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The use of technology in ecology and conservation offers unprecedented opportunities to survey and monitor wildlife remotely, for example by using camera traps. However, such solutions typically cause challenges stemming from the big datasets gathered, such as millions of camera trap images. Artificial intelligence is a proven, powerful tool to automate camera trap image analyses, but this is so far largely been restricted to species identification from images. Here, we develop and test an artificial intelligence algorithm that allows discrimination of individual animals carrying a tag (in this case a patagial yellow tag on vultures) from a large array of camera trap images. Such a tool could assist scientists and practitioners using similar patagial tags on vultures, condors and other large birds worldwide. We show that the overall performance of such an algorithm is relatively good, with 88.9% of all testing images (i.e. those not used for training or validation) correctly classified using a cut-off discrimination of 0.4. Specifically, performance was high for correctly classifying images with a tag (95.2% of all positive images correctly classified), but less so for images without a tag (87.0% of all negative images). The correct classification of images with a tag was, however, significantly higher when the tag code was at least partly readable compared with the other cases. Overall, this study underscores the potential of artificial intelligence for assisting scientists and practitioners in analysing big datasets from camera traps.

The current study investigated the dynamic reciprocal relationships between adolescents' school victimization and self-esteem during the first 2 years in secondary schools and how the relationships varied by social support. Participants were 2550 Chinese adolescents (52% males; 48% females) aged 11-16 years (Mage = 12.99 years, SDage = 0.58) who had just entered secondary school and were followed for 2 years. A cross-lagged path analysis was used to examine the reciprocal relationships between school victimization and self-esteem, and a multiple-group analysis was used to examine the moderating roles of peer support and teacher support. The results showed that from the fall semester to the spring semester in Grade 7, adolescents' victimization predicted subsequent low self-esteem, while from the spring semester in Grade 7 to the fall semester in Grade 8 and from the fall semester in Grade 8 to the spring semester in Grade 8, adolescents' low self-esteem predicted subsequent victimization. Furthermore, teacher support moderated the relationship between victimization and self-esteem, such that the above negative associations existed only when adolescents' perceived teacher support was low. However, this protective effect was not found with peer support. The findings highlight the transactional dynamics between school victimization and self-esteem and the protective role of teacher support, which has implications for effectively preventing and intervening school bullying.

Specialized diterpenoid metabolites are important mediators of plant-environment interactions in monocot crops. To understand metabolite functions in plant environmental adaptation that ultimately can enable crop improvement strategies, a deeper knowledge of the underlying species-specific biosynthetic pathways is required. Here, we report the genomics-enabled discovery of five cytochrome P450 monooxygenases (CYP71Z25-CYP71Z29) that form previously unknown furanoditerpenoids in the monocot bioenergy crop Panicum virgatum (switchgrass). Combinatorial pathway reconstruction showed that CYP71Z25-CYP71Z29 catalyze furan ring addition directly to primary diterpene alcohol intermediates derived from distinct class II diterpene synthase products. Transcriptional co-expression patterns and the presence of select diterpenoids in switchgrass roots support the occurrence of P450-derived furanoditerpenoids in planta. Integrating molecular dynamics, structural analysis and targeted mutagenesis identified active site determinants that contribute to the distinct catalytic specificities underlying the broad substrate promiscuity of CYP71Z25-CYP71Z29 for native and non-native diterpenoids.

Electrochemical organic synthesis has attracted increasing attentions as a sustainable and versatile synthetic platform. Quantitative assessment of the electro-organic reactions, including reaction thermodynamics, electro-kinetics, and coupled chemical processes, can lead to effective analytical tool to guide their future design. Herein, we demonstrate that electrochemical parameters such as onset potential, Tafel slope, and effective voltage can be utilized as electro-descriptors for the evaluation of reaction conditions and prediction of reactivities (yields). An "electro-descriptor-diagram" is generated, where reactive and non-reactive conditions/substances show distinct boundary. Successful predictions of reaction outcomes have been demonstrated using electro-descriptor diagram, or from machine learning algorithms with experimentally-derived electro-descriptors. This method represents a promising tool for data-acquisition, reaction prediction, mechanistic investigation, and high-throughput screening for general organic electro-synthesis.

Background Muscular invasive bladder cancer (MIBC) is a common malignant tumor in the world. Because of their heterogeneity in prognosis and response to treatment, biomarkers that can predict survival or help make treatment decisions in patients with MIBC are essential for individualized treatment. Aim We aimed to integrate bioinformatics research methods to identify a set of effective biomarkers capable of predicting, diagnosing, and treating MIBC. To provide a new theoretical basis for the diagnosis and treatment of bladder cancer. Methods and results Gene expression profiles and clinical data of MIBC were obtained by downloading from the Cancer Genome Atlas database. A dataset of 129 MIBC cases and controls was included. 2084 up-regulated genes and 2961 down-regulated genes were identified by differentially expressed gene (DEG) analysis. Then, gene ontology analysis was performed to explore the biological functions of DEGs, respectively. The up-regulated DEGs are mainly enriched in epidermal cell differentiation, mitotic nuclear division, and so forth. They are also involved in the cell cycle, p53 signaling pathway, PPAR signaling pathway, and so forth. The weighted gene co-expression network analysis yielded five modules related to pathological stages and grading, of which blue and turquoise were the most relevant modules for MIBC. Next, Using Kaplan-Meier survival analysis to identify further hub genes, the screening criteria at p ≤ .05, we found CNKSR1, HIP1R, CFL2, TPM1, CSRP1, SYNM, POPDC2, PJA2, and RBBP8NL genes associated with the progression and prognosis of MIBC patients. Finally, immunohistochemistry experiments further confirmed that CNKSR1 plays a vital role in the tumorigenic context of MIBC. Conclusion The research suggests that CNKSR1, POPDC2, and PJA2 may be novel biomarkers as therapeutic targets for MIBC, especially we used immunohistochemical further to validate CNKSR1 as a therapeutic target for MIBC which may help to improve the prognosis for MIBC.

Helical topological structures are often found in chiral biological systems, but seldom in synthesized polymers. Now, controllable microphase separation of amphiphilic liquid-crystalline block copolymers (LCBCs) consisting of hydrophilic poly(ethylene oxide) and hydrophobic azobenzene-containing poly(methylacrylate) is combined with chirality transfer to fabricate helical nanostructures by doping with chiral additives (enantiopure tartaric acid). Through hydrogen-bonding interactions, chirality is transferred from the dopant to the aggregation, which directs the hierarchical self-assembly in the composite system. Upon optimized annealing condition, helical structures in film are fabricated by the induced aggregation chirality. The photoresponsive azobenzene mesogens in the LCBC assist photoregulation of the self-assembled helical morphologies. This allows the construction and non-contact manipulation of complicated nanostructures.

A photothermal genome-editing strategy is described to improve immune checkpoint blockade (ICB) therapy by CRISPR/Cas9-mediated disruption of PD-L1 and mild-hyperthermia-induced activation of immunogenic cell death (ICD). This strategy relies on a supramolecular cationic gold nanorod that not only serves as a carrier to deliver CRISPR/Cas9 targeting PD-L1, but also harvests the second near-infrared-window (NIR-II) light and converts into mild hyperthermia to induce both ICD and gene expression of Cas9. The genomic disruption of PD-L1 significantly augments ICB therapy by improving the conversion of dendritic cells to T cells, followed by promoting the infiltration of cytotoxic T lymphocytes into tumors, thereby reprogramming immunosuppressive tumor microenvironment into immunoactive one. Such a therapeutic modality greatly inhibits the activity of primary and metastatic tumors and exhibits long-term immune memory effects against both rechallenged and recurrent tumors. The current therapeutic strategy for synergistic PD-L1 disruption and ICD activation represents an appealing way for cancer immunotherapy.

A synergic interface design is demonstrated for photostable inorganic mixed-halide perovskite solar cells (PVSCs) by applying an amino-functionalized polymer (PN4N) as cathode interlayer and a dopant-free hole-transporting polymer poly[5,5'-bis(2-butyloctyl)-(2,2'-bithiophene)-4,4'-dicarboxylate-alt-5,5'-2,2'-bithiophene] (PDCBT) as anode interlayer. First, the interfacial dipole formed at the cathode interface reduces the workfunction of SnO2 , while PDCBT with deeper-lying highest occupied molecular orbital (HOMO) level provides a better energy-level matching at the anode, leading to a significant enhancement in open-circuit voltage (Voc ) of the PVSCs. Second, the PN4N layer can also tune the surface wetting property to promote the growth of high-quality all-inorganic perovskite films with larger grain size and higher crystallinity. Most importantly, both theoretical and experimental results reveal that PN4N and PDCBT can interact strongly with the perovskite crystal, which effectively passivates the electronic surface trap states and suppresses the photoinduced halide segregation of CsPbI2 Br films. Therefore, the optimized CsPbI2 Br PVSCs exhibit reduced interfacial recombination with efficiency over 16%, which is one of the highest efficiencies reported for all-inorganic PVSCs. A high photostability with a less than 10% efficiency drop is demonstrated for the CsPbI2 Br PVSCs with dual interfacial modifications under continuous 1 sun equivalent illumination for 400 h.