Plants can detect neighbouring plants through a reduction in the ratio between red and far-red light (R:FR). This provides a signal of plant-plant competition and induces rapid plant growth while inhibiting defence against biotic stress, two interlinked responses designated as the shade avoidance syndrome (SAS). Consequently, the SAS can influence plant-herbivore interactions that could cascade to higher trophic levels. However, little is known on how the expression of the SAS can influence tritrophic interactions. We investigated whether changes in R:FR affect the emission of herbivore-induced plant volatiles (HIPVs), and whether these changes influence the attraction of the zoophytophagous predator Macrolophus pygmaeus. We also studied how the expression of the SAS and subsequent inhibition of plant defences affects the reproduction of M. pygmaeus in both the presence and absence of the greenhouse whitefly ( Trialeurodes vaporariorum) as arthropod prey. The results show that changes in R:FR have little effect on HIPV emissions and predator attraction. However, a reduction in R:FR leads to increased reproduction of both the predator and the whiteflies. We conclude that shade avoidance responses can increase the population development of M. pygmaeus directly by reducing plant defences, and indirectly by supporting higher herbivore densities.

This paper aims to understand the binding strategies of a nanobody-protein pair by studying known complexes. Rigid body protein-ligand docking programs produce several complexes, called decoys, which are good candidates with high scores of shape complementarity, electrostatic interactions, desolvation, buried surface area, and Lennard-Jones potentials. It is not known which decoy represents the true structure. We studied thirty-seven nanobody-protein complexes from the Single Domain Antibody Database, sd-Ab DB, [http://www.sdab-db.ca/](http://www.sdab-db.ca/). For each structure, a large number of decoys are generated using the Fast Fourier Transform algorithm of the software ZDOCK. The decoys were ranked according to their target protein-nanobody interaction energies, calculated by using the Dreiding Force Field, with rank 1 having the lowest interaction energy. Out of thirty-six PDB structures, twenty-five true structures were predicted as rank 1. Eleven of the remaining structures required Ångstrom size rigid body translations of the nanobody relative to the protein to match the given PDB structure. After the translation the Dreiding interaction (DI) energies of all complexes decreased and became rank 1. In one case, rigid body rotations as well as translations of the nanobody were required for matching the crystal structure. We used a Monte Carlo algorithm that randomly translates and rotates the nanobody of a decoy and calculates the DI energy. Results show that rigid body translations and the DI energy are sufficient for determining the correct binding location and pose of ZDOCK created decoys. A survey of the sd-Ab DB showed that each nanobody makes at least one salt bridge with its partner protein, indicating that salt bridge formation is an essential strategy in nanobody-protein recognition. Based on the analysis of the thirty-six crystal structures and evidence from existing literature, we propose a set of principles that could be used in the design of nanobodies.

Title: Sweet syndrome masquerading as a disseminated and pulmonary fungal disease in a child with acute myeloid leukemia: case report and review of the literature

Here we present a diagnostically challenging Bing-Neel Syndrome (BNS) case successfully treated with systemic chemoimmunotherapy and ibrutinib, with remarkable clinical response. BNS is an extremely rare direct central nervous system infiltration by malignant lymphoplasmocytic lymphoma cells in patients with Waldenstroms macroglobulinaemia.

Connectivity maintains the spatial dynamics of metapopulations by promoting dispersal between habitat patches, potentially buffering populations and communities against continued global change. However, this function is threatened by habitats becoming increasingly fragmented, and habitat matrices becoming increasingly inhospitable, potentially reducing the resilience and persistence of populations. Yet, we lack a clear understanding of how reduced connectivity interacts with rates of environmental change to destabilise populations. Using laboratory microcosms containing metapopulations of the Collembola Folsomia candida, we investigate the impact of habitat connectivity on metapopulation persistence under a range of simulated droughts, a key stressor for this species. We manipulated both drought severity and the number of patches affected by drought across landscapes connected by either good or poor-quality corridors. We measured the time of population extinction, the maximum rate of population decline, and the variability of abundance among patches as criteria to evaluate the persistence ability of metapopulations. We show that whilst drought severity and number of drought-affected patches negatively influenced population persistence, these results were mitigated by increased habitat connectivity, which increased population persistence time and decreased both how fast populations declined and the variability in abundance among patches. Our results suggest that enhancing spatial connectivity can increase the persistence of metapopulations, increasing the time available for conservation actions to take effect, and/or for species to adapt or move in the face of continued stress. Given that fragmentation increases the isolation of habitats, improving habitat connectivity by using good quality corridors may provide a useful strategy to enhance the resistance of spatially structured populations.

Background Malignant brain tumors are among the most threatening diseases of the central nervous system, and despite increasingly updated treatments, the prognosis has not been improved. Tumor treating fields (TTFields) are an emerging approach in cancer treatment using intermediate-frequency and low-intensity electric field, and can lead to development of novel therapeutic options. Recent findings A series of biological processes induced by TTFields to exert anti-cancer effects have been identified, and applications of TTFields in oncology have been increasingly reported. This review addresses the mechanisms of TTFields and recent advances in the application of TTFields therapy in malignant brain tumors, especially in glioblastoma (GBM). Conclusions As a novel therapeutic strategies, TTFields have shown promising results in many clinical trials, especially in GBM, and continue to evolve. A growing number of patients with malignant brain tumors are being enrolled in ongoing clinical studies demonstrating that TTFields-based combination therapies can improve treatment outcomes.

Direct visualization of polymer crystalline structure remains challenging due to the lack of contrast across different microphases of polymers. Here we address this conundrum using an aggregation-induced emission luminogen (AIEgen) with confinement fluorescence effect, which could be used as a “built-in” sensor to label different crystalline phases. Computational simulations reveal that the confined space induces the AIEgens to take a more planar conformation, resulting in a red-shifted emission spectrum. With this property, the information of various polymer crystalline forms is converted into different fluorescence colors, which is attributed to the different spatial dimensions of the polymer amorphous layer between lamellar crystals where the AIEgens are located. Finally, polymer crystalline phases distinction, quantitative crystallinity determination, and stereocomplex crystals visualization are achieved, providing a relationship between crystalline microstructure and fluorescence signals. This work demonstrates the potential of AIE fluorescence technology in polymer science, providing a theoretical and experimental guideline for the materials processing and optimization of mechanical performance.

Tropical rainforests around the world are rapidly converted into cash crop agricultural systems. The associated massive losses of plant and animal species lead to changes in arthropod food webs and the energy fluxes therein. These changes are poorly understood, in particular in the extremely biodiverse canopies of tropical ecosystems. Using canopy fogging followed by stable isotope and energy flux analyses, we show that land-use conversion from rainforest to rubber and oil palm plantations not only causes a drastic reduction in energy fluxes of up to 75%, but also shifts fluxes among trophic groups. While rainforest featured high levels of both herbivory and algae-microbivory, and a balanced ratio of herbivory to predation, relative fluxes were shifted towards predation in rubber and towards herbivory in oil palm plantations, indicating profound shifts in ecosystem functioning. Our results highlight that the ongoing loss of animal biodiversity and biomass in tropical canopies degrades animal-driven functions and restructures canopy food webs.

Single junction crystalline silicon (c-Si) solar cells are reaching their practical efficiency limit while perovskite/c-Si tandem solar cells have achieved efficiencies above the theoretical limit of single junction c-Si solar cells. Next to low-thermal budget silicon heterojunction architecture, high-thermal budget carrier-selective passivating contacts (CSPCs) based on polycrystalline-SiO x (poly-SiO x) also constitute a promising architecture for high efficiency perovskite/c-Si tandem solar cells. In this work, we present the development of c-Si bottom cells based on high-temperature poly-SiO x CSPCs and demonstrate novel high-efficiency four-terminal (4T) and two-terminal (2T) perovskite/c-Si tandem solar cells. First, we tuned the ultra-thin, thermally grown SiO x. Then we optimized the passivation properties of p-type and n-type doped poly-SiO x CSPCs. Here, we have optimized the p-type doped poly-SiO x CSPC on textured interfaces via a two-step annealing process. Finally, we integrated such bottom solar cells in both 4T and 2T tandems, achieving 28.1% and 23.2% conversion efficiency, respectively.

Background: Hispanic people with cystic fibrosis (CF) have decreased life expectancy and earlier acquisition of Pseudomonas aeruginosa compared to non-Hispanic white individuals with CF. Racial and ethnic differences in the airway microbiome of CF may contribute to known health disparity, but have not been studied. The objective was to describe differences in the upper airway microbial community in Hispanic and non-Hispanic white children with CF. Methods: This prospective, observational cohort study of fifty-nine Hispanic and non-Hispanic white children with CF, ages 2-10 years old, was performed at Texas Children’s Hospital (TCH) from February 2019 to January 2020. Oropharyngeal swabs were collected from the cohort during clinic visit. Swab samples underwent sequencing (16S V4 rRNA), diversity analysis, and taxonomic profiling. Key demographic and clinical data were collected from the electronic medical record and the Cystic Fibrosis Foundation Patient Registry (CFFPR). Statistical analysis compared sequencing, demographic, and clinical data. Results: We found no significant difference in Shannon diversity or relative abundance of bacterial phyla between Hispanic and non-Hispanic children with CF. However, a low abundant taxa- “uncultured bacterium” belonging to the order Saccharimonadales was significantly higher in Hispanic children (mean relative abundance=0.13%) compared to the non-Hispanic children (0.03%). Hispanic children had increased incidence of Pseudomonas aeruginosa (p=0.045) compared to non-Hispanic children. Conclusion: We did not find a significant difference in the airway microbial diversity between Hispanic and non-Hispanic white children with CF. However, we found a greater relative abundance of Saccharimonadales and higher incidence of Pseudomonas aeruginosa in Hispanic children with CF.

Soft tissue candidiasis is an opportunistic infection that occurs in immunocompromised patients and must always be diagnosed and treated as soon as possible. In this case report, the patient is a 14-year-old boy with acute myeloid leukemia M3-type who presented with numerous soft tissue and hepatosplenic candidal abscesses.

Chronic kidney disease associated with incidental tuberculoma represents one of the rarest conditions occurring worldwide. Among tuberculous patients, only 1% show Central Nervous System involvement. We present a case of 45-year-old male with CKD who presented with seizure, diagnosed to have incidental Tuberculoma

Schizophrenia remains a sizable socioeconomic burden that continues to be treated with therapeutics based on 70-year old science. All currently approved therapeutics primarily target the dopamine D2 receptor to achieve their efficacy. Whilst dopaminergic dysregulation is a key feature in this disorder, the targeting of dopaminergic machinery has yielded limited efficacy and an appreciable side effect burden. Over the recent decades, numerous drugs that engage non-dopaminergic GPCRs have yielded a promise of efficacy without the deleterious side effect profile, yet none have successfully completed clinical studies and progressed to the market. More recently, there has been increased attention around non-dopaminergic GPCR-targeting drugs, notably KarXT, which demonstrated efficacy in some schizophrenia symptom domains. This provides renewed hope that effective schizophrenia may lay outside of the dopaminergic space. Despite the potential for muscarinic receptor- (and other well-characterised GPCR families) targeting drugs to treat schizophrenia, they are often plagued with complications such as lack of receptor subtype selectivity and peripheral on-target side-effects. Orphan GPCR studies have opened a new avenue of exploration with many demonstrating schizophrenia-relevant mechanisms and a favourable expression profile, thus offering potential for novel drug development. This review discusses centrally-expressed orphan G protein-coupled receptors: GPR3, GPR6, GPR12, GPR52, GPR85, GPR88 and GPR139 and their relationship to schizophrenia. We review their expression, signalling mechanisms and cellular function, in conjunction with small molecule development and structural insights. We seek to provide a snapshot of the growing evidence and development potential of new classes of schizophrenia therapeutics.

Background Several good results of clinical trial of nivolumab or involving nivolumab in advanced esophageal squamous cell carcinoma were reported. However, the response rate was still poor. A rare phenomenon called the “abscopal effect” refers to the regression of not only the irradiated tumor but also non-irradiated distant tumors after local radiotherapy. The mechanism is not completely clear, but it is thought that the activation of anti-tumor immunity induced by radiotherapy is the main factor. Case A 66-year-old man with recurred and nivolumab resistant esophageal squamous cell carcinoma in left-side cervical and abdominal para-aortal lymph node metastasis was treated with a total of 40 Gy (10 fractions) of radiotherapy to the left-side cervical lymph node metastasis which caused neck pain as a palliative treatment. Nivolumab was resumed the day after completion of radiotherapy. At 3 months after radiotherapy showed that the irradiated lesion in the left neck had regressed to a scar-like appearance. Notably, the abdominal para-aortal lymph nodes outside the irradiation area, which had previously tended to progress, had also shrunk (abscopal effect). The T cell receptor and B cell receptor (TCR/BCR) repertoire analysis before and after radiotherapy revealed that radiotherapy caused the changes in the TCR/BCR repertoire. Conclusion Changes in the TCR/BCR receptor repertoire repertoires were assumed to be a part of the mechanism of the abscopal effect. The findings in this patient suggest that combination of immune checkpoint inhibitors and radiotherapy can be a promising treatment approach, even for patients with immune checkpoint inhibitors resistant cancer.

In recent years, developing dopant-free carrier-selective contacts, instead of heavily doped Si layer (either externally or internally), for crystalline silicon (c-Si) solar cells have attracted considerable interests with the aims to reduce parasitic light absorption and fabrication cost. However, the stability still remains a big challenge for dopant-free contacts, especially when thermal treatment is involved, which limits their industrial adoption. In this study, a perovskite material ZnTiO 3 combining with an ultrathin (~1 nm) SiO 2 film and Al layer is used as an electron-selective contact, forming an isotype heterojunction with n-type c-Si. The perovskite/c-Si heterojunction solar cells exhibit a performance-enhanced effect by post-metallization annealing when the annealing temperature is 200-350 °C. Thanks to the post-annealing treatment, an impressive efficiency of 22.0% has been demonstrated, which is 3.5% in absolute value higher than that of the as-fabricated solar cell. A detailed material and device characterization reveal that post annealing leads to the diffusion of Al into ZnTiO 3 film, thus doping the film and reducing its work function. Besides, the coverage of SiO 2 is also improved. Both these two factors contribute to the enhanced passivation effect and electron selectivity of the ZnTiO 3-based contact, and hence improve the cell performance.

By protein structure prediction (PSP) we refer to the prediction of the 3-dimensional (3D) folding of a protein, known as tertiary structure, starting from its amino acid sequence, known as primary structure. The state-of-the-art in PSP is currently achieved by complex deep learning pipelines that require several input features extracted from amino acid sequences. It has been demonstrated that features that grasp the relative orientation of amino acids in space positively impacts the prediction accuracy of the 3D coordinates of atoms in the protein backbone. In this paper, we demonstrate the relevance of Geometric Algebra (GA) in instantiating orientational features for PSP problems. We do so by proposing two novel GA-based metrics which contain information on relative orientations of amino acid residues. We then employ these metrics as an additional input features to a Graph Transformer (GT) architecture to aid the prediction of the 3D coordinates of a protein, and compare them to classical angle-based metrics. We show how our GA features yield comparable results to angle maps in terms of accuracy of the predicted coordinates. This is despite being constructed from less initial information about the protein backbone. The features are also fewer and more informative, and can be (i) closely associated to protein secondary structures and (ii) more readily predicted compared to angle maps. We hence deduce that GA can be employed as a tool to simplify the modeling of protein structures and pack orientational information in a more natural and meaningful way.

Background Artificial intelligence (AI) is a promising field in the neonatal field.  We focused on lung ultrasound (LUS), a useful tool for the neonatologist. Our aim was to train a neural network to create a model able to interpret LUS. Methods Our multicentric, prospective study included newborns with gestational age (GA) ≥ 33+0 weeks with early tachypnea/dyspnea/oxygen requirements. For each baby, three LUS were performed: within 3 hours of life (T0), at 4–6 hours of life (T1) and in the absence of respiratory support (T2). Each scan was processed to extract ROI used to train a neural network to classify it according to the LUS score. We assessed sensitivity, specificity, positive and negative predictive value of the AI model’s scores in predicting the need for respiratory assistance with nasal Continuous Positive Airway Pressure (nCPAP) and for surfactant, compared to the “classical” scores. Results We enrolled 62 newborns (GA=36±2 weeks). In the prediction of the need for CPAP, we found a cut-off of 6 (at T0) and 5 (at T1) for both the classical nLUS and AI score. In the prediction of surfactant therapy we found a cut-off of 9 for both scores at T0, at T1 the nLUS cut-off was 6, while the AI’s one was 5. Classification accuracy was good both at the image and classes level. Conclusions This is, to our knowledge, the first attempt to use an AI model to interpret early neonatal LUS and can be extremely useful for neonatologist in the clinical setting.

Adhesion G protein-coupled receptors (aGPCRs) possess a unique topology including the presence of a GPCR proteolysis site (GPS) which upon autoproteolysis generates two functionally distinct fragments that remain non-covalently associated at the plasma membrane. A proposed activation mechanism for aGPCRs involves the release of a tethered agonist which depends on cleavage at the GPS. However, this hypothesis has been challenged by the observation that non-cleavable aGPCRs exhibit constitutive activity, thus making the function of GPS cleavage widely enigmatic. In this study, we sought to elucidate the function of GPS-mediated cleavage through the study of G protein coupling with Latrophilin-3/ADGRL3, a prototypical aGPCR involved in synapse formation and function. Using BRET-based G protein biosensors, we reveal that an autoproteolysis-deficient mutant of ADGRL3 retains constitutive activity. Surprisingly, we uncover that cleavage deficiency leads to a signaling bias directed at potentiating the activity of select G proteins such as Gi2 and G12/13. These data unveil the underpinnings of biased signaling for aGPCRs defined by GPS autoproteolysis.