Contemporary hormone therapy with LHRH agonists for prostate cancer: avoiding osteoporosis and fracture.

© 2015 Polish Urological Association. All Rights Reserved.Introduction Prostate cancer is a large clinical burden across Europe. It is, in fact, the most common cancer in males, accounting for more than 92,300 deaths annually throughout the continent. Prostate cancer is androgen-sensitive; thus an androgen deprivation therapy (ADT) is often used for treatment by reducing androgen to castrate levels. Several ADT agents have achieved benefits with effective palliation, but, unfortunately, severe adverse events are frequent. Contemporary ADT (Luteinising Hormone Releasing Hormone agonist - LHRHa injections) can result in side effects that include osteoporosis and fractures, compromising quality of life and survival.  Methods In this review we analysed the associated bone toxicity consequent upon contemporary ADT and based on the literature and our own experience we present future perspectives that seek to mitigate this associated toxicity both by development of novel therapies and by better identification and prediction of fracture risk. Results Preliminary results indicate that parenteral oestrogen can mitigate associated osteoporotic risk and that CT scans could provide a more accurate indicator of overall bone quality and hence fracture risk.  Conclusions As healthcare costs increase globally, cheap and effective alternatives that achieve ADT, but mitigate or avoid such bone toxicities, will be needed. More so, innovative techniques to improve both the measurement and the extent of this toxicity, by assessing bone health and prediction of fracture risk, are also required

Cell geometry across the ring structure of Sitka spruce.

For wood to be used to its full potential as an engineering material, it is necessary to quantify links between its cell geometry and the properties it exhibits at bulk scale. Doing so will make it possible to predict timber properties crucial to engineering, such as mechanical strength and stiffness, and the resistance to fluid flow, and to inform strategies to improve those properties as required, as well as to measure the effects of interventions such as genetic manipulation and chemical modification. Strength, stiffness and permeability of timber all derive from the geometry of its cells, and yet current practice is to predict them based on properties, such as bulk density, that do not directly describe the cell structure. This work explores links between micro-computed tomography data for structural-size pieces of wood, which show the variation of porosity across the wood's ring structure, and high-resolution tomography showing the geometry of the cells, from which we measure cell length, lumen area, porosity, cell wall thickness and the number density of cells. High-resolution scans, while informative, are time-consuming and expensive to run on a large number of samples at the scale of building components. By scanning the same volume of timber at both low and high resolutions (high-resolution scans over a near-continuous volume of timber of approx. 20 mm3 at 15 μm3 per voxel), we are able to demonstrate correlations between the measurements at the two different resolutions, reveal the physical basis for these correlations, and demonstrate that the data from the low-resolution scan can be used to estimate the variation in (small-scale) cell geometry throughout a structural-size piece of wood.This work was funded in major part by a Leverhulme Trust Programme Grant. The X-ray imaging work was supported by the Advanced Imaging of Materials (AIM) facility (EPSRC Grant No. EP/M028267/1), the European Social Fund (ESF) through the European Union’s Convergence programme administered by the Welsh Government

Natural language processing for mimicking clinical trial recruitment in critical care: a semi-automated simulation based on the LeoPARDS trial

Clinical trials often fail to recruit an adequate number of appropriate patients. Identifying eligible trial participants is resource-intensive when relying on manual review of clinical notes, particularly in critical care settings where the time window is short. Automated review of electronic health records (EHR) may help, but much of the information is in free text rather than a computable form. We applied natural language processing (NLP) to free text EHR data using the CogStack platform to simulate recruitment into the LeoPARDS study, a clinical trial aiming to reduce organ dysfunction in septic shock. We applied an algorithm to identify eligible patients using a moving 1-hour time window, and compared patients identified by our approach with those actually screened and recruited for the trial, for the time period that data were available. We manually reviewed records of a random sample of patients identified by the algorithm but not screened in the original trial. Our method identified 376 patients, including 34 patients with EHR data available who were actually recruited to LeoPARDS in our centre. The sensitivity of CogStack for identifying patients screened was 90% (95% CI 85%, 93%). Of the 203 patients identified by both manual screening and CogStack, the index date matched in 95 (47%) and CogStack was earlier in 94 (47%). In conclusion, analysis of EHR data using NLP could effectively replicate recruitment in a critical care trial, and identify some eligible patients at an earlier stage, potentially improving trial recruitment if implemented in real time

Correction to: Identifying Efficient Transport Pathways in Early‑Wood Timber: Insights from 3D X‑ray CT Imaging of Softwood in the Presence of Flow (Transport in Porous Media, (2021), 136, 3, (813-830), 10.1007/s11242-020-01540-8)

A correction to this paper has been published: https://doi.org/10.1007/s11242-021-01569-3The contributions of TR, GW, DUS, OAS, MHR and PFL were funded by a Leverhulme Trust Programme Gran

Shoulder pain due to cervical radiculopathy: an underestimated long-term complication of herpes zoster virus reactivation?

Purpose To evaluate if herpes zoster virus (HZV) reactivation may be considered in the aetiology of cervical radiculopathy. Methods The study group was composed of 110 patients (52 M-58F;mean age ± SD:46.5 ± 6.12; range:40-73) with a clinical diagnosis of cervical radiculopathy. Patients with signs of chronic damage on neurophysiological studies were submitted to an X-ray and to an MRI of the cervical spine in order to clarify the cause of the cervical radiculopathy and were investigated for a possible reactivation of HZV; HZV reactivation was considered as “recent” or “antique” if it occurs within or after 24 months from the onset of symptoms, respectively. Data were submitted to statistics. Results Thirty-eight patients (34,5%,16 M-22F) had a history of HZV reactivation: four (2 M-2F) were “recent” and 34 (14 M-20F) were “antique”. In 68 of 110 participants (61,8%,30 M-38F), pathological signs on X-ray and/or MRI of the cervical spine appeared; in the remaining 42 (38,2%,22 M-20F) X-ray and MRI resulted as negative. Among patients with HZV reactivation, seven (18,4%) had a “positive” X-ray-MRI while in 31 (81,6%) the instrumental exams were considered as negative. The prevalence of “antique” HZV reactivations was statistically greater in the group of patients with no pathological signs on X-ray/MRI of the cervical spine with respect to the group with a pathological instrumental exam (p < 0.01). Conclusions It may be useful to investigate the presence of a positive history of HZV reactivation and to consider it as a long-term complication of a cervical root inflammation especially in patients in which X-ray and MRI of the cervical spine did not show pathological findings

Evolution of Taxis Responses in Virtual Bacteria: Non-Adaptive Dynamics

Bacteria are able to sense and respond to a variety of external stimuli, with responses that vary from stimuli to stimuli and from species to species. The best-understood is chemotaxis in the model organism Escherichia coli, where the dynamics and the structure of the underlying pathway are well characterised. It is not clear, however, how well this detailed knowledge applies to mechanisms mediating responses to other stimuli or to pathways in other species. Furthermore, there is increasing experimental evidence that bacteria integrate responses from different stimuli to generate a coherent taxis response. We currently lack a full understanding of the different pathway structures and dynamics and how this integration is achieved. In order to explore different pathway structures and dynamics that can underlie taxis responses in bacteria, we perform a computational simulation of the evolution of taxis. This approach starts with a population of virtual bacteria that move in a virtual environment based on the dynamics of the simple biochemical pathways they harbour. As mutations lead to changes in pathway structure and dynamics, bacteria better able to localise with favourable conditions gain a selective advantage. We find that a certain dynamics evolves consistently under different model assumptions and environments. These dynamics, which we call non-adaptive dynamics, directly couple tumbling probability of the cell to increasing stimuli. Dynamics that are adaptive under a wide range of conditions, as seen in the chemotaxis pathway of E. coli, do not evolve in these evolutionary simulations. However, we find that stimulus scarcity and fluctuations during evolution results in complex pathway dynamics that result both in adaptive and non-adaptive dynamics depending on basal stimuli levels. Further analyses of evolved pathway structures show that effective taxis dynamics can be mediated with as few as two components. The non-adaptive dynamics mediating taxis responses provide an explanation for experimental observations made in mutant strains of E. coli and in wild-type Rhodobacter sphaeroides that could not be explained with standard models. We speculate that such dynamics exist in other bacteria as well and play a role linking the metabolic state of the cell and the taxis response. The simplicity of mechanisms mediating such dynamics makes them a candidate precursor of more complex taxis responses involving adaptation. This study suggests a strong link between stimulus conditions during evolution and evolved pathway dynamics. When evolution was simulated under conditions of scarce and fluctuating stimulus conditions, the evolved pathway contained features of both adaptive and non-adaptive dynamics, suggesting that these two types of dynamics can have different advantages under distinct environmental circumstances

Genome-Wide Characterization of Menin-Dependent H3K4me3 Reveals a Specific Role for Menin in the Regulation of Genes Implicated in MEN1-Like Tumors

Inactivating mutations in the MEN1 gene predisposing to the multiple endocrine neoplasia type 1 (MEN1) syndrome can also cause sporadic pancreatic endocrine tumors. MEN1 encodes menin, a subunit of MLL1/MLL2-containing histone methyltransferase complexes that trimethylate histone H3 at lysine 4 (H3K4me3). The importance of menin-dependent H3K4me3 in normal and transformed pancreatic endocrine cells is unclear. To study the role of menin-dependent H3K4me3, we performed in vitro differentiation of wild-type as well as menin-null mouse embryonic stem cells (mESCs) into pancreatic islet-like endocrine cells (PILECs). Gene expression analysis and genome-wide H3K4me3 ChIP-Seq profiling in wild-type and menin-null mESCs and PILECs revealed menin-dependent H3K4me3 at the imprinted Dlk1-Meg3 locus in mESCs, and all four Hox loci in differentiated PILECs. Specific and significant loss of H3K4me3 and gene expression was observed for genes within the imprinted Dlk1-Meg3 locus in menin-null mESCs and the Hox loci in menin-null PILECs. Given that the reduced expression of genes within the DLK1-MEG3 locus and the HOX loci is associated with MEN1-like sporadic tumors, our data suggests a possible role for menin-dependent H3K4me3 at these genes in the initiation and progression of sporadic pancreatic endocrine tumors. Furthermore, our investigation also demonstrates that menin-null mESCs can be differentiated in vitro into islet-like endocrine cells, underscoring the utility of menin-null mESC-derived specialized cell types for genome-wide high-throughput studies

A cautionary tale of virus and disease

The recent identification of the gammaretrovirus XMRV and a second gammaretrovirus of a different subtype in chronic fatigue syndrome has aroused much interest, not least among sufferers. However, it remains highly controversial whether the detection of these viruses represents true infection or laboratory artifacts

The ‘new normality’ in research? What message are we conveying our medical students?

The impact of COVID-19 on medical education has been mainly viewed from the perspective of the imposed transition from face-to- face to online delivery of information and the inforced stopping of practical teaching in hospitals.1-5 However, unfortunately, the deleterious effects of COVID-19 on how research findings are obtained, communicated and valued needs also careful consideration. Whilst teaching students that it is a genuinely exciting and unique time to be in medicine, as teachers of a subject entitled ‘Introduction to Research’ to second-year medical students, we feel particularly worried about what the handling of the pandemia is transmitting our future physicians. Now, more than ever before, scholars need to reaffirm the importance on how research findings are obtained and communicated

Metabolomics to unveil and understand phenotypic diversity between pathogen populations

Visceral leishmaniasis is caused by a parasite called Leishmania donovani, which every year infects about half a million people and claims several thousand lives. Existing treatments are now becoming less effective due to the emergence of drug resistance. Improving our understanding of the mechanisms used by the parasite to adapt to drugs and achieve resistance is crucial for developing future treatment strategies. Unfortunately, the biological mechanism whereby Leishmania acquires drug resistance is poorly understood. Recent years have brought new technologies with the potential to increase greatly our understanding of drug resistance mechanisms. The latest mass spectrometry techniques allow the metabolome of parasites to be studied rapidly and in great detail. We have applied this approach to determine the metabolome of drug-sensitive and drug-resistant parasites isolated from patients with leishmaniasis. The data show that there are wholesale differences between the isolates and that the membrane composition has been drastically modified in drug-resistant parasites compared with drug-sensitive parasites. Our findings demonstrate that untargeted metabolomics has great potential to identify major metabolic differences between closely related parasite strains and thus should find many applications in distinguishing parasite phenotypes of clinical relevance