009 and 2010 from the Brazilian Network for Surveillance of Severe Maternal Morbidity, encompassing 27 obstetric reference centers in Brazil. Machine-learning models, including decision trees, Random Forest, Gradient Boosting Machine (GBM), and Extreme Gradient Boosting (XGBoost), were employed to create a risk prediction tool for ICU admission. Subsequently, sensitivity analysis was conducted to compare the accuracy, predictive power, sensitivity, and specificity of these models, with differences analyzed using the Wilcoxon test.

RESULTS

The XGBoost algorithm demonstrated superior efficiency, achieving an accuracy rate of 85%, sensitivity of 42%, specificity of 97%, and an area under the receiver operating characteristic curve of 86.7%. Notably, the estimated prevalence of ICU utilization by the model (11.6%) differed from the prevalence of ICU use from the study (21.52%).

CONCLUSION

The developed risk engine yielded positive results, emphasizing the need to optimize intensive care bed utilization and objectively identify high-risk pregnant women requiring these services. This approach promises to enhance the effective and efficient management of pregnant women, particularly in resource-constrained regions worldwide. By streamlining ICU admissions for high-risk cases, healthcare providers can better allocate critical resources, ultimately contributing to improved maternal health outcomes.

Hydrogel-Based Therapies for Ischemic and Hemorrhagic Stroke: A Comprehensive Review

Stroke remains the second leading cause of death and a major cause of disability worldwide, significantly impacting individuals, families, and healthcare systems. This neurological emergency can be triggered by ischemic events, including small vessel arteriolosclerosis, cardioembolism, and large artery atherothromboembolism, as well as hemorrhagic incidents resulting from macrovascular lesions, venous sinus thrombosis, or vascular malformations, leading to significant neuronal damage. The resultant motor impairment, cognitive dysfunction, and emotional disturbances underscore the urgent need for effective therapeutic interventions. Recent advancements in biomaterials, particularly hydrogels, offer promising new avenues for stroke management. Hydrogels, composed of three-dimensional networks of hydrophilic polymers, are notable for their ability to absorb and retain substantial amounts of water. Commonly used polymers in hydrogel formulations include natural polymers like alginate, chitosan, and collagen, as well as synthetic polymers such as polyethylene glycol (PEG), polyvinyl alcohol (PVA), and polyacrylamide. Their customizable characteristics-such as their porosity, swelling behavior, mechanical strength, and degradation rates-make hydrogels ideal for biomedical applications, including drug delivery, cell delivery, tissue engineering, and the controlled release of therapeutic agents. This review comprehensively explores hydrogel-based approaches to both ischemic and hemorrhagic stroke therapy, elucidating the mechanisms by which hydrogels provide neuroprotection. It covers their application in drug delivery systems, their role in reducing inflammation and secondary injury, and their potential to support neurogenesis and angiogenesis. It also discusses current advancements in hydrogel technology and the significant challenges in translating these innovations from research into clinical practice. Additionally, it emphasizes the limited number of clinical trials utilizing hydrogel therapies for stroke and addresses the associated limitations and constraints, underscoring the need for further research in this field.

Profiling protein-protein interactions to predict the efficacy of B-cell-lymphoma-2-homology-3 mimetics for acute myeloid leukaemia

B-cell-lymphoma-2 (BCL2) homology-3 (BH3) mimetics are inhibitors of protein-protein interactions (PPIs) that saturate anti-apoptotic proteins in the BCL2 family to induce apoptosis in cancer cells. Despite the success of the BH3-mimetic ABT-199 for the treatment of haematological malignancies, only a fraction of patients respond to the drug and most patients eventually develop resistance to it. Here we show that the efficacy of ABT-199 can be predicted by profiling the rewired status of the PPI network of the BCL2 family via single-molecule pull-down and co-immunoprecipitation to quantify more than 20 types of PPI from a total of only 1.2 × 106 cells per sample. By comparing the obtained multidimensional data with BH3-mimetic efficacies determined ex vivo, we constructed a model for predicting the efficacy of ABT-199 that designates two complexes of the BCL2 protein family as the primary mediators of drug effectiveness and resistance, and applied it to prospectively assist therapeutic decision-making for patients with acute myeloid leukaemia. The characterization of PPI complexes in clinical specimens opens up opportunities for individualized protein-complex-targeting therapies.

Reconstitution of human tissue barrier function for precision and personalized medicine

Tissue barriers in a body, well known as tissue-to-tissue interfaces represented by endothelium of the blood vessels or epithelium of organs, are essential for maintaining physiological homeostasis by regulating molecular and cellular transports. It is crucial for predicting drug response to understand physiology of tissue barriers through which drugs are absorbed, distributed, metabolized and excreted. Since the FDA Modernization Act 2.0, which prompts the inception of alternative technologies for animal models, tissue barrier chips, one of the applications of organ-on-a-chip or microphysiological system (MPS), have only recently been utilized in the context of drug development. Recent advancements in stem cell technology have brightened the prospects for the application of tissue barrier chips in personalized medicine. In past decade, designing and engineering these microfluidic devices, and demonstrating the ability to reconstitute tissue functions were main focus of this field. However, the field is now advancing to the next level of challenges: validating their utility in drug evaluation and creating personalized models using patient-derived cells. In this review, we briefly introduce key design parameters to develop functional tissue barrier chip, explore the remarkable recent progress in the field of tissue barrier chips and discuss future perspectives on realizing personalized medicine through the utilization of tissue barrier chips.

Precision medicine for respiratory diseases: A current viewpoint

In the realm of respiratory illnesses, despite the immense costs and efforts invested in diagnosis and treatment, numerous patients with chronic respiratory conditions or malignancies do not respond well to existing therapies. Delayed diagnoses and inadequate treatments contribute to these challenges, along with adverse reactions or treatment limitations due to side-effects. However, recent advancements in understanding respiratory diseases have paved the way for personalized medical treatments, considering individual genetic, molecular and environmental factors. Precision medicine, which accommodates individual differences in disease susceptibility and response to treatments, aims to improve patient care by aligning medical research with tailored therapies. Innovative technologies, such as genomic sequencing and biomarker identification contribute to this approach, allowing for customized treatments and the identification of effective therapies. Additionally, the application of precision medicine in lung cancer treatment exemplifies the forefront of individualized care within respiratory medicine. Several studies have explored the role of precision medicine in managing respiratory infectious diseases, asthma and idiopathic pulmonary fibrosis, aiming to categorize diseases more accurately and design targeted therapies. The ultimate goal is to enhance treatment effectiveness, minimize adverse events, and shift towards a patient-centered approach to managing respiratory conditions. Despite limitations, precision medicine holds promise for improving patient outcomes and emphasizing personalized care in respiratory medicine.

Stratified medicine for acute and chronic coronary syndromes: A patient-tailored approach

The traditional approach to management of cardiovascular disease relies on grouping clinical presentations with common signs and symptoms into pre-specified disease pathways, all uniformly treated according to evidence-based guidelines ("one-size-fits-all"). The goal of precision medicine is to provide the right treatment to the right patients at the right time, combining data from time honoured sources (e.g., history, physical examination, imaging, laboratory) and those provided by multi-omics technologies. In patients with ischemic heart disease, biomarkers and intravascular assessment can be used to identify endotypes with different pathophysiology who may benefit from distinct treatments. This review discusses strategies for the application of stratified management to patients with acute and chronic coronary syndromes.

Precision endoscopy in colorectal polyps' characterization and planning of endoscopic therapy

Precision endoscopy in the management of colorectal polyps and early colorectal cancer has emerged as the standard of care. It includes optical characterization of polyps and estimation of submucosal invasion depth of large nonpedunculated colorectal polyps to select the appropriate endoscopic resection modality. Over time, several imaging modalities have been implemented in endoscopic practice to improve optical performance. Among these, image-enhanced endoscopy systems and magnification endoscopy represent now well-established tools. New advanced technologies, such as endocytoscopy and confocal laser endomicroscopy, have recently shown promising results in predicting the histology of colorectal polyps. In recent years, artificial intelligence has continued to enhance endoscopic performance in the characterization of colorectal polyps, overcoming the limitations of other imaging modes. In this review we retrace the path of precision endoscopy, analyzing the yield of various endoscopic imaging techniques in personalizing management of colorectal polyps and early colorectal cancer.

Artificial intelligence and personalized diagnostics in periodontology: A narrative review

Periodontal diseases pose a significant global health burden, requiring early detection and personalized treatment approaches. Traditional diagnostic approaches in periodontology often rely on a "one size fits all" approach, which may overlook the unique variations in disease progression and response to treatment among individuals. This narrative review explores the role of artificial intelligence (AI) and personalized diagnostics in periodontology, emphasizing the potential for tailored diagnostic strategies to enhance precision medicine in periodontal care. The review begins by elucidating the limitations of conventional diagnostic techniques. Subsequently, it delves into the application of AI models in analyzing diverse data sets, such as clinical records, imaging, and molecular information, and its role in periodontal training. Furthermore, the review also discusses the role of research community and policymakers in integrating personalized diagnostics in periodontal care. Challenges and ethical considerations associated with adopting AI-based personalized diagnostic tools are also explored, emphasizing the need for transparent algorithms, data safety and privacy, ongoing multidisciplinary collaboration, and patient involvement. In conclusion, this narrative review underscores the transformative potential of AI in advancing periodontal diagnostics toward a personalized paradigm, and their integration into clinical practice holds the promise of ushering in a new era of precision medicine for periodontal care.

Insomnia symptoms and neurofunctional correlates among adults receiving buprenorphine for opioid use disorder

OBJECTIVES

Insomnia symptoms are negatively related to opioid use disorder (OUD) treatment outcomes, possibly reflecting the influence of sleep on neurofunctional domains implicated in addiction. Moreover, the intersection between OUD recovery and sleep represents an area well-suited for the development of novel, personalized treatment strategies. This study assessed the prevalence of clinically significant insomnia symptoms and characterized its neurofunctional correlates among a clinical sample of adults with OUD receiving buprenorphine.

METHODS

Adults (N = 129) receiving buprenorphine for OUD from an outpatient clinic participated in a cross-sectional survey. Participants completed an abbreviated version of NIDA's Phenotyping Assessment Battery, which assessed 6 neurofunctional domains: sleep, negative emotionality, metacognition, interoception, cognition, and reward. Bivariate descriptive statistics compared those with evidence of clinically significant insomnia symptoms (Insomnia Severity Index [ISI] score of ≥11) to those with minimal evidence of clinically significant insomnia symptoms (ISI score of ≤10) across each of the neurofunctional domains.

RESULTS

Roughly 60% of participants reported clinically significant insomnia symptoms (ISI score of ≥11). Experiencing clinically significant insomnia symptoms was associated with reporting greater levels of depression, anxiety, post-traumatic stress, stress intolerance, unhelpful metacognition, and interoceptive awareness (ps<0.05). Participants with evidence of clinically significant insomnia were more likely to report that poor sleep was interfering with their OUD treatment and that improved sleep would assist with their treatment (ps<0.05).

CONCLUSIONS

Insomnia was prevalent among adults receiving buprenorphine for OUD. Insomnia was associated with neurofunctional performance, which may impact OUD treatment trajectories. Our findings indicate potential targets in the development of personalized treatment plans for patients with co-morbid insomnia and OUD. To inform the development of novel treatment strategies, more research is needed to understand the potential mechanistic links between sleep disturbances and substance use.

Single nucleotide polymorphism-based biomarker in primary hypertension

Primary hypertension is a multiplex and multifactorial disease influenced by various strong components including genetics. Extensive research such as Genome-wide association studies and candidate gene studies have revealed various single nucleotide polymorphisms (SNPs) related to hypertension, providing insights into the genetic basis of the condition. This review summarizes the current status of SNP research in primary hypertension, including examples of hypertension-related SNPs, their location, function, and frequency in different populations. The potential clinical implications of SNP research for primary hypertension management are also discussed, including disease risk prediction, personalized medicine, mechanistic understanding, and lifestyle modifications. Furthermore, this review highlights emerging technologies and methodologies that have the potential to revolutionize the vast understanding of the basis of genetics in primary hypertension. Gene editing holds the potential to target and correct any kind of genetic mutations that contribute to the development of hypertension or modify genes involved in blood pressure regulation to prevent or treat the condition. Advances in computational biology and machine learning enable researchers to analyze large datasets and identify complex genetic interactions contributing to hypertension risk. In conclusion, SNP research in primary hypertension is rapidly evolving with emerging technologies and methodologies that have the potential to transform the knowledge about genetic basis related to the condition. These advances hold promise for personalized prevention and treatment strategies tailored to an individual's genetic profile ultimately improving patient outcomes and reducing healthcare costs.

Assessing the potential for precision medicine in body weight reduction with regard to type 2 diabetes mellitus therapies: A meta-regression analysis of 120 randomized controlled trials

AIMS

To assess the potential for precision medicine in type 2 diabetes by quantifying the variability of body weight as response to pharmacological treatment and to identify predictors which could explain this variability.

METHODS

We used randomized clinical trials (RCTs) comparing glucose-lowering drugs (including but not limited to sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists and thiazolidinediones) to placebo from four recent systematic reviews. RCTs reporting on body weight after treatment to allow for calculation of its logarithmic standard deviation (log[SD], i.e., treatment response heterogeneity) in verum (i.e., treatment) and placebo groups were included. Meta-regression analyses were performed with respect to variability of body weight after treatment and potential predictors.

RESULTS

A total of 120 RCTs with a total of 43 663 participants were analysed. A slightly larger treatment response heterogeneity was shown in the verum groups, with a median log(SD) of 2.83 compared to 2.79 from placebo. After full adjustment in the meta-regression model, the difference in body weight log(SD) was -0.026 (95% confidence interval -0.044; 0.008), with greater variability in the placebo groups. Scatterplots did not show any slope divergence (i.e., interaction) between clinical predictors and the respective treatment (verum or placebo).

CONCLUSIONS

We found no major treatment response heterogeneity in RCTs of glucose-lowering drugs for body weight reduction in type 2 diabetes. The precision medicine approach may thus be of limited value in this setting.

Drug screening on digital microfluidics for cancer precision medicine

Drug screening based on in-vitro primary tumor cell culture has demonstrated potential in personalized cancer diagnosis. However, the limited number of tumor cells, especially from patients with early stage cancer, has hindered the widespread application of this technique. Hence, we developed a digital microfluidic system for drug screening using primary tumor cells and established a working protocol for precision medicine. Smart control logic was developed to increase the throughput of the system and decrease its footprint to parallelly screen three drugs on a 4 × 4 cm2 chip in a device measuring 23 × 16 × 3.5 cm3. We validated this method in an MDA-MB-231 breast cancer xenograft mouse model and liver cancer specimens from patients, demonstrating tumor suppression in mice/patients treated with drugs that were screened to be effective on individual primary tumor cells. Mice treated with drugs screened on-chip as ineffective exhibited similar results to those in the control groups. The effective drug identified through on-chip screening demonstrated consistency with the absence of mutations in their related genes determined via exome sequencing of individual tumors, further validating this protocol. Therefore, this technique and system may promote advances in precision medicine for cancer treatment and, eventually, for any disease.

Ultrasound measurement of traumatic scar and skin thickness: a scoping review of evidence across the translational pipeline of research-to-practice

OBJECTIVES

To identify the ultrasound methods used in the literature to measure traumatic scar thickness, and map gaps in the translation of these methods using evidence across the research-to-practice pipeline.

DESIGN

Scoping review.

DATA SOURCES

Electronic database searches of Ovid MEDLINE, Embase, Cumulative Index of Nursing and Allied Health Literature and Web of Science. Grey literature searches were conducted in Google. Searches were conducted from inception (date last searched 27 May 2022).

DATA EXTRACTION

Records using brightness mode (B-mode) ultrasound to measure scar and skin thickness across the research-to-practice pipeline of evidence were included. Data were extracted from included records pertaining to: methods used; reliability and measurement error; clinical, health service, implementation and feasibility outcomes; factors influencing measurement methods; strengths and limitations; and use of measurement guidelines and/or frameworks.

RESULTS

Of the 9309 records identified, 118 were analysed (n=82 articles, n=36 abstracts) encompassing 5213 participants. Reporting of methods used was poor. B-mode, including high-frequency (ie, >20 MHz) ultrasound was the most common type of ultrasound used (n=72 records; 61% of records), and measurement of the combined epidermal and dermal thickness (n=28; 24%) was more commonly measured than the epidermis or dermis alone (n=7, 6%). Reliability of ultrasound measurement was poorly reported (n=14; 12%). The scar characteristics most commonly reported to be measured were epidermal oedema, dermal fibrosis and hair follicle density. Most records analysed (n=115; 97%) pertained to the early stages of the research-to-practice pipeline, as part of research initiatives.

CONCLUSIONS

The lack of evaluation of measurement initiatives in routine clinical practice was identified as an evidence gap. Diverse methods used in the literature identified the need for greater standardisation of ultrasound thickness measurements. Findings have been used to develop nine methodological considerations for practitioners to guide methods and reporting.

Robust, Sprayable, and Multifunctional Hydrogel Coating through a Polycation Reinforced (PCR) Surface Bridging Strategy

The sprayable hydrogel coatings that can establish robust adhesion onto diverse materials and devices hold enormous potential; however, a significant challenge persists due to monomer hydration, which impedes even coverage during spraying and induces inadequate adhesion post-gelation. Herein, a polycation-reinforced (PCR) surface bridging strategy is presented to achieve tough and sprayable hydrogel coatings onto diverse materials. The polycations offer superior wettability and instant electrostatic interactions with plasma-treated substrates, facilitating an effective spraying application. This PCR-based hydrogel coatings demonstrate tough adhesion performance to inert PTFE and silicone, including remarkable shear strength (161 ± 49 kPa for PTFE), interfacial toughness (198 ± 27 J m-2 for PTFE), and notable tolerance to cyclic tension (10 000 cycles, 200% strain, silicone). Meanwhile, this method can be applied to various hydrogel formulations, offering diverse functionalities, including underwater adhesion, lubrication, and drug delivery. Furthermore, the PCR concept enables the conformal construction of durable hydrogel coatings onto sophisticated medical devices like cardiovascular stents. Given its simplicity and adaptability, this approach paves an avenue for incorporating hydrogels onto solid surfaces and potentially promotes untapped applications.

Patient-centered precision care in anaesthesia - the PC-square (PC) 2 approach

PURPOSE OF REVIEW

This review navigates the landscape of precision anaesthesia, emphasising tailored and individualized approaches to anaesthetic administration. The aim is to elucidate precision medicine principles, applications, and potential advancements in anaesthesia. The review focuses on the current state, challenges, and transformative opportunities in precision anaesthesia.

RECENT FINDINGS

The review explores evidence supporting precision anaesthesia, drawing insights from neuroscientific fields. It probes the correlation between high-dose intraoperative opioids and increased postoperative consumption, highlighting how precision anaesthesia, especially through initiatives like Safe Brain Initiative (SBI), could address these issues. The SBI represents multidisciplinary collaboration in perioperative care. SBI fosters effective communication among surgical teams, anaesthesiologists, and other medical professionals.

SUMMARY

Precision anaesthesia tailors care to individual patients, incorporating genomic insights, personalised drug regimens, and advanced monitoring techniques. From EEG to cerebral/somatic oximetry, these methods enhance precision. Standardised reporting, patient-reported outcomes, and continuous quality improvement, alongside initiatives like SBI, contribute to improved patient outcomes. Precision anaesthesia, underpinned by collaborative programs, emerges as a promising avenue for enhancing perioperative care.

Endoscopic ultrasound-guided tissue acquisition for comprehensive genomic profiling

Advances in next-generation sequencing have made comprehensive genomic profiling (CGP) using tumor tissue specimens and liquid biopsy using blood samples feasible in routine clinical practice. In the context of pancreaticobiliary cancer, it is necessary to consider CGP in formulating individualized treatment strategies. Performing CGP with tumor tissue specimens requires a sufficient number of high-quality samples. EUS-guided tissue acquisition (EUS-TA) is expected to play a significant role in this regard, and endosonographers need to address this role. Here, we review the current status of EUS-TA for CGP focusing on pancreatic cancer and biliary tract cancer.

Pseudomesotheliomatous Carcinoma of the Lung with Morphological Characteristics of Signet Ring Cell Carcinoma: An Autopsy Case Report

A 50-year-old woman presented with left pleural effusion. A pleural fluid cell-block specimen and longitudinal lymph node needle biopsy suggested signet ring cell carcinoma (SRCC). Although computed tomography showed a consolidation shadow in the left lower lobe, a left lung biopsy could not be performed. Upper gastrointestinal endoscopy revealed no malignancies. We administered carboplatin, pemetrexed, ipilimumab, and nivolumab for lung cancer; however, she died due to progressive respiratory failure. Pathological autopsy revealed that the left pleura was thickened as in mesothelioma, based on which pseudomesotheliomatous carcinoma of the lung (PMCL) was diagnosed. PMCLs exhibiting an SRCC morphology are rare.

Classified functional mixed effects model prediction

In nowadays biomedical research, there has been a growing demand for making accurate prediction at subject levels. In many of these situations, data are collected as longitudinal curves and display distinct individual characteristics. Thus, prediction mechanisms accommodated with functional mixed effects models (FMEM) are useful. In this paper, we developed a classified functional mixed model prediction (CFMMP) method, which adapts classified mixed model prediction (CMMP) to the framework of FMEM. Performance of CFMMP against functional regression prediction based on simulation studies and the consistency property of CFMMP estimators are explored. Real-world applications of CFMMP are illustrated using real world examples including data from the hormone research menstrual cycles and the diffusion tensor imaging.

Unleashing the power of antibodies: Engineering for tomorrow's therapy

Antibodies play a crucial role in host defense against various diseases. Antibody engineering is a multidisciplinary field that seeks to improve the quality of life of humans. In the context of disease, antibodies are highly specialized proteins that form a critical line of defense against pathogens and the disease caused by them. These infections trigger the innate arm of immunity by presenting on antigen-presenting cells such as dendritic cells. This ultimately links to the adaptive arm, where antibody production and maturation occur against that particular antigen. Upon binding with their specific antigens, antibodies trigger various immune responses to eliminate pathogens in a process called complement-dependent cytotoxicity and phagocytosis of invading microorganisms by immune cells or induce antibody-dependent cellular cytotoxicity is done by antibodies. These engineered antibodies are being used for various purposes, such as therapeutics, diagnostics, and biotechnology research. Cutting-edge techniques that include hybridoma technology, transgenic mice, display techniques like phage, yeast and ribosome displays, and next-generation sequencing are ways to engineer antibodies and mass production for the use of humankind. Considering the importance of antibodies in protecting from a diverse array of pathogens, investing in research holds great promise to develop future therapeutic targets to combat various diseases.

Decoding active compounds and molecular targets of herbal medicine by high-throughput metabolomics technology: A systematic review

Clinical experiences of herbal medicine (HM) have been used to treat a variety of human intractable diseases. As the treatment of diseases using HM is characterized by multi-components and multi-targets, it is difficult to determine the bio-active components, explore the molecular targets and reveal the mechanisms of action. Metabolomics is frequently used to characterize the effect of external disturbances on organisms because of its unique advantages on detecting changes in endogenous small-molecule metabolites. Its systematicity and integrity are consistent with the effective characteristics of HM. After HM intervention, metabolomics can accurately capture and describe the behavior of endogenous metabolites under the disturbance of functional compounds, which will be used to decode the bioactive ingredients of HM and expound the molecular targets. Metabolomics can provide an approach for explaining HM, addressing unclear clinical efficacy and undefined mechanisms of action. In this review, the metabolomics strategy and its applications in HM are systematically introduced, which offers valuable insights for metabolomics methods to characterizing the pharmacological effects and molecular targets of HM.

[Precision medicine enhances personalized medicine in cardiology]

Personalized medicine and precision medicine, frequently used synonymously, shall be clearly differentiated. Accordingly, personalization in cardiac medicine is based on the clinical presentation of a patient, as well as his/her cardiovascular risk factors and comorbidities, electrocardiography, imaging, and biomarkers for myocardial load and ischemia. Personalization is based on large clinical trials with detailed subgroup analyses and is practiced on the basis of guidelines. Further in depth personalization is achieved by precision medicine, which is based on innovative imaging for myocardial structure, coronary morphology, and electrophysiology. From the clinical perspective, genome analyses are relevant for comparatively rare monogenetic cardiovascular diseases. While these as well as transcriptome and metabolome analyses play a significant role in cardiovascular research with great translation potential, they have not yet been broadly introduced in the diagnosis, prevention, and treatment of complex cardiovascular diseases. Furthermore, digital technologies have considerable potential in cardiovascular precision medicine. On the one hand, this is based on the frequency of the diseases with the availability of Big Data and, on the other hand, on the availability of bio-signals and sensors of those signals in cardiovascular diseases.

Endoscopic Ultrasound-Guided Fine-Needle Biopsy Versus Aspiration for Tissue Sampling Adequacy for Molecular Testing in Pancreatic Ductal Adenocarcinoma

BACKGROUND AND AIMS

There is limited literature on sample adequacy for molecular testing in pancreatic ductal adenocarcinoma obtained via endoscopic ultrasound (EUS) fine-needle aspiration (FNA) versus EUS fine-needle biopsy (FNB). We aimed to compare these two modalities regarding sample adequacy for molecular and genomic sequencing.

METHODS

We reviewed all patients with pancreatic ductal adenocarcinoma who underwent EUS at Saint Luke's Hospital from 2018 to 2021. The patients were categorized based on the method of EUS tissue acquisition, specifically FNA or FNB. A comprehensive evaluation was conducted for all cases by cytotechnologists.

RESULTS

Out of 132 patients who underwent EUS-guided biopsies, 76 opted for FNA, 48 opted for FNB, and 8 opted for a combination of both. The average number of passes required for FNB and FNA was 2.58 ± 1.06 and 2.49 ± 1.07, respectively (p = 0.704), indicating no significant difference. Interestingly, 71.4% (35) of FNB-obtained samples were deemed adequate for molecular testing, surpassing the 32.1% (26) adequacy observed with FNA (p < 0.001). Additionally, 46.4% (26) of FNB-obtained samples were considered adequate for genomic testing, a notable improvement over the 23.8% (20) adequacy observed with FNA (p = 0.005).

CONCLUSION

Although the number of passes required for cytologic diagnosis did not differ significantly between EUS-FNB and EUS-FNA, the former demonstrated superiority in obtaining samples adequate for molecular testing. Tumor surface area and cellularity were crucial parameters in determining sample adequacy for molecular testing, irrespective of the chosen tissue acquisition modality.

Applying the treatable traits approach in bronchiectasis-A scoping review of traits, measurements and treatments implemented by allied health professionals and nurses

BACKGROUND

Using treatable traits as a management approach in bronchiectasis involves determining identifiable, clinically relevant, measurable and treatable problems to develop a management strategy in collaboration with the patient.

OBJECTIVE

To identify new treatable traits not previously reported in the literature and treatment strategies for new and existing traits that could be implemented in an outpatient clinic or community setting by an allied health professional or nurse in adults with bronchiectasis.

METHODS

A scoping review was conducted with searches of MEDLINE, CINAHL, AMED, Embase, Cochrane Central Register of Controlled Trials and PsycInfo. The search yielded 9963 articles with 255 articles proceeding to full text review and 114 articles included for data extraction.

RESULTS

Sixteen new traits were identified, including fatigue (number of studies with new trait (n) = 13), physical inactivity (n = 13), reduced peripheral muscle power and/or strength (n = 12), respiratory muscle weakness (n = 9) and sedentarism (n = 6). The main treatment strategies for new and existing traits were airway clearance therapy (number of citations (n) = 86), pulmonary rehabilitation (n = 58), inspiratory muscle training (n = 20) and nebulised saline (n = 12).

CONCLUSION

This review identifies several new traits in bronchiectasis and highlights the common treatments for new and existing traits that can be implemented in a treatable traits approach in an outpatient clinic or community setting by an allied health professional or nurse.

The Peritoneal Membrane and Its Role in Peritoneal Dialysis

A healthy and functional peritoneal membrane is key to achieving sufficient ultrafiltration and restoring fluid balance, a major component of high-quality prescription in patients treated with peritoneal dialysis (PD). Variability in membrane function at the start of PD or changes over time on treatment influence dialysis prescription and outcomes, and dysfunction of the peritoneal membrane contributes to fluid overload and associated complications. In this review, we summarize the current knowledge about the structure, function, and pathophysiology of the peritoneal membrane with a focus on clinical implications for patient-centered care. We also discuss the molecular and genetic mechanisms of solute and water transport across the peritoneal membrane, including the role of aquaporin water channels in crystalloid versus colloid osmosis; why and how to assess membrane function using peritoneal equilibration tests; the etiologies of membrane dysfunction and their specific management; and the effect of genetic variation on membrane function and outcomes in patients treated with PD. This review also identifies the gaps in current knowledge and perspectives for future research to improve our understanding of the peritoneal membrane and, ultimately, the care of patients treated with PD.

Towards personalized genome-scale modeling of inborn errors of metabolism for systems medicine applications

Inborn errors of metabolism (IEMs) are a group of more than 1000 inherited diseases that are individually rare but have a cumulative global prevalence of 50 per 100,000 births. Recently, it has been recognized that like common diseases, patients with rare diseases can greatly vary in the manifestation and severity of symptoms. Here, we review omics-driven approaches that enable an integrated, holistic view of metabolic phenotypes in IEM patients. We focus on applications of Constraint-based Reconstruction and Analysis (COBRA), a widely used mechanistic systems biology approach, to model the effects of inherited diseases. Moreover, we review evidence that the gut microbiome is also altered in rare diseases. Finally, we outline an approach using personalized metabolic models of IEM patients for the prediction of biomarkers and tailored therapeutic or dietary interventions. Such applications could pave the way towards personalized medicine not just for common, but also for rare diseases.

Biomarkers of response to treatment in acromegaly

INTRODUCTION

Medical treatment of acromegaly is based in a `trial and error` approach. First-generation somatostatin receptor ligands (fg-SRL) are prescribed as first-line medical therapy to the vast majority of patients, despite lack of disease control in approximately 60% of patients. However, other drugs used in acromegaly treatment are available (cabergoline, pasireotide and pegvisomant).

AREAS COVERED

In this article, we review and discuss the biomarkers of response to medical treatment in acromegaly.

EXPERT OPINION

Biomarkers for fg-SRL that can already be applied in clinical practice are: gender, age, pretreatment GH and IGF-I levels, cytokeratin granulation pattern, and the expression of somatostatin receptor type 2. Using biomarkers of response could guide treatment towards precision medicine with greater efficacy and lower costs.

Treatable traits models of care

Treatable traits is a personalized approach to the management of respiratory disease. The approach involves a multidimensional assessment to understand the traits present in individual patients. Traits are phenotypic and endotypic characteristics that can be identified, are clinically relevant and can be successfully treated by therapy to improve clinical outcomes. Identification of traits is followed by individualized and targeted treatment to those traits. First proposed for the management of asthma and chronic obstructive pulmonary disease (COPD) the approach is recommended in many other areas of respiratory and now immunology medicine. Models of care for treatable traits have been proposed in different diseases and health care setting. In asthma and COPD traits are identified in three domains including pulmonary, extrapulmonary and behavioural/lifestyle/risk-factors. In bronchiectasis and interstitial lung disease, a fourth domain of aetiological traits has been proposed. As the core of treatable traits is personalized and individualized medicine; there are several key aspects to treatable traits models of care that should be considered in the delivery of care. These include person centredness, consideration of patients' values, needs and preferences, health literacy and engagement. We review the models of care that have been proposed and provide guidance on the engagement of patients in this approach to care.

Treat-to-Target in Atopic Dermatitis

Atopic dermatitis is one of the most common inflammatory skin diseases among children and adults. Over the last 5 years, the armamentarium for the treatment of this disease, with both topical and systemic drugs, has increased. Treat-to-target is basically the concept where a treatment goal and a time frame for that goal is set at initiation of a new treatment, and if the goals are not achieved in time, treatment will be adjusted. In clinical trials, treatment targets are based on scoring systems for disease severity as recommended by the Harmonizing Outcome Measure for Eczema (HOME) initiative, with the primary endpoint being a reduction of at least 75% of the baseline Eczema Area and Severity Index (EASI) score (EASI-75). The question, however, is if these are useful targets in real-world settings and how this should be implemented in everyday clinical practice. In rheumatology, setting a measurable target and a time frame for an instigated therapy has been shown to lead to more efficient and successful treatment. For atopic dermatitis, the instruments recommended by HOME form the core outcome measures for the treat-to-target frameworks published to date, which are based on expert consensus and Delphi processes. Although atopic dermatitis patients have a high risk of co-morbidities, including physical, psychological and socioeconomic, instruments to measure the severity of co-morbidities have not been included in these existing frameworks. In order to apply a treat-to-target strategy that is meaningful for both the patient and the doctor, validated tools for the measurement of treatment effect on co-morbidities exist and should be included in a shared decision-making process with the individual patient when choosing which targets to aim for and what should be considered treatment success. An obvious limitation for the implementation of a treat-to-target strategy in the clinical setting with atopic dermatitis is that retrieving the data needed is very time consuming. This could to some degree be mitigated by the use of electronic applications in which patients could report their outcomes.

Treatable traits in asthma during pregnancy: a call for a shift towards a precision-based management approach

Asthma is the most common chronic medical condition in pregnancy. Asthma exacerbations in pregnancy are unpredictable, and are associated with adverse maternal and fetal perinatal outcomes such as preterm birth and low birthweight. Goals of asthma management in pregnancy are to establish effective asthma control and prevent exacerbations. Optimising the management of asthma in pregnancy is an important goal of practice and future research.Treatable traits is a precision medicine paradigm proposed for the management of airways diseases, which holistically addresses the complexity and heterogeneity of airways disease. It is an individualised treatment approach that aims to improve outcomes. This makes treatable traits well suited for pregnant women with asthma, who have a high prevalence of obesity, mental health conditions, poor symptom perception and suboptimal asthma management skills including low treatment adherence. These traits are measurable and treatable. In this review, we explore current knowledge on the burden of asthma, maternal and perinatal consequences of asthma during pregnancy, the treatable traits paradigm, the prevalence of treatable traits in pregnant women with asthma, and consider how the treatable traits paradigm can be integrated into the management of asthma in pregnancy.

A Comprehensive Review of Small Interfering RNAs (siRNAs): Mechanism, Therapeutic Targets, and Delivery Strategies for Cancer Therapy

Small interfering RNA (siRNA) delivery by nanocarriers has been identified as a promising strategy in the study and treatment of cancer. Short nucleotide sequences are synthesized exogenously to create siRNA, which triggers RNA interference (RNAi) in cells and silences target gene expression in a sequence-specific way. As a nucleic acid-based medicine that has gained popularity recently, siRNA exhibits novel potential for the treatment of cancer. However, there are still many obstacles to overcome before clinical siRNA delivery devices can be developed. In this review, we discuss prospective targets for siRNA drug design, explain siRNA drug properties and benefits, and give an overview of the current clinical siRNA therapeutics for the treatment of cancer. Additionally, we introduce the siRNA chemical modifications and delivery systems that are clinically sophisticated and classify bioresponsive materials for siRNA release in a methodical manner. This review will serve as a reference for researchers in developing more precise and efficient targeted delivery systems, promoting ongoing advances in clinical applications.

Transform diabetes care with precision medicine

Background and Aims

Diabetes is a global concern. This article took a closer look at diabetes and precision medicine.

Methods

A literature search of studies related to the use of precision medicine in diabetes care was conducted in various databases (PubMed, Google Scholar, and Scopus).

Results

Precision medicine encompasses the integration of a wide array of personal data, including clinical, lifestyle, genetic, and various biomarker information. Its goal is to facilitate tailored treatment approaches using contemporary diagnostic and therapeutic techniques that specifically target patients based on their genetic makeup, molecular markers, phenotypic traits, or psychosocial characteristics. This article not only highlights significant advancements but also addresses key challenges, particularly focusing on the technologies that contribute to the realization of personalized and precise diabetes care.

Conclusion

For the successful implementation of precision diabetes medicine, collaboration and coordination among multiple stakeholders are crucial.

Comprehensive genomic profiling of Japanese patients with thoracic malignancies: A single-center retrospective study

BACKGROUND

Few studies have been conducted on comprehensive genomic profiling (CGP) panels in Japanese patients with thoracic malignancies after completing standard treatment. Consequently, its value in clinical practice remains unclear.

METHODS

We conducted a retrospective study of Japanese patients with thoracic malignancies who underwent CGP between June 2019 and November 2022 at our hospital. We evaluated the detection rate of actionable genetic alterations and percentage of patients who received genomically-matched therapy. Furthermore, we examined the value of the CGP panel in patients who underwent multiplex gene-panel testing prior to their initial treatment. This study was performed in accordance with the principles of the Declaration of Helsinki.

RESULTS

The study included 56 patients, of whom 47 (83.9%) had actionable genetic alterations and 8 (14.3%) received genomically-matched therapy. Of these, four patients were treated with approved drugs and three patients were treated with investigational agents. In addition, one patient was treated with approved drugs using the patient-directed care system. Of the 17 patients who had multiplex gene-panel testing performed at the start of their initial therapy, two (11.8%) were newly identified by the CGP panel and subsequently received genomically-matched therapy. EGFR L718Q and MET amplification were observed in two of the seven patients with epidermal growth factor receptor-tyrosine kinase inhibitor resistance.

CONCLUSIONS

The CGP panel could identify genetic alterations, thereby facilitating genomically-matched therapy, even in patients with thoracic malignancies who could not be identified using multiplex gene-panel testing.

Precision medicine of obesity as an integral part of type 2 diabetes management - past, present, and future

Obesity is a complex and heterogeneous condition that leads to various metabolic complications, including type 2 diabetes. Unfortunately, for some, treatment options to date for obesity are insufficient, with many people not reaching sustained weight loss or having improvements in metabolic health. In this Review, we discuss advances in the genetics of obesity from the past decade-with emphasis on developments from the past 5 years-with a focus on metabolic consequences, and their potential implications for precision management of the disease. We also provide an overview of the potential role of genetics in guiding weight loss strategies. Finally, we propose a vision for the future of precision obesity management that includes developing an obesity-centred multidisease management algorithm that targets both obesity and its comorbidities. However, further collaborative efforts and research are necessary to fully realise its potential and improve metabolic health outcomes.

Model-informed precision dosing of vancomycin for rapid achievement of target area under the concentration-time curve: A simulation study

In this study, we aimed to evaluate limited sampling strategies for achieving the therapeutic ranges of the area under the concentration-time curve (AUC) of vancomycin on the first and second day (AUC0-24 , AUC24-48 , respectively) of therapy. A virtual population of 1000 individuals was created using a population pharmacokinetic (PopPK) model, which was validated and incorporated into our model-informed precision dosing tool. The results were evaluated using six additional PopPK models selected based on a study design of prospective or retrospective data collection with sufficient concentrations. Bayesian forecasting was performed to evaluate the probability of achieving the therapeutic range of AUC, defined as a ratio of estimated/reference AUC within 0.8-1.2. The Bayesian posterior probability of achieving the AUC24-48 range increased from 51.3% (a priori probability) to 77.5% after using two-point sampling at the trough and peak on the first day. Sampling on the first day also yielded a higher Bayesian posterior probability (86.1%) of achieving the AUC0-24 range compared to the a priori probability of 60.1%. The Bayesian posterior probability of achieving the AUC at steady-state (AUCSS ) range by sampling on the first or second day decreased with decreased kidney function. We demonstrated that second-day trough and peak sampling provided accurate AUC24-48 , and first-day sampling may assist in rapidly achieving therapeutic AUC24-48 , although the AUCSS should be re-estimated in patients with reduced kidney function owing to its unreliable predictive performance.

Precision Endoscopy in Peroral Myotomies for Motility Disorders of the Upper Gastrointestinal Tract: Current Insights and Prospective Avenues-A Comprehensive Review

Our review delves into the realm of peroral endoscopic myotomies (POEMs) in the upper gastrointestinal tract (UGT). In recent years, POEMs have brought about a revolution in the treatment of UGT motility disorders. Esophageal POEM, the first to be introduced, has now been validated as the primary treatment for achalasia. Subsequently developed, G-POEM displays promising results in addressing refractory gastroparesis. Over time, multiple endoscopic myotomy techniques have emerged for the treatment of Zenker's diverticulum, including Z-POEM, POES, and hybrid approaches. Despite the well-established efficacy outcomes, new challenges arise in the realm of POEMs in the UGT. For esophageal POEM, the future scenario lies in customizing the myotomy extent to the minimum necessary, while for G-POEM, it involves identifying patients who can optimally benefit from the treatment. For ZD, it is crucial to validate an algorithm that considers various myotomy options according to the diverticulum's size and in relation to individual patients. These challenges align with the concept of precision endoscopy, personalizing the technique for each subject. Within our text, we comprehensively examine each myotomy technique, analyzing indications, outcomes, and adverse events. Additionally, we explore the emerging challenges posed by myotomies within the context of the evolving field of precision endoscopy.

The Next Frontier in Sarcoma Care: Digital Health, AI, and the Quest for Precision Medicine

The landscape of sarcoma care is on the cusp of a transformative era, spurred by the convergence of digital health and artificial intelligence (AI). This perspectives article explores the multifaceted opportunities and challenges in leveraging these technologies for value-based, precision sarcoma care. We delineate the current state-of-the-art methodologies and technologies in sarcoma care and outline their practical implications for healthcare providers, administrators, and policymakers. The article also addresses the limitations of AI and digital health platforms, emphasizing the need for high-quality data and ethical considerations. We delineate the promise held by the synergy of digital health platforms and AI algorithms in enhancing data-driven decision-making, outcome analytics, and personalized treatment planning. The concept of a sarcoma digital twin serves as an illustrative paradigm for this integration, offering a comprehensive, patient-centric view of the healthcare journey. The paper concludes with proposals for future research aimed at advancing the field, including the need for randomized controlled trials or target trial emulations and studies focusing on ethical and economic aspects. While the road to this transformative care is laden with ethical, regulatory, and practical challenges, we believe that the potential benefits far outweigh the obstacles. We conclude with a call to action for multidisciplinary collaboration and systemic adoption of these technologies, underscoring the urgency to act now for the future betterment of sarcoma care and healthcare at large.

Walking the path of treatable traits in interstitial lung diseases

Interstitial lung diseases (ILDs) are complex and heterogeneous diseases. The use of traditional diagnostic classification in ILD can lead to suboptimal management, which is worsened by not considering the molecular pathways, biological complexity, and disease phenotypes. The identification of specific "treatable traits" in ILDs, which are clinically relevant and modifiable disease characteristics, may improve patient's outcomes. Treatable traits in ILDs may be classified into four different domains (pulmonary, aetiological, comorbidities, and lifestyle), which will facilitate identification of related assessment tools, treatment options, and expected benefits. A multidisciplinary care team model is a potential way to implement a "treatable traits" strategy into clinical practice with the aim of improving patients' outcomes. Multidisciplinary models of care, international registries, and the use of artificial intelligence may facilitate the implementation of the "treatable traits" approach into clinical practice. Prospective studies are needed to test potential therapies for a variety of treatable traits to further advance care of patients with ILD.

GLP-1R signaling neighborhoods associate with the susceptibility to adverse drug reactions of incretin mimetics

G protein-coupled receptors are important drug targets that engage and activate signaling transducers in multiple cellular compartments. Delineating therapeutic signaling from signaling associated with adverse events is an important step towards rational drug design. The glucagon-like peptide-1 receptor (GLP-1R) is a validated target for the treatment of diabetes and obesity, but drugs that target this receptor are a frequent cause of adverse events. Using recently developed biosensors, we explored the ability of GLP-1R to activate 15 pathways in 4 cellular compartments and demonstrate that modifications aimed at improving the therapeutic potential of GLP-1R agonists greatly influence compound efficacy, potency, and safety in a pathway- and compartment-selective manner. These findings, together with comparative structure analysis, time-lapse microscopy, and phosphoproteomics, reveal unique signaling signatures for GLP-1R agonists at the level of receptor conformation, functional selectivity, and location bias, thus associating signaling neighborhoods with functionally distinct cellular outcomes and clinical consequences.

Treatable Traits in Systemic Sclerosis

Systemic sclerosis (SSc) is a chronic systemic disease within the spectrum of connective tissue diseases, specifically characterized by vascular abnormalities and inflammatory and fibrotic involvement of the skin and internal organs resulting in high morbidity and mortality. The clinical phenotype of SSc is heterogeneous, and serum autoantibodies together with the extent of skin involvement have a predictive value in the risk stratification. Current recommendations include an organ-based management according to the predominant involvement with only limited individual factors included in the treatment algorithm. Similar to what has been proposed for other chronic diseases, we hypothesize that a "treatable trait" approach based on relevant phenotypes and endotypes could address the unmet needs in SSc stratification and treatment to maximize the outcomes. We provide herein a comprehensive review and a critical discussion of the literature regarding potential treatable traits in SSc, focusing on established and candidate biomarkers, with the purpose of setting the bases for a precision medicine-based approach. The discussion, structured based on the organ involvement, allows to conjugate the pathogenetic mechanisms of tissue injury with the proposed predictors, particularly autoantibodies and other serum biomarkers. Ultimately, we are convinced that precision medicine is the ideal guide to manage a complex condition such as SSc for which available treatments are largely unsatisfactory.

Hematologic setpoints are a stable and patient-specific deep phenotype

The complete blood count is an important screening tool for healthy adults and is the most commonly ordered test at periodic physical exams. However, results are usually interpreted relative to one-size-fits-all reference intervals, undermining the goal of precision medicine to tailor medical care to the needs of individual patients based on their unique characteristics. Here we show that standard complete blood count indices in healthy adults have robust homeostatic setpoints that are patient-specific and stable, with the typical healthy adult's set of 9 blood count setpoints distinguishable from 98% of others, and with these differences persisting for decades. These setpoints reflect a deep physiologic phenotype, enabling improved detection of both acquired and genetic determinants of hematologic regulation, including discovery of multiple novel loci via GWAS analyses. Patient-specific reference intervals derived from setpoints enable more accurate personalized risk assessment, and the setpoints themselves are significantly correlated with mortality risk, providing new opportunities to enhance patient-specific screening and early intervention. This study shows complete blood count setpoints are sufficiently stable and patient-specific to help realize the promise of precision medicine for healthy adults.

Wearable sensor platforms for real-time monitoring and early warning of metabolic disorders in humans

Nowadays, the prevalence of metabolic syndromes (MSs) has attracted increasing concerns as it is closely related to overweight and obesity, physical inactivity and overconsumption of energy, making the diagnosis and real-time monitoring of the physiological range essential and necessary for avoiding illness due to defects in the human body such as higher risk of cardiovascular disease, diabetes, stroke and diseases related to artery walls. However, the current sensing techniques are inconvenient and do not continuously monitor the health status of humans. Alternatively, the use of recent wearable device technology is a preferable method for the prevention of these diseases. This can enable the monitoring of the health status of humans in different health domains, including environment and structure. The use wearable devices with the purpose of facilitating rapid treatment and real-time monitoring can decrease the prevalence of MS and long-time monitor the health status of patients. This review highlights the recent advances in wearable sensors toward continuous monitoring of blood pressure and blood glucose, and further details the monitoring of abnormal obesity, triglycerides and HDL. We also discuss the challenges and future prospective of monitoring MS in humans.

Population Pharmacogenomics for Health Equity

Health equity means the opportunity for all people and populations to attain optimal health, and it requires intentional efforts to promote fairness in patient treatments and outcomes. Pharmacogenomic variants are genetic differences associated with how patients respond to medications, and their presence can inform treatment decisions. In this perspective, we contend that the study of pharmacogenomic variation within and between human populations-population pharmacogenomics-can and should be leveraged in support of health equity. The key observation in support of this contention is that racial and ethnic groups exhibit pronounced differences in the frequencies of numerous pharmacogenomic variants, with direct implications for clinical practice. The use of race and ethnicity to stratify pharmacogenomic risk provides a means to avoid potential harm caused by biases introduced when treatment regimens do not consider genetic differences between population groups, particularly when majority group genetic profiles are assumed to hold for minority groups. We focus on the mitigation of adverse drug reactions as an area where population pharmacogenomics can have a direct and immediate impact on public health.

Virtual twin for healthcare management

Healthcare is increasingly fragmented, resulting in escalating costs, patient dissatisfaction, and sometimes adverse clinical outcomes. Strategies to decrease healthcare fragmentation are therefore attractive from payer and patient perspectives. In this commentary, a patient-centered smart phone application called Virtual Twin for Healthcare Management (VTHM) is proposed, including its organizational layout, basic functionality, and potential clinical applications. The platform features a virtual twin hub that displays the body and its health data. This is a physiologically based human model that is "virtualized" for the patient based on their unique genetic, molecular, physiological, and disease characteristics. The spokes of the system are a full service and interoperable electronic-health record, accessible to healthcare providers with permission on any device with internet access. Theoretical case studies based on real scenarios are presented to show how VTHM could potentially improve patient care and clinical efficiency. Challenges that must be overcome to turn VTHM into reality are also briefly outlined. Notably, the VTHM platform is designed to operationalize current and future precision medicine initiatives, such as access to molecular diagnostic results, pharmacogenomics-guided prescribing, and model-informed precision dosing.

Personalised simulation of hemodynamics in cerebrovascular disease: lessons learned from a study of diagnostic accuracy

Intracranial atherosclerotic disease (ICAD) poses a significant risk of subsequent stroke but current prevention strategies are limited. Mechanistic simulations of brain hemodynamics offer an alternative precision medicine approach by utilising individual patient characteristics. For clinical use, however, current simulation frameworks have insufficient validation. In this study, we performed the first quantitative validation of a simulation-based precision medicine framework to assess cerebral hemodynamics in patients with ICAD against clinical standard perfusion imaging. In a retrospective analysis, we used a 0-dimensional simulation model to detect brain areas that are hemodynamically vulnerable to subsequent stroke. The main outcome measures were sensitivity, specificity, and area under the receiver operating characteristics curve (ROC AUC) of the simulation to identify brain areas vulnerable to subsequent stroke as defined by quantitative measurements of relative mean transit time (relMTT) from dynamic susceptibility contrast MRI (DSC-MRI). In 68 subjects with unilateral stenosis >70% of the internal carotid artery (ICA) or middle cerebral artery (MCA), the sensitivity and specificity of the simulation were 0.65 and 0.67, respectively. The ROC AUC was 0.68. The low-to-moderate accuracy of the simulation may be attributed to assumptions of Newtonian blood flow, rigid vessel walls, and the use of time-of-flight MRI for geometric representation of subject vasculature. Future simulation approaches should focus on integrating additional patient data, increasing accessibility of precision medicine tools to clinicians, addressing disease burden disparities amongst different populations, and quantifying patient benefit. Our results underscore the need for further improvement of mechanistic simulations of brain hemodynamics to foster the translation of the technology to clinical practice.

Next-Generation Sequencing of Breast Cancer in the Neoadjuvant Setting

INTRODUCTION

Many patients with locally advanced breast cancer are proposed to neoadjuvant chemotherapy (NAT) before surgery. Only some of them achieve a pathological complete response (pCR). The determination of gene somatic alterations using next-generation sequencing (NGS) in the non-pCR tumors is important, in order to identify potential opportunities of treatment for the patients, if targeted therapies are available.

METHODS

Breast cancer tissue samples of 31 patients, collected before NAT, were analyzed by NGS using the Oncomine™ Comprehensive Assay Plus (OCA-Plus) panel.

RESULTS

Twelve patients achieved pCR after NAT. ERBB2 gene alterations were the most frequent in this cohort of pCR patients, followed by BRCA 1 and 2, MYC, TP53, PIK3CA, and MET alterations. Tumors that did not achieve a pCR were mainly triple negative. In this subgroup some BRCA 1 and 2 and PIK3CA gene alterations were identified, as well as TP53 mutations. The NGS panel employed in this study also allowed for the determination of tumor mutation burden (TMB).

CONCLUSION

This study showcases the significance of employing comprehensive genomic testing in breast cancer cases, primarily due to the scarcity of specific target assays. The detection of somatic mutations, coupled with the availability of targeted therapies, holds promise as a potential therapeutic avenue to enhance tumor response rates during NAT, or as a complementary treatment following surgery. Moreover, evaluating the TMB in non-pCR samples could serve as a valuable criterion for selecting patients suitable for immunotherapy. Further exploration through clinical trials is imperative to investigate these prospects.