The increasing spread of marine non-indigenous species (NIS) due to the growth in global shipping traffic is causing widespread concern for the ecological and economic impacts of marine bioinvasions. Risk management authorities need tools to identify pathways and source regions of priority concern in order to better target efforts for preventing NIS introduction. The probability of a successful NIS introduction is affected by the probability that a marine species entrained in a transport vector will survive the voyage between origin and destination locations, and establish an independently reproducing population at the destination. Three important risk factors are voyage duration, range of environmental conditions encountered during transit, and environmental similarity between origin and destination. In this study, we aimed for a globally comprehensive approach of assembling quantifications of source-destination risk factors from every potential origin to every potential destination. To derive estimates of voyage-related marine biosecurity risk, we used computer-simulated vessel paths between pairs of ecoprovinces in the Marine Ecoregions Of the World biogeographic classification system. We used the physical length of each path to calculate voyage duration risk, and the cross-latitudinal extent of the path to calculate voyage path risk. Environmental similarity risk was based on comparing annual average sea surface temperature and salinity within each ecoprovince to those of other ecoprovinces. We derived three separate sets of risk quantifications, one each for voyage duration, voyage path, and environmental similarity. Our quantifications can be applied to studies that require source-destination risk estimates. They can be used separately or combined, depending on the importance of the types of source-destination risks that might be relevant to particular scientific or risk management questions or applications.

In this paper, the problem of state estimation for a fractional-order neural networks system with uncertainties is studied by a sampled-data controller. First, considering the convenience of digital field, such as anti-interference, not affected by noise, a novel sampled-data controller is designed for the fractional-order neural network system of uncertainties with changeable sampling time. In the light of the input delay approach, the sampled-data control system of fractional-order is simulated by the delay system. The main purpose of the presented method is to obtain a sampled-data controller gain K to estimate the state of neurons, which can guarantee the asymptotic stability of the closed-loop fractional-order system. Then, the fractional-order Razumishin theorem and linear matrix inequalities (LMIs) are utilized to derive the stable conditions. Improved delay-dependent and order-dependet stability conditions are given in the form of LMIs. Furthermore, the sampled-data controller can be acquired to promise the stability and stabilization for fractional-order system. Finally, two numerical examples are proposed to demonstrate the effectiveness and advantages of the provided method.

Short-term wind speed prediction is essential for economical wind power utilization. The real-world wind speed data is typically intermittent and fluctuating, presenting great challenges to existing shallow models. In this paper, we present a novel deep hybrid model for multi-step wind speed prediction, namely LR-FFT-RP-MLP/LSTM (Linear Fast Fourier Transformation Rank Pooling Multiple-Layer Perception/Long Short-Term Memory). Our hybrid model processes the local and global input features simultaneously. We leverage Rank Pooling (RP) for the local feature extraction to capture the temporal structure while maintaining the temporal order. Besides, to understand the wind periodic patterns, we exploit Fast Fourier Transformation (FFT) to extract global features and relevant frequency components in the wind speed data. The resulting local and global features are respectively integrated with the original data and are fed into an MLP/LSTM layer for the initial wind speed predictions. Finally, we leverage a linear regression layer to collaborate these initial predictions to produce the final wind speed prediction. The proposed hybrid model is evaluated using real wind speed data collected from 2010 to 2020, demonstrating superior forecasting capabilities when compared to state-of-the-art single and hybrid models. Overall, this study presents a promising approach for improving the accuracy of wind speed forecasting.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homo-dimers, 3 homo-trimers, 13 hetero-dimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their 5 best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% for the targets compared to 8% two years earlier, a remarkable improvement resulting from the wide use of the AlphaFold2 and AlphaFold-Multimer software. Creative use was made of the deep learning inference engines affording the sampling of a much larger number of models and enriching the multiple sequence alignments with sequences from various sources. Wide use was also made of the AlphaFold confidence metrics to rank models, permitting top performing groups to exceed the results of the public AlphaFold-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.

Carbanion-based ionic liquids are proposed and utilized as the key components for the construction of five super-nucleophilic deep eutectic solvents (SNDESs) in the paper. The super-nucleophilic nature of carbanion-based ILs is found to enable the capture of CO2 with large absorption capacity. However, the absorption is very slow in the IL due to high viscosity. The synergy of carbanion siting and hydrogen bonding is found to enable high and fast absorption of CO2 in [N2222][CH(CN)2]-ethylimidazole (Eim), and a synergistic absorption mechanism is proposed and validated from spectroscopic analyses and quantum calculations. The enthalpy change of CO2 absorption in [N2222][CH(CN)2]-Eim is calculated to be -39.6 kJ/mol according to the thermodynamic model, and the moderate value implies that both absorption and desorption of CO2 in the DES are favored and well balanced. The synergism of carbanion and hydrogen bond mediated by SNDESs provides a novel insight into the efficient CO2 capture.

In this work, we demonstrate plasma-catalytic synthesis of hydrogen and acrylonitrile (AN) from CH4 and N2. The process involves two steps: 1) plasma synthesis of C2H2 and HCN in a nominally 1:1 stoichiometric ratio with high yield up to 90% and high methane conversion > 90%; and 2) downstream thermocatalytic reaction of these intermediates to make AN. The effect of process parameters on product distributions and specific energy requirements are reported. If the catalytic conversion of C2H2 and HCN in the downstream thermocatalytic step to AN were perfect, which will require further improvements in the thermocatalytic reactor, then at the maximum output of our 1 kW radiofrequency 13.56 MHz transformer, a specific energy requirement of 73 kWh kgAN-1was determined. The expectation is that scaling up the process to higher throughputs would result in decreases in specific energy requirement into the predicted economically viable range less than 10 kWh kgAN-1.

Untangling the responses of protistan communities associated with soil and plant compartments and their associations with bacterial and fungal communities to pathogen invasion are critical for understanding the ecological processes governing plant microbiome assembly. Here we examined the protistan communities across the soil–plant continuum of healthy chili peppers and those with Fusarium wilt disease (FWD) and integrated the bacterial and fungal microbiome data from our previous investigation in China. We found that FWD was associated with a significant enrichment of phagotrophic protists in roots and an increase in the proportion and connectivity of these phagotrophic protists in intra- and interkingdom networks. Specifically, FWD increased the negative correlations between phagotrophic protists (especially Cercozoa and Ciliophora) and several members of Actinobacteria, Alphaproteobacteria, and Gammaproteobacteria in the interkingdom networks. Furthermore, the microbiomes of diseased plants not only exhibit a higher relative abundance of functional genes related to bacterial anti-predator responses compared to healthy plants, but also contained a greater abundance of metagenome-assembled genomes possessing functional traits involved in this response. The increased microbial interkingdom correlations among bacteria, fungi, and protists, coupled with the enhanced effects of protists on bacteria and fungi, as well as the notable bacterial anti-predator feedback in the diseased plant microbiome, all suggest that FWD catalyzes the associations between different groups of microbiomes. These findings highlight the role of predatory protists in shaping microbial assembly and functionality through top-down forces during pathogenic stress, potentially contributing to co-evolution within these soil and plant microbiomes.

Molecular imaging is a non-invasive imaging method that is widely used for visualization and detection of biological events at cellular or molecular levels. Stimuli-responsive linkers that can be selectively cleaved by specific biomarkers at desired sites to release or activate imaging agents are appealing tools to improve the specificity, sensitivity, and efficacy of molecular imaging. This review summarizes the recent advances of stimuli-responsive linkers and their application in molecular imaging, highlighting the potential of these linkers in the design of activatable molecular imaging probes. We hope that this review could inspire more research interests in the development of responsive linkers and associated imaging applications.

A document by Haleema Qayyum Abbasi. Click on the document to view its contents.

Cure rates for acute lymphoblastic leukemia (ALL), the most common childhood cancer have steadily improved over the past five decades. This is due to intensifying systemic therapy, recognizing and treating the central nervous system as a sanctuary site, and implementing modern risk stratification to deliver varying intensities of therapy based on age, presenting white blood count (WBC), sentinel somatic genetics, and therapy response. Recently, numerous Children’s Oncology Group trials have demonstrated the lack of benefit of intensifying traditional chemotherapy, providing evidence that new approaches are needed to cure the patients for whom cure has been elusive. Distinguishing those who require intensive or novel therapeutic approaches from others who will be cured with minimal therapy is key for future trials. Incorporating new genomic biomarkers and more sensitive measures of minimal/measurable residual disease (MRD) provide opportunities to achieve these goals.

Laboratory science sometimes looks like it’s built exclusively for young people, but if you look closely, you’ll find another group of scientists waiting to join your lab: those of us who didn’t quite launch our careers on a normal trajectory. Welcoming a second-career scientist into your lab takes time and resources, but may just be well worth it. Here’s what one second-career scientist wants you to know about supporting second careers in immunology.

Environmental enrichment (EE) has been shown to produce beneficial effects in addiction disorders; however, due to its configurational complexity, the underlying mechanisms are not yet fully elucidated. Recent evidence suggests that EE, acting as a metaplastic agent, may affect glutamatergic mechanisms underlying appetitive memory and, in turn, modulate reward-seeking behaviors: here, we have investigated such possibility following a brief EE exposure. Adult male Sprague-Dawley rats were exposed to EE for 22h and the expression of critical elements of the glutamate synapse was measured 2h after the end of EE in the medial prefrontal cortex (mPFC), nucleus accumbens (NAc), and hippocampus (Hipp) brain areas, which are critical for reward and memory. We focused our investigation on the expression of NMDA and AMPA receptor subunits, their scaffolding proteins SAP102 and SAP97, vesicular and membrane glutamate transporters vGluT1 and GLT-1, and critical structural components such as proteins involved in morphology and function of glutamatergic synapses, PSD95 and Arc/Arg3.1. Our findings demonstrate that a brief EE exposure induces metaplastic changes in glutamatergic mPFC, NAc, and Hipp. Such changes are area-specific and involve postsynaptic NMDA/AMPA receptor subunit composition, as well as changes in the expression of their main scaffolding proteins, thus influencing the retention of such receptors at synaptic sites. Our data indicate that brief EE exposure is sufficient to dynamically modulate the glutamatergic synapses in mPFC-NAc-Hipp circuits, which may modulate rewarding and memory processes.

Early life adversities alter the development of a still maturing nervous system and can have long-term consequences on its function at adult age. This include nociceptive circuits that are critical to shape an adaptive pain response to protect our organism from potentially damaging insults. As such, adult rats with a history of neonatal maternal separation (NMS) display a visceral and somatic nociceptive hypersensitivity and inefficient analgesic responses to stress. In this study, we have characterized the consequences of NMS on wide dynamic range neurons (WDR) in the spinal cord of anesthetized adult rat during the nociceptive processing of hot and cold noxious information. We found that WDR neurons of NMS rats display an excessive coding of mechanical and thermal information applied at the rat hindpaws. This nicely explains the hypernociceptive behaviors seen after noxious mechanical, cold and hot peripheral stimulation. A peripheral change in the expression of molecular transducers for these stimuli (i.e. TRPV1, TRPM8, TRPA1) does not seem to account for this general hyperexcitability. Instead, a decreased chloride-mediated inhibitory tone on WDR neurons may play a role as indicated by the abnormal elevated of the type 1 Na-K-Cl cotransporter transcripts. Altogether, we propose that long-term consequences of NMS is associated with a reduced spinal cord inhibition favoring the expression of pain hypersensitivity. We cannot exclude that this phenomenon is also present at supraspinal sites as other NMS-associated symptoms include also excessive anxiety and impaired sociability.

The KEAP1-NRF2 system plays a central role in cytoprotection and defense mechanisms against oxidative stress. Because KEAP1 serves as a biosensor for electrophiles by using its reactive thiols and because NRF2 is a transcriptional factor regulating genes involved in the sulfur-mediated redox reactions, the KEAP1-NRF2 system has been regarded as a sulfur-utilizing cytoprotective mechanism. NRF2 is a key regulator of cytoprotective genes, such as antioxidant and detoxification genes, and also to possess potent anti-inflammatory activity. NRF2 has been recently focused as a great modifier/regulator for the cellular metabolism and mitochondrial function. Particularly, the NRF2-mediated regulatory mechanisms of metabolites and mitochondria has been considered diverse, but has not been fully-clarified yet. This review article provides an overview of the molecular mechanisms that regulate NRF2 signaling and its cytoprotective roles, and also highlights NRF2 contribution to the cellular metabolism, particularly in the context of mitochondrial function and newly found sulfur metabolism.

ABSTRACT Maternal hyperoxygenation (MH) has been studied as a diagnostic tool to evaluate pulmonary vasculature and as a treatment option to improve the growth of fetal left heart in fetuses with left-sided cardiac defects. Chronic maternal hyperoxygenation (CMH) therapy leads to an improvement in fetal pulmonary blood flow resulting in an enhanced venous return to the left heart with increased gestational age. With this manipulation it is anticipated to augment blood flow directed remodeling of the left heart structures and to improve left heart growth spanning from the mitral valve to the aortic isthmus. However, there are concerns about CMH therapy with regard to fetal complications with growth restriction and fetal brain development. Now, with two successful cases we try to discuss this fetal treatment option and related concerns.

Plant-microbe interactions in the rhizosphere shape carbon and nitrogen cycling in soil organic matter (SOM). However, there is conflicting evidence on whether these interactions lead to a net loss or increase of SOM. In part, this conflict is driven by uncertainty in how living roots and microbes alter SOM formation or loss in the field. To address these uncertainties, we traced the fate of isotopically labeled litter into SOM using root and fungal ingrowth cores incubated in a Miscanthus x giganteus field . Roots stimulated litter decomposition, but balanced this loss by transferring carbon into more persistent, aggregate associated SOM. Further, roots selectively mobilized nitrogen from litter without additional carbon release. Overall, our fundings suggest that roots can efficiently mine nitrogen and build persistent soil carbon.

This is a very first attempt to study various parameters of a medicinal plant, Delphinium suave Huth. The plant is erect, geophytic, herbaceous, with tuberous root, trifid in a palmatipartite, strigose cuneate leaf and white spurred zygomorphic flower. The root was isodiametric phellem with single non-glandular trichomes. The stem revealed single-layered cuticle, multiseriate epidermis, cortex, pith ray and uniserate bowed non-glandular trichomes. The leaf was amphistomatic, showed tapering trichomes, prismatic crystals and ranunculaceous stomata with circumference 144.66-182.67 µm. Pollen grains in Light Microscopy (LM), were prolate, spheroidal trizonocolpate, isopolar, radiosymmetric, scabrate, elliptic and monads. Scanning Electron Microscope (SEM) pollen surface was scabrate, monad, size varied from 18.06 µm-16.67µm, colpus to inaperturate, tricolpate, ornamented, echinus, isopolar, isodiametric and circular. SEM roots showed sclerenchymatic tissues, stellate, glandular, non-glandular trichomes and crystals. The stem showed scalariform, pitted vessels, warty protuberances, unicellular, silicified, non-glandular trichomes. Leaves powder revealed, simple, unicellular, tapered headed, uniseriate, sessile, capitate, unbranched glandular, non-glandular, trichomes with crystals. Capitate, stellate, circular, unicellular, branchy trichomes were observed for the first time through SEM. Powder drug study of root, stem leaves through LM also revealed different tissues. Preliminary phytochemical revealed alkaloids, anthocyanins, anthraquinones, coumarins, flavones, mucilages, saponins, steroids, terpenoids, volatile oils and proteins. GC/MS showed 36 compounds in roots 33 in stem while 40 in leaves. Fluorescence analysis of roots, stem and leaves showed variation in colour when treated with chemicals. This study will assist pharmacognostic exploration, authentication from adulterants/allied species for consistent quality, resulting in safe use, preservation and efficacy.

Since the publication of the last Cellular Therapy and Stem Cell Transplant blueprint in 2013, Children’s Oncology Group cellular therapy-based trials for advanced the field and created new standards of care across a wide spectrum of pediatric cancer diagnoses. Key findings include that tandem autologous transplant improved survival for patients with neuroblastoma and atypical teratoid/rhabdoid brain tumors, one umbilical cord blood (UCB) donor was safer than two UCB donors, killer immunoglobulin receptor (KIR) mismatched donors did not improve survival for pediatric acute myeloid leukemia when in vivo T cell depletion is used and the depth of remission as measured by next-generation sequencing based minimal residual disease assessment pre-transplant was the best predictor of relapse for acute lymphoblastic leukemia. Plans for the next decade include optimizing donor selection for transplants for acute leukemia/myelodysplastic syndrome, using novel engineered cellular therapies to target a wide array of malignancies, and developing better treatments for cellular therapy toxicities such as viral infections and graft-vs-host disease.