Incidence and prognostic factors of residual back pain in patients treated for osteoporotic vertebral compression fractures: a systematic review and meta-analysis.

BACKGROUND: Osteoporotic vertebral compression fracture (OVCF) is a common consequence of osteoporosis and can significantly impact the quality of life for affected individuals. Despite treatment options such as vertebroplasty and kyphoplasty, many patients continue to experience residual back pain (RBP) even after the fracture has healed. The incidence of RBP after OVCF treatment varies among studies, and there is a need for further research to understand the risk factors associated with RBP. METHODS: A systematic review and meta-analysis were conducted following the PRISMA guidelines. Electronic databases were searched, and relevant studies were selected based on inclusion and exclusion criteria. Data extraction and quality assessment were performed independently by two authors. Statistical analysis included single-proportion meta-analyses and pooling of odds ratios (OR) using the inverse-variance method, to calculate the overall incidences of RBP and cement leakage and identify risk factors associated with RBP. RESULTS: A total of 19 studies were included in the analysis. The overall incidences of RBP and cement leakage were found to be 16% and 18%, respectively. Several risk factors were identified, including gender, bone mineral density, depression, baseline visual analog scale (VAS) score, intravertebral vacuum cleft, number of fractured segments, cement distribution, history of vertebral fracture, thoracolumbar fascial injury, and fracture non-union. CONCLUSIONS: This study provides potential value within the scope of the incidence and risk factors of RBP following treatment of OVCFs. The identified risk factors can help clinicians identify high-risk patients and tailor appropriate interventions. Future research should focus on standardizing the definition of RBP and patient selection criteria to improve the accuracy of estimates and facilitate better management strategies for OVCF patients.

De novo generation of SARS-CoV-2 antibody CDRH3 with a pre-trained generative large language model.

Artificial Intelligence (AI) techniques have made great advances in assisting antibody design. However, antibody design still heavily relies on isolating antigen-specific antibodies from serum, which is a resource-intensive and time-consuming process. To address this issue, we propose a Pre-trained Antibody generative large Language Model (PALM-H3) for the de novo generation of artificial antibodies heavy chain complementarity-determining region 3 (CDRH3) with desired antigen-binding specificity, reducing the reliance on natural antibodies. We also build a high-precision model antigen-antibody binder (A2binder) that pairs antigen epitope sequences with antibody sequences to predict binding specificity and affinity. PALM-H3-generated antibodies exhibit binding ability to SARS-CoV-2 antigens, including the emerging XBB variant, as confirmed through in-silico analysis and in-vitro assays. The in-vitro assays validate that PALM-H3-generated antibodies achieve high binding affinity and potent neutralization capability against spike proteins of SARS-CoV-2 wild-type, Alpha, Delta, and the emerging XBB variant. Meanwhile, A2binder demonstrates exceptional predictive performance on binding specificity for various epitopes and variants. Furthermore, by incorporating the attention mechanism inherent in the Roformer architecture into the PALM-H3 model, we improve its interpretability, providing crucial insights into the fundamental principles of antibody design.

Comparative Analysis of Codon Usage Bias in Six Eimeria Genomes.

The codon usage bias (CUB) of genes encoded by different species' genomes varies greatly. The analysis of codon usage patterns enriches our comprehension of genetic and evolutionary characteristics across diverse species. In this study, we performed a genome-wide analysis of CUB and its influencing factors in six sequenced Eimeria species that cause coccidiosis in poultry: Eimeria acervulina, Eimeria necatrix, Eimeria brunetti, Eimeria tenella, Eimeria praecox, and Eimeria maxima. The GC content of protein-coding genes varies between 52.67% and 58.24% among the six Eimeria species. The distribution trend of GC content at different codon positions follows GC1 > GC3 > GC2. Most high-frequency codons tend to end with C/G, except in E. maxima. Additionally, there is a positive correlation between GC3 content and GC3s/C3s, but a significantly negative correlation with A3s. Analysis of the ENC-Plot, neutrality plot, and PR2-bias plot suggests that selection pressure has a stronger influence than mutational pressure on CUB in the six Eimeria genomes. Finally, we identified from 11 to 15 optimal codons, with GCA, CAG, and AGC being the most commonly used optimal codons across these species. This study offers a thorough exploration of the relationships between CUB and selection pressures within the protein-coding genes of Eimeria species. Genetic evolution in these species appears to be influenced by mutations and selection pressures. Additionally, the findings shed light on unique characteristics and evolutionary traits specific to the six Eimeria species.

Study on the role of microbial metabolites in in-situ noncontact bioleaching of ion-adsorption rare earth ore.

Ion adsorption rare earth ore nearly satisfy global market demand for heavy rare earth elements (HREEs). Bio-leaching has important potential for the clean and efficient extraction of ion-adsorption rare earth ore. However, the complexities of in-situ mining restrict the use of contact/direct bio-leaching, and non-contact/indirect bio-leaching would be the best choice. This study explore the potential of fermentation broths prepared by Yarrowia lipolytica (ATCC 30162) for the bio-leaching of ion-adsorption rare earth ore, and three typical metabolites (potassium citrate (K3Cit), sodium citrate (Na3Cit) and ammonium citrate ((NH4)3Cit) of Yarrowia lipolytica were further evaluated in simulated bioleaching (non-contact bioleaching) of ion-adsorption rare earth ore, including leaching behavior, seepage rule and rare earth elements (REEs) morphological transformation. The column leaching experiments shown that direct leaching of REEs using fermentation broths results in incomplete leaching of REEs due to the influence of impurities. Using the purified and prepared metabolites as lixiviant, REEs can be effectively extracted (leaching efficiency >90%) at cation concentration was only 10 % of the commonly used ammonium sulfate concentration (45 mM). Cation type had less effect on leaching efficiency. During the ion-adsorption rare earth ore leaching process, rare earth ions form a variety of complex chelates with citrate, thus transferring rare earth elements from the mineral surface to the leachate. Experimental results showed that pH and concentration together determined the type and form of rare earth chelates, which in turn affect the leaching behavior of REEs and solution seepage rule. This study helps to provide a theoretical basis for the regulation and enhancement of ion-adsorption rare earth ore non-contact bioleaching process.

Research on sound quality prediction of vehicle interior noise using the human-ear physiological model.

In order to improve the prediction accuracy of the sound quality of vehicle interior noise, a novel sound quality prediction model was proposed based on the physiological response predicted metrics, i.e., loudness, sharpness, and roughness. First, a human-ear sound transmission model was constructed by combining the outer and middle ear finite element model with the cochlear transmission line model. This model converted external input noise into cochlear basilar membrane response. Second, the physiological perception models of loudness, sharpness, and roughness were constructed by transforming the basilar membrane response into sound perception related to neuronal firing. Finally, taking the calculated loudness, sharpness, and roughness of the physiological model and the subjective evaluation values of vehicle interior noise as the parameters, a sound quality prediction model was constructed by TabNet model. The results demonstrate that the loudness, sharpness, and roughness computed by the human-ear physiological model exhibit a stronger correlation with the subjective evaluation of sound quality annoyance compared to traditional psychoacoustic parameters. Furthermore, the average error percentage of sound quality prediction based on the physiological model is only 3.81%, which is lower than that based on traditional psychoacoustic parameters.

Transcriptomic decoding of regional cortical vulnerability to major depressive disorder.

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Concomitant targeting of FLT3 and SPHK1 exerts synergistic cytotoxicity in FLT3-ITD+ acute myeloid leukemia by inhibiting ß-catenin activity via the PP2A-GSK3ß axis.

BACKGROUND: Approximately 25-30% of patients with acute myeloid leukemia (AML) have FMS-like receptor tyrosine kinase-3 (FLT3) mutations that contribute to disease progression and poor prognosis. Prolonged exposure to FLT3 tyrosine kinase inhibitors (TKIs) often results in limited clinical responses due to diverse compensatory survival signals. Therefore, there is an urgent need to elucidate the mechanisms underlying FLT3 TKI resistance. Dysregulated sphingolipid metabolism frequently contributes to cancer progression and a poor therapeutic response. However, its relationship with TKI sensitivity in FLT3-mutated AML remains unknown. Thus, we aimed to assess mechanisms of FLT3 TKI resistance in AML. METHODS: We performed lipidomics profiling, RNA-seq, qRT-PCR, and enzyme-linked immunosorbent assays to determine potential drivers of sorafenib resistance. FLT3 signaling was inhibited by sorafenib or quizartinib, and SPHK1 was inhibited by using an antagonist or via knockdown. Cell growth and apoptosis were assessed in FLT3-mutated and wild-type AML cell lines via Cell counting kit-8, PI staining, and Annexin-V/7AAD assays. Western blotting and immunofluorescence assays were employed to explore the underlying molecular mechanisms through rescue experiments using SPHK1 overexpression and exogenous S1P, as well as inhibitors of S1P2, ß-catenin, PP2A, and GSK3ß. Xenograft murine model, patient samples, and publicly available data were analyzed to corroborate our in vitro results. RESULTS: We demonstrate that long-term sorafenib treatment upregulates SPHK1/sphingosine-1-phosphate (S1P) signaling, which in turn positively modulates ß-catenin signaling to counteract TKI-mediated suppression of FLT3-mutated AML cells via the S1P2 receptor. Genetic or pharmacological inhibition of SPHK1 potently enhanced the TKI-mediated inhibition of proliferation and apoptosis induction in FLT3-mutated AML cells in vitro. SPHK1 knockdown enhanced sorafenib efficacy and improved survival of AML-xenografted mice. Mechanistically, targeting the SPHK1/S1P/S1P2 signaling synergizes with FLT3 TKIs to inhibit ß-catenin activity by activating the protein phosphatase 2 A (PP2A)-glycogen synthase kinase 3ß (GSK3ß) pathway. CONCLUSIONS: These findings establish the sphingolipid metabolic enzyme SPHK1 as a regulator of TKI sensitivity and suggest that combining SPHK1 inhibition with TKIs could be an effective approach for treating FLT3-mutated AML.

Artificial Intelligence Measurement of Preoperative Radiographs in Adolescent Idiopathic Scoliosis Based on Multiple-View Semantic Segmentation.

STUDY DESIGN: Cross-sectional study. OBJECTIVES: Imaging classification of adolescent idiopathic scoliosis (AIS) is directly related to the surgical strategy, but the artificial classification is complex and depends on doctors' experience. This study investigated deep learning-based automated classification methods (DL group) for AIS and validated the consistency of machine classification and manual classification (M group). METHODS: A total of 506 cases (81 males and 425 females) and 1812 AIS full spine images in the anteroposterior (AP), lateral (LAT), left bending (LB) and right bending (RB) positions were retrospectively used for training. The mean age was 13.6 ± 1.8. The mean maximum Cobb angle was 46.8 ± 12.0. U-Net semantic segmentation neural network technology and deep learning methods were used to automatically segment and establish the alignment relationship between multiple views of the spine, and to extract spinal features such as the Cobb angle. The type of each test case was automatically calculated according to Lenke's rule. An additional 107 cases of adolescent idiopathic scoliosis imaging were prospectively used for testing. The consistency of the DL group and M group was compared. RESULTS: Automatic vertebral body segmentation and recognition, multi-view alignment of the spine and automatic Cobb angle measurement were implemented. Compare to the M group, the consistency of the DL group was significantly higher in 3 aspects: type of lateral convexity (0.989 vs 0.566), lumbar curvature modifier (0.932 vs 0.738), and sagittal plane modifier (0.987 vs 0.522). CONCLUSIONS: Deep learning enables automated Cobb angle measurement and automated Lenke classification of idiopathic scoliosis whole spine radiographs with higher consistency than manual measurement classification.

Cephalopods' Skin-Inspired Design of Nanoscale Electronic Transport Layers for Adaptive Electrochromic Tuning.

Cephalopods can change their skin color by using high-speed electron transduction among receptors, neural networks, and pigmentary effectors. However, it remains challenging to realize a neuroelectrical transmission system like that found in cephalopods, where electrons/ions transmit on nanoscale, which is crucial for fast adaptive electrochromic tuning. Inspired by that, hereby an ideal, rapidly responsive, and multicolor electrochromic biomimetic skin is introduced. Specifically, the biomimetic skin comprises W18O49 nanowires (NWs) that are either colorless or blue, Au nanoparticles@polyaniline (Au NPs@PANI) ranging from green to pink, and a flexible conductive substrate. As the applied voltage changes from 0.4 V to -0.7 V and back to 0 V, the color of the biomimetic skin transforms from green to blue and ultimately to pink. This color change is attributed to the electrically induced redox reaction of Au NPs@PANI and W18O49 NWs, triggered by the transfer of electrons and ions. Furthermore, the high versatility and adaptability of electrical stimulus enable the creation of a highly interactive electrochromic biomimetic skin system through the integration of sensitive acoustic sensors, providing a perfect environment-responsive platform. This work provides a biomimetic multicolor electrochromic skin that depends on electron/ion transfer on nanoscale, expands potential uses for camouflage skin.

Integrative transcriptome analysis reveals the molecular events underlying impaired T-cell responses in EGFR-mutant lung cancer.

EGFR mutations are critical oncogenic drivers in lung adenocarcinoma (LUAD). However, the mechanisms by which they impact the tumor microenvironment (TME) and tumor immunity are unclear. Furthermore, the reasons underlying the poor response of EGFR-mutant (EGFR-MU) LUADs to immunotherapy with PD-1/PD-L1 inhibitors are unknown. Utilizing single-cell RNA (sc-RNA) and bulk RNA sequencing datasets, we conducted high-dimensional weighted gene coexpression network analysis to identify key genes and immune-related pathways contributing to the immunosuppressive TME. EGFR-MU cancer cells downregulated MHC class I genes to evade CD8+ cytotoxic T cells, expressed substantial levels of MHC class II molecules, and engaged with CD4+ regulatory T cells (Tregs). EGFR-MU tumors may recruit Tregs primarily through the CCL17/CCL22/CCR4 axis, leading to a Treg-enriched TME. High levels of MHC class II-positive cancer-associated fibroblasts and tumor endothelial cells were found within EGFR-MU tumors. Owing to the absence of costimulatory factors, they may inhibit rather than activate the tumor antigen-specific CD4+ T-cell response, contributing further to immune suppression. Multiplex immunohistochemistry analyses in a LUAD cohort confirmed increased expression of MHC class II molecules in cancer cells and fibroblasts in EGFR-MU tumors. Our research elucidates the highly immunosuppressive TME in EGFR-MU LUAD and suggests potential targets for effective immunotherapy.

Metal-free photoinduced generation and alkynylation of carbamoyl radicals: a facile synthesis of alkynyl amides.

A metal-free photoinduced alkynylation of carbamoyl radicals with hypervalent iodine(III) reagents for a facile synthesis of alkynyl amides is described. This protocol features good functional group tolerance and a broad substrate scope for direct synthesis of alkynyl amide derivatives in good to excellent yields under mild and redox-neutral reaction conditions. The synthetic application is demonstrated by the late-stage installation of alkynyl amides into natural products and active pharmaceutical relevant molecules. The mechanistic studies indicated the simultaneous existence of photoredox catalytic and direct photoexcited processes, and the quantum yields confirmed the occurrence of the radical chain propagation process.

Insights from Ab Initio Molecular Dynamics on the Interface Reaction between Electrolyte and Li2MnO3 Cathode during the Charging Process.

The complex interface reactions are crucial to the performance of the Li2MnO3 cathode material. Here, the interface reactions between the liquid electrolyte and the typical surfaces of Li2MnO3 during the charging process are systematically investigated by ab initio molecular dynamics (AIMD) simulation and first-principles calculation. The results indicate that these interface reactions lead to the formation of hydroxide radicals, oxygen, carbon dioxide, carbonate radicals, and other products, which are consistent with the experimental findings. These processes primarily result from the conversion of the stable closed-shell O2- into reactive oxygen ions by electron loss. All surfaces exhibit some degree of layered- and spinel-like phase transitions during the AIMD simulations, consistent with the experiment. This is mainly attributed to the decrease in the Mn-O bond strength and the increase in the Li/O ion vacancy concentration. This study offers valuable theoretical insights into the interface reaction between lithium-rich cathode materials and liquid electrolytes.

Transcriptomic analyses reveals a diverse venom composition in Agelena limbata (Araneae: Agelenaidae).

Spider venom is a natural source of diverse biomolecules, but due to technical limitations, only a small fraction has been studied. With the advancement of omics technologies, research on spider venom has broadened, greatly promoting systematic studies of spider venom. Agelena limbata is a common spider found in vegetation, known for constructing funnel-shaped webs, and feeding on insects such as Diptera and Homoptera. However, due to its small size and the difficulty in obtaining venom, the composition of Agelena limbata venom has never been studied. In this study, a transcriptomics approach was used to analyze the toxin components in the venom of Agelena limbata, resulting in the identification of 28 novel toxin-like sequences and 24 peptidases. Based on sequence similarity and differences in cysteine motifs, the 28-novel toxin-like sequences were classified into 10 superfamilies. According to the results annotated in the database, the 24 peptidases were divided into six distinct families, with the serine protease family being the most common. A phylogenetic tree was constructed using the toxin-like sequences of Agelena limbata along with Psechrus triangulus and Hippasa lycosina. An analysis of the structural domains and motifs of Agelena limbata was also conducted. The results indicated that Agelena limbata is more distantly related to the other two species of funnel-web spiders, and that the toxin superfamily IX has a unique function compared to the other superfamilies. This study reveals the components of the Agelena limbata venom, deepening our understanding of it, and through bioinformatics analysis, has identified unique functions of the toxin superfamilies, providing a scientific basis for the development of bioactive drugs in the future.

A comprehensive analysis of aroma quality and perception mechanism in ginger-infused stewed beef using instrumental analysis, sensory evaluation and molecular docking.

The ginger-infused stewed beef exhibited a satisfactory odor in Chinese cooking meat. This study aimed to reveal its aroma quality and perception mechanism through electronic nose, sensory evaluation and gas chromatography-mass spectrometry (GC-MS), gas chromatography-ion mobility spectrometry (GC-IMS) coupled with chemometric methods and molecular docking. Sensory evaluation and electronic nose analysis indicated ginger could greatly modify aroma profile of beef. Most C6-C10 aldehydes significantly decreased and terpenes increased in ginger-infused stewed beef. Orthogonal partial least squares-discriminant analysis (OPLS-DA) found 7 key markers for distinguishing stewed beef with or without ginger. Ginger additions could reduce fatty acids consumption. Moreover, the key contributors of fatty, bloody, meaty, ginger and mint aroma attributes, namely (E)-2-octenal, 1-octen-3-ol, 2-acetylthiazole, zingiberene and γ-elemene, respectively, selected by partial least squares regression (PLSR) analysis were docked with the olfactory receptor. Hydrogen bonds and hydrophobic interactions were the main interaction forces between olfactory receptor and the five compounds.

Chiral whispering gallery modes and chirality-dependent symmetric optical force induced by a spin-polarized surface wave of photonic Dirac semimetal.

Dirac degeneracy is a fourfold band crossing point in a three-dimensional momentum space, which possesses Fermi-arc-like surface states, and has extensive application prospects. In this work, we systematically study the exceptional effects of the robust chiral surface wave supported by photonic Dirac semimetal acts on the dielectric particles. Theoretical results show that orthogonal electromagnetic modes and helical or chiral whispering gallery modes (WGMs) of dielectric particles can be efficiently excited by the unidirectional spin-polarized surface wave. More importantly, optical forces exerted by the spin-polarized surface wave exhibit chirality-dependent symmetric behavior and high chiral Q factor with precise size selectivity. Our findings may provide potential applications in the area of chiral microcavity, spin optical devices, and optical manipulations.

Protein blend extrusion: Crafting meat analogues with varied textural structures and characteristics.

With an increasing emphasis on health and environmental consciousness, there is a growing inclination toward plant protein-based meat substitutes as viable alternatives to animal meat. In the pursuit of creating diverse and functional plant protein-based substitutes, innovative plant proteins have been introduced in conjunction with soy protein isolate (SPI), encompassing pea protein isolate (PPI), rice bran protein (RBP), fava bean protein isolate (FPI), and spirulina protein isolate (SPPI). Notably, SPI-WG extrudates and SPI-PPI extrudates exhibited superior fiber structures (fiber degrees were 1.72 and 1.88, respectively), with coarse fibers in SPI-WG extrudates and fine, dense fibers in SPI-PPI extrudates. The addition of RBP, FPI and SPPI had minimal effect on fiber structure. Fresh SPI-FPI displayed the slowest rate of water loss, losing about 7.11% of their total weight in 5 h. Different plant proteins can be selected for the preparation of plant protein-based meat substitutes according to practical needs.

[Identification and expression pattern analysis of Trihelix transcription factor family genes of ginseng].

The function of the Trihelix transcription factor is that it plays an important role in many abiotic stresses, especially in the signaling pathway of low temperature, drought, flood, saline, abscisic acid, methyl jasmonate, and other abiotic stresses. However, there are few studies on the Trihelix gene family of ginseng. In this study, 41 Trihelix gene family members were identified and screened from the ginseng genome database, and their physicochemical properties, cis-acting elements, subcellular localization, chromosomal assignment, and abiotic stress-induced expression patterns were analyzed by bioinformatics methods. The results showed that 85% of Trihelix family members of ginseng were located in the nucleus, and the main secondary structure of Trihelix protein was random coil and α helix. In the promoter region of Trihelix, cis-acting regulatory elements related to various abiotic stresses such as low temperature, hormone response, and growth and development were identified. Through the collinearity analysis of interspecific Trihelix transcription factors of model plants Arabidopsis thaliana and ginseng, 19 collinear gene pairs were found between A. thaliana and ginseng, and no collinear gene pairs existed on chromosomes 3, 6, and 12 only. qRT-PCR analysis showed that the expression of GWHGBEIJ010320.1 was significantly up-regulated under low temperature stress, a significant response to low temperature stress. This study lays a foundation for further research on the role of the Trihelix transcription factor of ginseng in abiotic stress, as well as the growth and development of ginseng.

Searching for the optimal precondition procedure for mesenchymal stem/stromal cell treatment: Facts and perspectives.

Mesenchymal stem/stromal cells are potential optimal cell sources for stem cell therapies, and pretreatment has proven to enhance cell vitality and function. In a recent publication, Li et al explored a new combination of pretreatment conditions. Here, we present an editorial to comment on their work and provide our view on mesenchymal stem/stromal cell precondition.

A machine learning-assisted fluorescent sensor array utilizing silver nanoclusters for coffee discrimination.

Coffee is a globally consumed commodity of substantial commercial significance. In this study, we constructed a fluorescent sensor array based on two types of polymer templated silver nanoclusters (AgNCs) for the detection of organic acids and coffees. The nanoclusters exhibited different interactions with organic acids and generated unique fluorescence response patterns. By employing principal component analysis (PCA) and random forest (RF) algorithms, the sensor array exhibited good qualitative and quantitative capabilities for organic acids. Then the sensor array was used to distinguish coffees with different processing methods or roast degrees and the recognition accuracy achieved 100%. It could also successfully identify 40 coffee samples from 12 geographical origins. Moreover, it demonstrated another satisfactory performance for the classification of pure coffee samples with their binary and ternary mixtures or other beverages. In summary, we present a novel method for detecting and identifying multiple coffees, which has considerable potential in applications such as quality control and identification of fake blended coffees.