ITPKA phosphorylates PYCR1 and promotes the progression of glioma.

Glioma is one of the prevalent malignancies, and identifying therapeutic targets for glioma is highly important. Findings of current study revealed that inositol-trisphosphate 3-kinase A (ITPKA) was found abnormally over expressed and thereby exhibited poor prognosis with glioma. Extensive academic research has meticulously elucidated ITPKA's pivotal role in enhancing glioma cell proliferation and invasion, highlighting its significance in oncogenic pathways and cellular dynamics specific to aggressive brain tumors. Inhibiting the ITPKA has wide scope to reduce the tumorigenicity in gliomas in vivo. We also noticed that ITPKA interacts with PYCR1 and phosphorylates serine 29 of PYCR1. Phosphorylation of serine 29 inhibits the E3 ligase Stub1-mediated ubiquitination of PYCR1, thereby stabilizing its protein level. Based on our findings, it was determined that the phosphorylation of serine 29 in PYCR1 by ITPKA enhances the stability of the phosphorylated PYCR1 protein. This, in turn, involved significantly in oncogenic function of ITPKA in glioblastoma. Consequently, ITPKA holds promise as a potential target in prospective glioma therapy.

Topography-guided photorefractive keratectomy combined with accelerated corneal collagen cross-linking versus cross-linking alone for progressive keratoconus: a long-term prospective cohort study.

Purpose: To comprehensively compare the long-term outcome of the combined topography guided photorefractive keratectomy (TG-PRK) with accelerated corneal cross-linking (ACXL) and ACXL alone in eyes with progressive keratoconus. The analysis focused on the changes in the detailed corneal aberrometric values. Methods: This single-center, prospective cohort study included 28 patients (30 eyes) of the TG-PRK plus ACXL group and 14 patients (15 eyes) of the ACXL alone group. The mean duration of the follow-up was 44 ± 10.18 months (ranged from 31 to 65 months). The preoperative data and the postoperative measurement data at the last follow-up visit, including demographic data, uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), manifest refraction, corneal topography, pachymetry, aberrometry and densitometry were analyzed. Results: The CDVA significantly improved in the TG-PRK plus ACXL group at the last follow-up visit (p = 0.006), while no significant improvement was found in the ACXL alone group (p = 0.432). The maximal keratometry of the anterior corneal surface (Kmax) of both groups significantly decreased at the last follow-up visit (p < 0.05). Compared with the ACXL alone group, the Kmax of the TG-PRK plus ACXL group showed a greater decline (p = 0.008). The total corneal aberrations, the corneal lower-order aberrations (LOAs), the corneal higher order aberrations (HOAs), the vertical coma and the spherical aberration (SA) at the 4.0 mm and 6.0 mm zone of the TG-PRK plus ACXL group significantly decreased at the last follow-up visit (all p < 0.05). The declines of the total corneal aberrations, the corneal LOAs, the corneal HOAs and the vertical coma at the 4.0 mm and 6.0 mm zone of the TG-PRK plus ACXL group were significantly higher than those in the ACXL alone group (p < 0.001). Conclusion: Compared with ACXL alone, combined TG-PRK with ACXL procedure had a significantly higher reduction in the corneal HOAs and better CDVA, while providing a similar long-term stability and safety. For progressive keratoconus patients with adequate corneal thickness, the combined procedure might be a recommended treatment option.

DST-DETR: Image Dehazing RT-DETR for Safety Helmet Detection in Foggy Weather.

In foggy weather, outdoor safety helmet detection often suffers from low visibility and unclear objects, hindering optimal detector performance. Moreover, safety helmets typically appear as small objects at construction sites, prone to occlusion and difficult to distinguish from complex backgrounds, further exacerbating the detection challenge. Therefore, the real-time and precise detection of safety helmet usage among construction personnel, particularly in adverse weather conditions such as foggy weather, poses a significant challenge. To address this issue, this paper proposes the DST-DETR, a framework for foggy weather safety helmet detection. The DST-DETR framework comprises a dehazing module, PAOD-Net, and an object detection module, ST-DETR, for joint dehazing and detection. Initially, foggy images are restored within PAOD-Net, enhancing the AOD-Net model by introducing a novel convolutional module, PfConv, guided by the parameter-free average attention module (PfAAM). This module enables more focused attention on crucial features in lightweight models, therefore enhancing performance. Subsequently, the MS-SSIM + ℓ2 loss function is employed to bolster the model's robustness, making it adaptable to scenes with intricate backgrounds and variable fog densities. Next, within the object detection module, the ST-DETR model is designed to address small objects. By refining the RT-DETR model, its capability to detect small objects in low-quality images is enhanced. The core of this approach lies in utilizing the variant ResNet-18 as the backbone to make the network lightweight without sacrificing accuracy, followed by effectively integrating the small-object layer into the improved BiFPN neck structure, resulting in CCFF-BiFPN-P2. Various experiments were conducted to qualitatively and quantitatively compare our method with several state-of-the-art approaches, demonstrating its superiority. The results validate that the DST-DETR algorithm is better suited for foggy safety helmet detection tasks in construction scenarios.

Genetically predicted inflammatory proteins and the risk of atrial fibrillation: a bidirectional Mendelian randomization study.

Purpose: The causal associations between inflammatory factors and atrial fibrillation (AF) remained unclear. We aimed to investigate whether genetically predicted inflammatory proteins are related to the risk of AF, and vice versa. Methods: A bidirectional two-sample Mendelian randomization study was performed. The genetic variation of 91 inflammatory proteins were derived from genome-wide association study (GWAS) data of European ancestry (n = 14,824). Summary statistics for AF were obtained from a published meta-analysis study (n = 1,030,836) and the FinnGen study (n = 261,395). Results: Genetically predicted fibroblast growth factor 5 (FGF5) was significantly positively associated with risk of AF [[odds ratio (OR): 1.07; 95% CI: 1.04-1.10; P < 0.01], and CD40l receptor was significantly negatively associated with risk of AF (OR: 0.95; 95% CI: 0.92-0.98; P = 0.02) in the meta-analysis study. In the FinnGen study, similar results were observed in FGF5 (OR: 1.11; 95% CI: 1.06-1.16; P < 0.01) and CD40l receptor (OR: 0.93; 95% CI: 0.89-0.97; P = 0.03) for AF. In the FinnGen study, TNF-beta was significantly positively associated with risk of AF (OR: 1.05; 95% CI: 1.02-1.09; P = 0.03) and leukemia inhibitory factor receptor was significantly negatively associated with risk of AF (OR: 0.86; 95% CI: 0.80-0.91; P = 0.001). The causal effect of AF on inflammatory proteins was not observed. Conclusion: Our study suggested that FGF5 and CD40l receptor have a potential causal association with AF, and targeting these factors may help in the treatment of AF.

Ultrastable and efficient slight-interlayer-displacement 2D Dion-Jacobson perovskite solar cells.

Stability has been a long-standing concern for solution-processed perovskite photovoltaics and their practical applications. However, stable perovskite materials for photovoltaic remain insufficient to date. Here we demonstrate a series of ultrastable Dion-Jacobson (DJ) perovskites (1,4-cyclohexanedimethanammonium)(methylammonium)n-1PbnI3n+1 (n ≥ 1) for photovoltaic applications. The scalable technology by blade-coated solar cells for the designed DJ perovskites (nominal n = 5) achieves a maximum stabilized power conversion efficiency (PCE) of 19.11% under an environmental atmosphere. Un-encapsulated cells by blade-coated technology retain 92% of their initial efficiencies for over 4000 hours under ~90% relative humidity (RH) aging conditions. More importantly, these cells also exhibit remarkable thermal (85 °C) and operational stability, which shows negligible efficiency loss after exceeding 5000-hour heat treatment or after operation at maximum power point (MPP) exceeding 6000 hours at 45 °C under a 100 mW cm-2 continuous light illumination.

Influence of short-term hypoxia exposure on dynamic visual acuity.

Background: To quantify the changes in dynamic visual acuity (DVA) and explain the hidden reasons after acute exposure to hypobaric hypoxia status. Methods: The study group comprised 18 healthy male and 15 healthy female participants aged 20-24 years old. DVA was measured with the self-developed software of Meidixin (Tianjin) Co., Ltd. Measurements were taken at eight altitudes. Data analysis was performed using the Kolmogorov-Smirnov test, paired sample T-test, and two-way repeated measures analysis of variance (ANOVA) for repeated measurements. Results: At constant altitude, DVA showed an overall decreasing trend with increasing angular velocity and a fluctuating decrease at the vast majority of altitudes. At constant angular velocities, DVA gradually increased with altitude, with the most pronounced increase in DVA at altitude 5, and thereafter a gradual decrease in DVA as altitude increased. Finally, as altitude decreased, DVA increased again and reached a higher level at the end of the experiment, which was superior to the DVA in the initial state. Conclusion: Under a hypobaric hypoxic environment at high altitude, DVA was affected by the angular velocity and the degree of hypoxia, manifesting as an increase or decrease in DVA, which affects the pilot's observation of the display and control interfaces during the driving process, acquisition of information, and decision-making ability, which in turn may potentially jeopardize the safety of the flight.

Fusion of Laser-Induced Breakdown Spectroscopy and Raman Spectroscopy for Mineral Identification Based on Machine Learning.

Rapid and reliable identification of mineral species is a challenging but crucial task with promising application prospects in mineralogy, metallurgy, and geology. Spectroscopic techniques such as laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy (RS) efficiently capture the elemental composition and structural information of minerals, making them a potential tool for in situ and real-time analysis of minerals. This study introduces an integrated LIBS-RS system and the fusion of LIBS and RS spectra coupled with machine learning to classify six different types of natural mineral. In order to visualize the separability of different mineral species clearly, the spectral data were projected into low-dimensional space through t-distributed stochastic neighbor embedding (t-SNE). Additionally, the Fisher score (FS) was used to identify important variables that contribute to the data classification, and the corresponding chemical elements and molecular bonds were then interpreted. The between-minerals difference in the feature spectral intensity of LIBS and RS variables could also be observed. After the minerals spectra were pre-processed, the relationship between spectral intensity and the mineral category was modeled using machine learning methods, including partial least squares-discriminant analysis (PLS-DA) and kernel extreme learning machine (K-ELM). The results show that K-ELM and PLS-DA based on the fusion LIBS-RS data achieved the highest accuracy of 98.4%. These findings demonstrate the feasibility of the integrated LIBS-RS system combined with machine learning for the fast and reliable classification of minerals.

The role of LncRNA-mediated autophagy in cancer progression.

Long non-coding RNAs (lncRNAs) are a sort of transcripts that are more than 200 nucleotides in length. In recent years, many studies have revealed the modulatory role of lncRNAs in cancer. Typically, lncRNAs are linked to a variety of essential events, such as apoptosis, cellular proliferation, and the invasion of malignant cells. Simultaneously, autophagy, an essential intracellular degradation mechanism in eukaryotic cells, is activated to respond to multiple stressful circumstances, for example, nutrient scarcity, accumulation of abnormal proteins, and organelle damage. Autophagy plays both suppressive and promoting roles in cancer. Increasingly, studies have unveiled how dysregulated lncRNAs expression can disrupt autophagic balance, thereby contributing to cancer progression. Consequently, exploring the interplay between lncRNAs and autophagy holds promising implications for clinical research. In this manuscript, we methodically compiled the advances in the molecular mechanisms of lncRNAs and autophagy and briefly summarized the implications of the lncRNA-mediated autophagy axis.

Identification of Dendrobium Using Laser-Induced Breakdown Spectroscopy in Combination with a Multivariate Algorithm Model.

Dendrobium, a highly effective traditional Chinese medicinal herb, exhibits significant variations in efficacy and price among different varieties. Therefore, achieving an efficient classification of Dendrobium is crucial. However, most of the existing identification methods for Dendrobium make it difficult to simultaneously achieve both non-destructiveness and high efficiency, making it challenging to truly meet the needs of industrial production. In this study, we combined Laser-Induced Breakdown Spectroscopy (LIBS) with multivariate models to classify 10 varieties of Dendrobium. LIBS spectral data for each Dendrobium variety were collected from three circular medicinal blocks. During the data analysis phase, multivariate models to classify different Dendrobium varieties first preprocess the LIBS spectral data using Gaussian filtering and stacked correlation coefficient feature selection. Subsequently, the constructed fusion model is utilized for classification. The results demonstrate that the classification accuracy of 10 Dendrobium varieties reached 100%. Compared to Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN), our method improved classification accuracy by 14%, 20%, and 20%, respectively. Additionally, it outperforms three models (SVM, RF, and KNN) with added Principal Component Analysis (PCA) by 10%, 10%, and 17%. This fully validates the excellent performance of our classification method. Finally, visualization analysis of the entire research process based on t-distributed Stochastic Neighbor Embedding (t-SNE) technology further enhances the interpretability of the model. This study, by combining LIBS and machine learning technologies, achieves efficient classification of Dendrobium, providing a feasible solution for the identification of Dendrobium and even traditional Chinese medicinal herbs.

Baicalin inhibits monosodium urate crystal-induced pyroptosis in renal tubular epithelial cell line through Panx-1/P2X7 pathways: Molecular docking, molecular dynamics, and in vitro experiments.

Pyroptosis is a programmed cell death process that frequently occurs in many diseases, including hyperuricemic nephropathy (HN). In HN, a range of stimuli mediates inflammation, leading to the activation of inflammasomes and the production of gasdermin D (GSDMD). Baicalin (BA), a natural flavonoid renowned for its antioxidant and anti-inflammatory properties, was investigated for its role in HN in this study. Initially, HN-like inflammation and pyroptosis were induced in HK-2 cells with treatment of monosodium urate (MSU), followed by the BA treatment. The expression of pyroptosis-associated genes, Panx-1 and P2X7, at both mRNA and protein levels was assessed through real-time polymerase chain reaction (RT-qPCR) and Western blotting (WB) without or with BA treatment. The results showed that expression of Panx-1 and P2X7 at mRNA and protein levels was increased in MSU-treated HK-2 cells, which subsequently decreased upon the BA treatment. Further experiments showed that BA could combine NLRP3 inflammasome and GSDMD, destabilizing GSDMD protein. Moreover, BA protected the cell membrane from MSU-induced damage, as evidenced by Hoechst 33342 and PI double staining, lactate dehydrogenase (LDH) assays, and electron microscopy observations. These results suggest that BA is involved in the regulating Panx-1/P2X7 pathways and thus inhibits pyroptosis, highlighting its potential therapeutic effect for HN.

Identification of TAP1 as a T-cell related therapeutic target in gastric cancer by mediating oxalipliatin-related synergistic enhancement of immunotherapy.

BACKGROUND: Given the intricate molecular complexities and heterogeneity inherent in T-cell immunotherapy of gastric cancer (GC), elucidative T-cell-related biomarkers were imperative needed for facilitating the prediction of GC patient prognosis and identify potential synergistic therapeutic targets. METHODS: We conducted COX regression analysis in TISIDB, TCGA-STAD, and GEO databases to identify 19 GC T-cell-mediated sensitivity tumor killing (TTK) genes (key GCTTKs). Based on key GCTTKs, we constructed two TTK patterns and analyzed their metabolic pathways, mutation features, clinical data distribution, immune cell infiltration, and prognosis. LASSO regression was performed to develop a T-cell-mediated GC Prognosis (TGCP) model. We validated the TGCP model in GC patients. TAP1 was further selected for investigation of its biological functions and molecular mechanisms. We assessed the potential of TAP1 as a promising therapeutic target for GC using Patient-derived organoids (PDOs)-derived xenografts (PDOXs) models of GC. RESULTS: The TTK patterns display notable disparities. The TGCP model showcases its proficiency in predicting immune response efficacy, effectively distinguishes immunotherapy difference GC patients. Our findings find further confirmation in PDOX models, affirming TAP1 can enhance immunotherapy facilitated by PDL1 inhibitors. Furthermore, Oxaliplatin, by promoting TAP1 expression, augments PDL1 expression, thereby enhancing the efficacy of immunotherapy. CONCLUSIONS: We constructed a TGCP model, which demonstrates satisfactory predictive accuracy. Out of 9 prognostic genes, TAP1 was validated as a synergistic target for Oxaliplatin and PDL1 inhibitors, offering a genetic-level explanation for the synergy observed in GC treatment involving Oxaliplatin in combination with PDL1 inhibitors.

Therapeutic efficacy of a novel self-assembled immunostimulatory siRNA combining apoptosis promotion with RIG-I activation in gliomas.

BACKGROUND: Current cancer therapies often fall short in addressing the complexities of malignancies, underscoring the urgent need for innovative treatment strategies. RNA interference technology, which specifically suppresses gene expression, offers a promising new approach in the fight against tumors. Recent studies have identified a novel immunostimulatory small-interfering RNA (siRNA) with a unique sequence (sense strand, 5'-C; antisense strand, 3'-GGG) capable of activating the RIG-I/IRF3 signaling pathway. This activation induces the release of type I and III interferons, leading to an effective antiviral immune response. However, this class of immunostimulatory siRNA has not yet been explored in cancer therapy. METHODS: IsiBCL-2, an innovative immunostimulatory siRNA designed to suppress the levels of B-cell lymphoma 2 (BCL-2), contains a distinctive motif (sense strand, 5'-C; antisense strand, 3'-GGG). Glioblastoma cells were subjected to 100 nM isiBCL-2 treatment in vitro for 48 h. Morphological changes, cell viability (CCK-8 assay), proliferation (colony formation assay), migration/invasion (scratch test and Transwell assay), apoptosis rate, reactive oxygen species (ROS), and mitochondrial membrane potential (MMP) were evaluated. Western blotting and immunofluorescence analyses were performed to assess RIG-I and MHC-I molecule levels, and ELISA was utilized to measure the levels of cytokines (IFN-ß and CXCL10). In vivo heterogeneous tumor models were established, and the anti-tumor effect of isiBCL-2 was confirmed through intratumoral injection. RESULTS: IsiBCL-2 exhibited significant inhibitory effects on glioblastoma cell growth and induced apoptosis. BCL-2 mRNA levels were significantly decreased by 67.52%. IsiBCL-2 treatment resulted in an apoptotic rate of approximately 51.96%, accompanied by a 71.76% reduction in MMP and a 41.87% increase in ROS accumulation. Western blotting and immunofluorescence analyses demonstrated increased levels of RIG-I, MAVS, and MHC-I following isiBCL-2 treatment. ELISA tests indicated a significant increase in IFN-ß and CXCL10 levels. In vivo studies using nude mice confirmed that isiBCL-2 effectively impeded the growth and progression of glioblastoma tumors. CONCLUSIONS: This study introduces an innovative method to induce innate signaling by incorporating an immunostimulatory sequence (sense strand, 5'-C; antisense strand, 3'-GGG) into siRNA, resulting in the formation of RNA dimers through Hoogsteen base-pairing. This activation triggers the RIG-I signaling pathway in tumor cells, causing further damage and inducing a potent immune response. This inventive design and application of immunostimulatory siRNA offer a novel perspective on tumor immunotherapy, holding significant implications for the field.

H3K18 lactylation-mediated VCAM1 expression promotes gastric cancer progression and metastasis via AKT-mTOR-CXCL1 axis.

The role of the Immunoglobulin Superfamily (IgSF) as adhesion molecules in orchestrating inflammation is pivotal, yet its specific involvement in gastric cancer (GC) remains unknown. We analyzed IgSF components and discerned conspicuously elevated VCAM1 expression in GC, correlating with a poor prognosis. Remarkably, VCAM1 enhances GC cell proliferation and migration by activating AKT-mTOR signaling. Moreover, lactate in the tumor microenvironment (TME) promotes dynamic lactylation of H3K18 (H3K18la), leading to transcriptional activation of VCAM1 in GC cells. Furthermore, VCAM1 actively mediates intercellular communication in the TME. AKT-mTOR-mediated CXCL1 expression is increased by VCAM1, facilitating the recruitment of human GC-derived mesenchymal stem cells (hGC-MSCs), thereby fostering immunesuppression and accelerating cancer progression. In summary, H3K18 lactylation upregulated VCAM1 transcription, which activated AKT-mTOR signaling, and promoted tumor cell proliferation, EMT Transition and tumor metastasis. VCAM1 upregulated CXCL1 expression by AKT-mTOR pathway, so as to facilitate hGC-MSCs and M2 macrophage recruitment and infiltration. These findings provide novel therapeutic targets for GC.

Investigation on Gold Dissolution Performance and Mechanism in Imidazolium Cyanate Ionic Liquids.

To explore green gold leaching reagents, a series of imidazolium cyanate ionic liquids (ILs), 1-ethyl-3-methyl-imidazolium cyanate ([C2MIM][OCN]), 1-propyl-3-methyl-imidazolium cyanate ([C3MIM][OCN]) and 1-butyl-3-methyl-imidazolcyanate ([C4MIM][OCN]) were synthesized and characterized by Nuclear Magnetic Resonance (NMR), Fourier Transform Infrared Spectroscopy (FTIR) and thermogravimetric (TG) analysis. In this research, the imidazolium cyanates were utilized as a solute, which not only decreased the usage of ILs but also increased their gold dissolution capability. The gold dissolution performances of three imidazolium cyanates were characterized by dynamic leaching test and Scanning Electron Microscopy (SEM). The results show that the all three imidazolium cyanates had a gold dissolution ability, and the shorter the carbon chain on the imidazole ring in imidazolium cyanate, the faster the gold dissolution rate. The gold dissolution performance of [C2MIM][OCN] was the best, and the weight loss of gold leaf was 2.9 mg/cm2 at 40 °C after 120 h dissolution in [C2MIM][OCN] mixed with 10 wt. % water. Besides this, the gold dissolution rate increased with the increase in the concentration of imidazolium cyanates as well as the reaction temperature. The gold dissolution performances of imidazolium cyanates in different solvents including water, acetonitrile, dimethyl sulfoxide (DMSO) and dimethylformamide (DMF) were also investigated, and the weaker the polarity of the solvent, the more conducive it was to the gold dissolution reaction. The mechanism of gold dissolution by imidazolium cyanates was investigated through NMR spectroscopy and Electrospray Ionization Mass Spectrometry (ESI-MS). It was inferred that during the process of gold dissolution, Au was oxidized to Au+ and the imidazolium cations were deprotonated to form N-heterocyclic carbenes, which coordinated with gold to form gold complexes and achieve gold dissolution.

Multielement simultaneous quantitative analysis of trace elements in stainless steel via full spectrum laser-induced breakdown spectroscopy.

Laser-Induced Breakdown Spectroscopy (LIBS) instruments are increasingly recognized as valuable tools for detecting trace metal elements due to their simplicity, rapid detection, and ability to perform simultaneous multi-element analysis. Traditional LIBS modeling often relies on empirical or machine learning-based feature band selection to establish quantitative models. In this study, we introduce a novel approach-simultaneous multi-element quantitative analysis based on the entire spectrum, which enhances model establishment efficiency and leverages the advantages of LIBS. By logarithmically processing the spectra and quantifying the cognitive uncertainty of the model, we achieved remarkable predictive performance (R2) for trace elements Mn, Mo, Cr, and Cu (0.9876, 0.9879, 0.9891, and 0.9841, respectively) in stainless steel. Our multi-element model shares features and parameters during the learning process, effectively mitigating the impact of matrix effects and self-absorption. Additionally, we introduce a cognitive error term to quantify the cognitive uncertainty of the model. The results suggest that our approach has significant potential in the quantitative analysis of trace elements, providing a reliable data processing method for efficient and accurate multi-task analysis in LIBS. This methodology holds promising applications in the field of LIBS quantitative analysis.

Small-sample stacking model for qualitative analysis of aluminum alloys based on femtosecond laser-induced breakdown spectroscopy.

Material characterization using laser-induced breakdown spectroscopy (LIBS) often relies on extensive data for effective analysis. However, data acquisition can be challenging, and the high dimensionality of raw spectral data combined with a large-scale sample dataset can strain computational resources. In this study, we propose a small sample size stacking model based on femtosecond LIBS to achieve accurate qualitative analysis of aluminum alloys. The proposed three-layer stacking algorithm performs data reconstruction and feature extraction to enhance the analysis. In the first layer, random forest spectral feature selection and specific spectral line spreading are employed to reconstruct the data. The second layer utilizes three heterogeneous classifiers to extract features from the reconstructed spectra in different feature spaces, generating second-level reconstructed data. Finally, the third layer utilizes the reconstructed dataset for qualitative prediction. Results indicate that the Stacking algorithm outperforms traditional methods such as k-nearest neighbors (KNN), support vector machine (SVM), and random forest (RF), including those combined with principal component analysis (PCA). The Stacking algorithm achieves an impressive 100% recognition rate in classification, with Accuracy, precision, recall, and F1 scores reaching 1.0. Moreover, as the number of samples decreases, the gap between the recognition accuracy of the Stacking algorithm and traditional approaches widens. For instance, using only 15 spectra for training, the Stacking algorithm achieves a recognition accuracy of 96.47%, significantly surpassing the improved RF's accuracy of 71.76%. Notably, the model demonstrates strong robustness compared to traditional modeling approaches, and the qualitative prediction error remains consistently below 5%. These findings underscore the model's enhanced generalization ability and higher prediction accuracy in small sample machine learning. This research contributes significantly to improving the applicability of the LIBS technique for fast detection and analysis of small samples. It provides valuable insights into the development of effective methodologies for material characterization, paving the way for advancements in the field.

Puckered Zigzag Monolayer Ice: Does a Confined Flat Four-Coordinated Monolayer Ice Always Have a Corresponding Puckered Phase?

We note that a flat, four-coordinated monolayer ice under confinement always has a corresponding puckered phase. Recently, a monolayer ice consisting of an array of zigzag water chains (ZZMI) predicted by first-principles calculations of water under confinement is a flat four-coordinated monolayer ice. Herein, to investigate whether puckered ZZMI exists stably, we perform molecular dynamics simulations of two-dimensional (2D) ice formation for water constrained in graphene nanocapillaries. We find a novel monolayer ice structure that can be viewed as the ZZMI puckered along the direction perpendicular to the zigzag chain (pZZMI). Unlike ZZMI that does not satisfy the ice rule, each water molecule in pZZMI can form four hydrogen bonds (HBs) via forming two stable intersublayer HBs and two intrasublayer HBs. This work provides a fresh perspective on 2D confined ice, highlighting the intrinsic connections between 2D confined ices.

The major influence of anterior and equatorial zonular fibres on the far-to-near accommodation revealed by a 3D pre-stressed model of the anterior eye.

PURPOSE: To explore the synergistic function of the ligaments in eye, the zonular fibres, that mediate change in eye lens shape to allow for focussing over different distances. METHODS: A set of 3D Finite Element models of the anterior eye together with a custom developed pre-stress modelling approach was proposed to simulate vision for distant objects (the unaccommodated state) to vision for near objects (accommodation). One of the five zonular groups was cut off in sequence creating five models with different zonular arrangements, the contribution of each zonular group was analysed by comparing results of each specific zonular-cut model with those from the all-zonules model in terms of lens shape and zonular tensions. RESULTS: In the all-zonular model, the anterior and equatorial zonules carry the highest tensions. In the anterior zonular-cut model, the equatorial zonular tension increases while the posterior zonular tension decreases, resulting in an increase in the change in Central Optical Power (COP). In the equatorial zonular-cut model, both the anterior and posterior zonular tensions increase, causing a decreasing change in COP. The change in COP decreases only slightly in the other models. For vitreous zonular-cut models, little change was seen in either the zonular tension or the change in COP. CONCLUSIONS: The anterior and the equatorial zonular fibres have the major influence on the change in lens optical power, with the anterior zonules having a negative effect and the equatorial zonules contributing a positive effect. The contribution to variations in optical power by the equatorial zonules is much larger than by the posterior zonules.

Long-Term Efficacy of Orthokeratology to Control Myopia Progression.

OBJECTIVES: To assess the efficacy of orthokeratology in controlling the rate of myopia progression in children and investigate the factors associated with axial length (AL) growth rate with an average of 48 months of orthokeratology lens wear. METHODS: As a retrospective study, 84 subjects underwent relatively complete ophthalmologic examinations. After initial lens wear, AL was measured on average every 12 months. The linear mixed-effects model (LMM) was used to compare the differences in AL growth rates at each time interval. The contribution of the independent variables to AL change was assessed using multiple linear regression. RESULTS: In the LMM, there was a significant difference in the AL growth rate ( P <0.001) at each follow-up. The growth rate of AL was associated with initial AL, spherical equivalent refractive errors (SERs) and diameter of lens ( P =0.045, 0.003 and 0.037, respectively). When the baseline age was included as a factor, the influence of initial AL and SER became insignificant in the analysis, whereas age and diameter of lens were significantly correlated with the growth rate of AL ( P< 0.001 and P< 0.001, respectively). There were significant differences in growth rates among different age groups. CONCLUSIONS: Results of the study demonstrated that the factors associated with lower growth rate in AL were older age and longer diameter of lens.