Among natural products, essential oils from aromatic plants have been reported to possess potent anticancer properties. In this work, we aimed to perform the cytotoxic concentration range screening and antiproliferative activity screening of chemically characterized Thymus vulgaris L. essential oil. In vivo bioassay was conducted using the brine shrimp lethality test (BSLT). In vitro evaluation of antiproliferative activity was carried out on three human tumor cell lines: breast adenocarcinoma MCF-7, lung carcinoma H460 and acute lymphoblastic leukemia MOLT-4 using MTT assay. Essential oil components thymol (36.7%), p-cymene (30.0%), γ-terpinene (9.0%) and carvacrol (3.6%) were identified by gas chromatography/mass spectrometry. Analyzed essential oil should be considered as toxic/highly toxic with LC50 60.38 µg/mL in BSLT and moderate/weakly cytotoxic with IC50 range 52.65–228.78 µg/mL in vitro, according to evaluated cytotoxic criteria. Essential oil induced a dose-dependent inhibition of cell proliferation in all tested tumor cell lines and showed different sensitivity. Dose dependent toxicity observed in bioassay as well as the in vitro assay confirmed that brine shrimp lethality test is an adequate method for preliminary toxicity testing of Thymus vulgaris L. essential oil in tumor cell lines.

The rising opioid crisis has become a worldwide societal and public health burden, resulting from the abuse of prescription opioids. Targeting the κ-opioid receptor (KOR) in the periphery has emerged as a powerful approach to develop novel pain medications without central side effects. Inspired by the traditional use of sunflower (Helianthus annuus) preparations for analgesic purposes, we developed novel stabilized KOR ligands (termed as helianorphins) by incorporating different dynorphin A sequence fragments into a cyclic sunflower peptide scaffold. As a result, helianorphin-19 selectively bound to and fully activated the KOR with nanomolar potency. Importantly, helianorphin-19 exhibited strong KOR-specific peripheral analgesic activity in a mouse model of chronic visceral pain, without inducing unwanted central effects on motor coordination/sedation. Our study provides a proof of principle that cyclic peptides from plants may be used as templates to develop potent and stable peptide analgesics applicable via enteric administration by targeting the peripheral KOR for the treatment of chronic abdominal pain.

In this paper, we present a hybrid adaptive feedback (HAF) obstacle-avoidance algorithm for source seeking applications that overcomes the obstacle-avoidance problem, as defined in [1], when using artificial potential functions (APF). Differently from [2], our algorithm does not require any knowledge on the location and orientation of the obstacle with respect to the source. Finally, we show via numerical simulations the effectiveness of our algorithm compared with the APF approach.

Background To date (April 2021), medical device (MD) design approaches have failed to consider the contexts where MDs can be operationalised. Although most of the global population lives and is treated in Low- and Middle-Income Countries (LMCIs), over 80% of the MD market share is in high-resource settings, which set de facto standards that cannot be taken for granted in lower resource settings. Using a MD designed for high-resource settings in LMICs may hinder its safe and efficient operationalisation. In the literature, many criteria for frameworks to support resilient MD design were presented. However, since the available criteria (as of 2021) are far from being consensual and comprehensive, the aim of this study is to raise awareness about such challenges and to scope experts’ consensus regarding the essentiality of MD design criteria. Results This paper presents a novel application of Delphi study and Multiple Criteria Decision Analysis (MCDA) to develop a framework comprising 26 essential criteria, which were evaluated and chosen by international experts coming from different parts of the world. This framework was validated by analysing some MDs presented in the WHO Compendium of innovative health technologies for low-resource settings. Conclusions This novel holistic framework takes into account some domains that are usually underestimated by MDs designers. For this reason, it can be used by experts designing MDs resilient to low-resource settings and it can also assist policymakers and non-governmental organisations in shaping the future of global healthcare.

We analyze two classes of Kuramoto models on spheres that have been introduced in previous studies. Our analysis is restricted to ensembles of identical oscillators with the global coupling. In such a setup, with an additional assumption that the initial distribution of oscillators is uniform on the sphere, one can derive equations for order parameters in closed form. The rate of synchronization in a real Kuramoto model depends on the dimension of the sphere. Specifically, synchronization is faster on higher-dimensional spheres. On the other side, real order parameter in complex Kuramoto models always satisfies the same ODE, regardless of the dimension. The derivation of equations for real order parameters in Kuramoto models on spheres is based on recently unveiled connections of these models with geometries of unit balls. Simulations of the system with several hundreds of oscillators yield perfect fits with the theoretical predictions, that are obtained by solving equations for the order parameter.

Microneedles (MNs) represent the concept of attractive, minimally invasive puncture devices of micron-sized dimensions that penetrate the skin painlessly and thus facilitate the transdermal administration of a wide range of active substances. MNs have been manufactured by a variety of production technologies, from a range of materials, but most of these manufacturing methods are time-consuming and expensive for screening new designs and making any modifications. Additive manufacturing (AM) has become one of the most revolutionary tools in the pharmaceutical field, with its unique ability to manufacture personalized dosage forms and patient-specific medical devices such as MNs. This review aims to summarize various 3D printing technologies that can produce MNs from digital models in a single step, including a survey on their benefits and drawbacks. In addition, this paper highlights current research in the field of 3D printed MN-assisted transdermal drug delivery systems and analyzes parameters affecting the mechanical properties of 3D printed MNs. The current regulatory framework associated with 3D printed MNs as well as different methods for the analysis and evaluation of 3D printed MN properties are outlined.

Two-dimensional (2D) materials have emerged as a platform for a broad array of future nanoelectronic devices. Here we use first-principles calculations and phonon interface transport modeling to calculate the temperature-dependent thermal boundary conductance (TBC) in single layers of beyond-graphene 2D materials silicene, hBN, boron arsenide (BAs), and blue and black phosphorene (BP) on amorphous SiO2 and crystalline GaN substrates. Our results show that for 2D/3D systems, the room temperature TBC can span a wide range from 7 to 70 MW m−2 K−1 with the lowest being for BP and highest for hBN. We also show that 2D/3D TBC has a strong temperature dependence that can be alleviated by encapsulating the 2D/3D stack. Upon encapsulation with AlO x , the TBC of several beyond-graphene 2D materials can match or exceed reported values for graphene and numerous transition-metal dichalcogendies which are in the range of 15–40 MW m−2 K−1. We also compute the room temperature TBC as a function of van der Waals spring coupling (K a ) where the TBC falls in the range of 50–150 MW m−2 K−1 at coupling strengths of K a = 2–4 N m−1 for silicene, BAs, and blue phosphorene. We further identify group III–V materials with ultra-soft flexural branches as being promising 2D materials for thermal isolation and energy scavenging applications when matched with crystalline substrates.

Microstructural and cavitation erosion testing was carried out on Cu-12.8Al-4.1Ni (wt. %) shape memory alloy (SMA) samples produced by continuous casting followed by heat treatment consisting of solution annealing at 885 °C for 60 min and, later, water quenching. Cavitation resistance testing was applied using a standard ultrasonic vibratory cavitation set up with stationary specimen. Surface changes during the cavitation were monitored by metallographic analysis using an optical microscope (OM), atomic force microscope (AFM), and scanning electron microscope (SEM) as well as by weight measurements. The results revealed a martensite microstructure after both casting and quenching. Microhardness value was higher after water quenching than in the as-cast state. After 420 min of cavitation exposure, a negligible mass loss was noticed for both samples. Based on the obtained results, both samples showed excellent cavitation resistance. Mass loss and morphological analysis of the formed pits indicated better cavitation resistance for the as-cast state (L).

Background We are facing the outburst of coronavirus disease 2019 (COVID-19) defined as a serious, multisystem, disorder, including various neurological manifestations in its presentation. So far, autonomic dysfunction (AD) has not been reported in patients with COVID-19 infection. Aim Assessment of AD in the early phase of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus). Patients and methods We analyzed 116 PCR positive COVID-19 patients. After the exclusion of 41 patients with associate diseases (CADG), partitioned to patients with diabetes mellitus, hypertension, and syncope, the remaining patients were included into a severe group (45 patients with confirmed interstitial pneumonia) and mild group (30 patients). Basic cardiovascular autonomic reflex tests (CART) were performed, followed by beat-to-beat heart rate variability (HRV) and systolic and diastolic blood pressure variability (BPV) analysis, along with baroreceptor sensitivity (BRS). Non-linear analysis of HRV was provided by Poincare Plot. Results were compared to 77 sex and age-matched controls. Results AD (sympathetic, parasympathetic, or both) in our study has been revealed in 51.5% of severe, 78.0% of mild COVID-19 patients, and the difference compared to healthy controls was significant (p = 0.018). Orthostatic hypotension has been established in 33.0% COVID-19 patients compared to 2.6% controls (p = 0.001). Most of the spectral parameters of HRV and BPV confirmed AD, most prominent in the severe COVID-19 group. BRS was significantly lower in all patients (severe, mild, CADG), indicating significant sudden cardiac death risk. Conclusion Cardiovascular autonomic neuropathy should be taken into account in COVID-19 patients’ assessment. It can be an explanation for a variety of registered manifestations, enabling a comprehensive diagnostic approach and further treatment.

Introduction Elderberries (the genus Sambucus) are a highly heterogeneous group of deciduous shrubs or small trees that can be found in sunlight-exposed locations in almost every continent of the world (Veberic et al., 2009). Wild elderberry species originate mostly from the northern hemisphere, while their semi-domesticated and cultivated relatives are present throughout temperate, subtropical and tropical regions, usually close to human settlements (Ritter and McKee, 1964). The Sambucus Initially, it was ranked in the Caprifoliaceae family (Donoghue et al., 2001), but newer genetic research places it in the Adoxaceae family (Jacobs et al., 2010; Anton et al., 2013), which includes between 5 and 30 species, depending on taxonomy. The most widely used taxonomy is that proposed by Bolli (1994), which recognizes only nine species, including the black elderberry (Sambucus nigra L.). The black elderberry (S. nigra) is the most widespread elderberry species in Europe (Mikulic-Petkovsek et al., 2016). In general, elderberry shrubs are multi-stemmed with small, relatively weak branches that can reach up to 10 m in height.

Explanations can help users to better understand why items have been recommended. Additionally, explanations for group recommender systems need to consider further goals than single-user recommender systems. For example, we need to balance group members’ need for privacy with their need for transparency, since a transparent explanation might pose a privacy hazard. In an online experiment with real groups (n=114 participants: 38 groups of size 3), we seek to understand which factors influence people’s privacy concerns when a single explanation is presented to a group in the tourism domain. In particular, we study the direct effects of three factors on privacy concern: a) group members’ personality (using the ‘Big Five’ personality traits), b) specific preference scenarios (i.e., having minority or majority preferences compared to two other group members), c) the type of relationship they have in the group (i.e., loosely coupled heterogeneous, versus tightly coupled homogeneous). We find that for personality two traits, Extroversion, and Agreeableness, each significantly affects the privacy concern. Moreover, having the minority or majority preferences in the group, as well as the type of relationship people have in the group, have a strong and significant influence on participants’ privacy concern. These results suggest that explanations presented to groups need to be adapted to all three factors (personality, type of relationship, and preference scenario) when considering the privacy concern of users.