Enhancing Breast Cancer Diagnosis: A Nomogram Model Integrating AI Ultrasound and Clinical Factors.

PURPOSE: A novel nomogram incorporating artificial intelligence (AI) and clinical features for enhanced ultrasound prediction of benign and malignant breast masses. MATERIALS AND METHODS: This study analyzed 340 breast masses identified through ultrasound in 308 patients. The masses were divided into training (n = 260) and validation (n = 80) groups. The AI-based analysis employed the Samsung Ultrasound AI system (S-detect). Univariate and multivariate analyses were conducted to construct nomograms using logistic regression. The AI-Nomogram was based solely on AI results, while the ClinAI- Nomogram incorporated additional clinical factors. Both nomograms underwent internal validation with 1000 bootstrap resamples and external validation using the independent validation group. Performance was evaluated by analyzing the area under the receiver operating characteristic (ROC) curve (AUC) and calibration curves. RESULTS: The ClinAI-Nomogram, which incorporates patient age, AI-based mass size, and AI-based diagnosis, outperformed an existing AI-Nomogram in differentiating benign from malignant breast masses. The ClinAI-Nomogram surpassed the AI-Nomogram in predicting malignancy with significantly higher AUC scores in both training (0.873, 95% CI: 0.830-0.917 vs. 0.792, 95% CI: 0.748-0.836; p = 0.016) and validation phases (0.847, 95% CI: 0.763-0.932 vs. 0.770, 95% CI: 0.709-0.833; p < 0.001). Calibration curves further revealed excellent agreement between the ClinAI-Nomogram's predicted probabilities and actual observed risks of malignancy. CONCLUSION: The ClinAI- Nomogram, combining AI alongside clinical data, significantly enhanced the differentiation of benign and malignant breast masses in clinical AI-facilitated ultrasound examinations.

Characteristics and influencing factors of demoralization in patients with lung cancer: A latent class analysis.

OBJECTIVE: Demoralization has garnered increasing attention in recent years as a significant psychological distress. This study aims to identify latent classes of demoralization in lung cancer patients using Latent Class Analysis (LCA) from a person-centered perspective and to explore the factors influencing the latent classes of demoralization. METHODS: A cross-sectional study using convenience sampling was conducted among 567 lung cancer patients in three tertiary hospitals in China. LCA was employed to classify heterogeneous classes of demoralization. Multinomial logistic regression analyses were performed to explore the associations between demographic and clinical characteristics, as well as physical symptoms, resilience, family function, and coping strategies, with class membership in the identified heterogeneous subgroups of lung cancer patients. RESULTS: Three latent classes of demoralization were identified: the high demoralization group (Class 1, 14.8%), the moderate demoralization-distress and helplessness group (Class 2, 37.2%), and the low demoralization group (Class 3, 48.0%). In comparison to Class 3, lung cancer patients with hypertension, higher core symptom burden, poorer resilience, dysfunctional family dynamics, and resignation coping were more likely to belong to Class 1 and Class 2. CONCLUSIONS: The demoralization patterns in lung cancer patients were varied. Targeted intervention should be developed based on the characteristics of each class, and timely attention should be paid to high-risk patients.

Understanding factors influencing demoralization among cancer patients based on the bio-psycho-social model: A systematic review.

OBJECTIVE: Demoralization is a prevalent psychological problem among cancer patients and reflects a sense of subjective incompetence. This systematic review aims to identify factors influencing demoralization among cancer patients. METHODS: Eleven databases were systematically searched from database inception to 31 December 2020. Google Scholar and relevant reference lists were supplementarily searched. Studies reporting demoralization measured by Demoralization Scale and its influencing factors among cancer patients were included. A qualitative synthesis was conducted owing to the heterogeneity of the study outcome. RESULTS: A total of 49 studies involving 10,712 participants were included in this review. The results showed substantial effect size variation, but the psychological factors showed the strongest magnitude of association. Among the biological factors, the number of physical symptoms (mean r values [rs]: 0.331) was associated with increased demoralization. Among the psychological factors, negative psychological factors include hopelessness (mean rs: 0.633), desire for death (mean rs: 0.620), dignity-related distress (mean rs: 0.595), depression (mean rs: 0.593), anxiety (mean rs: 0.589), psychological distress (mean rs: 0.465), and suicidal ideation (mean rs: 0.460) were related to increased demoralization; whereas positive psychological factors including hope (mean rs: -0.565), attachment security (mean rs: -0.530), and sense of coherence (mean rs: -0.453) were related to decreased demoralization. Among the social factors, social support (mean rs: -0.330) was negatively related to demoralization, and the demographic factors were still controversial. Quality of life was considered to be at the intersection of biopsychosocial factors and negatively associated with demoralization (mean rs: -0.599). CONCLUSIONS: Demoralization is a consequence of the interaction of physical, psychological, and social factors among cancer patients. Factors with a significant effect should not be overlooked when designing an intervention to reduce demoralization. It is necessary to distinguish demoralization from other negative psychological states and further explore positive psychological factors influencing demoralization among cancer patients.

Barriers and facilitators to uptake of lung cancer screening: A mixed methods systematic review.

Numerous factors contribute to the low adherence to lung cancer screening (LCS) programs. A theory-informed approach to identifying the obstacles and facilitators to LCS uptake is required. This study aimed to identify, assess, and synthesize the available literature at the individual and healthcare provider (HCP) levels based on a social-ecological model and identify gaps to improve practice and policy decision-making. Systematic searches were conducted in nine electronic databases from inception to December 31, 2020. We also searched Google Scholar and manually examined the reference lists of systematic reviews to include relevant articles. Primary studies were scored for quality assessment. Among 3938 potentially relevant articles, 36 studies, including 25 quantitative and 11 qualitative studies, were identified for inclusion in the review. Fifteen common factors were extracted from 34 studies, including nine barriers and six facilitators. The barriers included individual factors (n = 5), health system factors (n = 3), and social/environmental factors (n = 1). The facilitators included only individual factors (n = 6). However, two factors, age and screening harm, remain mixed. This systematic review identified and combined barriers and facilitators to LCS uptake at the individual and HCP levels. The interaction mechanisms among these factors should be further explored, which will allow the construction of tailored LCS recommendations or interventions for the Chinese context.

Barriers and facilitators of lung cancer screening uptake: protocol of a mixed methods systematic review.

INTRODUCTION: The global uptake rates of lung cancer screening (LCS) with low-dose CT remain low. Since numerous factors contribute to the underuse of LCS, a theory-informed approach to identify and address the uptake of LCS barriers and facilitators is required. This study aims to document the methods which were used to identify, appraise, and synthesise the available qualitative, quantitative, and mixed methods evidence, addressing the barriers and facilitators at the individual and healthcare provider level, according to the social-ecological model, before identifying gaps to aid future practices and policies. METHODS AND ANALYSIS: The following databases will be searched: PubMed, Ovid (Journals @ Ovid Full Text and Ovid MEDLINE), EMBASE, CINAHL, PsycINFO, Cochrane Library, Chinese Biomedical Database, Chinese National Knowledge Infrastructure, and Wanfang database, from their creation up to 31 December 2020. Two reviewers will be involved in independently screening, reviewing, and synthesising the data; and calibration exercises will be conducted at each stage. Disagreements between the two reviewers will be resolved by arbitration by a third reviewer. The Critical Appraisal Checklist for Studies Reporting Prevalence Data from the Joanna Briggs Institute, the Critical Appraisal Skills Programme criteria adapted for qualitative studies, and the 16-item Quality Assessment Tool (QATSDD) will be used in the quality assessment of primary studies. We will perform data synthesis using the Review Manager software, V.5.3. ETHICS AND DISSEMINATION: This study is a review of published data and therefore needs no ethical approval. The findings of this systematic review will be published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: CRD42020162802.

Cognitive reactivity among high-risk individuals at the first and recurrent episode of depression symptomology: A structural equation modelling analysis.

Understanding the particular mechanisms by which vulnerability and capability factors influence cognitive reactivity (CR) can contribute to an enhanced capacity to adequately react to depression. However, few studies have explored the CR model. The main aim of the present study was to develop a model that specifies the predictive effects of CR for depression among individuals at high risk for first-episode and recurrent depression. A national cross-sectional, online study using convenience sampling was conducted among 587 vulnerable healthy individuals and 224 depressed patients in China. A battery of indices, including measures of CR, social support, resilience, self-compassion, life events, neuroticism, sleep condition, and negative emotion, were collected. A structural equation model was applied to analyse the data. The final first-episode and recurrent depressive symptoms of the CR models showed good model fit. According to the models, 45%-52% of the variance in depressive symptom was predicted by CR. Social support, self-compassion, resilience, and positive life events directly influenced CR, with ß values ranging from -0.18 to -0.24 (P < 0.01). Neuroticism, negative emotion, poor sleep conditions, and negative life events also directly and positively influenced CR (P < 0.01). The relationship between these negative or positive contributing factors and depression was also indirectly influenced by CR (P < 0.01). Our findings demonstrate the role of CR in the prevention and treatment of depression. The first-episode and recurrent depressive symptoms of the CR models considering both vulnerabilities and capabilities of CR in the psychopathology of depression provide a theoretical basis for interventions that reduce CR in high-risk populations.

Efficacy validation of a lymphatic drainage device for lymphedema drainage in a rat model.

BACKGROUND: Vascularized lymph node transfer (VLNT) is an effective surgery for extremity lymphedema. This study evaluated a lymphatic drainage device (LDD) for the drainage of accumulated fluid into the venous system. METHODS: Micropore filtering membranes with pore sizes of 5, 0.65, and 0.22 µm polyvinylidene difluoride, and 0.8 µm Nylon Net Filter were evaluated to determine the in vitro efficiency of drainage flow of an LDD. The two superior membranes were further used for the evaluation of the inflow and outflow of the LDD in vivo using 5% albumin. RESULTS: At 5 minutes, the volumes drained with 5, 0.65, and 0.22 µm polyvinylidene difluoride and 0.8 µm nylon membranes were 15.2, 2.77, 2.37, and 0.59 mL, respectively (P < .01). At 10 minutes, the collected volumes of 5 and 0.65 µm polyvinylidene difluoride were 1788 and 1051 µL (P = .3). The indocyanine green fluorescence was detected at 50 seconds for the 5 µm polyvinylidene difluoride membrane but not for the 0.65 µm membrane. CONCLUSIONS: The study successfully demonstrated the proof-of-concept of the LDD prototype that mimicked VLNT with drainage of 5% albumin into the venous system in a rat model.

Identification of plant vacuolar transporters mediating phosphate storage.

Plant vacuoles serve as the primary intracellular compartments for inorganic phosphate (Pi) storage. Passage of Pi across vacuolar membranes plays a critical role in buffering the cytoplasmic Pi level against fluctuations of external Pi and metabolic activities. Here we demonstrate that the SPX-MFS proteins, designated as PHOSPHATE TRANSPORTER 5 family (PHT5), also named Vacuolar Phosphate Transporter (VPT), function as vacuolar Pi transporters. Based on (31)P-magnetic resonance spectroscopy analysis, Arabidopsis pht5;1 loss-of-function mutants accumulate less Pi and exhibit a lower vacuolar-to-cytoplasmic Pi ratio than controls. Conversely, overexpression of PHT5 leads to massive Pi sequestration into vacuoles and altered regulation of Pi starvation-responsive genes. Furthermore, we show that heterologous expression of the rice homologue OsSPX-MFS1 mediates Pi influx to yeast vacuoles. Our findings show that a group of Pi transporters in vacuolar membranes regulate cytoplasmic Pi homeostasis and are required for fitness and plant growth.

Fibroblast growth factor 9 prevents MPP+-induced death of dopaminergic neurons and is involved in melatonin neuroprotection in vivo and in vitro.

Oxidative stress and down-regulated trophic factors are involved in the pathogenesis of nigrostriatal dopamine(DA)rgic neurodegeneration in Parkinson's disease. Fibroblast growth factor 9 (FGF9) is a survival factor for various cell types; however, the effect of FGF9 on DA neurons has not been studied. The antioxidant melatonin protects DA neurons against neurotoxicity. We used MPP(+) to induce neuron death in vivo and in vitro and investigated the involvement of FGF9 in MPP(+) intoxication and melatonin protection. We found that MPP(+) in a dose- and time-dependent manner inhibited FGF9 mRNA and protein expression, and caused death in primary cortical neurons. Treating neurons in the substantia nigra and mesencephalic cell cultures with FGF9 protein inhibited the MPP(+)-induced cell death of DA neurons. Melatonin co-treatment attenuated MPP(+)-induced FGF9 down-regulation and DA neuronal apoptosis in vivo and in vitro. Co-treating DA neurons with melatonin and FGF9-neutralizing antibody prevented the protective effect of melatonin. In the absence of MPP(+), the treatment of FGF9-neutralizing antibody-induced DA neuronal apoptosis whereas FGF9 protein reduced it indicating that endogenous FGF9 is a survival factor for DA neurons. We conclude that MPP(+) down-regulates FGF9 expression to cause DA neuron death and that the prevention of FGF9 down-regulation is involved in melatonin-provided neuroprotection.

The structural integrity exerted by N-terminal pyroglutamate is crucial for the cytotoxicity of frog ribonuclease from Rana pipiens.

Onconase, a cytotoxic ribonuclease from Rana pipiens, possesses pyroglutamate (Pyr) at the N-terminus and has a substrate preference for uridine-guanine (UG). To identify residues responsible for onconase's cytotoxicity, we cloned the rpr gene from genomic DNA and expressed it in Escherichia coli BL21(DE3). The recombinant onconase with Met at the N-terminus had reduced thermostability, catalytic activity and antigenicity. Therefore, we developed two methods to produce onconase without Met. One relied on the endogeneous E.coli methionine aminopeptidase and the other relied on the cleavage of a pelB signal peptide. The Pyr1 substitutional variants maintained similar secondary structures to wild-type onconase, but with less thermostability and specific catalytic activity for the innate substrate UG. However, the non-specific catalytic activity for total RNAs varied depending on the relaxation of base specificity. Pyr1 promoted the structural integrity by forming a hydrogen bond network through Lys9 in alpha1 and Val96 in beta6, and participated in catalytic activity by hydrogen bonds to Lys9 and P(1) catalytic phosphate. Residues Thr35 and Asp67 determined B(1) base specificity, and Glu91 determined B(2) base specificity. The cytotoxicity of onconase is largely determined by structural integrity and specific catalytic activity for UG through Pyr1, rather than non-specific activity for total RNAs.