Two Decades of Global Progress in Authorized Advanced Therapy Medicinal Products: An Emerging Revolution in Therapeutic Strategies

The introduction of advanced therapy medicinal products (ATMPs) to the global pharma market has been revolutionizing the pharmaceutical industry and has opened new routes for treating various types of cancers and incurable diseases. In the past two decades, a noticeable part of clinical practices has been devoting progressively to these products. The first step to develop such an ATMP product is to be familiar with other approved products to obtain a general view about this industry trend. The present paper depicts an overall perspective of approved ATMPs in different countries, while reflecting the degree of their success in a clinical point of view and highlighting their main safety issues and also related market size as a whole. In this regard, published articles regarding safety, efficacy, and market size of approved ATMPs were reviewed using the search engines PubMed, Scopus, and Google Scholar. For some products which the related papers were not available, data on the relevant company website were referenced. In this descriptive study, we have introduced and classified approved cell, gene, and tissue engineering-based products by different regulatory agencies, along with their characteristics, manufacturer, indication, approval date, related regulatory agency, dosage, product description, price and published data about their safety and efficacy. In addition, to gain insights about the commercial situation of each product, we have gathered accessible sale reports and market size information that pertain to some of these products

Nutrient composition of Algerian strawberry-tree fruits (Arbutus unedo L.)

Arbutus unedo L. (strawberry-tree fruit) is indigenous plant in North Africa with few published works about the composition of its fruits. For their valorization, morphological and chemical characterizations were carried out for two harvesting seasons of four different areas of Algeria. Materials and methods. Wild strawberry-tree fruits were collected in four different sites located in Tell Atlas, and two different seasons. Fruit size and shape, pH, titratable acidity, moisture, total available carbohydrate (TAC), soluble sugars, dietary fiber, protein, lipid, ash, fatty acids and mineral composition (K, Na, Ca, Mg, Fe, Cu, Mn, Zn, Ni and Cd) were determined. Results and discussion. Fruit contents (in g kg−1) varied between 637.3 ± 33.8 to 741.3 ±12.0, 126.8 ± 11.1 to 189.3 ± 4.1, 22.6 ± 2.2 to 35.5 ± 2.1, 5.1 ± 0.3 to 8.8 ± 0.5 for moisture, TAC, protein and lipid, respectively. For iron, fruit weight and polyunsaturated fatty acids (PUFA), the contents varied between 7.01 ± 0.15 to 17.24 ± 0.74 mg kg−1 of fruit, 4.91 ± 1.58 to 6.76 ± 2.04 g and 56.34 ± 1.37 to 68.18 ± 0.14% of lipid, respectively. Conclusion. This study provides original data about the morphological and chemical composition of strawberry-tree fruits from Algeria. The results show that the fruits can be essentially a potential source of dietary fiber, PUFA and iron.The authors are grateful to the Algerian Ministry of Higher Education and Scientific Research for funding the study; to ALIMNOVA research group (UCMGR35/10A) for financial support and to the Foundation for Science and Technology (FCT, Portugal) for financial support to CIMO (Pest-OE/AGR/UI0690/2015) and L. Barros (SFRH/BPD/107855/2015)info:eu-repo/semantics/publishedVersio

Assessing changes in airflow and energy loss in a progressive tracheal compression before and after surgical correction

The energy needed to drive airflow through the trachea normally constitutes a minor component of the work of breathing. However, with progressive tracheal compression, patient subjective symptoms can include severe breathing difficulties. Many patients suffer multiple respiratory co-morbidities and so it is important to assess compression effects when evaluating the need for surgery. This work describes the use of computational prediction to determine airflow resistance in compressed tracheal geometries reconstructed from a series of CT scans. Using energy flux analysis, the regions that contribute the most to airway resistance during inhalation are identified. The principal such region is where flow emerging from the zone of maximum constriction undergoes breakup and turbulent mixing. Secondary regions are also found below the tongue base and around the glottis, with overall airway resistance scaling nearly quadratically with flow rate. Since the anatomical extent of the imaged airway varied between scans - as commonly occurs with clinical data and when assessing reported differences between research studies - the effect of sub-glottic inflow truncation is considered. Analysis shows truncation alters the location of jet breakup and weakly influences the pattern of pressure recovery. Tests also show that placing a simple artificial glottis in the inflow to a truncated model can replicate patterns of energy loss in more extensive models, suggesting a means to assess sensitivity to domain truncation in tracheal airflow simulations

Parameter-Independent Strategies for pMDPs via POMDPs

Markov Decision Processes (MDPs) are a popular class of models suitable for solving control decision problems in probabilistic reactive systems. We consider parametric MDPs (pMDPs) that include parameters in some of the transition probabilities to account for stochastic uncertainties of the environment such as noise or input disturbances. We study pMDPs with reachability objectives where the parameter values are unknown and impossible to measure directly during execution, but there is a probability distribution known over the parameter values. We study for the first time computing parameter-independent strategies that are expectation optimal, i.e., optimize the expected reachability probability under the probability distribution over the parameters. We present an encoding of our problem to partially observable MDPs (POMDPs), i.e., a reduction of our problem to computing optimal strategies in POMDPs. We evaluate our method experimentally on several benchmarks: a motivating (repeated) learner model; a series of benchmarks of varying configurations of a robot moving on a grid; and a consensus protocol.Comment: Extended version of a QEST 2018 pape

Sleep EEG signatures in mouse models of 15q11.2-13.1 duplication (Dup15q) syndrome

BackgroundSleep disturbances are a prevalent and complex comorbidity in neurodevelopmental disorders (NDDs). Dup15q syndrome (duplications of 15q11.2-13.1) is a genetic disorder highly penetrant for NDDs such as autism and intellectual disability and it is frequently accompanied by significant disruptions in sleep patterns. The 15q critical region harbors genes crucial for brain development, notably UBE3A and a cluster of gamma-aminobutyric acid type A receptor (GABAAR) genes. We previously described an electrophysiological biomarker of the syndrome, marked by heightened beta oscillations (12-30 Hz) in individuals with Dup15q syndrome, akin to electroencephalogram (EEG) alterations induced by allosteric modulation of GABAARs. Those with Dup15q syndrome exhibited increased beta oscillations during the awake resting state and during sleep, and they showed profoundly abnormal NREM sleep. This study aims to assess the translational validity of these EEG signatures and to delve into their neurobiological underpinnings by quantifying sleep physiology in chromosome-engineered mice with maternal (matDp/ + mice) or paternal (patDp/ + mice) inheritance of the full 15q11.2-13.1-equivalent duplication, and mice with duplication of just the UBE3A gene (Ube3a overexpression mice; Ube3a OE mice) and comparing the sleep metrics with their respective wildtype (WT) littermate controls.MethodsWe collected 48-h EEG/EMG recordings from 35 (23 male, 12 female) 12-24-week-old matDp/ + , patDp/ + , Ube3a OE mice, and their WT littermate controls. We quantified baseline sleep, sleep fragmentation, spectral power dynamics during sleep states, and recovery following sleep deprivation. Within each group, distinctions between Dup15q mutant mice and WT littermate controls were evaluated using analysis of variance (ANOVA) and student's t-test. The impact of genotype and time was discerned through repeated measures ANOVA, and significance was established at p < 0.05.ResultsOur study revealed that across brain states, matDp/ + mice mirrored the elevated beta oscillation phenotype observed in clinical EEGs from individuals with Dup15q syndrome. Time to sleep onset after light onset was significantly reduced in matDp/ + and Ube3a OE mice. However, NREM sleep between Dup15q mutant and WT littermate mice remained unaltered, suggesting a divergence from the clinical presentation in humans. Additionally, while increased beta oscillations persisted in matDp/ + mice after 6-h of sleep deprivation, recovery NREM sleep remained unaltered in all groups, thus suggesting that these mice exhibit resilience in the fundamental processes governing sleep-wake regulation.ConclusionsQuantification of mechanistic and translatable EEG biomarkers is essential for advancing our understanding of NDDs and their underlying pathophysiology. Our study of sleep physiology in the Dup15q mice underscores that the beta EEG biomarker has strong translational validity, thus opening the door for pre-clinical studies of putative drug targets, using the biomarker as a translational measure of drug-target engagement. The unaltered NREM sleep may be due to inherent differences in neurobiology between mice and humans. These nuanced distinctions highlight the complexity of sleep disruptions in Dup15q syndrome and emphasize the need for a comprehensive understanding that encompasses both shared and distinct features between murine models and clinical populations

Improving the tokenisation of identifier names

Identifier names are the main vehicle for semantic information during program comprehension. For tool-supported program comprehension tasks, including concept location and requirements traceability, identifier names need to be tokenised into their semantic constituents. In this paper we present an approach to the automated tokenisation of identifier names that improves on existing techniques in two ways. First, it improves the tokenisation accuracy for single-case identifier names and for identifier names containing digits, which existing techniques largely ignore. Second, performance gains over existing techniques are achieved using smaller oracles, making the approach easier to deploy. Accuracy was evaluated by comparing our algorithm to manual tokenizations of 28,000 identifier names drawn from 60 well-known open source Java projects totalling 16.5 MSLOC. Moreover, the projects were used to perform a study of identifier tokenisation features (single case, camel case, use of digits, etc.) per object-oriented construct (class names, method names, local variable names, etc.), thus providing an insight into naming conventions in industrial-scale object-oriented code. Our tokenisation tool and datasets are publicly available

Random walk forecast of urban water in Iran under uncertainty

There are two significant reasons for the uncertainties of water demand. On one hand, an evolving technological world is plagued with accelerated change in lifestyles and consumption patterns; and on the other hand, intensifying climate change. Therefore, with an uncertain future, what enables policymakers to define the state of water resources, which are affected by withdrawals and demands? Through a case study based on thirteen years of observation data in the Zayandeh Rud River basin in Isfahan province located in Iran, this paper forecasts a wide range of urban water demand possibilities in order to create a portfolio of plans which could be utilized by different water managers. A comparison and contrast of two existing methods are discussed, demonstrating the Random Walk Methodology, which will be referred to as the â On uncertainty pathâ , because it takes the uncertainties into account and can be recommended to managers. This On Uncertainty Path is composed of both dynamic forecasting method and system simulation. The outcomes show the advantage of such methods particularly for places that climate change will aggravate their water scarcity, such as Iran

Dietary soy and meat proteins induce distinct physiological and gene expression changes in rats

This study reports on a comprehensive comparison of the effects of soy and meat proteins given at the recommended level on physiological markers of metabolic syndrome and the hepatic transcriptome. Male rats were fed semi-synthetic diets for 1 wk that differed only regarding protein source, with casein serving as reference. Body weight gain and adipose tissue mass were significantly reduced by soy but not meat proteins. The insulin resistance index was improved by soy, and to a lesser extent by meat proteins. Liver triacylglycerol contents were reduced by both protein sources, which coincided with increased plasma triacylglycerol concentrations. Both soy and meat proteins changed plasma amino acid patterns. The expression of 1571 and 1369 genes were altered by soy and meat proteins respectively. Functional classification revealed that lipid, energy and amino acid metabolic pathways, as well as insulin signaling pathways were regulated differently by soy and meat proteins. Several transcriptional regulators, including NFE2L2, ATF4, Srebf1 and Rictor were identified as potential key upstream regulators. These results suggest that soy and meat proteins induce distinct physiological and gene expression responses in rats and provide novel evidence and suggestions for the health effects of different protein sources in human diets

Is Perioperative Hypothermia a Risk Factor for Post-Cesarean Infection?

Objective: To determine whether hypothermia during Cesarean delivery is a risk factor for postoperative infection. Methods: An historical cohort investigation was conducted on all women delivered by Cesarean at our center during 2001. Initial recovery-room temperature, taken via the oral or axillary route, was used as a surrogate for intraoperative temperature. Adding 0.5(°)C to axillary temperatures generated oral temperature equivalents. Women with chorioamnionitis were excluded, as were those with an initial recovery-room temperature that exceeded 37.9(°)C or was recorded more than 20 minutes after the end of surgery. Prophylactic antibiotics (cefazolin, 1 g) were given during Cesarean delivery. Results: A total of 42 women (7.6%) were diagnosed with postoperative infections. Infections included endometritis (n= 25), wound abscess (n = 7), wound cellulitis (n = 7) and urinary tract infection (UTI) (n = 4). No cases of septic pelvic thrombophlebitis or pelvic abscess occurred. One woman had both endometritis and a UTI. Mean temperatures were higher, rather than lower, for women who subsequently had postoperative infections compared with those who did not (36.4 ± 0.8(°)Cvs. 35.9 ± 0.7(°)C; p < 0.001). Mean temperatures for the various postoperative infections were as follows: endometritis, 36.5 ± 0.8(°)C (p < 0.001 vs. uninfected group); wound abscess 36.0 ± 0.8(°)C (p = 0.63); wound cellulitis, 36.3 ± 0.6(°)C (p = 0.14); UTI, 36.7 ± 0.9(°)C (p = 0.04). Conclusions: Women who develop post-Cesarean infections have higher initial recovery-room temperatures than those who do not develop such infections. This suggests the presence of subclinical infection at the time of Cesarean. Evaluating whether intraoperative warming has any role during Cesarean delivery requires a randomized clinical trial

Lithofacies uncertainty modeling in a siliciclastic reservoir setting by incorporating geological contacts and seismic information

Deterministic modeling lonely provides a unique boundary layout, depending on the geological interpretation or interpolation from the hard available data. Changing the interpreter’s attitude or interpolation parameters leads to displacing the location of these borders. In contrary, probabilistic modeling of geological domains such as lithofacies is a critical aspect to providing information to take proper decision in the case of evaluation of oil reservoirs parameters, that is, applicable for quantification of uncertainty along the boundaries. These stochastic modeling manifests itself dramatically beyond this occasion. Conventional approaches of probabilistic modeling (object and pixel-based) mostly suffers from consideration of contact knowledge on the simulated domains. Plurigaussian simulation algorithm, in contrast, allows reproducing the complex transitions among the lithofacies domains and has found wide acceptance for modeling petroleum reservoirs. Stationary assumption for this framework has implications on the homogeneous characterization of the lithofacies. In this case, the proportion is assumed constant and the covariance function as a typical feature of spatial continuity depends only on the Euclidean distances between two points. But, whenever there exists a heterogeneity phenomenon in the region, this assumption does not urge model to generate the desired variability of the underlying proportion of facies over the domain. Geophysical attributes as a secondary variable in this place, plays an important role for generation of the realistic contact relationship between the simulated categories. In this paper, a hierarchical plurigaussian simulation approach is used to construct multiple realizations of lithofacies by incorporating the acoustic impedance as soft data through an oil reservoir in Iran.This research was funded by the National Elites Foundation of Iran in collaboration with research Institute Petroleum of Industry in Iran under the project number of 9265005