Sex-difference of multifactorial intervention on cardiovascular and mortality risk in DKD: post-hoc analysis of a randomised clinical trial.

OBJECTIVE: Women with type 2 diabetes experience higher cardiovascular and mortality risk than men possibly because of a sub-optimal cardio-protective treatment. We evaluated whether an intensive multifactorial therapy (MT) produces similar protective effect on development of adverse outcomes in women and men. RESEARCH DESIGN AND METHODS: Nephropathy in Diabetes type 2 study is an open-label cluster randomized trial comparing the effect of Usual Care (UC) or MT of main cardiovascular risk factors (blood pressure < 130/80 mmHg, HbA1c < 7%, LDL < 100 mg/dL, and total cholesterol < 175 mg/dL) on cardiovascular and mortality risk in patients with type 2 diabetes. In this post-hoc analysis, we stratified patients by sex to compare the occurrence of MACEs (primary endpoint) and all-cause death (secondary endpoint) between women (104 MT and 105 UC) and men (103 MT and 83 UC). RESULTS: Achievement of therapeutic goals was similar by sex, with 44% and 47% of women and men in MT achieving at least 3 targets vs. 16% and 20% of women and men in UC. During a median follow-up of 13.0 years, we recorded 262 MACE (48.5% in women) and 189 deaths (53.6% in women). Compared to the UC group, the risk of MACE in the MT group was reduced by 52% in women and by 44% in men (P = 0.11). Conversely, the reduction in mortality risk by MT was greater in women (44% versus 12%, P = 0.019). CONCLUSIONS: MT similarly reduces the risk of MACEs in either sex. This therapeutic approach is associated with a survival advantage in women as compared with men and it may represent an important rationale to motivate physicians in overcoming their therapeutic inertia often encountered in female patients as well as to encourage patients of both sexes at improving their adherence to multidrug therapy.

An adversarial learning approach to generate pressure support ventilation waveforms for asynchrony detection.

BACKGROUND AND OBJECTIVE: Mechanical ventilation is a life-saving treatment for critically-ill patients. During treatment, patient-ventilator asynchrony (PVA) can occur, which can lead to pulmonary damage, complications, and higher mortality. While traditional detection methods for PVAs rely on visual inspection by clinicians, in recent years, machine learning models are being developed to detect PVAs automatically. However, training these models requires large labeled datasets, which are difficult to obtain, as labeling is a labour-intensive and time-consuming task, requiring clinical expertise. Simulating the lung-ventilator interactions has been proposed to obtain large labeled datasets to train machine learning classifiers. However, the obtained data lacks the influence of different hardware, of servo-controlled algorithms, and different sources of noise. Here, we propose VentGAN, an adversarial learning approach to improve simulated data by learning the ventilator fingerprints from unlabeled clinical data. METHODS: In VentGAN, the loss functions are designed to add characteristics of clinical waveforms to the generated results, while preserving the labels of the simulated waveforms. To validate VentGAN, we compare the performance for detection and classification of PVAs when training a previously developed machine learning algorithm with the original simulated data and with the data generated by VentGAN. Testing is performed on independent clinical data labeled by experts. The McNemar test is applied to evaluate statistical differences in the obtained classification accuracy. RESULTS: VentGAN significantly improves the classification accuracy for late cycling, early cycling and normal breaths (p< 0.01); no significant difference in accuracy was observed for delayed inspirations (p = 0.2), while the accuracy decreased for ineffective efforts (p< 0.01). CONCLUSIONS: Generation of realistic synthetic data with labels by the proposed framework is feasible and represents a promising avenue for improving training of machine learning models.

Evaluation of the accuracy of established patient inspiratory effort estimation methods during mechanical support ventilation.

There is a clinical need for monitoring inspiratory effort to prevent lung- and diaphragm injury in patients who receive supportive mechanical ventilation in an Intensive Care Unit. Different pressure-based techniques are available to estimate this inspiratory effort at the bedside, but the accuracy of their effort estimation is uncertain since they are all based on a simplified linear model of the respiratory system, which omits gas compressibility of air, and the viscoelasticity and nonlinearities of the respiratory system. The aim of this in-silico study was to provide an overview of the pressure-based estimation techniques and to evaluate their accuracy using a more sophisticated model of the respiratory system and ventilator. The influence of the following parameters on the accuracy of the pressure-based estimation techniques was evaluated using the in-silico model: 1) the patient's respiratory mechanics 2) PEEP and the inspiratory pressure of the ventilator 3) gas compressibility of air 4) viscoelasticity of the respiratory system 5) the strength of the inspiratory effort. The best-performing technique in terms of accuracy was the whole breath occlusion. The average error and maximum error were the lowest for all patient archetypes. We found that the error was related to the expansion of gas in the breathing set and lungs and respiratory compliance. However, concerns exist that other factors not included in the model, such as a changed muscle-force relation during an occlusion, might influence the true accuracy. The estimation techniques based on the esophageal pressure showed an error related to the viscoelastic element in the model which leads to a higher error than the occlusion. The error of the esophageal pressure-based techniques is therefore highly dependent on the pathology of the patient and the settings of the ventilator and might change over time while a patient recovers or becomes more ill.

3D printing and 3D bioprinting technology in medicine: ethical and legal issues.

Abstract: There has been a surge of interest in new technologies in medicine because of their promising clinical applications. Extensive research on additive manufacturing and its applications in the medical field has been carried out with good results and very high expectations. Due to their disruptive nature and potential, 3D printing and even more 3D bioprinting raise many ethical and safety concerns that need to be adequately addressed to provide good regulation before entering clinical practice. This article aims to highlight the general ethical concerns associated with the use of additive manufacturing in medicine and the lack of current international regulatory directives to guide these experiments. Transparency about how these new medical devices are regulated and approved is a fundamental requirement to promote and improve public trust, efficiency, safety and quality.

Death occurred due to undiagnosed systemic amyloidosis: a case report.

Abstract: Amyloidosis is a disorder related to errors in protein folding. We present a clinical case of systemic amyloidosis manifesting as hypotension, tachycardia, pain, weight loss, asthenia, anorexia, dysphagia, and mood deflection in a 49-year-old-year-old woman with a previous clinical history of articular and muscular pain, correlated to suspected seronegative arthritis. The blood test revealed kidney insufficiency, an electrocardiogram identified low voltages of the peripheral leads and T waves anomalies. A serum protein electrophoresis revealed the presence of high levels of monoclonal kappa free chains. The woman started to have a sense of suffocation, and after one week she was found dead in her bed. After the autopsy, the results of Congo red staining of the myocardium were characteristic of amyloid. According to the autoptic and the histological examination, death occurred due to acute cardiac and respiratory arrest secondary to amyloid cardiomyopathy in a patient with undiagnosed systemic amyloidosis.

A model-based approach to generating annotated pressure support waveforms.

Large numbers of asynchronies during pressure support ventilation cause discomfort and higher work of breathing in the patient, and are associated with an increased mortality. There is a need for real-time decision support to detect asynchronies and assist the clinician towards lung-protective ventilation. Machine learning techniques have been proposed to detect asynchronies, but they require large datasets with sufficient data diversity, sample size, and quality for training purposes. In this work, we propose a method for generating a large, realistic and labeled, synthetic dataset for training and validating machine learning algorithms to detect a wide variety of asynchrony types. We take a model-based approach in which we adapt a non-linear lung-airway model for use in a diverse patient group and add a first-order ventilator model to generate labeled pressure, flow, and volume waveforms of pressure support ventilation. The model was able to reproduce basic measured lung mechanics parameters. Experienced clinicians were not able to differentiate between the simulated waveforms and clinical data (P = 0.44 by Fisher's exact test). The detection performance of the machine learning trained on clinical data gave an overall comparable true positive rate on clinical data and on simulated data (an overall true positive rate of 94.3% and positive predictive value of 93.5% on simulated data and a true positive rate of 98% and positive predictive value of 98% on clinical data). Our findings demonstrate that it is possible to generate labeled pressure and flow waveforms with different types of asynchronies.

A Model-based Approach to Generating Annotated Pressure Support Waveforms.

During pressure support ventilation, every breath is triggered by the patient. Mismatches between the patient and the ventilator are called asynchronies. It has been reported that large numbers of asynchronies may be harmful and may lead to increased mortality. Automatic asynchrony detection and classification, with subsequent feedback to clinicians, will improve lung ventilation and, possibly, patient outcome. Machine learning techniques have been used to detect asynchronies. However, large, diverse and high-quality training and verification data sets are needed. In this work, we propose a model for generating a large, realistic, labeled, synthetic dataset for training and testing machine learning algorithms to detect a wide variety of asynchrony types. Next to a morphological evaluation of the obtained waveforms, validation of the proposed model includes a test with a machine learning algorithm trained on clinical data.

Role of post mortem CT (PMCT) in high energy traumatic deaths.

BACKGROUND: Post Mortem Computed Tomography (PMCT) is being increasingly implemented in forensic field and could be an adjuvant to classic autopsies. In this study we evaluated the feasibility of complementation of conventional autopsy in trauma victims with PMCT. MATERIALS AND METHODS: A total of 21 subjects, who had sustained various types of blunt high-energy trauma, were selected from the casuistry of the Section of Legal Medicine at University of Pisa: before autopsy, a PMCT examination (Toshiba Aquilion 16 CT scanner) was performed, and after the acquisition of the raw images, MPR and VR reconstructions were performed with dedicated software. RESULTS: PMCT is more sensitive than conventional autopsy in detecting skeletal injuries, whilst autopsy constitutes the method of choice for the detection of thoracic and abdominal visceral injuries. CONCLUSIONS: PMCT should be considered a useful tool in addition to conventional autopsy in evaluating trauma victims: it detects further bone fractures in body parts difficult to investigate during autopsy (i.e. posterior regions), facilitating the pathologist in the reconstruction of events and in determining the cause of death.

A machine learning method for automatic detection and classification of patient-ventilator asynchrony.

Patients suffering from respiratory failure are often put on assisted mechanical ventilation. Patient-ventilator asynchrony (PVA) can occur during mechanical ventilation, which cause damage to the lungs and has been linked to increased mortality in the intensive care unit. In current clinical practice PVA is still detected using visual inspection of the air pressure, flow, and volume curves, which is time-consuming and sensitive to subjective interpretation. Correct detection of the patient respiratory efforts is needed to properly asses the type of asynchrony. Therefore, we propose a method for automatic detection of the patient respiratory efforts using a one-dimensional convolution neural network. The proposed method was able to detect patient efforts with a sensitivity and precision of 98.6% and 97.3% for the inspiratory efforts, and 97.7% and 97.2% for the expiratory efforts. Besides allowing detection of PVA, combining the estimated timestamps of patient's inspiratory and expiratory efforts with the timings of the mechanical ventilator further allows for classification of the asynchrony type. In the future, the proposed method could support clinical decision making by informing clinicians on the quality of ventilation and providing actionable feedback for properly adjusting the ventilator settings.

Method for measurement of arterial compliance by fusion of oscillometry and pulse wave velocity.

Up until now estimation of arterial compliance has been performed either by analysis of arterial pressure changes with respect to volume changes or by inference based on pulse wave velocity (PWV). In this study we demonstrate the possibility of an approach to assess arterial compliance by fusing the two information sources namely the pressure/volume relationship obtained from oscillography and PWV data. The goal is to assess arterial properties easily and robustly, enhancing current hemodynamic monitoring. The approach requires as input signals: an electrocardiogram (ECG), a photo- plethysmogram (PPG) and the arterial oscillation as measured during non-invasive blood pressure measurements based on oscillometry with a cuff. These signals are fused by an algorithm using Bayesian principles underpinned by a physiological model. In our simulations, we demonstrate the feasibility to infer arterial compliance by our proposed strategy. A very first measurement on a healthy volunteer supports our findings from the simulation.Clinical Relevance- Arterial compliance/stiffness is recognized as a key hemodynamic parameter, which is not easily accessible and not a standard parameter currently. The presented method and obtained results are encouraging for future research in this area.

Changes in cardiovascular performance, biochemistry, gastric motility and muscle temperature induced by acute exercise on a treadmill in healthy military dogs.

Changes in physiological parameters that are induced by acute exercise on a treadmill in healthy military dogs have not been thoroughly investigated, especially with regard to age. This study investigated the effects of acute exercise on a treadmill on cardiovascular function, biochemical parameters and gastric antral motility in military dogs. Thermography was used to assess variations in superficial hindlimb muscle temperature. Nine healthy dogs were distributed into three groups according to their age (Group I: 25 ± 7 months; Group II: 51 ± 12 months; Group III: 95 ± 10 months) and sequentially subjected to running exercise on a treadmill for 12 min (3.2 km/h at 0° incline for 4 min, 6.4 km/h at 0° incline for 4 min and 6.4 km/h at 10° incline for 4 min). Heart rate, systolic and diastolic arterial pressure (DAP), gastric motility, haematocrit and biochemical analyses were performed at rest and after each session of treadmill exercise. Infrared thermographic images of muscles in the pelvic member were taken. Exercise decreased DAP in Group I, increased systolic arterial pressure in Groups II and III and increased mean arterial pressure in Group III (all p < 0.05). After the exercise protocol, plasma creatine kinase and aspartate aminotransferase levels increased only in Group I (p < 0.05). Exercise increased heart rate and decreased the gastric motility of a solid meal at 180 min in all groups (all p < 0.05). Exercise also elevated temperature in the femoral biceps muscles in Group I compared with the older dogs. The results indicate that acute exercise decreased gastric motility in dogs, regardless of age, and caused more pronounced cardiovascular changes in older dogs than in younger dogs. Acute exercise also altered biochemical parameters and superficial hindlimb muscle temperature in younger military dogs.

A New Natural Antioxidant Mixture Protects against Oxidative and DNA Damage in Endothelial Cell Exposed to Low-Dose Irradiation.

Exposure to ionizing radiation during diagnostic procedures increases systemic oxidative stress and predisposes to higher risk of cancer and cardiovascular disease development. Many studies indicated that antioxidants protect against radiation-induced damage and have high efficacy and lack of toxicity in preventing radiation exposure damages. The purpose of this study was to investigate the in vitro protective effect of a new antioxidant mixture, named RiduROS, on oxidative stress generation and DNA double-strand breaks (DSBs) induced by low doses of X-rays in endothelial cells. Human umbilical vein endothelial cells (HUVEC) were treated with RiduROS mixture 24 h before a single exposure to X-rays at an absorbed dose of 0.25 Gy. The production of reactive oxygen species (ROS) was evaluated by fluorescent dye staining and nitric oxide (NO) by the Griess reaction, and DSBs were evaluated as number of γ-H2AX foci. We demonstrated that antioxidant mixture reduced oxidative stress induced by low dose of X-ray irradiation and that RiduROS pretreatment is more effective in protecting against radiation-induced oxidative stress than single antioxidants. Moreover, RiduROS mixture is able to reduce γ-H2AX foci formation after low-dose X-ray exposure. The texted mixture of antioxidants significantly reduced oxidative stress and γ-H2AX foci formation in endothelial cells exposed to low-dose irradiation. These results suggest that RiduROS could have a role as an effective radioprotectant against low-dose damaging effects.

Low threshold Fabry-Perot optofluidic resonator fabricated by femtosecond laser micromachining.

We report the realization and characterization of an optofluidic microlaser based on a Fabry-Perot resonator fabricated by exploiting two direct writing fabrication techniques: the femtosecond laser micromachining and the inkjet printing technology. In this way a standard Fabry-Perot cavity has been integrated into an optofluidic chip. When using rhodamine 6G dissolved in ethanol at concentration of 5∙10-3 mol/l, laser emission was detected at a threshold energy density of 1.8 µJ/mm2 at least one order of magnitude lower than state-of-the-art optofluidic lasers. Linewidth below ~0.6 nm was measured under these conditions with a quality factor Q~103. These performances and robustness of the device makes it an excellent candidate for biosensing, security and environment monitoring applications.

Acute effects of different degrees of ultra-endurance exercise on systemic inflammatory responses.

BACKGROUND: Intense physical stress might promote inflammatory responses, whereas a regular physical exercise has positive influence. Little is known on the acute metabolic and inflammatory responses to different levels of strenuous exercise in trained athletes. AIM: To compare the short-term effect of two different ultra-endurance competitions on the inflammatory profile in male triathletes. METHODS: We studied 14 Ironman (IR) and 13 Half Ironman (HIR) before and after their own specific race. We assessed body composition and measured blood cells, lipids, iron metabolism and plasma levels of some acute-phase cytokines and inflammatory markers. RESULTS: After the race, IR showed reduced total body water and fat-free mass, not related with the duration of exercise, and increased white cells and platelets; high-density lipoprotein levels also increased. IR, but not HIR, showed reduced iron levels, increased ferritin and transferrin, reduced % saturated transferrin. HIR showed higher basal interleukin (IL)-6, tumour necrosis factor (TNF)-α, IL-10, IL-1ß than IR; however, the post-performance rise was greater in IR. Irisin increased only in HIR and osteocalcin decreased in IR. In the whole study group, delta of white blood cells was directly related with delta of monocyte chemoattractant protein 1, and Δ ferritin was inversely related with Δosteocalcin. CONCLUSIONS: A single ultra-endurance competition induces an inflammatory response depending on the duration of physical effort, with increased acute-phase cytokines, and an altered iron metabolism. Irisin, whose biological meaning is still uncertain, seems to be associated with acute variations of some metabolic parameters.

Closed-form solution of the convolution integral in the magnetic resonance dispersion model for quantitative assessment of angiogenesis.

Prostate cancer (PCa) diagnosis and treatment is still limited due to the lack of reliable imaging methods for cancer localization. Based on the fundamental role played by angiogenesis in cancer growth and development, several dynamic contrast enhanced (DCE) imaging methods have been developed to probe tumor angiogenic vasculature. In DCE magnetic resonance imaging (MRI), pharmacokinetic modeling allows estimating quantitative parameters related to the physiology underlying tumor angiogenesis. In particular, novel magnetic resonance dispersion imaging (MRDI) enables quantitative assessment of the microvascular architecture and leakage, by describing the intravascular dispersion kinetics of an extravascular contrast agent with a dispersion model. According to this model, the tissue contrast concentration at each voxel is given by the convolution between the intravascular concentration, described as a Brownian motion process according to the convective-dispersion equation, with the interstitium impulse response, represented by a mono-exponential decay, and describing the contrast leakage in the extravascular space. In this work, an improved formulation of the MRDI method is obtained by providing an analytical solution for the convolution integral present in the dispersion model. The performance of the proposed method was evaluated by means of dedicated simulations in terms of estimation accuracy, precision, and computation time. Moreover, a preliminary clinical validation was carried out in five patients with proven PCa. The proposed method allows for a reduction by about 40% of computation time without any significant change in estimation accuracy and precision, and in the clinical performance.

Cell fate following ER stress: just a matter of "quo ante" recovery or death?

The endoplasmic reticulum (ER) is a complex and multifunctional organelle. It is the intracellular compartment of protein folding, a complex task, both facilitated and monitored by ER folding enzymes and molecular chaperones. The ER is also a stress-sensing organelle. It senses stress caused by disequilibrium between ER load and folding capacity and responds by activating signal transduction pathways, known as unfolded protein response (UPR). Three major classes of transducer are known, inositol-requiring protein-1 (IRE1), activating transcription factor-6 (ATF6), and protein kinase RNA (PKR)-like endoplasmic reticulum kinase (PERK), which sense with their endoluminal domain the state of protein folding, although the exact mechanism(s) involved is not entirely clear. Depending on whether the homeostatic response of the UPR is successful in restoring an equilibrium between ER load and protein folding or not, the two possible outcomes of the UPR so far considered have been life or death. Indeed, recent efforts have been devoted to understand the life/death switch mechanisms. However, recent data suggest that what appears to be a pure binary decision may in fact be more complex, and survival may be achieved at the expenses of luxury cell functions, such as expression of differentiation genes.

A micro-PET/CT approach using O-(2-[18F]fluoroethyl)-L-tyrosine in an experimental animal model of F98 glioma for BNCT.

The present study focuses on a micro-PET/CT application to be used for experimental Boron Neutron Capture Therapy (BNCT), which integrates, in the same frame, micro-CT derived anatomy and PET radiotracer distribution. Preliminary results have demonstrated that (18)F-fluoroethyl-tyrosine (FET)/PET allows the identification of the extent of cerebral lesions in F98 tumor bearing rat. Neutron autoradiography and α-spectrometry on axial tissues slices confirmed the tumor localization and extraction, after the administration of fructose-boronophenylalanine (BPA). Therefore, FET-PET approach can be used to assess the transport, the net influx, and the accumulation of FET, as an aromatic amino acid analog of BPA, in experimental animal model. Coregistered micro-CT images allowed the accurate morphological localization of the radiotracer distribution and its potential use for experimental BNCT.

Leishmania infantum: Lipophosphoglycan intraspecific variation and interaction with vertebrate and invertebrate hosts.

Interspecies variations in lipophosphoglycan (LPG) have been the focus of intense study over the years due its role in specificity during sand fly-Leishmania interaction. This cell surface glycoconjugate is highly polymorphic among species with variations in sugars that branch off the conserved Gal(ß1,4)Man(α1)-PO(4) backbone of repeat units. However, the degree of intraspecies polymorphism in LPG of Leishmania infantum (syn. Leishmania chagasi) is not known. In this study, intraspecific variation in the repeat units of LPG was evaluated in 16 strains of L. infantum from Brazil, France, Algeria and Tunisia. The structural polymorphism in the L. infantum LPG repeat units was relatively slight and consisted of three types: type I does not have side chains; type II has one ß-glucose residue that branches off the disaccharide-phosphate repeat units and type III has up to three glucose residues (oligo-glucosylated). The significance of these modifications was investigated during in vivo interaction of L. infantum with Lutzomyia longipalpis, and in vitro interaction of the parasites and respective LPGs with murine macrophages. There were no consequential differences in the parasite densities in sand fly midguts infected with Leishmania strains exhibiting type I, II and III LPGs. However, higher nitric oxide production was observed in macrophages exposed to glucosylated type II LPG.

High plasma levels of the soluble receptor for advanced glycation endproducts in patients with symptomatic carotid atherosclerosis.

BACKGROUND: Advanced glycation endproducts (AGEs), particularly carboxymethyl(lysine)-adducts (CML), exert part of their cellular effects by binding to a receptor, named receptor for AGEs (RAGE). The soluble form of this receptor (sRAGE) has been shown to have an athero-protective role. We hypothesized the existence of a relationship between the AGE-RAGE axis and the occurrence of symptoms related to carotid atherosclerosis in nondiabetic conditions. MATERIALS AND METHODS: We evaluated plasma levels of CML and sRAGE (by ELISA), and tissue levels (tAGEs and tRAGE, semiquantitatively, by immunohistochemistry) in endarterectomy carotid plaque tissue in 29 nondiabetic patients. At the time of surgery, 10 patients were asymptomatic and 19 were symptomatic. RESULTS: Plasma levels of sRAGE were higher in symptomatic patients than in asymptomatic patients [median (interquartile range): 676 (394-858) pg mL(-1) vs. 347 (284-479) pg mL(-1), P = 0.009]. In symptomatic patients, plasma levels of sRAGE correlated positively with CML (r = 0.60, P < 0.01), C-reactive protein (CRP) (r = 0.618, P < 0.01) and fibrinogen (r = 0.522, P<0.005), while in asymptomatic patients, no correlation was observed. Although tissue and plasma levels of AGEs and RAGE did not correlate between each other, tAGEs and tRAGE were also positively correlated only in symptomatic patients (chi(2) = 8.93, P = 0.003). CONCLUSIONS: Plasma levels of sRAGE are higher in symptomatic than asymptomatic carotid atherosclerosis. Higher levels of sRAGE in symptomatic patients may be markers of a higher degree of vascular inflammation in such patients.