Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses

The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined

The re-professionalization of the police in England and Wales

In this article contemporary police claims to professional status are analysed and related to a new structure of police regulation in England and Wales. It is argued that the notion of the police as a profession is not new and, unlike police and academic commentary, analysis of this subject, should draw on sociological understandings of professions. The wider policy context within which claims to professionalisation are made is also considered. It is argued that a new, loosely-coupled system of regulation has been developed in England and Wales. Policing’s professional body, the College of Policing, is central to this regulatory framework that has placed government at a distance from constabularies and police representative associations. Finally, some of the consequences of the hybrid system are considered and benefits of the framework of analysis proposed are discussed

Assessment of optimal strategies in a two-patch dengue transmission model with seasonality

Emerging and re-emerging dengue fever has posed serious problems to public health officials in many tropical and subtropical countries. Continuous traveling in seasonally varying areas makes it more difficult to control the spread of dengue fever. In this work, we consider a two-patch dengue model that can capture the movement of host individuals between and within patches using a residence-time matrix. A previous two-patch dengue model without seasonality is extended by adding host demographics and seasonal forcing in the transmission rates. We investigate the effects of human movement and seasonality on the two-patch dengue transmission dynamics. Motivated by the recent Peruvian dengue data in jungle/rural areas and coast/urban areas, our model mimics the seasonal patterns of dengue outbreaks in two patches. The roles of seasonality and residence-time configurations are highlighted in terms of the seasonal reproduction number and cumulative incidence. Moreover, optimal control theory is employed to identify and evaluate patch-specific control measures aimed at reducing dengue prevalence in the presence of seasonality. Our findings demonstrate that optimal patch-specific control strategies are sensitive to seasonality and residence-time scenarios. Targeting only the jungle (or endemic) is as effective as controlling both patches under weak coupling or symmetric mobility. However, focusing on intervention for the city (or high density areas) turns out to be optimal when two patches are strongly coupled with asymmetric mobility.ope

Image based machine learning for identification of macrophage subsets

Macrophages play a crucial rule in orchestrating immune responses against pathogens and foreign materials. Macrophages have remarkable plasticity in response to environmental cues and are able to acquire a spectrum of activation status, best exemplified by pro-inflammatory (M1) and anti-inflammatory (M2) phenotypes at the two ends of the spectrum. Characterisation of M1 and M2 subsets is usually carried out by quantification of multiple cell surface markers, transcription factors and cytokine profiles. These approaches are time consuming, require large numbers of cells and are resource intensive. In this study, we used machine learning algorithms to develop a simple and fast imaging-based approach that enables automated identification of different macrophage functional phenotypes using their cell size and morphology. Fluorescent microscopy was used to assess cell morphology of different cell types which were stained for nucleus and actin distribution using DAPI and phalloidin respectively. By only analysing their morphology we were able to identify M1 and M2 phenotypes effectively and could distinguish them from naïve macrophages and monocytes with an average accuracy of 90%. Thus we suggest high-content and automated image analysis can be used for fast phenotyping of functionally diverse cell populations with reasonable accuracy and without the need for using multiple markers

Tumour expression of leptin is associated with chemotherapy resistance and therapy-independent prognosis in gastro-oesophageal adenocarcinomas

Background: Cytotoxic chemotherapy remains the main systemic therapy for gastro-oesophageal adenocarcinoma, but resistance to chemotherapy is common, resulting in ineffective and often toxic treatment for patients. Predictive biomarkers for chemotherapy response would increase the probability of successful therapy, but none are currently recommended for clinical use. We used global gene expression profiling of tumour biopsies to identify novel predictive biomarkers for cytotoxic chemotherapy. Methods: Tumour biopsies from patients (n=14) with TNM stage IB–IV gastro-oesophageal adenocarcinomas receiving platinum-based combination chemotherapy were used as a discovery cohort and profiled with Affymetrix ST1.0 Exon Genechips. An independent cohort of patients (n=154) treated with surgery with or without neoadjuvant platinum combination chemotherapy and gastric adenocarcinoma cell lines (n=22) were used for qualification of gene expression profiling results by immunohistochemistry. A cisplatin-resistant gastric cancer cell line, AGS Cis5, and the oesophageal adenocarcinoma cell line, OE33, were used for in vitro validation investigations. Results: We identified 520 genes with differential expression (Mann–Whitney U, P<0.020) between radiological responding and nonresponding patients. Gene enrichment analysis (DAVID v6.7) was used on this list of 520 genes to identify pathways associated with response and identified the adipocytokine signalling pathway, with higher leptin mRNA associated with lack of radiological response (P=0.011). Similarly, in the independent cohort (n=154), higher leptin protein expression by immunohistochemistry in the tumour cells was associated with lack of histopathological response (P=0.007). Higher leptin protein expression by immunohistochemistry was also associated with improved survival in the absence of neoadjuvant chemotherapy, and patients with low leptin protein-expressing tumours had improved survival when treated by neoadjuvant chemotherapy (P for interaction=0.038). In the gastric adenocarcinoma cell lines, higher leptin protein expression was associated with resistance to cisplatin (P=0.008), but not to oxaliplatin (P=0.988) or 5fluorouracil (P=0.636). The leptin receptor antagonist SHLA increased the sensitivity of AGS Cis5 and OE33 cell lines to cisplatin. Conclusions: In gastro-oesophageal adenocarcinomas, tumour leptin expression is associated with chemoresistance but a better therapy-independent prognosis. Tumour leptin expression determined by immunohistochemistry has potential utility as a predictive marker of resistance to cytotoxic chemotherapy, and a prognostic marker independent of therapy in gastro-oesophageal adenocarcinoma. Leptin antagonists have been developed for clinical use and leptin and its associated pathways may also provide much needed novel therapeutic targets for gastro-oesophageal adenocarcinoma

Molecular bases of diabetic nephropathy

The determinant of the diabetic nephropathy is hyperglycemia, but hypertension and other genetic factors are also involved. Glomerulus is the focus of the injury, where mesangial cell proliferation and extracellular matrix occur because of the increase of the intra- and extracellular glucose concentration and overexpression of GLUT1. Sequentially, there are increases in the flow by the poliol pathway, oxidative stress, increased intracellular production of advanced glycation end products (AGEs), activation of the PKC pathway, increase of the activity of the hexosamine pathway, and activation of TGF-beta1. High glucose concentrations also increase angiotensin II (AII) levels. Therefore, glucose and AII exert similar effects in inducing extracellular matrix formation in the mesangial cells, using similar transductional signal, which increases TGF-beta1 levels. In this review we focus in the effect of glucose and AII in the mesangial cells in causing the events related to the genesis of diabetic nephropathy. The alterations in the signal pathways discussed in this review give support to the observational studies and clinical assays, where metabolic and antihypertensive controls obtained with angiotensin-converting inhibitors have shown important and additive effect in the prevention of the beginning and progression of diabetic nephropathy. New therapeutic strategies directed to the described intracellular events may give future additional benefits.O principal determinante da nefropatia diabética é a hiperglicemia, mas hipertensão e fatores genéticos também estão envolvidos. O glomérulo é o foco de lesão, onde proliferação celular mesangial e produção excessiva de matriz extracelular decorrem do aumento da glicose intracelular, por excesso de glicose extracelular e hiperexpressão de GLUT1. Seguem-se aumento do fluxo pela via dos polióis, estresse oxidativo intracelular, produção intracelular aumentada de produtos avançados da glicação não enzimática (AGEs), ativação da via da PKC, aumento da atividade da via das hexosaminas e ativação de TGF-beta1. Altas concentrações de glicose também aumentam angiotensina II (AII) nas células mesangiais por aumento intracelular da atividade da renina (ações intrácrinas, mediando efeitos proliferativos e inflamatórios diretamente). Portanto, glicose e AII exercem efeitos proliferativos celulares e de matriz extracelular nas células mesangiais, utilizando vias de transdução de sinais semelhantes, que levam a aumento de TGF-beta1. Nesse estudo são revisadas as vias que sinalizam os efeitos da glicose e AII nas células mesangiais em causar os eventos-chaves relacionados à gênese da glomerulopatia diabética. As alterações das vias de sinalização implicadas na glomerulopatia, aqui revisadas, suportam dados de estudos observacionais/ensaios clínicos, onde controle metabólico e anti-hipertensivo, especificamente com inibidores do sistema renina-angiotensina, têm-se mostrado importantes - e aditivos - na prevenção do início e progressão da nefropatia. Novas estratégias terapêuticas dirigidas aos eventos intracelulares descritos deverão futuramente promover benefício adicional.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)HC Instituto do Coração Unidade de HipertensãoUSP FMUniversidade Federal de São Paulo (UNIFESP), Escola Paulista de Medicina (EPM) Laboratório de NefrologiaFundação Universitária de Cardiologia Instituto de Cardiologia Laboratório de Cardiologia Molecular e CelularUNIFESP, EPM, Laboratório de NefrologiaSciEL

QCD and strongly coupled gauge theories : challenges and perspectives

We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe

Protein kinase C and cardiac dysfunction: a review

Heart failure (HF) is a physiological state in which cardiac output is insufficient to meet the needs of the body. It is a clinical syndrome characterized by impaired ability of the left ventricle to either fill or eject blood efficiently. HF is a disease of multiple aetiologies leading to progressive cardiac dysfunction and it is the leading cause of deaths in both developed and developing countries. HF is responsible for about 73,000 deaths in the UK each year. In the USA, HF affects 5.8 million people and 550,000 new cases are diagnosed annually. Cardiac remodelling (CD), which plays an important role in pathogenesis of HF, is viewed as stress response to an index event such as myocardial ischaemia or imposition of mechanical load leading to a series of structural and functional changes in the viable myocardium. Protein kinase C (PKC) isozymes are a family of serine/threonine kinases. PKC is a central enzyme in the regulation of growth, hypertrophy, and mediators of signal transduction pathways. In response to circulating hormones, activation of PKC triggers a multitude of intracellular events influencing multiple physiological processes in the heart, including heart rate, contraction, and relaxation. Recent research implicates PKC activation in the pathophysiology of a number of cardiovascular disease states. Few reports are available that examine PKC in normal and diseased human hearts. This review describes the structure, functions, and distribution of PKCs in the healthy and diseased heart with emphasis on the human heart and, also importantly, their regulation in heart failure

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median $z\sim 0.03$). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between $z\sim 0.6$ and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July