On-chip integrated metasystem for spin-dependent multi-channel color holography.

On-chip integrated metasurface driven by in-plane guided waves is of great interests in various light-field manipulation applications such as colorful augmented reality and holographic display. However, it remains a challenge to design colorful multichannel holography by a single on-chip metasurface. Here we present metasurfaces integrated on top of a guided-wave photonic slab that achieves multi-channel colorful holographic light display. An end-to-end scheme is used to inverse design the metasurface for projecting off-chip preset multiple patterns. Particular examples are presented for customized patterns that were encoded into the metasurface with a single-cell meta-atom, working simultaneously at RGB color channels and for several different diffractive distances, with polarization dependence. Holographic images are generated at 18 independent channels with such a single-cell metasurface. The proposed design scheme is easy to implement, and the resulting device is viable for fabrication, promising plenty of applications in nanophotonics.

The added value of ultrasound imaging biomarkers to clinicopathological factors for the prediction of high-risk Oncotype DX recurrence scores in patients with breast cancer.

Background: The Oncotype DX (ODX) recurrence score (RS), a 21-gene assay, has been proven to recognize patients at high risk of recurrence (RS ≥26) who would benefit from chemotherapy. However, it has limited availability and high costs. Our study thus aimed to identify ultrasound (US) imaging biomarkers and develop a prediction model for identifying patients with a high ODX RS. Methods: In this retrospective study, consecutive patients with T1-3N0-1M0 breast cancer who were hormone receptor positive and human epidermal growth factor receptor 2 (HER2) negative who had an available ODX RS were reviewed. Patients treated from May 2012 and December 2015 were placed into a training cohort, and those treated from January 2016 to January 2017 were placed in a validation cohort. Clinicopathologic data were collected, and preoperative US scans were analyzed. Univariable and multivariable regression analyses were performed to evaluate the independent predictors for a high-risk of breast cancer in the training cohort, and a nomogram was developed and evaluated with the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). Results: A total of 363 patients were in the training cohort and 160 in the validation cohort, with the proportion with a high RS (RS 26-100) being 14% and 13.1%, respectively. Echogenic halo, enhanced posterior echo, low level of progesterone receptor (PR), and high Ki-67 index were identified as independent risk factors for high RS (all P values <0.05). The nomogram was constructed based on the combined model, which showed a better discrimination ability than did the clinicopathological model [combined model: AUC =0.95, 95% confidence interval (CI): 0.93-0.97; clinicopathological model: AUC =0.89, 95% CI: 0.86-0.92; P=0.001] and greater clinical benefit according to DCA. Furthermore, the nomogram was found to be effective in the validation cohort (AUC =0.90, 95% CI: 0.84-0.94), especially in patients with stage T1N0M0 disease (AUC =0.91, 95% CI: 0.84-0.95). Conclusions: US features may serve as valuable imaging biomarkers for the prediction of high recurrence risk in patients with T1-3N0-1M0 breast cancer and hormone receptor (HR)-positive and HER2-negative status. A nomogram incorporating PR status, Ki-67 index, and US imaging biomarkers showed a good discrimination ability in the early selection of patients at high risk of recurrence, especially in those with stage T1N0M0 disease.

Classification of congenital cataracts based on multidimensional phenotypes and its association with visual outcomes.

AIM: To establish a classification for congenital cataracts that can facilitate individualized treatment and help identify individuals with a high likelihood of different visual outcomes. METHODS: Consecutive patients diagnosed with congenital cataracts and undergoing surgery between January 2005 and November 2021 were recruited. Data on visual outcomes and the phenotypic characteristics of ocular biometry and the anterior and posterior segments were extracted from the patients' medical records. A hierarchical cluster analysis was performed. The main outcome measure was the identification of distinct clusters of eyes with congenital cataracts. RESULTS: A total of 164 children (299 eyes) were divided into two clusters based on their ocular features. Cluster 1 (96 eyes) had a shorter axial length (mean±SD, 19.44±1.68 mm), a low prevalence of macular abnormalities (1.04%), and no retinal abnormalities or posterior cataracts. Cluster 2 (203 eyes) had a greater axial length (mean±SD, 20.42±2.10 mm) and a higher prevalence of macular abnormalities (8.37%), retinal abnormalities (98.52%), and posterior cataracts (4.93%). Compared with the eyes in Cluster 2 (57.14%), those in Cluster 1 (71.88%) had a 2.2 times higher chance of good best-corrected visual acuity [<0.7 logMAR; OR (95%CI), 2.20 (1.25-3.81); P=0.006]. CONCLUSION: This retrospective study categorizes congenital cataracts into two distinct clusters, each associated with a different likelihood of visual outcomes. This innovative classification may enable the personalization and prioritization of early interventions for patients who may gain the greatest benefit, thereby making strides toward precision medicine in the field of congenital cataracts.

Assessment of the impact of residual tumors at different sites post-neoadjuvant chemotherapy on prognosis in breast cancer patients and development of a disease-free survival prediction model.

Background: Residual disease after neoadjuvant chemotherapy (NAC) in breast cancer patients predicts worse outcomes than pathological complete response. Differing prognostic impacts based on the anatomical site of residual tumors are not well studied. Objectives: The study aims to assess disease-free survival (DFS) in breast cancer patients with different residual tumor sites following NAC and to develop a nomogram for predicting 1- to 3-year DFS in these patients. Design: A retrospective cohort study. Methods: Retrospective analysis of 953 lymph node-positive breast cancer patients with residual disease post-NAC. Patients were categorized into three groups: residual disease in breast (RDB), residual disease in lymph nodes (RDN), and residual disease in both (RDBN). DFS compared among groups. Patients were divided into a training set and a validation set in a 7:3 ratio. Prognostic factors for DFS were analyzed to develop a nomogram prediction model. Results: RDB patients had superior 3-year DFS of 94.6% versus 85.2% for RDN and 81.8% for RDBN (p < 0.0001). Clinical T stage, N stage, molecular subtype, and postoperative pN stage were independently associated with DFS on both univariate and multivariate analyses. Nomogram integrating clinical tumor-node-metastasis (TNM) stage, molecular subtype, pathological response demonstrated good discrimination (C-index 0.748 training, 0.796 validation cohort), and calibration. Conclusion: The location of residual disease has prognostic implications, with nodal residuals predicting poorer DFS. The validated nomogram enables personalized DFS prediction to guide treatment decisions.

Understanding the impact of residual tumor location on prognosis after breast cancer treatment After receiving neoadjuvant chemotherapy, a treatment to shrink tumors before surgery, some breast cancer patients may still have residual tumor cells. Our study focuses on how the location of these remaining tumors ­ whether in the breast, lymph nodes, or both ­ affects the likelihood of the cancer not returning within the next 1 to 3 years. This likelihood is known as 'disease-free survival' (DFS). We analyzed data from 953 breast cancer patients who underwent neoadjuvant chemotherapy and still had residual tumors. By comparing DFS among patients with tumors remaining in different locations, we discovered that the specific location of the residual tumor significantly impacts the patient's long-term health and recovery. Additionally, we developed a predictive tool called a 'nomogram' to help doctors and patients assess the risk of cancer recurrence in the next 1 to 3 years. This tool considers various factors such as the size and type of the tumor, as well as the location and extent of the residual tumor after chemotherapy. Our research offers new insights into understanding the risk of recurrence after breast cancer treatment. This work not only enhances our comprehension of breast cancer management but also aids in devising more personalized and effective treatment strategies for patients in the future.

Evaluation of systemic medications associated with diabetic retinopathy: a nested case-control study from the UK Biobank.

AIMS: This study aims to investigate the associations between commonly used systemic medications and diabetic retinopathy (DR). METHODS: Individuals with linked primary care prescription data from the UK Biobank were included. Cases were defined as individuals with a Hospital Episode Statistics-coded or primary care recorded diagnosis of DR or self-reported DR. Controls were matched for age, sex, glycosylated haemoglobin, duration of diabetes mellitus (DM), hypertension status and cardiovascular disease status. ORs and 95% CIs were calculated using conditional univariate and multivariable logistic regression models. RESULTS: A total of 3377 case subjects with DR were included in the study and matched with 3377 control subjects. In multivariable logistic regression, increased odds of incident DR were observed for exposure to short-acting insulins (OR 1.63; 95% CI 1.22 to 2.18), medium-acting insulins (OR 2.10; 95% CI 1.60 to 2.75), sulfonylureas (OR 1.30; 95% CI 1.16 to 1.46). Instead, the use of fibrates (OR 0.71; 95% CI 0.53 to 0.94) and Cox-2 inhibitors (OR 0.68; 95% CI 0.58 to 0.79) was associated with decreased odds of incident DR. Dose-response relationships were observed for all five drug categories (all p<0.05). CONCLUSIONS: This study comprehensively investigated the associations between systemic medication use and DR and found significant associations between the use of short-acting insulins, medium-acting insulins and sulfonylureas with increased odds of incident DR. In contrast, fibrates and Cox-2 inhibitors were associated with decreased odds of incident DR. These findings may provide valuable insights into DM medication management and serve as a reference for the prevention of DR in patients with DM.

Association between triglyceride glucose-body mass index and long-term adverse outcomes of heart failure patients with coronary heart disease.

BACKGROUND: The triglyceride glucose-body mass index (TyG-BMI) is recognized as a reliable surrogate for evaluating insulin resistance and an effective predictor of cardiovascular disease. However, the link between TyG-BMI index and adverse outcomes in heart failure (HF) patients remains unclear. This study examines the correlation of the TyG-BMI index with long-term adverse outcomes in HF patients with coronary heart disease (CHD). METHODS: This single-center, prospective cohort study included 823 HF patients with CHD. The TyG-BMI index was calculated as follows: ln [fasting triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2] × BMI. To explore the association between the TyG-BMI index and the occurrences of all-cause mortality and HF rehospitalization, we utilized multivariate Cox regression models and restricted cubic splines with threshold analysis. RESULTS: Over a follow-up period of 9.4 years, 425 patients died, and 484 were rehospitalized due to HF. Threshold analysis revealed a significant reverse "J"-shaped relationship between the TyG-BMI index and all-cause mortality, indicating a decreased risk of all-cause mortality with higher TyG-BMI index values below 240.0 (adjusted model: HR 0.90, 95% CI 0.86-0.93; Log-likelihood ratio p = 0.003). A distinct "U"-shaped nonlinear relationship was observed with HF rehospitalization, with the inflection point at 228.56 (adjusted model: below: HR 0.95, 95% CI 0.91-0.98; above: HR 1.08, 95% CI 1.03-1.13; Log-likelihood ratio p < 0.001). CONCLUSIONS: This study reveals a nonlinear association between the TyG-BMI index and both all-cause mortality and HF rehospitalization in HF patients with CHD, positioning the TyG-BMI index as a significant prognostic marker in this population.

Effect and mechanism of C-terminal cysteine on the properties of HEV p222 protein.

Preliminary investigations have demonstrated that the cysteines located at the C-terminus of HEV ORF2 protein exhibits disulfide bonding capability during virus-like particles (VLPs) assembly. However, the effect and mechanism underlying the pairing of disulfide bonds formed by C627, C630, and C638 remains unclear. The p222 protein encompasses C-terminus and serves as a representative of HEV ORF2 to investigate the specific impacts of C627, C630, and C638. The three cysteines were subjected to site-directed mutagenesis and expressed in prokaryotes; Both the mutated proteins and p222 underwent polymerization except for p222A; Surprisingly, only p222 was observed as abundant spherical particles under transmission electron microscope (TEM); Stability and immunogenicity of the p222 exhibited higher than other mutated proteins; LC/MS/MS analysis identified four disulfide bonds in the p222. The novel findings suggest that the three cysteines contribute to structural and functional properties of ORF2 protein, highlighting the indispensability of each cysteine.

Robust Epileptic Seizure Detection Based on Biomedical Signals Using an Advanced Multi-View Deep Feature Learning Approach.

Epilepsy is a neurological disorder characterized by abnormal neuronal discharges that manifest in life-threatening seizures. These are often monitored via EEG signals, a key aspect of biomedical signal processing (BSP). Accurate epileptic seizure (ES) detection significantly depends on the precise identification of key EEG features, which requires a deep understanding of the data's intrinsic domain. Therefore, this study presents an Advanced Multi-View Deep Feature Learning (AMV-DFL) framework based on machine learning (ML) technology to enhance the detection of relevant EEG signal features for ES. Our method initially applies a fast Fourier transform (FFT) to EEG data for traditional frequency domain feature (TFD-F) extraction and directly incorporates time domain (TD) features from the raw EEG signals, establishing a comprehensive traditional multi-view feature (TMV-F). Deep features are subsequently extracted autonomously from optimal layers of one-dimensional convolutional neural networks (1D CNN), resulting in multi-view deep features (MV-DF) integrating both time and frequency domains. A multi-view forest (MV-F) is an interpretable rule-based advanced ML classifier used to construct a robust, generalized classification. Tree-based SHAP explainable artificial intelligence (T-XAI) is incorporated for interpreting and explaining the underlying rules. Experimental results confirm our method's superiority, surpassing models using TMV-FL and single-view deep features (SV-DF) by 4% and outperforming other state-of-the-art methods by an average of 3% in classification accuracy. The AMV-DFL approach aids clinicians in identifying EEG features indicative of ES, potentially discovering novel biomarkers, and improving diagnostic capabilities in epilepsy management.

NREP, transcriptionally upregulated by HIF-1α, aggravates breast cancer cell growth and metastasis by promoting glycolysis.

Breast cancer (BC) poses a great threat to women's health. Neuronal regeneration related protein (NREP) is a multifunctional protein that is involved in embryonic development, regeneration, and human disease. However, the biological function of NREP in tumors is rarely reported and its role in BC remains unknown. Bioinformatics analysis showed that NREP is highly expressed and closely correlated with poor survival in BC patients. Under hypoxic conditions, NREP was upregulated in BC cells, and this promotion was reversed by hypoxia-inducible factor HIF-1α suppression. Luciferase reporter system and chromatin immunoprecipitation assays confirmed that HIF-1α directly binds to the promoter of NREP to increase the transcriptional activity of NREP. NREP suppression inhibited cell proliferation, arrested the cell cycle at the G1/S phase, and promoted apoptosis and caspase-3 activity in BC cells. Suppression of NREP decreased the tube formation ability of HUVECs. In addition, NREP downregulation showed an inhibition effect on cell migration, invasion, and EMT of BC cells. In NREP overexpressed cells, all these changes were reversed. In vivo, animal experiments also confirmed that NREP promotes BC tumor growth and metastasis. In addition, NREP promoted cellular glycolysis and enhanced the levels of glucose consumption, ATP, lactate production, and glucose transporters expression in NREP-overexpressed BC cells. In summary, our results demonstrated that NREP could be transcriptional activated by HIF-1α, which may aggravate BC tumor growth and metastasis by promoting cellular glycolysis. This result suggested that NREP may play an essential part in BC progression.

Changes in corneal endothelial cells after scleral-sutured fixation of intraocular lens in children with congenital ectopia lentis: a 2-year follow-up.

PURPOSE: To investigate the changing patterns of corneal endothelial cells and the associated factors in children with congenital ectopia lentis (CEL) after scleral-sutured fixation of intraocular lens (SSFIOL). SETTING: Zhongshan ophthalmic center, Guangzhou, China. DESIGN: Retrospective study. METHODS: Patients were divided into the surgery group and the control group. Central endothelial cell density (ECD), coefficient of variation in cell size (CV), the percentage of hexagonal cells (hexagonality, HEX), average cell size (AVG) and central corneal thickness (CCT) were analyzed for both group at baseline and each follow-up visit. Clinic characteristic, ocular parameters, IOL decentration and IOL tilt of patients in the surgery group were collected. Multiple linear regression was performed to assess the potential associated factors for the postoperative changes in corneal endothelial cells in the surgery group. RESULTS: After 2-year follow-up, the decline of ECD was 17.8% (95%CI: -21.8 to -13.9) in the surgery group and -3.1% (95%CI: -5.2 to -1.0) in the control group(P<0.001), while the increase of AVG was 24.3%(17.1to 31.6) in the surgery group and 2.7%(1.0 to 4.5) in the control group (P<0.001). Multivariate analysis showed that AL≥24mm and WTW<12.2mm were significantly associated with greater loss of ECD (ß=-241.41, 95% CI: -457.91 to -24.91, P=0.030 and ß=251.63, 95% CI: 42.10 to 461.17,P=0.020, respectively) and AL≥ 24mm was significantly positively associated with the increase of AVG (ß=34.81, 95% CI: 0.90 to 68.71, P=0.044). CONCLUSIONS: SSFIOL has a significant impact on corneal endothelium in children with CEL. More attention should be paid to monitor postoperative corneal endothelium change during long-term follow-up in CEL children, especially for those with longer AL and smaller WTW.

A nomogram for predicting pathologic node negativity after neoadjuvant chemotherapy in breast cancer patients: a nationwide, multicenter retrospective cohort study (CSBrS-012).

Purpose: This study aimed to investigate the factors associated with pathologic node-negativity (ypN0) in patients who received neoadjuvant chemotherapy (NAC) to develop and validate an accurate prediction nomogram. Methods: The CSBrS-012 study (2010-2020) included female patients with primary breast cancer treated with NAC followed by breast and axillary surgery in 20 hospitals across China. In the present study, 7,711 eligible patients were included, comprising 6,428 patients in the primary cohort from 15 hospitals and 1,283 patients in the external validation cohort from five hospitals. The hospitals were randomly assigned. The primary cohort was randomized at a 3:1 ratio and divided into a training set and an internal validation set. Univariate and multivariate logistic regression analyses were performed on the training set, after which a nomogram was constructed and validated both internally and externally. Results: In total, 3,560 patients (46.2%) achieved ypN0, and 1,558 patients (20.3%) achieved pathologic complete response in the breast (bpCR). A nomogram was constructed based on the clinical nodal stage before NAC (cN), ER, PR, HER2, Ki67, NAC treatment cycle, and bpCR, which were independently associated with ypN0. The area under the receiver operating characteristic curve (AUC) for the training set was 0.80. The internal and external validation demonstrated good discrimination, with AUCs of 0.79 and 0.76, respectively. Conclusion: We present a real-world study based on nationwide large-sample data that can be used to effectively screen for ypN0 to provide better advice for the management of residual axillary disease in breast cancer patients undergoing NAC.

Leveraging diffusion models for unsupervised out-of-distribution detection on image manifold.

Out-of-distribution (OOD) detection is crucial for enhancing the reliability of machine learning models when confronted with data that differ from their training distribution. In the image domain, we hypothesize that images inhabit manifolds defined by latent properties such as color, position, and shape. Leveraging this intuition, we propose a novel approach to OOD detection using a diffusion model to discern images that deviate from the in-domain distribution. Our method involves training a diffusion model using in-domain images. At inference time, we lift an image from its original manifold using a masking process, and then apply a diffusion model to map it towards the in-domain manifold. We measure the distance between the original and mapped images, and identify those with a large distance as OOD. Our experiments encompass comprehensive evaluation across various datasets characterized by differences in color, semantics, and resolution. Our method demonstrates strong and consistent performance in detecting OOD images across the tested datasets, highlighting its effectiveness in handling images with diverse characteristics. Additionally, ablation studies confirm the significant contribution of each component in our framework to the overall performance.

Schisandrin B protect inner hair cells from cisplatin by inhibiting celluar oxidative stress and apoptosis.

Cisplatin is an effective chemotherapeutic agent; however, ototoxicity is one of its negative effects that greatly limits the use of cisplatin in clinical settings. Previous research has shown that the most important process cisplatin damage to inner ear cells, such as hair cells (HCs), is the excessive production and accumulation of ROS. Schisandrin B (SchB), is a low-toxicity, inexpensive, naturally occurring antioxidant with a variety of pharmacological effects. Therefore, the potential antioxidant effects of SchB may be useful for cisplatin ototoxicity treatment. In this study, the effects of SchB on cochlear hair cell viability, ROS levels, and expression of apoptosis-related molecules were evaluated by CCK-8, immunofluorescence, flow cytometry, and qRT-PCR, as well as auditory brainstem response (ABR) and dysmorphic product otoacoustic emission (DPOAE) tests to assess the effects on inner ear function. The results showed that SchB treatment increased cell survival, prevented apoptosis, and reduced cisplatin-induced ROS formation. SchB treatment reduced the loss of cochlear HCs caused by cisplatin in exosome culture. In addition, SchB treatment attenuated cisplatin-induced hearing loss and HC loss in mice. This study demonstrates the ability of SchB to inhibit cochlear hair cell apoptosis and ROS generation and shows its potential therapeutic effect on cisplatin ototoxicity.

Hybrid Surface Modification and Bulk Doping Enable Spent LiCoO2 Cathodes for High-voltage Operation.

The emerging market demand for high-energy-density of energy storage devices has been pushing the disposal of end-of-life LiCoO2 (LCO) to shift toward sustainable upgrading into structurally stable high-voltage cathode materials. Herein, an integrated bulk and surface commodification strategy has been proposed to render spent LCO (S-LCO) to operate at high voltages, involving bulk Mn doping, near surface P gradient doping and Li3PO4/CoP (LPO/CP) coating on the LCO surface to yield upcycled LCO (defined as MP-LCO@LPO/CP). Benefiting from hybrid surface coating with Li+-conductive Li3PO4 and electron conductive CoP coupled with Mn and P co-doping, the optimized MP-LCO@LPO/CP cathode exhibits enhanced high-voltage performance, delivering an initial discharge capacity of 218.8 mAh g-1 at 0.2 C with excellent capacity retention of 80.9% (0.5 C) after 200 cycles at a cut-off voltage of 4.6 V, along with 96.3% of capacity retention over 100 cycles at 4.5 V. Our findings might afford meaningful construction for the upcycling of commercial S-LCO into next-generation upmarket cathode materials through the elaborate surface and bulk modification design. This article is protected by copyright. All rights reserved.

The use of longitudinal CT-based radiomics and clinicopathological features predicts the pathological complete response of metastasized axillary lymph nodes in breast cancer.

BACKGROUND: Accurate assessment of axillary status after neoadjuvant therapy for breast cancer patients with axillary lymph node metastasis is important for the selection of appropriate subsequent axillary treatment decisions. Our objectives were to accurately predict whether the breast cancer patients with axillary lymph node metastases could achieve axillary pathological complete response (pCR). METHODS: We collected imaging data to extract longitudinal CT image features before and after neoadjuvant chemotherapy (NAC), analyzed the correlation between radiomics and clinicopathological features, and developed models to predict whether patients with axillary lymph node metastasis can achieve axillary pCR after NAC. The clinical utility of the models was determined via decision curve analysis (DCA). Subgroup analyses were also performed. Then, a nomogram was developed based on the model with the best predictive efficiency and clinical utility and was validated using the calibration plots. RESULTS: A total of 549 breast cancer patients with metastasized axillary lymph nodes were enrolled in this study. 42 independent radiomics features were selected from LASSO regression to construct a logistic regression model with clinicopathological features (LR radiomics-clinical combined model). The AUC of the LR radiomics-clinical combined model prediction performance was 0.861 in the training set and 0.891 in the testing set. For the HR + /HER2 - , HER2 + , and Triple negative subtype, the LR radiomics-clinical combined model yields the best prediction AUCs of 0.756, 0.812, and 0.928 in training sets, and AUCs of 0.757, 0.777 and 0.838 in testing sets, respectively. CONCLUSIONS: The combination of radiomics features and clinicopathological characteristics can effectively predict axillary pCR status in NAC breast cancer patients.

Synthesis and characterisation of K2CO3-activated carbon produced from distilled spent grains for the adsorption of CO2.

Activated carbon was prepared from distilled spent grains (DSG) using K2CO3 activation and chitosan modification. The effects of activator dosage, activation temperature, and the incorporation of chitosan as a nitrogen source on the adsorption performance were studied in this paper. The activated carbons were characterised by scanning electron microscopy, X-ray photoelectron spectroscopy, and nitrogen and carbon dioxide gas adsorption. Under the optimal conditions, the BET-specific surface area, total pore volume, and microporous volume of the activated carbon were as high as 1142 m2/g, 0.62 cm3/g, and 0.40 cm3/g, respectively. Chitosan was used as the nitrogen source, and surface modification was carried out concurrently with the K2CO3 activation process. The results revealed a carbon dioxide adsorption capacity of 5.2 mmol/g at 273.15 K and 1 bar without a nitrogen source, which increased to 5.76 mmol/g after chitosan modification. The isosteric heat of adsorption of CO2 all exceed 20 kJ/mol, hinting at the coexistence of both physisorption and chemisorption. The adsorption behaviour of the DSG-based activated carbon can be well-described by the Freundlich model.

Association Between Preoperative Ocular Parameters and Myopic Shift in Children Undergoing Primary Intraocular Lens Implantation.

Purpose: To evaluate the association between preoperative ocular parameters and myopic shift following primary intraocular lens (IOL) implantation in pediatric cataracts. Methods: Eyes from pediatric patients undergoing bilateral cataract surgery with primary IOL implantation were included. Eyes were grouped by age at surgery and subdivided into three axial length (AL) subgroups and three keratometry subgroups. Mixed-effects linear regression was utilized to assess the trend in myopic shift among subgroups. Multivariable analysis was performed to determine factors associated with myopic shift. Results: A total of 222 eyes were included. The median age at surgery was 4.36 years (interquartile range [IQR], 3.16-6.00 years) and the median follow-up was 4.18 years (IQR, 3.48-4.64 years). As preoperative AL increased, a decreased trend was observed in myopic shift and rate of myopic shift (P = 0.008 and P = 0.003, respectively, in the 4 to <6 years old group; P = 0.002 and P < 0.001, respectively, in the ≥6 years old group). Greater myopic shift and rate of myopic shift were associated with younger age at surgery (P = 0.008 and P = 0.008, respectively). Both myopic shift and rate of myopic shift were negatively associated with AL. Conclusions: Age at surgery and preoperative AL were associated with myopic shift in pediatric cataracts following primary IOL implantation. Adjusting the target refraction based on preoperative AL could potentially improve patients' long-term refractive outcome. Translational Relevance: This study may help to guide the selection of postoperative target refraction according to age at surgery and preoperative ocular parameters for pediatric cataracts.

Targeted axillary dissection after neoadjuvant chemotherapy for highly selective patients with initial cN1 breast cancer: A single-center prospective trial.

BACKGROUND: Sentinel lymph node (SLN) biopsy is gradually accepted as the standard of care in breast cancer patients with down-staged axillary disease after neoadjuvant chemotherapy (NAC). However, it is still difficult to precisely define pre-NAC clinical node-positive (cN1) and post-NAC clinical node-negative (ycN0). This prospective single-center trial was designed to evaluate the feasibility and accuracy of standard targeted axillary dissection (TAD) after NAC in highly selective pre-NAC cN1 patients (not considering ultrasound-based axillary ycN staging). METHODS: This prospective trial included patients with initial pre-NAC cT1-3N1M0 invasive breast cancer but with a rigorous definition of cN1 from the Affiliated Cancer Hospital of Zhengzhou University. When NAC was effective (including complete and partial responses) and preoperative axillary palpation was negative, preoperative ultrasound-based axillary staging was not considered, and all patients underwent TAD followed by axillary lymph node (LN) dissection. The detection rate (DR) and false-negative rate (FNR) of TAD were calculated. RESULTS: A total of 82 patients were included, and 77 of them were eligible for data analysis. The DR for TAD was 94.8% (73/77). There were 26 patients with one abnormal LN at the time of diagnosis based on ultrasound, 45 patients with two, and 2 patients with three. One patient had one TAD LN, four patients had two TAD LNs, and 68 patients had three or more TAD LNs. Preoperative axillary palpation yielded negative results for all 73 patients who successfully underwent TAD. Preoperative ultrasound-based ycN0 and ycN+ conditions were detected for 52 and 21 cases, respectively. The FNR was 7.4% (2/27) for standard TAD (≥3 SLNs), which was lower than that of all successful TAD (≥1 SLN; 10.0%, 3/30). CONCLUSIONS: In rigorously defined pre-NAC cN1 breast cancer patients, standard TAD is feasible for those with negative axillary palpation after NAC, and FNR is also less than 10%. REGISTRATION: chictr.org.cn, ChiCTR2100049093.

RUNX1-BMP2 promotes vasculogenic mimicry in laryngeal squamous cell carcinoma via activation of the PI3K-AKT signaling pathway.

BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumors of the head and neck. Vasculogenic mimicry (VM) is crucial for tumor growth and metastasis and refers to the formation of fluid channels by invasive tumor cells rather than endothelial cells. However, the regulatory mechanisms underlying VM during the malignant progression of LSCC remain largely unknown. METHODS: Gene expression and clinical data for LSCC were obtained from the TCGA and Gene GEO (GSE27020) databases. A risk prediction model associated with VM was established using LASSO and Cox regression analyses. Based on their risk scores, patients with LSCC were categorized into high- and low-risk groups. The disparities in immune infiltration, tumor mutational burden (TMB), and functional enrichment between these two groups were examined. The core genes in LSCC were identified using the machine learning (SVM-RFE) and WGCNA algorithms. Subsequently, the involvement of bone morphogenetic protein 2 (BMP2) in VM and metastasis was investigated both in vitro and in vivo. To elucidate the downstream signaling pathways regulated by BMP2, western blotting was performed. Additionally, ChIP experiments were employed to identify the key transcription factors responsible for modulating the expression of BMP2. RESULTS: We established a new precise prognostic model for LSCC related to VM based on three genes: BMP2, EPO, and AGPS. The ROC curves from both TCGA and GSE27020 validation cohorts demonstrated precision survival prediction capabilities, with the nomogram showing some net clinical benefit. Multiple algorithm analyses indicated BMP2 as a potential core gene. Further experiments suggested that BMP2 promotes VM and metastasis in LSCC. The malignant progression of LSCC is promoted by BMP2 via the activation of the PI3K-AKT signaling pathway, with the high expression of BMP2 in LSCC resulting from its transcriptional activation by runt-related transcription factor 1 (RUNX1). CONCLUSION: BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1. BMP2 may be a novel, precise, diagnostic, and therapeutic biomarker of LSCC.

Prognostic value of growth differentiation factor-15 in heart failure among whole ejection fraction phenotypes.

AIMS: The utility of growth differentiation factor-15 (GDF-15) in predicting long-term adverse outcomes in heart failure (HF) patients is not well established. This study explored the relationship between GDF-15 levels and adverse outcomes in HF patients across various ejection fraction (EF) phenotypes associated with coronary heart disease (CHD) and evaluated the added prognostic value of incorporating GDF-15 into the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score-based model. METHODS AND RESULTS: This single-centre cohort study included 823 HF patients, categorized into 230 (27.9%) reduced EF (HFrEF), 271 (32.9%) mid-range EF (HFmrEF), and 322 (39.1%) preserved EF (HFpEF) groups. The median age was 68.0 years (range: 56.0-77.0), and 245 (29.8%) were females. Compared with the HFrEF and HFmrEF groups, the HFpEF group had a higher GDF-15 concentration (P = 0.002) and a higher MAGGIC risk score (P < 0.001). We examined the associations between GDF-15 levels and the risks of all-cause mortality and HF rehospitalization using Cox regression models. The C-index, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) metrics were employed to assess the incremental prognostic value. During the 9.4 year follow-up period, 425 patients died, and 484 were rehospitalized due to HF. Multivariate Cox regression analysis revealed that elevated GDF-15 levels were significantly associated with an increased risk of all-cause mortality [hazard ratio (HR) = 1.36, 95% confidence interval (CI): 1.20-1.54; P < 0.001] and HF rehospitalization (HR = 1.75, 95% CI: 1.57-1.95; P < 0.001) across all HF phenotypes. This association remained significant when GDF-15 was treated as a categorical variable (high GDF-15 group: all-cause death: HR = 1.73, 95% CI: 1.40-2.14; P < 0.001; HF rehospitalization: HR = 3.37, 95% CI: 2.73-4.15; P < 0.001). Inclusion of GDF-15 in the MAGGIC risk score-based model provided additional prognostic value for all HF patients (Δ C-index = 0.021, 95% CI: 0.002-0.041; IDI = 0.011, 95% CI: 0.001-0.025; continuous NRI = 0.489, 95% CI: 0.174-0.629) and HF rehospitalization (Δ C-index = 0.034, 95% CI: 0.005-0.063; IDI = 0.021, 95% CI: 0.007-0.032; continuous NRI = 0.307, 95% CI: 0.147-0.548), particularly in the HFpEF subgroup. CONCLUSIONS: GDF-15 is identified as an independent risk factor for adverse outcomes in HF patients across the entire EF spectrum in the context of CHD. Integrating GDF-15 into the MAGGIC risk score-based model enhances its prognostic capability for adverse outcomes in the general HF population. This incremental prognostic effect was observed specifically in the HFpEF subgroup and not in other subgroups.