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 .

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.

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.

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.

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.

Cation transporters in cell fate determination and plant adaptive responses to a low-oxygen environment.

Soil flooding creates low-oxygen environments in root zones and thus severely affects plant growth and productivity. Plants adapt to low-oxygen environments by a suite of orchestrated metabolic and anatomical alterations. Of these, formation of aerenchyma and development of adventitious roots are considered very critical to enable plant performance in waterlogged soils. Both traits have been firmly associated with stress-induced increases in ethylene levels in root tissues that operate upstream of signalling pathways. Recently, we used a bioinformatic approach to demonstrate that several Ca2+ and K+ -permeable channels from KCO, AKT, and TPC families could also operate in low oxygen sensing in Arabidopsis. Here we argue that low-oxygen-induced changes to cellular ion homeostasis and operation of membrane transporters may be critical for cell fate determination and formation of the lysigenous aerenchyma in plant roots and shaping the root architecture and adventitious root development in grasses. We summarize the existing evidence for a causal link between tissue-specific changes in oxygen concentration, intracellular Ca2+ and K+ homeostasis, and reactive oxygen species levels, and their role in conferring those two major traits enabling plant adaptation to a low-oxygen environment. We conclude that, for efficient operation, plants may rely on several complementary signalling pathway mechanisms that operate in concert and 'fine-tune' each other. A better understanding of this interaction may create additional and previously unexplored opportunities to crop breeders to improve cereal crop yield losses to soil flooding.

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.

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.

Liposomal Controlled Release Ag-Activated DNAzyme Cycle Amplification on a 2D Pyrene COF-Based Photocathode for α-Synuclein Immunosensing.

Ultrasensitive and accurate monitoring of ultralow-level biomarkers is imperiously needed in clinical diagnosis. So far, exploring high-performance photocathodes and developing new sensing strategies have remained central challenges in photoelectrochemical bioassays. Herein, a two-dimensional (2D) pyrene covalent organic framework (COF, PAF-130) is exemplified for the first time as a high-performance photocathode for precise immunosensing of α-synuclein (α-Syn) by integrating a DNAzyme-induced signal cycle amplification strategy with Ag nanoparticles (NPs)-mediated liposomal immunoassay. Through sequential immunobinding, lysis treatment, and acidolysis, numerous Ag+ ions are released, and then they activate the DNAzyme, which further recycles the cleavage of hairpin DNA (HDNA) on the photoelectrode and induces signal cycle amplification. As a result, an ultralow detection limit (3.6 fg/mL) and a wide linear range (10-5-103 ng/mL) are achieved, which surpass those of most methods reported so far. The proposed sensing approach can be readily extended to detect various biomarkers by substituting the biorecognition events, providing great promise for biomedical and related applications.

"Dual Signal-On" Split-Type Aptasensor for TNF-α: Integrating MQDs/ZIF-8@ZnO NR Arrays with MB-Liposome-Mediated Signal Amplification.

Ultrasensitive and accurate detection of biomarkers in serum is of great importance for disease diagnosis and treatment. So far, the commonly used single-mode signal suffers from certain instinct drawbacks that restrict assay performances. Herein, we report the proof-of-concept fabrication of a split-type photoelectrochemical (PEC) and electrochemical (EC) dual-modal aptasensor for ultrasensitively tracing tumor necrosis factor-α, a noteworthy biological biomarker with essential clinical importance. By smart integrating molybdenum disulfide QDs/zeolitic imidazolate framework-8@ZnO nanorod arrays with a methylene blue-liposome-mediated signal amplification strategy, "dual signal-on" detection is accomplished based on a sandwich reaction of the target with aptamer-anchored carboxyl magnetic beads and an aptamer-confined MB liposome. Linear ranges of 5 fg/mL-5 µg/mL (detection limit 1.46 fg/mL) for PEC and 10 fg/mL-0.5 µg/mL (detection limit 6.14 fg/mL) for EC are obtained, respectively. An independent signal transduction mechanism supports the accuracy improvement, and a separate biological process from a translator enables convenient fabrication, short-time consumption, wider linearity, as well as outstanding reproducibility and stability in practical application. This work presents a universal bioassay route with prospects in biomedical and related areas.

Identifying Potential Polymicrobial Pathogens: Moving Beyond Differential Abundance to Driver Taxa.

It is now recognized that some diseases of aquatic animals are attributed to polymicrobial pathogens infection. Thus, the traditional view of "one pathogen, one disease" might mislead the identification of multiple pathogens, which in turn impedes the design of probiotics. To address this gap, we explored polymicrobial pathogens based on the origin and timing of increased abundance over shrimp white feces syndrome (WFS) progression. OTU70848 Vibrio fluvialis, OTU35090 V. coralliilyticus, and OTU28721 V. tubiashii were identified as the primary colonizers, whose abundances increased only in individuals that eventually showed disease signs but were stable in healthy subjects over the same timeframe. Notably, the random Forest model revealed that the profiles of the three primary colonizers contributed an overall 91.4% of diagnosing accuracy of shrimp health status. Additionally, NetShift analysis quantified that the three primary colonizers were important "drivers" in the gut microbiotas from healthy to WFS shrimp. For these reasons, the primary colonizers were potential pathogens that contributed to the exacerbation of WFS. By this logic, we further identified a few "drivers" commensals in healthy individuals, such as OUT50531 Demequina sediminicola and OTU_74495 Ruegeria lacuscaerulensis, which directly antagonized the three primary colonizers. The predicted functional pathways involved in energy metabolism, genetic information processing, terpenoids and polyketides metabolism, lipid and amino acid metabolism significantly decreased in diseased shrimp compared with those in healthy cohorts, in concordant with the knowledge that the attenuations of these functional pathways increase shrimp sensitivity to pathogen infection. Collectively, we provide an ecological framework for inferring polymicrobial pathogens and designing antagonized probiotics by quantifying their changed "driver" feature that intimately links shrimp WFS progression. This approach might generalize to the exploring disease etiology for other aquatic animals.

Meta-analysis of major QTL for abiotic stress tolerance in barley and implications for barley breeding.

MAIN CONCLUSION: We projected meta-QTL (MQTL) for drought, salinity, and waterlogging tolerance to the physical map of barley through meta-analysis. The positions of these MQTL were refined and candidate genes were identified. Drought, salinity and waterlogging are three major abiotic stresses limiting barley yield worldwide. Breeding for abiotic stress-tolerant crops has drawn increased attention, and a large number of quantitative trait loci (QTL) for drought, salinity, and waterlogging tolerance in barley have been detected. However, very few QTL have been successfully used in marker-assisted selection (MAS) in breeding. In this study, we summarized 632 QTL for drought, salinity and waterlogging tolerance in barley. Among all these QTL, only 195 major QTL were used to conduct meta-analysis to refine QTL positions for MAS. Meta-analysis was used to map the summarized major QTL for drought, salinity, and waterlogging tolerance from different mapping populations on the barley physical map. The positions of identified meta-QTL (MQTL) were used to search for candidate genes for drought, salinity, and waterlogging tolerance in barley. Both MQTL3H.4 and MQTL6H.2 control drought tolerance in barley. Fine-mapped QTL for salinity tolerance, HvNax4 and HvNax3, were validated on MQTL1H.4 and MQTL7H.2, respectively. MQTL2H.1 and MQTL5H.3 were also the target regions for improving salinity tolerance in barley. MQTL4H.4 is the main region controlling waterlogging tolerance in barley with fine-mapped QTL for aerenchyma formation under waterlogging conditions. Detected and refined MQTL and candidate genes are crucial for future successful MAS in barley breeding.

A new major-effect QTL for waterlogging tolerance in wild barley (H. spontaneum).

KEY MESSAGE: We report the first study on the unique allele from wild barley that can improve waterlogging tolerance in cultivated barley with a substantially higher contribution to aerenchyma formation. Waterlogging is one of the major abiotic stresses that dramatically reduce barley crop yield. Direct selection on waterlogging tolerance in the field is less effective due to its viability to environment. The most effective way of selection is to choose traits that make significant contributions to the overall tolerance and are easy to score. Aerenchyma formation under waterlogging stress is one of the most effective mechanisms to provide adequate oxygen supply and overcome stress-induced hypoxia imposed on plants. In this study, a new allele for aerenchyma formation was identified from a wild barley accession TAM407227 on chromosome 4H. Compared to that identified in cultivated barley, this allele not only produced a greater proportion of aerenchyma but made a greater contribution to the overall waterlogging tolerance. The QTL explained 76.8% of phenotypic variance in aerenchyma formation with a LOD value of 51.4. Markers co-segregating with the trait were identified and can be effectively used in marker assisted selection.

Identification of aerenchyma formation-related QTL in barley that can be effective in breeding for waterlogging tolerance.

KEY MESSAGE: Aerenchyma formation after 7 days of waterlogging in commercial potting mixture can be a reliable, fast, and widely utilized approach for the selection of waterlogging tolerant barley genotypes. One major QTL for aerenchyma formation after 7 days of waterlogging treatment was identified and the newly developed markers explained 44 % of the phenotypic variance. This QTL can now be effectively used in barley breeding programs. Waterlogging is one of the important limiting conditions for crop yield and productivity. The main feature of waterlogged soils is oxygen deprivation, due to slow gas diffusion in water. Decreased oxygen content in waterlogged soils leads to the oxygen deficiency in plant tissues, resulting in reduced energy availability for plants. Rapidly induced aerenchyma formation is critical to maintaining adequate oxygen supply and overall waterlogging tolerance in barley. In this study, we have proved that quantifying aerenchyma formation after 7 days of waterlogging in commercial potting mixture can be a reliable, fast, and widely utilised approach for the selection of waterlogging tolerant barley genotypes, which is supported by measurements of redox potential (an indicator of anaerobic conditions). This protocol was also used to identify quantitative trait loci (QTL) in a doubled haploid population of barley from the cross between Yerong (tolerant) and Franklin (sensitive) genotypes. The QTL for aerenchyma formation and root porosity were at the same location as the waterlogging tolerance QTL. Seven new markers were developed and added onto this region on chromosome 4H. One major QTL for aerenchyma formation after 7 days waterlogging treatment explained 44.0 % of the phenotypic variance. This successful QTL for aerenchyma formation can be effectively used in the marker assisted selection to improve waterlogging tolerance in barley.

Band Alignment Modulated Polarity-Switchable PEC Ratiometric Sensor through Coupling a pH-Responsive CuTCPP MOF with i-Motif Sensing tool.

In conventional ratiometric photoelectrochemical (PEC) sensors, the detection and reference signals are output sequentially from two independent photosensitive materials. In such a "two-to-two" ratiometric mode, unavoidable difference during dual-interface modification exists, resulting in questionable ratiometric signals and detection results. To address this issue, we propose a novel "one-to-two" ratiometric PEC sensor on a single electrode interface through pH-modulated band alignment engineering. The double ratiometric signals are generated by the synergistic action of a pH-responsive CuTCPP/WS2 photoelectric substrate material and the i-motif sensing tool. Specifically, a ternary heterostructure to generate a photoanodic detection signal is formed under alkaline conditions between CuTCPP/WS2 and signal label CdS QDs binding to the i-motif. While under acidic conditions, a photocurrent polarity conversion and signaling labels detachment, induced by the band realignment of CuTCPP/WS2 and the i-motif conformational switching, produce a reliable internal reference photocathodic signal. The feasibility of this two-wing signal generation strategy is validated by detecting mycotoxin ochratoxin A, which achieves accurate and reliable ratio detection results. Overall, this work provides guidance for the design of a PEC ratiometric determination system and exhibits great potential to be applied in practical analysis research.

Photocurrent switchable dual-target bioassay: Signal distinction and interface reconfiguration via pH-responsive triplex DNA programming.

Most multiplexed photoelectrochemical (PEC) sensors require additional instrumentation and cumbersome electrode modification and surface partitioning, which limits their portability and instrument miniaturization. Herein, a pH-responsive programmable triple DNA nanomachine was developed for constructing a reconfigurable multiplex PEC sensing platform. By programming the base sequence, T-A·T-riched triple DNA was designed to construct integrated nano-controlled release machine (INCRM) for simultaneous recognition of multiple targets. The INCRM enables to recognize two targets in one step, and sequentially separate the signal labels by pH adjustment. The detached signal label catalyzes glucose to produce gluconic acid, causing the C-riched DNA fold into a triple structure on the electrode surface. As a result, one target can be detected relying on the enhanced photocurrent due to accelerated electron transfer between the CdS QD labeled at the end of C-riched DNA and the electrode. The triplex DNA dissociation in pH 7.4 buffer reconfigures the electrode interface, which can be continued to detect another target. The feasibility of the multiplexed sensor is verified by the detection of extensively coexisting antibiotics enrofloxacin (ENR) and ciprofloxacin (CIP). Under the optimal conditions, wide linear range (10 fg/mL âˆ¼ 1 µg/mL) and low detection limit (3.27 fg/mL and 9.60 fg/mL) were obtained. The pH-regulated programmable triplex DNA nanomachine-based sensing platform overcomes the technical difficulties of conventional multiplexed PEC assay, which may open the way for miniaturization of multiplexed PEC sensors.

Advanced deep learning algorithm for instant discriminating of tea leave stress symptoms by smartphone-based detection.

The primary challenges in tea production under multiple stress exposures have negatively affected its global market sustainability, so introducing an infield fast technique for monitoring tea leaves' stresses has tremendous urgent needs. Therefore, this study aimed to propose an efficient method for the detection of stress symptoms based on a portable smartphone with deep learning models. Firstly, a database containing over 10,000 images of tea garden canopies in complex natural scenes was developed, which included healthy (no stress) and three types of stress (tea anthracnose (TA), tea blister blight (TB) and sunburn (SB)). Then, YOLOv5m and YOLOv8m algorithms were adapted to discriminate the four types of stress symptoms; where the YOLOv8m algorithm achieved better performance in the identification of healthy leaves (98%), TA (92.0%), TB (68.4%) and SB (75.5%). Furthermore, the YOLOv8m algorithm was used to construct a model for differentiation of disease severity of TA, and a satisfactory result was obtained with the accuracy of mild, moderate, and severe TA infections were 94%, 96%, and 91%, respectively. Besides, we found that CNN kernels of YOLOv8m could efficiently extract the texture characteristics of the images at layer 2, and these characteristics can clearly distinguish different types of stress symptoms. This makes great contributions to the YOLOv8m model to achieve high-precision differentiation of four types of stress symptoms. In conclusion, our study provided an effective system to achieve low-cost, high-precision, fast, and infield diagnosis of tea stress symptoms in complex natural scenes based on smartphone and deep learning algorithms.

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.

Population structure and selective signature of Kirghiz sheep by Illumina Ovine SNP50 BeadChip.

Objective: By assessing the genetic diversity and associated selective traits of Kirghiz sheep (KIR), we aim to uncover the mechanisms that contribute to sheep's adaptability to the Pamir Plateau environment. Methods: This study utilized Illumina Ovine SNP50 BeadChip data from KIR residing in the Pamir Plateau, Qira Black sheep (QBS) inhabiting the Taklamakan Desert, and commonly introduced breeds including Dorper sheep (DOR), Suffolk sheep (SUF), and Hu sheep (HU). The data was analyzed using principal component analysis, phylogenetic analysis, population admixture analysis, kinship matrix analysis, linkage disequilibrium analysis, and selective signature analysis. We employed four methods for selective signature analysis: fixation index (Fst), cross-population extended homozygosity (XP-EHH), integrated haplotype score (iHS), and nucleotide diversity (Pi). These methods aim to uncover the genetic mechanisms underlying the germplasm resources of Kirghiz sheep, enhance their production traits, and explore their adaptation to challenging environmental conditions. Results: The test results unveiled potential selective signals associated with adaptive traits and growth characteristics in sheep under harsh environmental conditions, and annotated the corresponding genes accordingly. These genes encompass various functionalities such as adaptations associated with plateau, cold, and arid environment (ETAA1, UBE3D, TLE4, NXPH1, MAT2B, PPARGC1A, VEGFA, TBX15 and PLXNA4), wool traits (LMO3, TRPS1, EPHA5), body size traits (PLXNA2, EFNA5), reproductive traits (PPP3CA, PDHA2, NTRK2), and immunity (GATA3). Conclusion: Our study identified candidate genes associated with the production traits and adaptation to the harsh environment of the Pamir Plateau in Kirghiz sheep. These findings provide valuable resources for local sheep breeding programs. The objective of this study is to offer valuable insights for the sustainable development of the Kirghiz sheep industry.

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.