Fresnel lens three-dimensionally printed on the facet of a single mode fiber for trapping, manipulation, and spectrum.

Fiber optical tweezers (FOTs) provide a functionality for micro-/nanoparticle manipulation with a slim and flexible optical fiber setup. An added in situ spectroscopic functionality can achieve characterization of the trapped particle, potentially useful for endoscopic, in-vivo studies in an inherently heterogeneous environment if the applicator end is all-fiber-built. Here, we demonstrate all-fiber optical tweezers (a-FOTs) for the trapping and in situ spectral measurement of a single, cell-sized microparticle. The key to ensure the simultaneous bifunctionality is a high numerical aperture (NA) Fresnel lens fabricated by two-photon direct laser writing (DLW) corrected by grid-correction methods. We demonstrate trapping and time-resolved, in situ spectroscopy of a single upconversion particle (UCP), a common fluorescent biomarker in biophotonics. The system achieves a 0.5-s time resolution in the in situ spectral measurement of a trapped UCP. The all-fiber designed system preserves the advantages of flexibility and robustness of the fiber, potentially useful for in-vivo biomedical studies such as cell-to-cell interactions, pH and temperature detection, and nucleic acids detection.

Monolayer directional metasurface for all-optical image classifier doublet: publisher's note.

This publisher's note contains a correction to Opt. Lett.49, 2505 (2024)10.1364/OL.520642.

Efficacy of telemedicine intervention in the self-management of patients with type 2 diabetes: a systematic review and meta-analysis.

Purpose: We aimed to report the latest and largest pooled analyses and evidence updates to assess the effectiveness of telemedicine interventions for self-management (DSM) in patients with type 2 diabetes mellitus (T2DM). Methods: A systematic literature search was conducted using PubMed, Cochrane, Embase, and Web of Science in December 2023. We included randomized controlled trials (RCTs) of adults (≥18 years of age) diagnosed with T2DM where the intervention was the application of telemedicine. The Cochrane Risk of Bias Assessment was used to evaluate quality. The study's main outcome indicators were glycosylated hemoglobin (HbA1c) and diabetes self-management (DSM) capacity. Results: A total of 17 eligible articles, comprising 20 studies and 1,456 patients (734 in the intervention group and 722 in the control group), were included in the evidence synthesis. The baseline characteristics of both groups were similar in all outcomes. Comprehensive analyses showed post-intervention decreases in HbA1c, 2-h postprandial glucose, systolic and diastolic blood pressure, increases in Diabetes Self- Care activities, DSM competencies based on dietary and medication adherence, and improvements in overall DSM scores, all of which were statistically significant. While no statistically significant differences were observed in body mass index, lipids, and other DSM dimensions. Based on subgroup analyses, app-based experimental interventions targeting under 60 years old populations in Asia and North America were found to be more effective and less heterogeneity in the short term (<6 months of intervention). Conclusion: Telemedicine interventions may assist patients with T2DM in enhancing their DSM and improving their HbA1c levels. Clinician can use various telemedicine interventions to enhance DSM in T2DM patients, considering local circumstances. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, CRD42024508522.

Monolayer directional metasurface for all-optical image classifier doublet.

Diffractive deep neural networks, known for their passivity, high scalability, and high efficiency, offer great potential in holographic imaging, target recognition, and object classification. However, previous endeavors have been hampered by spatial size and alignment. To address these issues, this study introduces a monolayer directional metasurface, aimed at reducing spatial constraints and mitigating alignment issues. Utilizing this methodology, we use MNIST datasets to train diffractive deep neural networks and realize digital classification, revealing that the metasurface can achieve excellent digital image classification results, and the classification accuracy of ideal phase mask plates and metasurface for phase-only modulation can reach 84.73% and 84.85%, respectively. Despite a certain loss of degrees of freedom compared to multi-layer phase mask plates, the single-layer metasurface is easier to fabricate and align, thereby improving spatial utilization efficiency.

Analysis of factors influencing college students' food waste behavior and evaluation of labor education intervention.

Background: Food waste remains a major problem for the world and food security. Despite the fact that consumers are significant producers of food waste, little research attention has been paid to college students. The present study aimed to assess food waste and the influence factors among college students. Additionally, the goal was to improve college students' food waste attitudes and behaviors through labor education. Methods: Through an online questionnaire survey, 407 college students from three universities were asked about food waste; 27 students of them were randomly selected as the research object, and labor practice was carried out in groups in the student cafeteria. Mann-Whitney U test was performed to show food waste behavior of college students and logistical regression analysis was used to analyze the factors affecting food waste behavior. Results: The results indicated that the food waste is more serious among college students in East China, senior or female students, BMI plays a positive role in food waste among college students, while monthly consumption and peers waste play a negative role in food waste. After participating in the labor education, the students' views and practices toward their peer's food waste have improved. Conclusion: The implementation of labor education in college canteens is conducive to the establishment of a correct outlook on labor as well as saving consciousness among college students, and to the formation of a social consciousness of saving.

MIR396-GRF/GIF enhances in planta shoot regeneration of Dendrobium catenatum.

Recent studies on co-transformation of the growth regulator, TaGRF4-GIF1 chimera (Growth Regulating Factor 4-GRF Interacting Factor 1), in cultivated wheat varieties (Triticum aestivum), showed improved regeneration efficiency, marking a significant breakthrough. Here, a simple and reproducible protocol using the GRF4-GIF1 chimera was established and tested in the medicinal orchid Dendrobium catenatum, a monocot orchid species. TaGRF4-GIF1 from T. aestivum and DcGRF4-GIF1 from D. catenatum were reconstructed, with the chimeras significantly enhancing the regeneration efficiency of D. catenatum through in planta transformation. Further, mutating the microRNA396 (miR396) target sites in TaGRF4 and DcGRF4 improved regeneration efficiency. The target mimicry version of miR396 (MIM396) not only boosted shoot regeneration but also enhanced plant growth. Our methods revealed a powerful tool for the enhanced regeneration and genetic transformation of D. catenatum.

The temperature sensor TWA1 is required for thermotolerance in Arabidopsis.

Plants exposed to incidences of excessive temperatures activate heat-stress responses to cope with the physiological challenge and stimulate long-term acclimation1,2. The mechanism that senses cellular temperature for inducing thermotolerance is still unclear3. Here we show that TWA1 is a temperature-sensing transcriptional co-regulator that is needed for basal and acquired thermotolerance in Arabidopsis thaliana. At elevated temperatures, TWA1 changes its conformation and allows physical interaction with JASMONATE-ASSOCIATED MYC-LIKE (JAM) transcription factors and TOPLESS (TPL) and TOPLESS-RELATED (TPR) proteins for repressor complex assembly. TWA1 is a predicted intrinsically disordered protein that has a key thermosensory role functioning through an amino-terminal highly variable region. At elevated temperatures, TWA1 accumulates in nuclear subdomains, and physical interactions with JAM2 and TPL appear to be restricted to these nuclear subdomains. The transcriptional upregulation of the heat shock transcription factor A2 (HSFA2) and heat shock proteins depended on TWA1, and TWA1 orthologues provided different temperature thresholds, consistent with the sensor function in early signalling of heat stress. The identification of the plant thermosensors offers a molecular tool for adjusting thermal acclimation responses of crops by breeding and biotechnology, and a sensitive temperature switch for thermogenetics.

Microstructural Evolution and Failure in Fibrous Network Materials: Failure Mode Transition from the Competition between Bond and Fiber.

For the complex structure of fibrous network materials, it is a challenge to analyze the network strength and deformation mechanism. Here, we identify a failure mode transition within the network material comprising brittle fibers and bonds, which is related to the strength ratio of the bond to the fiber. A failure criterion for this type of fibrous network is proposed to quantitatively characterize this transition between bond damage and fiber damage. Additionally, tensile experiments on carbon and ceramic fibrous network materials were conducted, and the experimental results show that the failure modes of these network materials satisfy the theoretical prediction. The relationship between the failure mode, the relative density of network and strength of the components is established based on finite element analysis of the 3D network model. The failure mode transforms from bond damage to fiber damage as increasing of bond strength. According to the transition of the failure modes in the brittle fibrous network, it is possible to tailor the mechanical properties of fibrous network material by balancing the competition between bond and fiber properties, which is significant for optimizing material design and engineering applications.

LncRNA NUTM2A-AS1 silencing inhibits glioma via miR-376a-3p/YAP1 axis.

The lncRNA NUTM2A-AS1 has been shown to be dysregulated in gastric cancer, while the roles in glioma is unclear. The aim of this study was to investigate the roles and potential mechanisms of lncRNA NUTM2A-AS1 in the proliferation and apoptosis of glioma cells. The StarBase software and dual luciferase reporter assay were used to identify the relationship between lncRNA NUTM2A-AS1 and miR-376a-3p, and miR-376a-3p and YAP1. The expression of lncRNA NUTM2A-AS1, miR-376a-3p, and YAP1 in human glioma cell lines was detected by qRT-PCR. MTT and flow cytometry were used to detect the effects of lncRNA NUTM2A-AS1 or miR-376a-3p on the proliferation and apoptosis of U251 and A172 cells, respectively. In addition, changes of Bax and Bcl-2 expression in glioma cells were further verified by western blotting and qRT-PCR. The results showed that the expression of lncRNA NUTM2A-AS1 was elevated in glioma cell lines, while miR-376a-3p was decreased. LncRNA NUTM2A-AS1 was negatively correlated with miR-376a-3p. Silencing of lncRNA NUTM2A-AS1 enhanced the levels of miR-376a-3p, leading to reduced cell proliferation and increased apoptosis in glioma cells. YAP1 was a direct target of miR-376a-3p, and it was negatively regulated by miR-376a-3p in U251 and A172 cells. Further mechanistic studies suggested that miR-376a-3p reduced glioma cell proliferation and increased apoptosis by inhibiting YAP1 expression. In addition, lncRNA NUTM2A-AS1 positively regulated of YAP1 expression in glioma cells. In conclusion, silencing of lncRNA NUTM2A-AS1 inhibited proliferation and induced apoptosis in human glioma cells via the miR-376a-3p/YAP1 axis.

Identification and verification of AK4 as a protective immune-related biomarker in adipose-derived stem cells and breast cancer.

Background: Breast cancer (BC) remains the most common cancer among women, and novel post-surgical reconstruction techniques, including autologous fat transplantation, have emerged. While Adipose-derived stem cells (ADSCs) are known to impact the viability of fat grafts, their influence on breast cancer progression remains unclear. This study aims to elucidate the genetic interplay between ADSCs and breast cancer, focusing on potential therapeutic targets. Methods: Using the GEO and TCGA databases, we pinpointed differentially expressed (DE) mRNAs, miRNAs, lncRNAs, and pseudogenes of ADSCs and BC. We performed functional enrichment analysis and constructed protein-protein interaction (PPI), RNA binding protein (RBP)-pseudogene-mRNA, and lncRNA-miRNA-transcription factor (TF)-gene networks. Our study delved into the correlation of AK4 expression with 33 different malignancies and examined its impact on prognostic outcomes across a pan-cancer cohort. Additionally, we scrutinized immune infiltration, microsatellite instability, and tumor mutational burden, and conducted single-cell analysis to further understand the implications of AK4 expression. We identified novel sample subtypes based on hub genes using the ConsensusClusterPlus package and examined their association with immune infiltration. The random forest algorithm was used to screen DE mRNAs between subtypes to validate the powerful prognostic prediction ability of the artificial neural network. Results: Our analysis identified 395 DE mRNAs, 3 DE miRNAs, 84 DE lncRNAs, and 26 DE pseudogenes associated with ADSCs and BC. Of these, 173 mRNAs were commonly regulated in both ADSCs and breast cancer, and 222 exhibited differential regulation. The PPI, RBP-pseudogene-mRNA, and lncRNA-miRNA-TF-gene networks suggested AK4 as a key regulator. Our findings support AK4 as a promising immune-related therapeutic target for a wide range of malignancies. We identified 14 characteristic genes based on the AK4-related cluster using the random forest algorithm. Our artificial neural network yielded excellent diagnostic performance in the testing cohort with AUC values of 0.994, 0.973, and 0.995, indicating its ability to distinguish between breast cancer and non-breast cancer cases. Conclusions: Our research sheds light on the dual role of ADSCs in BC at the genetic level and identifies AK4 as a key protective mRNA in breast cancer. We found that AK4 significantly predicts cancer prognosis and immunotherapy, indicating its potential as a therapeutic target.

[Prevalence of and risk factors for perceived absence of breast milk supply in Chinese lactating women in 2013].

OBJECTIVE: To investigate the prevalence and influencing factors of postpartum perceived absence of breast milk supply among Chinese mothers in 2013. METHODS: This is a cross-sectional study based on the data collected from children and mothers under 2 years of age in 2013 as part of the nutrition and health surveillance of Chinese residents. In this study, multistage stratified cluster sampling method was used to select subjects from 55 countires/districts in 30 provinces in China. The perceived absence of breast milk supply was defined as the mother's self-reported absence of breast milk and failure to breastfeed. Breastfeeding knowledge, maternal breastfeeding knowledge and general characteristics were collected through a structured questionnaire. Univariate analysis and Logistic regression were used to analyze the factors associated with perceived absence of breast milk supply. RESULTS: A total of 12091 mothers were included in the study, including 419 in the perceived non-breastfeeding group, the prevalence of perceived absence of breast milk supply was 3.5%. Multivariate Logistic regression showed maternal age(OR=1.04, 95%CI 1.02-1.06), postpartum hemorrhage(OR=2.03, 95%CI 1.30-3.16), and belief that breastfeeding should continue beyond 12 months of age(OR=0.27, 95%CI 0.17-0.45), not knowing how to breastfeed(OR=3.31, 95%CI: 2.31-4.74) were the main influencing factors for perceived absence of breast milk supply after delivery. CONCLUSION: Age, postpartum hemorrhage and knowledge level of breastfeeding are the main risk factors for perceived absence of breast milk supply, and knowledge level of breastfeeding is a modifiable factor.

Integrating multi-omics data reveals energy and stress signaling activated by abscisic acid in Arabidopsis.

Phytohormones are essential signaling molecules regulating various processes in growth, development, and stress responses. Genetic and molecular studies, especially using Arabidopsis thaliana (Arabidopsis), have discovered many important players involved in hormone perception, signal transduction, transport, and metabolism. Phytohormone signaling pathways are extensively interconnected with other endogenous and environmental stimuli. However, our knowledge of the huge and complex molecular network governed by a hormone remains limited. Here we report a global overview of downstream events of an abscisic acid (ABA) receptor, REGULATORY COMPONENTS OF ABA RECEPTOR (RCAR) 6 (also known as PYRABACTIN RESISTANCE 1 [PYR1]-LIKE [PYL] 12), by integrating phosphoproteomic, proteomic and metabolite profiles. Our data suggest that the RCAR6 overexpression constitutively decreases the protein levels of its coreceptors, namely clade A protein phosphatases of type 2C, and activates sucrose non-fermenting-1 (SNF1)-related protein kinase 1 (SnRK1) and SnRK2, the central regulators of energy and ABA signaling pathways. Furthermore, several enzymes in sugar metabolism were differentially phosphorylated and expressed in the RCAR6 line, and the metabolite profile revealed altered accumulations of several organic acids and amino acids. These results indicate that energy- and water-saving mechanisms mediated by the SnRK1 and SnRK2 kinases, respectively, are under the control of the ABA receptor-coreceptor complexes.

PeNAC67-PeKAN2-PeSCL23 and B-class MADS-box transcription factors synergistically regulate the specialization process from petal to lip in Phalaenopsis equestris.

The molecular basis of orchid flower development involves a specific regulatory program in which MADS-box transcription factors play a central role. The recent 'perianth code' model hypothesizes that two types of higher-order heterotetrameric complexes, namely SP complex and L complex, play pivotal roles in the orchid perianth organ formation. Therefore, we explored their roles and searched for other components of the regulatory network.Through the combined analysis for transposase-accessible chromatin with high-throughput sequencing and RNA sequencing of the lip-like petal and lip from Phalaenopsis equestris var.trilip, transcription factor-(TF) genes involved in lip development were revealed. PeNAC67 encoding a NAC-type TF and PeSCL23 encoding a GRAS-type TF were differentially expressed between the lip-like petal and the lip. PeNAC67 interacted with and stabilized PeMADS3, which positively regulated the development of lip-like petal to lip. PeSCL23 and PeNAC67 competitively bound with PeKAN2 and positively regulated the development of lip-like petal to petal by affecting the level of PeMADS3. PeKAN2 as an important TF that interacts with PeMADS3 and PeMADS9 can promote lip development. These results extend the 'perianth code' model and shed light on the complex regulation of orchid flower development.

KLF5 regulates actin remodeling to enhance the metastasis of nasopharyngeal carcinoma.

Transcription factors (TFs) engage in various cellular essential processes including differentiation, growth and migration. However, the master TF involved in distant metastasis of nasopharyngeal carcinoma (NPC) remains largely unclear. Here we show that KLF5 regulates actin remodeling to enhance NPC metastasis. We analyzed the msVIPER algorithm-generated transcriptional regulatory networks and identified KLF5 as a master TF of metastatic NPC linked to poor clinical outcomes. KLF5 regulates actin remodeling and lamellipodia formation to promote the metastasis of NPC cells in vitro and in vivo. Mechanistically, KLF5 preferentially occupies distal enhancer regions of ACTN4 to activate its transcription, whereby decoding the informative DNA sequences. ACTN4, extensively localized within actin cytoskeleton, facilitates dense and branched actin networks and lamellipodia formation at the cell leading edge, empowering cells to migrate faster. Collectively, our findings reveal that KLF5 controls robust transcription program of ACTN4 to modulate actin remodeling and augment cell motility which enhances NPC metastasis, and provide new potential biomarkers and therapeutic interventions for NPC.

Segmentation method of magnetic resonance imaging brain tumor images based on improved UNet network.

Background: Glioma is a primary malignant craniocerebral tumor commonly found in the central nervous system. According to research, preoperative diagnosis of glioma and a full understanding of its imaging features are very significant. Still, the traditional segmentation methods of image dispensation and machine wisdom are not acceptable in glioma segmentation. This analysis explores the potential of magnetic resonance imaging (MRI) brain tumor images as an effective segmentation method of glioma. Methods: This study used 200 MRI images from the affiliated hospital and applied the 2-dimensional residual block UNet (2DResUNet). Features were extracted from input images using a 2×2 kernel size (64-kernel) 1-step 2D convolution (Conv) layer. The 2DDenseUNet model implemented in this study incorporates a ResBlock mechanism within the UNet architecture, as well as a Gaussian noise layer for data augmentation at the input stage, and a pooling layer for replacing the conventional 2D convolutional layers. Finally, the performance of the proposed protocol and its effective measures in glioma segmentation were verified. Results: The outcomes of the 5-fold cross-validation evaluation show that the proposed 2DResUNet and 2DDenseUNet structure has a high sensitivity despite the slightly lower evaluation result on the Dice score. At the same time, compared with other models used in the experiment, the DM-DA-UNet model proposed in this paper was significantly improved in various indicators, increasing the reliability of the model and providing a reference and basis for the accurate formulation of clinical treatment strategies. The method used in this study showed stronger feature extraction ability than the UNet model. In addition, our findings demonstrated that using generalized die harm and prejudiced cross entropy as loss functions in the training process effectively alleviated the class imbalance of glioma data and effectively segmented glioma. Conclusions: The method based on the improved UNet network has obvious advantages in the MRI brain tumor portrait segmentation procedure. The result showed that we developed a 2D residual block UNet, which can improve the incorporation of glioma segmentation into the clinical process.

Hippuric acid alleviates dextran sulfate sodium-induced colitis via suppressing inflammatory activity and modulating gut microbiota.

Inflammatory bowel disease (IBD) is a chronic inflammatory disease associated with metabolic disorder and gut dysbiosis. Decreased abundance of hippuric acid (HA) was found in patients with IBD. HA, metabolized directly from benzoic acid in the intestine and indirectly from polyphenols, serves as a marker of polyphenol catabolism. While polyphenols and benzoic acid have been shown to alleviate intestinal inflammation, the role of HA in this context remains unknown. Herein, we investigated the effects and mechanism of HA on DSS-induced colitis mice. The results revealed that HA alleviated clinical activity and intestinal barrier damage, decreased pro-inflammatory cytokine production. Metagenomic sequencing suggested that HA treatment restored the gut microbiota, including an increase in beneficial gut bacteria such as Adlercreutzia, Eubacterium, Schaedlerella and Bifidobacterium_pseudolongum. Furthermore, we identified 113 candidate genes associated with IBD that are potentially under HA regulation through network pharmacological analyses. 10 hub genes including ALB, IL-6, HSP90AA1, and others were identified using PPI analysis and validated using molecular docking and mRNA expression analysis. Additionally, KEGG analysis suggested that the renin-angiotensin system (RAS), NF-κB signaling and Rap1 signaling pathways were important pathways in the response of HA to colitis. Thus, HA may provide novel biotherapy options for IBD.

Trajectory of gestational weight gain is related to birthweight: The TAWS cohort study in China.

Few studies have reported the timing and amount of gestational weight gain (GWG) to prevent large-for-gestational-age (LGA) or small-for-gestational-age (SGA). This study aimed to evaluate the association of GWG velocity in each trimester with LGA or SGA based on data from the Taicang and Wuqiang cohort study (TAWS, n = 2008). We used a linear mixed model to evaluate the association of trimester-specific GWG velocity with birthweight categories and stratified by prepregnancy body mass index category and parity. For normal-weight pregnant women, mothers with LGA births had higher GWG velocities than mothers with appropriate-for-gestational-age (AGA) births in the first trimester (0.108 vs. 0.031 kg/week, p < 0.01), second trimester (0.755 vs. 0.631 kg/week, p < 0.01) and third trimester (0.664 vs. 0.594 kg/week, p < 0.01); in contrast, mothers with SGA births had lower GWG velocities than mothers with AGA births in the second trimester (0.528 vs. 0.631 kg/week, p < 0.01) and third trimester (0.541 vs. 0.594 kg/week, p < 0.01). For normal-weight pregnant women with AGA births, multiparous women had lower GWG velocities than primiparous women in the second (0.602 vs. 0.643 kg/week, p < 0.01) and third trimesters (0.553 vs. 0.606 kg/week, p < 0.01). Therefore, for normal-weight women, LGA prevention would begin in early pregnancy and continue until delivery and the second and third trimesters may be critical periods for preventing SGA; in addition, among normal-weight pregnant women with AGA births, multiparous women tend to have lower weight gain velocities than primiparous women.

Dose-Incorporated Deep Ensemble Learning for Improving Brain Metastasis Stereotactic Radiosurgery Outcome Prediction.

PURPOSE: To develop a novel deep ensemble learning model for accurate prediction of brain metastasis (BM) local control outcomes after stereotactic radiosurgery (SRS). METHODS AND MATERIALS: A total of 114 brain metastases (BMs) from 82 patients were evaluated, including 26 BMs that developed biopsy-confirmed local failure post-SRS. The SRS spatial dose distribution (Dmap) of each BM was registered to the planning contrast-enhanced T1 (T1-CE) magnetic resonance imaging (MRI). Axial slices of the Dmap, T1-CE, and planning target volume (PTV) segmentation (PTVseg) intersecting the BM center were extracted within a fixed field of view determined by the 60% isodose volume in Dmap. A spherical projection was implemented to transform planar image content onto a spherical surface using multiple projection centers, and the resultant T1-CE/Dmap/PTVseg projections were stacked as a 3-channel variable. Four Visual Geometry Group (VGG-19) deep encoders were used in an ensemble design, with each submodel using a different spherical projection formula as input for BM outcome prediction. In each submodel, clinical features after positional encoding were fused with VGG-19 deep features to generate logit results. The ensemble's outcome was synthesized from the 4 submodel results via logistic regression. In total, 10 model versions with random validation sample assignments were trained to study model robustness. Performance was compared with (1) a single VGG-19 encoder, (2) an ensemble with a T1-CE MRI as the sole image input after projections, and (3) an ensemble with the same image input design without clinical feature inclusion. RESULTS: The ensemble model achieved an excellent area under the receiver operating characteristic curve (AUCROC: 0.89 ± 0.02) with high sensitivity (0.82 ± 0.05), specificity (0.84 ± 0.11), and accuracy (0.84 ± 0.08) results. This outperformed the MRI-only VGG-19 encoder (sensitivity: 0.35 ± 0.01, AUCROC: 0.64 ± 0.08), the MRI-only deep ensemble (sensitivity: 0.60 ± 0.09, AUCROC: 0.68 ± 0.06), and the 3-channel ensemble without clinical feature fusion (sensitivity: 0.78 ± 0.08, AUCROC: 0.84 ± 0.03). CONCLUSIONS: Facilitated by the spherical image projection method, a deep ensemble model incorporating Dmap and clinical variables demonstrated excellent performance in predicting BM post-SRS local failure. Our novel approach could improve other radiation therapy outcome models and warrants further evaluation.

Prognostic value of different discretization parameters in 18fluorodeoxyglucose positron emission tomography radiomics of oropharyngeal squamous cell carcinoma.

Purpose: We aim to interrogate the role of positron emission tomography (PET) image discretization parameters on the prognostic value of radiomic features in patients with oropharyngeal cancer. Approach: A prospective clinical trial (NCT01908504) enrolled patients with oropharyngeal squamous cell carcinoma (N=69; mixed HPV status) undergoing definitive radiotherapy and evaluated intra-treatment 18fluorodeoxyglucose PET as a potential imaging biomarker of early metabolic response. The primary tumor volume was manually segmented by a radiation oncologist on PET/CT images acquired two weeks into treatment (20 Gy). From this, 54 radiomic texture features were extracted. Two image discretization techniques-fixed bin number (FBN) and fixed bin size (FBS)-were considered to evaluate systematic changes in the bin number ({32, 64, 128, 256} gray levels) and bin size ({0.10, 0.15, 0.22, 0.25} bin-widths). For each discretization-specific radiomic feature space, an LASSO-regularized logistic regression model was independently trained to predict residual and/or recurrent disease. The model training was based on Monte Carlo cross-validation with a 20% testing hold-out, 50 permutations, and minor-class up-sampling to account for imbalanced outcomes data. Performance differences among the discretization-specific models were quantified via receiver operating characteristic curve analysis. A final parameter-optimized logistic regression model was developed by incorporating different settings parameterizations into the same model. Results: FBN outperformed FBS in predicting residual and/or recurrent disease. The four FBN models achieved AUC values of 0.63, 0.61, 0.65, and 0.62 for 32, 64, 128, and 256 gray levels, respectively. By contrast, the average AUC of the four FBS models was 0.53. The parameter-optimized model, comprising features joint entropy (FBN = 64) and information measure correlation 1 (FBN = 128), achieved an AUC of 0.70. Kaplan-Meier analyses identified these features to be associated with disease-free survival (p=0.0158 and p=0.0180, respectively; log-rank test). Conclusions: Our findings suggest that the prognostic value of individual radiomic features may depend on feature-specific discretization parameter settings.

Enhancing Fat Transplantation Efficiency in a Mouse Model through Pretreatment of Adipose-Derived Stem Cells with RIP3 Inhibitors.

BACKGROUND: Autologous fat transplantation, widely used in cosmetic and reparative surgery for volumetric enhancements, faces challenges with its inconsistent long-term survival rates. The technique's efficacy, crucial for its development, is hindered by unpredictable outcomes. Enriching fat grafts with adipose-derived stem cells (ADSCs) shows promise in improving survival efficiency. OBJECTIVES: This study aimed to explore the potential of receptor-interacting protein kinase 3 (RIP3) kinase inhibitors as a pretreatment for ADSCs in enhancing autologous fat graft retention over a long term. METHODS: ADSCs were isolated, cultured under normal or oxygen-glucose deprivation conditions, and mixed with particulate fat grafts to form distinct experimental groups in female nude mice. Fat graft mass and volume, along with underlying mechanisms, were evaluated using quantitative reverse transcription polymerase chain reaction (RT-qPCR), immunohistochemistry, and Western blot analysis. RESULTS: The experimental group, pretreated with RIP3 kinase inhibitors, had higher graft mass and volume, greater adipocyte integrity, and increased peroxisome proliferator-activated receptor gamma (PPARγ) mRNA levels than control groups. Furthermore, the experimental group demonstrated lower expression of necroptosis pathway proteins in the short term and an ameliorated inflammatory response as indicated by interleukin-1 beta (IL-1ß), interleukin-10 (IL-10) mRNA levels, and histological analyses. Notably, enhanced neovascularization was evident in the experimental group. CONCLUSIONS: These findings suggest that RIP3 kinase inhibitor pretreatment of ADSCs can improve fat graft survival, promote adipocyte integrity, potentially decrease inflammation, and enhance neovascularization. NO LEVEL ASSIGNED: This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .