The association between lower extremity function and cardiovascular diseases risk in older Chinese adults: Longitudinal evidence from a nationwide cohort.

BACKGROUND: Older adults in China are at a high risk of cardiovascular diseases (CVD), and impaired lower extremity function (LEF) is commonly observed in this demographic. This study aimed at assessing the association between LEF and CVD, thus providing valuable insights for clinical practice and public health policies. METHODS: A sample of 4,636 individuals was included from the China Health and Retirement Longitudinal Study (CHARLS) dataset. Logistic regression and cox proportional hazard regression model was utilized to study the association between LEF and CVD incidence. Cross-lagged panel models were utilized to investigate the potential causal association between LEF and CVD over time. RESULTS: Poor LEF was significantly associated with a higher risk of CVD in the total population [OR (95 % CI): 1.62 (1.27-2.05), P < 0.001]. Individuals with poor LEF demonstrated an increased risk of developing CVD [HR (95 % CI): 1.11 (1.02-1.23), P < 0.05], particularly stroke, compared to those with good LEF. And those with poor LEF had higher risks for heart disease [1.21 (1.00-1.45), P < 0.05] and stroke [1.98 (1.47-2.67), P < 0.001]. CONCLUSION: The results suggest the potential usefulness of the Short Physical Performance Battery (SPPB) for classifying stroke risk in older Chinese adults, which also suggested that preventing and/or improving LEF may be beneficial for reducing stroke incidence and promoting healthy aging for older adults.

Application of PLS-NN model based on mid-infrared spectroscopy in the origin identification of Cornus officinalis.

Mid-infrared spectroscopy has been increasingly used as a nondestructive analytical technique in Chinese herbal medicine identification in recent years. In this study, a new chemometric model named as PLS-NN model was proposed based on the mid-infrared spectral data of Cornus officinalis samples from 11 origins. It was realized by combining the partial least squares and neural networks for the identification of the origin of Chinese herbal medicines. First, we extracted features from the spectral data in 3448 bands using the partial least squares method, and extracted 122 components that contained more than 95% of the information. Then, we trained the PLS-NN model by neural network using the extracted components as inputs and the corresponding origin classes as outputs. Finally, based on an external test set, we evaluated the generalization ability of the PLS-NN model using metrics such as accuracy, F1-Score and Kappa coefficient. The results show that the PLS-NN model performs well in all three metrics when compared to models such as Decision trees, Support vector machine, Partial least squares Discriminant analysis, and Naive bayes. The model not only realizes the dimensionality reduction of full-spectrum data and improves the training efficiency of the model, but also has higher accuracy compared with the full-spectrum data model. The PLS-NN model was applied to identify the origin of Cornus officinalis with an accuracy of 91.9%.

Development and validation of prognostic nomograms for adult with papillary renal cell carcinoma: A retrospective study.

OBJECTIVE: The aim of the study was to create two consensus nomograms for predicting Overall Survival (OS) and Cancer-Specific Survival (CSS) in adults with papillary Renal Cell Carcinoma (pRCC). METHODS: Using the Surveillance, Epidemiology, and End Results databases, a retrospective analysis of 1,074 adults with pRCC from 2004 to 2015 was performed. These patients were then randomly divided into two independent cohorts with a ratio of 7:3 (training cohort: 752; validation cohort: 322). In a retrospective analysis of 752 patients from the training cohort, independent prognostic variables affecting OS and CSS were found. R software was used to create prognostic nomograms based on the findings of Cox regression analysis. The performance of the nomograms was assessed using the Concordance Index (C-index), the Area Under Curve (AUC), a calibration curve, and Decision Curve Analysis (DCA). Data from the 107 postoperative pRCC patients at the Affiliated Hospital of Xuzhou Medical University were used for external validation of the nomogram. RESULTS: For OS and CSS, the C-indices and AUCs of the training cohort and the validation cohort indicated that the model had excellent discrimination. The DCA demonstrated that the model was clinically applicable, and the calibration curves in the internal and external validations showed that the model's accuracy was high. CONCLUSION: The authors developed and validated a prognostic nomogram that accurately predicted the 3-, 5-, and 8-year OS and CSS of adults with pRCC. Clinicians can use this knowledge to direct the clinical management and counseling of patients with pRCC.

HHLA2 promotes hepatoma cell proliferation, migration, and invasion via SPP1/PI3K/AKT signaling pathway.

Hepatocellular carcinoma (HCC) stands as one of the most malignant tumors characterized by poor prognosis and high mortality rates. Emerging evidence underscores the crucial role of the B7 protein family in various cancers, including HCC. However, the involvement of the human endogenous retrovirus H long-terminal repeat-associated protein 2 (HHLA2, or B7-H5) in HCC remains unclear. Immunohistochemistry was employed to assess the differential expression of HHLA2 between HCC and normal liver tissues. A battery of assays, including CCK8, EdU, tablet clone-forming, Transwell, and wound healing assays, were conducted to elucidate the function and potential mechanisms of HHLA2 in the malignant biological behaviors of HCC. Additionally, a xenograft mouse model was established to evaluate the tumorigenicity of hepatoma cell lines exhibiting different HHLA2 expression levels in vivo. Western blot analysis was used to analyze HHLA2, secretory phosphoprotein 1 (SPP1), and PI3K/AKT/mTOR levels. HHLA2 exhibited elevated expression in HCC tissues, correlating with poor tumor differentiation and shortened overall survival in HCC patients. In vitro experiments demonstrated that HHLA2 overexpression (OE) promoted the proliferation, migration, and invasion of hepatoma cells, while in vivo experiments revealed that HHLA2 OE enhanced HCC tumor growth. Conversely, inhibition of HHLA2 expression yielded the opposite effect. Downregulation of SPP1 inhibited the proliferation, migration, and invasion induced by HHLA2 OE, and this effect was linked to the PI3K/AKT/mTOR signaling pathway. Our findings indicate that HHLA2 promotes the proliferation, migration, and invasion of hepatoma cells via the SPP1/PI3K/AKT signaling pathway, establishing it as a potential therapeutic target for HCC.

Interference with mitochondrial metabolism could serve as a potential therapeutic strategy for advanced prostate cancer.

Metabolic reprogramming has been defined as a hallmark of malignancies. Prior studies have focused on the single nucleotide polymorphism (SNP) of POLG2 gene, which is reportedly responsible for encoding mitochondrial DNA genes and is implicated in the material and energy metabolism of tumor cells, whereas its function in prostate cancer has been elusive. Gene expression profile matrix and clinical information were downloaded from TCGA (The Cancer Genome Atlas) data portal, and GSE3325 and GSE8511 were retrieved from GEO (Gene Expression Omnibus) database. We conducted analysis of the relative expression of POLG2, clinical characterization, survival analysis, GO / KEGG and GSEA (Gene Set Enrichment Analysis) enrichment analysis in R and employed STRING portal to acquaint ourselves with the protein-protein interaction (PPI). IHC (Immunohistochemical) profiles of POLG2 protein between normal and cancerous tissues were consulted via HPA (Human protein atlas) database and the immunohistochemical POLG2 were verified between para-cancerous and cancerous tissues in tissue array. At the cellular level, Mitochondrial dysfunction assay, DNA synthesis test, wound healing assay, and invasion assay were implemented to further validate the phenotype of POLG2 knockdown in PCa cell lines. RT-qPCR and western blotting were routinely adopted to verify variations of molecular expression within epithelial mesenchymal transition (EMT). Results showed that POLG2 was over-expressed in most cancer types, and the over-expression of POLG2 was correlated with PCa progression and suggested poor OS (Overall Survival) and PFI (Progress Free Interval). Multivariate analysis showed that POLG2 might be an independent prognostic factor of prostate cancer. We also performed GO/KEGG, GSEA analysis, co-expression genes, and PPI, and observed the metabolism-related gene alterations in PCa. Furthermore, we verified that POLG2 knockdown had an inhibitory effect on mitochondrial function, proliferation, cell motility, and invasion, we affirmed POLG2 could affect the prognosis of advanced prostate cancer via EMT. In summary, our findings indicate that over-expressed POLG2 renders poor prognosis in advanced prostate cancer. This disadvantageous factor can serve as a potential indicator, making it possible to target mitochondrial metabolism to treat advanced prostate cancer.

Finite Element Analysis of Different Carbon Fiber Reinforced Polyetheretherketone Dental Implants in Implant-supported Fixed Denture.

OBJECTIVES: The purpose of this study is to determine the feasibility of polyetheretherketone-based dental implants, and analyze the stress and strain around different kinds of dental implants by finite element analysis. METHODS: The radiographic data was disposed to models in Mimics 19.0. 3D models of implants, crowns and jawbones were established and combined in SolidWorks 2018. Appling axial and oblique loads of 100 N, cloud pictures were exported in Ansys Workbench 18.0 to calculate and analyze the stress and strain in and around different implants. RESULTS: Oblique load tended to deliver more stress to bone tissue than axial load. The uniformity of stress distribution was the best for 30% short carbon fiber reinforced polyetheretherketone implants at axial and buccolingual directions. Stress shielding phenomenon occurred at the neck of 60% continuous carbon fiber reinforced polyetheretherketone and titanium implants. Stress concentration appeared in PEEK implants and the load of bone tissue would aggravate. CONCLUSIONS: 30% short carbon fiber reinforced polyetheretherketone implants demonstrate a more uniform stress distribution in bone-implant contact and surrounding bone than titanium. Stress shielding and stress concentration may be avoided in bone-implant interface and bone tissue. Bone disuse-atrophy may be inhibited in PEEK-based implants.

Synergistic targeting of TrxR1 and ATM/AKT pathway in human colon cancer cells.

Thioredoxin reductase 1 (TrxR1) has emerged as a promising target for cancer therapy. In our previous research, we discovered several new TrxR1 inhibitors and found that they all have excellent anti-tumor activity. At the same time, we found these TrxR1 inhibitors all lead to an increase in AKT phosphorylation in cancer cells, but the detailed role of AKT phosphorylation in TrxR1 inhibitor-mediated cell death remains unclear. In this study, we identified the combination of AKT and TrxR1 inhibitor displayed a strong synergistic effect in colon cancer cells. Furthermore, we demonstrated that the synergistic effect of auranofin (TrxR1 inhibitor) and MK-2206 (AKT inhibitor) was caused by ROS accumulation. Importantly, we found that ATM inhibitor KU-55933 can block the increase of AKT phosphorylation caused by auranofin, and exhibited a synergistic effect with auranofin. Taken together, our study demonstrated that the activation of ATM/AKT pathway is a compensatory mechanism to cope with ROS accumulation induced by TrxR1 inhibitor, and synergistic targeting of TrxR1 and ATM/AKT pathway is a promising strategy for treating colon cancer.

Sarcopenia is associated with leukopenia in urothelial carcinoma patients who receive tislelizumab combined with gemcitabine and cisplatin therapy.

BACKGROUND: In the era of combination therapy, there has been limited research on body composition. Specific body composition, such as sarcopenia, possesses the potential to serve as a predictive biomarker for toxic effects and clinical response in patients with urothelial carcinoma (UC) undergoing tislelizumab combined with gemcitabine and cisplatin (T + GC). MATERIALS AND METHODS: A total of 112 UC patients who received T + GC were selected at the Affiliated Hospital of Xuzhou Medical University from April 2020 to January 2023. Baseline patient characteristics and detailed hematological parameters were collected using the electronic medical system and laboratory examinations. The computed tomography images of patients were analyzed to calculate psoas muscle mass index (PMI). We evaluated the association between sarcopenia (PMI < 4.5 cm2/m2 in men; PMI < 3.3 cm2/m2 in women) and both hematological toxicity and tumor response. RESULTS: Overall, of the 112 patients (65.2% male, median age 56 years), 43 (38.4%) were defined as sarcopenia. Patients with sarcopenia were notably older (p = 0.037), more likely to have hypertension (p = 0.009), and had poorer ECOG-PS (p = 0.027). Patients with sarcopenia were more likely to develop leukopenia (OR 2.969, 95% CI 1.028-8.575, p = 0.044) after receiving at least two cycles of T + GC. However, these significant differences were not observed in thrombocytopenia and anemia. There were no significant differences in the tumor response and grade 3-4 hematological toxicity between patients with sarcopenia and those without sarcopenia. CONCLUSIONS: Patients with sarcopenia were more likely to develop leukopenia after receiving T + GC. There were no notable alterations observed in relation to anemia or thrombocytopenia. No significant difference was found between the sarcopenia group and non-sarcopenia group in terms of tumor response and grade 3-4 hematological toxicity.

Integrative analysis identifies oxidative stress biomarkers in non-alcoholic fatty liver disease via machine learning and weighted gene co-expression network analysis.

Background: Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease globally, with the potential to progress to non-alcoholic steatohepatitis (NASH), cirrhosis, and even hepatocellular carcinoma. Given the absence of effective treatments to halt its progression, novel molecular approaches to the NAFLD diagnosis and treatment are of paramount importance. Methods: Firstly, we downloaded oxidative stress-related genes from the GeneCards database and retrieved NAFLD-related datasets from the GEO database. Using the Limma R package and WGCNA, we identified differentially expressed genes closely associated with NAFLD. In our study, we identified 31 intersection genes by analyzing the intersection among oxidative stress-related genes, NAFLD-related genes, and genes closely associated with NAFLD as identified through Weighted Gene Co-expression Network Analysis (WGCNA). In a study of 31 intersection genes between NAFLD and Oxidative Stress (OS), we identified three hub genes using three machine learning algorithms: Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine - Recursive Feature Elimination (SVM-RFE), and RandomForest. Subsequently, a nomogram was utilized to predict the incidence of NAFLD. The CIBERSORT algorithm was employed for immune infiltration analysis, single sample Gene Set Enrichment Analysis (ssGSEA) for functional enrichment analysis, and Protein-Protein Interaction (PPI) networks to explore the relationships between the three hub genes and other intersecting genes of NAFLD and OS. The distribution of these three hub genes across six cell clusters was determined using single-cell RNA sequencing. Finally, utilizing relevant data from the Attie Lab Diabetes Database, and liver tissues from NASH mouse model, Western Blot (WB) and Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) assays were conducted, this further validated the significant roles of CDKN1B and TFAM in NAFLD. Results: In the course of this research, we identified 31 genes with a strong association with oxidative stress in NAFLD. Subsequent machine learning analysis and external validation pinpointed two genes: CDKN1B and TFAM, as demonstrating the closest correlation to oxidative stress in NAFLD. Conclusion: This investigation found two hub genes that hold potential as novel targets for the diagnosis and treatment of NAFLD, thereby offering innovative perspectives for its clinical management.

Synthesis and Anti-Inflammatory Activity of Ferulic Acid-Sesquiterpene Lactone Hybrids.

Acute lung injury (ALI) is a respiratory failure disease associated with high mortality rates in patients. The primary pathological damage is attributed to the excessive release of pro-inflammatory mediators in pulmonary tissue. However, specific therapy for ALI has not been developed. In this study, a series of novel ferulic acid-parthenolide (FA-PTL) and ferulic acid-micheliolide (FA-MCL) hybrid derivatives were designed, synthesized, and evaluated for their anti-inflammatory activities in vitro. Compounds 2, 4, and 6 showed pronounced anti-inflammatory activity against LPS-induced expression of pro-inflammatory cytokines in vitro. Importantly, compound 6 displayed good water solubility, and treatment of mice with compound 6 (10 mg/kg) significantly prevented weight loss and ameliorated inflammatory cell infiltration and edema in lung tissue, as well as improving the alveolar structure. These results suggest that compound 6 (((1aR,7aS,8R,10aS,10bS,E)-8-((dimethylamino)methyl)-1a-methyl-9-oxo-1a,2,3,6,7,7a,8,9,10a,10b-decahydrooxireno[2',3':9,10]cyclodeca[1,2-b]furan-5-yl)methyl (E)-3-(4-hydroxy-3-methoxyphenyl)acrylate 2-hydroxypropane-1,2,3-tricarboxylate) might be considered as a lead compound for further evaluation as a potential anti-ALI agent.

A converged ubiquitin-proteasome pathway for the degradation of TOC and TOM tail-anchored receptors.

In plants, thousands of nucleus-encoded proteins translated in the cytosol are sorted to chloroplasts and mitochondria by binding to specific receptors of the TOC (translocon on the outer chloroplast membrane) and the TOM (translocon on the outer mitochondrial membrane) complexes for import into those organelles. The degradation pathways for these receptors are unclear. Here, we discovered a converged ubiquitin-proteasome pathway for the degradation of Arabidopsis thaliana TOC and TOM tail-anchored receptors. The receptors are ubiquitinated by E3 ligase(s) and pulled from the outer membranes by the AAA+ adenosine triphosphatase CDC48, after which a previously uncharacterized cytosolic protein, transmembrane domain (TMD)-binding protein for tail-anchored outer membrane proteins (TTOP), binds to the exposed TMDs at the C termini of the receptors and CDC48, and delivers these complexes to the 26S proteasome.

Plasmonic Gold Nanostar-Based Probes with Distance-Dependent Plasmon-Enhanced Fluorescence for Ultrasensitive DNA Methyltransferase Assay.

The ultrasensitive DNA methyltransferase (Dam MTase) assay is of high significance for biomedical research and clinical diagnosis because of its profound effect on gene regulation. However, detection sensitivity is still limited by shortcomings, including photobleaching and weak signal intensities of conventional fluorophores at low concentrations. Plasmonic nanostructures with ultrastrong electromagnetic fields and fluorescence enhancement capability that can overcome these intrinsic defects hold great potential for ultrasensitive bioanalysis. Herein, a silica-coated gold nanostars (Au NSTs@SiO2)-based plasmon-enhanced fluorescence (PEF) probe with 20 "hot spots" was developed for ultrasensitive detection of Dam MTase. Here, the Dam Mtase assay was achieved by detecting the byproduct PPi of the rolling circle amplification reaction. It is worth noting that, benefiting from the excellent fluorescence enhancement capability of Au NSTs originating from their 20 "hot spots", the detection limit of Dam Mtase was reduced by nearly 105 times. Moreover, the proposed Au NST-based PEF probe enabled versatile evaluation of Dam MTase inhibitors as well as endogenous Dam MTase detection in GW5100 and JM110 Escherichia coli cell lysates, demonstrating its potential in biomedical analysis.

Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome.

Very preterm (VPT) infants (born at less than 32 weeks gestational age) are at high risk for various adverse neurodevelopmental deficits. Unfortunately, most of these deficits cannot be accurately diagnosed until the age of 2-5 years old. Given the benefits of early interventions, accurate diagnosis and prediction soon after birth are urgently needed for VPT infants. Previous studies have applied deep learning models to learn the brain structural connectome (SC) to predict neurodevelopmental deficits in the preterm population. However, none of these models are specifically designed for graph-structured data, and thus may potentially miss certain topological information conveyed in the brain SC. In this study, we aim to develop deep learning models to learn the SC acquired at term-equivalent age for early prediction of neurodevelopmental deficits at 2 years corrected age in VPT infants. We directly treated the brain SC as a graph, and applied graph convolutional network (GCN) models to capture complex topological information of the SC. In addition, we applied the supervised contrastive learning (SCL) technique to mitigate the effects of the data scarcity problem, and enable robust training of GCN models. We hypothesize that SCL will enhance GCN models for early prediction of neurodevelopmental deficits in VPT infants using the SC. We used a regional prospective cohort of ∼280 VPT infants who underwent MRI examinations at term-equivalent age from the Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS). These VPT infants completed neurodevelopmental assessment at 2 years corrected age to evaluate cognition, language, and motor skills. Using the SCL technique, the GCN model achieved mean areas under the receiver operating characteristic curve (AUCs) in the range of 0.72∼0.75 for predicting three neurodevelopmental deficits, outperforming several competing models. Our results support our hypothesis that the SCL technique is able to enhance the GCN model in our prediction tasks.

Comparative transcriptomics analysis identifies crucial genes and pathways during goose spleen development.

As the largest peripheral lymphoid organ in poultry, the spleen plays an essential role in regulating the body's immune capacity. However, compared with chickens and ducks, information about the age- and breed-related changes in the goose spleen remains scarce. In this study, we systematically analyzed and compared the age-dependent changes in the morphological, histological, and transcriptomic characteristics between Landes goose (LG; Anser anser) and Sichuan White goose (SWG; Anser cygnoides). The results showed a gradual increase in the splenic weights for both LG and SWG until week 10, while their splenic organ indexes reached the peak at week 6. Meanwhile, the splenic histological indexes of both goose breeds continuously increased with age, reaching the highest levels at week 30. The red pulp (RP) area was significantly higher in SWG than in LG at week 0, while the splenic corpuscle (AL) diameter was significantly larger in LG than in SWG at week 30. At the transcriptomic level, a total of 1710 and 1266 differentially expressed genes (DEGs) between week 0 and week 30 were identified in spleens of LG and SWG, respectively. Meanwhile, a total of 911 and 808 DEGs in spleens between LG and SWG were identified at weeks 0 and 30, respectively. Both GO and KEGG enrichment analysis showed that the age-related DEGs of LG or SWG were dominantly enriched in the Cell cycle, TGF-beta signaling, and Wnt signaling pathways, while most of the breed-related DEGs were enriched in the Neuroactive ligand-receptor interaction, Cytokine-cytokine receptor interaction, ECM-receptor interaction, and metabolic pathways. Furthermore, through construction of protein-protein interaction networks using significant DEGs, it was inferred that three hub genes including BUB1, BUB1B, and TTK could play crucial roles in regulating age-dependent goose spleen development while GRIA2, GRIA4, and RYR2 could be crucial for the breed-specific goose spleen development. These data provide novel insights into the splenic developmental differences between Chinese and European domestic geese, and the identified crucial pathways and genes are helpful for a better understanding of the mechanisms regulating goose immune functions.

When autophagy meets placenta development and pregnancy complications.

Autophagy is a common biological phenomenon in eukaryotes that has evolved and reshaped to maintain cellular homeostasis. Under the pressure of starvation, hypoxia, and immune damage, autophagy provides energy and nutrients to cells, which benefits cell survival. In mammals, autophagy is an early embryonic nutrient supply system involved in early embryonic development, implantation, and pregnancy maintenance. Recent studies have found that autophagy imbalance in placental tissue plays a key role in the occurrence and development of pregnancy complications, such as gestational hypertension, gestational obesity, premature birth, miscarriage, and intrauterine growth restriction. This mini-review summarizes the molecular mechanism of autophagy regulation, the autophagy pathways, and related factors involved in placental tissue and comprehensively describes the role of autophagy in pregnancy complications.

Zonal demand-controlled ventilation strategy to minimize infection probability and energy consumption: A coordinated control based on occupant detection.

Due to the outbreak of COVID-19, an increased risk of airborne transmission has been experienced in buildings, particularly in confined public places. The need for ventilation as a means of infection prevention has become more pronounced given that some basic precautions (like wearing masks) are no longer mandatory. However, ventilating the space as a whole (e.g., using a unified ventilation rate) may lead to situations where there is either insufficient or excessive ventilation in localized areas, potentially resulting in localized virus accumulation or large energy consumption. It is of urgent need to investigate real-time control of ventilation systems based on local demands of the occupants to strike a balance between infection risk and energy saving. In this work, a zonal demand-controlled ventilation (ZDCV) strategy was proposed to optimize the ventilation rates in sub-zones. A camera-based occupant detection method was developed to detect occupants (with eight possible locations in sub-zones denoted as 'A' to 'H'). Linear ventilation model (LVM), dimension reduction, and artificial neural network (ANN) were integrated for rapid prediction of pollutant concentrations in sub-zones with the identified occupants and ventilation rates as inputs. Coordinated ventilation effects between sub-zones were optimized to improve infection prevention and energy savings. Results showed that rapid prediction models achieved an average prediction error of 6 ppm for CO2 concentration fields compared with the simulation under different occupant scenarios (i.e., occupant locations at ABH, ABCFH, and ABCDEFH). ZDCV largely reduced the infection risk to 2.8% while improved energy-saving efficiency by 34% compared with the system using constant ventilation rate. This work can contribute to the development of building environmental control systems in terms of pollutant removal, infection prevention, and energy sustainability.

Outcomes following the excision of sarcoma and chest wall reconstruction using 3D printed implant.

The survival outcomes of patients with chest wall sarcomas (CWS) were evaluated after receiving wide excision and chest wall reconstruction by using three-dimensional printed (3DP) implants. The survival outcomes evaluating the effect of 3DP implants for chest wall reconstruction is lacking. Here, forty-nine patients with CWS underwent radical wide excision and chest wall reconstruction using 3DP implants. The surgical data and long-term survival outcomes were collected and analyzed. With a median follow-up of 36 months, the disease-free survival (DFS) and overall survival (OS) were 31.7% and 58.5%, respectively. In addition, the 3-year DFS and OS can be significantly differentiated using the classification criteria of tumor grade, tumor size tumor area. Hence, wide excision and chest wall reconstruction using three-dimensional printed implants are a safe and effective treatment for chest wall sarcoma. The novel classification criteria of tumor size and area have the potential to predict the prognosis of CWS.

Exploring General Intelligence via Gated Graph Transformer in Functional Connectivity Studies.

Functional connectivity (FC) as derived from fMRI has emerged as a pivotal tool in elucidating the intricacies of various psychiatric disorders and delineating the neural pathways that underpin cognitive and behavioral dynamics inherent to the human brain. While Graph Neural Networks (GNNs) offer a structured approach to represent neuroimaging data, they are limited by their need for a predefined graph structure to depict associations between brain regions, a detail not solely provided by FCs. To bridge this gap, we introduce the Gated Graph Transformer (GGT) framework, designed to predict cognitive metrics based on FCs. Empirical validation on the Philadelphia Neurodevelopmental Cohort (PNC) underscores the superior predictive prowess of our model, further accentuating its potential in identifying pivotal neural connectivities that correlate with human cognitive processes.

Effects of cage vs. net-floor mixed rearing system on goose spleen histomorphology and gene expression profiles.

Due to the demands for both environmental protection and modernization of the goose industry in China, the traditional goose waterside rearing systems have been gradually transitioning to the modern intensive dryland rearing ones, such as the net-floor mixed rearing system (MRS) and cage rearing system (CRS). However, the goose immune responses to different dryland rearing systems remain poorly understood. This study aimed to investigate and compare the age-dependent effects of MRS and CRS on the splenic histomorphological characteristics and immune-related genes expression profiles among three economically important goose breeds, including Sichuan White goose (SW), Gang goose (GE), and Landes goose (LD). Morphological analysis revealed that the splenic weight and organ index of SW were higher under CRS than under MRS (p < 0.05). Histological observations showed that for SW and LD, the splenic corpuscle diameter and area as well as trabecular artery diameter were larger under MRS than under CRS at 30 or 43 weeks of age (p < 0.05), while the splenic red pulp area of GE was larger under CRS than under MRS at 43 weeks of age (p < 0.05). Besides, at 43 weeks of age, higher mRNA expression levels of NGF, SPI1, and VEGFA in spleens of SW were observed under MRS than under CRS (p < 0.05), while higher levels of HSPA2 and NGF in spleens of LD were observed under MRS than under CRS (p < 0.05). For GE, there were higher mRNA expression levels of MYD88 in spleens under CRS at 30 weeks of age (p < 0.05). Moreover, our correlation analysis showed that there appeared to be more pronounced positive associations between the splenic histological parameters and expression levels of several key immune-related genes under MRS than under CRS. Therefore, it is speculated that the geese reared under MRS might exhibit enhanced immune functions than those under CRS, particularly for SW and LD. Although these phenotypic differences are assumed to be associated with the age-dependent differential expression profiles of HSPA2, MYD88, NGF, SPI1, and VEGFA in the goose spleen, the underlying regulatory mechanisms await further investigations.

Semipinacol Rearrangement of Iododifluorohomoallyl Alcohols and Its Application in the Allylic C-H Esterification Reactions.

We herein present a study on the Ag(I)-mediated semipinacol rearrangement of iododifluorohomoallyl alcohols, the resulting allylic difluoromethyl ketones underwent oxidative allylic C-H esterification under palladium catalysis in the absence of external ligand. This process yielded a range of difluoromethyl ketones derived from allyl esters in a single operation. The reaction features broad scope of o-nitrobenzoic acids and homoallylic iododifluoroalcohols affording the targeted molecules in synthetically useful yields. Control experiments illustrated that the silver salt acted as not only a Lewis acid to promote the cleavage of a C-I bond and furnish the semipinacol rearrangement but also a co-oxidant in the catalytic cycle for the allylic C-H esterification.