Enhancing surgical outcomes: accurate identification and removal of prostate cancer with B7-H3-targeted NIR-II molecular imaging.

PURPOSE: One of the main reasons for prostate cancer (PCa) recurrence is the difficulty in identifying and removing cancerous lesions during surgery. Accurately localizing and excising cancerous tissue remains a significant challenge. The second near-infrared window (NIR-II, 1000-1700 nm) fluorescence offers enhanced resolution, a high signal-to-noise ratio, and the potential for deeper tissue penetration. However, this technology is not currently employed for intraoperative imaging of PCa. This study aims to construct a new NIR-II probe targeting B7-H3 (AbB7-H3-800CW) for accurate intraoperative identification and resection of PCa. METHODS: Based on the differential expression of B7-H3 in PCa, we designed a novel imaging probe to accurately identify and guide the resection of preclinical PCa models and ex vivo human PCa tissues using NIR-II fluorescence imaging technology. RESULTS: Analyzing tissue samples from 60 clinical cases of PCa, along with benign prostatic hyperplasia and normal prostate tissue from 22 cases, we observed a significant difference in B7-H3 protein expression levels (P < 0.001). Subcutaneous and orthotopic mouse models of PCa were imaged using NIR-II fluorescence after AbB7-H3-800CW injection, showing promising results with successful tumor targeting and high-contrast images achieved within 24-48 h post-injection. The imaging also enabled the detection of occult PCa lesions approximately 1 mm in diameter. In addition, imaging analysis of human PCa and adjacent tissues using AbB7-H3-800CW incubation revealed that cancer tissues exhibited a significantly higher fluorescence intensity than adjacent tissues (P < 0.05), which was conducive to the evaluation of tumor resection margin in vitro. CONCLUSION: The findings revealed that B7-H3 was a compelling imaging target for PCa. The AbB7-H3-800CW molecular imaging probe is capable of accurately identifying PCa lesions and guiding their removal. This approach can potentially reduce the rate of surgical margins under NIR-II fluorescence guidance.

Multi-Parameter Optimization of Rubidium Laser Optically Pumped Magnetometers with Geomagnetic Field Intensity.

Rubidium laser optically pumped magnetometers (OPMs) are widely used magnetic sensors based on the Zeeman effect, laser pumping, and magnetic resonance principles. They measure the magnetic field by measuring the magnetic resonance signal passing through a rubidium atomic gas cell. The quality of the magnetic resonance signal is a necessary condition for a magnetometer to achieve high sensitivity. In this research, to obtain the best magnetic resonance signal of rubidium laser OPMs in the Earth's magnetic field intensity, the experiment system of rubidium laser OPMs is built with a rubidium atomic gas cell as the core component. The linewidth and amplitude ratio (LAR) of magnetic resonance signals is utilized as the optimization objective function. The magnetic resonance signals of the magnetometer experiment system are experimentally measured for different laser frequencies, radio frequency (RF) intensities, laser powers, and atomic gas cell temperatures in a background magnetic field of 50,765 nT. The experimental results indicate that optimizing these parameters can reduce the LAR by one order of magnitude. This shows that the optimal parameter combination can effectively improve the sensitivity of the magnetometer. The sensitivity defined using the noise spectral density measured under optimal experimental parameters is 1.5 pT/Hz1/2@1 Hz. This work will provide key technical support for rubidium laser OPMs' product development.

A radiomics nomogram model for predicting prognosis of pancreatic ductal adenocarcinoma after high-intensity focused ultrasound surgery.

OBJECTIVE: To develop and validate a radiomics nomogram for predicting the survival of patients with pancreatic ductal adenocarcinoma (PDAC) after receiving high-intensity focused ultrasound (HIFU) treatment. METHODS: A total of 52 patients with PDAC were enrolled. To select features, the least absolute shrinkage and selection operator algorithm were applied, and the radiomics score (Rad-Score) was obtained. Radiomics model, clinics model, and radiomics nomogram model were constructed by multivariate regression analysis. The identification, calibration, and clinical application of nomogram were evaluated. Survival analysis was performed using Kaplan-Meier (K-M) method. RESULTS: According to conclusions made from the multivariate Cox model, Rad-Score, and tumor size were independent risk factors for OS. Compared with the clinical model and radiomics model, the combination of Rad-Score and clinicopathological factors could better predict the survival of patients. Patients were divided into high-risk and low-risk groups according to Rad-Score. K-M analysis showed that the difference between the two groups was statistically significant (p < 0.05). In addition, the radiomics nomogram model indicated better discrimination, calibration, and clinical practicability in training and validation cohorts. CONCLUSION: The radiomics nomogram effectively evaluates the prognosis of patients with advanced pancreatic cancer after HIFU surgery, which could potentially improve treatment strategies and promote individualized treatment of advanced pancreatic cancer.

Exploring psychological resilience of entrepreneurial college students for post-pandemic pedagogy: The mediating role of self-efficacy.

The psychological impact of the COVID-19 epidemic on college students is an important topic. With the entry of the post-epidemic era, how universities can better improve students' psychological resilience in teaching is the research topic of this article. In the form of a questionnaire survey, some entrepreneurial college students investigated the loneliness and psychological resilience of college students after the outbreak of the epidemic and explored the role of self-efficacy in it. The data is collected online through cooperation with an entrepreneurial event, and the participating students are asked for background information such as colleges, grade, and majors. After collecting this information, they answered a series of simplified scale questions about loneliness, self-efficacy, and psychological resilience. In the end, a total of 200 questionnaires from different universities were collected, and the structural equation model was used to explore the role of self-efficacy. The results show that: loneliness has a significant negative effect on Self-efficacy, ß = -0.292, p < 0.001; Self-efficacy has a significant positive effect on psychological resilience, ß = 0.556, p < 0.0 01; loneliness has a significant negative effect on psychological resilience, ß = -0.244, p < 0.01. Self-Efficacy has a significant intermediate effect in loneliness and psychological resilience, with an effective value of -0.111 and p < 0.01. The results show that this exploratory survey finds it important to provide targeted personal self-efficacy improvement activities for college students with a strong sense of loneliness and to combine school and family education organically to help college students form a healthy and upward mentality to better cope with the unknown and troubles caused by the epidemic, which will help improve the psychological resilience of college students in the epidemic.

Data leaking scandal, risks, and financial consumption behaviors in online tourism platforms: The role of trust on college students and teachers.

Given the importance of data safety for psychology, the present study investigated the influence of data leaking scandal on campus customers' financial consumption behaviors at intelligent tourism platforms in China, and explored the roles that individual characteristics play in this process by focusing on a set of participants from colleges. Data were collected through sending out an online questionnaire, where respondents were asked to finish a series of questions about their background information, their trust, future consuming intention, and defensive behaviors toward intelligent platforms. After they finished these questions, a short description about an online tourism platform leaking customers' personal information was presented to the respondents, following which they were asked to report about their future consuming intentions and defensive behaviors again. In total, 236 participants of college students and teachers were recruited. Paired samples mean comparison showed that after the stimulus was presented, the respondents had a significant decrease in future financial consumption intention, and a significant increase in defensive behaviors toward online tourism platforms due to risks perceived. Multiple regression analysis was conducted subsequently to investigate individual characteristics that may account for part of the decrease (increase) in consuming intention (defensive behaviors). Results showed that, customers with higher level of trust and monthly income, as well as older customers, tend to experience higher level of decrease in consuming intention, and increase in defensive behaviors. These findings highlighted the importance of online tourism platforms guaranteeing data security of their customers.

Preoperative Evaluation of Gd-EOB-DTPA-Enhanced MRI Radiomics-Based Nomogram in Small Solitary Hepatocellular Carcinoma (≤3 cm) With Microvascular Invasion: A Two-Center Study.

BACKGROUND: Preoperative evaluation of microvascular invasion (MVI) in small solitary hepatocellular carcinoma (HCC; maximum lesion diameter ≤ 3 cm) is important for treatment decisions. PURPOSE: To apply gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI to develop and validate a nomogram for preoperative evaluation of MVI in small solitary HCC and to compare the effectiveness of radiomics evaluation models based on different volumes of interest (VOIs). STUDY TYPE: Retrospective. POPULATION: A total of 196 patients include 62 MVI-positive and 134 MVI-negative patients were enrolled (training cohort, n = 105; testing cohort, n = 45; external validation cohort, n = 46). FIELD STRENGTH/SEQUENCE: 3.0 T, fat suppressed fast-spin-echo T2-weighted and Gd-EOB-DTPA-enhanced T1-weighted magnetization-prepared rapid gradient-echo sequences. ASSESSMENT: Radiomics features were extracted on T2-weighted, arterial phase (AP), and hepatobiliary phase (HBP) images from different VOIs (VOIintratumor and VOIintratumor+peritumor ) and filtered by the least absolute shrinkage selection operator (LASSO) regression. From VOIintratumor and VOIintratumor+peritumor , eight radiomics models were constructed based on three MRI sequences (T2-weighted, AP, and HBP) and fused sequences (combined of three sequences). Nomograms were constructed of a clinical-radiological (CR) model and a clinical-radiological-radiomics (CRR) model. STATISTICAL TESTS: One-way analysis of variance, independent t-test, Chi-square test or Fisher's exact test, Wilcoxon rank-sum test, LASSO, logistic regression analysis, area under the curve (AUC), nomograms, decision curve, net reclassification improvement (NRI), integrated discrimination improvement (IDI) analyses, and DeLong test. RESULTS: Among eight radiomics models, the fused sequences-based VOIintratumor+peritumor radiomics model showed the best performance. The CRR model containing the best performance radiomics model and CR model with the AUC values were 0.934, 0.889, and 0.875, respectively. NRI and IDI analyses showed that the CRR model improved evaluation efficacy over the CR model for all three cohorts (all P-value <0.05). DATA CONCLUSION: The CRR model nomogram could preoperatively evaluate MVI in small solitary HCC. The radiomics model based on VOIintratumor+peritumor might achieve better evaluation results. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY STAGE: 2.

Characterization of phytoplankton community in a river ecosystem using pigment composition: a feasibility study.

CHEMTAX is a mathematical software for phytoplankton composition evaluation using pigment composition. Although this method has been previously applied in the ocean environment, we firstly utilized the combination of matrix factorization program CHEMTAX and high-performance liquid chromatography (HPLC) to characterize the phytoplankton community from a river system (western part of Weihe River Basin). The obtained results were compared with those from microscopic examination. Based on the comparison, it is suggested that after increasing the ratio of characteristic pigment to chlorophyll a of diatoms and euglena, the diatoms calculated by the CHEMTAX method accounted for 80% of the total biomass, and the results were consistent with microscopic examination, but diatoms obtained from F2, C1 and W5 sample sites were significantly overestimated 33%~60%. The comparison also showed that the model always underestimated cyanobacteria (sample sites F2, C1 were underestimated 25%) and euglena were overestimated (sample sites W3, Q1 were respectively overestimated 33%, 23%), but for chlorophytes, both overestimation and underestimation could occur. When the relevant results from previous applications in the ocean phytoplankton community evaluation were taken into consideration, it can be concluded that CHEMTAX-HPLC method was not accurate enough to characterize the phytoplankton communities in the freshwater (river/lake) ecosystem.