Label-Free Multiplex Profiling of Exosomal Proteins with a Deep Learning-Driven 3D Surround-Enhancing SERS Platform for Early Cancer Diagnosis.

Identification of protein profiling on plasma exosomes by SERS can be a promising strategy for early cancer diagnosis. However, it is still challenging to detect multiple exosomal proteins simultaneously by SERS since the Raman signals of exosomes detected by conventional colloidal nanocrystals or two-dimensional SERS substrates are incomplete and complex. Herein, we develop a novel three-dimensional (3D) surround-enhancing SERS platform, named 3D se-SERS, for the multiplex detection of exosomal proteins. In this 3D se-SERS, proteins and exosomes are covered with "hotspots" generated by the gold nanoparticles, which surround the analytes densely and three-dimensionally, providing sensitive and comprehensive SERS signals. Combining this 3D se-SERS with a deep learning model, we successfully quantitatively profiled seven proteins including CD63, CD81, CD9, CD151, CD171, TSPAN8, and PD-L1 on the surface of plasma exosomes from patients, which can predict the occurrence and advancement of lung cancer. This 3D se-SERS integrating deep learning technique benefits from high sensitivity and significant multiplexing ability for comprehensive analysis of proteins and exosomes, demonstrating the potential of deep learning-driven 3D se-SERS technology for plasma exosome-based early cancer diagnosis.

Who Are the Anatomic Outliers Undergoing Total Knee Arthroplasty? A Computed Tomography-Based Analysis of the Hip-Knee-Ankle Axis Across 1,352 Preoperative Computed Tomographies Using a Deep Learning and Computer Vision-Based Pipeline.

BACKGROUND: Dissatisfaction after total knee arthroplasty (TKA) ranges from 15 to 30%. While patient selection may be partially responsible, morphological and reconstructive challenges may be determinants. Preoperative computed tomography (CT) scans for TKA planning allow us to evaluate the hip-knee-ankle axis and establish a baseline phenotypic distribution across anatomic parameters. The purpose of this cross-sectional analysis was to establish the distributions of 27 parameters in a pre-TKA cohort and perform threshold analysis to identify anatomic outliers. METHODS: There were 1,352 pre-TKA CTs that were processed. A 2-step deep learning pipeline of classification and segmentation models identified landmark images and then generated contour representations. We used an open-source computer vision library to compute measurements for 27 anatomic metrics along the hip-knee axis. Normative distribution plots were established, and thresholds for the 15th percentile at both extremes were calculated. Metrics falling outside the central 70th percentile were considered outlier indices. A threshold analysis of outlier indices against the proportion of the cohort was performed. RESULTS: Significant variation exists in pre-TKA anatomy across 27 normally distributed metrics. Threshold analysis revealed a sigmoid function with a critical point at 9 outlier indices, representing 31.2% of subjects as anatomic outliers. Metrics with the greatest variation related to deformity (tibiofemoral angle, medial proximal tibial angle, lateral distal femoral angle), bony size (tibial width, anteroposterior femoral size, femoral head size, medial femoral condyle size), intraoperative landmarks (posterior tibial slope, transepicondylar and posterior condylar axes), and neglected rotational considerations (acetabular and femoral version, femoral torsion). CONCLUSIONS: In the largest non-industry database of pre-TKA CTs using a fully automated 3-stage deep learning and computer vision-based pipeline, marked anatomic variation exists. In the pursuit of understanding the dissatisfaction rate after TKA, acknowledging that 31% of patients represent anatomic outliers may help us better achieve anatomically personalized TKA, with or without adjunctive technology.

A novel lysosome-targeted fluorescent probe for precise formaldehyde detection in water samples, living cells and breast cancer tumors.

This study investigated the potential ability of the fluorescent probe Ly-CHO to detect formaldehyde (FA) in living cells and tumor-bearing mice. Ly-CHO exhibited great selectivity, excellent sensitivity, and rapid response to FA, making it a valuable tool for tracking FA concentration changes. The probe was also found to target lysosomes specifically. Furthermore, Ly-CHO showed an obvious fluorescence increase in endogenous CHO detection after adding tetrahydrogen folic acid (THFA). This study validated Ly-CHO's possibility for FA imaging in vivo, with potential applications in understanding formaldehyde-related diseases.

Tomographic FLEET with a wedge array for multi-point three-component velocimetry.

Femtosecond laser electronic excitation tagging (FLEET) velocimetry is an important diagnostic technique for seedless velocimetry measurements particularly in supersonic and hypersonic flows. Typical FLEET measurements feature a single laser line and camera system to achieve one-component velocimetry along a line, although some multiple-spot and multiple-component configurations have been demonstrated. In this work, tomographic imaging is used to track the three-dimensional location of many FLEET spots. A quadscope is used to combine four unique views onto a single high-speed image intensifier and camera. Tomographic reconstructions of the FLEET emission are analyzed for three-component velocimetry from multiple FLEET spots. Glass wedges are used to create many (nine) closely spaced FLEET spots with less than 10% transmission losses. These developments lead to a significant improvement in the dimensionality and spatial coverage of a FLEET instrument with some increases in experimental complexity and data processing. Multiple-point three-component FLEET velocimetry is demonstrated in an underexpanded jet.

Predicting the unpredictable: a robust nomogram for predicting recurrence in patients with ampullary carcinoma.

OBJECTIVE: To screen the risk factors affecting the recurrence risk of patients with ampullary carcinoma (AC)after radical resection, and then to construct a model for risk prediction based on Lasso-Cox regression and visualize it. METHODS: Clinical data were collected from 162 patients that received pancreaticoduodenectomy treatment in Hebei Provincial Cancer Hospital from January 2011 to January 2022. Lasso regression was used in the training group to screen the risk factors for recurrence. The Lasso-Cox regression and Random Survival Forest (RSF) models were compared using Delong test to determine the optimum model based on the risk factors. Finally, the selected model was validated using clinical data from the validation group. RESULTS: The patients were split into two groups, with a 7:3 ratio for training and validation. The variables screened by Lasso regression, such as CA19-9/GGT, AJCC 8th edition TNM staging, Lymph node invasion, Differentiation, Tumor size, CA19-9, Gender, GPR, PLR, Drinking history, and Complications, were used in modeling with the Lasso-Cox regression model (C-index = 0.845) and RSF model (C-index = 0.719) in the training group. According to the Delong test we chose the Lasso-Cox regression model (P = 0.019) and validated its performance with time-dependent receiver operating characteristics curves(tdROC), calibration curves, and decision curve analysis (DCA). The areas under the tdROC curves for 1, 3, and 5 years were 0.855, 0.888, and 0.924 in the training group and 0.841, 0.871, and 0.901 in the validation group, respectively. The calibration curves performed well, as well as the DCA showed higher net returns and a broader range of threshold probabilities using the predictive model. A nomogram visualization is used to display the results of the selected model. CONCLUSION: The study established a nomogram based on the Lasso-Cox regression model for predicting recurrence in AC patients. Compared to a nomogram built via other methods, this one is more robust and accurate.

Effect of e-learning program for improving nurse knowledge and practice towards managing pressure injuries: A systematic review and meta-analysis.

AIM: The aim of this review was to determine the effectiveness of the e-learning programs for improving the knowledge and professional practices of nursing personnel in managing pressure injuries patients. DESIGN: Systematic review and meta-analysis. METHODS: Systematic search was done in EMBASE, SCOPUS, Cochrane library, MEDLINE, Google Scholar, ScienceDirect and Clinicaltrials.gov databases until August 2022. Meta-analysis was carried out using random-effects model, and the results were reported as pooled standardized mean differences (SMD), or odds ratios (OR) with 95% confidence intervals (CIs). RESULTS: Eight studies were included in the analysis. Most of the studies had higher risk of bias. The pooled SMD for knowledge score and for the classification skill were 1.40 (95%CI: 0.45-2.35; I2 = 93.1%) and 1.75 (95%CI: 0.94-3.24; I2 = 78.3%) respectively. The pooled OR for the classification skills was 1.75 (95%CI: 0.94-3.24; I2 = 78.3%). PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

[Spatial and Temporal Evolution and Prediction of Carbon Storage in Kunming City Based on InVEST and CA-Markov Model].

Land use/cover change is an important driving factor for carbon stock changes in terrestrial ecosystems and affects the carbon cycle of the whole ecosystem. Taking Kunming City as a case study, based on the modified carbon density coefficient, this study analyzed the spatio-temporal characteristics of carbon storage changes in the terrestrial ecosystem under different land use scenarios from 2000 to 2020 and "three-line" constraints by coupling the carbon storage module of the InVEST model and CA-Markov model. The results showed that:① cultivated land, forest land, and grassland were the main types of land use in Kunming City, and land use transfer also occurred among the three types. ② From 2000 to 2020, the overall carbon storage in Kunming City was low in the south and high in the north, and the carbon storage decreased yearly with a cumulative loss of 5.27×106 t. The degradation of forest land and grassland was the main reason for the decrease in carbon storage. ③ From 2020 to 2030, the carbon storage of the four scenarios should decrease, and the decline in carbon storage in the inertia development scenario was the most obvious, which was mainly caused by the rapid expansion of construction land. The cultivated land protection scenario effectively slowed down the reduction in carbon storage compared with the inertia development scenario. The ecological protection scenario could enhance the carbon sequestration capacity of the study area, with carbon storage reaching 262.49×106 t, but could not effectively control the reduction in cultivated land area. The scenario of preventing urban expansion effectively inhibited the disorderly expansion of construction land and indirectly prevented further reduction in carbon storage. Therefore, the cultivated land protection scenario, ecological protection scenario, and urban expansion prevention scenario can be considered comprehensively in the study area, which could not only increase the carbon sink space of the study area but also ensure food and ecological security.

Evaluation of a biomarker (NO) dynamics in inflammatory zebrafish and periodontitis saliva samples via a fast-response and sensitive fluorescent probe.

Many pathological processes include nitric oxide (NO), a signaling transduction molecule. Tumors, cardiovascular, cerebrovascular, neurodegenerative, and other illnesses are linked to abnormal NO levels. Thus, evaluating NO levels in vitro and in vivo is crucial for studying chemical biology process of associated disorders. This work devised and manufactured a coumarin-based fluorescent probe ZPS-NO to detect nitric oxide (NO). The reaction between ZPS-NO and NO produced a highly selective and sensitive optical response that caused a powerful fluorescence "turn-on" effect with a ultra-low NO detection limit of 14.5 nM. Furthermore, the probe was applied to sense and image NO in living cells and inflammatory model of zebrafish, as well as to detect NO in periodontitis patients' saliva samples. We anticipate that probe ZPS-NO will serve as a practical and effective tool for assessing the interactions and evaluation of periodontitis development.

Factors Influencing Noise Following Primary Ceramic-on-Ceramic Total Hip Arthroplasty.

BACKGROUND: The noise associated with ceramic-on-ceramic (CoC) total hip arthroplasty (THA) has been a concerning issue, while its underlying causes remain unclear. METHODS: We conducted a retrospective analysis of 119 patients (174 primary CoC THAs) who had a mean follow-up of 28 months (range, 12 to 106). A questionnaire was designed to collect information on nature, frequency, onset, duration, and impact of the noise. Postoperative x-rays were evaluated. Clinical evaluations, including Harris and Oxford hip scores, were documented at follow-up time points (6 weeks, 3 months, 6 months, and 1 year). RESULTS: Of the 174 hips, 31.6% reported noise, including 26 popping (14.9%), 24 clicking (12.1%), and 5 grinding (2.9%). No patients reported squeaking. Noisy hips had lower age (P = .009) and body mass index (P = .019). Among patients with developmental dysplasia of the hip, 17 of 55 hips reported noise associated with smaller cup anteversion angle (P = .004), greater body height (P = .022), and larger acetabular cup size (P = .049). Noise typically began at a mean of 193 days (range, 1 to 2,598) after surgery and disappeared spontaneously in 50.9% of hips before final follow-up, with an average disappearance time of 211 days (range, 60 to 730). Noise did not affect daily life in 74.5% of patients, while 26.9% of patients who had popping reported painful sensations. One patient experienced joint dislocation, and another experienced a ceramic liner fracture during follow-up. No statistical difference was observed in outcome scores between noise and silent groups at 4 follow-up time points. CONCLUSIONS: Incidence of noise after primary CoC THA is relatively high. Smaller cup anteversion and larger acetabular cup size were associated with noise production in patients who had developmental dysplasia of the hip.

Lack of causal association between epilepsy and dementia: A Mendelian randomization analysis.

OBJECTIVE: Epidemiological studies have reported an association between epilepsy and dementia. However, the causal relationship between epilepsy and the risk of dementia is not clear. We aimed to inspect the causal effect of epilepsy on memory loss and dementia. METHODS: We analyzed summary data of epilepsy, memory loss, and dementia from the genome-wide association study (GWAS) using the two-sample Mendelian randomization (MR) method. We used the estimated odds ratio of memory loss and dementia associated with each of the genetically defined traits to infer evidence for a causal relationship with the following exposures: all epilepsy, focal epilepsy (including focal epilepsy with hippocampal sclerosis, lesion-negative focal epilepsy, and focal epilepsy with other lesions), and genetic generalized epilepsy (including childhood absence epilepsy, generalized tonic-clonic seizures alone, Juvenile absence epilepsy, and Juvenile myoclonic epilepsy). RESULTS: According to the result of MR using the inverse variance weighted method (IVW), we found that genetically predicted epilepsy did not causally increase the risk of memory loss and dementia (p > 0.05). Results of the MR-Egger and weighted median method were consistent with the IVW method. CONCLUSIONS: No evidence has been found to support the notion that epilepsy can result in memory loss and dementia. The associations observed in epidemiological studies could be attributed, in part, to confounding or nongenetic determinants.

Evaluation of complexity and deliverability of IMRT treatment plans for breast cancer.

This study aimed to predict the outcome of patient specific quality assurance (PSQA) in IMRT for breast cancer using complexity metrics, such as MU factor, MAD, CAS, MCS. Several breast cancer plans were considered, including LBCS, RBCS, LBCM, RBCM, left breast, right breast and the whole breast for both Edge and TrueBeam LINACS. Dose verification was completed by Portal Dosimetry (PD). The receiver operating characteristic (ROC) curve was employed to determine whether the treatment plans pass or failed. The area under the curve (AUC) was used to assess the classification performance. The correlation of PSQA and complexity metrics was examined using Spearman's rank correlation coefficient (Rs). For LINACS, the most suitable complexity metric was found to be the MU factor (Edge Rs = - 0.608, p < 0.01; TrueBeam Rs = - 0.739, p < 0.01). Regarding the specific breast cancer categories, the optimal complexity metrics were as follows: MAD (AUC = 0.917) for LBCS, MCS (AUC = 0.681) for RBCS, MU factor (AUC = 0.854) for LBCM and MAD (AUC = 0.731) for RBCM. On the Edge LINAC, the preferable method for breast cancers was MCS (left breast, AUC = 0.938; right breast, AUC = 0.813), while on the TrueBeam LINAC, it became MU factor (left breast, AUC = 0.950) and MCS (right breast, AUC = 0.806), respectively. Overall, there was no universally suitable complexity metric for all types of breast cancers. The choice of complexity metric depended on different cancer types, locations and treatment LINACs. Therefore, when utilizing complexity metrics to predict PSQA outcomes in IMRT for breast cancer, it was essential to select the appropriate metric based on the specific circumstances and characteristics of the treatment.

Visualization of photothermal therapy by semiconducting polymer dots mediated photoacoustic detection in NIR II.

Visualization of photothermal therapy mediated by photothermal transduction agents (PTAs) is important to promote individual treatment of patients with low side effects. Photoacoustic detection has emerged as a promising noninvasive method for the visualization of PTAs distribution but still has limitations in temperature measurement, including poor measurement accuracy and low tissue penetration depth. In this study, we developed biocompatible semiconducting polymer dots (SPD) for in situ coupling of photothermal and photoacoustic detection in the near-infrared II window. SPD has dual photostability under pulsed laser and continuous-wave laser irradiation with a photothermal conversion efficiency of 42.77%. Meanwhile, a strong correlation between the photoacoustic signal and the actual temperature of SPD can be observed. The standard deviation of SPD-mediated photoacoustic thermometry can reach 0.13 °C when the penetration depth of gelatin phantom is 9.49 mm. Preliminary experimental results in vivo show that SPD-mediated photoacoustic signal has a high signal-to-noise ratio, as well as good performance in temperature response and tumor enrichment. Such a study not only offers a new nanomaterial for the visualization of photothermal therapy but will also promote the theranostic platform for clinical applications.

Treatment with a flow diverter-assisted coil embolization for ruptured blood blister-like aneurysms of the internal carotid artery: a technical note and analysis of single-center experience with pooled data.

Treatment of blood blister-like aneurysms (BBAs) of the supraclinoid internal carotid artery (ICA) with flow diverters (FDs) has become widespread in recent years. However, ruptured blood blister-like aneurysm (BBA) of ICA treatment with flow diverter-assisted coil embolization (FDAC) remains controversial. Moreover, limited direct comparative studies have been conducted between the two treatment modalities, FDs and FDAC, for BBAs. The purpose of this study was to document our experience and evaluate the effectiveness and safety of FDAC. We conducted a retrospective analysis of clinical and radiological information from ten patients who experienced ruptured BBAs of the supraclinoid ICA at our center from January 2021 to February 2023. The technical details of FDAC for ruptured BBAs were described, and the technical steps were named "pipeline embolization device (PED)-Individualized shaping(microcatheter)-Semi deploying-Rivet(coils)-Massage(microwire)" as the PEISSERM technique. Clinical outcomes were assessed using the modified Rankin Scale (mRS), whereas radiological results were determined through angiography. A pooled analysis was implemented, incorporating data from literature sources that reported perioperative and long-term clinical and angiographic outcomes of ruptured BBAs treated with FD and FDAC strategies, along with our data. Data in our analysis pool were categorized into FD and FDAC strategy groups to explore the preferred treatment modalities for BBAs. The PEISSERM technique was utilized to treat ten patients, seven males, and three females, with an average age of 41.7 years. A single PED was deployed in conjunction with coils in all ten patients. All PEDs were documented to have good wall apposition. The immediate postoperative angiograms demonstrated Raymond grade I in ten aneurysms. Angiographic follow-up of nine patients at 4-25 months showed total occlusion of the aneurysms. At the most recent follow-up, the mRS scores of nine patients hinted at a good prognosis. Pooled analysis of 233 ICA-BBA cases of FD revealed a technical success rate of 91% [95% confidence interval (CI), 0.88 to 0.95], a rate of complete occlusion of 79% (95% CI, 0.73 to 0.84), a recurrence rate of 2% (95% CI, 0.00 to 0.04), a rebleed rate of 2% (95% CI, 0.00 to 0.04), and the perioperative stroke rate was 8% (95% CI, 0.04 to 0.11). The perioperative mortality was 4% (95% CI, 0.01 to 0.07). The long-term good clinical outcome rate was 85% (95% CI, 0.80 to 0.90). The mortality rate was 6% (95% CI, 0.03 to 0.09). Results from the subgroup analysis illustrated that the FDAC strategy for BBAs had a significantly higher immediate postoperative complete occlusion rate (P < 0.001), total occlusion rate (P = 0.016), and a good outcome rate (P = 0.041) compared with the FD strategy. The FDAC strategy can yield a higher rate of good outcomes than the FD strategy. The PEISSERM technique employed by the FDAC is a reliable and effective treatment approach as it can minimize the hemodynamic burden of BBA's fragile dome, thereby achieving an excellent occlusion rate. The PEISSERM technique in the FDAC strategy contributes to understanding the BBA's treatment and offers a potentially optimal treatment for BBA.

Foldback-crRNA-Enhanced CRISPR/Cas13a System (FCECas13a) Enables Direct Detection of Ultrashort sncRNA.

The CRISPR/Cas13a system has promising applications in clinical small noncoding RNA (sncRNA) detection because it is free from the interference of genomic DNA. However, detecting ultrashort sncRNAs (less than 20 nucleotides) has been challenging because the Cas13a nuclease requires longer crRNA-target RNA hybrids to be activated. Here, we report the development of a foldback-crRNA-enhanced CRISPR/Cas13a (FCECas13a) system that overcomes the limitations of the current CRISPR/Cas13a system in detecting ultrashort sncRNAs. The FCECas13a system employs a 3'-terminal foldback crRNA that hybridizes with the target ultrashort sncRNA, forming a double strand that "tricks" the Cas13a nuclease into activating the HEPN structural domain and generating trans-cleavage activity. The FCECas13a system can accurately detect miRNA720 (a sncRNA currently known as tRNA-derived small RNA), which is only 17 nucleotides long and has a concentration as low as 15 fM within 20 min. This FCECas13a system opens new avenues for ultrashort sncRNA detection with significant implications for basic biological research, disease prognosis, and molecular diagnosis.

Crash frequency prediction based on extreme value theory using roadside lidar-based vehicle trajectory data.

Crash prediction models (CPMs) are mostly developed using statistical or data-driven methods that rely on observed crashes. However, the historical crash records can be unreliable due to availability and data quality issues. Near-crashes based CPMs offer a proactive approach to predict crash frequencies prior to the occurrence of crashes. Surrogate safety measures can be used to identify near-crashes from road user trajectories. Roadside LiDAR offers an innovative approach to collect vehicle trajectory data at a microscopic resolution with high accuracy providing detailed information of all road user movements. This study presents a methodology to identify near-crashes from Roadside LiDAR based vehicle trajectory data using the surrogate indicators: TTC (Time to Collision), PET (Post Encroachment Time), ACT (Anticipated Collision Time) and MaxD (Maximum Deceleration). Additionally, time-based, and evasive-action-based surrogate measures are combined as different pairs to obtain crash probabilities using extreme value theory (EVT). The study results show that the bivariate EVT model displays a better fit to conflict extremes, predicting crash frequencies better than the univariate model. Likewise, while the bivariate model with ACT and MaxD pair performed the best in terms of accuracy, the TTC and MaxD pair was able to reflect the relative threat levels at the study intersections. Overall, the methodology lays ground for using roadside lidar based trajectory data for proactive safety analysis of signalized intersections.

Lower Serum Iron Level Predicts Postoperative Global Cerebral Edema Following Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: Iron plays an important role in neuronal injury and edema formation after intracranial hemorrhage. However, the role of serum iron in aneurysmal subarachnoid hemorrhage (aSAH) is yet to be well-established. This study aims to identify whether serum iron could predict postoperative global cerebral edema (GCE) and poor outcome in aSAH. METHODS: 847 patients' aSAH clinical data were retrospectively collected at the First Affiliated Hospital of Fujian Medical University. Data on demographics, clinical characteristics, and laboratory values were collected and analyzed through univariate and multivariate analyses. Propensity score matching (PSM) analysis was performed to balance the baseline differences between the groups. RESULTS: The incidence of high-grade global cerebral edema (H-GCE) following aSAH was 12.99% (110/847). Serum iron levels [odds ratio (OR) = 1.143; 95% confidence interval (CI), (1.097-1.191); p < 0.001] were associated with the occurrence of H-GCE following aSAH in the univariate analysis. This association remained statistically significant even after adjusting for other variables in the multivariate model, with serum iron having an OR of 1.091 (95% CI, 1.043-1.141; p < 0.001) for GCE. After 1:1 PSM, serum iron levels ≤ 10.7 µmol/L remained a significant independent predictor of GCE (p = 0.002). The receiver operating characteristic (ROC) curve analysis determined that a serum iron cut-off value of ≤ 10.7 µmol/L was optimal for predicting H-GCE [Areas under the ROC curves (AUC) = 0.701, 95% CI, (0.669-0.732), p < 0.001; sensitivity, 67.27%; specificity, 63.77%] in patients with aSAH. Additionally, a trend was observed in which higher Hunt-Hess grades (HH grade) were associated with lower serum iron levels, and higher modified Fisher grades (mFisher grade) were associated with lower serum iron levels. In addition, the serum iron level was also associated with a 3-month functional neurological outcome (p < 0.001). CONCLUSIONS: The results of this study indicate that a decreased serum iron level serves as a clinically significant biomarker for the prediction of postoperative GCE and a poor outcome at 3-months in patients with aSAH.

Experience of Physical Activity in Breast Cancer Survivors: A Qualitative Study.

BACKGROUND: Physical activity plays an important role in the recovery of breast cancer survivors. However, previous studies have shown that most breast cancer survivors have inadequate levels of physical activity. OBJECTIVE: This study aimed to explore the influencing factors of physical activity in breast cancer survivors. METHODS: Twelve participants aged 38 to 65 years who had completed surgery and related treatment for breast cancer were recruited from the outpatient service of a hospital in Daqing, China. The phenomenological method was used in this qualitative research. Semistructured interviews were conducted to explore the influencing factors of physical activity in breast cancer survivors. Colaizzi's 7-step analysis method was used to code the data and identify descriptive themes. RESULTS: Four themes affecting the daily physical activity of breast cancer patients were extracted: perception and motivation (knowledge about benefits, goals, and motivation for physical activity), symptom burden (psychological and physical symptoms), social support (support from oncology staff, family, and peers) and environmental resources (seasonal impact, community resources). CONCLUSION: The physical activity of breast cancer survivors is affected by many factors. Oncology providers need to strengthen assessment, identify barriers, and provide interventions to promote the patients' participation in physical activity and to improve their quality of life. IMPLICATION FOR PRACTICE: It is necessary for providers to integrate medical and social support resources, use strategies to enhance motivation, and effectively solve barriers to increase physical activity in breast cancer survivors.

Mapping and validation of a novel major QTL for resistance to stripe rust in four wheat populations derived from landrace Qishanmai.

Wheat yield has been constrained by stripe rust disease globally. A wheat landrace (Qishanmai, QSM) consistently showed lower stripe rust severities in multiple year studies than susceptible check varieties including Suwon11 (SW) at the adult plant stage. To detect QTL for reducing the severity in QSM, 1218 recombinant inbred lines (RILs) were developed from SW × QSM. QTL detection was conducted firstly using 112 RILs selected for similarity in pheno-morphological characters. The 112 RILs were assessed for stripe rust severity at the 2nd leaf, 6th leaf and flag leaf stages under field and greenhouse conditions, and genotyping was done primarily with a single nucleotide polymorphism (SNP) array. On the basis of these phenotypic and genotypic data, a major QTL (QYr.cau-1DL) was detected on chromosome 1D at the 6th leaf and flag leaf stages. Further mapping was conducted by genotyping 1218 RILs using new simple sequence repeat (SSR) markers, which were developed by referring to the sequences of the wheat line Chinese Spring (IWGSC RefSeq v1.0). QYr.cau-1DL was mapped within a 0.5 cM (5.2 Mb) interval delimited by the SSR markers 1D-320.58 and 1D-325.79. These markers were applied to select for QYr.cau-1DL by screening F2 or BC4F2 plants of the wheat crosses RL6058 × QSM, Lantian10 × QSM and Yannong21 × QSM. F2:3 or BC4F2:3 families derived from the selected plants were assessed for stripe rust resistance in the fields of two locations and in a greenhouse. Wheat plants carrying the resistant marker haplotype in homozygous state for QYr.cau-1DL showed lower stripe rust severities (by 44% to 48%) than plants lacking this QTL. The trial of RL6058 (a carrier of Yr18) × QSM also indicated that QYr.cau-1DL had larger effect than Yr18 on reducing severity; they acted synergistically, yielding an elevated level of stripe rust resistance.

Overcome the "Buckets Effect": Integration of AIEgens into Proteins for Fluorescence-Enhanced Two-Photon Imaging.

Luminogens with aggregation-induced emission characteristics (AIEgens) are considered good options for two-photon (2P) probes, owing to their flexibility of design, heavy-metal-free composition, and resistance to photobleaching. However, the design principles for large 2P absorption cross-section (δ) generally require high coplanarity, strong donor-acceptor (D-A) interactions, and long conjugation, which can severely weaken the brightness of AIEgens at the aggregated state and undermine their potential in 2P fluorescence imaging (2PFI). Exploration of a feasible approach to overcome the "Buckets Effect" of AIEgen-based 2P probes is thus a fascinating yet challenging task. Herein, an AIEgen, namely (Z)-2-(4-aminophenyl)-3-(5-(4-(bis(4-methoxyphenyl)amino)phenyl)thiophen-2-yl)acrylonitrile (MTAA) is designed to have a big δ according to the calculation result and a low fluorescence quantum yield (QY) of 2.2% in dimethyl sulfoxide (DMSO). Impressively, upon integrating into bovine serum albumin (BSA), the protein-sized MTAA@BSA dots exhibit a 25-fold higher fluorescence QY compared to MTAA molecules, contributing to an imaging depth of 818 µm in the brain vasculature. The retention and clearance of MTAA@BSA dots in the liver and kidney are also studied using 2PFI. Overall, this work provides a facile approach to overcome the "Buckets Effect" of AIEgen to generate highly efficient, reliable, and biocompatible 2P probes.