The Uncharted Territories of Esophageal Cancer with Cardiac and Skeletal Muscle Metastasis: A Case Report and Literature Review.

Background: Esophageal cancer (EC) comprises 1% of all diagnosed cancers in the USA. It is more common in other parts of the world. If there is distant metastasis, the relative survival rate is 6%. There are no standardized screening methods for EC. Case Presentation: We reported a four-year case of esophageal cancer, a P53-positive mutation with atypical distant metastasis to the cardiac and skeletal muscles. The patient was managed with multimodal therapy, including immunotherapy, which could have been a factor in prolonged survival. Conclusions: Distant metastases are typically seen postmortem, and with prolonged survival, we are able to find such unique metastases antemortem. Despite a history of negative scans, the patient's ctDNA (circulating tumor DNA) remained positive, which was a better predictor of recurrence in this case. Future research is required to establish cost-effective screening methods and standardized treatments.

Children and adolescents with differentiated thyroid cancer from 1998 to 2018: a retrospective analysis.

OBJECTIVES: This study aims to investigate the clinical features of differentiated thyroid carcinoma (DTC) in children and adolescents under 18 years and assess the impact of surgery combined with thyroid hormone and radioactive iodine (RAI) on their prognosis. METHODS: A retrospective observational study was conducted, involving children/adolescents with DTC who underwent surgery at the Head and Neck Department of Tianjin Medical University Cancer Institute and Hospital from January 1998 to December 2018. RESULTS: Among 198 patients, 130 (65.7 %) were female. According to the American Thyroid Association guidelines, cases were categorized as low (106, 53.5 %), intermediate (54, 27.3 %), and high (38, 19.2 %) risk. The follow-up duration ranged from 3 to 23 years. Local recurrence and distant metastasis were identified in 21 (10.6 %) and 14 (7.1 %) cases, respectively. All patients received levothyroxine, while RAI therapy was administered to intermediate- and high-risk patients. The local recurrence and distant metastasis rates in these two groups were 33.3 and 39.5 %, respectively, with no recurrence or metastasis in the low-risk group. Persistent without structural evidence of disease were 0.9, 3.7, and 26.3 % at end of follow-up for the low-, intermediate-, and high-risk groups, respectively. The overall survival rates for all three groups were 100 %, while disease-free survival rates were 99.1, 63.0, and 34.2 % for the low-, intermediate-, and high-risk groups, respectively. CONCLUSIONS: Children/adolescents with low-risk DTC exhibited a favorable prognosis even without RAI. However, intermediate- and high-risk DTC patients, despite RAI and levothyroxine treatment, showed elevated rates of persistent disease, local recurrence, and distant metastasis.

Exploring the impact of digital concept mapping methods on nurse students' learning anxiety, learning motivation.

In involuntary distance education, like during epidemics and wars, students often feel heightened learning anxiety, impacting outcomes. Despite innovative teaching methods, many face hurdles in distance learning. We want to propose specific strategies to solve learning difficulties in distance education. AIM: This study explored whether using digital concept maps (DCM) in physiology courses can reduce learning anxiety among nursing students. DESIGN: The study was quasi-experimental, including a pre-and post-test control group. METHODS: 71 nursing students aged 16-18 enrolled in a physiology course were recruited in the study. DCM was the intervention as a tool for in-person learning (first 12 weeks) and distant learning (final six weeks). Each student was required to complete the assignments independently to compare learning outcomes. Questionnaires were administered, and an assignment evaluation was completed before and after the course's different formats. RESULTS: DCM using software using mobile vehicles (mobile, notebook, pad) is digital learning to help nursing students learn difficult subjects. DCM improved the students' learning motivation and effectiveness more in distance learning than in-person learning, decreasing learning anxiety in both face-to-face and distance learning. CONCLUSIONS: DCM promoted students' self-regulated learning and positively affected learning outcomes by increasing motivation and reducing stress. This study offers a tailored teaching framework for international settings to reduce student anxiety and improve learning effectiveness.

Development of a novel dynamic nomogram for predicting overall survival in anaplastic thyroid cancer patients with distant metastasis: a population-based study based on the SEER database.

Background: Anaplastic thyroid cancer (ATC) is highly invasive, prone to distant metastasis (DM), and has a very poor prognosis. This study aims to construct an accurate survival prediction model for ATC patients with DM, providing reference for comprehensive assessment and treatment planning. Methods: We extracted data of ATC patients with DM diagnosed between 2004 and 2019 from the SEER database, randomly dividing them into a training set and a validation set in a ratio of 7:3. Univariate and multivariate Cox regression analyses were sequentially performed on the training set to identify independent prognostic factors for overall survival (OS) and construct nomograms for 3-month, 6-month, and 8-month OS for ATC patients with DM based on all identified independent prognostic factors. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) curve analysis, and calibration curves were separately plotted on the training and validation sets to demonstrate the model's performance. Furthermore, patients were stratified into high- and low-risk groups based on their risk scores, and the Kaplan-Meier (KM) survival curves were used to illustrate the survival differences between the two groups. Results: A total of 322 patients were included in this study. Univariate and multivariate Cox regression analyses identified five independent prognostic factors for OS in ATC patients with DM: surgery, tumor size, age, chemotherapy, and radiotherapy. Nomograms for 3-month, 6-month, and 8-month OS were established based on these factors. The training set AUC values (3-month AUC: 0.767, 6-month AUC: 0.789, 8-month AUC: 0.795) and validation set AUC values (3-month AUC: 0.753, 6-month AUC: 0.798, 8-month AUC: 0.806) as well as the calibration curves demonstrated excellent applicability and accuracy of the model. Additionally, the DCA curves indicated substantial clinical net benefit of the model. The KM curves also confirmed the model's excellent stratification ability for patient OS. Conclusion: The nomogram developed in this study accurately predicts OS for ATC patients with DM. It can assist clinicians in formulating appropriate treatment strategies for these patients.

The addition of Psathyrostachys Huashanica Keng 6Ns large segment chromosomes has positive impact on stripe rust resistance and plant spikelet number of common wheat.

BACKGROUND: Developing novel germplasm by using wheat wild related species is an effective way to rebuild the wheat resource bank. The Psathyrostachys huashanica Keng (P. huashanica, 2n = 2x = 14, NsNs) is regarded as a superior species to improve wheat breeding because of its multi-resistance, early maturation and numerous tiller traits. Introducing genetic components of P. huashanica into the common wheat background is the most important step in achieving the effective use. Therefore, the cytogenetic characterization and influence of the introgressed P. huashanica large segment chromosomes in the wheat background is necessary to be explored. RESULTS: In this study, we characterized a novel derived line, named D88-2a, a progeny of the former characterized wheat-P. huashanica partial amphiploid line H8911 (2n = 7x = 49, AABBDDNs). Cytological identification showed that the chromosomal composition of D88-2a was 2n = 44 = 22II, indicating the addition of exogenous chromosomes. Genomic in situ hybridization demonstrated that the supernumerary chromosomes were a pair of homologues from the P. huashanica and could be stably inherited in the common wheat background. Molecular markers and 15 K SNP array indicated that the additional chromosomes were derived from the sixth homoeologous group (i.e., 6Ns) of P. huashanica. Based on the distribution of the heterozygous single-nucleotide polymorphism sites and fluorescence in situ hybridization karyotype of each chromosome, this pair of additional chromosomes was confirmed as P. huashanica 6Ns large segment chromosomes, which contained the entire short arm and the proximal centromere portion of the long arm. In terms of the agronomic traits, the addition line D88-2a exhibited enhanced stripe rust resistance, improved spike characteristics and increased protein content than its wheat parent line 7182. CONCLUSIONS: The new wheat germplasm D88-2a is a novel cytogenetically stable wheat-P. huashanica 6Ns large segment addition line, and the introgressed large segment alien chromosome has positive impact on plant spikelet number and stripe rust resistance. Thus, this germplasm can be used for genetic improvement of cultivated wheat and the study of functional alien chromosome segment.

Genomic profiling of lymph node and distant metastases from papillary and poorly differentiated thyroid carcinomas.

PURPOSE: To perform a molecular profiling of the metastases from papillary thyroid carcinomas (PTCs) and poorly differentiated thyroid carcinomas (PDTCs). METHODS: We retrieved and analyzed the molecular and clinical features of 136 metastases from PTCs and 35 metastases from PDTCs subjected to targeted DNA sequencing, from cBioPortal. The clinicopathological data included the number and location of the metastases, and genomic data included mutations, translocations, copy number alterations and fraction of the genome altered (FGA). RESULTS: Bone metastases from PTCs had a lower frequency of BRAF mutations than the lymph node metastases (LNMs) (43% vs 88%, p < 0.01), and a higher frequency of RBM10 and NRAS mutations than the LNMs (21% vs 3% for both, p < 0.05). The FGA of the bone metastases was higher than the FGA of the lung metastases (5.6% vs 1.3%, p < 0.05). The frequency of RET translocations was higher in the lung metastases from PTCs than the LNMs (15% vs 3%, p < 0.05). The LNMs from PTC patients harboring 4 or more distant metastases (DMs) had a higher frequency of TERT promoter mutations than the LNMs from patients harboring less than 4 DMs (96% vs 65%, p < 0.001). SDHA gene amplifications were enriched in the bone metastases from PDTCs and absent in the LNMs (38% vs 0%, p < 0.05). CONCLUSION: Metastases from PTCs and PDTCs harbor clinically relevant alterations affecting distinct body locations, such as NRAS and RBM10 mutations, RET translocations and SDHA amplifications that may be explored therapeutically.

Predicting distant metastasis in nasopharyngeal carcinoma using gradient boosting tree model based on detailed magnetic resonance imaging reports.

BACKGROUND: Development of distant metastasis (DM) is a major concern during treatment of nasopharyngeal carcinoma (NPC). However, studies have demonstrated improved distant control and survival in patients with advanced NPC with the addition of chemotherapy to concomitant chemoradiotherapy. Therefore, precise prediction of metastasis in patients with NPC is crucial. AIM: To develop a predictive model for metastasis in NPC using detailed magnetic resonance imaging (MRI) reports. METHODS: This retrospective study included 792 patients with non-distant metastatic NPC. A total of 469 imaging variables were obtained from detailed MRI reports. Data were stratified and randomly split into training (50%) and testing sets. Gradient boosting tree (GBT) models were built and used to select variables for predicting DM. A full model comprising all variables and a reduced model with the top-five variables were built. Model performance was assessed by area under the curve (AUC). RESULTS: Among the 792 patients, 94 developed DM during follow-up. The number of metastatic cervical nodes (30.9%), tumor invasion in the posterior half of the nasal cavity (9.7%), two sides of the pharyngeal recess (6.2%), tubal torus (3.3%), and single side of the parapharyngeal space (2.7%) were the top-five contributors for predicting DM, based on their relative importance in GBT models. The testing AUC of the full model was 0.75 (95% confidence interval [CI]: 0.69-0.82). The testing AUC of the reduced model was 0.75 (95%CI: 0.68-0.82). For the whole dataset, the full (AUC = 0.76, 95%CI: 0.72-0.82) and reduced models (AUC = 0.76, 95%CI: 0.71-0.81) outperformed the tumor node-staging system (AUC = 0.67, 95%CI: 0.61-0.73). CONCLUSION: The GBT model outperformed the tumor node-staging system in predicting metastasis in NPC. The number of metastatic cervical nodes was identified as the principal contributing variable.

Transcriptomics reveals that NAD(P)H affects the development of the Zig-zag eel (Mastacembelus armatus ♀) × Spiny eel (Sinobdella sinensis ♂) hybrid offspring leading to low hatching rates.

Zig-zag eel (Mastacembelus armatus (2 n = 48)) and Spiny eel (Sinobdella sinensis (2 n = 48)) are two species of the Mastacembelidae family commonly found in southern China. Hybridization between the two has a very high deformity rate and a very low hatching rate. In order to investigate the reasons for this, the first hybridization between M. armatus and S. sinensis was carried out using artificial insemination, and the embryonic development of the hybrid offspring was examined using microphotography, and the malformations of the hybrid offspring were investigated by transcriptomics. The experiments showed that the average egg production was 4265.7 ± 322.94 (Mean ± SD), the average fertilization rate of hybrid offspring was 98.67 ± 0.58 % (Mean ± SD), the hatching rate was 12.06 ± 3.44 % (Mean ± SD), the deformity rate was 98.15 ± 3.21 % (Mean ± SD), and the embryonic development successively went through the five main stages of fertilized egg, egg cleavage, embryo formation, organogenesis, and exertion of membranes. Transcriptomics showed that the expression of NAD(P)H-related enzyme activity DEGs was increased, and many DEGs related to cell signaling molecule transmission and metabolic regulation are enriched in KEGG pathways, such as IL-17 signaling pathway, Osteoclast differentiation, TNF signaling pathway and MAPK signaling pathway. etc. The major types of DEGs corresponded to those coding for proteins. This study suggests that the high malformation rate in hybrid offspring may be caused by impaired synthesis of proteins during embryonic development.

Clinicopathological spectrum, management, and outcome of ectopic parathyroid carcinoma: Experience with 24 cases.

PURPOSE: Ectopic parathyroid carcinoma (EPC) is a rare clinical entity with multiple diagnostic pitfalls, making surgical cures challenging. We assessed the clinicopathological spectrum and outcome of EPCs. METHODS: In this retrospective cohort study, 24 EPCs were identified from 133 PC patients treated at a tertiary referral center. The relationship between clinicopathological findings and locations was analyzed. RESULTS: The locations of EPCs were predominantly intrathyroidal (62.5%), followed by 16.7% in the mediastinum, 8.3% in the retropharyngeal space, 8.3% in the carotid sheath, and 4.2% in the upper neck. Intrathyroidal EPC patients experienced higher serum calcium (p = 0.020), a higher rate of vascular invasion (p = 0.040), and a slightly higher incidence of non-R0 initial resection (p = 0.092) than those in other ectopic locations. Intrathyroidal EPC patients also suffered a trend of higher upper aerodigestive tract (UAT) invasion rate (p = 0.070) and higher risks of distant metastasis (p = 0.037) than the other PC patients. The 5-year disease-free survival rate after surgery was slightly compromised at 41.5% in intrathyroidal EPC patients compared with 77.8% among those in other ectopic locations (p = 0.143) and 59.7% among the other PC patients (log-rank = 3.194; p = 0.074), though without statistical significance. CONCLUSION: Intrathyroidal EPC might cause a more biochemically and invasively distinct PC picture compared with other PCs. Special caution should be exercised in the preoperative diagnosis and management of such cases.

Surveillance for Distant Metastasis in Breast Cancer Patients Who Underwent Contemporary Management: A Report from the Korean Breast Cancer Society Survivor Research Group.

BACKGROUND: Current guidelines recommend against the use of routine imaging tests to detect distant metastasis in asymptomatic breast cancer patients. However, recent advancements in effective therapeutics and diagnostic accuracy have raised the need to reassess the clinical efficacy of intensive metastasis surveillance. We report the results of a multicenter retrospective study to investigate the association between intensive imaging studies and survival outcomes. PATIENTS AND METHODS: We retrospectively reviewed the data of 4130 patients who underwent surgery from 11 hospitals in Korea between January 2010 and December 2011. Patients were divided into two groups on the basis of the intensity of metastasis imaging studies during their disease-free period. The types and intervals of the imaging studies were based on each physician's decisions. RESULTS: High-intensive screening showed a shorter distant metastasis-free survival [p < 0.001, hazard ratio (HR) 1.62; 95% confidence interval (CI) 1.29-2.04], especially for patients in whom bone or lung was the first site of metastasis. With a median follow-up period of 110.0 months, the 5-year breast cancer-specific survival (BCSS) rate was 96.5%. The high-intensity screening group showed significantly poorer BCSS compared with the low-intensity screening group (p < 0.001, HR 3.13; 95% CI 2.32-4.21). However, both multivariable analysis and propensity score matching analysis showed no significant association between the screening intensity and BCSS. CONCLUSIONS: Frequent imaging studies to detect distant metastasis were associated with earlier detection of distant metastasis, especially for lung and bone metastasis. However, intensive surveillance showed no apparent association with BCSS despite the use of currently available treatments.

Distant lymph node metastasis in differentiated thyroid cancer: A population-based cohort study.

BACKGROUND: Cervical lymph node metastasis (LNM) is the most common clinical event in patients with differentiated thyroid cancer (DTC). However, the incidence, pattern, treatment, and prognosis of distant LNM are yet to be reported. METHODS: DTC patients with distant LNM were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2016 and 2020. Multivariate models and propensity score matching (PSM) were used to account for the effects of covariates. The Kaplan-Meier method was used to evaluate the overall survival (OS) and cancer-specific survival (CSS). A nomogram was established to predict the probability of distant LNM in DTC patients, with calibration and Receiver Operating Characteristic (ROC) curves utilized to validate the nomogram's accuracy. RESULTS: Of the 42,339 DTC patients screened, 100 (0.24 %) patients presented with distant LNM. Risk factors including age, sex, T stage, N stage, bone metastasis, brain metastasis, and lung metastasis were included in the nomogram to predict the probability of distant LNM. The calibration curve of the nomogram was close to the ideal diagonal line and the area under the curve (AUC) of the ROC curve is 0.953. Distant LNM showed a worse prognosis after adjusting for confounders compared with non-distant LNM (P < 0.05). Remarkably, radioactive iodine (RAI) therapy did not improve the OS and CSS in DTC patients with distant LNM in the overall or PSM cohort. CONCLUSIONS: Distant LNM presents as a comparatively rare but grave condition with a substantial negative impact on prognosis in patients with DTC. Identified risk factors of distant LNM are older age, male, advanced T stage and N stage, bone metastasis, brain metastasis, and lung metastasis. Remarkably, the current RAI therapy does not appear to significantly improve the survival outcome of DTC patients with distant LNM.

A nomogram combining neutrophil to lymphocyte ratio (NLR) and prognostic nutritional index (PNI) to predict distant metastasis in gastric cancer.

In this study, We aim to explore the association between the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), lymphocyte to monocyte ratio (LMR) and prognostic nutritional index (PNI) and distant metastasis of gastric cancer and develop an efficient nomogram for screening patients with distant metastasis. A total of 1281 inpatients with gastric cancer were enrolled and divided into the training and validation set.Univariate, Lasso regression and Multivariate Logistic Regression Analysis was used to identify the risk factors of distant metastasis. The independent predictive factors were then enrolled in the nomogram model. The nomogram's predictive perform and clinical practicality was evaluated by receiver operating characteristics (ROC) curves, calibration curves and decision curve analysis. Multivariate Logistic Regression Analysis identified D-dimer, CA199, CA125, NLR and PNI as independent predictive factors. The area under the curve of our nomogram based on these factors was 0.838 in the training cohort and 0.811 in the validation cohort. The calibration plots and decision curves demonstrated the nomogram's good predictive performance and clinical practicality in both training and validation cohort. Therefore,our nomogram could be an important tool for clinicians in screening gastric cancer patients with distant metastasis.

Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.

Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of research utilizing big data to predict UM distant metastasis. This study leveraged machine learning methods on the Surveillance, Epidemiology, and End Results (SEER) database to forecast the risk probability of distant metastasis. Therefore, the information on UM patients from the SEER database (2000-2020) was split into a 7:3 ratio training set and an internal test set based on distant metastasis presence. Univariate and multivariate logistic regression analyses assessed distant metastasis risk factors. Six machine learning methods constructed a predictive model post-feature variable selection. The model evaluation identified the multilayer perceptron (MLP) as optimal. Shapley additive explanations (SHAP) interpreted the chosen model. A web-based calculator personalized risk probabilities for UM patients. The results show that nine feature variables contributed to the machine learning model. The MLP model demonstrated superior predictive accuracy (Precision = 0.788; ROC AUC = 0.876; PR AUC = 0.788). Grade recode, age, primary site, time from diagnosis to treatment initiation, and total number of malignant tumors were identified as distant metastasis risk factors. Diagnostic method, laterality, rural-urban continuum code, and radiation recode emerged as protective factors. The developed web calculator utilizes the MLP model for personalized risk assessments. In conclusion, the MLP machine learning model emerges as the optimal tool for predicting distant metastasis in UM patients. This model facilitates personalized risk assessments, empowering early and tailored treatment strategies.

Characteristics and risk differences of different tumor sizes on distant metastases of pancreatic neuroendocrine tumors: A retrospective study in the SEER database.

BACKGROUND: The rate of distant metastasis in patients with pancreatic neuroendocrine tumors (PNETs) is 20%-50% at the time of initial diagnosis. However, whether tumor size can predict distant metastasis for PNETs remains unknown up to date. METHODS: We used Surveillance, Epidemiology, and End Results (SEER) population-based data to collect 6089 patients with PNETs from 2010 to 2019. The optimal cut-off point of tumor size to predict distant metastasis was calculated by Youden's index. Multivariate logistic regression analysis was used to figure out the association between tumor size and distant metastasis patterns. RESULTS: The most common metastatic site was liver (27.2%), followed by bone (3.0%), lung (2.3%) and brain (0.4%). Based on an optimal cut-off value of tumor size (25.5 mm) for predicting distant metastasis determined by Youden's index, patients were categorized into groups of tumor size < 25.5 mm and ≥ 25.5 mm. Multivariate logistic regression analyses showed that, compared with < 25.5 mm, tumor size ≥ 25.5 mm was an independent risk predictor of overall distant metastasis [odds ratio (OR) = 4.491, 95% confidence interval (CI): 3.724-5.416, P < 0.001] and liver metastasis (OR = 4.686, 95% CI: 3.886-5.651, P < 0.001). CONCLUSIONS: Tumor size ≥ 25.5 mm was significantly associated with more overall distant and liver metastases. Timely identification of distant metastasis for tumor size ≥ 25.5 mm may provide survival benefit for timely and precise treatment.

Comprehensive Analysis of a Six-Gene Signature Predicting Survival and Immune Infiltration of Liposarcoma Patients and Deciphering Its Therapeutic Significance.

BACKGROUND: As a common soft tissue sarcoma, liposarcoma (LPS) is a heterogeneous malignant tumor derived from adipose tissue. Due to the high risk of metastasis and recurrence, the prognosis of LPS remains unfavorable. To improve clinical treatment, a robust risk prediction model is essential to evaluate the prognosis of LPS patients. METHODS: By comprehensive analysis of data derived from GEO datasets, differentially expressed genes (DEGs) were obtained. Univariate and Lasso Cox regressions were subsequently employed to reveal distant recurrence-free survival (DRFS)-associated DEGs and develop a prognostic gene signature, which was assessed by Kaplan-Meier survival and ROC curve. GSEA and immune infiltration analyses were conducted to illuminate molecular mechanisms and immune correlations of this model in LPS progression. Furthermore, a correlation analysis was involved to decipher the therapeutic significance of this model for LPS. RESULTS: A six-gene signature was developed to predict DRFS of LPS patients and showed higher precision performance in more aggressive LPS subtypes. Then, a nomogram was further established for clinical application based on this risk model. Via GSEA, the high-risk group was significantly enriched in cell cycle-related pathways. In the LPS microenvironment, neutrophils, memory B cells and resting mast cells exhibited significant differences in cell abundance between high-risk and low-risk patients. Moreover, this model was significantly correlated with therapeutic targets. CONCLUSION: A prognostic six-gene signature was developed and significantly associated with cell cycle pathways and therapeutic target genes, which could provide new insights into risk assessment of LPS progression and therapeutic strategies for LPS patients to improve their prognosis.

Risk factors associated with self-rated health among elderly females with different visual abilities in Chinese urban areas: a population-based study.

OBJECTIVE: Self-rated health (SRH) has been documented as an important predictor of quality of life among the elderly and its risk factors are vision-specific among elderly males. The aim of this study was to clarify vision-specific risk factors to SRH among elderly females without dementia in Chinese urban areas. METHODS: From March to November 2012, 2147 elderly women in Liaoning Province of China were selected using a stratified sampling method. After cognitive screening, 1956 participants without dementia were finally enrolled. A questionnaire including SRH, visual ability and factors including demographic characteristics, physical conditions, lifestyle factors, social psychological status and social activities were analyzed. Multivariate logistic regression was used to clarify the association of SRH with risk factors, while stepwise multivariate logistic regression was used to examine the vision-specific associations with SRH. RESULTS: The mean age was 73.6 ± 5.82 (mean ± SD). The percentages of good SRH in good and impaired visual ability groups were 36.2% and 24.4%, respectively. Most characteristics between elderly females with different visual abilities were significantly different. Visual ability had interactions with physical conditions, lifestyle factors and social activities to affect SRH. Among elderly females with good visual ability, depressive symptoms, rather than chronic disease had the strongest association with good SRH followed by marital status, regular diet, going out alone to distant places, taking a walk, smoking and alcohol consumption. In the impaired visual ability group, going out alone to distant places had the strongest association with good SRH followed by chronic disease, filial piety, taking a walk, participating in entertainment, ethnicity, quality of sleep, worrying about falling and alcohol consumption. CONCLUSIONS: Good SRH status was at a low level especially among elderly females with impaired visual ability and the risk factors differed between elderly females with different visual abilities. Social psychological status was crucial for SRH among elderly females with good visual ability whereas physical conditions were prominent for impaired visual ability group.

Development and validation of AI models using LR and LightGBM for predicting distant metastasis in breast cancer: a dual-center study.

Objective: This study aims to develop an artificial intelligence model utilizing clinical blood markers, ultrasound data, and breast biopsy pathological information to predict the distant metastasis in breast cancer patients. Methods: Data from two medical centers were utilized, Clinical blood markers, ultrasound data, and breast biopsy pathological information were separately extracted and selected. Feature dimensionality reduction was performed using Spearman correlation and LASSO regression. Predictive models were constructed using LR and LightGBM machine learning algorithms and validated on internal and external validation sets. Feature correlation analysis was conducted for both models. Results: The LR model achieved AUC values of 0.892, 0.816, and 0.817 for the training, internal validation, and external validation cohorts, respectively. The LightGBM model achieved AUC values of 0.971, 0.861, and 0.890 for the same cohorts, respectively. Clinical decision curve analysis showed a superior net benefit of the LightGBM model over the LR model in predicting distant metastasis in breast cancer. Key features identified included creatine kinase isoenzyme (CK-MB) and alpha-hydroxybutyrate dehydrogenase. Conclusion: This study developed an artificial intelligence model using clinical blood markers, ultrasound data, and pathological information to identify distant metastasis in breast cancer patients. The LightGBM model demonstrated superior predictive accuracy and clinical applicability, suggesting it as a promising tool for early diagnosis of distant metastasis in breast cancer.

The predictive value of LGR for distant metastasis-free survival in locally advanced rectal cancer patients.

Studies show that inflammation induced by cancer is a key factor in carcinogenesis. Here, we sought to assess the relationship between patients with locally advanced rectal cancer (LARC) and the lymphocyte to neutrophil granulocyte ratio (LGR) prior to neoadjuvant chemoradiotherapy (nCRT) and distant metastasis-free survival (DMFS). Using a receiver operating characteristic (ROC) analysis of 326 LARC patients who underwent total mesorectal excision (TME) surgery and neoadjuvant chemoradiotherapy, we were able to determine the ideal LGR cutoff value. We used the Kaplan-Meier method and univariate and multivariate Cox regression to study the clinical characteristics of LARC patients in comparison between the low LGR group and the high LGR group. DMFS analysis was one of the primary clinical variables examined. We discovered that the low LGR group of LARC patients had a longer DMFS than the high LGR group. The median duration of follow-up for LARC patients was 89.4 months, with a significantly lower DMFS observed in the high LGR group compared to the low LGR group. Multivariate Cox regression analysis revealed that LARC patients with low LGR levels, early ypTNM stages, and BRAF wild had longer DMFS. LGR prior to nCRT was a critical prognostic indicator that contributed extra predictive value beyond conventional clinicopathological characteristics to predict the outcome of LARC patients receiving neoadjuvant chemoradiotherapy followed by TME surgery.