A variety of machine learning methods such as naive Bayesian, support vector machines and more recently deep neural networks are demonstrating their utility for drug discovery and development. These ...leverage the generally bigger datasets created from high-throughput screening data and allow prediction of bioactivities for targets and molecular properties with increased levels of accuracy. We have only just begun to exploit the potential of these techniques but they may already be fundamentally changing the research process for identifying new molecules and/or repurposing old drugs. The integrated application of such machine learning models for end-to-end (E2E) application is broadly relevant and has considerable implications for developing future therapies and their targeting.
Examining how exposure to pre-migration war related trauma and duration of living in refugee camp can impact on PTSD and psychiatric morbidity, while assessing the moderating role of trait resilience ...and coping style.
In a cross-sectional study, exposure to war related trauma and duration of living in refugee camp was evaluated in a sample of 83 asylum seekers and refugees from the Middle East, together with an assessment of PTSD and psychiatric morbidity via self-rating instruments. Trait resilience and coping style were also measured.
Eighty-three participants were included in the analysis, 96.4% reported having experienced more than one war related traumatic event while the mean duration of living in refugee camps was 23.6 (SD = 7.6) years. Of the entire sample, 32.5% reached the threshold for clinical presence of PTSD and 38.8% for psychiatric morbidity. Both pre-migration war related trauma (F(1,82) = 24.118, p < .001) and duration of living in refugee camp (F(2,81) = 2.511, p = .008) were significantly associated with PTSD. Trait resilience moderated effects of high-profile trauma exposure on PTSD severity, R2 = 0.26, MSE = 0.547, F(3,79) = 9.6357, p < .0001, with higher resilience levels weakening the effect of traumatic exposure on PTSD development.
Our results shed light on the ways that resilience can influence the relationship between war trauma exposure and PTSD symptoms. Findings support the role of resilience-based interventions in order to bolster resilient functioning and optimize treatment of this disadvantaged and highly distressed population.
•Pre-migration trauma and chronic stress conditions of refugee life are associated with PTSD.•Disengagement focused coping was positively and significantly correlated with clinical levels of PTSD.•Engagement focused coping was significantly and positively related with no/low levels of PTSD.•Trait resilience moderated effects of pre-migration trauma on PTSD.•Results highlight the need for a more nuanced approach to intervention and treatment of this population.
Nitrogen dioxide (NO2) is a gas species that plays an important role in certain industrial, farming, and healthcare sectors. However, there are still significant challenges for NO2 sensing at low ...detection limits, especially in the presence of other interfering gases. The NO2 selectivity of current gas-sensing technologies is significantly traded-off with their sensitivity and reversibility as well as fabrication and operating costs. In this work, we present an important progress for selective and reversible NO2 sensing by demonstrating an economical sensing platform based on the charge transfer between physisorbed NO2 gas molecules and two-dimensional (2D) tin disulfide (SnS2) flakes at low operating temperatures. The device shows high sensitivity and superior selectivity to NO2 at operating temperatures of less than 160 °C, which are well below those of chemisorptive and ion conductive NO2 sensors with much poorer selectivity. At the same time, excellent reversibility of the sensor is demonstrated, which has rarely been observed in other 2D material counterparts. Such impressive features originate from the planar morphology of 2D SnS2 as well as unique physical affinity and favorable electronic band positions of this material that facilitate the NO2 physisorption and charge transfer at parts per billion levels. The 2D SnS2-based sensor provides a real solution for low-cost and selective NO2 gas sensing.
The first order and second order corrected photoluminescence quantum yields are computed and compared to experiment for naphthalene in this manuscript discussing negative results. Results for ...anthracene and tetracene are recalled from previous work (Manian et al. in J Chem Phys 155:054108, 2021), and the results for all three polyacenes are juxtaposed to each other. While at the Franck-Condon point, each of the three noted polyacenes were found to possess a quantum yield near unity. Following the consideration of Herzberg-Teller effects, quantum yields stabilised for anthracene and tetracene to 0.19 and 0.08, respectively. Conversely, the second order corrected quantum yield for naphthalene was found to be 0.91. Analysis of this result showed that while the predicted non-radiative pathways correlate well with what should be expected, the approximation used to calculate second order corrected fluorescence, which yielded very positive results for many other molecular systems, here is unable to account for strong second order contributions, resulting in a grossly overestimated rate of fluorescence. However, substitution of an experimental radiative rate results in a quantum yield of 0.33. This work extols the importance of Herzberg-Teller terms in photophysical descriptions of chromophores, and highlights those cases in which a treatment beyond the above approximation is required.
Abstract
The predicted strong piezoelectricity for monolayers of group IV monochalcogenides, together with their inherent flexibility, makes them likely candidates for developing flexible ...nanogenerators. Within this group, SnS is a potential choice for such nanogenerators due to its favourable semiconducting properties. To date, access to large-area and highly crystalline monolayer SnS has been challenging due to the presence of strong inter-layer interactions by the lone-pair electrons of S. Here we report single crystal across-the-plane and large-area monolayer SnS synthesis using a liquid metal-based technique. The characterisations confirm the formation of atomically thin SnS with a remarkable carrier mobility of ~35 cm
2
V
−1
s
−1
and piezoelectric coefficient of ~26 pm V
−1
. Piezoelectric nanogenerators fabricated using the SnS monolayers demonstrate a peak output voltage of ~150 mV at 0.7% strain. The stable and flexible monolayer SnS can be implemented into a variety of systems for efficient energy harvesting.
The discovery of biocompatible or bioactive nanoparticles for medicinal applications is an expensive and time-consuming process that may be significantly facilitated by incorporating more rational ...approaches combining both experimental and computational methods. However, it is currently hindered by two limitations: (1) the lack of high-quality comprehensive data for computational modeling and (2) the lack of an effective modeling method for the complex nanomaterial structures. In this study, we tackled both issues by first synthesizing a large library of nanoparticles and obtained comprehensive data on their characterizations and bioactivities. Meanwhile, we virtually simulated each individual nanoparticle in this library by calculating their nanostructural characteristics and built models that correlate their nanostructure diversity to the corresponding biological activities. The resulting models were then used to predict and design nanoparticles with desired bioactivities. The experimental testing results of the designed nanoparticles were consistent with the model predictions. These findings demonstrate that rational design approaches combining high-quality nanoparticle libraries, big experimental data sets, and intelligent computational models can significantly reduce the efforts and costs of nanomaterial discovery.
Traditional experimental testing to identify endocrine disruptors that enhance estrogenic signaling relies on expensive and labor-intensive experiments. We sought to design a knowledge-based deep ...neural network (k-DNN) approach to reveal and organize public high-throughput screening data for compounds with nuclear estrogen receptor α and β (ERα and ERβ) binding potentials. The target activity was rodent uterotrophic bioactivity driven by ERα/ERβ activations. After training, the resultant network successfully inferred critical relationships among ERα/ERβ target bioassays, shown as weights of 6521 edges between 1071 neurons. The resultant network uses an adverse outcome pathway (AOP) framework to mimic the signaling pathway initiated by ERα and identify compounds that mimic endogenous estrogens (i.e., estrogen mimetics). The k-DNN can predict estrogen mimetics by activating neurons representing several events in the ERα/ERβ signaling pathway. Therefore, this virtual pathway model, starting from a compound’s chemistry initiating ERα activation and ending with rodent uterotrophic bioactivity, can efficiently and accurately prioritize new estrogen mimetics (AUC = 0.864–0.927). This k-DNN method is a potential universal computational toxicology strategy to utilize public high-throughput screening data to characterize hazards and prioritize potentially toxic compounds.
Abstract
Catalytic solvent regeneration has attracted broad interest owing to its potential to reduce energy consumption in CO
2
separation, enabling industry to achieve emission reduction targets of ...the Paris Climate Accord. Despite recent advances, the development of engineered acidic nanocatalysts with unique characteristics remains a challenge. Herein, we establish a strategy to tailor the physicochemical properties of metal-organic frameworks (MOFs) for the synthesis of water-dispersible core-shell nanocatalysts with ease of use. We demonstrate that functionalized nanoclusters (Fe
3
O
4
-COOH) effectively induce missing-linker deficiencies and fabricate mesoporosity during the self-assembly of MOFs. Superacid sites are created by introducing chelating sulfates on the uncoordinated metal clusters, providing high proton donation capability. The obtained nanomaterials drastically reduce the energy consumption of CO
2
capture by 44.7% using only 0.1 wt.% nanocatalyst, which is a ∽10-fold improvement in efficiency compared to heterogeneous catalysts. This research represents a new avenue for the next generation of advanced nanomaterials in catalytic solvent regeneration.
Medical education is highly demanding and evidence shows that medical students are three times more susceptible to deteriorating physical and mental health than the average college student. While ...trait anxiety may further increase such risk, little is known about the role of trait mindfulness in mitigating these effects. Here we examine the protective role of specific mindfulness facets as mediators in pathways from trait anxiety to perceived stress, psychosomatic burden and sleep-wake quality in medical students, across repeated measurements throughout the first trimester of the school year. Preclinical medical students enrolled in the second year of the Medical School of University of Bologna completed self-report questionnaires examining personality traits as well as physical and psychological wellbeing. Data were collected at the beginning (Time 1: N = 349) and the end of the first trimester (Time 2: N = 305). As students approached the end of the trimester and upcoming exams, reported levels of perceived stress, psychosomatic problems and difficulties in wakefulness increased significantly compared to the beginning of the trimester. Mediation results showed that trait anxiety predicted such outcomes whereas the protective role of mindfulness facets in mitigating these effects was significant only at Time 2. Specific facets of Nonjudging of inner experience and Acting with awareness proved to be the most effective mediators. Findings highlight that the beneficial role of mindfulness facets in mitigating negative consequences of trait anxiety on medical student wellbeing is revealed in high-pressure periods and when self-regulation is needed the most. Cultivating awareness and nonjudgmental acceptance of one’s inner experiences is a crucial self-regulation resource that can help medical students sustain their wellbeing as they learn and throughout their high-pressure education and professional careers.
Tunable plasmon resonances in suspended 2D molybdenum oxide flakes are demonstrated. The 2D configuration generates a large depolarization factor and the presence of ultra-doping produces ...visible-light plasmon resonances. The ultra-doping process is conducted by reducing the semiconducting 2D MoO sub(3) flakes using simulated solar irradiation. The generated plasmon resonances can be controlled by the doping levels and the flakes' lateral dimensions, as well as by exposure to a model protein.
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