BRAFV600E mutation does not predict lymph node metastases and recurrence in Chinese papillary thyroid microcarcinoma patients.

OBJECT: Previous studies suggest BRAFV600E mutation is a marker for poor prognosis in papillary thyroid cancer, however, its ability to further risk stratify papillary thyroid microcarcinoma (PTMC) remains controversial. We aimed to explore the association between BRAFV600E mutation and the clinicopathological features and recurrence in Chinese PTMC patients. METHODS: We retrospectively reviewed 2094 PTMC patients who underwent surgery and had a valid BRAFV600E mutation test result. Among them, 1292 patients had complete follow-up data. The mutation incidence was determined. Moreover, the clinicopathological characteristics, disease-free survival (DFS), and response to therapy distribution were compared between the mutation and non-mutation groups. RESULTS: BRAFV600E mutation was observed in 90.6 % of all patients and 89.2 % of patients with complete follow-up data. No significant difference was observed in lymph node metastases (LNM) number categories between the mutation and non-mutation groups among all patients (P = 0.329) and 1292 patients (P = 0.408). Neither the 3-year DFS (97.9 % vs. 98.0 %, P = 0.832) nor the response to therapy distribution (P > 0.05) indicated a significant difference between the mutation and non-mutation groups. The 3-year DFS differs among patients having different LNM number categories (99.8 % vs. 98.5 % vs. 77.3 %, P < 0.001). Multivariate analysis revealed that high-volume (over 5) LNM (Total thyroidectomy (TT): OR = 4.000, 95 % CI 2.390-6.694, P < 0.001; Unilateral thyroidectomy (UT): OR = 4.183, 95 % CI 1.565-11.190, P = 0.004), rather than BRAFV600E mutation (P > 0.05), was an independent risk factor of response to therapy. CONCLUSIONS: Our results suggested that BRAFV600E mutation could not accurately predict LNM or the recurrence of Chinese PTMC patients. Moreover, high-volume LNM is significantly associated with PTMC prognosis.

A Long-Term Study Comparing the Quality of Life and Psychological Status of Patients with Highly Suspicious Thyroid Nodules ≤1 cm Undergoing Active Surveillance with Those Undergoing Immediate Surgery.

Background: Limited information is available on the long-term impact of active surveillance (AS) and immediate surgery (IS) on the quality of life (QoL) and psychological status of patients with highly suspicious subcentimeter thyroid nodules. Methods: A prospective study was conducted on 752 patients showing highly suspicious subcentimeter thyroid nodules, among whom 584 chose AS and 168 chose IS. All patients underwent at least two assessments regarding their QoL and psychological status, using three questionnaires: Thyroid Cancer-Specific Quality of Life (THYCA-QoL), Hospital Anxiety and Depression Scale (HADS), and European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Core Questionnaire (QLQ-C30). Propensity-score matching (PSM) at a ratio of 3:1 was utilized on patients in the AS and IS groups to mitigate selection bias (504 patients in the AS group and 168 in the IS group). Subsequently, the mixed linear model was used to analyze the QoL data. Results: The median time from the initial evaluation to the last follow-up in the AS and IS groups was 24.0 and 14.2 months, respectively. The AS group showed superior QoL outcomes compared to the IS group, mainly manifested in voice (p < 0.001), sympathetic (p = 0.008), throat/mouth (p < 0.001), and problems with scar (p < 0.001) domains, as per the THYCA-QoL questionnaire. Further, the EORTC QLQ-C30 questionnaire highlighted better outcomes in physical function (p = 0.029), role function (p < 0.001), social function (p < 0.001), global health status (p < 0.001), fatigue (p = 0.012), pain (p = 0.028), appetite loss (p = 0.017), and financial difficulties (p < 0.001). Compared to the initial assessment (1 week after surgery), the IS group showed progressive improvements in QoL, especially in voice (p = 0.024), throat/mouth (p < 0.001), physical function (p = 0.004), social function (p = 0.014), nausea and vomiting (p < 0.001), pain (p = 0.006), and appetite loss (p = 0.048) domains as per both questionnaires. Conclusion: Patients with highly suspicious subcentimeter thyroid nodules who choose IS tend to experience a poorer long-term QoL compared to those who choose AS. Although the situation may improve over time, certain issues might persist, making AS a favorable option for these patients.

Criteria to Evaluate Tumor Enlargement During the Active Surveillance of High-Risk Thyroid Nodules: Which is Better, Diameter or Volume?

INTRODUCTION: Tumor enlargement is the most common parameter identifying disease progression during active surveillance, but the value and significance of the changes in tumor diameter and volume in the evaluation of tumor growth have not been compared. METHODS: This cohort study included 468 patients with high-risk thyroid nodule, in whom nodule size change was monitored using ultrasound, to compare the changes in tumor diameter and volume in assessing tumor growth. RESULTS: A total of 569 high-risk thyroid nodules were found in the 468 patients. A total of 14 nodules (2.5%) showed a diameter increase ≥ 3 mm. The number of nodules with a peak volume change exceeding 50% and 100% was 185 (32.5%) and 86 (15.1%), respectively. Among the 555 stable nodules, the number of nodules with volume fluctuations exceeding 50% and 100% was 171 (30.8%) and 72 (13.0%), respectively. Among 212 stable nodules at the baseline and in the first three follow-up, the percentage of peak volume fluctuations exceeding 50% (48.5% vs. 28.5%, p = 0.004) and 100% (26.5% vs. 8.3%, p < 0.001) in the nodules with the sum of three diameters (SOTDs) ≤ 1 cm was significantly higher than that of nodules with SOTDs > 1 cm. A statistically significant difference was also found in the range distribution of SOTDs ≤ 1 cm and SOTDs > 1 cm (p = 0.007). CONCLUSIONS: Volume is not an appropriate method for determining tumor growth. Tumor diameter measurement alone serves as a better surrogate for disease progression in sonographically high-risk thyroid nodules than volume.

Active surveillance versus immediate surgery: A comparison of clinical and quality of life outcomes among patients with highly suspicious thyroid nodules 1 cm or smaller in China.

INTRODUCTION: Active surveillance (AS) is considered an alternative to immediate surgery (IS) for low-risk papillary thyroid microcarcinoma (PTMC) patients. However, it is difficult to decide between AS and IS due to limited evidence regarding risks and benefits for patients in China. METHODS: This study prospectively enrolled 485 patients with highly suspicious thyroid nodules

Dynamics analysis of building block synthesis reactions for virus assembly in vitro.

Virus assembly from structural protein monomers to virus shells is a key step of virus replication. Some drug targets were found in this process. It consists of two steps. Virus structural protein monomers firstly polymerize to building blocks, then these building blocks assemble into virus shells. So, these building block synthesis reactions in the first step are fundamental for virus assembly. Typically, virus building blocks are made up of less than six monomers. They are of five types, including dimer, trimer, tetramer, pentamer and hexamer. In this work, we develop five synthesis reaction dynamical models for these five types, respectively. Then, we prove the existence and uniqueness of the positive equilibrium solution for these dynamical models one by one. Subsequently, we also analyze the stability of the equilibrium states, respectively. We got the function of monomer and dimer concentrations for dimer building blocks in the equilibrium state. We also got the function of all intermediate polymers and monomers for trimer, tetramer, pentamer and hexamer building blocks in the equilibrium state, respectively. Based on our analysis, dimer building blocks in the equilibrium state will decrease as the ratio of the off-rate constant to the on-rate constant increases. Trimer building blocks in the equilibrium state will decrease with the increasing ratio of the off-rate constant to the on-rate constant of trimers. These results may provide further insight into the virus-building block synthesis dynamic property in vitro.

LangMoDHS: A deep learning language model for predicting DNase I hypersensitive sites in mouse genome.

DNase I hypersensitive sites (DHSs) are a specific genomic region, which is critical to detect or understand cis-regulatory elements. Although there are many methods developed to detect DHSs, there is a big gap in practice. We presented a deep learning-based language model for predicting DHSs, named LangMoDHS. The LangMoDHS mainly comprised the convolutional neural network (CNN), the bi-directional long short-term memory (Bi-LSTM) and the feed-forward attention. The CNN and the Bi-LSTM were stacked in a parallel manner, which was helpful to accumulate multiple-view representations from primary DNA sequences. We conducted 5-fold cross-validations and independent tests over 14 tissues and 4 developmental stages. The empirical experiments showed that the LangMoDHS is competitive with or slightly better than the iDHS-Deep, which is the latest method for predicting DHSs. The empirical experiments also implied substantial contribution of the CNN, Bi-LSTM, and attention to DHSs prediction. We implemented the LangMoDHS as a user-friendly web server which is accessible at http:/www.biolscience.cn/LangMoDHS/. We used indices related to information entropy to explore the sequence motif of DHSs. The analysis provided a certain insight into the DHSs.

MultiScale-CNN-4mCPred: a multi-scale CNN and adaptive embedding-based method for mouse genome DNA N4-methylcytosine prediction.

N4-methylcytosine (4mC) is an important epigenetic mechanism, which regulates many cellular processes such as cell differentiation and gene expression. The knowledge about the 4mC sites is a key foundation to exploring its roles. Due to the limitation of techniques, precise detection of 4mC is still a challenging task. In this paper, we presented a multi-scale convolution neural network (CNN) and adaptive embedding-based computational method for predicting 4mC sites in mouse genome, which was referred to as MultiScale-CNN-4mCPred. The MultiScale-CNN-4mCPred used adaptive embedding to encode nucleotides, and then utilized multi-scale CNNs as well as long short-term memory to extract more in-depth local properties and contextual semantics in the sequences. The MultiScale-CNN-4mCPred is an end-to-end learning method, which requires no sophisticated feature design. The MultiScale-CNN-4mCPred reached an accuracy of 81.66% in the 10-fold cross-validation, and an accuracy of 84.69% in the independent test, outperforming state-of-the-art methods. We implemented the proposed method into a user-friendly web application which is freely available at: http://www.biolscience.cn/MultiScale-CNN-4mCPred/ .

A capsule network-based method for identifying transcription factors.

Transcription factors (TFs) are typical regulators for gene expression and play versatile roles in cellular processes. Since it is time-consuming, costly, and labor-intensive to detect it by using physical methods, it is desired to develop a computational method to detect TFs. Here, we presented a capsule network-based method for identifying TFs. This method is an end-to-end deep learning method, consisting mainly of an embedding layer, bidirectional long short-term memory (LSTM) layer, capsule network layer, and three fully connected layers. The presented method obtained an accuracy of 0.8820, being superior to the state-of-the-art methods. These empirical experiments showed that the inclusion of the capsule network promoted great performances and that the capsule network-based representation was superior to the property-based representation for distinguishing between TFs and non-TFs. We also implemented the presented method into a user-friendly web server, which is freely available at http://www.biolscience.cn/Capsule_TF/ for all scientific researchers.

Related factor analysis for predicting large-volume central cervical lymph node metastasis in papillary thyroid carcinoma.

The aim of this study was to investigate the factors related to large-volume central cervical lymph node metastasis (LNM) in papillary thyroid carcinoma. A retrospective study of 340 patients with 642 papillary thyroid carcinoma nodules who underwent thyroidectomy in Peking Union Medical College Hospital between 2011 and 2015 was conducted. These nodules were divided into two groups by the number of central cervical lymph node metastases: large-volume central cervical LNM (>5 metastatic lymph nodes, n = 129) and no central cervical LNM (n = 211). We evaluated the correlations between gender, age, chronic lymphocytic thyroiditis, thyroid ultrasonographic features, and large-volume central cervical LNM. We found that younger age (≤40 years) (OR = 3.796, 95% CI = 2.842, 5.070), male gender (OR = 4.005, 95% CI = 2.858, 5.61), and ultrasonographic features such as tumor macroaxis size (OR = 2.985, 95% CI = 1.581, 5.633), tumor located in the isthmus (OR = 7.578, 95% CI = 4.863, 11.810), ill-defined margin (OR = 3.008, 95% CI = 1.986, 4.556), microcalcification (OR = 2.155, 95% CI = 1.585, 2.929), and abnormal cervical lymph nodes (OR = 13.753, 95% CI = 9.278, 20.385) were independent risk factors for large-volume central cervical LNM in papillary thyroid carcinoma, while chronic lymphocytic thyroiditis (OR = 0.248, 95% CI = 0.172, 0.358) was a protective factor. Younger age (≤40 years), male sex, and ultrasonographic features such as tumor macroaxis size, tumor located in the isthmus, ill-defined margin, microcalcification, and abnormal cervical lymph nodes were independent risk factors for large-volume central cervical LNM in papillary thyroid carcinoma, while chronic lymphocytic thyroiditis can be considered a protective factor. Our results provide a reference for adjusting clinical treatment approaches.

Active surveillance of highly suspicious thyroid nodules cohort in China shows a worse psychological status in younger patients.

Background: Active surveillance has been considered a safe alternative to surgery for low-risk papillary thyroid microcarcinoma. This study aimed to assess the oncological outcomes and psychological status of active surveillance of highly suspicious thyroid nodules ≤10 mm in China. Methods: This prospective single-center cohort study enrolled 336 patients with highly suspicious thyroid nodules for active surveillance to assess oncological outcomes and psychological status. The psychological status of patients was assessed by two different questionnaires and compared among different patient groups. Results: During a median follow-up period of 28.5 months, eight patients underwent delayed surgery for tumor enlargement and one for lymph node metastases. The cumulative incidence of disease progression at 5 and 10 years was 6.0% and 12.8%, respectively. Patients who underwent delayed surgery had no permanent complications, and no patient had distant metastasis or death. Patients ≤30 years old had a higher baseline anxiety score (4.9 vs. 3.8, p=0.024), a higher proportion of baseline anxiety score, i.e., ≥8 points (24.0% vs. 12.6%, p=0.033), and a worse baseline emotional function (62.7 vs. 70.7, p=0.013) than patients >30. During AS, patients ≤30 years of age had higher overall anxiety levels (p=0.005) and a worse overall emotional function (p=0.001). Conclusions: Active surveillance in Chinese patients with highly suspicious subcentimetre thyroid nodules has good oncological outcomes and can be used as a safe alternative to surgery. Younger patients (≤30) show a worse psychological status; therefore, more attention should be paid to younger patients.

An immediate postoperative response to therapy assessment can help avoid unnecessary RAI therapy.

Background: Radioiodine (RAI) therapy plays a vital role in the postoperative treatment of differentiated thyroid cancer (DTC) patients underwent total thyroidectomy (TT). However, even in the presence of capsular invasion and lymph node metastasis prognosis can be excellent and a postoperative RAI treatment might not be necessary for all patients. Therefore, this study explored the criteria for avoiding unnecessary RAI therapy in these patients. Method: We applied response to therapy assessment immediately after surgery and prospectively recruited 179 excellent or indeterminate response DTC patients with capsular invasion and/or LNM who underwent TT without RAI therapy. During the follow-up, thyroglobulin (Tg), thyroglobulin antibody (TgAb) levels, and cervical ultrasonography were collected and analyzed. Disease-free survival (DFS) was calculated using the Kaplan-Meier method. In addition, response to therapy assessments was performed on patients during each follow-up. Results: The mean follow-up period was 29.85 ± 17.44 months, and the 3- and 5-year DFS for all the patients was 99.3% in each. At the last follow-up, 165 (92.2%) patients had excellent responses, while 12 (6.7%) had an indeterminate response, and one (0.6%) each had biochemical and incomplete responses. No significant difference was observed in response to therapy between the subgroups of LNM and tumor invasion (P>0.05). For patients with capsular invasion and a number of metastatic lymph nodes ≤5 and >5, the proportions of recorded excellent responses were 95.9%, 91.0%, and 85.7%, respectively. Better responses were observed in females (excellent response: 95.5%, P=0.023), patients with stimulated Tg (s-Tg) ≤1ng/ml (excellent response: 100%, P<0.001), s-Tg ≤ 2ng/ml (excellent response: 98.4%, P<0.001), and excellent response for the immediate postoperative assessment (excellent response: 98.5%, P=0.004). Conclusions: The current study suggested that the response to therapy assessment immediately applied postoperatively could help avoid unnecessary RAI therapy among DTC patients with capsular invasion and/or LNM. Moreover, excellent response patients and patients with indeterminate response and s-Tg ≤ 2ng/ml could be managed without RAI therapy.

Enhancer-LSTMAtt: A Bi-LSTM and Attention-Based Deep Learning Method for Enhancer Recognition.

Enhancers are short DNA segments that play a key role in biological processes, such as accelerating transcription of target genes. Since the enhancer resides anywhere in a genome sequence, it is difficult to precisely identify enhancers. We presented a bi-directional long-short term memory (Bi-LSTM) and attention-based deep learning method (Enhancer-LSTMAtt) for enhancer recognition. Enhancer-LSTMAtt is an end-to-end deep learning model that consists mainly of deep residual neural network, Bi-LSTM, and feed-forward attention. We extensively compared the Enhancer-LSTMAtt with 19 state-of-the-art methods by 5-fold cross validation, 10-fold cross validation and independent test. Enhancer-LSTMAtt achieved competitive performances, especially in the independent test. We realized Enhancer-LSTMAtt into a user-friendly web application. Enhancer-LSTMAtt is applicable not only to recognizing enhancers, but also to distinguishing strong enhancer from weak enhancers. Enhancer-LSTMAtt is believed to become a promising tool for identifying enhancers.

MPMABP: A CNN and Bi-LSTM-Based Method for Predicting Multi-Activities of Bioactive Peptides.

Bioactive peptides are typically small functional peptides with 2-20 amino acid residues and play versatile roles in metabolic and biological processes. Bioactive peptides are multi-functional, so it is vastly challenging to accurately detect all their functions simultaneously. We proposed a convolution neural network (CNN) and bi-directional long short-term memory (Bi-LSTM)-based deep learning method (called MPMABP) for recognizing multi-activities of bioactive peptides. The MPMABP stacked five CNNs at different scales, and used the residual network to preserve the information from loss. The empirical results showed that the MPMABP is superior to the state-of-the-art methods. Analysis on the distribution of amino acids indicated that the lysine preferred to appear in the anti-cancer peptide, the leucine in the anti-diabetic peptide, and the proline in the anti-hypertensive peptide. The method and analysis are beneficial to recognize multi-activities of bioactive peptides.

Deep6mAPred: A CNN and Bi-LSTM-based deep learning method for predicting DNA N6-methyladenosine sites across plant species.

DNA N6-methyladenine (6mA) is a key DNA modification, which plays versatile roles in the cellular processes, including regulation of gene expression, DNA repair, and DNA replication. DNA 6mA is closely associated with many diseases in the mammals and with growth as well as development of plants. Precisely detecting DNA 6mA sites is of great importance to exploration of 6mA functions. Although many computational methods have been presented for DNA 6mA prediction, there is still a wide gap in the practical application. We presented a convolution neural network (CNN) and bi-directional long-short term memory (Bi-LSTM)-based deep learning method (Deep6mAPred) for predicting DNA 6mA sites across plant species. The Deep6mAPred stacked the CNNs and the Bi-LSTMs in a paralleling manner instead of a series-connection manner. The Deep6mAPred also employed the attention mechanism for improving the representations of sequences. The Deep6mAPred reached an accuracy of 0.9556 over the independent rice dataset, far outperforming the state-of-the-art methods. The tests across plant species showed that the Deep6mAPred is of a remarkable advantage over the state of the art methods. We developed a user-friendly web application for DNA 6mA prediction, which is freely available at http://106.13.196.152:7001/ for all the scientific researchers. The Deep6mAPred would enrich tools to predict DNA 6mA sites and speed up the exploration of DNA modification.

PRIP: A Protein-RNA Interface Predictor Based on Semantics of Sequences.

RNA-protein interactions play an indispensable role in many biological processes. Growing evidence has indicated that aberration of the RNA-protein interaction is associated with many serious human diseases. The precise and quick detection of RNA-protein interactions is crucial to finding new functions and to uncovering the mechanism of interactions. Although many methods have been presented to recognize RNA-binding sites, there is much room left for the improvement of predictive accuracy. We present a sequence semantics-based method (called PRIP) for predicting RNA-binding interfaces. The PRIP extracted semantic embedding by pre-training the Word2vec with the corpus. Extreme gradient boosting was employed to train a classifier. The PRIP obtained a SN of 0.73 over the five-fold cross validation and a SN of 0.67 over the independent test, outperforming the state-of-the-art methods. Compared with other methods, this PRIP learned the hidden relations between words in the context. The analysis of the semantics relationship implied that the semantics of some words were specific to RNA-binding interfaces. This method is helpful to explore the mechanism of RNA-protein interactions from a semantics point of view.

Survival prognostic factors for differentiated thyroid cancer patients with pulmonary metastases: A systematic review and meta-analysis.

Background: The prognostic factors for differentiated thyroid cancer (DTC) patients with pulmonary metastases (PM) remain scantly identified and analyzed. Therefore, this systematic review and meta-analysis were performed to identify and summarize the prognostic factors in adult DTC patients with PM to help distinguish patients with different prognoses and inform the rational treatment regimens. Method: We performed a comprehensive search of the relevant studies published in the Cochrane Library, PubMed, Scopus, Embase, Wanfang database, VIP database, China National Knowledge Infrastructure, and Google Scholar from their inception until February 2021. The pooled hazard ratios (HR) for overall survival and/or progression-free survival (PFS) with 95% confidence intervals were applied to evaluate and identify the potential prognostic factors. Pooled OS at different time points were also calculated for the available data. A random-effects model was used in the meta-analysis. Results: The review and meta-analysis included 21 studies comprising 2722 DTC patients with PM. The prognostic factors for poor OS were: age over 40 years (HR=7.21, 95% confidence interval [CI] 1.52-34.10, P=0.01, N=788), age over 45 years (HR=2.18, 95% CI 1.26-3.77, P<0.01, N=601), male gender (HR=1.01, 95% CI 1.01-1.19, P=0.03, N=1396), follicular subtype of thyroid cancer (HR=1.63, 95% CI 1.36-1.96, P<0.01, N=2110), iodine non-avidity (HR=3.10, 95% CI 1.79-5.37, P<0.01, N=646), and metastases to other organs (HR=3.18, 95% CI 2.43-4.16, P<0.01, N=1713). Factors associated with poor PFS included age over 45 years (HR=3.85, 95% CI 1.29-11.47, P<0.01, N=306), male gender (HR=1.36, 95% CI 1.06-1.75, P=0.02, N=546), iodine non-avidity (HR=2.93, 95% CI 2.18-3.95, P<0.01, N=395), pulmonary metastatic nodule size over 10mm (HR=2.56, 95% CI 2.02-3.24, P<0.01, N=513), and extra-thyroidal invasion (HR=2.05, 95% CI 1.15-3.67, P=0.02, N=271). The pooled 1, 3, 5, 10, 15, and 20-years OS were 95.24%, 88.46%, 78.36%, 64.86%, 56.57%, and 51.03%, respectively. Conclusions: This review and meta-analysis identified the prognostic factors of DTC patients with PM. Notably, FTC, metastases to other organs, and iodine non-avidity were particularly associated with poor prognosis. The identified prognostic factors will help guide the clinical management of DTC patients with PM. Systematic review registration: https://inplasy.com/inplasy-2022-2-0026/, identifier (INPLASY202220026).

Exploring Heat-Response Mechanisms of MicroRNAs Based on Microarray Data of Rice Post-meiosis Panicle.

To explore heat response mechanisms of mircoRNAs (miRNAs) in rice post-meiosis panicle, microarray analysis was performed on RNA isolated from rice post-meiosis panicles which were treated at 40°C for 0 min, 10 min, 20 min, 60 min, and 2 h. By integrating paired differentially expressed (DE) miRNAs and mRNA expression profiles, we found that the expression levels of 29 DE-miRNA families were negatively correlated to their 178 DE-target genes. Further analysis showed that the majority of miRNAs in 29 DE-miRNA families resisted the heat stress by downregulating their target genes and a time lag existed between expression of miRNAs and their target genes. Then, GO-Slim classification and functional identification of these 178 target genes showed that (1) miRNAs were mainly involved in a series of basic biological processes even under heat conditions; (2) some miRNAs might play important roles in the heat resistance (such as osa-miR164, osa-miR166, osa-miR169, osa-miR319, osa-miR390, osa-miR395, and osa-miR399); (3) osa-miR172 might play important roles in protecting the rice panicle under the heat stress, but osa-miR437, osa-miR418, osa-miR164, miR156, and miR529 might negatively affect rice fertility and panicle flower; and (4) osa-miR414 might inhibit the flowering gene expression by downregulation of LOC_Os 05g51830 to delay the heading of rice. Finally, a heat-induced miRNA-PPI (protein-protein interaction) network was constructed, and three miRNA coregulatory modules were discovered.

Ultrasonography for the Prediction of High-Volume Lymph Node Metastases in Papillary Thyroid Carcinoma: Should Surgeons Believe Ultrasound Results?

BACKGROUND: Lymph node metastasis (LNM) often occurs in papillary thyroid carcinoma (PTC); the efficacy of ultrasound for predicting high-volume lymph node metastases (LNMs) in patients with PTC remains unexplored. METHODS: The medical records of 2073 consecutive PTC patients were reviewed. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated to evaluate the efficacy of ultrasound. Risk factors for LNM/high-volume LNMs and lymph node involvement on ultrasound (usLNM) were identified by univariate and multivariate analyses. RESULTS: Of all the patients, 936 (45.2%) patients had LNMs, and 254 (12.3%) patients had high-volume LNMs. The sensitivity of ultrasound for detecting LNM/high-volume LNMs was 27.9% and 63.8%, respectively; the specificity was 93.1% and 90.3%, respectively. The NPV for ultrasound in detecting high-volume LNMs was 94.7%. In multivariate analysis, male sex (OR = 2.108, p < 0.001), tumor diameter > 1.0 cm (OR = 2.304, p < 0.001) and usLNM (+) (OR = 12.553, p < 0.001) were independent clinical risk factors for high-volume LNMs. Tumor diameter > 1 cm (OR = 3.036, p < 0.001) and male sex (OR = 1.642, p < 0.001) were independent clinical risk factors for usLNM; a skilled sonographer (OR = 1.121, p = 0.358) was not significantly associated with usLNM. CONCLUSIONS: Lymph node involvement found by ultrasound has great predictive value for high-volume LNMs; the NPV is very high for patients without lymph node involvement on ultrasound. The ultrasound results do not appear to be influenced by the experience of the sonographer.

Risk factors for high-volume lymph node metastases in cN0 papillary thyroid microcarcinoma.

BACKGROUND: Lymph node metastasis (LNM) often occurs in clinical lymph node negative (cN0) papillary thyroid microcarcinoma (PTMC). The risk factors for LNM, especially for high-volume LNM, were investigated in this study. METHODS: The medical records of 1,974 consecutive PTMC patients admitted to the Peking Union Medical College Hospital (PUMCH) from 2013 to 2015 were reviewed. Their clinicopathological features were collected. Univariate and multivariate analyses were performed to identify the risk factors for LNM/high-volume LNM. RESULTS: Of all the patients, cervical lymph node metastases were detected in 690 patients (34.95%), and high-volume LNM was detected in 75 patients (3.80%). The results of univariate analysis revealed that sex, age, chronic thyroiditis, multifocality, and tumor diameter were significantly correlated with LNM (P<0.05) and that sex, age, multifocality, and tumor diameter were significantly correlated with high-volume LNM (P<0.05). Multivariate logistic regression analysis demonstrated that male sex [odds ratio (OR) =1.657, P<0.001], multifocality (OR =1.601, P<0.001), and tumor diameter >0.5 cm (OR =1.770, P<0.001) were independent risk factors for LNM; age of 40-59 years old (OR =0.427, P<0.001), age ≥60 years old (OR =0.291, P<0.001), and chronic thyroiditis (OR =0.562, P<0.001) were independent protective factors for LNM. For high-volume LNM, male sex (OR =2.250, P=0.002), tumor diameter >0.5 cm (OR =3.664, P=0.013) and multifocality (OR =2.034, P=0.004) were independent risk factors, whereas age ≥40 years old (OR =0.240, P<0.001) was an independent protective factor. CONCLUSIONS: Lymph node metastases are common in cN0 PTMC, whereas high-volume LNM is rare. Active surveillance may be reasonable for patients with tumor diameter ≤0.5 cm, age ≥40 years old, female sex and isolated lesions.

A New Model System for Exploring Assembly Mechanisms of the HIV-1 Immature Capsid In Vivo.

The assembly of the HIV-1 immature capsid (HIC) is an essential step in the virus life cycle. In vivo, the HIC is composed of [Formula: see text] hexameric building blocks, and it takes 5-6 min to complete the assembly process. The involvement of numerous building blocks and the rapid timecourse makes it difficult to understand the HIC assembly process. In this work, we study HIC assembly in vivo by using differential equations. We first obtain a full model with 420 differential equations. Then, we reduce six addition reactions for separate building blocks to a single complex reaction. This strategy reduces the full model to 70 equations. Subsequently, the theoretical analysis of the reduced model shows that it might not be an effective way to decrease the HIC concentration at the equilibrium state by decreasing the microscopic on-rate constants. Based on experimental data, we estimate that the nucleating structure is much smaller than the HIC. We also estimate that the microscopic on-rate constant for nucleation reactions is far less than that for elongation reactions. The parametric collinearity investigation testifies the reliability of these two characteristics, which might explain why free building blocks do not readily polymerize into higher-order polymers until their concentration reaches a threshold value. These results can provide further insight into the assembly mechanisms of the HIC in vivo.