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Transmitted HIV drug resistance in Bulgaria was first reported in 2015 using data from 1988–2011. We determined the prevalence of surveillance drug resistance mutations (SDRMs) and HIV-1 genetic diversity in Bulgaria during 2012–2020 using polymerase sequences from 1053 of 2010 (52.4%) antiretroviral therapy (ART)-naive individuals. Sequences were analyzed for DRM using the WHO HIV SDRM list implemented in the calculated population resistance tool at Stanford University. Genetic diversity was inferred using automated subtyping tools and phylogenetics. Cluster detection and characterization was performed using MicrobeTrace. The overall rate of SDRMs was 5.7% (60/1053), with 2.2% having resistance to nucleoside reverse transcriptase inhibitors (NRTIs), 1.8% to non-nucleoside reverse transcriptase inhibitors (NNRTIs), 2.1% to protease inhibitors (PIs), and 0.4% with dual-class SDRMs. We found high HIV-1 diversity, with the majority being subtype B (60.4%), followed by F1 (6.9%), CRF02_AG (5.2%), A1 (3.7%), CRF12_BF (0.8%), and other subtypes and recombinant forms (23%). Most (34/60, 56.7%) of the SDRMs were present in transmission clusters of different subtypes composed mostly of male-to-male sexual contact (MMSC), including a 14-member cluster of subtype B sequences from 12 MMSC and two males reporting heterosexual contact; 13 had the L90M PI mutation and one had the T215S NRTI SDRM. We found a low SDRM prevalence amid high HIV-1 diversity among ART-naive patients in Bulgaria during 2012–2020. The majority of SDRMs were found in transmission clusters containing MMSC, indicative of onward spread of SDRM in drug-naive individuals. Our study provides valuable information on the transmission dynamics of HIV drug resistance in the context of high genetic diversity in Bulgaria, for the development of enhanced prevention strategies to end the epidemic.

Membrane oxygenators are devices that benefit from automatic control. This is especially true for implantable membrane oxygenators—a class of wearable rehabilitation devices that show high potential for fast recovery after lung injury. We present a performance comparison for reference tracking of carbon dioxide partial pressure between three control algorithms—a classical proportional-integral (PI) controller, a modern non-linear model predictive controller, and a novel deep reinforcement learning controller. The results are based on simulation studies of an improved compartmental model of a membrane oxygenator. The compartmental model of the oxygenator was improved by decoupling the oxygen kinetics from the system and only using the oxygen saturation as an input to the model. Both the gas flow rate and blood flow rate were used as the manipulated variable of the controllers. All three controllers were able to track references satisfactorily, based on several performance metrics. The PI controller had the fastest response, with an average rise time and settling time of 1.18 s and 2.24 s and the lowest root mean squared error of 1.06 mmHg. The NMPC controller showed the lowest steady state error of 0.17 mmHg and reached the reference signal with less than 2% error in 90% of the cases within 15 s. The PI and RL reached the reference with less than 2% error in 84% and 50% of the cases, respectively, and showed a steady state error of 0.29 mmHg and 0.5 mmHg.

Unprecedented tandem allylic alkylation/intermolecular Michael addition was used in the preparation of novel bicyclic azalides. NMR spectroscopy was used not only to unambiguously determine and characterize the structures of these unexpected products of chemical reaction but also to investigate the effect the rigid bicyclic modification has on the conformation of the whole molecule. Thus, some of the macrolides prepared showed antibacterial activity in the range of well-known antibiotic drug azithromycin.

CO2 removal via membrane oxygenators has become an important and reliable clinical technique. Nevertheless, oxygenators must be further optimized to increase CO2 removal performance and to reduce severe side effects. Here, in vitro tests with water can significantly reduce costs and effort during development. However, they must be able to reasonably represent the CO2 removal performance observed with blood. In this study, the deviation between the CO2 removal rate determined in vivo with porcine blood from that determined in vitro with water is quantified. The magnitude of this deviation (approx. 10%) is consistent with results reported in the literature. To better understand the remaining difference in CO2 removal rate and in order to assess the application limits of in vitro water tests, CFD simulations were conducted. They allow to quantify and investigate the influences of the differing fluid properties of blood and water on the CO2 removal rate. The CFD results indicate that the main CO2 transport resistance, the diffusional boundary layer, behaves generally differently in blood and water. Hence, studies of the CO2 boundary layer should be preferably conducted with blood. In contrast, water tests can be considered suitable for reliable determination of the total CO2 removal performance of oxygenators.

Extracorporeal membrane oxygenators are essential medical devices for the treatment of patients with respiratory failure. A promising approach to improve oxygenator performance is the use of microstructured hollow fiber membranes that increase the available gas exchange surface area. However, by altering the traditional circular fiber shape, the risk of low flow, stagnating zones that obstruct mass transfer and encourage thrombus formation, may increase. Finding an optimal fiber shape is therefore a significant task. In this study, experimentally validated computational fluid dynamics simulations were used to investigate transverse flow within fiber packings of circular and microstructured fiber geometries. A numerical model was applied to calculate the local Sherwood number on the membrane surface, allowing for qualitative comparison of gas exchange capacities in low-velocity areas caused by the microstructured geometries. These adverse flow structures lead to a tradeoff between increased surface area and mass transfer. Based on our simulations, we suggest an optimal fiber shape for further investigations that increases potential mass transfer by up to 48% in comparison to the traditional, circular hollow fiber shape.

CO2 removal via membrane oxygenators during lung protective ventilation has become a reliable clinical technique. For further optimization of oxygenators, accurate prediction of the CO2 removal rate is necessary. It can either be determined by measuring the CO2 content in the exhaust gas of the oxygenator (sweep flow-based) or using blood gas analyzer data and a CO2 solubility model (blood-based). In this study, we determined the CO2 removal rate of a prototype oxygenator utilizing both methods in in vitro trials with bovine and in vivo trials with porcine blood. While the sweep flow-based method is reliably accurate, the blood-based method depends on the accuracy of the solubility model. In this work, we quantified performances of four different solubility models by calculating the deviation of the CO2 removal rates determined by both methods. Obtained data suggest that the simplest model (Loeppky) performs better than the more complex ones (May, Siggaard-Anderson, and Zierenberg). The models of May, Siggaard-Anderson, and Zierenberg show a significantly better performance for in vitro bovine blood data than for in vivo porcine blood data. Furthermore, the suitability of the Loeppky model parameters for bovine blood (in vitro) and porcine blood (in vivo) is evaluated.

HIV-1 subtype CRF01_AE is the second most predominant strain in Bulgaria, yet little is known about the molecular epidemiology of its origin and transmissibility. We used a phylodynamics approach to better understand this sub-epidemic by analyzing 270 HIV-1 polymerase (pol) sequences collected from persons diagnosed with HIV/AIDS between 1995 and 2019. Using network analyses at a 1.5% genetic distance threshold (d), we found a large 154-member outbreak cluster composed mostly of persons who inject drugs (PWID) that were predominantly men. At d = 0.5%, which was used to identify more recent transmission, the large cluster dissociated into three clusters of 18, 12, and 7 members, respectively, five dyads, and 107 singletons. Phylogenetic analysis of the Bulgarian sequences with publicly available global sequences showed that CRF01_AE likely originated from multiple Asian countries, with Vietnam as the likely source of the outbreak cluster between 1988 and 1990. Our findings indicate that CRF01_AE was introduced into Bulgaria multiple times since 1988, and infections then rapidly spread among PWID locally with bridging to other risk groups and countries. CRF01_AE continues to spread in Bulgaria as evidenced by the more recent large clusters identified at d = 0.5%, highlighting the importance of public health prevention efforts in the PWID communities.

Blood pumps have found applications in heart support devices, oxygenators, and dialysis systems, among others. Often, there is no room for sensors, or the sensors are simply unreliable when long-term operation is required. However, control systems rely on those hard-to-measure parameters, such as blood flow rate and pressure difference, thus their estimation takes a central role in the development process of such medical devices. The viscosity of the blood not only influences the estimation of those parameters but is often a parameter that is of great interest to both doctors and engineers. In this work, estimation methods for blood flow rate, pressure difference, and viscosity are presented using Gaussian process regression models. Different water−glycerol mixtures were used to model blood. Data was collected from a custom-built blood pump, designed for intracorporeal oxygenators in an in vitro test circuit. The estimation was performed from motor current and motor speed measurements and its accuracy was measured for: blood flow rate r2 = 0.98, root mean squared error (RMSE) = 46 mL.min−1; pressure difference r2 = 0.98, RMSE = 8.7 mmHg; and viscosity r2 = 0.98, RMSE = 0.049 mPa.s. The results suggest that the presented methods can be used to accurately predict blood flow rate, pressure, and viscosity online.