HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints.

In recent years, cyclic peptides have emerged as a promising therapeutic modality due to their diverse biological activities. Understanding the structures of these cyclic peptides and their complexes is crucial for unlocking invaluable insights about protein target-cyclic peptide interaction, which can facilitate the development of novel-related drugs. However, conducting experimental observations is time-consuming and expensive. Computer-aided drug design methods are not practical enough in real-world applications. To tackles this challenge, we introduce HighFold, an AlphaFold-derived model in this study. By integrating specific details about the head-to-tail circle and disulfide bridge structures, the HighFold model can accurately predict the structures of cyclic peptides and their complexes. Our model demonstrates superior predictive performance compared to other existing approaches, representing a significant advancement in structure-activity research. The HighFold model is openly accessible at https://github.com/hongliangduan/HighFold.

Author Correction: The Apostasia genome and the evolution of orchids.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

APEX-pHLA: A novel method for accurate prediction of the binding between exogenous short peptides and HLA class I molecules.

Human leukocyte antigen (HLA) molecules play critically significant role within the realm of immunotherapy due to their capacities to recognize and bind exogenous antigens such as peptides, subsequently delivering them to immune cells. Predicting the binding between peptides and HLA molecules (pHLA) can expedite the screening of immunogenic peptides and facilitate vaccine design. However, traditional experimental methods are time-consuming and inefficient. In this study, an efficient method based on deep learning was developed for predicting peptide-HLA binding, which treated peptide sequences as linguistic entities. It combined the architectures of textCNN and BiLSTM to create a deep neural network model called APEX-pHLA. This model operated without limitations related to HLA class I allele variants and peptide segment lengths, enabling efficient encoding of sequence features for both HLA and peptide segments. On the independent test set, the model achieved Accuracy, ROC_AUC, F1, and MCC is 0.9449, 0.9850, 0.9453, and 0.8899, respectively. Similarly, on an external test set, the results were 0.9803, 0.9574, 0.8835, and 0.7863, respectively. These findings outperformed fifteen methods previously reported in the literature. The accurate prediction capability of the APEX-pHLA model in peptide-HLA binding might provide valuable insights for future HLA vaccine design.

Oridonin attenuates liver ischemia-reperfusion injury by suppressing PKM2/NLRP3-mediated macrophage pyroptosis.

BACKGROUND: The NOD-like receptor protein 3 (NLRP3) mediated pyroptosis of macrophages is closely associated with liver ischemia reperfusion injury (IRI). As a covalent inhibitor of NLRP3, Oridonin (Ori), has strong anti-inflammasome effect, but its effect and mechanisms for liver IRI are still unknown. METHODS: Mice and liver macrophages were treated with Ori, respectively. Co-IP and LC-MS/MS analysis of the interaction between PKM2 and NLRP3 in macrophages. Liver damage was detected using H&E staining. Pyroptosis was detected by WB, TEM, and ELISA. RESULTS: Ori ameliorated liver macrophage pyroptosis and liver IRI. Mechanistically, Ori inhibited the interaction between pyruvate kinase M2 isoform (PKM2) and NLRP3 in hypoxia/reoxygenation（H/R）-induced macrophages, while the inhibition of PKM2/NLRP3 reduced liver macrophage pyroptosis and liver IRI. CONCLUSION: Ori exerted protective effects on liver IRI via suppressing PKM2/NLRP3-mediated liver macrophage pyroptosis, which might become a potential therapeutic target in the clinic.

Dual-domain mean-reverting diffusion model-enhanced temporal compressive coherent diffraction imaging.

Temporal compressive coherent diffraction imaging is a lensless imaging technique with the capability to capture fast-moving small objects. However, the accuracy of imaging reconstruction is often hindered by the loss of frequency domain information, a critical factor limiting the quality of the reconstructed images. To improve the quality of these reconstructed images, a method dual-domain mean-reverting diffusion model-enhanced temporal compressive coherent diffraction imaging (DMDTC) has been introduced. DMDTC leverages the mean-reverting diffusion model to acquire prior information in both frequency and spatial domain through sample learning. The frequency domain mean-reverting diffusion model is employed to recover missing information, while hybrid input-output algorithm is carried out to reconstruct the spatial domain image. The spatial domain mean-reverting diffusion model is utilized for denoising and image restoration. DMDTC has demonstrated a significant enhancement in the quality of the reconstructed images. The results indicate that the structural similarity and peak signal-to-noise ratio of images reconstructed by DMDTC surpass those obtained through conventional methods. DMDTC enables high temporal frame rates and high spatial resolution in coherent diffraction imaging.

Lycorine relieves the CCl4-induced liver fibrosis mainly via the JAK2/STAT3 and PI3K/AKT signaling pathways.

Liver fibrosis, a progressive process of fibrous scarring, results from the accumulation of extracellular matrix proteins (ECM). If left untreated, it often progresses to diseases such as cirrhosis and hepatocellular carcinoma. Lycorine, a natural alkaloid derived from medicinal plants, has shown diverse bioactivities by targeting JAK2/STAT3 signaling, but its pharmacological effects and potential molecular mechanisms in liver fibrosis remains largely unexplored. The purpose of this study is to elucidate the pharmacological activity and molecular mechanism of lycorine in anti-hepatic fibrosis. Findings indicate that lycorine significantly inhibited hepatic stellate cells (HSCs) activation by reducing the expression of α-SMA and collagen-1. In vivo, lycorine treatment alleviated carbon tetrachloride (CCl4) -induced mice liver fibrosis, improving liver function, decreasing ECM deposition, and inhibiting fibrosis-related markers' expression. Mechanistically, it was found that lycorine exerts protective activity through the JAK2/STAT3 and PI3K/AKT signaling pathways, as evidenced by transcriptome sequencing technology and small molecule inhibitors. These results underscore lycorine's potential as a therapeutic drug for liver fibrosis.

Predicting Drug-Drug Interactions Involving Rifampicin Using a Semi-mechanistic Hepatic Compartmental Model.

AIMS: To develop a semi-mechanistic hepatic compartmental model to predict the effects of rifampicin, a known inducer of CYP3A4 enzyme, on the metabolism of five drugs, in the hope of informing dose adjustments to avoid potential drug-drug interactions. METHODS: A search was conducted for DDI studies on the interactions between rifampicin and CYP substrates that met specific criteria, including the availability of plasma concentration-time profiles, physical and absorption parameters, pharmacokinetic parameters, and the use of healthy subjects at therapeutic doses. The semi-mechanistic model utilized in this study was improved from its predecessors, incorporating additional parameters such as population data (specifically for Chinese and Caucasians), virtual individuals, gender distribution, age range, dosing time points, and coefficients of variation. RESULTS: Optimal parameters were identified for our semi-mechanistic model by validating it with clinical data, resulting in a maximum difference of approximately 2-fold between simulated and observed values. PK data of healthy subjects were used for most CYP3A4 substrates, except for gilteritinib, which showed no significant difference between patients and healthy subjects. Dose adjustment of gilteritinib co-administered with rifampicin required a 3-fold increase of the initial dose, while other substrates were further tuned to achieve the desired drug exposure. CONCLUSIONS: The pharmacokinetic parameters AUCR and CmaxR of drugs metabolized by CYP3A4, when influenced by Rifampicin, were predicted by the semi-mechanistic model to be approximately twice the empirically observed values, which suggests that the semi-mechanistic model was able to reasonably simulate the effect. The doses of four drugs adjusted via simulation to reduce rifampicin interaction.

Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and obstructive sleep apnea: a cross-sectional study from NHANES.

BACKGROUND: Obstructive Sleep Apnea (OSA) is a widespread sleep disturbance linked to metabolic and cardiovascular conditions. The Non-High-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratios (NHHR) has been proposed as being a potential biomarker to gauge cardiovascular risk. However, its relationship with OSA remains unclear. METHODS: This survey investigated the link NHHR to OSA in American citizens aged 20 and older using information collected via the National Health and Nutrition Examination Survey (NHANES) during the years 2017 to 2020. Logistic regression models with multivariable adjustments were employed to assess this relationship. Nonlinear associations were explored using smooth curve fitting, with a two-part linear regression model identifying a threshold effect. Subgroup analyses were conducted to evaluate population-specific differences. RESULTS: The survey encompassed 6763 participants, with an average age of 50.75 ± 17.32. The average NHHR stood at 2.74, accompanied by a standard deviation of 1.34, while the average frequency of OSA was 49.93%. Upon adjusting for covariates, each unit increase in NHHR may be associated with a 9% rise in OSA incidence. (95% confidence intervals 1.04-1.14; P < 0.0001). Notably, a U-shaped curve depicted the NHHR-OSA relationship, with an inflection point at 4.12. Subgroup analyses revealed consistent associations, with educational attainment and diabetes status modifying the NHHR-OSA relationship. CONCLUSION: The study highlights NHHR as a potential tool for OSA prediction, presenting avenues for advanced risk evaluation, tailored interventions, personalized treatment approaches, and preventive healthcare.

Unraveling the role of low-density lipoprotein-related genes in lung adenocarcinoma: Insights into tumor microenvironment and clinical prognosis.

BACKGROUND: The hypothesized link between low-density lipoprotein (LDL) and oncogenesis has garnered significant interest, yet its explicit impact on lung adenocarcinoma (LUAD) remains to be elucidated. This investigation aims to demystify the function of LDL-related genes (LRGs) within LUAD, endeavoring to shed light on the complex interplay between LDL and carcinogenesis. METHODS: Leveraging single-cell transcriptomics, we examined the role of LRGs within the tumor microenvironment (TME). The expression patterns of LRGs across diverse cellular phenotypes were delineated using an array of computational methodologies, including AUCell, UCell, singscore, ssGSEA, and AddModuleScore. CellChat facilitated the exploration of distinct cellular interactions within LDL_low and LDL_high groups. The findmarker utility, coupled with Pearson correlation analysis, facilitated the identification of pivotal genes correlated with LDL indices. An integrative approach to transcriptomic data analysis was adopted, utilizing a machine learning framework to devise an LDL-associated signature (LAS). This enabled the delineation of genomic disparities, pathway enrichments, immune cell dynamics, and pharmacological sensitivities between LAS stratifications. RESULTS: Enhanced cellular crosstalk was observed in the LDL_high group, with the CoxBoost+Ridge algorithm achieving the apex c-index for LAS formulation. Benchmarking against 144 extant LUAD models underscored the superior prognostic acuity of LAS. Elevated LAS indices were synonymous with adverse outcomes, diminished immune surveillance, and an upsurge in pathways conducive to neoplastic proliferation. Notably, a pronounced susceptibility to paclitaxel and gemcitabine was discerned within the high-LAS cohort, delineating prospective therapeutic corridors. CONCLUSION: This study elucidates the significance of LRGs within the TME and introduces an LAS for prognostication in LUAD patients. Our findings accentuate putative therapeutic targets and elucidate the clinical ramifications of LAS deployment.

CCDN-DETR: A Detection Transformer Based on Constrained Contrast Denoising for Multi-Class Synthetic Aperture Radar Object Detection.

The effectiveness of the SAR object detection technique based on Convolutional Neural Networks (CNNs) has been widely proven, and it is increasingly used in the recognition of ship targets. Recently, efforts have been made to integrate transformer structures into SAR detectors to achieve improved target localization. However, existing methods rarely design the transformer itself as a detector, failing to fully leverage the long-range modeling advantages of self-attention. Furthermore, there has been limited research into multi-class SAR target detection. To address these limitations, this study proposes a SAR detector named CCDN-DETR, which builds upon the framework of the detection transformer (DETR). To adapt to the multiscale characteristics of SAR data, cross-scale encoders were introduced to facilitate comprehensive information modeling and fusion across different scales. Simultaneously, we optimized the query selection scheme for the input decoder layers, employing IOU loss to assist in initializing object queries more effectively. Additionally, we introduced constrained contrastive denoising training at the decoder layers to enhance the model's convergence speed and improve the detection of different categories of SAR targets. In the benchmark evaluation on a joint dataset composed of SSDD, HRSID, and SAR-AIRcraft datasets, CCDN-DETR achieves a mean Average Precision (mAP) of 91.9%. Furthermore, it demonstrates significant competitiveness with 83.7% mAP on the multi-class MSAR dataset compared to CNN-based models.

Quantifying Atomically Dispersed Catalysts Using Deep Learning Assisted Microscopy.

The catalytic performance of atomically dispersed catalysts (ADCs) is greatly influenced by their atomic configurations, such as atom-atom distances, clustering of atoms into dimers and trimers, and their distributions. Scanning transmission electron microscopy (STEM) is a powerful technique for imaging ADCs at the atomic scale; however, most STEM analyses of ADCs thus far have relied on human labeling, making it difficult to analyze large data sets. Here, we introduce a convolutional neural network (CNN)-based algorithm capable of quantifying the spatial arrangement of different adatom configurations. The algorithm was tested on different ADCs with varying support crystallinity and homogeneity. Results show that our algorithm can accurately identify atom positions and effectively analyze large data sets. This work provides a robust method to overcome a major bottleneck in STEM analysis for ADC catalyst research. We highlight the potential of this method to serve as an on-the-fly analysis tool for catalysts in future in situ microscopy experiments.

Identification of nsLTP family in Chinese white pear (Pyrus bretschneideri) reveals its potential roles in russet skin formation.

MAIN CONCLUSION: Identification of PbLTP genes in pear and functional characterization of PbLTP4 in the transport of suberin monomers of russet skin formation. Non-specific lipid-transfer protein (nsLTP) is an abundant and diverse alkaline small molecule protein in the plant kingdom with complex and diverse biophysiological functions, such as transfer of phospholipids, reproductive development, pathogen defence and abiotic stress response. Up to now, only a tiny fraction of nsLTPs have been functionally identified, and the distribution of nsLTPs in pear (Pyrus bretschneideri) (PbLTPs) has not been fully characterized. In this study, the genome-wide analysis of the nsLTP gene family in the pear genome identified 67 PbLTP proteins, which could be divided into six types (1, 2, C, D, E, and G). Similar intron/exon structural patterns were observed in the same type, strongly supporting their close evolutionary relationship. In addition, PbLTP4 was highly expressed in russet pear skin compared with green skin, which was located in the plasma membrane. Coexpression network analysis showed that PbLTP4 closely related to suberin biosynthetic genes. The biological function of PbLTP4 in promoting suberification has been demonstrated by overexpression in Arabidopsis. Identification of suberin monomers showed that PbLTP4 promotes suberification by regulating 9,12-octadecadienoic acid and hexadecanoic acid transport. These results provide helpful insights into the characteristics of PbLTP genes and their biological function in the transport of suberin monomers of russet skin formation.

A near-complete assembly of asparagus bean provides insights into anthocyanin accumulation in pods.

Asparagus bean (Vigna unguiculata ssp. sesquipedialis), a subspecies of V. unguiculata, is a vital legume crop widely cultivated in Asia for its tender pods consumed as vegetables. However, the existing asparagus bean assemblies still contain numerous gaps and unanchored sequences, which presents challenges to functional genomics research. Here, we present an improved reference genome sequence of an elite asparagus bean variety, Fengchan 6, achieved through the integration of nanopore ultra-long reads, PacBio high-fidelity reads, and Hi-C technology. The improved assembly is 521.3 Mb in length and demonstrates several enhancements, including a higher N50 length (46.4 Mb), an anchor ratio of 99.8%, and the presence of only one gap. Furthermore, we successfully assembled 14 telomeres and all 11 centromeres, including four telomere-to-telomere chromosomes. Remarkably, the centromeric regions cover a total length of 38.1 Mb, providing valuable insights into the complex architecture of centromeres. Among the 30 594 predicted protein-coding genes, we identified 2356 genes that are tandemly duplicated in segmental duplication regions. These findings have implications for defence responses and may contribute to evolutionary processes. By utilizing the reference genome, we were able to effectively identify the presence of the gene VuMYB114, which regulates the accumulation of anthocyanins, thereby controlling the purple coloration of the pods. This discovery holds significant implications for understanding the underlying mechanisms of color determination and the breeding process. Overall, the highly improved reference genome serves as crucial resource and lays a solid foundation for asparagus bean genomic studies and genetic improvement efforts.

Homozygous missense variant in MEIOSIN causes premature ovarian insufficiency.

STUDY QUESTION: Are variants of genes involved in meiosis initiation responsible for premature ovarian insufficiency (POI)? SUMMARY ANSWER: A MEIOSIN variant participates in the pathogenesis of human POI by impairing meiosis due to insufficient transcriptional activation of essential meiotic genes. WHAT IS KNOWN ALREADY: Meiosis is the key event for the establishment of the ovarian reserve, and several gene defects impairing meiotic homologous recombination have been found to contribute to the pathogenesis of POI. Although STRA8 and MEIOISN variants have been found to associate with POI in a recent study, the condition of other meiosis initiation genes is unknown and direct evidence of variants participating in the pathogenesis of POI is still lacking. STUDY DESIGN, SIZE, DURATION: This was a retrospective genetic study. An in-house whole exome sequencing (WES) database of 1030 idiopathic POI patients was screened for variations of meiosis initiation genes. PARTICIPANTS/MATERIALS, SETTING, METHODS: Homozygous or compound heterozygous variations of genes involved in meiosis initiation were screened in the in-house WES database. The pathogenicity of the variation was verified by in vitro experiments, including protein structure prediction and dual-luciferase reporter assay. The effect of the variant on ovarian function and meiosis was demonstrated through histological analyses in a point mutation mouse model. MAIN RESULTS AND THE ROLE OF CHANCE: One homozygous variant in MEIOSIN (c.1735C>T, p.R579W) and one in STRA8 (c.258 + 1G>A), which initiates meiosis via the retinoic acid-dependent pathway, were identified in a patient with idiopathic POI respectively. The STRA8 variation has been reported in the recently published work. For the MEIOSIN variation, the dual-luciferase reporter assay revealed that the variant adversely affected the transcriptional function of MEIOSIN in upregulating meiotic genes. Furthermore, knock-in mice with the homologous mutation confirmed that the variation impacted the meiotic prophase I program and accelerated oocyte depletion. Moreover, the variant p.R579W localizing in the high-mobility group (HMG) box domain disrupted the nuclear localization of the MEIOSIN protein but was dispensable for the cell-cycle switch of oocytes, suggesting a unique role of the MEIOSIN HMG box domain in meiosis initiation. LIMITATIONS, REASONS FOR CAUTION: Further studies are needed to explore the role of other meiosis initiation genes in the pathogenesis of POI. WIDER IMPLICATIONS OF THE FINDINGS: The MEIOSIN variant was verified to cause POI by impaired transcriptional regulation of meiotic genes and was inherited by a recessive mode. The function of HMG box domain in MEIOSIN protein was also expanded by this study. Although causative variations in meiotic initiation genes are rare in POI, our study confirmed the pathogenicity of a MEIOSIN variant and elucidated another mechanism of human infertility. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Key Research & Developmental Program of China (2022YFC2703800, 2022YFC2703000), National Natural Science Foundation for Distinguished Young Scholars (82125014), National Natural Science Foundation of China (32070847, 32170867, 82071609), Basic Science Center Program of NSFC (31988101), Natural Science Foundation of Shandong Province for Grand Basic Projects (ZR2021ZD33), Natural Science Foundation of Shandong Province for Excellent Young Scholars (ZR2022YQ69), Taishan Scholars Program for Young Experts of Shandong Province (tsqn202211371), and Qilu Young Scholars Program of Shandong University. The authors declare no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.

Efficient Computational Framework for Target-Specific Active Peptide Discovery: A Case Study on IL-17C Targeting Cyclic Peptides.

The development of potentially active peptides for specific targets is critical for the modern pharmaceutical industry's growth. In this study, we present an efficient computational framework for the discovery of active peptides targeting a specific pharmacological target, which combines a conditional variational autoencoder (CVAE) and a classifier named TCPP based on the Transformer and convolutional neural network. In our example scenario, we constructed an active cyclic peptide library targeting interleukin-17C (IL-17C) through a library-based in vitro selection strategy. The CVAE model is trained on the preprocessed peptide data sets to generate potentially active peptides and the TCPP further screens the generated peptides. Ultimately, six candidate peptides predicted by the model were synthesized and assayed for their activity, and four of them exhibited promising binding affinity to IL-17C. Our study provides a one-stop-shop for target-specific active peptide discovery, which is expected to boost up the process of peptide drug development.

Impact of dietary sucralose and sucrose-sweetened water intake on lipid and glucose metabolism in male mice.

AIMS: Overconsumption of sugar-sweetened beverages (SSBs) is associated with an increased risk of metabolic disorders, including obesity and diabetes. However, accumulating evidence also suggests the potential negative impact of consuming nonnutritive sweeteners (NNSs) on weight and glycaemic control. The metabolic effects of sucralose, the most widely used NNS, remain controversial. This study aimed to compare the impact of intake of dietary sucralose (acceptable daily intake dose, ADI dose) and sucrose-sweetened water (at the same sweetness level) on lipid and glucose metabolism in male mice. MATERIALS AND METHODS: Sucralose (0.1 mg/mL) or sucrose (60 mg/mL) was added to the drinking water of 8-week-old male C57BL/6 mice for 16 weeks, followed by oral glucose and intraperitoneal insulin tolerance tests, and measurements of bone mineral density, plasma lipids, and hormones. After the mice were sacrificed, the duodenum and ileum were used for examination of sweet taste receptors (STRs) and glucose transporters. RESULTS: A significant increase in fat mass was observed in the sucrose group of mice after 16 weeks of sweetened water drinking. Sucrose consumption also led to increased levels of plasma LDL, insulin, lipid deposition in the liver, and increased glucose intolerance in mice. Compared with the sucrose group, mice consuming sucralose showed much lower fat accumulation, hyperlipidaemia, liver steatosis, and glucose intolerance. In addition, the daily dose of sucralose only had a moderate effect on T1R2/3 in the intestine, without affecting glucose transporters and plasma insulin levels. CONCLUSION: Compared with mice consuming sucrose-sweetened water, daily drinking of sucralose within the ADI dose had a much lower impact on glucose and lipid homeostasis.

The Apostasia genome and the evolution of orchids.

Constituting approximately 10% of flowering plant species, orchids (Orchidaceae) display unique flower morphologies, possess an extraordinary diversity in lifestyle, and have successfully colonized almost every habitat on Earth. Here we report the draft genome sequence of Apostasia shenzhenica, a representative of one of two genera that form a sister lineage to the rest of the Orchidaceae, providing a reference for inferring the genome content and structure of the most recent common ancestor of all extant orchids and improving our understanding of their origins and evolution. In addition, we present transcriptome data for representatives of Vanilloideae, Cypripedioideae and Orchidoideae, and novel third-generation genome data for two species of Epidendroideae, covering all five orchid subfamilies. A. shenzhenica shows clear evidence of a whole-genome duplication, which is shared by all orchids and occurred shortly before their divergence. Comparisons between A. shenzhenica and other orchids and angiosperms also permitted the reconstruction of an ancestral orchid gene toolkit. We identify new gene families, gene family expansions and contractions, and changes within MADS-box gene classes, which control a diverse suite of developmental processes, during orchid evolution. This study sheds new light on the genetic mechanisms underpinning key orchid innovations, including the development of the labellum and gynostemium, pollinia, and seeds without endosperm, as well as the evolution of epiphytism; reveals relationships between the Orchidaceae subfamilies; and helps clarify the evolutionary history of orchids within the angiosperms.

Size-dependent miscibility controls the kinetics of anion exchange in cesium lead halide nanocrystals.

Anion exchange is a facile, post-synthetic method to tune the emission wavelength of colloidal cesium lead halide (CsPbX3, X = Cl, Br, I) perovskite nanocrystals. While colloidal nanocrystals can exhibit size-dependent phase stability and chemical reactivity, the role of size in the mechanism of anion exchange in CsPbX3 nanocrystals has not been elucidated. We used single-particle fluorescence microscopy to monitor the transformation of individual CsPbBr3 nanocrystals to CsPbI3. By systematically varying the size of the nanocrystals and the concentration of substitutional iodide, we observed that smaller nanocrystals exhibit longer transition times in their fluorescence trajectories, while larger nanocrystals undergo a more abrupt transition during anion exchange. Monte Carlo simulations were used to rationalize the size-dependent reactivity, in which we varied how each exchange event affects the probability for further exchange. Greater cooperativity for simulated ion exchange leads to shorter transition times to complete the exchange. We propose that size-dependent miscibility between CsPbBr3 and CsPbI3 at the nanoscale controls the reaction kinetics. Smaller nanocrystals maintain a homogeneous composition during anion exchange. As the nanocrystal size increases, variations in the octahedral tilting patterns of the perovskite crystals lead to different structures for CsPbBr3 and CsPbI3. Thus, an iodide-rich region must first nucleate within larger CsPbBr3 nanocrystals, which is followed by rapid transformation to CsPbI3. While higher concentrations of substitutional anions can suppress this size-dependent reactivity, the inherent differences in reactivity between nanocrystals of different sizes are important to consider when scaling up this reaction for applications in solid-state lighting and biological imaging.

The correlation between osteoporotic vertebrae fracture risk and bone mineral density measured by quantitative computed tomography and dual energy X-ray absorptiometry: a systematic review and meta-analysis.

This paper presents a comparison of quantitative computed tomography (QCT) and dual-energy X-ray absorptiometry (DXA) in osteoporosis with vertebral fracture and osteoporosis without fracture. It has been proved that the volumetric bone mineral density (vBMD) measured by QCT exhibits a stronger correlation with fracture risk than areal bone mineral density (aBMD) measured by DXA. PURPOSE: This study aims to systematically evaluate the ability of QCT and DXA to distinguish between osteoporosis with vertebral fracture and osteoporosis without fracture according to vBMD and aBMD. METHODS: We conducted a primary literature search of the online databases up to 3 July, 2022, in both English and Chinese publications, combining synonyms for "QCT", "DXA" and "osteoporosis". The Newcastle-Ottawa scale (NOS) was employed to evaluate the quality of the selected articles. vBMD obtained through QCT and aBMD obtained through DXA were extracted, and were analyzed by Review Manager 5.4 and RStudio. RESULTS: Six studies with 610 individuals aged 45 to 90, of which 179 had vertebral fractures, were included in the final analysis. The weighted mean difference (WMD) between osteoporosis with vertebral fracture and osteoporosis without fracture for vBMD was - 27.08 (95% CI - 31.24 to - 22.92), while for aBMD was - 0.05 (95% CI - 0.08 to - 0.03). CONCLUSIONS: Both vBMD detected by QCT and aBMD detected by DXA could discriminate fracture status in the spine, and vBMD performed a stronger correlation with fracture risk. TRIAL REGISTRATION: PROSPERO 2022 CRD42022349185.

Expression profile and functional prediction of novel LncRNA 5.8S rRNA-OT1 in cattle.

Long non-coding RNAs (LncRNAs) are generally longer than 200 bp in length and play an important regulatory role in the growth and development of skeletal muscle. In the previous work, the non-coding RNAs with abundant expression in bovine tissues were screened out. After quantitative real-time PCR (qPCR), 33 lncRNAs with differential expression in various bovine tissues were identified. Differential expression analysis base on tissue expression profiles of 33 lncRNAs, a long non-coding RNA LncRNA13, which may have effects on bovine muscle development, was found. The expression levels in embryo muscle and adult cattle muscle were significantly different (p < 0.01), so it is speculated that it may have a certain impact on the development of cattle muscle. It was named LncRNA 5.8S rRNA-OT1, and its overexpression vector pcDNA3.1-LncRNA 5.8S rRNA-OT1 was cloned and constructed. The purpose of this study is to further explore its impact on the proliferation and differentiation of bovine muscle cells and accumulate data to lay a foundation for further exploration of the function of LncRNA 5.8S rRNA-OT1 and add basic data for the study of the regulatory mechanism of lncRNA.