A Difluoro-Methoxylated Ending-Group Asymmetric Small Molecule Acceptor Lead Efficient Binary Organic Photovoltaic Blend.

Developing a new end group for synthesizing asymmetric small molecule acceptors (SMAs) is crucial for achieving high-performance organic photovoltaics (OPVs). Herein, an asymmetric small molecule acceptor, BTP-BO-4FO, featuring a new difluoro-methoxylated end-group is reported. Compared to its symmetric counterpart L8-BO, BTP-BO-4FO exhibits an upshifted energy level, larger dipole moment, and more sequential crystallinity. By adopting two representative and widely available solvent additives (1-chloronaphthalene (CN) and 1,8-diiodooctane (DIO)), the device based on PM6:BTP-BO-4FO (CN) photovoltaic blend demonstrates a power conversion efficiency (PCE) of 18.62% with an excellent open-circuit voltage (VOC) of 0.933 V, which surpasses the optimal result of L8-BO. The PCE of 18.62% realizes the best efficiencies for binary OPVs based on SMAs with asymmetric end groups. A series of investigations reveal that optimized PM6:BTP-BO-4FO film demonstrates similar molecular packing motif and fibrillar phase distribution as PM6:L8-BO (DIO) does, resulting in comparable recombination dynamics, thus, similar fill factor. Besides, it is found PM6:BTP-BO-4FO possesses more efficient charge generation, which yields better VOC-JSC balance. This study provides a new ending group that enables a cutting-edge efficiency in asymmetric SMA-based OPVs, enriching the material library and shed light on further design ideas.

Precisely Controlling Polymer Acceptors with Weak Intramolecular Charge Transfer Effect and Superior Coplanarity for Efficient Indoor All-Polymer Solar Cells with over 27% Efficiency.

Indoor photovoltaics (IPVs) are garnering increasing attention from both the academic and industrial communities due to the pressing demand of the ecosystem of Internet-of-Things. All-polymer solar cells (all-PSCs), emerging as a sub-type of organic photovoltaics, with the merits of great film-forming property, remarkable morphological and light stability, hold great promise to simultaneously achieve high efficiency and long-term operation in IPV's application. However, the dearth of polymer acceptors with medium-bandgap has impeded the rapid development of indoor all-PSCs. Herein, we report a highly efficient medium-bandgap polymer acceptor (PYFO-V) through the synergistic effects of side chain engineering and linkage modulation and apply it for indoor all-PSCs operation. As a result, the PM6:PYFO-V-based indoor all-PSC yielded a highest efficiency of 27.1% under LED light conditions, marking the highest value for reported binary indoor all-PSCs to date. More importantly, the blade coated devices using non-halogenated solvent (o-xylene) maintained an efficiency over 23%, demonstrating the potential for industry-scale fabrication. Our work not only highlights the importance of fine-tuning intramolecular charge transfer effect and intrachain coplanarity in developing high-performance medium-bandgap polymer acceptors, but also provides a highly efficient strategy for indoor all-PSC application. This article is protected by copyright. All rights reserved.

Exploring the autophagy-related pathogenesis of active ulcerative colitis.

BACKGROUND: The pathogenesis of ulcerative colitis (UC) is complex, and recent therapeutic advances remain unable to fully alleviate the condition. AIM: To inform the development of novel UC treatments, bioinformatics was used to explore the autophagy-related pathogenesis associated with the active phase of UC. METHODS: The GEO database was searched for UC-related datasets that included healthy controls who met the screening criteria. Differential analysis was conducted to obtain differentially expressed genes (DEGs). Autophagy-related targets were collected and intersected with the DEGs to identiy differentially expressed autophagy-related genes (DEARGs) associated with active UC. DEARGs were then subjected to KEGG, GO, and DisGeNET disease enrichment analyses using R software. Differential analysis of immune infiltrating cells was performed using the CiberSort algorithm. The least absolute shrinkage and selection operator algorithm and protein-protein interaction network were used to narrow down the DEARGs, and the top five targets in the Dgree ranking were designated as core targets. RESULTS: A total of 4822 DEGs were obtained, of which 58 were classified as DEARGs. SERPINA1, BAG3, HSPA5, CASP1, and CX3CL1 were identified as core targets. GO enrichment analysis revealed that DEARGs were primarily enriched in processes related to autophagy regulation and macroautophagy. KEGG enrichment analysis showed that DEARGs were predominantly associated with NOD-like receptor signaling and other signaling pathways. Disease enrichment analysis indicated that DEARGs were significantly linked to diseases such as malignant glioma and middle cerebral artery occlusion. Immune infiltration analysis demonstrated a higher presence of immune cells like activated memory CD4 T cells and follicular helper T cells in active UC patients than in healthy controls. CONCLUSION: Autophagy is closely related to the active phase of UC and the potential targets obtained from the analysis in this study may provide new insight into the treatment of active UC patients.

Dissection of rhizosphere microbiome and exploiting strategies for sustainable agriculture.

The rhizosphere microbiome plays critical roles in plant growth and provides promising solutions for sustainable agriculture. While the rhizosphere microbiome frequently fluctuates with the soil environment, recent studies have demonstrated that a small proportion of the microbiome is consistently assembled in the rhizosphere of a specific plant genotype regardless of the soil condition, which is determined by host genetics. Based on these breakthroughs, which involved exploiting the plant-beneficial function of the rhizosphere microbiome, we propose to divide the rhizosphere microbiome into environment-dominated and plant genetic-dominated components based on their different assembly mechanisms. Subsequently, two strategies to explore the different rhizosphere microbiome components for agricultural production are suggested, that is, the precise management of the environment-dominated rhizosphere microbiome by agronomic practices, and the elucidation of the plant genetic basis of the plant genetic-dominated rhizosphere microbiome for breeding microbiome-assisted crop varieties. We finally present the major challenges that need to be overcome to implement strategies for modulating these two components of the rhizosphere microbiome.

Arecoline induces neurotoxicity in HT22 cells via the promotion of endoplasmic reticulum stress and downregulation of the Nrf2/HO-1 pathway.

Arecoline, the predominant bioactive substance extracted from areca nut (AN), is the world's fourth most frequently used psychoactive material. Research has revealed that chewing AN can affect the central nervous system (CNS) and may lead to neurocognitive deficits that are possibly linked to the action of arecoline. However, the mechanism behind the neurotoxicity caused by arecoline remains unclear. This study aimed to investigate the neurotoxic effects of arecoline and its underlying mechanism. The results showed that arecoline caused cytotoxicity against HT22 cells in a dose-dependent manner and induced apoptosis by upregulating the expression of pro-apoptotic caspase and Bcl-2 family proteins. Furthermore, arecoline escalated intracellular reactive oxygen species (ROS) levels and Ca2+ concentration with increasing doses, thereby motivating endoplasmic reticulum stress (ERS) and ERS-associated apoptotic protein expression. Additionally, the study found that arecoline attenuates intracellular antioxidant defense by inhibiting the translocation of NF-E2-related factor-2 (Nrf2) into the nucleus and decreasing downstream Heme oxygenase-1 (HO-1) levels. The specific inhibitor Sodium 4-phenylbutyrate (4-PBA) can dramatically attenuate arecoline-mediated cell apoptosis and ERS-associated apoptotic pathway expression by blocking ERS. The antioxidant N-Acetylcysteine (NAC) also effectively reverses the arecoline-mediated increase of ERS-related apoptotic pathway protein levels by scavenging intracellular ROS accumulation. In conclusion, this study suggests that arecoline induces neurotoxicity in HT22 cells via ERS mediated by oxidative stress- and Ca2+ disturbance, as well as by downregulation of the Nrf2/HO-1 pathway.

Solid-Phase Extraction and Enhanced Amplification-Free Detection of Pathogens Integrated by Multifunctional CRISPR-Cas12a.

Public healthcare demands effective and pragmatic diagnostic tools to address the escalating challenges in infection management in resource-limited areas. Recent advances in clustered regularly interspaced short palindromic repeat (CRISPR)-based biosensing promise the development of next-generation tools for disease diagnostics, including point-of-care (POC) testing for infectious diseases. The currently prevailing strategy of developing CRISPR/Cas-based diagnostics exploits only the target identification and trans-cleavage activity of a CRISPR-Cas12a/Cas13a system to provide diagnostic results, and they need to be combined with an additional preamplification reaction to enhance sensitivity. In contrast to this dual-function strategy, here, we present a new approach that collaboratively integrates the triple functions of CRISPR-Cas12a: target identification, sequence-specific enrichment, and signal generation. With this approach, we develop a nucleic acid assay termed Solid-Phase Extraction and Enhanced Detection Assay integrated by CRISPR-Cas12a (SPEEDi-CRISPR) that negates the need for preamplification but significantly improves the detection of limit (LOD) from the pM to fM level. Specifically, using Cas12a-coated magnetic beads, this assay combines efficient solid-phase extraction and enrichment of DNA targets enabled by the sequence-specific affinity of CRISPR-Cas12a with fluorogenic detection by activated Cas12a on beads. SPEEDi-CRISPR, for the first time, leverages the possibility of employing CRISPR/Cas12a in nucleic acid extraction and integrates the ability of both enrichment and detection of CRISPR/Cas into a single platform. Our proof-of-concept studies revealed that the SPEEDi-CRISPR assay has great specificity to distinguish HPV-18 from HPV-16, and Parvovirus B19, in addition to being able to detect HPV-18 at a concentration as low as 2.3 fM in 100 min and 4.7 fM in 60 min. Furthermore, we proved that this assay can be coupled with two point-of-care testing strategies: the smartphone-based fluorescence detector and the lateral flow assay. Overall, these results suggested that our assay could pave a new way for developing CRISPR diagnostics.

Non-halogenated Solvent-Processed Organic Solar Cells with Approaching 20 % Efficiency and Improved Photostability.

The development of high-efficiency organic solar cells (OSCs) processed from non-halogenated solvents is crucially important for their scale-up industry production. However, owing to the difficulty of regulating molecular aggregation, there is a huge efficiency gap between non-halogenated and halogenated solvent processed OSCs. Herein, we fabricate o-xylene processed OSCs with approaching 20 % efficiency by incorporating a trimeric guest acceptor named Tri-V into the PM6:L8-BO-X host blend. The incorporation of Tri-V effectively restricts the excessive aggregation of L8-BO-X, regulates the molecular packing and optimizes the phase-separation morphology, which leads to mitigated trap density states, reduced energy loss and suppressed charge recombination. Consequently, the PM6:L8-BO-X:Tri-V-based device achieves an efficiency of 19.82 %, representing the highest efficiency for non-halogenated solvent-processed OSCs reported to date. Noticeably, with the addition of Tri-V, the ternary device shows an improved photostability than binary PM6:L8-BO-X-based device, and maintains 80 % of the initial efficiency after continuous illumination for 1380 h. This work provides a feasible approach for fabricating high-efficiency, stable, eco-friendly OSCs, and sheds new light on the large-scale industrial production of OSCs.

Unraveling the copper-death connection: Decoding COVID-19's immune landscape through advanced bioinformatics and machine learning approaches.

This study aims to analyze Coronavirus Disease 2019 (COVID-19)-associated copper-death genes using the Gene Expression Omnibus (GEO) dataset and machine learning, exploring their immune microenvironment correlation and underlying mechanisms. Utilizing GEO, we analyzed the GSE217948 dataset with control samples. Differential expression analysis identified 16 differentially expressed copper-death genes, and Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) quantified immune cell infiltration. Gene classification yielded two copper-death clusters, with Weighted Gene Co-expression Network Analysis (WGCNA) identifying key module genes. Machine learning models (random forest, Support Vector Machine (SVM), Generalized Linear Model (GLM), eXtreme Gradient Boosting (XGBoost)) selected 6 feature genes validated by the GSE213313 dataset. Ferredoxin 1 (FDX1) emerged as the top gene, corroborated by Area Under the Curve (AUC) analysis. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) revealed enriched pathways in T cell receptor, natural killer cytotoxicity, and Peroxisome Proliferator-Activated Receptor (PPAR). We uncovered differentially expressed copper-death genes and immune infiltration differences, notably CD8 T cells and M0 macrophages. Clustering identified modules with potential implications for COVID-19. Machine learning models effectively predicted COVID-19 risk, with FDX1's pivotal role validated. FDX1's high expression was associated with immune pathways, suggesting its role in COVID-19 pathogenesis. This comprehensive approach elucidated COVID-19-related copper-death genes, their immune context, and risk prediction potential. FDX1's connection to immune pathways offers insights into COVID-19 mechanisms and therapy.

Competency of malaria laboratory diagnosis at national and provincial levels at the beginning of malaria post-elimination phase, China.

BACKGROUND: Qualified malaria diagnosis competency has contributed to the great achievement of malaria elimination in China. After eliminating malaria, it is still critical to the prevention of re-establishment of malaria transmission in China. This study was aimed to assess the malaria detection competency at national and provincial levels in China at the beginning of malaria post-elimination phase. METHODS: In the present study, different competency assessment activities on the laboratory malaria diagnosis were carried out for national and provincial malaria diagnostic laboratories based on the WHO scoring schedules, including malaria microscopy or nucleic acid amplification tests (NAAT), at the beginning of malaria post-elimination phase (2021-2022) in China. RESULTS: A total of 60 slides for malaria microscopy and 10 specimen for NAAT were included into the WHO External Quality Assessments of malaria parasite qualitative detection and species identification, and the scoring rate was 96.6% (microscopy: 171/177) and 85.0% (NAAT: 17/20), respectively. Moreover, 124 samples were included into the national NAAT quality assessment, and an accuracy of 87.9% (109/124) was found without significance among reference laboratories and non-reference laboratories. CONCLUSIONS: The findings suggest that there is still a need for sustained strengthening of malaria detection competency, particularly in the areas of parasite counting and detection of low-density parasitemia, to ensure prompt detection of the sources of infection and accurate identification of Plasmodium species, and contribute to case management and focus disposal, thereby effectively preventing the malaria re-establishment.

Functional Selection of Tau Oligomerization-Inhibiting Aptamers.

Pathological hyperphosphorylation and aggregation of microtubule-associated Tau protein contribute to Alzheimer's Disease (AD) and other related tauopathies. Currently, no cure exists for Alzheimer's Disease. Aptamers offer significant potential as next-generation therapeutics in biotechnology and the treatment of neurological disorders. Traditional aptamer selection methods for Tau protein focus on binding affinity rather than interference with pathological Tau. In this study, we developed a new selection strategy to enrich DNA aptamers that bind to surviving monomeric Tau protein under conditions that would typically promote Tau aggregation. Employing this approach, we identified a set of aptamer candidates. Notably, BW1c demonstrates a high binding affinity (Kd=6.6 nM) to Tau protein and effectively inhibits arachidonic acid (AA)-induced Tau protein oligomerization and aggregation. Additionally, it inhibits GSK3ß-mediated Tau hyperphosphorylation in cell-free systems and okadaic acid-mediated Tau hyperphosphorylation in cellular milieu. Lastly, retro-orbital injection of BW1c tau aptamer shows the ability to cross the blood brain barrier and gain access to neuronal cell body. Through further refinement and development, these Tau aptamers may pave the way for a first-in-class neurotherapeutic to mitigate tauopathy-associated neurodegenerative disorders.

Data Cleansing and Sub-Unit-Based Molecular Description Enable Accurate Prediction of The Energy Levels of Non-Fullerene Acceptors Used in Organic Solar Cells.

Non-fullerene acceptors (NFAs) have recently emerged as pivotal materials for enhancing the efficiency of organic solar cells (OSCs). To further advance OSC efficiency, precise control over the energy levels of NFAs is imperative, necessitating the development of a robust computational method for accurate energy level predictions. Unfortunately, conventional computational techniques often yield relatively large errors, typically ranging from 0.2 to 0.5 electronvolts (eV), when predicting energy levels. In this study, the authors present a novel method that not only expedites energy level predictions but also significantly improves accuracy , reducing the error margin to 0.06 eV. The method comprises two essential components. The first component involves data cleansing, which systematically eliminates problematic experimental data and thereby minimizes input data errors. The second component introduces a molecular description method based on the electronic properties of the sub-units comprising NFAs. The approach simplifies the intricacies of molecular computation and demonstrates markedly enhanced prediction performance compared to the conventional density functional theory (DFT) method. Our methodology will expedite research in the field of NFAs, serving as a catalyst for the development of similar computational approaches to address challenges in other areas of material science and molecular research.

GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference.

The recent advances of single-cell RNA sequencing (scRNA-seq) have enabled reliable profiling of gene expression at the single-cell level, providing opportunities for accurate inference of gene regulatory networks (GRNs) on scRNA-seq data. Most methods for inferring GRNs suffer from the inability to eliminate transitive interactions or necessitate expensive computational resources. To address these, we present a novel method, termed GMFGRN, for accurate graph neural network (GNN)-based GRN inference from scRNA-seq data. GMFGRN employs GNN for matrix factorization and learns representative embeddings for genes. For transcription factor-gene pairs, it utilizes the learned embeddings to determine whether they interact with each other. The extensive suite of benchmarking experiments encompassing eight static scRNA-seq datasets alongside several state-of-the-art methods demonstrated mean improvements of 1.9 and 2.5% over the runner-up in area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC). In addition, across four time-series datasets, maximum enhancements of 2.4 and 1.3% in AUROC and AUPRC were observed in comparison to the runner-up. Moreover, GMFGRN requires significantly less training time and memory consumption, with time and memory consumed <10% compared to the second-best method. These findings underscore the substantial potential of GMFGRN in the inference of GRNs. It is publicly available at https://github.com/Lishuoyy/GMFGRN.

Separation of anti-TMV active components and modes of action of Omphalia lapidescens.

BACKGROUND: Omphalia lapidescens is a saprophytic and parasitic fungus belonging to the Polypora genus of Tricholomataceae. It has repellent, insecticidal, anti-inflammatory and immunomodulatory effects. RESULT: This study found that the extract of O. lapidescens had significant anti-TMV activity, and the main active component was homopolysaccharide LW-1 by Bioassay-guided fractionation. LW-1 is a glucan with ß-(1,3) glucoside bond as the main chain and ß-(1,6) glucoside bond as the branch chain, with molecular weight in the range of 172,916-338,827 Da. The protective and inactive efficacies of LW-1(100 mg/L) against TMV were 78.10% and 48.20%, but had no direct effect on the morphology of TMV particles. The results of mechanism of action showed that LW-1 induced the increase of the activity of defense enzymes such as POD, SOD and PAL in Nicotiana glutinosa. The overexpression of resistance genes such as NPR1, PR1 and PR5, and the increase of SA content. Further transcriptome sequencing showed that LW-1 activated MAPK signaling pathway, plant-pathogen interaction pathway and glucosinolide metabolic pathway in Arabidopsis thaliana. Besides, LW-1 induced crops resistance against plant pathogenic fungi. CONCLUSION: Taken together, the anti-TMV mechanism of LW-1 was to activate MAPK signaling pathway, inducing overexpression of resistance genes, activating plant immune system, and improving the synthesis and accumulation of plant defencins such as glucosinolide. LW-1-induced plant disease resistance has the advantages of broad spectrum and long duration, which has the potential to be developed as a new antiviral agent or plant immune resistance inducer.

Tailoring the Position of Ester Group on N-Alkyl Chains of Benzotriazole-based Small Molecule Acceptors for High-Performance Organic Solar Cells.

Side chain engineering plays a vital role in exploring high-performance small molecule acceptors (SMAs) for organic solar cells (OSCs). In this work, we designed and synthesized a series of A-DA'D-A type SMAs by introducing different N-substituted alkyl and ester alkyl side chains on benzotriazole (BZ) central unit and aimed to investigate the effect of different ester substitution positions on photovoltaic performances. All the new SMAs with ester groups exhibit lower the lowest unoccupied molecular orbital (LUMO) energy levels and more blue-shifted absorption, but relatively higher absorption coefficients than alkyl chain counterpart. After blending with the donor PM6, the ester side chain-based devices demonstrate enhanced charge mobility, reduced amorphous intermixing domain size and long-lived charge transfer state compared to the alkyl chain counterpart, which are beneficial to achieve higher short-circuit current density (Jsc ) and fill factor (FF), simultaneously. Thereinto, the PM6 : BZ-E31 based device achieves a higher power conversion efficiency (PCE) of 18.33 %, which is the highest PCE among the OSCs based on the SMAs with BZ-core. Our work demonstrated the strategy of ester substituted side chain is a feasible and effective approach to develop more efficient SMAs for OSCs.

An all-fiber system biosensor for trace ß-lactam antibiotics detection enhanced by functionalized microfiber and fiber bragg grating.

An all-fiber-optic system for rapid detection of antibiotic concentration, based on an optical enzyme biosensor with microfiber interferometer (MFI) and fiber gratings (FBGs) power variation, is proposed and experimentally validated. During the experiment, ß-lactamase(ß-LS) is fixed on the polyaniline (PANI)-coated optical fiber by cross-linking through glutaraldehyde (GA) covalent bonding. ß-LS can hydrolyze ß-lactam antibiotics to generate acidic by-products that transform polyaniline from the form of the emerald base to emerald salt, which results in the surface refractive index (RI) variation of MFI, to convert MFI wavelength and FBGs power macroscopic change for feedbackingly detecting the concentration of ß-lactam antibiotics. The detection of amoxicillin (AMX) in deionized water at concentrations in the range of 0.01-100 nM resulted in a wavelength change sensitivity of 0.6 nm/nM, and FBGs power difference change sensitivity of 1.3 dB/nM, with a detection limit LOD = 0.04 nM in real food and urine samples. The sensing system by the same calibration technique can detect antibiotic concentrations in different substances (tap water, milk and artificial urine). This developed all-fiber-optic system can be used as a rapid solution for the measurement of ß-lactam antibiotic residues in food and the environment.

miR-429-3p mediates memory decline by targeting MKP-1 to reduce surface GluA1-containing AMPA receptors in a mouse model of Alzheimer's disease

Alzheimer's disease (AD) is a leading cause of dementia in the elderly. Mitogen-activated protein kinase phosphatase 1 (MKP-1) plays a neuroprotective role in AD. However, the molecular mechanisms underlying the effects of MKP-1 on AD have not been extensively studied. MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level, thereby repressing mRNA translation. Here, we reported that the microRNA-429-3p (miR-429-3p) was significantly increased in the brain of APP23/PS45 AD model mice and N2AAPP AD model cells. We further found that miR-429-3p could downregulate MKP-1 expression by directly binding to its 3'-untranslated region (3' UTR). Inhibition of miR-429-3p by its antagomir (A-miR-429) restored the expression of MKP-1 to a control level and consequently reduced the amyloidogenic processing of APP and Aβ accumulation. More importantly, intranasal administration of A-miR-429 successfully ameliorated the deficits of hippocampal CA1 long-term potentiation and spatial learning and memory in AD model mice by suppressing extracellular signal-regulated kinase (ERK1/2)-mediated GluA1 hyperphosphorylation at Ser831 site, thereby increasing the surface expression of GluA1-containing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs). Together, these results demonstrate that inhibiting miR-429-3p to upregulate MKP-1 effectively improves cognitive and synaptic functions in AD model mice, suggesting that miR-429/MKP-1 pathway may be a novel therapeutic target for AD treatment.

Short-Term Exposure to Ambient Air Pollution and Influenza: A Multicity Study in China.

BACKGROUND: Air pollution is a major risk factor for planetary health and has long been suspected of predisposing humans to respiratory diseases induced by pathogens like influenza viruses. However, epidemiological evidence remains elusive due to lack of longitudinal data from large cohorts. OBJECTIVE: Our aim is to quantify the short-term association of influenza incidence with exposure to ambient air pollutants in Chinese cities. METHODS: Based on air pollutant data and influenza surveillance data from 82 cities in China over a period of 5 years, we applied a two-stage time series analysis to assess the association of daily incidence of reported influenza cases with six common air pollutants [particulate matter with aerodynamic diameter ≤2.5µm (PM2.5), particulate matter with aerodynamic diameter ≤10µm (PM10), NO2, SO2, CO, and O3], while adjusting for potential confounders including temperature, relative humidity, seasonality, and holiday effects. We built a distributed lag Poisson model for one or multiple pollutants in each individual city in the first stage and conducted a meta-analysis to pool city-specific estimates in the second stage. RESULTS: A total of 3,735,934 influenza cases were reported in 82 cities from 2015 to 2019, accounting for 72.71% of the overall case number reported in the mainland of China. The time series models for each pollutant alone showed that the daily incidence of reported influenza cases was positively associated with almost all air pollutants except for ozone. The most prominent short-term associations were found for SO2 and NO2 with cumulative risk ratios of 1.094 [95% confidence interval (CI): 1.054, 1.136] and 1.093 (95% CI: 1.067, 1.119), respectively, for each 10 µg/m3 increase in the concentration at each of the lags of 1-7 d. Only NO2 showed a significant association with the daily incidence of influenza cases in the multipollutant model that adjusts all six air pollutants together. The impact of air pollutants on influenza was generally found to be greater in children, in subtropical cities, and during cold months. DISCUSSION: Increased exposure to ambient air pollutants, particularly NO2, is associated with a higher risk of influenza-associated illness. Policies on reducing air pollution levels may help alleviate the disease burden due to influenza infection. https://doi.org/10.1289/EHP12146.

Study on the Antifungal Activity and Potential Mechanism of Natamycin against Colletotrichum fructicola.

In this investigation, the antifungal activity, its influence on the quality of apples, and the molecular mechanism of natamycin against Colletotrichum fructicola were systematically explored. Our findings indicated that natamycin showed significant inhibition against C. fructicola. Moreover, it efficaciously maintained the apple quality by modulating the physicochemical index. Research on the antifungal mechanism showed that natamycin altered the mycelial microstructure, disrupted the plasma membrane integrality, and decreased the ergosterol content of C. fructicola. Interestingly, the exogenous addition of ergosterol weakened the antifungal activity of natamycin. Importantly, natamycin markedly inhibited the expression of Cyp51A and Cyp51B genes in C. fructicola, which was contrary to the results obtained after treatment with triazole fungicide flusilazole. All these results exhibited sufficient proof that natamycin had enormous potential to be conducive as a promising biopreservative against C. fructicola on apples, and these findings will advance our knowledge on the mechanism of natamycin against pathogenic fungi.

Auxiliary sequential deposition enables 19%-efficiency organic solar cells processed from halogen-free solvents.

High-efficiency organic solar cells are often achieved using toxic halogenated solvents and additives that are constrained in organic solar cells industry. Therefore, it is important to develop materials or processing methods that enabled highly efficient organic solar cells processed by halogen free solvents. In this paper, we report an innovative processing method named auxiliary sequential deposition that enables 19%-efficiency organic solar cells processed by halogen free solvents. Our auxiliary sequential deposition method is different from the conventional blend casting or sequential deposition methods in that it involves an additional casting of dithieno[3,2-b:2',3'-d]thiophene between the sequential depositions of the donor (D18-Cl) and acceptor (L8-BO) layers. The auxiliary sequential deposition method enables dramatic performance enhancement from 15% to over 18% compared to the blend casting and sequential deposition methods. Furthermore, by incorporating a branched-chain-engineered acceptor called L8-BO-X, device performance can be boosted to over 19% due to increased intermolecular packing, representing top-tier values for green-solvent processed organic solar cells. Comprehensive morphological and time-resolved characterizations reveal that the superior blend morphology achieved through the auxiliary sequential deposition method promotes charge generation while simultaneously suppressing charge recombination. This research underscores the potential of the auxiliary sequential deposition method for fabricating highly efficient organic solar cells using environmentally friendly solvents.

Step-by-Step Modulation of Crystalline Features and Exciton Kinetics for 19.2% Efficiency Ortho-Xylene Processed Organic Solar Cells.

With plenty of popular and effective ternary organic solar cells (OSCs) construction strategies proposed and applied, its power conversion efficiencies (PCEs) have come to a new level of over 19% in single-junction devices. However, previous studies are heavily based in chloroform (CF) leaving behind substantial knowledge deficiencies in understanding the influence of solvent choice when introducing a third component. Herein, we present a case where a newly designed asymmetric small molecular acceptor using fluoro-methoxylated end-group modification strategy, named BTP-BO-3FO with enlarged bandgap, brings different morphological evolution and performance improvement effect on host system PM6:BTP-eC9, processed by CF and ortho-xylene (o-XY). With detailed analyses supported by a series of experiments, the best PCE of 19.24% for green solvent-processed OSCs is found to be a fruit of finely tuned crystalline ordering and general aggregation motif, which furthermore nourishes a favorable charge generation and recombination behavior. Likewise, over 19% PCE can be achieved by replacing spin-coating with blade coating for active layer deposition. This work focuses on understanding the commonly met yet frequently ignored issues when building ternary blends to demonstrate cutting-edge device performance, hence, will be instructive to other ternary OSC works in the future.