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Abstract We aimed to build a deep learning-based pathomics model to predict the early recurrence of non-muscle-infiltrating bladder cancer (NMIBC) in this work. A total of 147 patients from Xuzhou Central Hospital were enrolled as the training cohort, and 63 patients from Suqian Affiliated Hospital of Xuzhou Medical University were enrolled as the test cohort. Based on two consecutive phases of patch level prediction and WSI-level predictione, we built a pathomics model, with the initial model developed in the training cohort and subjected to transfer learning, and then the test cohort was validated for generalization. The features extracted from the visualization model were used for model interpretation. After migration learning, the area under the receiver operating characteristic curve for the deep learning-based pathomics model in the test cohort was 0.860 (95% CI 0.752–0.969), with good agreement between the migration training cohort and the test cohort in predicting recurrence, and the predicted values matched well with the observed values, with p values of 0.667766 and 0.140233 for the Hosmer–Lemeshow test, respectively. The good clinical application was observed using a decision curve analysis method. We developed a deep learning-based pathomics model showed promising performance in predicting recurrence within one year in NMIBC patients. Including 10 state prediction NMIBC recurrence group pathology features be visualized, which may be used to facilitate personalized management of NMIBC patients to avoid ineffective or unnecessary treatment for the benefit of patients.

In this paper, we study the expansion of Noble-Abel gas into a vacuum around the convex corner of the two-dimensional compressible magnetohydrodynamic system. We reduce this problem to the interaction of a centered simple wave emanating from the convex corner with a backward planar simple wave. Mathematically, this is a Goursat problem. By using the method of characteristic decomposition and construction of invariant regions, combining $ C^{0} $ and $ C^{1} $ estimation as well as hyperbolicity estimation, we obtain the existence of a global classical solution by extending the local classical solution.

Abstract Acinetobacter baumannii is a gram-negative bacillus prevalent in nature, capable of thriving under various environmental conditions. As an opportunistic pathogen, it frequently causes nosocomial infections such as urinary tract infections, bacteremia, and pneumonia, contributing to increased morbidity and mortality in clinical settings. Consequently, developing novel vaccines against Acinetobacter baumannii is of utmost importance. In our study, we identified 10 highly conserved antigenic proteins from the NCBI and UniProt databases for epitope mapping. We subsequently screened and selected 8 CTL, HTL, and LBL epitopes, integrating them into three distinct vaccines constructed with adjuvants. Following comprehensive evaluations of immunological and physicochemical parameters, we conducted molecular docking and molecular dynamics simulations to assess the efficacy and stability of these vaccines. Our findings indicate that all three multi-epitope mRNA vaccines designed against Acinetobacter baumannii are promising; however, further animal studies are required to confirm their reliability and effectiveness.

Abstract Dual inhibition of vascular endothelial growth factor and epidermal growth factor receptor (EGFR) signaling pathways offers the prospect of improving the effectiveness of EFGR-targeted therapy. In this phase 3 study (ClinicalTrial.gov: NCT04028778), 315 patients with treatment-naïve, EGFR-mutated, advanced non-small cell lung cancer (NSCLC) were randomized (1:1) to receive anlotinib or placebo plus gefitinib once daily on days 1–14 per a 3-week cycle. At the prespecified final analysis of progression-free survival (PFS), a significant improvement in PFS was observed for the anlotinib arm over the placebo arm (hazards ratio [HR] = 0.64, 95% CI, 0.48–0.80, P = 0.003). Particularly, patients with brain metastasis and those harboring EGFR amplification or high tumor mutation load gained significant more benefits in PFS from gefitinib plus anlotinib. The incidence of grade 3 or higher treatment-emergent adverse events was 49.7% of the patients receiving gefitinib plus anlotinib versus 31.0% of the patients receiving gefitinib plus placebo. Anlotinib plus gefitinib significantly improves PFS in patients with treatment-naïve, EGFR-mutated, advanced NSCLC, with a manageable safety profile.

Abstract Background Uterine corpus endometrial carcinoma (UCEC) is a prevalent gynecologic malignancy with a favorable prognosis if detected early. However, there is a lack of accurate and reliable early detection tests for UCEC. This study aims to develop a precise and non-invasive diagnostic method for UCEC using circulating cell-free DNA (cfDNA) fragmentomics. Methods Peripheral blood samples were collected from all participants, and cfDNA was extracted for analysis. Low-coverage whole-genome sequencing was performed to obtain cfDNA fragmentomics data. A robust machine learning model was developed using these features to differentiate between UCEC and healthy conditions. Results The cfDNA fragmentomics-based model showed high predictive power for UCEC detection in training (n = 133; AUC 0.991) and validation cohorts (n = 89; AUC 0.994). The model manifested a specificity of 95.5% and a sensitivity of 98.5% in the training cohort, and a specificity of 95.5% and a sensitivity of 97.8% in the validation cohort. Physiological variables and preanalytical procedures had no significant impact on the classifier’s outcomes. In terms of clinical benefit, our model would identify 99% of Chinese UCEC patients at stage I, compared to 21% under standard care, potentially raising the 5-year survival rate from 84 to 95%. Conclusion This study presents a novel approach for the early detection of UCEC using cfDNA fragmentomics and machine learning showing promising sensitivity and specificity. Using this model in clinical practice could significantly improve UCEC management and control, enabling early intervention and better patient outcomes. Further optimization and validation of this approach are warranted to establish its clinical utility.

Abstract Previous studies that focused on univariate correlations between neuroanatomy and cognition in schizophrenia identified some inconsistent findings. Moreover, antipsychotic medication may impact the brain-behavior profiles in affected individuals. It remains unclear whether unmedicated and medicated individuals with schizophrenia would share common neuroanatomy-cognition associations. Therefore, we aimed to investigate multivariate neuroanatomy-cognition relationships in both groups. A sample of 59 drug-naïve individuals with first-episode schizophrenia (FES) and a sample of 115 antipsychotic-treated individuals with schizophrenia were finally included. Multivariate modeling was conducted in the two patient samples between multiple cognitive domains and neuroanatomic features, such as cortical thickness (CT), cortical surface area (CSA), and subcortical volume (SV). We observed distinct multivariate correlational patterns between the two samples of individuals with schizophrenia. In the FES sample, better performance in token motor, symbol coding, and verbal fluency tests was associated with greater thalamic volumes but lower CT in the prefrontal and anterior cingulate cortices. Two significant multivariate correlations were identified in antipsychotic-treated individuals: 1) worse verbal memory performance was related to smaller volumes for the most subcortical structures and smaller CSA mainly in the temporal regions and inferior parietal lobule; 2) a lower symbol coding test score was correlated with smaller CSA in the right parahippocampal gyrus but greater volume in the right caudate. These multivariate patterns were sample-specific and not confounded by imaging quality, illness duration, antipsychotic dose, or psychopathological symptoms. Our findings may help to understand the neurobiological basis of cognitive impairments and the development of cognition-targeted interventions.

The chemoselective probe technique combines the benefits of chemical derivatization and solid-phase extraction, allowing for simultaneous enhancement of analyte ionization efficiency, reduction of matrix interference, and improvement in chromatographic separation. This innovative technique holds great promise for applications in metabolomics research, metabolic tracking, and natural product isolation and purification. This review provides a comprehensive overview of the advancements in chemoselective probes from 2007 to 2024, focusing on the progress in probe design, particularly cleavable linkers. Additionally, it discusses the application of chemoselective probes in LC-MS analysis of small-molecular-weight compounds.

ABSTRACT The interactions between hosts and the gut microbiota are intricate and can significantly affect the ecology and evolution of both parties. Various host traits, including taxonomy, diet, social behaviour, and external factors such as prey availability and the local environment, all play an important role in shaping composition and diversity of the gut microbiogta. In this study, we explored the impact of intestinal microorganisms on the host in adapting to their respective ecological niches in two species of snakes. We collected feces from Lycodon rufozonatus and Lycodon rosozonatus from different geographical locations and used 16S rRNA gene sequencing technology to sequence the v3‐v4 region. The results revealed that there was no significant difference in the alpha diversity of intestinal microorganisms between L. rufozonatus and L. rosozonatus. The gut microbiota of all individuals comprised four main phyla: Pseudomonadota, Bacteroidota, Bacillota, and Actinomycetota. At the genus level, the genus Salmonella dominated the enterobacterial microbiota in the samples from Hainan, while there was no obvious dominant genus in the enterobacterial microbiota of the samples from the other four localities. Comparative analysis of enzyme families annotated to the gut microbiota between L. rufozonatus and L. rosozonatus from the four sampling regions by CAZy carbohydrate annotation revealed that nine enzyme families differed significantly in terms of glycoside hydrolases (GHs). In addition, we compared the composition of gut microbial communities between L. rufozonatus and L. rosozonatus and investigated the impact of the differences on their functions. Our results will provide insights into the coevolution of host and gut microbes.

BackgroundAlectinib has demonstrated promising disease-free survival (DFS) benefit for early-stage non-small cell lung cancer (NSCLC) patients with ALK rearrangement positive in phase 3 ALINA trial. However, real-world evidence for the efficacy and safety of alectinib in early-stage ALK-positive NSCLC is limited.Materials and methodsWe retrospectively reviewed 68 patients with stage IB-IIIB ALK-positive NSCLC who underwent complete pulmonary resections from April 2010 to July 2023 at a single institution. 38 (55.9%) enrolled patients had N2 lymph node metastasis, and 17 (24.9%) patients had multi-station N2 metastasis. Patients were stratified into two groups according to the adjuvant treatment regimen, with 19 patients in the alectinib group and 49 patients in the chemotherapy group. There were no significant differences in clinicopathological characteristics between the two groups. After curative resection surgery, patients in alectinib group received oral alectinib at a dose of 600 mg twice daily and patients in chemotherapy group received platinum-based doublet chemotherapy regimen every 3 weeks for 4 cycles. The primary endpoint was 3-year DFS. The Kaplan-Meier method was used to estimate DFS and overall survival (OS). Safety analyses were conducted by comparing the incidence of adverse events between the two groups.ResultsAt the last follow-up date (January 22th, 2024), A total of 1 (5.3%) and 28 (57.1%) DFS events were observed in alectinib group and chemotherapy group respectively. The 3-year DFS showed significant improvement in the alectinib group compared with chemotherapy group (91.7% vs 60.7%, P=0.051). In the IIIAN2 subgroup, the 3-year DFS rate in the alectinib group reached a satisfactory 87.5%. In both groups, the majority of AEs were graded as level 1 or 2, No grade 3-4 AEs were observed in alectinib group.ConclusionAlectinib, as adjuvant therapy, demonstrated favorable efficacy and manageable safety in patients with completely resected ALK-positive stage I B-IIIB non-small cell lung cancer. A limitation of this study is the small sample size, and a larger-scale real-world sample study is needed to further evaluate the efficacy and safety of alectinib as adjuvant therapy.

The family Nemouridae, belonging to Plecoptera, comprises 21 genera and over 700 species found globally, with the greatest diversity observed in temperate regions. Nemoura Latreille, 1796 and Amphinemura Ris, 1902 are two largest genera of the family with the highest diversity in China.Two new species of Nemoura Latreille, 1796 of the family Nemouridae, Nemoura exterclava Zhu, Rehman & Du sp. nov. and Nemoura cerciserrata Zhu, Du & Rehman sp. nov., are described and illustrated from the Nanling Mountains Region in Guangdong Province, southern China. The morphological characteristics of the new species are compared with related taxa. Additionally, the status of Indonemoura voluta Li & Yang, 2008, originally from Maoershan National Natural Reserve in Guangxi Zhuang Autonomous Region, was addressed and moved to the genus Amphinemura Ris, 1902 on the basis of newly-caught topotypes.

Background Targeting kinases presents a potential strategy for treating solid tumors; however, the therapeutic potential of vaccines targeting kinases remains uncertain.Methods Adenovirus (Ad) vaccines encoding Aurora kinase A (AURKA) or cyclin-dependent kinase 7 (CDK7) were developed, and their therapeutic potentials were investigated by various methods including western blot, flow cytometry, cytotoxic T lymphocyte assay, and enzyme-linked immunospot (ELISpot), in mouse and humanized solid tumor models.Results Co-immunization with Ad-AURKA/CDK7 effectively prevented subcutaneous tumor growth in the Renca, RM-1, MC38, and Hepa1-6 tumor models. In therapeutic tumor models, Ad-AURKA/CDK7 treatment impeded tumor growth and increased immune cell infiltration. Administration of Ad-AURKA/CDK7 promoted the induction and maturation of dendritic cell subsets and augmented multifunctional CD8+ T-cell antitumor immunity. Furthermore, the vaccine induced a long-lasting antitumor effect by promoting the generation of memory CD8+ T cells. Tumor recovery on CD8+ T-cell depletion underscored the indispensable role of these cells in the observed therapeutic effects. The potent efficacy of the Ad-AURKA/CDK7 vaccine was consistently demonstrated in lung metastasis, orthotopic, and humanized tumor models by inducing multifunctional CD8+ T-cell antitumor immune responses.Conclusions Our findings illustrate that the Ad-AURKA/CDK7 vaccine targeting dual kinases AURKA and CDK7 emerges as a promising and effective therapeutic approach for the treatment of solid tumors.

Purpose The aim of this study was to identify factors associated with difficult video laryngoscopy in obese patients. Methods A total of 579 obese patients undergoing elective laparoscopic weight loss surgery were intubated with a single-lumen endotracheal tube using a video laryngoscopy under general anesthesia, and the patients were divided into two groups based on the Cormack-Lehane classification (difficult video laryngoscopy defined as ≥ 3): the easy video laryngoscopy group and the difficult video laryngoscopy group. Record the general condition of the patient, bedside testing indicators related to the airway, Cormack-Lehane classification during intubation, and intubation failure rate. Results The findings of this study show that the incidence of difficult video laryngoscopy in obese patients is 4.8%. Multivariate logistic regression analysis indicated that body mass index was significantly associated with difficult video laryngoscopy (OR = 1.082, 95% CI [1.033–1.132], P

Galectins (Gals) are a type of S-type lectin that are widespread and evolutionarily conserved among metazoans, and can act as pattern recognition receptors (PRRs) to recognize pathogen-associated molecular patterns (PAMPs). In this study, 10 Gals (ToGals) were identified in the Golden pompano (Trachinotus ovatus), and their conserved domains, motifs, and collinearity relationships were analyzed. The expression of ToGals was regulated following infection to Cryptocaryon irritans and Streptococcus agalactiae, indicating that ToGals participate in immune responses against microbial pathogens. Further analysis was conducted on one important member, Galectin-3, subcellular localization showing that ToGal-3like protein is expressed both in the nucleus and cytoplasm. Recombinant protein obtained through prokaryotic expression showed that rToGal-3like can agglutinate red blood cells of rabbit, carp and golden pompano and also agglutinate and kill Staphylococcus aureus, Bacillus subtilis, Vibrio vulnificus, S. agalactiae, Pseudomonas aeruginosa, and Aeromonas hydrophila. This study lays the foundation for further research on the immune roles of Gals in teleosts.

The pre-stressed flexible cable-supported photovoltaic (PV) systems (FCSPSs) are gradually becoming the preferred PV structure for large-span and mountain photovoltaic power plants. The wind-induced response of FCSPSs under negative wind conditions is more pronounced than under positive wind conditions. In this study, a series of two-way fluid-structure interaction (FSI) coupling numerical simulations are conducted to investigate the effect of ground anchors on the wind-induced vibration response of FCSPSs. Firstly, an analysis approach for wind-induced vibration coefficients of FCSPSs is established, involving model equivalency, coefficient definitions, model creation, and grid and solution settings. Secondly, modal analysis is performed on FCSPSs by varying the stiffness ratio (SR) of the ground anchor. Subsequently, changes in support reaction, ground anchor tension, translational displacement, and rotational displacement, as well as the wind field variation in the fluid domain under wind load, are evaluated for SR values ranging from 0 to 5. Finally, a quantitative evaluation of the wind-induced vibration coefficient in the FCSPS is conducted for different SR values. The results indicate that the configuration of ground anchor cables significantly mitigates the support reaction and displacement response of the FCSPS under negative wind conditions. Moreover, the stiffness ratio of the ground anchor has a relatively minor impact on wind-induced vibration coefficients (reaction force, displacement).

Abstract Extreme glacier melt has important implications for climate change studies and glacier‐related hazards. Few attempts have been made to study the characteristics and mechanisms of extreme melt on the Tibetan Plateau (TP) and surroundings, one of the largest concentrations of glaciers beyond the polar regions. To address this gap, we investigated the magnitude and possible drivers of anomalous early spring glacier melt in 2022 on the central TP using multi‐source observations (October 2020–July 2022) of Kuoqionggangri and Sangqu glaciers and an energy and mass balance model. Our results show that anomalous melt of both glaciers occurred in early spring (18 March–10 April 2022), when glaciers are traditionally expected to be frozen. There were 89 cumulative hours with air temperatures above 0°C, with a positive cumulative air temperature of 121.80°C hour at 5,700 m on Kuoqionggangri Glacier. The glacier‐wide cumulative melts on Kuoqionggangri and Sangqu glaciers from 18 March to 10 April 2022 were 22 ± 14.2 and 48 ± 37.5 mm w.e., respectively. Such anomalous glacier melt was driven by high incoming shortwave radiation and sensible heat flux, which were influenced by low cloud fraction and precipitation, and high air temperature during early spring. The weakening and northward‐shift of the westerlies, coupled with descending air motions over the central TP, reduced cloud fraction and hindered the transport of cold, moist air to the central TP. These changes occurred both in the central TP and the Himalaya, indicating the influence of macroscale atmospheric circulation patterns on this extreme glacier melt.

Research on soil contamination has become increasingly important, but there is limited information about where to sample for pollutants. Thus, the use of three-dimensional (3D) spatial interpolation techniques has been promoted in this area of study. However, the application of traditional interpolation methods is limited in geography, especially in the expression of anisotropy, and it is not associated with geographical properties. To address this issue, we used a test site (a factory in Nanjing) to develop a new research method based on the geographical shading radial basis function (RBF) interpolation method, which considers 3D anisotropy and geographical attribute expression. Drilling and uniform sampling were used to sample the contaminated area at this test site. This approach included two steps: i) An ellipsoid with anisotropic properties was constructed. Thus, the first step was to determine the shape of the ellipsoid using principal component analysis (PCA) to determine the main orientations and construct a rotational and stretched matrix. The second step was determining the ellipsoid size by computing the range using the variogram method for orientations. ii) During field measurement, the geospatial direction influences soil attribute values, so a shadowing calculation method was derived for quadratic weight determination. Then, the weight of the attribute value of known points can be assigned to meet the field conditions. Lastly, the model was evaluated using the root mean square error (RMSE). For the 2D space, the RMSE values of Kriging, RBF, and the proposed method are 6.09, 7.12, and 5.02, respectively. The R2 values of Kriging, RBF, and the proposed method are 0.871, 0.832, and 0.946, respectively. For the 3D space, the RMSE values of Kriging, RBF, and the proposed method are 2.65, 2.23, and 2.58, respectively. The R2 values of Kriging, RBF, and the proposed method are 0.934, 0.912, and 0.953, respectively. The resulting fitted model was relatively smooth and met experimental needs. Thus, we believe that the interpolation method can be applied as a new method to predict the distribution of soil pollutants.

Abstract Background Indotyphlops braminus, the only known triploid parthenogenetic snake, is a compelling species for revealing the mechanism of polyploid emergence in vertebrates. Methods In this study, we applied PacBio isoform sequencing technology to generate the first full-length transcriptome of I. braminus, aiming to improve the understanding of the molecular characteristics of this species. Results A total of 51,849 nonredundant full-length transcript assemblies (with an N50 length of 2980 bp) from I. braminus were generated and fully annotated using various gene function databases. Our analysis provides preliminary evidence supporting a recent genome duplication event in I. braminus. Phylogenetic analysis indicated that the divergence of I. braminus subgenomes occurred approximately 11.5 ~ 15 million years ago (Mya). The full-length transcript resource generated as part of this research will facilitate transcriptome analysis and genomic evolution studies in the future.

In recent years, convolutional neural network (CNN) based methods have been widely used in remote sensing image compression tasks. However, CNN is commonly used to extract local information and does not fully utilize global contextual information. The transformer model can effectively extract the latent contextual information in remote sensing images due to its multihead self-attention mechanisms. Due to the multiscale local features and global low-frequency information of remote sensing images, existing deep-learning-based compression methods have not effectively combined CNN and transformer. In order to overcome the limitations of the above methods, a multihead global attention and spatial spectral information fusion network (MGSSNet) is proposed for remote sensing image compression. First, a spatial spectral information fusion attention module (SSIF-AM) is constructed to obtain multiscale local information. Second, a multihead global attention module (MHG-AM) is proposed to capture rich global context information. Third, a local global collaboration module is developed to explore the correlation between the multiscale local features obtained by SSIF-AM and the global visual features obtained by MHG-AM, and to efficiently model the intrinsic relationships between them to achieve effective feature fusion. Experimental results show that compared with advanced compression models, the proposed MGSSNet method achieves better compression performance. In addition, using reconstructed images obtained by different compression methods for classification tasks has proven that the proposed method can help achieve better classification performance, indicating that the proposed compression method can more fully preserve important information in the image.

Abstract Background The growing demand for electrophysiology (EP) treatment in China presents a challenge for current EP care delivery systems. This study constructed a discrete event simulation (DES) model of an inpatient EP care delivery process, simulating a generalized inpatient journey of EP patients from admission to discharge in the cardiology department of a tertiary hospital in China. The model shows how many more patients the system can serve under different resource constraints by optimizing various phases of the care delivery process. Methods Model inputs were based on and validated using real-world data, simulating the scheduling of limited resources among competing demands from different patient types. The patient stay consists of three stages, namely: the pre-operative stay, the EP procedure, and the post-operative stay. The model outcome was the total number of discharges during the simulation period. The scenario analysis presented in this paper covers two capacity-limiting scenarios (CLS): (1) fully occupied ward beds and (2) fully occupied electrophysiology laboratories (EP labs). Within each CLS, we investigated potential throughput when the length of stay or operative time was reduced by 10%, 20%, and 30%. The reductions were applied to patients with atrial fibrillation, the most common indication accounting for almost 30% of patients. Results Model validation showed simulation results approximated actual data (137.2 discharges calculated vs. 137 observed). With fully occupied wards, reducing pre- and/or post-operative stay time resulted in a 1–7% increased throughput. With fully occupied EP labs, reduced operative time increased throughput by 3–12%. Conclusions Model validation and scenario analyses demonstrated that the DES model reliably reflects the EP care delivery process. Simulations identified which phases of the process should be optimized under different resource constraints, and the expected increases in patients served.

Objectiveγ-aminobutyric acid (GABA) is a neurotransmitter inhibitor that has beneficial effects on various health conditions such as hypertension, cognitive dysfunction, and anxiety. In this study, we investigated a novel yogurt naturally enriched with GABA using a Levilactobacillus brevis strain isolated in our laboratory; the specific optimum yogurt production conditions for this strain were determined.MethodsWe isolated an L. brevis strain and used it to produce yogurt naturally enriched with GABA. We explored the optimal conditions to enhance GABA yield, including fermentation temperature, inoculation amount, L-monosodium glutamate (L-MSG) concentration, fermentation time, and sucrose content. We also performed mixed fermentation with Streptococcus thermophilus and evaluated the quality of the yogurt.ResultsFollowing optimization (43°C, 8% inoculation amount, 1.5 g/L L-MSG, and 8% sucrose for 40 h of fermentation), the GABA yield of the yogurt increased by 2.2 times, reaching 75.3 mg/100 g. Mixed fermentation with S. thermophilus demonstrated favorable results, achieving a GABA yield akin to that found in some commercially available functional foods. Moreover, the viable microbe count in the GABA-enriched yogurt exceeded 1 × 108 cfu/mL, which is higher than that of commercial standards. The yogurt also exhibited a suitable water-holding capacity, viscosity, 3-week storage time, and favorable sensory test results.ConclusionThis study highlights the potential of naturally enriched GABA yogurt as a competitive commercial yogurt with beneficial health effects.

Although the relationship between employer brand and employee creativity has become a popular theme, this nexus is indirect and ambiguous. Additionally, most studies ignore the consistency of instrumental and symbolic attributes when discussing the consequences of employer brand. This study explored the mechanism of employer brand attributes congruence on employee creativity through career satisfaction, and further revealed the moderating role of proactive personality. Based on the cue consistency theory and the social information processing theory, a polynomial regression model was created and a response surface analysis was conducted using 488 paired questionnaires. The results showed that employer brand attributes congruence impacted employee creativity via career satisfaction. A consistent employer brand strategy is more effective for the creativity of less proactive individuals, while a high-level proactive personality can compensate for the deficiencies of employer brand attributes incongruence. The results complemented employer brand research from the perspective of the instrumental–symbolic attribute configuration and provided supportive empirical evidence of employer brand practices aiming at improving employee creativity. This study has certain practical implications for HR practitioners.

Abstract Background Studies on the epidemiological information and prognosis of primary malignant lacrimal gland tumors (MLGTs) are rare for its low occurrence. The goal of our research was to investigate the epidemiological characteristics and survival outcomes of patients with MLGTs. Methods Incidence and demographic information of patients with MLGTs were collected from the Surveillance, Epidemiology, and End Results (SEER) database. To identify independent prognostic factors for disease‐specific survival (DSS) and overall survival (OS), univariate and multivariate Cox regression analysis were performed. Results The overall incidence of primary MLGTs from 1975 to 2020 was 0.413/1,000,000 (according to the 2000 American standard population), with a steadily increasing incidence over years. A total of 964 patients with primary MLGTs were diagnosed, with an average age of 59.3 years. Of these, 53.2% were aged ≥60 years, 57.4% were female, and 77.1% were whites. Multivariate Cox regression analysis demonstrated that year of diagnosis, age, sex, histological type, SEER stage, surgery, and chemotherapy were independent prognostic factors of DSS or OS. Conclusions Although primary MLGT is rare, its incidence has steadily increased in the past 46 years, and surgery was related to a better prognosis.

Abstract Background and purpose: There is increasing evidence to support a role for human herpes viruses in the development of neurodegenerative disorders; however, the association between varicella‐zoster virus (VZV) infection and dementia, and the effect of antiviral therapy on the risk for dementia remain unclear. Methods We searched PubMed, Embase, and the Cochrane Library databases from their dates of inception to May 2023. Odds ratios (ORs) with 95% confidence intervals (CIs) served as indicators of effect sizes in evaluations of the effect of VZV infection and antiviral treatment on dementia risk. Subgroup analyses based on study design, study location, diagnostic criteria of dementia, and VZV subtype classification were also performed. Results A total of 10 studies with 316,846 dementia cases were included in the meta‐analysis. We found that any VZV infection (OR: 1.04, 95% CI: .97–1.12; p = .22), herpes zoster (HZ) (OR: 1.05, 95% CI: .96–1.13; p = .28), or HZ involving the cranial nerves (OR: 1.36, 95% CI: .76–2.43; p = .304) was not associated with an increased risk of dementia. The results of subgroup analyses were consistent with these findings. However, patients infected with VZV who received antiviral treatment had a lower OR than untreated patients infected with VZV. Compared to individuals not infected with VZV, antiviral therapy in those infected with VZV was associated with reduced risk for dementia. Conclusion The association between VZV infection and dementia may be masked by antiviral treatment. Further studies with longer follow‐up times that consider the severity of VZV infection and antiviral treatment are needed to clarify the contribution of VZV infection to the risk for dementia.

α-Cembrenediol exhibits a wide range of biological activities, including antibacterial, antitumor, and neuroprotective effects. However, knowledge of the absorption, transport, and release of α-cembrenediol in drug metabolism within the body is currently limited. Therefore, we aimed to gain a comprehensive understanding of the in vivo transport, distribution, and elimination mechanisms of α-cembrenediol and investigate the interaction between α-cembrenediol and HSA. To this end, we utilized various methods including UV absorption spectroscopy, steady-state fluorescence analysis, circular dichroism measurements, molecular docking studies, and molecular dynamics simulations. The results of the UV and fluorescence spectra clearly demonstrated that HSA interacts with α-cembrenediol. Specifically, the fluorescence spectra results showed that at a temperature of 310 K, the fluorescence quenching constant (KSV) and binding constant (Kb) between HSA and α-cembrenediol were determined to be 1.28 × 103 Lmol−1 and 218.27 Lmol−1, respectively. As the temperature was decreased from 310 K to 293 K, both KSV and Kb values increased, indicating the presence of a static quenching mechanism throughout the interaction process. Moreover, the results indicated the presence of a singular, specific binding site for α-cembrenediol on HSA, as evidenced by an approximate count of one binding site at all three temperatures. Additionally, this binding process occurred spontaneously (ΔG

Hemicellulose can be selectively removed by acid pretreatment. In this study, selective removal of hemicellulose was achieved using dilute sulfuric acid assisted by aluminum sulfate pretreatment. The optimal pretreatment conditions were 160 °C, 1.5 wt% aluminum sulfate, 0.7 wt% dilute sulfuric acid, and 40 min. A component analysis showed that the removal rate of hemicellulose and lignin reached 98.05% and 9.01%, respectively, which indicated that hemicellulose was removed with high selectivity by dilute sulfuric acid assisted by aluminum sulfate pretreatment. Structural characterizations (SEM, FTIR, BET, TGA, and XRD) showed that pretreatment changed the roughness, crystallinity, pore size, and functional groups of corn straw, which was beneficial to improve the efficiency of enzymatic hydrolysis. This study provides a new approach for the high-selectivity separation of hemicellulose, thereby offering novel insights for its subsequent high-value utilization.

Permeable concrete is a type of porous concrete with the special function of water permeability, but the permeability of permeable concrete will decrease gradually due to the clogging behavior arising from the surrounding environment. To reliably characterize the clogging behavior of permeable concrete, particle swarm optimization (PSO) and random forest (RF) hybrid artificial intelligence techniques were developed in this study to predict the permeability coefficient of permeable concrete and optimize the aggregate mix ratio of permeable concrete. Firstly, a reliable database was collected and established to characterize the input and output variables for the machine learning. Then, PSO and 10-fold cross-validation were used to optimize the hyperparameters of the RF model using the training and testing datasets. Finally, the accuracy of the developed model was verified by comparing the predicted value with the actual value of the permeability coefficients (R = 0.978 and RMSE = 1.3638 for the training dataset; R = 0.9734 and RMSE = 2.3246 for the testing dataset). The proposed model can provide reliable predictions of the clogging behavior that permeable concrete may face and the trend of its development.

In vitro fertilization (IVF) is a highly effective treatment for infertility; however, it poses challenges for women with decreased ovarian reserve (DOR). Despite the importance of understanding the impact of DOR on IVF outcomes, limited research has explored this relationship, particularly using omics approaches. Hence, we conducted a study to investigate the association between DOR and IVF outcomes, employing a metabolomic approach. We analyzed serum samples from 207 women undergoing IVF treatment, including 89 with DOR and 118 with normal ovarian reserve (NOR). Our findings revealed that DOR was significantly associated with unfavorable IVF outcomes, characterized by a reduced oocyte count, lower embryo quality, and decreased rates of pregnancy and live births. Furthermore, we identified 82 metabolites that displayed significant alterations in DOR patients, impacting diverse metabolic pathways. Notably, a distinct panel of metabolites, including palmitic acid, stearic acid, LysoPC(9:0(CHO)/0:0), PC(18:0/9:0(CHO)), and PC(16:0/9:0(CHO)), exhibited discriminatory power between the DOR and NOR groups, showcasing a strong correlation with IVF outcomes. These findings emphasize the crucial role of metabolomic disruptions in influencing IVF outcomes among women with DOR.

In this work, a surface dispersed heterojunction of BiVO4-nanoparticle@WO3-nanoflake was successfully prepared by hydrothermal combined with solvothermal method. We optimized the morphology of the WO3 nanoflakes and BiVO4 nanoparticles by controlling the synthesis conditions to get the uniform BiVO4 loaded on the surface of WO3 arrays. The phase composition and morphology evolution with different reaction precursors were investigated in detail. When used as photoanodes, the WO3/BiVO4 composite exhibits superior activity with photocurrent at 3.53 mA cm−2 for photoelectrochemical (PEC) water oxidation, which is twice that of pure WO3 photoanode. The superior surface dispersion structure of the BiVO4-nanoparticle@WO3-nanoflake heterojunction ensures a large effective heterojunction area and relieves the interfacial hole accumulation at the same time, which contributes to the improved photocurrents together with the stability of the WO3/BiVO4 photoanodes.

The standard approach for testing ordinary concrete compressive strength (CS) is to cast samples and test them after different curing times. However, testing adds cost and time to projects, and, therefore, construction sites experience delays. Because carbon nanotubes (CNTs) vary in length, composition, diameter, and dispersion, experiment and formula fitting alone cannot reliably predict the strength of CNTs-based composites. For empirical equations or traditional statistical approaches to properly forecast complex materials’ mechanical characteristics, various significant parameters, databases, and nonlinear relationships between variables must be considered. Machine learning (ML) tools are the most advanced for accurate predictions of material behaviour. This study employed gradient boosting, light gradient boosting machine, and extreme gradient boosting techniques to forecast the CS of CNTs-modified concrete. Also, in order to explore the influence and interaction of various features, an interaction analysis was conducted. In terms of R2, gradient boosting, light gradient boosting machine, and extreme gradient boosting models proved their accuracy. Extreme gradient boosting had the highest R2 of 0.97, followed by light gradient boosting machine and gradient boosting with scores of 0.94 and 0.93, respectively. This type of research may help both academics and industry forecast material properties and influential elements, thereby reducing lab test requirements.

The present study utilized machine learning (ML) techniques to investigate the effects of eggshell powder (ESP) and recycled glass powder (RGP) on cement composites subjected to an acidic setting. A dataset acquired from the published literature was employed to develop machine learning-based predictive models for the cement mortar’s compressive strength (CS) decrease. Artificial neural network (ANN), K-nearest neighbor (KNN), and linear regression (LR) were chosen for modeling. Also, RreliefF analysis was performed to study the relevance of variables. A total of 234 data points were utilized to train/test ML algorithms. Cement, sand, water, silica fume, superplasticizer, glass powder, eggshell powder, and 90 days of CS were considered as input variables. The outcomes of the research showed that the employed models could be applied to evaluate the reduction percentage of CS in cement composites, including ESP and RGP, after being exposed to acid. Based on the R2 values (0.87 for the ANN, 0.81 for the KNN, and 0.78 for LR), as well as the assessment of variation between test values and anticipated outcomes and errors (1.32% for ANN, 1.57% for KNN, and 1.69% for LR), it was determined that the accuracy of the ANN model was superior to the KNN and LR. The sieve diagram exhibited a correlation amongst the model predicted and target results. The outcomes of the RreliefF analysis suggested that ESP and RGP significantly influenced the CS loss of samples with RreliefF scores of 0.26 and 0.21, respectively. Based on the outcomes of the research, the ANN approach was determined suitable for predicting the CS loss of mortar subjected to acidic environments, thereby eliminating lab testing trails.

Proteolysis-targeting chimeras (PROTACs) introduce a novel paradigm in drug development, incorporating three essential components: the warhead, the E3 ligand, and the linker. The complexity of the ternary structure, particularly the intricate design of the linker, presents a significant challenge in PROTACs drug design. Here an integrated protocol for design and evaluation of PROTACs targeting specific proteins, called TRL-PROTAC is proposed. TRL-PROTAC is focused on the de novo design of complete PROTACs by effectively joining the designed ligands targeting the proteins of interest (POI) with linkers. The ligands for POIs and E3 ligases are generated by a molecular generation model for targeting proteins, and the linker design is generated by a sequence-to-sequence model consisting of a transformer variant and the policy-based reinforcement learning method which is employed to optimize the reward values for generating PROTACs. The three components are then integrated and optimized based on their pharmacokinetic (PK) and degradation (DEG) properties. The experimental results have strongly confirmed that TRL-PROTAC is superior in optimizing properties. For existing PROTACs, TRL-PROTAC improves DEG scores by 0.45 and lowers PK scores by 1.20. Moreover, TRL-PROTAC enhances binding affinity by 2.15 in PROTACs generated from scratch. [ABSTRACT FROM AUTHOR]

Myocardial ischemia/reperfusion (IR) injury is a significant annual clinical threat. Reperfusion injury exacerbates this issue by causing an excessive overload of reactive oxygen species (ROS) due to heme degradation and dysfunction in mitochondrial complexes. Subsequently, this surge in ROS leads to mitochondrial damage, further compromising cardiomyocyte mitochondrial function and eventually causing cell death. Given its pivotal role, targeting ROS has emerged as a viable strategy for treating myocardial ischemic injury. One promising therapeutic intervention involves the use of nanomaterials to eliminate ROS. In this study, we synthesized a polyvinylpyrrolidone-modified ultrathin niobium carbide (Nb2C) MXene, which effectively alleviated myocardial IR injury by scavenging ROS and enhancing mitochondrial function. Nb2C demonstrated multiple enzymatic-like abilities, including catalase and superoxide dismutase, which offered effective protection against myocardial ischemic injury by neutralizing superoxide anions and hydrogen peroxide. Furthermore, in the IR mice treated with Nb2C, mitochondrial injury was significantly reduced, and mitochondrial function was notably improved. Intravenous administration of Nb2C resulted in substantial recovery of cardiac function in IR mice and a marked reduction in the infarct area. This research offers insights into the potential of Nb2C MXene as a treatment for myocardial IR injury. [ABSTRACT FROM AUTHOR]