DCES-PA: Deformation-controllable elastic shape model for 3D bone proliferation analysis using hand HR-pQCT images.

Bone proliferation is an important pathological feature of inflammatory rheumatic diseases. Although recent advance in high-resolution peripheral quantitative computed tomography (HR-pQCT) enables physicians to study microarchitectures, physicians' annotation of proliferation suffers from slice inconsistency and subjective variations. Also, there are only few effective automatic or semi-automatic tools for proliferation detection. In this study, by integrating pathological knowledge of proliferation formation with the advancement of statistical shape analysis theory, we present an unsupervised method, named Deformation-Controllable Elastic Shape model, for 3D bone Proliferation Analysis (DCES-PA). Unlike previous shape analysis methods that directly regularize the smoothness of the displacement field, DCES-PA regularizes the first and second-order derivative of the displacement field and decomposes these vector fields according to different deformations. For the first-order elastic metric, DCES-PA orthogonally decomposes the first-order derivative of the displacement field by shearing, scaling and bending deformation, and then penalize deformations triggering proliferation formation. For the second-order elastic metric, DCES-PA encodes both intrinsic and extrinsic surface curvatures into the second-order derivative of the displacement field to control the generation of high-curvature regions. By integrating the elastic shape metric with the varifold distances, DCES-PA achieves correspondence-free shape analysis. Extensive experiments on both simulated and real clinical datasets demonstrate that DCES-PA not only shows an improved accuracy than other state-of-the-art shape-based methods applied to proliferation analysis but also produces highly sensitive proliferation annotations to assist physicians in proliferation analysis.

Lithiated porous silicon nanowires stimulate periodontal regeneration.

Periodontal disease is a significant burden for oral health, causing progressive and irreversible damage to the support structure of the tooth. This complex structure, the periodontium, is composed of interconnected soft and mineralised tissues, posing a challenge for regenerative approaches. Materials combining silicon and lithium are widely studied in periodontal regeneration, as they stimulate bone repair via silicic acid release while providing regenerative stimuli through lithium activation of the Wnt/ß-catenin pathway. Yet, existing materials for combined lithium and silicon release have limited control over ion release amounts and kinetics. Porous silicon can provide controlled silicic acid release, inducing osteogenesis to support bone regeneration. Prelithiation, a strategy developed for battery technology, can introduce large, controllable amounts of lithium within porous silicon, but yields a highly reactive material, unsuitable for biomedicine. This work debuts a strategy to lithiate porous silicon nanowires (LipSiNs) which generates a biocompatible and bioresorbable material. LipSiNs incorporate lithium to between 1% and 40% of silicon content, releasing lithium and silicic acid in a tailorable fashion from days to weeks. LipSiNs combine osteogenic, cementogenic and Wnt/ß-catenin stimuli to regenerate bone, cementum and periodontal ligament fibres in a murine periodontal defect.

Continuous identification of the tea shoot tip and accurate positioning of picking points for a harvesting from standard plantations.

To address the current problems of large positioning error, low picking efficiency, and high cost of tea shoot picking, a continuous and precise harvesting scheme for tea shoots based on a two-dimensional (2D) perspective is designed in this study. A high-speed harvesting method for tea shoots in a standardized tea plantation assembly line type was proposed. First, a 2D view recognition model of tea shoot tips in a multi-disturbance environment was constructed, and accurate picking point coordinates were determined by combining a skeleton algorithm and curve growth. To avoid the losses of recognition accuracy caused by the mistaken clamping of blades and vibrations during harvester operations, accurate control of the harvester was realized by combining path planning and the S-curve speed control function. The recognition accuracy for the verification set of the recognition model was 99.9%, and the mean average precision (0.5:0.95) value was 0.97. The test results show that the error between the actual picking point position and the position determined by the model was within ± 3 mm, and the picking success rate was 83.6%. Therefore, we can realize fast and accurate picking of tea shoots and lay the foundation for continuous tea picking in the future by simplifying the identification and picking process.

ECL 3.0: a sensitive peptide identification tool for cross-linking mass spectrometry data analysis.

BACKGROUND: Cross-linking mass spectrometry (XL-MS) is a powerful technique for detecting protein-protein interactions (PPIs) and modeling protein structures in a high-throughput manner. In XL-MS experiments, proteins are cross-linked by a chemical reagent (namely cross-linker), fragmented, and then fed into a tandem mass spectrum (MS/MS). Cross-linkers are either cleavable or non-cleavable, and each type requires distinct data analysis tools. However, both types of cross-linkers suffer from imbalanced fragmentation efficiency, resulting in a large number of unidentifiable spectra that hinder the discovery of PPIs and protein conformations. To address this challenge, researchers have sought to improve the sensitivity of XL-MS through invention of novel cross-linking reagents, optimization of sample preparation protocols, and development of data analysis algorithms. One promising approach to developing new data analysis methods is to apply a protein feedback mechanism in the analysis. It has significantly improved the sensitivity of analysis methods in the cleavable cross-linking data. The application of the protein feedback mechanism to the analysis of non-cleavable cross-linking data is expected to have an even greater impact because the majority of XL-MS experiments currently employs non-cleavable cross-linkers. RESULTS: In this study, we applied the protein feedback mechanism to the analysis of both non-cleavable and cleavable cross-linking data and observed a substantial improvement in cross-link spectrum matches (CSMs) compared to conventional methods. Furthermore, we developed a new software program, ECL 3.0, that integrates two algorithms and includes a user-friendly graphical interface to facilitate wider applications of this new program. CONCLUSIONS: ECL 3.0 source code is available at https://github.com/yuweichuan/ECL-PF.git . A quick tutorial is available at https://youtu.be/PpZgbi8V2xI .

Methanogenic and methanotrophic communities determine lower CH4 fluxes in a subtropical paddy field under long-term elevated CO2.

Clarifying the effects of elevated CO2 concentration (e[CO2]) on CH4 emissions from paddy fields and its mechanisms is a crucial part of the research on agricultural systems in response to global climate change. However, the response of CH4 fluxes from rice fields to long-term e[CO2] (e[CO2] duration >10 years) and its microbial mechanism is still lacking. In this study, we used a long-term free-air CO2 enrichment experiment to examine the relationship between CH4 fluxes and the methanogenic and methanotrophic consortia under long- and short-term e[CO2]. We demonstrated that contrary to the effect of short-term e[CO2], long-term e[CO2] decreased CH4 fluxes. This may be associated with the reduction of methanogenic abundance and the increase of methanotrophic abundance under long-term e[CO2]. In addition, long-term e[CO2] also changed the community structure and composition of methanogens and methanotrophs compared with short-term e[CO2]. Partial least squares path modeling analysis showed that long-term e[CO2] also could affect the abundance and composition of methanogens and methanotrophs indirectly by influencing soil physical and chemical properties, thereby ultimately altering CH4 fluxes in paddy soils. These findings suggest that current estimates of short-term e[CO2]-induced CH4 fluxes from paddy fields may be overestimated. Therefore, a comprehensive assessment of climate­carbon cycle feedbacks may need to consider the microbial regulation of CH4 production and oxidation processes in paddy ecosystems under long-term e[CO2].

HCR/DNAzyme-triggered cascaded feedback cycle amplification for self-powered dual-photoelectrode detection of femtomolar HPV16.

For high-performance dual-photoelectrode assay, developing a pair of photoactive materials with well-matched band structure and the design of a powerful sensing strategy are highly desirable. Herein, the Zn-TBAPy pyrene-based MOF and BiVO4/Ti3C2 Schottky junction were employed as photocathode and photoanode to form an efficient dual-photoelectrode system. The integration of the cascaded hybridization chain reaction (HCR)/DNAzyme-assisted feedback amplification with DNA walker-mediated cycle amplification strategy realizes femtomolar HPV16 dual-photoelectrode bioassay. Through the activation of the HCR cascaded with the DNAzyme system in the presence of HPV16, plentiful HPV16 analogs are generated that leads to exponential positive feedback signal amplification. Meanwhile on the Zn-TBAPy photocathode, the NDNA hybridizes with the bipedal DNA walker followed by circular cleavage by Nb.BbvCI NEase, producing a dramatically enhanced PEC readout. The achieved ultralow detection limit of 0.57 fM and a wide linear range of 10-6 nM-103 nM showcase the excellent performance of the developed dual-photoelectrode system.

Self-Cleaning Recyclable Multiplexed Photoelectrochemical Sensing Strategy Based on Exonuclease III-Assisted Signal Discrimination.

For discriminating the signals of multi-targets, multiplexed photoelectrochemical (PEC) detection is generally accomplished by modulating the light source or voltage, which prospect is usually limited by expensive instrumentation, tedious operational steps, and time-consuming material screening. To realize multiplexed determination on single photoelectric interface using the routine technique, a non-instrument-assisted strategy for signal discrimination needs to be explored. Herein, we propose an exonuclease III-mediated multiple PEC signals resolution strategy and construct a self-cleaning recyclable multiplexed PEC sensor using a porphyrin-bipyridine-based covalent organic framework (Por-Bpy COF) photocathode. Specifically, following the dual-target recognition event, exonuclease III cleaves the DNA strand attached to the magnetic bead so that the two signal labels can be separated. Once the signal label binds to the DNA on the electrode surface (E-DNA), exonuclease III turns to excise the DNA strand of the signal label and consequently the E-DNA can repeatedly bind different signal labels. As a result, distinguishable photocurrent signals of different targets can be generated on a single photoelectric interface. The feasibility of this multiplexed sensor is verified by detecting two coexisting mycotoxins aflatoxin B1 and zearalenone. On account of eliminating the instrumentation constraints and simplifying the experimental procedures, the proposed sensing strategy may provide a brand-new idea for the exploration of portable multiplexed PEC sensing devices.

Design and operation of a Peucedani Radix weeding device based on YOLOV5 and a parallel manipulator.

To avoid excessive use of herbicides in the weeding operations of Peucedani Radix, a common Chinese herb, a precision seedling avoidance and weeding agricultural robot was designed for the targeted spraying of herbicides. The robot uses YOLOV5 combined with ExG feature segmentation to detect Peucedani Radix and weeds and obtain their corresponding morphological centers. Optimal seedling avoidance and precise herbicide spraying trajectories are generated using a PSO-Bezier algorithm based on the morphological characteristics of Peucedani Radix. Seedling avoidance trajectories and spraying operations are executed using a parallel manipulator with spraying devices. The validation experiments showed that the precision and recall of Peucedani Radix detection were 98.7% and 88.2%, respectively, and the weed segmentation rate could reach 95% when the minimum connected domain was 50. In the actual Peucedani Radix field spraying operation, the success rate of field precision seedling avoidance herbicide spraying was 80.5%, the collision rate between the end actuator of the parallel manipulator and Peucedani Radix was 4%, and the average running time of the parallel manipulator for precision herbicide spraying on a single weed was 2 s. This study can enrich the theoretical basis of targeted weed control and provide reference for similar studies.

Nitrogen inhibitors improve soil ecosystem multifunctionality by enhancing soil quality and alleviating microbial nitrogen limitation.

Soil quality (SQI) is a comprehensive indicator reflecting the agricultural productivity of soil, and soil ecosystem multifunctionality (performing multiple functions simultaneously; EMF) can reflect complex biogeochemical processes. However, the effects of enhanced efficiency nitrogen fertilizers (EENFs; urease inhibitors (NBPT), nitrification inhibitors (DCD), and coated controlled-release urea (RCN)) application on the SQI and soil EMF and their relationships are still unclear. Therefore, we conducted a field experiment to study the effects of different EENFs on the SQI, enzyme stoichiometry and soil EMF in semiarid areas of Northwest China (Gansu, Ningxia, Shaanxi, Shanxi). Across the four study sites, DCD and NBPT increased SQI by 7.61-16.80 % and 2.61 %-23.20 % compared to mineral fertilizer, respectively. N fertilizer application (N200 and EENFs) alleviated microbial N limitation, and EENFs alleviated microbial N and C limitations to a greater extent in Gansu and Shanxi. Moreover, nitrogen inhibitors (Nis; DCD and NBPT) improved the soil EMF to a greater extent than N200 and RCN, DCD increased by 205.82-340.00 % and 145.00-215.47 % in Gansu and Shanxi, respectively; NBPT increased by 332.75-778.59 % and 364.44-929.62 % in Ningxia and Shanxi, respectively. A random forest model showed that the microbial biomass carbon (MBC), microbial biomass nitrogen (MBN) and soil water content (SWC) of the SQI factors were the main driving forces of soil EMF. Moreover, SQI improvement could alleviate microbial C and N limitations and promote the improvement of soil EMF. It is worth noting that soil EMF was mainly affected by microbial N limitation rather than C limitation. Overall, NIs application is an effective way to improve the SQI and soil EMF in the semiarid region of Northwest China.

Comparing the variations and influencing factors of CH4 emissions from paddies and wetlands under CO2 enrichment: A data synthesis in the last three decades.

Understanding and quantifying the impact of elevated tropospheric carbon dioxide concentration (e [CO2]) on methane (CH4) globally is important for effectively assessing and mitigating climate warming. Paddies and wetlands are the two important sources of CH4 emissions. Yet, a quantitative synthetic investigation of the effects of e [CO2] on CH4 emissions from paddies and wetlands on a global scale has not been conducted. Here, we conducted a meta-analysis of 488 observation cases from 40 studies to assess the long-term effects of e [CO2] (ambient [CO2]+ 53-400 µmol mol-1) on CH4 emissions and to identify the relevant key drivers. On aggregate, e [CO2] increased CH4 emissions by 25.7% (p < 0.05) from paddies but did not affect CH4 emissions from wetlands (-3.29%; p > 0.05). The e [CO2] effects on paddy CH4 emissions were positively related to that on belowground biomass and soil-dissolved CH4 content. However, these factors under e [CO2] resulted in no significant change in CH4 emissions in wetlands. Particularly, the e [CO2]-induced abundance of methanogens increased in paddies but decreased in wetlands. In addition, tillering number of rice and water table levels affected e [CO2]-induced CH4 emissions in paddies and wetlands, respectively. On a global scale, CH4 emissions changed from an increase (+0.13 and + 0.86 Pg CO2-eq yr-1) under short-term e [CO2] into a decrease and no changes (-0.22 and + 0.03 Pg CO2-eq yr-1) under long-term e [CO2] in paddies and wetlands, respectively. This suggested that e [CO2]-induced CH4 emissions from paddies and wetlands changed over time. Our results not only shed light on the different stimulative responses of CH4 emissions to e [CO2] from paddy and wetland ecosystems but also suggest that estimates of e [CO2]-induced CH4 emissions from global paddies and wetlands need to account for long-term changes in various regions.

Automatic 3D joint erosion detection for the diagnosis and monitoring of rheumatoid arthritis using hand HR-pQCT images.

Rheumatoid arthritis (RA) is a chronic inflammatory disease. It leads to bone erosion in joints and other complications, which severely affect patients' quality of life. To accurately diagnose and monitor the progression of RA, quantitative imaging and analysis tools are desirable. High-resolution peripheral quantitative computed tomography (HR-pQCT) is such a promising tool for monitoring disease progression in RA. However, automatic erosion detection tools using HR-pQCT images are not yet available. Inspired by the consensus among radiologists on the erosions in HR-pQCT images, in this paper we define erosion as the significant concave regions on the cortical layer, and develop a model-based 3D automatic erosion detection method. It mainly consists of two steps: constructing closed cortical surface, and detecting erosion regions on the surface. In the first step, we propose an initialization-robust region competition methods for joint segmentation, and then fill the surface gaps by using joint bone separation and curvature-based surface alignment. In the second step, we analyze the curvature information of each voxel, and then aggregate the candidate voxels into concave surface regions and use the shape information of the regions to detect the erosions. We perform qualitative assessments of the new method using 59 well-annotated joint volumes. Our method has shown satisfactory and consistent performance compared with the annotations provided by medical experts.

[Effects of Vegetation Restoration on Soil Organic Carbon Sequestration and Aggregate Stability in Water-Eroded Environment: A Meta-analysis].

In order to clarify the differences in the effects of vegetation restoration strategies on soil carbon sequestration and aggregate stability under different water-eroded environments, we collected experimental data from 91 papers and evaluated the response of soil organic carbon (SOC) stock and aggregate stability to vegetation restoration based on Meta-analysis. The results showed the following:① compared with cropland or bare land, forestland/grassland restoration was beneficial to increase SOC stock and improve aggregate stability, but the dominant functions of the two were different. The effect of forestland restoration on carbon sequestration was stronger than that of grassland reforestation, and the effect of grassland restoration on aggregate stability was stronger than that of forestland restoration. ② Multi-factor Meta-analysis showed that the factors that significantly affected SOC were restoration year, soil clay content, vegetation coverage, mean annual precipitation (MAP), mean annual temperature (MAT), and soil depth. The positive effect of vegetation restoration on SOC stock increased with the increase in vegetation coverage rate. Grassland restoration had a more significant effect on SOC stock when soil clay content was 20%-32%, it was more likely to promote the carbon sequestration effect of grassland when MAP>800 mm or MAT<15℃, and there was no significant change in SOC stock under different restoration years. However, the effect of forestland restoration on SOC stock was more significant when soil clay content was>32%. Climate conditions had no limited effect on SOC stock in forestland, and there was a positive effect between SOC stock under forestland restoration and restoration years. ③ Vegetation restoration had stronger significant positive effects on mean weight diameter (MWD) and mean geometric diameter (GMD) when the clay content was 20%-32%, and MWD and GMD increased with the increase in vegetation coverage. ④SOC stock growth could explain 25% and 24% of the variation in the effect value of MWD and GMD, respectively. These results indicated that the formation of SOC was the result of multiple factors, and soil aggregate stability was limited only by vegetation coverage and soil clay content. The increase in SOC stock could promote the improvement of water stability MWD and GMD. These results can clarify the carbon sequestration effect of different vegetation restoration measures in water-eroded environments and provide theoretical reference for the restoration and reconstruction of degraded ecosystems.

Fertilizer-induced N2O and NO emissions in tea gardens and the main controlling factors: A recent three-decade data synthesis.

Tea gardens have been widely documented to be hotspots for nitrogen (N) oxide emissions (i.e., nitrous oxide (N2O) and nitric oxide (NO)). However, a quantitative understanding of N oxide emissions related to different fertilizer regimes and the main controlling factors is lacking. Here, we performed a meta-analysis of 56 peer-reviewed publications on N oxide emissions from global tea gardens over the past three decades. Overall, fertilization increased N2O and NO emissions (p < 0.001) by 584 % and 790 %, respectively. The stimulating effect of fertilizer on N2O and NO emissions was mainly related to high N application rates. Furthermore, organic fertilizer treatment, combined fertilizer treatment, biochar amendment, and inhibitor amendment reduced N2O emissions (p < 0.05) by 63 %, 64 %, 69 %, and 94 %, respectively, relative to chemical fertilizer treatment. For NO emissions, only biochar amendment decreased fertilizer-driven stimulation (by 80 %, p < 0.05). Notably, the dominant factors that influenced fertilizer-induced N2O and NO emissions in tea gardens were fertilization regimes, climatic conditions, and soil properties. On a global scale, fertilization increased mean N2O and NO emissions (p < 0.05) from global tea gardens by 44.5 Gg N yr-1 and 34.3 Gg N yr-1, respectively, whereas compared with no amendment application, inhibitors reduced N2O emissions (p < 0.05) by 32.2 Gg N yr-1 and biochar reduced NO emissions (p < 0.05) by 23.6 Gg N yr-1. Our results suggest that to obtain maximum ecological and economic benefits, appropriate N fertilizer and biochar and inhibitor amendments should be applied for site-specific mitigation purposes, and long-term, multiarea, in situ experiments and microbial mechanism studies should be conducted.

The spatial distribution of rhizosphere microbial activities under drought: water availability is more important than root-hair-controlled exudation.

Root hairs and soil water content are crucial in controlling the release and diffusion of root exudates and shaping profiles of biochemical properties in the rhizosphere. But whether root hairs can offset the negative impacts of drought on microbial activity remains unknown. Soil zymography, 14 C imaging and neutron radiography were combined to identify how root hairs and soil moisture affect rhizosphere biochemical properties. To achieve this, we cultivated two maize genotypes (wild-type and root-hair-defective rth3 mutant) under ambient and drought conditions. Root hairs and optimal soil moisture increased hotspot area, rhizosphere extent and kinetic parameters (Vmax and Km ) of ß-glucosidase activities. Drought enlarged the rhizosphere extent of root exudates and water content. Colocalization analysis showed that enzymatic hotspots were more colocalized with root exudate hotspots under optimal moisture, whereas they showed higher dependency on water hotspots when soil water and carbon were scarce. We conclude that root hairs are essential in adapting rhizosphere properties under drought to maintain plant nutrition when a continuous mass flow of water transporting nutrients to the root is interrupted. In the rhizosphere, soil water was more important than root exudates for hydrolytic enzyme activities under water and carbon colimitation.

Parental attachment and cyberbullying among college students: the mediating role of loneliness and the moderating role of interdependent self.

Although considerable research has shown that attachment is a protective factor for cyberbullying, little research has investigated the mechanisms underlying this relationship among college students. This study examined whether loneliness mediates the association between parental attachment and cyberbullying and whether this process is moderated by interdependent self. A sample of 1125 college students (Mage = 19.14, SDage = 1.52 years) in China completed a questionnaire measuring parental attachment, cyberbullying, loneliness, and interdependent self. Loneliness partially mediated the relationship between parental attachment and cyberbullying. Moreover, the mediation effect of loneliness was moderated by interdependent self. A moderated mediation analysis further revealed that interdependent-self moderated the predictive effect of loneliness on cyberbullying. Specifically, the predictive effect of loneliness on cyberbullying was only significant among college students with low interdependent self. The study highlights the complex nature of the association between parental attachment and cyberbullying. These findings provide new perspectives for intervention and prevention of cyberbullying among college students.

Microscale Spatiotemporal Variation and Generation Mechanisms of Reactive Oxygen Species in the Rhizosphere of Ryegrass: Coupled Biotic-Abiotic Processes.

Reactive oxygen species (ROS) play key roles in soil biogeochemical processes, yet the occurrence and accumulation of ROS in the rhizosphere are poorly documented. Herein, we first developed a ROS-trapping membrane to in situ determine ROS in the ryegrass rhizosphere and then quantified the temporal and spatial variations of representative ROS (i.e., O2•─, H2O2, and •OH). Fluorescence imaging clearly visualized the production of ROS in the rhizosphere. Both O2•─ and H2O2 content increased first and then declined throughout the life cycle of ryegrass, while •OH concentration decreased continuously. Spatially, ROS contents remained at a relatively high level at 0-5 mm and then descended with increasing distance. The concentrations of ROS in different soils followed the order of black soil > latosol soil > yellow-brown soil > tier soil ∼ red soil. Analysis of soil properties suggested that both biotic factors (microbial community) and abiotic factors (Fe(II) and water-soluble phenols) played critical roles in ROS production. The combined processes, including Fe(II) and water-soluble phenol-mediated electron transfer, microbial community-driven extracellular O2•─ release, and Fe(II)/Fe(III) cycling, may be responsible for ROS production. These findings provide insights into ROS-associated rhizosphere effects and inspiration for the phytoremediation of pollutants and element cycling.

Keep oxygen in check: An improved in-situ zymography approach for mapping anoxic hydrolytic enzyme activities in a paddy soil.

Paddy soils regularly experience redox oscillations during the wetting and draining stages, yet the effects of short-term presence of oxygen (O2) on in-situ microbial hotspots and enzyme activities in anoxic ecosystems remain unclear. To fill this knowledge gap, we applied soil zymography to localize hotspots and activities of phosphomonoesterase (PME), ß-glucosidase (BG), and leucine aminopeptidase (LAP) in three compartments of rice-planted rhizoboxes (top bulk, rooted, and bottom bulk paddy soil) under oxic (+O2) and anoxic (O2) conditions. Short-term (35 min) aeration decreased PME activity by 13-49 %, BG by 4-52 %, and LAP by 12-61 % as compared with O2 in three soil compartments. The percentage of hotspot area was higher by 3-110 % for PME, by 10-60 % for BG, and by 12-158 % for LAP under +O2 vs. O2 conditions depending on a rice growth stage. Irrespective of the aeration conditions, the rhizosphere extent of rice plants for three enzymes was generally greater under higher moisture conditions and at earlier growth stage. Higher O2 sensitivity for the tested enzymes at bottom bulk soil versus other compartments suggested that short-term aeration during conventional zymography may lead to underestimation of nutrient mobilization in subsoil compared to top bulk soil. The intolerance of anaerobic microorganisms against the toxicity of O2 in the cells and the shift of microbial metabolic pathways may explain such a short-term suppression by O2. Our findings, therefore, show that anoxic conditions and soil moisture should be kept during zymography and probably other in-situ soil imaging methods when studying anoxic systems.

Oral stem cells, decoding and mapping the resident cells populations.

The teeth and their supporting tissues provide an easily accessible source of oral stem cells. These different stem cell populations have been extensively studied for their properties, such as high plasticity and clonogenicity, expressing stem cell markers and potency for multilineage differentiation in vitro. Such cells with stem cell properties have been derived and characterised from the dental pulp tissue, the apical papilla region of roots in development, as well as the supporting tissue of periodontal ligament that anchors the tooth within the alveolar socket and the soft gingival tissue. Studying the dental pulp stem cell populations in a continuously growing mouse incisor model, as a traceable in vivo model, enables the researchers to study the properties, origin and behaviour of mesenchymal stem cells. On the other side, the oral mucosa with its remarkable scarless wound healing phenotype, offers a model to study a well-coordinated system of healing because of coordinated actions between epithelial, mesenchymal and immune cells populations. Although described as homogeneous cell populations following their in vitro expansion, the increasing application of approaches that allow tracing of individual cells over time, along with single-cell RNA-sequencing, reveal that different oral stem cells are indeed diverse populations and there is a highly organised map of cell populations according to their location in resident tissues, elucidating diverse stem cell niches within the oral tissues. This review covers the current knowledge of diverse oral stem cells, focusing on the new approaches in studying these cells. These approaches "decode" and "map" the resident cells populations of diverse oral tissues and contribute to a better understanding of the "stem cells niche architecture and interactions. Considering the high accessibility and simplicity in obtaining these diverse stem cells, the new findings offer potential in development of translational tissue engineering approaches and innovative therapeutic solutions.

Switchable Multiplex Photoelectrochemical Immunoassay of Aß42 and Aß40 Based on a pH-Responsive i-Motif Probe and Pyrene-Based MOF Photocathode.

In accurately diagnosing Alzheimer's disease (AD) and distinguishing AD from other dementia, the concentration ratio of amyloid-beta 42 (Aß42) to Aß40 is more reliable than the concentration of Aß42 alone. For the multiplex PEC assay, generating an independent photocurrent of multiple targets on a single interface is a great challenge. Herein, an i-motif-based switchable sensing approach is proposed to construct a pH-regulated multiplex PEC immunosensor for Aß42 and Aß40 by using Bi-TBAPy as an efficient photoactive cathode material. An independent photocurrent signal of Aß42 and Aß40 is produced through the regulation of the electron-transfer tunneling distance by a pH-dependent configuration transition of the i-motif DNA. In a 96-well plate, immunological recognition of Aß42 (or Aß40) coupled with an enzymatic catalytic reaction produces an acidic (or alkaline) lysis solution, which triggers the formation and unravelment of the i-motif structure. The above configuration transition regulates the distance between Au NPs labeled SH-DNA and Bi-TBAPy, leading to PEC signal switching. Smart integration of the pH-responsive switchable DNA probe with a high-efficiency photocathode enables the precise monitoring of Aß42 and Aß40 at a single interface in a wide detection range (10 fg/mL ∼ 1 µg/mL and 1 pg/mL ∼ 1 µg/mL) with detection limit of 4.5 fg/mL and 0.52 pg/mL, respectively. The proposed i-motif-based switchable sensing strategy paves a new avenue for a multiplex PEC assay on a single interface, showing great prospects in bioanalysis and early disease diagnosis.

Optimization of Roasted Green Tea Winnowing via Fluid-Solid Interaction Experiments and Simulations.

In the tea industry, achieving a high winnowing accuracy to produce high-quality tea is a complex challenge. The complex shape of the tea leaves and the uncertainty of the flow field lead to the difficulty in determining the wind selection parameters. The purpose of this paper was to determine the accurate wind selection parameters of tea through simulation and improve the precision of tea wind selection. This study used three-dimensional modeling to establish a high-precision simulation of dry tea sorting. The simulation environment of the tea material, flow field, and wind field wall were defined using a fluid-solid interaction method. The validity of the simulation was verified via experiments. The actual test found that the velocity and trajectory of tea particles in the actual and simulated environments were consistent. The numerical simulations identified wind speed, wind speed distribution, and wind direction as the main factors affecting the winnowing efficacy. The weight-to-area ratio was used to define the characteristics of different types of tea materials. The indices of discrete degree, drift limiting velocity, stratification height, and drag force were employed to evaluate the winnowing results. The separation of tea leaves and stems is best in the range of the wind angle of 5-25 degrees under the same wind speed. Orthogonal and single-factor experiments were conducted to analyze the influence of wind speed, wind speed distribution, and wind direction on wind sorting. The results of these experiments identified the optimal wind-sorting parameters: a wind speed of 12 m s-1, wind speed distribution of 45%, and wind direction angle of 10°. The larger the difference between the weight-to-area ratios of the tea leaves and stems, the more optimized the wind sorting. The proposed model provides a theoretical basis for the design of wind-based tea-sorting structures.