Enhancing the Efficiency and Stability of Perovskite Solar Cells Using Chemical Bath Deposition of SnO2 Electron Transport Layers and 3D/2D Heterojunctions.

Chemical bath deposition (CBD) is an effective technique used to produce high-quality SnO2 electron transport layers (ETLs) employed in perovskite solar cells (PSCs). By optimizing the CBD process, high-quality SnO2 films are obtained with minimal oxygen vacancies and close energy level alignment with the perovskite layer. In addition, the 3D perovskite layers are passivated with n-butylammonium iodide (BAI), iso-pentylammonium iodide (PNAI), or 2-methoxyethylammonium iodide (MOAI) to form 3D/2D heterojunctions, resulting in defect passivation, suppressing ion migration and improving charge carrier extraction. As a result of these heterojunctions, the power conversion efficiency (PCE) of the PSCs increased from 21.39% for the reference device to 23.70% for the device containing the MOAI-passivated film. The 2D perovskite layer also provides a hydrophobic barrier, thus enhancing stability to humidity. Notably, the PNAI-based device exhibited remarkable stability, retaining approximately 95% of its initial efficiency after undergoing 1000-h testing in an N2 environment at room temperature.

Visible light-induced metal-free cascade denitrogenative borylation and iodination of nitroarenes.

An efficient method was developed for the one-pot construction of C-B and C-I via visible light-induced transformation of nitroarenes. This protocol relies on the photochemical properties of nitroarenes under visible light, followed by reduction with B2pin2 and diazotization with tBuONO. An array of arylboronates and iodobenzenes were constructed smoothly after excitation with purple LEDs at room temperature. In addition, the synthetic utility of this method was further demonstrated in the late-stage modification of a drug molecule. The advantages of this strategy include metal-free system, mild reaction conditions and acceptable substrate scope.

Biogated mesoporous silica nanoagents for inhibition of cell migration and combined cancer therapy.

Migration is an initial step in tumor expansion and metastasis; suppressing cellular migration is beneficial to cancer therapy. Herein, we designed a novel biogated nanoagents that integrated the migration inhibitory factor into the mesoporous silica nanoparticle (MSN) drug delivery nanosystem to realize cell migratory inhibition and synergistic treatment. Antisense oligonucleotides (Anti) of microRNA-330-3p, which is positively related with cancer cell proliferation, migration, invasion, and angiogenesis, not only acted as the locker for blocking drugs but also acted as the inhibitory factor for suppressing migration via gene therapy. Synergistic with gene therapy, the biogated nanoagents (termed as MSNs-Gef-Anti) could achieve on-demand drug release based on the intracellular stimulus-recognition and effectively kill tumor cells. Experimental results synchronously demonstrated that the migration suppression ability of MSNs-Gef-Anti nanoagents (nearly 30%) significantly contributed to cancer therapy, and the lethality rate of the non-small-cell lung cancer was up to 70%. This strategy opens avenues for realizing efficacious cancer therapy and should provide an innovative way for pursuing the rational design of advanced nano-therapeutic platforms with the combination of cancer cell migratory inhibition.

Core-shell "loading-type" nanomaterials enabling glucometer readout for portable and sensitive detection of p-aminophenol in real samples.

A one-target-many-trigger signal model sensing strategy is proposed for quickly, sensitive and on-site detection of the environmental pollutant p-aminophenol (PAP) by use of a commercial personal glucose meter (PGM) for signal readout with the core-shell "loading-type" nanomaterial MSNs@MnO2 as amplifiable nanoprobes. In this design, the mesoporous silica nanoparticles (MSNs) nanocontainer with entrapped signal molecule glucose is coated with redoxable manganese dioxide (MnO2) nanosheets to form the amplifiable nanoprobes (Glu-MSNs@MnO2). When encountered with PAP, the redox reaction between the MnO2 and PAP can induce the degradation of the outer layer of MSNs@MnO2, liberating multiple copies of the loaded glucose to light up the PGM signal. Owing to the high loading capability of nanocarriers, a "one-to-many" relationship exists between the target and the signal molecule glucose, which can generate adequate signal outputs to achieve the requirement of on-site determination of environmental pollutants. Taking advantage of this amplification mode, the developed PAP assay owns a dynamic linear range of 10.0-400 µM with a detection limit of 2.78 µM and provides good practical application performance with above 96.7 ± 4.83% recovery in environmental water and soil samples. Therefore, the PGM-based amplifiable sensor for PAP proposed can accommodate these requirements of environment monitoring and has promising potential for evaluating pollutants in real environmental samples.

Controlling Tin Halide Perovskite Oxidation Dynamics in Solution for Perovskite Optoelectronic Devices.

As a leading contender to replace lead halide perovskites, tin-based perovskites have demonstrated ever increasing performance in solar cells and light-emitting diodes (LEDs). They tend to be processed with dimethyl sulfoxide (DMSO) solvent, which has been identified as a major contributor to the Sn(II) oxidation during film fabrication, posing a challenge to the further improvement of Sn-based perovskites. Herein, we use NMR spectroscopy to investigate the kinetics of the oxidation of SnI2, revealing that autoamplification takes place, accelerating the oxidation as the reaction progresses. We propose a mechanism consistent with these observations involving water participation and HI generation. Building upon these insights, we have developed low-temperature Sn-based perovskite LEDs (PeLEDs) processed at 60 °C, achieving enhanced external quantum efficiencies (EQEs). Our research underscores the substantial potential of low-temperature DMSO solvent processes and DMSO-free solvent systems for fabricating oxidation-free Sn-based perovskites, shaping the future direction in processing Sn-containing perovskite materials and optoelectronic devices.

Activation of mTORC1 Signaling Cascade in Hippocampus and Medial Prefrontal Cortex Is Required for Antidepressant Actions of Vortioxetine in Mice.

BACKGROUND: Although thought of as a multimodal-acting antidepressant targeting the serotonin system, more molecules are being shown to participate in the antidepressant mechanism of vortioxetine. A previous report has shown that vortioxetine administration enhanced the expression of rapamycin complex 1 (mTORC1) in neurons. It has been well demonstrated that mTORC1 participates in not only the pathogenesis of depression but also the pharmacological mechanisms of many antidepressants. Therefore, we speculate that the antidepressant mechanism of vortioxetine may require mTORC1. METHODS: Two mouse models of depression (chronic social defeat stress and chronic unpredictable mild stress) and western blotting were first used together to examine whether vortioxetine administration produced reversal effects against the chronic stress-induced downregulation in the whole mTORC1 signaling cascade in both the hippocampus and medial prefrontal cortex (mPFC). Then, LY294002, U0126, and rapamycin were used together to explore whether the antidepressant effects of vortioxetine in mouse models of depression were attenuated by pharmacological blockade of the mTORC1 system. Furthermore, lentiviral-mTORC1-short hairpin RNA-enhanced green fluorescence protein (LV-mTORC1-shRNA-EGFP) was adopted to examine if genetic blockade of mTORC1 also abolished the antidepressant actions of vortioxetine in mice. RESULTS: Vortioxetine administration produced significant reversal effects against the chronic stress-induced downregulation in the whole mTORC1 signaling cascade in both the hippocampus and mPFC. Both pharmacological and genetic blockade of the mTORC1 system notably attenuated the antidepressant effects of vortioxetine in mice. CONCLUSIONS: Activation of the mTORC1 system in the hippocampus and mPFC is required for the antidepressant actions of vortioxetine in mice.

Cucurbitacin B Exerts Significant Antidepressant-Like Effects in a Chronic Unpredictable Mild Stress Model of Depression: Involvement of the Hippocampal BDNF-TrkB System.

BACKGROUND: Although depression has been a serious neuropsychiatric disorder worldwide, current antidepressants used in clinical practice have various weaknesses, including delayed onset and low rates of efficacy. Recently, the development of new antidepressants from natural herbal medicine has become one of the important research hotspots. Cucurbitacin B is a natural compound widely distributed in the Cucurbitaceae and Cruciferae families and has many pharmacological activities. The present study aimed to investigate whether cucurbitacin B possess antidepressant-like effects in mice. METHODS: The antidepressant-like effects of cucurbitacin B on mice behaviors were explored using the forced swim test, tail suspension test, open field test, sucrose preference test, and a chronic unpredictable mild stress model of depression together. Then, western blotting and immunofluorescence were used to examine the effects of cucurbitacin B on the brain-derived neurotrophic factor (BDNF)-tyrosine kinase B (TrkB) signaling cascade and neurogenesis in the hippocampus of mice. Furthermore, BDNF-short hairpin RNA, K252a, and p-chlorophenylalanine methyl ester were adopted together to determine the antidepressant mechanism of cucurbitacin B. RESULTS: It was found that administration of cucurbitacin B indeed produced notable antidepressant-like effects in mice, which were accompanied with significant promotion in both the hippocampal BDNF-TrkB pathway and neurogenesis. The antidepressant mechanism of cucurbitacin B involves the hippocampal BDNF-TrkB system but not the serotonin system. CONCLUSIONS: Cucurbitacin B has the potential to be a novel antidepressant candidate.

Salt-inducible kinase 1-CREB-regulated transcription coactivator 1 signalling in the paraventricular nucleus of the hypothalamus plays a role in depression by regulating the hypothalamic-pituitary-adrenal axis.

Elucidating the molecular mechanism underlying the hyperactivity of the hypothalamic-pituitary-adrenal axis during chronic stress is critical for understanding depression and treating depression. The secretion of corticotropin-releasing hormone (CRH) from neurons in the paraventricular nucleus (PVN) of the hypothalamus is controlled by salt-inducible kinases (SIKs) and CREB-regulated transcription co-activators (CRTCs). We hypothesised that the SIK-CRTC system in the PVN might contribute to the pathogenesis of depression. Thus, the present study employed chronic social defeat stress (CSDS) and chronic unpredictable mild stress (CUMS) models of depression, various behavioural tests, virus-mediated gene transfer, enzyme-linked immunosorbent assay, western blotting, co-immunoprecipitation, quantitative real-time reverse transcription polymerase chain reaction, and immunofluorescence to investigate this connection. Our results revealed that both CSDS and CUMS induced significant changes in SIK1-CRTC1 signalling in PVN neurons. Both genetic knockdown of SIK1 and genetic overexpression of CRTC1 in the PVN simulated chronic stress, producing a depression-like phenotype in naive mice, and the CRTC1-CREB-CRH pathway mediates the pro-depressant actions induced by SIK1 knockdown in the PVN. In contrast, both genetic overexpression of SIK1 and genetic knockdown of CRTC1 in the PVN protected against CSDS and CUMS, leading to antidepressant-like effects in mice. Moreover, stereotactic infusion of TAT-SIK1 into the PVN also produced beneficial effects against chronic stress. Furthermore, the SIK1-CRTC1 system in the PVN played a role in the antidepressant actions of fluoxetine, paroxetine, venlafaxine, and duloxetine. Collectively, SIK1 and CRTC1 in PVN neurons are closely involved in depression neurobiology, and they could be viable targets for novel antidepressants.

Self-powered DNA nanomachines for fluorescence detection of lead.

A versatile DNA nanomachine detection system has been developed via the combination of DNAzyme with catalytic hairpin assembly (CHA) technology for achieving accurate and sensitive detection of lead ions (Pb2+). In the presence of target Pb2+, capture DNA nanomachine formed by AuNP and DNAzyme recognized and reacted with Pb2+, which yielded an "active" DNAzyme, that induced the cleavage of substrate strand, and then released the initiator DNA (TT) for CHA. With the help of the initiator DNA TT, self-powered CHA was activated to achieve the signal amplification reaction in the detection of DNA nanomachine. Meanwhile, the initiator DNA TT was released and hybridized with the other H1 strand to initiate another CHA, replacement, and turnovers, producing enhanced fluorescence signal of fluorophore FAM (excitation 490 nm/emission 520 nm) for sensitive determination of Pb2+. Under the optimized conditions, the DNA nanomachine detection system revealed high selectivity toward Pb2+ in the concentration range 50-600 pM, with the limit of detection (LOD) of 31 pM. Recovery tests demonstrated that the DNA nanomachine detection system has excellent detection capability in real samples. Therefore, the proposed strategy can be extended and act as a basic platform for highly accurate and sensitive detection of various heavy metal ions.

Heterogeneous deep graph convolutional network with citation relational BERT for COVID-19 inline citation recommendation.

The outbreak of COVID-19 brings almost the biggest explosions of scientific literature ever. Facing such volume literature, it is hard for researches to find desired citation when carrying out COVID-19 related research, especially for junior researchers. This paper presents a novel neural network based method, called citation relational BERT with heterogeneous deep graph convolutional network (CRB-HDGCN), for COVID-19 inline citation recommendation task. The CRB-HDGCN contains two main stages. The first stage is to enhance the representation learning of BERT model for COVID-19 inline citation recommendation task through CRB. To achieve the above goal, an augmented citation sentence corpus, which replaces the citation placeholder with the title of the cited papers, is used to lightly retrain BERT model. In addition, we extract three types of sentence pair according citation relation, and establish sentence prediction tasks to further fine-tune the BERT model. The second stage is to learn effective dense vector of nodes among COVID-19 bibliographic graph through HDGCN. The HDGCN contains four layers which are essentially all sub neural networks. The first layer is initial embedding layer which generates initial input vectors with fixed size through CRB and a multilayer perceptron. The second layer is a heterogeneous graph convolutional layer. In this layer, we expand traditional homogeneous graph convolutional network into heterogeneous by subtly adding heterogeneous nodes and relations. The third layer is a deep attention layer. This layer uses trainable project vectors to reweight the node importance simultaneously according to both node types and convolution layers, which further promotes the performance of learnt node vectors. The last decoder layer recovers the graph structure and let the whole network trainable. The recommendation is finally achieved by integrating the high performance heterogeneous vectors learnt from CRB-HDGCN with the query vectors. We conduct experiments on the CORD-19 and LitCovid datasets. The results show that compared with the second best method CO-Search, CRB-HDGCN improves MAP, MRR, P@100 and R@100 with 21.8%, 22.7%, 37.6% and 21.2% on CORD-19, and 29.1%, 25.9%, 15.3% and 11.3% on LitCovid, respectively.