A Cost-Effective and Easy-to-Fabricate Conductive Velcro Dry Electrode for Durable and High-Performance Biopotential Acquisition.

Compared with the traditional gel electrode, the dry electrode is being taken more seriously in bioelectrical recording because of its easy preparation, long-lasting ability, and reusability. However, the commonly used dry AgCl electrodes and silver cloth electrodes are generally hard to record through hair due to their flat contact surface. Claw electrodes can contact skin through hair on the head and body, but the internal claw structure is relatively hard and causes discomfort after being worn for a few hours. Here, we report a conductive Velcro electrode (CVE) with an elastic hook hair structure, which can collect biopotential through body hair. The elastic hooks greatly reduce discomfort after long-time wearing and can even be worn all day. The CVE electrode is fabricated by one-step immersion in conductive silver paste based on the cost-effective commercial Velcro, forming a uniform and durable conductive coating on a cluster of hook microstructures. The electrode shows excellent properties, including low impedance (15.88 kΩ @ 10 Hz), high signal-to-noise ratio (16.0 dB), strong water resistance, and mechanical resistance. After washing in laundry detergent, the impedance of CVE is still 16% lower than the commercial AgCl electrodes. To verify the mechanical strength and recovery capability, we conducted cyclic compression experiments. The results show that the displacement change of the electrode hook hair after 50 compression cycles was still less than 1%. This electrode provides a universal acquisition scheme, including effective acquisition of different parts of the body with or without hair. Finally, the gesture recognition from electromyography (EMG) by the CVE electrode was applied with accuracy above 90%. The CVE proposed in this study has great potential and promise in various human-machine interface (HMI) applications that employ surface biopotential signals on the body or head with hair.

Exploring Aqueous Solution-Processed Pseudohalide Rare-Earth Double Perovskite Ferroelectrics toward X-ray Detection with High Sensitivity.

Three-dimensional (3D) pseudohalide rare-earth double perovskites (PREDPs) have garnered significant attention for their versatile physical properties, including ferroelectricity, ferroelasticity, large piezoelectric responses, and circularly polarized luminescence. However, their potential for X-ray detection remains unexplored, and the low Curie temperature (TC) limits the performance window for PREDP ferroelectrics. Here, by applying the chemical regulation strategies involving halogen substitution on the organic cation and Rb/Cs substitution to the PREDP [(R)-M3HQ]2RbEu(NO3)6 [(R)-M3HQ = (R)-N-methyl-3-hydroxylquinuclidinium] with a low TC of 285 K, a novel 3D PREDP ferroelectric [(R)-CM3HQ]2CsEu(NO3)6 [(R)-CM3HQ = (R)-N-chloromethyl-3-hydroxylquinuclidinium] are successfully synthesized, for which the TC reaches 344 K. More importantly, such a strategy endowed [(R)-CM3HQ]2CsEu(NO3)6 with notable X-ray detection capabilities. Centimeter-sized [(R)-CM3HQ]2CsEu(NO3)6 single crystals fabricated from aqueous solutions demonstrated a sensitivity of 1307 µC Gyair-1 cm-2 and a low detectable dose rate of 152 nGyair s-1, the highest sensitivity reported for hybrid double perovskite ferroelectric detectors. This work positions PREDPs as promising candidates for the next generation of eco-friendly optoelectronic materials and also offers substantial insights into the interaction between structure, composition, and functionality in ferroelectric materials.

TaNAC1 boosts powdery mildew resistance by phosphorylation-dependent regulation of TaSec1a and TaCAMTA4 via PP2Ac/CDPK20.

The integrity of wheat (Triticum aestivum) production is increasingly jeopardized by the fungal pathogen Blumeria graminis f. sp. tritici (Bgt), particularly amid the vicissitudes of climate change. Here, we delineated the role of a wheat transcription factor, TaNAC1, which precipitates cellular apoptosis and fortifies resistance against Bgt. Utilizing BiFC, co-immunoprecipitation, protein quantification, luciferase report assays, we determined that cytoplasmic TaNAC1-7A undergoes phosphorylation at the S184/S258 sites by TaCDPK20, facilitating its nuclear translocation. This migration appears to prime further phosphorylation by TaMPK1, thereby enhancing transcriptional regulatory activity. Notably, the apoptotic activity of phosphorylated TaNAC1-7A is negatively modulated by the nuclear protein phosphatase PP2Ac. Furthermore, activation of TaNAC1 phosphorylation initiates transcription of downstream genes TaSec1a and TaCAMTA4, through binding to the C[T/G]T[N7]A[A/C]G nucleic acid motif. Suppression of TaNAC1, TaCDPK20, and TaMPK1 in wheat compromises its resistance to Bgt strain E09, whereas overexpression of TaNAC1 and silencing of PP2Ac markedly elevate resistance levels. Our results reveal the pivotal role of TaNAC1 in basal resistance which is mediated by its effects on homotypic fusion, vacuolar protein sorting, and the expression of defense-related genes. The findings highlight the potential through targeting TaNAC1 and its regulators as a strategy for improving wheat's resistance to fungal pathogens.

Quantifying the impact of factors on soil available arsenic using machine learning.

Arsenic (As) can accumulate in edible plant parts and thus pose a serious threat to human health. Identifying the contributions of various factors to soil available As is crucial for evaluating environmental risks. However, research quantitatively assessing the importance of soil properties on available As is scarce. In this study, we utilized 442 datasets covering total As, available As, and properties of farmland soils. The five machine learning models were employed to predict soil available As content, and the model with the best predictive performance was selected to calculate the importance of soil properties on available As and interpret the model results. The Random Forest model exhibited the best predictive performance, with R2 for the test set of dryland and paddy fields being 0.83 and 0.82 respectively, while also outperforming other machine learning models in terms of accuracy. Concurrently, evaluating the contribution of soil properties to soil available As revealed that increases in soil total arsenic, pH, organic matter (OM), and cation exchange capacity (CEC) led to higher soil available As content. Among these factors, soil total As had the greatest impact, followed by CEC. The influence of pH on soil available As was greater in dryland compared to OM, while in paddy fields, it was smaller than OM (p < 0.01). Sensitivity analysis results indicated that reducing soil total As content had the greatest effect on available As. In both dryland and paddy field soils, reducing soil total As had the most pronounced effect on available As, leading to reductions of 10.09% and 8.48%, respectively. Therefore, prioritizing the regulation of soil total As and CEC is crucial in As contamination management practices to alter As availability in farmland soils.

Long-range, high-precision optical calibration path based on an optoelectronic oscillator.

We propose a laser ranging calibration optical path system using multiple optoelectronic oscillators (OEOs) that provides long range, high precision, low cost and high stability. A phase locked loop is used to control the length of the calibration optical path, which is measured with high precision by alternating the oscillations between the measurement loop and the reference loop. The calibration optical path length exceeds 9000 m with the stability of 6.8 µm during 3 minutes, and the relative measurement accuracy of the calibration optical path reaches 6.9 × 10-10.

MCP: Multi-Chicken Pose Estimation Based on Transfer Learning.

Poultry managers can better understand the state of poultry through poultry behavior analysis. As one of the key steps in behavior analysis, the accurate estimation of poultry posture is the focus of this research. This study mainly analyzes a top-down pose estimation method of multiple chickens. Therefore, we propose the "multi-chicken pose" (MCP), a pose estimation system for multiple chickens through deep learning. Firstly, we find the position of each chicken from the image via the chicken detector; then, an estimate of the pose of each chicken is made using a pose estimation network, which is based on transfer learning. On this basis, the pixel error (PE), root mean square error (RMSE), and image quantity distribution of key points are analyzed according to the improved chicken keypoint similarity (CKS). The experimental results show that the algorithm scores in different evaluation metrics are a mean average precision (mAP) of 0.652, a mean average recall (mAR) of 0.742, a percentage of correct keypoints (PCKs) of 0.789, and an RMSE of 17.30 pixels. To the best of our knowledge, this is the first time that transfer learning has been used for the pose estimation of multiple chickens as objects. The method can provide a new path for future poultry behavior analysis.

Carbene-mediated gelatin and hyaluronic acid hydrogel paints with ultra adhesive ability for arthroscopic cartilage repair.

In articular cartilage defect, particularly in arthroscopy, regenerative hydrogels are urgently needed. It should be able to firmly adhere to the cartilage tissue and maintain sufficient mechanical strength to withstand approximately 10 kPa of arthroscopic hydraulic flushing. In this study, we report a carbene-mediated ultra adhesive hybrid hydrogel paints for arthroscopic cartilage repair, which combined the photo initiation of double crosslinking system with the addition of diatomite, as a further reinforcing agent and biological inorganic substances. The double network consisting of ultraviolet initiated polymerization of hyaluronic acid methacrylate (HAMA) and carbene insertion chemistry of diazirine-grafted gelatin (GelDA) formed an ultra-strong adhesive hydrogel paint (H2G5DE). Diatomite helped the H2G5DE hydrogel paint firmly adhere to the cartilage defect, withstanding nearly 100 kPa of hydraulic pressure, almost 10 times that in clinical arthroscopy. Furthermore, the H2G5DE hydrogel supported cell growth, proliferation, and migration, thus successfully repairing cartilage defects. Overall, this study demonstrates a proof-of-concept of ultra-adhesive polysaccharide hydrogel paints, which can firmly adhere to the articular cartilage defects, can resist continuous hydraulic pressure, can promote effective cartilage regeneration, and is very suitable for minimally invasive arthroscopy.

Optimizing diagnosis and surgical decisions for chronic osteomyelitis through radiomics in the precision medicine era.

Introduction: Chronic osteomyelitis is a complex clinical condition that is associated with a high recurrence rate. Traditional surgical interventions often face challenges in achieving a balance between thorough debridement and managing resultant bone defects. Radiomics is an emerging technique that extracts quantitative features from medical images to reveal pathological information imperceptible to the naked eye. This study aims to investigate the potential of radiomics in optimizing osteomyelitis diagnosis and surgical treatment. Methods: Magnetic resonance imaging (MRI) scans of 93 suspected osteomyelitis patients were analyzed. Radiomics features were extracted from the original lesion region of interest (ROI) and an expanded ROI delineated by enlarging the original by 5 mm. Feature selection was performed and support vector machine (SVM) models were developed using the two ROI datasets. To assess the diagnostic efficacy of the established models, we conducted receiver operating characteristic (ROC) curve analysis, employing histopathological results as the reference standard. The model's performance was evaluated by calculating the area under the curve (AUC), sensitivity, specificity, and accuracy. Discrepancies in the ROC between the two models were evaluated using the DeLong method. All statistical analyses were carried out using Python, and a significance threshold of p < 0.05 was employed to determine statistical significance. Results and Discussion: A total of 1,037 radiomics features were extracted from each ROI. The expanded ROI model achieved significantly higher accuracy (0.894 vs. 0.821), sensitivity (0.947 vs. 0.857), specificity (0.842 vs. 0.785) and AUC (0.920 vs. 0.859) than the original ROI model. Key discriminative features included shape metrics and wavelet-filtered texture features. Radiomics analysis of MRI exhibits promising clinical translational potential in enhancing the diagnosis of chronic osteomyelitis by accurately delineating lesions and identifying surgical margins. The inclusion of an expanded ROI that encompasses perilesional tissue significantly improves diagnostic performance compared to solely focusing on the lesions. This study provides clinicians with a more precise and effective tool for diagnosis and surgical decision-making, ultimately leading to improved outcomes in this patient population.

Is fracture management merely a physical process? Exploring the psychological effects of internal and external fixation.

BACKGROUND: Internal and external fixation are common surgical procedures for treating fractures. However, the impact of different surgical approaches (including internal and external fixations) on patients' psychological status and Quality of Life (QoL) is rarely examined. Herein, we aimed to investigate the effects of internal and external fixation on anxiety, depression, insomnia, and overall mental and physical health in Distal Radius Fractures (DRF) patients. METHODS: We performed a retrospective study on 96 fracture patients who underwent internal fixation (57 patients) or external fixation (39 patients). The Visual Analog Scale (VAS), the Hospital Anxiety and Depression Scale (HADS), the Athens Insomnia Scale (AIS), and the Medical Outcomes Study Short Form 36 (SF-36) questionnaire were used to assess the patients' pain, anxiety, depression, sleep, and QoL before surgery and at seven days, one month, and three months post-surgery. RESULTS: The VAS scores were significantly lower in the Internal Fixation Group (IFG) than in the External Fixation Group (EFG) on the seventh day and one month postoperatively (P < 0.05). Although both groups showed no significant anxiety, depression, or insomnia before surgery (P > 0.05), the EFG showed significantly higher HADS-A, HADS-D, and AIS scores than the IFG at seven days and one and three months postoperatively (P < 0.05). Additionally, changes in HADS-A, HADS-D, and AIS scores were most significant at day seven post-surgery in the EFG (P < 0.05). Furthermore, no significant difference was found between the two groups in the average Physical Component Summary (PCS) and Mental Component Summary (MCS) scores before surgery (P > 0.05). However, both groups showed positive changes in PCS and MCS scores at postoperative day seven and one and three months postoperatively, with the IFG having significantly higher average PCS and MCS scores compared to the EFG (P < 0.05). CONCLUSION: Compared to external fixation, internal fixation did not significantly impact patients' emotions regarding anxiety and depression in the early postoperative period, and physical and mental health recovery was better during the postoperative rehabilitation period. Furthermore, when there are no absolute indications, the impact on patients' psychological well-being should be considered as one of the key factors in the treatment plan during surgical approach selection.

"One-Click Restart" Recycling of Metal-Free Perovskite X-Ray Detectors.

Halide perovskites have shown great potential in X-ray detection due to outstanding optoelectronic properties. However, finding a cost-effective and environmentally sustainable method for handling end-of-life devices has remained challenging. Here, a "One-Click Restart" eco-friendly recycling strategy is introduced for end-of-life perovskite X-ray detectors. This method, utilizing water, allows for the recapture and reuse of both perovskite and conductor materials. The process is straightforward and environmentally friendly, eliminating the need for further chemical treatment, purification, additional additives or catalysts, and complex equipment. A sustainable device cycle is developed by reconstructing flexible perovskite membranes for wearable electronics from recycled materials. Large-scale, flexible membranes made from metal-free perovskite DABCO-N2H5-I3 (DABCO = N-N'-diazabicyclo[2.2.2]octonium) achieve remarkably impressive average sensitivity of 6204 ± 268 µC Gyair -1 cm-2 and a low detection limit of 102.3 nGyair s-1, which makes highly effective for X-ray imaging. The sensitivity of recycled flexible devices not only matches that of single-crystal devices made with fresh materials but also ranks as the highest among all metal-free perovskite X-ray detectors. "One-Click Restart" applies to scalable flexible devices derived from aged single-crystal counterparts, offering significant cost, time, and energy savings compared to their single-crystal equivalents. Such advantages significantly boost future market competitiveness.

PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants.

N 6-methyladenosine (m6A), which is the mostly prevalent modification in eukaryotic mRNAs, is involved in gene expression regulation and many RNA metabolism processes. Accurate prediction of m6A modification is important for understanding its molecular mechanisms in different biological contexts. However, most existing models have limited range of application and are species-centric. Here we present PEA-m6A, a unified, modularized and parameterized framework that can streamline m6A-Seq data analysis for predicting m6A-modified regions in plant genomes. The PEA-m6A framework builds ensemble learning-based m6A prediction models with statistic-based and deep learning-driven features, achieving superior performance with an improvement of 6.7% to 23.3% in the area under precision-recall curve compared with state-of-the-art regional-scale m6A predictor WeakRM in 12 plant species. Especially, PEA-m6A is capable of leveraging knowledge from pretrained models via transfer learning, representing an innovation in that it can improve prediction accuracy of m6A modifications under small-sample training tasks. PEA-m6A also has a strong capability for generalization, making it suitable for application in within- and cross-species m6A prediction. Overall, this study presents a promising m6A prediction tool, PEA-m6A, with outstanding performance in terms of its accuracy, flexibility, transferability, and generalization ability. PEA-m6A has been packaged using Galaxy and Docker technologies for ease of use and is publicly available at https://github.com/cma2015/PEA-m6A.

lncRNA HCG22 regulated cell growth and metastasis of papillary thyroid cancer via negatively modulating miR-425-5p.

INTRODUCTION: Papillary thyroid cancer (PTC) is a common malignant tumour in the endocrine system with increasing incidence. LncRNA HCG22 (HCG22) was noticed to be dysregulated in PTC, but its specific function and mechanism remain unknown. The function of HCG22 and its underlying molecular mechanism was investigated to evaluate its potential as a biomarker for PTC. MATERIAL AND METHODS: The expression of HCG22 was detected in PTC cells (TPC-1, SNU790, GLAG-66, and BCPAP) and normal thyroid cells (Nthy-ori) using real time quantative polymerase chain reaction (RT-qPCR). HCG22 and miR-425-5p were regulated by cell transfection. The cell proliferation and metastasis were assessed by CCK8 and Transwell assay. RESULTS: HCG22 was upregulated in PTC cells, of which the knockdown suppressed the proliferation, migration, and invasion of PTC cells. miR-425-5p was downregulated in PTC cells, which was negatively regulated by HCG22. Silencing miR-425-5p could reverse the inhibitory effect of HCG22 knockdown on the cellular processes of PTC. CONCLUSIONS: HCG22 served as a tumour promoter in PTC cells, which regulated cell proliferation and metastasis via negatively regulating miR-425-5p.

Biocompatible Metal-Free Perovskite Membranes for Wearable X-ray Detectors.

Halide perovskites are emerging as promising materials for X-ray detection owing to their compatibility with flexible fabrication, cost-effective solution processing, and exceptional carrier transport behaviors. However, the challenge of removing lead from high-performing perovskites, crucial for wearable electronics, while retaining their superior performance, persists. Here, we present for the first time a highly sensitive and robust flexible X-ray detector utilizing a biocompatible, metal-free perovskite, MDABCO-NH4I3 (MDABCO = methyl-N'-diazabicyclo[2.2.2]octonium). This wearable X-ray detector, based on a MDABCO-NH4I3 thick membrane, exhibits remarkable properties including a large resistivity of 1.13 × 1011 Ω cm, a high mobility-lifetime product (µ-τ) of 1.64 × 10-4 cm2 V-1, and spin Seebeck effect coefficient of 1.9 nV K-1. We achieve a high sensitivity of 6521.6 ± 700 µC Gyair-1 cm-2 and a low detection limit of 77 nGyair s-1, ranking among the highest for biocompatible X-ray detectors. Additionally, the device exhibits effective X-ray imaging at a low dose rate of 1.87 µGyair s-1, which is approximately one-third of the dose rate used in regular medical diagnostics. Crucially, both the MDABCO-NH4I3 thick membrane and the device showcase excellent mechanical robustness. These attributes render the flexible MDABCO-NH4I3 thick membranes highly competitive for next-generation, high-performance, wearable X-ray detection applications.

Efficiently tuning the electrical performance of PBTTT-C14 thin film viainsitucontrollable multiple precursors (Al2O3:ZnO) vapor phase infiltration.

Conjugated polymer-based organic/inorganic hybrid materials become the current research frontier and show great potential to integrate flexible polymers and rigid solid materials, which have been widely used in the field of various flexible electronics and optical devices. In this study, based on the multiple vapor phase infiltration (VPI) process, various precursor molecules (diethylzinc DEZ, trimethylaluminum TMA, H2O) are applied for thein situmodification of PBTTT-C14 films. The conductivity of the PBTTT-C14/Al2O3:ZnO (AZO) film is significantly enhanced, and the maximum value of conductivity is 1.16 S cm-1, which is eight orders of magnitude higher than the undoped PBTTT-C14 thin film. Here, the change of morphologies and crystalline states are analyzed via SEM, AFM, and XRD. And the chemical changes during the VPI process of PBTTT-C14 are characterized through Raman, XPS, and UV-vis. During the AZO VPI process, the formation of new ZnS matrix in the polymer subsurface can generate new additional electron conduction pathways through the crosslinking of polymer chains with inorganic materials, and the addition of Al2O3can bring about the increase of average grain size of ZnO crystals, which is also benefit to the conductivity increase of PBTTT-C14 thin film. Generally, the synergistic effect between the inorganic and polymer constituents results in the significantly enhancement of the conductivity of PBTTT-C14/AZO thin films.

Three-Dimensional Modeling with Osteoblast-like Cells under External Magnetic Field Conditions Using Magnetic Nano-Ferrite Particles for the Development of Cell-Derived Artificial Bone.

The progress in artificial bone research is crucial for addressing fractures and bone defects in the aging population. However, challenges persist in terms of biocompatibility and structural complexity. Nanotechnology provides a promising avenue by which to overcome these challenges, with nano-ferrite particles (NFPs) exhibiting superparamagnetic properties. The ability to control cell positioning using a magnetic field opens up new possibilities for customizing artificial bones with specific shapes. This study explores the biological effects of NFPs on osteoblast-like cell lines (MC3T3-E1), including key analyses, such as cell viability, cellular uptake of NFPs, calcification processes, cell migration under external magnetic field conditions, and three-dimensional modeling. The results indicate that the impact of NFPs on cell proliferation is negligible. Fluorescence and transmission electron microscopy validated the cellular uptake of NFPs, demonstrating the potential for precise cell positioning through an external magnetic field. Under calcification-inducing conditions, the cells exhibited sustained calcification ability even in the presence of NFPs. The cell movement analysis observed the controlled movement of NFP-absorbing cells under an external magnetic field. Applying a magnetic field along the z-axis induced the three-dimensional shaping of cells incorporating NFPs, resulting in well-arranged z-axis directional patterns. In this study, NFPs demonstrated excellent biocompatibility and controllability under an external magnetic field, laying the foundation for innovative treatment strategies for customizing artificial bones.

Wheat (Triticum aestivum L.) seedlings performance mainly affected by soil nitrate nitrogen under the stress of polyvinyl chloride microplastics.

Microplastics are exotic pollutants and are increasingly detected in soil, but it remains poorly understood how microplastics impact soil and plant systematically. The present study was conducted to evaluate the effects of polyvinyl chloride microplastics (PVC-MPs) on wheat seedlings performance and soil properties. Under the stress of PVC-MPs, no new substance and functional groups were generated in soil by X-ray diffraction and the fourier transform infrared spectroscopy analyses, whereas the diffraction and characteristic peaks and of soil was affected by PVC-MPs. Wheat seedlings shoot biomass and soil nitrate nitrogen were significantly inhibited by PVC-MPs. Chlorophylls were not significant affected by PVC-MPs. Superoxide dismutase, catalase, and peroxidase activities in wheat seedlings increased, while malondialdehyde and proline contents decreased significantly. Redundancy analysis displayed that wheat seedlings traits can be largely explained by soil nitrate nitrogen. Our results indicate that PVC-MPs have more significant influence on soil structure than on soil substance composition. Moreover, even though antioxidant enzyme activities were improved to respond the stress of PVC-MPs, wheat seedlings are not severely impacted by PVC-MPs. Besides, soil nitrate nitrogen is the main factor on wheat seedlings performance and wheat seedlings are prone to ensure the root growth under the stress of PVC-MPs.

Comprehensively assessing priority odorants emitted from swine slurry combining nontarget screening with olfactory threshold prediction.

The lack of one-to-one olfactory thresholds (OTs) poses an obstacle to the comprehensive assessment of priority odorants emitted from swine slurry using mass spectrometric nontarget screening. This study screened out highly performing quantitative structure-activity relationship (QSAR) models of OT prediction to complement nontarget screening in olfactory perception evaluation. A total of 27 compounds emitted at different slurry removal frequencies were identified and quantified using gas chromatography-mass spectrometry (GC-MS), including thiirane, dimethyl trisulfide (DMTS), and dimethyl tetrasulfide (DMQS) without OT records. Ridge regression (RR, R2 = 0.77, RMSE = 0.93, MAE = 0.73) and random forest regression (RFR, R2 = 0.76, RMSE = 0.97, MAE = 0.69) rather than the commonly used principal component regression (PCR) and partial least squares regression (PLSR) were used to assign OTs and assess the contributions of emerging volatile sulfur compounds (VSCs) to the sum of odor activity value (SOAV). Priority odorants were p-cresol (25.0-58.9 %) > valeric acid (8.3-31.7 %) > isovaleric acid (6.7-19.0 %) > dimethyl disulfide (4.7-15.7 %) > methanethiol (0-13.6 %) > isobutyric acid (0-8.6 %), whereas the contributions of three emerging VSCs were below 10 %. Vital olfactory active structures were identified by QSAR models as having high molecular polarity, high hydrophilicity, high charge quantity, flexible structure, high reactivity, and a high number of sulfur atoms. This protocol can be further extended to evaluate odor pollution levels for distinct odor sources and guide the development of pertinent deodorization technologies.

Crystallization Control Based on the Regulation of Solvent-Perovskite Coordination for High-Performance Ambient Printable FAPbI3 Perovskite Solar Cells.

The critical requirement for ambient-printed formamidinium lead iodide (FAPbI3 ) lies in the control of nucleation-growth kinetics and defect formation behavior, which are extensively influenced by interactions between the solvent and perovskite. Here, a strategy is developed that combines a cosolvent and an additive to efficiently tailor the coordination between the solvent and perovskite. Through in situ characterizations, the direct crystallization from the sol-gel phase to α-FAPbI3 is illustrated. When the solvent exhibits strong interactions with the perovskite, the sol-gel phases cannot effectively transform into α-FAPbI3 , resulting in a lower nucleation rate and confined crystal growth directions. Consequently, it becomes challenging to fabricate high-quality void-free perovskite films. Conversely, weaker solvent-perovskite coordination promotes direct crystallization from sol-gel phases to α-FAPbI3 . This process exhibits more balanced nucleation-growth kinetics and restrains the formation of defects and microstrains in situ. This strategy leads to improved structural and optoelectronic properties within the FAPbI3 films, characterized by more compact grain stacking, smoother surface morphology, released lattice strain, and fewer defects. The ambient-printed FAPbI3 perovskite solar cells fabricated using this strategy exhibit a remarkable power conversion efficiency of 24%, with significantly reduced efficiency deviation and negligible decreases in the stabilized output.

Root-associated bacterial microbiome shaped by root selective effects benefits phytostabilization by Athyrium wardii (Hook.).

The root-associated microbiome assembly substantially promotes (hyper)accumulator plant growth and metal accumulation and is influenced by multiple factors, especially host species and environmental stress. Athyrium wardii (Hook.) is a phytostabilizer that grows in lead (Pb)-zinc (Zn) mine tailings and shows high root Pb accumulation. However, there remains little information on the assembly of the root-associated microbiome of A. wardii and its role in phytostabilization. A field study investigated the structural and functional variation in the root-associated bacterial microbiome of Athyrium wardii (Hook.) exposed to different levels of contamination in Pb-Zn mine tailings. The root compartment dominated the variation in the root-associated bacterial microbiome but the levels of contaminants showed less impact. Bacterial co-occurrence was enhanced in the rhizosphere soil and rhizoplane but tended to be much simpler in the endosphere in terms of network complexity and connectivity. This indicates that the microbial community assembly of A. wardii was non-random and shaped by root selective effects. Proteobacteria, Chloroflexi, Actinobacteria, Cyanobacteria, and Acidobacteriota were generally the dominant bacterial phyla. The genera Crossiella and Bradyrhizobium were enriched in the rhizosphere and cyanobacterial genera were enriched in the endosphere, demonstrating substantial advantages to plant survival and adaptation in the harsh mine environment. Functional categories involved in amino acid and carbohydrate metabolism were abundant in the rhizosphere soil, thus contributing to metal solubility and bioavailability in the rhizosphere. Membrane transporters, especially ATP-binding cassette transporters, were enriched in the endosphere, indicating a potential role in metal tolerance and transportation in A. wardii. The study shows substantial variation in the structure and function of microbiomes colonizing different compartments, with the rhizosphere and endophytic microbiota potentially involved in plant metal tolerance and accumulation during phytostabilization.