Local Electric-Field-Induced Spin Photocurrent in ReS2.

A spin-related photocurrent excited by circularly polarized light is observed near the electrodes on a few-layer ReS2 sample at room temperature. For both electrodes, the spatial distribution of the spin photocurrent shows a feature of two wings, with one positive and the other negative. In this work, it is suggested that this phenomenon arises from the inverse spin Hall effect due to the local electric field near the electrode. Bias voltage that modulates this field further controls the sign and magnitude of the spin photocurrent. Our research shows that the electric field near the electrodes has a significant impact on the spin transmission operation, and hence it could be taken into account for manufacturing spintronic devices in the future.

Extended adjuvant endocrine therapy for women with hormone receptor-positive early breast cancer: A meta-analysis with trial sequential analysis of randomized controlled trials.

Objectives: The aim of the current study is to explore the association between extended adjuvant endocrine treatment and prognosis of women with hormone receptor-positive (HR+) early breast cancer. Methods: Databases including PubMed, Web of Science, Embase and the Cochrane Library databases were electronically searched to identify randomized controlled trials (RCTs) that reported extended endocrine therapy for women with HR+ early breast cancer. The retrieval time was limited from inception to September 2022. Two reviewers independently screened literature, extracted data, and assessed risk bias of included studies. Meta-analysis was performed by using R software Version 4.1.2 and STATA Version 12.0. Results: A total of 15 RCTs involving 29497 cases were included. The overall analysis showed that compared with the control, extended adjuvant endocrine therapy increased disease-free survival (DFS) (HR=0.814, 95% CI: 0.720-0.922, 95% PI: 0.556-1.194), overall survival (OS) (HR=0.885, 95% CI: 0.822-0.953, 95% PI: 0.771-1.035), relapse-free survival (RFS) (HR=0.833, 95% CI: 0.747-0.927, 95% PI: 0.575-1.159), distant metastatic-free survival (DMFS) (HR=0.824, 95% CI: 0.694-0.979, 95% PI: 0.300-2.089) and reduced new breast cancer cumulative incidence (NBCCI) (HR=0.484, 95% CI: 0.403-0.583, 95% PI: 0.359-0.654). For adverse events, extended adjuvant endocrine treatment was associated with a significantly higher risk of bone fracture (RR=1.446, 95% CI: 1.208-1.730, 95% PI: 1.154-1.854) and osteoporosis (RR=1.377, 95% CI: 1.018-1.862, 95% PI: 0.347-5.456). Conclusion: Our study showed that extended adjuvant endocrine therapy increased DFS, OS, RFS, DMFS, the incidence of bone fracture and osteoporosis, and reduced NBCCI. Systematic Review Registration: https://www.crd.york.ac.uk/prospero, identifier (CRD42022351295).

Radiomics model based on features of axillary lymphatic nodes to predict axillary lymphatic node metastasis in breast cancer.

BACKGROUND: Breast cancer (BC) is among the most common cancers worldwide. Machine learning-based radiomics model could predict axillary lymph node metastasis (ALNM) of BC accurately. PURPOSE: The purpose is to develop a machine learning model to predict ALNM of BC by focusing on the radiomics features of axillary lymphatic node (ALN). METHODS: A group of 398 BC patients with 800 ALNs were retrospectively collected. A set of patient characteristics were obtained to form clinical factors. Three hundred and twenty-six radiomics features were extracted from each region of interest for ALN in contrast-enhanced computed tomography (CECT) image. A framework composed of four feature selection methods and 14 machine learning classification algorithms was systematically applied. A clinical model, a radiomics model, and a combined model were developed using a cross-validation approach and compared. Metrics of the area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the performance of these models in the prediction of ALNM in BC. RESULTS: Among the 800 cases of ALNs, there were 388 cases of positive metastasis (48.50%) and 412 cases of negative metastasis (51.50%). The baseline clinical model achieved the performance with an AUC = 0.8998 (95% CI [0.8540, 0.9457]). The radiomics model achieved an AUC = 0.9081 (95% CI [0.8640, 0.9523]). The combined model using the clinical factors and radiomics features achieved the best results with an AUC = 0.9305 (95% CI [0.8928, 0.9682]). CONCLUSIONS: Combinations of feature selection methods and machine learning-based classification algorithms can develop promising predictive models to predict ALNM in BC using CECT features. The combined model of clinical factors and radiomics features outperforms both the clinical model and the radiomic model.

Gemcitabine Combined with Cisplatin Has a Better Effect in the Treatment of Recurrent/Metastatic Advanced Nasopharyngeal Carcinoma.

Objective: To explore the efficacy and safety of gemcitabine (GEM) combined with cisplatin (DDP) in the treatment of recurrent/metastatic nasopharyngeal carcinoma (NPC). Methods: A total of 100 patients with recurrent/metastatic NPC treated in the First Affiliated Hospital, Hengyang Medical School, University of South China from January 2018 to March 2020 were retrospectively enrolled. Based on different chemotherapy schemes, they were assigned to an observation (Obs) group (DDP + GEM, n = 55) and a control (Con) group [DDP + FU (fluorouracil), n = 45]. The two groups were compared regarding the following items: therapeutic efficacy; serum levels of platelet-derived growth factor-BB (PDGF-BB), soluble epithelial cadherin (SE-CAD), and inflammation-related factors before and after treatment; toxic and side effects; 1-year survival rate; and quality of life (QOL) 6 months after treatment. Results: The Obs group outperformed the Con group in therapeutic efficacy (P < 0.05). There were no significant differences in the levels of PDGF-BB, SE-CAD, interleukin (IL)-6, IL-10 and tumor necrosis factor (TNF)-α between the two groups before treatment (P > 0.05). After treatment, better improvements in PDGF-BB, SE-CAD and inflammatory factors were observed in the Obs group (P < 0.05). The toxic and side effects were significantly lower and the 1-year survival rate and patients' QOL after 6 months of treatment were significantly higher in the Obs group compared with the Con group (P < 0.05). Conclusion: GEM combined with DDP can provide more clinical benefits for patients with recurrent/metastatic advanced NPC, with less side effects, high tolerance and significant efficacy, which can be further promoted in clinical use.

Prediction of Metastasis in the Axillary Lymph Nodes of Patients With Breast Cancer: A Radiomics Method Based on Contrast-Enhanced Computed Tomography.

BACKGROUND: The use of traditional techniques to evaluate breast cancer is restricted by the subjective nature of assessment, variation across radiologists, and limited data. Radiomics may predict axillary lymph node metastasis (ALNM) of breast cancer more accurately. PURPOSE: The aim was to evaluate the diagnostic performance of a radiomics model based on ALNs themselves that used contrast-enhanced computed tomography (CECT) to detect ALNM of breast cancer. METHODS: We retrospectively enrolled 402 patients with breast cancer confirmed by pathology from January 2016 to October 2019. Three hundred and ninety-six features were extracted for all patients from axial CECT images of 825 ALNs using Artificial Intelligent Kit software (GE Medical Systems, Version V3.1.0.R). Next, the radiomics model was trained, validated, and tested for predicting ALNM in breast cancer by using a support vector machine algorithm. Finally, the performance of the radiomics model was evaluated in terms of its classification accuracy and the value of the area under the curve (AUC). RESULTS: The radiomics model yielded the best classification accuracy of 89.1% and the highest AUC of 0.92 (95% CI: 0.91-0.93, p=0.002) for discriminating ALNM in breast cancer in the validation cohorts. In the testing cohorts, the model also demonstrated better performance, with an accuracy of 88.5% and an AUC of 0.94 (95% CI: 0.93-0.95, p=0.005) for predicting ALNM in breast cancer. CONCLUSION: The radiomics model based on CECT images can be used to predict ALNM in breast cancer and has significant potential in clinical noninvasive diagnosis and in the prediction of breast cancer metastasis.

Analysis of mRNA Expression Patterns in Peripheral Blood Cells of 3 Patients With Cancer After the First Fraction of 2 Gy Irradiation: An Integrated Case Report and Systematic Review.

BACKGROUND: Radiation therapy induces acute and chronic radiological toxicity, in particular hematological toxicity (HT). This study aimed to explore the mechanistic clue and potential predictors at the messenger RNA (mRNA) level. MATERIALS AND METHODS: Peripheral blood was collected from 3 patients with cervical cancer (CC), nasopharynx cancer (NC), and tongue cancer (TC) after the first 2 Gy fraction of radiotherapy (RT). High-throughput sequencing was used to assess mRNA profiles. RESULTS: Eleven genes, such as ALAS2(5-aminolevulinate synthase), SLC4A1(solute carrier family 4 member 1), HBG2(hemoglobin subunit gamma 2), TNFAIP3 (TNF α-induced protein 3), PER1 (period circadian clock 1), CCDC136 (coiled-coil domain containing 136), C9orf84 (chromosome 9 open reading frame 84), IL1B (interleukin 1ß), FOSB (FosB protooncogene), NR4A2 (nuclear receptor subfamily 4), PARP15 (polymerase family member 15), had overlapping expression changes in all 3 cancers of which 3 (ALAS2, FOSB, and HBG2) are suggested as potential predictors for the early diagnosis of HT after RT. CONCLUSIONS: ALAS2, FOSB, and HBG2 may be useful predictors of HT in patients after RT. Eleven overlapping expression mRNAs among 3 cancers might be potential predictors for early diagnosis of radiation toxicity in patients.

The analysis of correlation between frailty index and postoperative complications of aged patients with nodular goiter.

OBJECTIVE: To explore the correlation between frailty index (FI) and postoperative complications of aged patients with nodular goiter (NG). METHODS: A total of 120 aged patients with NG undergoing operative treatment from May 2013 to October 2015 in our hospital were selected. All of them were divided into 3 groups according to the FI as follows: nonfrail group (FI < 0.2), intermediately frail group (0.2 ≤ FI < 0.4), and frail group (FI ≥ 0.4). Clinical data of patients about general data, body mass index, American Society of Anesthesiology (ASA) classification, hospital stays, and postoperative complications were examined. Then, the correlations between the indexes above and FI were examined. RESULTS: Frailty index and the ASA classification have some relevance (r = .265, P = .007). The postoperative complication rates of total nonfrail group, intermediately frail group, and frail group were, respectively, 4 cases (11.4%), 11 cases (31.4%), and 24 cases (48.0%). With the increase in FI, the incidence of postoperative complications and hospital stays had also significantly increased. The area under receiver operating characteristic curve examining frailty's ability to forecast postoperative complications was 0. 815 (95% CI: 0.675-0.954, P = .000). CONCLUSION: The level of frailty index is a risk factor for postoperative complications of aged patients with NG. The preoperative frailty index evaluation can provide reference evidence for the treatment of aged NG patients undergoing surgery.

[Association of Toll-like receptor 2 and 4 gene polymorphisms with risk of coronary atherosclerotic artery disease in Hunan Han population].

OBJECTIVE: To explore Toll-like receptor 2 (TLR2) and TLR4 polymorphism in Han people from Hunan region and its association with coronary atherosclerotic heart disease.
 Methods: Sanger sequence and statistical analysis were performed to identify the polymorphism of TLR2 and TLR4 genes in 347 unrelated Hunan Han subjects, including 180 healthy people (control group) and 167 patients with coronary atherosclerotic heart disease (coronary atherosclerotic heart disease group).
 Results: There was no significant difference in the genotype frequency and allelic frequency for TLR2 SNP2258G>A and TLR4 SNP896A>G between the 2 groups (P>0.05), while there was significant difference in the TLR4 SNP1196C>T between the 2 groups (P<0.05).
 Conclusion: TLR4 SNP1196C>T polymorphism is associated with coronary atherosclerotic heart disease in Chinese Han populationin in Hunan region.