Theoretical Formulation Strategies towards Neutralizing Inter-individual Variability Associated with Tacrolimus Immunosuppressant Therapy: A Case Study on Nextgeneration Personalized Medicine.

Individualizing drug therapy and attaining maximum benefits of a drug devoid of adverse reactions is the benefit of personalized medicine. One of the important factors contributing to inter-individual variability is genetic polymorphism. As of now, dose titration is the only followed golden standard for implementing personalized medicine. Converting the genotypic data into an optimized dose has become easier now due to technology development. However, for many drugs, finding an individualized dose may not be successful, which further leads to a trial and error approach. These dose titration strategies are generally followed at the clinical level, and so industrial involvement and further standardizations are not feasible. On the other side, technologically driven pharmaceutical industries have multiple smart drug delivery systems which are underutilized towards personalized medicine. Transdisciplinary research with drug delivery science can additionally support the personalization by converting the traditional concept of "dose titration towards personalization" with novel "dose-cum-dosage form modification towards next-generation personalized medicine"; the latter approach is useful to overcome gene-based inter-individual variability by either blocking, to downregulate, or bypassing the biological protein generated by the polymorphic gene. This article elaborates an advanced approach to implementing personalized medicine with the support of novel drug delivery systems. As a case study, we further reviewed the genetic polymorphisms associated with tacrolimus and customized novel drug delivery systems to overcome these challenges factored towards personalized medicine for better clinical outcomes, thereby paving a new strategy for implementing personalized medicine for all other drug candidates.

Programa multidisciplinar para el diagnóstico y tratamiento de infección por virus de hepatitis C en prisiones / Multidisciplinary program for the diagnosis and treatment of hepatitis C virus infections in prisons

Objetivos: El diagnóstico y tratamiento del VHC en prisiones podría ser una estrategia para evitar su propagación. El objetivo es el desarrollo de un programa multidisciplinar de VHC en prisiones.Métodos: El programa se implantó en tres prisiones entre junio de 2016 – septiembre de 2019. El equipo sanitario estuvo compuesto por enfermeras, médicos y farmacéuticos hospitalarios. Se realizaron tests de serología para detección del VHC, determinándose carga viral y genotipado en casos positivos. Posteriormente, los reclusos con VHC fueron tratados. Se recogieron datos poblacionales y de tratamientos. La efectividad se evaluó mediante respuesta al final del tratamiento (RFT) y respuesta viral sostenida en semana 12 (RVS12). La tolerancia fue medida mediante efectos adversos irreversibles. Se compararon la prevalencia de VHC antes y después de implantar el programa.Resultados: La población global fue 2.065 presos. Los pacientes con serología positiva de VHC y carga viral detectable fueron 214. El 91,6% fueron varones. Los genotipos de VHC más frecuentes fueron 1a (31,3%) y 3 (26,2%). Los tratamientos más usados fueron glecaprevir/pibrentasvir (28,0%) y sofosbuvir/velpatasvir (22,9%). El 99,5% de los presidiarios tratados alcanzaron RFT. El 93,2% de pacientes valorables presentaron RVS12, con 5 recidivas. No se observaron casos de reinfección por VHC. Los efectos adversos irreversibles fueron observados en 2 pacientes. La prevalencia al comienzo del programa fue 10,4%, mientras que al final fue 1,7%.Conclusiones: El programa multidisciplinar de diagnóstico y tratamiento de VHC en prisiones consiguió una elevada curación de la enfermedad, evitando nuevas reinfecciones y con pocos efectos adversos irreversibles. (AU)

Aims: Diagnosis and treatment of HCV in prisons could be a strategy to prevent the spread of infection. The aim is the development of a multidisciplinary program for HCV in prisons.Method: The program was implemented in three prisons between June 2016 – September 2019. Health staff was composed of nurses, physicians and hospital pharmacists. Serology tests for the detection of VHC was performed. Viral load and genotyping were determined in the positive cases. Subsequently, inmates with HCV were treated. Population data and treatments were collected. The effectiveness was assessed by response at the end of treatment (EOT) and viral response sustained at week 12 (SVR12). Tolerance was measured by irreversible adverse effects. HCV prevalence before implementation of program was compared to with prevalence after the program.Results: Global population was 2,065 prisoners. Patients with positive HCV serology and detectable viral load was 214. The 91.6% of patients were male. The most frequent HCV genotypes were 1a (31.3%) and 3 (26.2%). Glecaprevir/pibrentasvir (28.0%) and sofosbuvir/velpatasvir (22.9%) were the most frequently used treatments. EOT was reached by 99.5% of inmates. SVR12 was presented by 93.2% valuable patients, with 5 recurrences. There were no HCV reinfections. Irreversible adverse effects associated were observed in 2 patients. The prevalence at the beginning of program was 10.4% while it was 1.7% at the end.Conclusions: The multidisciplinary program of diagnosis and treatment of HCV in prisons has achieved a high cure for the disease, avoiding new reinfections and few irreversible adverse effects. (AU)

Towards improved genetic diagnosis of human differences of sex development.

Despite being collectively among the most frequent congenital developmental conditions worldwide, differences of sex development (DSD) lack recognition and research funding. As a result, what constitutes optimal management remains uncertain. Identification of the individual conditions under the DSD umbrella is challenging and molecular genetic diagnosis is frequently not achieved, which has psychosocial and health-related repercussions for patients and their families. New genomic approaches have the potential to resolve this impasse through better detection of protein-coding variants and ascertainment of under-recognized aetiology, such as mosaic, structural, non-coding or epigenetic variants. Ultimately, it is hoped that better outcomes data, improved understanding of the molecular causes and greater public awareness will bring an end to the stigma often associated with DSD.

COVID-19 related interdisciplinary methods: Preventing errors and detecting research opportunities.

More than 130,000 peer-reviewed studies have been published within one year after COVID-19 emerged in many countries. This large and rapidly growing field may overwhelm the synthesizing abilities of both researchers and policy-makers. To provide a sinopsis, prevent errors, and detect cognitive gaps that may require interdisciplinary research methods, the literature on COVID-19 is summarized, twice. The overall purpose of this study is to generate a dialogue meant to explain the genesis of and/or find remedies for omissions and contradictions. The first review starts in Biology and ends in Policy. Policy is chosen as a destination because it is the setting where cognitive integration must occur. The second review follows the opposite path: it begins with stated policies on COVID-19 and then their assumptions and disciplinary relationships are identified. The purpose of this interdisciplinary method on methods is to yield a relational and explanatory view of the field -one strategy likely to be incomplete but usable when large bodies of literature need to be rapidly summarized. These reviews identify nine inter-related problems, research needs, or omissions, namely: (1) nation-wide, geo-referenced, epidemiological data collection systems (open to and monitored by the public); (2) metrics meant to detect non-symptomatic cases -e.g., test positivity-; (3) cost-benefit oriented methods, which should demonstrate they detect silent viral spreaders even with limited testing; (4) new personalized tests that inform on biological functions and disease correlates, such as cell-mediated immunity, co-morbidities, and immuno-suppression; (5) factors that influence vaccine effectiveness; (6) economic predictions that consider the long-term consequences likely to follow epidemics that growth exponentially; (7) the errors induced by self-limiting and/or implausible paradigms, such as binary and reductionist approaches; (8) new governance models that emphasize problem-solving skills, social participation, and the use of scientific knowledge; and (9) new educational programs that utilize visual aids and audience-specific communication strategies. The analysis indicates that, to optimally address these problems, disciplinary and social integration is needed. By asking what is/are the potential cause(s) and consequence(s) of each issue, this methodology generates visualizations that reveal possible relationships as well as omissions and contradictions. While inherently limited in scope and likely to become obsolete, these shortcomings are avoided when this 'method on methods' is frequently practiced. Open-ended, inter-/trans-disciplinary perspectives and broad social participation may help researchers and citizens to construct, de-construct, and re-construct COVID-19 related research.

Using the PhenX Toolkit to Select Standard Measurement Protocols for Your Research Study.

The goals of PhenX (consensus measures for Phenotypes and eXposures) are to promote the use of standard measurement protocols and to help investigators identify opportunities for collaborative research and cross-study analysis, thus increasing the impact of individual studies. The PhenX Toolkit (https://www.phenxtoolkit.org/) offers high-quality, well-established measurement protocols to assess phenotypes and exposures in studies with human participants. The Toolkit contains protocols representing 29 research domains and 6 specialty collections of protocols that add depth to the Toolkit in specific research areas (e.g., COVID-19, Social Determinants of Health [SDoH], Blood Sciences Research [BSR], Mental Health Research [MHR], Tobacco Regulatory Research [TRR], and Substance Abuse and Addiction [SAA]). Protocols are recommended for inclusion in the PhenX Toolkit by Working Groups of domain experts using a consensus process that includes input from the scientific community. For each PhenX protocol, the Toolkit provides a detailed description, the rationale for inclusion, and supporting documentation. Users can browse protocols in the Toolkit, search the Toolkit using keywords, or use Browse Protocols Tree to identify protocols of interest. The PhenX Toolkit provides data dictionaries compatible with the database of Genotypes and Phenotypes (dbGaP), Research Electronic Data Capture (REDCap) data submission compatibility, and data collection worksheets to help investigators incorporate PhenX protocols into their study design. The PhenX Toolkit provides resources to help users identify published studies that used PhenX protocols. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Using the PhenX Toolkit to support or extend study design.

Deciphering the Code: Stem Cell-Immune Function and Cardiac Regeneration.

The development of stem-cell-based and regenerative therapies for cardiovascular and other diseases has faced an unexpected roadblock in clinical translation [...].

From Reductionism to Reintegration: Solving society's most pressing problems requires building bridges between data types across the life sciences.

Decades of reductionist approaches in biology have achieved spectacular progress, but the proliferation of subdisciplines, each with its own technical and social practices regarding data, impedes the growth of the multidisciplinary and interdisciplinary approaches now needed to address pressing societal challenges. Data integration is key to a reintegrated biology able to address global issues such as climate change, biodiversity loss, and sustainable ecosystem management. We identify major challenges to data integration and present a vision for a "Data as a Service"-oriented architecture to promote reuse of data for discovery. The proposed architecture includes standards development, new tools and services, and strategies for career-development and sustainability.

Muertes en el buceo: un modelo de investigación multidisciplinar / Diving deaths: A multidisciplinary research model

El buceo es una de las actividades subacuáticas más practicadas en el litoral español. Los sistemas más comunes utilizados son el buceo con escafandra autónoma con circuito abierto, cerrado o semicerrado. Aunque hoy en día el buceo con escafandra autónoma se considera una práctica segura, cada año se describen nuevas muertes relacionadas con esta actividad. El ahogamiento es la principal causa de muerte, pero se han descrito otras, como la embolia gaseosa arterial, la enfermedad por descompresión, la enfermedad natural asociada y los traumatismos. Las autopsias de muertes relacionadas con el buceo son un gran desafío para cualquier patólogo forense, y es aconsejable poseer conocimientos sobre fisiopatología del buceo y experiencia en la práctica de técnicas de autopsia específicas. Colaborar con un equipo multidisciplinar proporciona información, evidencias y hallazgos patológicos suficientes para una investigación altamente calificada de los casos y poder resolver las principales cuestiones médico-legales

Diving is one of the most practiced underwater activities on the Spanish coast. The most common methods used in diving activities are SCUBA (self-contained underwater breathing apparatus), CCR (closed circuit rebreather) and SCR (semi-closed circuit rebreather). Although recreational diving is safe overall, diving accidents are potentially serious and even fatal. Despite all the precautions taken by divers, fatalities related to this activity are reported every year. Drowning is the main cause of death, but others have been described, such as arterial gas embolism, decompression sickness, natural pathology, and trauma. Autopsies of SCUBA diving-related deaths are a big challenge for any forensic pathologist. It is advisable to have some knowledge about diving physiopathology and experience in the practice of special autopsy techniques. Collaboration with a multidisciplinary team provides enough information, evidence and pathological findings for highly-qualified investigation of the incidents to be able to prevent similar incidents in the future

Managing a Large-Scale Multiomics Project: A Team Science Case Study in Proteogenomics.

Highly collaborative scientists are often called on to extend their expertise to different types of projects and to expand the scope and scale of projects well beyond their previous experience. For a large-scale project involving "big data" to be successful, several different aspects of the research plan need to be developed and tested, which include but are not limited to the experimental design, sample collection, sample preparation, metadata recording, technical capability, data acquisition, approaches for data analysis, methods for integration of different data types, recruitment of additional expertise as needed to guide the project, and strategies for clear communication throughout the project. To capture this process, we describe an example project in proteogenomics that built on our collective expertise and experience. Key steps included definition of hypotheses, identification of an appropriate clinical cohort, pilot projects to assess feasibility, refinement of experimental designs, and extensive discussions involving the research team throughout the process. The goal of this chapter is to provide the reader with a set of guidelines to support development of other large-scale multiomics projects.

Leveraging Basic Science for the Clinic-From Bench to Bedside.

Importance: The tools and insights of behavioral neuroscience grow apace, yet their clinical application is lagging. Observations: This article suggests that associative learning theory may be the algorithmic bridge to connect a burgeoning understanding of the brain with the challenges to the mind with which all clinicians and researchers are concerned. Conclusions and Relevance: Instead of giving up, talking past one another, or resting on the laurels of face validity, a consilient and collaborative approach is suggested: visiting laboratory meetings and clinical rounds and attempting to converse in the language of behavior and cognition to better understand and ultimately treat patients.

Artificial intelligence in radiology: relevance of collaborative work between radiologists and engineers for building a multidisciplinary team.

The use of artificial intelligence (AI) algorithms in the field of radiology is becoming more common. Several studies have demonstrated the potential utility of machine learning (ML) and deep learning (DL) techniques as aids for radiologists to solve specific radiological challenges. The decision-making process, the establishment of specific clinical or radiological targets, the profile of the different professionals involved in the development of AI solutions, and the relation with partnerships and stakeholders are only some of the main issues that have to be faced and solved prior to starting the development of radiological AI solutions. Among all the players in this multidisciplinary team, the communication between radiologists and data scientists is essential for a successful collaborative work. There are specific skills that are inherent to radiological and medical training that are critical for identifying anatomical or clinical targets as well as for segmenting or labelling lesions. These skills would then have to be transferred, explained, and taught to the data science experts to facilitate their comprehension and integration into ML or DL algorithms. On the other hand, there is a wide range of complex software packages, deep neural-network architectures, and data transfer processes for which radiologists need the expertise of software engineers and data scientists in order to select the optimal manner to analyse and post-process this amount of data. This paper offers a summary of the top five challenges faced by radiologists and data scientists including tips and tricks to build a successful AI team.

Anticoagulation for Patients With Atrial Fibrillation and End-Stage Renal Disease on Dialysis: A National Survey.

Patients with atrial fibrillation (AF) have a significant increased risk of embolic stroke. Patients with end-stage renal disease who are on dialysis have an increased risk of both embolic stroke and bleeding. Stroke-prevention studies with the use of anticoagulation for AF patients have excluded patients on dialysis, so there remains no consensus on their management. We developed and implemented a pan-Canadian multidisciplinary survey to explore the current beliefs and practices concerning patients with AF on dialysis. We developed an online investigator-designed survey with both quantitative and qualitative responses with the use of a secure university-affiliated electronic service. The survey was distributed to physicians via the QxMD platform and directly to internal medicine, cardiology, and nephrology residency program directors for distribution to faculty members. 130 participants responded, including 46 cardiologists, 45 nephrologists, 30 general internists, and 9 other physicians. The preferred anticoagulant was warfarin. The CHADS2 score used to initiate anticoagulation was highly variable, with specialties differing in use of a CHADS2 threshold of ≥ 1 (P < 0.001) and the impact of previous transient ischemic attack/stroke (P = 0.02). Calciphylaxis history affected the decision to prescribe anticoagulation. Specialties differed in thresholds used to consider direct oral anticoagulants for dialysis patients, with nephrologists more likely to prescribe anticoagulation at higher CHADS2 scores. Our survey demonstrated significant heterogeneity of anticoagulation use for stroke prevention in patients with AF on dialysis. Physician specialty and patient risk profiles contributed to the observed variability. This study reemphasises the need for clinical trials, large observational studies, and consensus guidelines to address evident equipoise.

Developing a program theory of patient engagement in patient-oriented research and the impacts on the health care system: protocol for a rapid realist review.

BACKGROUND: The patient-oriented research (POR) discourse has been criticized as being fragmented, lacking consistent terminology and having few evaluative studies. Our research team will use rapid realist review methodology to generate broad, process-based program theory regarding how partnering patients with researchers in POR generates an impact within a health care system. METHODS: This protocol for a rapid realist review will involve multiple steps, including research question development; preliminary program theory and search strategy development; study selection and appraisal; data extraction, analysis and synthesis; and program theory refinement. We will be guided by the Realist and Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) publication standards for realist synthesis. Unlike traditional reviews, a realist review aims to discover and understand causal processes that exist within a complex environment, asking questions regarding what works for whom, under what circumstances, how and why. Our multidisciplinary team consists of patient partners, health care professionals, a health sciences librarian and health services researchers. Patient partners are full research partners, supporting development of our guiding research question and identifying community partners and stakeholder groups to disseminate our findings. Patient partners will be asked to recommend literature sources, to review and vet our set of search terms, and to review, evaluate and reflect on our initial program theory in light of their personal, lived expertise. INTERPRETATION: We will share the results of our rapid realist review with community partners and stakeholder groups. We will also disseminate our program theory by means of publication in a peer-reviewed journal and presentation at scientific conferences.

Big Data Analysis y Machine Learning en medicina intensiva: identificando nuevos retos ético-jurídicos / Big Data Analysis and Machine Learning in Intensive Care Medicine: Identifying new ethical and legal challenges

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