Clinical Effectiveness and Safety of Transarterial Chemoembolization: Hepatic Artery Infusion Chemotherapy Plus Tyrosine Kinase Inhibitors With or Without Programmed Cell Death Protein-1 Inhibitors for Unresectable Hepatocellular Carcinoma-A Retrospective Study.

BACKGROUND: Locoregional treatment with transarterial chemoembolization (TACE) or hepatic artery infusion chemotherapy (HAIC) and systemic targeted immunotherapy with tyrosine kinase inhibitors (TKI) and programmed cell death protein-1 (PD-1) inhibitors in the treatment of unresectable hepatocellular carcinoma (uHCC) have achieved promising efficacy. The retrospective study aimed to evaluate the efficacy and safety of TACE and HAIC plus TKI with or without PD-1 for uHCC. PATIENTS AND METHODS: From November 2020 to February 2024, the data of 44 patients who received TACE-HAIC + TKI + PD-1 (THKP group) and 34 patients who received TACE-HAIC + TKI (THK group) were retrospectively analyzed. Primary outcomes were overall survival (OS) and progress-free survival (PFS), and secondary outcomes were objective response rate (ORR), disease control rate (DCR), conversion rates, and adverse events (AEs). RESULTS: A total of 78 patients were recruited in our single-center study. The patients in THKP group had prolonged median OS [25 months, 95% confidence interval (CI) 24.0-26.0 vs 18 months, 95% CI 16.1-19.9; p = 0.000278], median PFS [16 months, 95% CI 14.1-17.9 vs 12 months 95% CI 9.6-14.4; p = 0.004] and higher ORR (38.6% vs 23.5%, p = 0. 156) and DCR (88.6% vs 64.7%, p = 0.011) compared with those in THK group. Multivariate analysis showed that treatment option and alpha-fetoprotein (AFP) level were independent prognostic factors of OS and PFS. The frequency of AEs were similar between the two groups. CONCLUSIONS: The THKP group had better efficacy for uHCC than the THK group, with acceptable safety.

Effects of nutritional interventions on cognitive function in adult cancer survivors: A systematic review.

AIM: To evaluate the effectiveness and safety of nutritional interventions (i.e. nutritional support, dietary patterns and dietary supplements) on cognitive function in cancer survivors. DESIGN: Systematic review. METHODS: A systematic and comprehensive search of PubMed, Web of Science, the Cochrane Library, Embase, and CINAHL was conducted from the inception until March 10, 2023. The last search was conducted on December 10, 2023. REPORTING METHOD: PRISMA. RESULTS: A total of 59 randomized controlled trials were included for analysis. Nutritional support, dietary patterns and dietary supplements improved cognitive function in cancer survivors with no apparent safety concerns. The anti-inflammatory diet, the fasting-mimicking diet and the web-based diet significantly improved cognitive function. Whereas the ketogenic diet or dietary advice to consume more soluble dietary fibres and less insoluble dietary fibres and lactose could not. There was evidence from dietary supplements to support the beneficial effects of polyunsaturated fatty acid supplements, traditional herbal medicines and other supplements. CONCLUSIONS: Nutritional interventions have great promise for improving cognitive function in adult cancer survivors. Further validation of the nutritional interventions supported in this study in other survivors and exploration of more effective nutritional interventions are needed. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This work can support the construction of nutritional support interventions and dietary guidance programs to prevent cancer-related cognitive decline. IMPACT: This work filled a gap in preventive strategies for cancer-related cognitive decline from a nutritional perspective. Nutritional support, dietary patterns, and dietary supplements can prevent cancer-related cognitive decline without serious safety concerns. This work highlighted nutritional interventions that have the potential to improve cognitive function in cancer survivors, benefiting the further construction of evidence-based nutritional intervention programs. PROTOCOL REGISTRATION: PROSPERO. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Giant Iontronic Flexoelectricity in Soft Hydrogels Induced by Tunable Biomimetic Ion Polarization.

Flexoelectricity features the strain gradient-induced mechanoelectric conversion using materials not limited by their crystalline symmetry, but state-of-the-art flexoelectric materials exhibit very small flexoelectric coefficients and are too brittle to withstand large deformations. Here, inspired by the ion polarization in living organisms, this paper reports the giant iontronic flexoelectricity of soft hydrogels where the ion polarization is attributed to the different transfer rates of cations and anions under bending deformations. The flexoelectricity is found to be easily regulated by the types of anion-cation pairs and polymer networks in the hydrogel. A polyacrylamide hydrogel with 1 m NaCl achieves a record-high flexoelectric coefficient of ≈1160 µC m-1, which can even be improved to ≈2340 µC m-1 by synergizing with the effects of ion pairs and extra polycation chains. Furthermore, the hydrogel as flexoelectric materials can withstand larger bending deformations to obtain higher polarization charges owing to its intrinsic low modulus and high elasticity. A soft flexoelectric sensor is then demonstrated for object recognition by robotic hands. The findings greatly broaden the flexoelectricity to soft, biomimetic, and biocompatible materials and applications.

Changes in soil aggregate stability and aggregate-associated carbon under different slope positions in a karst region of Southwest China.

Soil aggregates are crucial for reducing soil erosion and enhancing soil organic carbon sequestration. However, knowledge regarding influences of different slope positions on compositions and carbon content for different soil aggregates is limited. Soil samples were collected from various slope positions including dip slope, anti-dip slope and valley depression in the Longtan karst valley of Southwest China. Contents of macroaggregate (> 0.25 mm), microaggregate (0.053-0.25 mm) and silt and clay fraction (< 0.053 mm), and aggregate-associated carbon contents under the three slope positions were measured. Compared to the anti-dip slope, the mean weight diameter under the dip slope and valley depression decreased by 28.48 % and 58.79 %, respectively, while the geometric mean diameter decreased by 39.01 % and 62.57 %, respectively. The mean carbon content in silt and clay fraction was 27.59 % and 21.00 % lower than the macroaggregate- and microaggregate-associated carbon content, respectively. Under the valley depression and dip slope, soil organic carbon contents in bulk soil (37.67 % and 10.36 %, respectively), microaggregate (37.56 % and 4.95 %), and silt and clay fraction (39.99 % and 12.84 %, respectively) were significantly lower than those under the anti-dip slope. However, the difference in macroaggregate-associated carbon content among the three slope positions was not significant. The silt and clay fraction was the major contributor to soil carbon pool in bulk soil in the study area because of its high content. Compared to the anti-dip slope, contribution of macroaggregates to soil carbon pool under the dip slope and valley depression decreased by 25.53 % and 47.95 %, respectively, whereas the contribution of silt and clay fraction increased by 22.68 % and 42.66 %, respectively. These results suggested that the anti-dip slope surpassed both the dip slope and valley depression in carbon sequestration and soil and water conservation in karst regions.

Variation of the Start Date of the Vegetation Growing Season (SOS) and Its Climatic Drivers in the Tibetan Plateau.

Climate change inevitably affects vegetation growth in the Tibetan Plateau (TP). Understanding the dynamics of vegetation phenology and the responses of vegetation phenology to climate change are crucial for evaluating the impacts of climate change on terrestrial ecosystems. Despite many relevant studies conducted in the past, there still remain research gaps concerning the dominant factors that induce changes in the start date of the vegetation growing season (SOS). In this study, the spatial and temporal variations of the SOS were investigated by using a long-term series of the Normalized Difference Vegetation Index (NDVI) spanning from 2001 to 2020, and the response of the SOS to climate change and the predominant climatic factors (air temperature, LST or precipitation) affecting the SOS were explored. The main findings were as follows: the annual mean SOS concentrated on 100 DOY-170 DOY (day of a year), with a delay from east to west. Although the SOS across the entire region exhibited an advancing trend at a rate of 0.261 days/year, there were notable differences in the advancement trends of SOS among different vegetation types. In contrast to the current advancing SOS, the trend of future SOS changes shows a delayed trend. For the impacts of climate change on the SOS, winter Tmax (maximum temperature) played the dominant role in the temporal shifting of spring phenology across the TP, and its effect on SOS was negative, meaning that an increase in winter Tmax led to an earlier SOS. Considering the different conditions required for the growth of various types of vegetation, the leading factor was different for the four vegetation types. This study contributes to the understanding of the mechanism of SOS variation in the TP.

Droplet-Based Direct-Current Electricity Generation Induced by Dynamic Electric Double Layers.

Harvesting energy from water droplets has received tremendous attention due to the pursuit of sustainable and green energy resources. The droplet-based electricity generator (DEG) provides an admirable strategy to harvest energy from droplets into electricity. However, most of the DEGs merely generate electricity of alternating current (AC) output rather than direct current (DC) without the utilization of rectifiers, impeding its practical applications in energy storage and power supply. Here, a direct current droplet-based electricity generator (DC-DEG) is developed by the simple configuration of the electrodes. The DC output originates from the dynamical electric double layer (EDL) formed at two electrodes and droplet interfaces where the charging/discharging process of EDL capacitance occurs. Several experiments are exhibited to demonstrate the rationality of the proposed principle. The influence of some factors on the output is investigated for further insight into the DC-DEG device. This work provides a novel strategy to harvest energy from water droplets directly into DC electricity and may expand the application of DEGs in powering electronic devices without the help of rectifiers.

Hierarchical porous dual-mode thermal management fabrics achieved by regulating solar and body radiations.

Personal thermal management (PTM) of fabrics is vital for human health; the ever-changing location of the human body poses a big challenge for fabrics to maintain a favorable metabolic temperature. Herein, a dual-mode thermal management fabric is designed to achieve both cooling and heating functions by regulating simultaneously solar and body radiations. The cooling or heating mode can be exchanged by flipping the fabric without an external energy supply. The passive cooling side consists of an electrospun polyacrylonitrile (PAN) fabric with a hierarchical porous structure, exhibiting high sunlight reflectance (91.42%) and an ∼14 °C temperature decrease under direct sunlight irradiation. The co-existence of nanoscale and microscale pores is proven to be essential for improved cooling performances. The other heating side, coated with an MXene layer, shows high photothermal conversion efficiency (37.5%) and outstanding heating capability outdoors. Furthermore, the contrary mid-infrared emissivity of the two sides (high emissivity of the cooling side while low emissivity of the heating side) leads to the dual-mode passive regulation of body thermal energy. Besides, this fabric demonstrates satisfactory wearability and excellent stability. Our work proposes an energy-saving and cost-effective approach for PTM fabrics potentially suitable for various scenarios (e.g., indoors/outdoors, summer/winter, low/high latitude areas).

Factors influencing college students' self-regulated learning in online learning environment: A systematic review.

OBJECTIVE: Drawing on the control value theory, this study aims to identify the pertinent factors of self-regulated learning in the online learning environment for college students. The analysis will inductively examine how these factors impact self-regulated learning, thereby furnishing a reference for educators and online learning platform developers to create more efficacious online learning and teaching modes. DESIGN: Systematic review. DATA SOURCES: In March 2023, electronic databases of PubMed, Web of Science, Embase, EBSCO, Cochrane and Scopus were searched, and there was no time limit for publication. REVIEW METHODS: The inclusion criteria were: (1) Includes both online learning environment and self-regulated learning variables. (2) The research object is college students. (3) The research focuses on online teaching. Assessment of risk of bias for all included studies using a mixed-methods assessment tool. RESULTS: After screening, 31 articles were finally included. Including 24 quantitative studies, 2 qualitative study and 5 mixed studies. According to the control value theory, the factors affecting self-regulated learning in online learning environment are divided into seven aspects, namely cognitive quality, motivational quality, autonomy support, goal structures and social expectations, feedback and considerations of achievement, perceived control and perceived value. CONCLUSIONS: Teachers should exercise reasonable management over the number of assignments and provide timely and supportive feedback, as well as actively create interactive learning environments to facilitate peer-to-peer communication. Developers of online learning platforms should improve the functions of the platforms according to students' needs, and provide training for teachers and students when necessary. Learners should adapt their learning status in a timely manner to realise efficient learning and improve learning outcomes.

A nomogram for intraoperatively predicting non-sentinel lymph node metastases in early breast cancer patients with positive sentinel lymph nodes.

Background: Individualized decisions are required in early-stage breast cancer patients. We aimed to establish a novel model for predicting non-sentinel lymph node (SLN) metastases in patients with positive SLNs, using preoperative and intraoperative characteristics and inflammatory indicators. Methods: The data of 489 patients with invasive breast cancer were retrospectively collected from Xuanwu Hospital between 2014 and 2021. Among them, 96 patients with at least one positive SLN were used to build the predictive model. Univariate and multivariate analyses were performed to identify the risk factors of non-SLN metastases. A nomogram was developed using these risk factors and was validated by calibration curves. The area under the receiver operating characteristics curve (AUC) and decision curve analyses (DCA) were used to compare our novel nomogram with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram. Cross-validation was performed for further internal validation of the predictive model. External validation was conducted using another treatment group (n=46 patients) in Xuanwu Hospital. Results: Non-SLN metastases occurred in 42 of the 83 patients with positive SLNs (50.6%). Multivariate stepwise logistic regression indicated that the risk factors were age (P=0.032), number of positive SLNs (P=0.020), number of negative SLNs (P=0.011), resected tumor size (P=0.038), and monocyte count (P=0.012). A predictive model was developed and virtualized by nomogram using these five risk factors. The AUC of our nomogram was 0.867, which was significantly higher than that of the MSKCC model. DCA also showed a superior clinical value for our novel nomogram. After 10-fold cross-validation with 400 times repetitions, the AUC of our model was still 0.830. External validation of our model showed an AUC of 0.727. The model was well-calibrated in the internal and external validation series. Conclusions: A five-factor nomogram was developed for predicting non-SLN metastases in early-stage breast cancer patients. This novel tool exhibited good accuracy and could assist clinicians with intraoperative decisions in breast cancer patients with positive SLNs.

Degradation of micropollutants in flow-through VUV/UV reactors: Impact of internal diameter and baffle allocation.

Application of VUV/UV process for micropollutants removal in decentralized water supply systems (e.g., rural drinking water treatment) is promising while few researches by far paid attention to the performance of practical flow-through reactors. This study investigated the degradation of atrazine (ATZ), sulfamethoxazole (SMX) and metoprolol (MET) under different hydrodynamic conditions in reactors with varied internal diameters and baffle allocations. Results showed that the target micropollutants could be degraded efficiently in the flow-through VUV/UV reactors following basically the pseudo-first order kinetics (R2 ≥ 0.97). The largest degradation rate constants were found in the D35 reactor and incorporation of baffles in the D50 and D80 reactors accelerated obviously the micrpollutants degradation. The improved performances of the baffled reactors were due mainly to the elevated utilization of HO•, and a new parameter named UEHO (HO• utilization efficiency) was proposed accordingly. The calculated UEHO values of the reactors ranged between 30.2% and 69.2% with the largest found in the D50-5 reactor. This testified the usually insufficient utilization of radicals in flow-through reactors and the effectiveness of baffle implementation. Electrical energy per order (EEO) values of micropollutants degradation in the reactors were in the range of 0.104-0.263 kWh m-3 order-1. The degradation was inhibited significantly by high-concentration nitrate yet the formed nitrite concentration stayed consistently below the drinking water limitation. The acute toxicity of the micropollutant solutions increased first and leveled off afterwards during the VUV/UV treatment, as indicated by the inhibition ratios of luminescence intensity of Vibrio fischeri.

Case-based learning interventions for undergraduate nursing students in a theoretical course: A review of design, implementation, and outcomes.

BACKGROUND: Case-based learning (CBL) is a contextualized learning and teaching method that can facilitate active and reflective learning to develop critical thinking and problem-solving skills. However, nursing educators have some difficulty in creating a CBL environment that matches the diverse professional nursing curriculum and students' needs, including developing relevant cases and appropriate CBL implementation processes. OBJECTIVE: To summarize the case design, implementation process, and their relationship with CBL effectiveness. METHODS: Electronic databases of PubMed, Embase, Web of Science, CINAHL, China National Knowledge Infrastructure (CNKI) and Wanfang Data (a Chinese database) were searched from inception until January 2022. Study quality was assessed using the Mixed Methods Appraisal Tool. A qualitative synthesis was then conducted to summarize the study findings. RESULTS: The systematic mixed studies review included twenty-one quantitative studies, five qualitative studies and two mixed methods studies. The case design and implementation process were indispensable parts of each study, but the application process of CBL in each study was slightly different, basically including case design, preparation, small-group interaction and exploration, collaborative efforts, teacher summary, assignment and teacher feedback. There were three themes in this review that indicate the effect of CBL on students, namely, knowledge, competence and attitude. CONCLUSION: The present review analyzes the available literature and suggests that there is no common format for the case design and CBL implementation process, but demonstrates that they are an indispensable part of each study. This review provides conceptual procedures for nurse educators to design and implement CBL in nursing theoretical courses to improve the effectiveness of CBL.

Factors influencing adherence to healthy eating behaviors among adult colorectal cancer survivors: a systematic mixed method review.

PURPOSE: Under the umbrella of social cognitive theory, we examined the influences of personal, environmental, and behavioral factors on adherence to healthy eating behaviors among colorectal cancer survivors. METHODS: Based on Pluye and Hong's framework, a systematic mixed studies review was conducted. An extensive search strategy was applied in PubMed, Web of Science, Embase, CINAHL, and PsycINFO (from date of record to 2022 January 22). The pillar integration process was employed to integrate the extracted data. The Mixed Methods Appraisal Tool was used to appraise the quality of all retained studies. RESULTS: Twenty-eight studies with a total sample size of 5106 were included in the analysis, with 15 quantitative studies, 12 qualitative studies, and 1 mixed method study. The critical appraisal showed that 22 of the 28 studies (79%) were rated with five stars, while 6 (21%) were rated with four stars. The personal factors influencing adherence to healthy eating behaviors among colorectal cancer survivors included outcome expectancies, self-efficacy, psychological factors, knowledge about healthy eating, demographic and disease characteristics, environmental factors incorporated outside information on healthy eating, power of surrounding people, social activities, cultural milieus, socioeconomic status, and education. The behavioral factors included self-regulation of diet, goals, and other behaviors closely related to healthy eating behaviors. CONCLUSIONS: Adherence to healthy eating behaviors among colorectal cancer survivors was influenced collectively by personal factors, environmental factors and behavioral factors.

A new magnetic ionic liquid based salting-out assisted dispersive liquid-liquid microextraction for the determination of parabens in environmental water samples.

In this study, a new magnetic ionic liquid (MIL) was designed and prepared, containing a magnetic cation from the ligand N,N-dimethyl biguanide (DMBG) complexing with magnetic center Co2+ and a bis-trifluoromethanesulfonimide (NTf2-) anion. Using the MIL as the extraction solvent, a salting-out assisted dispersive liquid-liquid microextraction (SA-DLLME) combined with high performance liquid chromatography-ultraviolet detection (HPLC-UV) was established for the enrichment and detection of four parabens in environmental water samples. The one-factor-at-a-time experiment was employed to optimize the conditions affecting the extraction efficiency. Under the optimized extraction conditions, the limits of quantification (LOQs) of the four target analytes ranged from 2.0 ng mL-1 to 2.8 ng mL-1, and the coefficients of determination (R2) were above 0.9996 in the linear range of 2.8-400 ng mL-1. On the other hand, the method displayed good repeatability and accuracy with intra-day and inter-day relative standard deviations (RSDs) of 2.1-13.0% and recoveries of 82.0-114.6%. The established method was applied to real samples with recoveries within 81.6-125.4%, and the results demonstrated that the method was practical.

Degradation of micropollutants in flow-through UV/chlorine reactors: Kinetics, mechanism, energy requirement and toxicity evaluation.

The degradation of three micropollutants (i.e., atrazine (ATZ), sulfamethoxazole (SMX) and metoprolol (MET)) was comprehensively investigated in flow-through UV/chlorine reactors. Results showed that the micropollutants degradation fitted well with pseudo-first-order kinetics (R2 > 0.92) with the order of rate constants following SMX > MET > ATZ. The developed steady-state approximation (SSA) model was roughly applicable in flow-through UV/chlorine reactors with the predictions deviated within 44%. UV photolysis here stood as the major degradation pathway for ATZ while the contribution of non-radical processes (UV photolysis and chlorination) to SMX degradation increased as the reactor internal diameter enlarged. The degradation rates were reduced to varying extents with complex water matrices (chloride, bicarbonate and dissolved organic matter (DOM)) where the inhibition from the DOM was most prominent (up to 73.6%). Although reactors with a larger internal diameter resulted in reduced degradation rate constants, the energy requirements were also lowered. The EEO values of micropollutants degradation by UV/chlorine fell mostly within 1.0 kWh m-3 order-1 in deionized water and under different water matrices. The acute toxicity was observed to be higher after UV/chlorine treatment in tap water, but still stayed low in general. This study revealed the different kinetics and mechanisms of micropollutants degradation in flow-through reactors and demonstrated the potential of the UV/chlorine process in terms of low energy consumption and acute toxicity.

Bioinspired soft electroreceptors for artificial precontact somatosensation.

Artificial haptic sensors form the basis of touch-based human-interfaced applications. However, they are unable to respond to remote events before physical contact. Some elasmobranch fishes, such as seawater sharks, use electroreception somatosensory system for remote environmental perception. Inspired by this ability, we design a soft artificial electroreceptor for sensing approaching targets. The electroreceptor, enabled by an elastomeric electret, is capable of encoding environmental precontact information into a series of voltage pulses functioning as unique precontact human interfaces. Electroceptor applications are demonstrated in a prewarning system, robotic control, game operation, and three-dimensional object recognition. These capabilities in perceiving proximal precontact events can lenrich the functionalities and applications of human-interfaced electronics.

Electricity Generation and Self-Powered Sensing Enabled by Dynamic Electric Double Layer at Hydrogel-Dielectric Elastomer Interfaces.

The electric double layer (EDL) at liquid-solid interfaces is fundamental to many research areas ranging from electrochemistry and microfluidics to colloidal chemistry. Here, we demonstrate the electricity generation by mechanically modulating the EDL at the hydrogel-dielectric polymer interfaces. It is found that contact electrification between the hydrogel and the dielectric polymer could charge the dielectric polymer surface at first; the mechanical deformation of the pyramid-shaped hydrogel results in the periodic variation of the EDL area and capacitance, which then induces an alternative current in the external circuits. This mechano-to-electrical energy conversion mechanism is then utilized to construct soft stretchable self-powered pressure sensors by designing dynamic EDL at hydrogel-dielectric elastomer interfaces. The sensitivity is optimized to 1.40 kPa-1 in the low-pressure range of 31-300 Pa by increasing the elastomer roughness. Its antifreeze performance is also improved by adding ethylene glycol into the hydrogel. The capability in detecting subtle human activities is further demonstrated. This mechano-electrical energy conversion and the corresponding self-powered sensor can be widely applied in future soft electronics.

Development and validation of a novel 14-gene signature for predicting lymph node metastasis in papillary thyroid carcinoma.

BACKGROUND: There is still no reasonably accurate method of preoperatively predicting central lymph node metastasis (LNM), and it is essential to develop an effective evaluation model for predicting LNM in papillary thyroid carcinoma (PTC) patients. METHODS: PTC samples were collected from The Cancer Genome Atlas database. Candidate genes were identified as continuously upregulated or downregulated genes in the process of N0 to N1a and N1a to N1b. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct the predictive model for LNM. Multivariate logistic regression analysis was performed to screen the potential factors related to LNM, and a nomogram was established. The risk score of the gene signature model for predicting disease-free survival (DFS) was evaluated by Kaplan-Meier analysis. RESULTS: A 14-gene signature was developed by LASSO regression for predicting LNM based on 69 differential expression genes (DEGs) that were continuously upregulated or downregulated in the progress of PTC. The receiver operating characteristic (ROC) curves of the 14-gene signature predicting LNM, central LNM and lateral LNM were generated. The area under the ROC (AUC) values were 0.806 [95% confidence interval (CI): 0.7608-0.8815], 0.755 (95% CI: 0.6839-0.8263) and 0.821 (95% CI: 0.7608-0.8815). The nomogram's C-index value, including the 14-gene signature and other potential risk factors, was 0.786 (95% CI: 0.7296-0.8425), and the calibration exhibited fairly good consistency with the perfect prediction. Based on the 14-gene risk score, high-risk PTC patients had a worse DFS. CONCLUSIONS: A novel 14-gene signature was developed for predicting LNM in PTC patients. The risk score also correlated with DFS in PTC patients.

Carbon nanoparticle-guided intraoperative lymph node biopsy predicts the status of lymph nodes posterior to right recurrent laryngeal nerve in cN0 papillary thyroid carcinoma.

BACKGROUND: The lymph nodes in the right central compartment can be divided into 2 parts by the right recurrent laryngeal nerve (RLN), and there is a lack of an accurate and convenient method for assessing metastases in the lymph node posterior to the right recurrent laryngeal nerve (LN-prRLN) in cN0 thyroid papillary carcinoma patients. METHODS: Patients diagnosed with cN0 thyroid papillary carcinoma and underwent intraoperative carbon nanoparticle-guided lymph node biopsy from January 2017 to November 2020 at the Center for Thyroid and Breast Surgery of Xuanwu Hospital were retrospectively analyzed. The intraoperative frozen section examination and postoperative LN-prRLN status should have been comprehensively recorded. The participants were divided into the LN-prRLN positive group and LN-prRLN negative group according to their recorded LN-prRLN status. RESULTS: In total, 189 cases (LN-prRLN positive group, n=30; LN-prRLN negative group, n=159) were included in the analysis. The univariate and multivariate regression analyses revealed that the number of metastatic lymph nodes during intraoperative lymph node biopsy was the potential predictor for LN-prRLN metastasis [odds ratio (OR): 1.320, 95% confidence interval (CI): 1.057 to 1.649, P=0.014]. The receiver operating characteristic (ROC) curve showed that the area under the curve (AUC) reached 0.7 upon a combined analysis of multiple lymph node statuses located at pre-laryngeal (Delphian), pre-tracheal, and para-tracheal lymph nodes ipsilateral to the tumor in predicting the metastasis of LN-prRLN, and the cut-off value was 0.5. CONCLUSIONS: Number of metastatic lymph nodes in intraoperative biopsy was an indicator of LN-prRLN metastasis in cN0 thyroid carcinoma patients. Patients staging in cN0 with negative intraoperative lymph node status might be considered not to require LN-prRLN dissection during central lymph nodes dissection.

A 10-Gene Signature for Predicting the Response to Neoadjuvant Trastuzumab Therapy in HER2-Positive Breast Cancer.

BACKGROUND AND PURPOSE: Dual-target therapy may increase the incidence of adverse events and cause economic burden to patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer. It is necessary to identify the patients who could benefit greatly from a single-target neoadjuvant therapy in order to avoid overtreatment of patients. PATIENTS AND METHODS: The baseline transcriptome data and clinical characteristics of patients with HER2-positive breast cancer who received neoadjuvant trastuzumab therapy were obtained from the Gene Expression Omnibus database. Least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct the predictive model for pathologic complete response (pCR). RESULTS: A 10-gene signature model for predicting pCR rate after neoadjuvant trastuzumab therapy was constructed by LASSO regression. The areas under the receiver operating characteristics (ROC) curves in the training set and validation set were 0.896 (95% confidence interval [CI], 0.8165-0.9758) and 0.775 (95% CI, 0.5402-1), respectively. The result of logistic regression analysis showed that the risk score calculated by the 10-gene signature model was a potential predictor for pCR. Among the 10-gene signature, TFAP2B, SUSD2, AQP3, MUCL1, and ANKRD30A were found to be predictors for worse relapse-free survival (RFS) in patients with HER2-positive breast cancer, whereas MGP, YIF1B, ANKRD36BP2, and FBXO6 were found to be predictors for favorable RFS. CONCLUSION: A novel 10-gene signature that could predict the response of neoadjuvant anti-HER2 therapy in patients with HER2-positive breast cancer was developed, and the risk score of the 10-gene signature could be calculated to guide the selection of anti-HER2 therapy regimens.