Objective:To construct a self-management scheme for osteoporosis related to endocrine therapy in patients with early-stage breast cancer, so as to provide a reference for clinical nursing intervention.Methods:In the chronic disease self-management domain theory as the instruction, using literature research, the semi-structured interview to build the first draft of the plan, through the expert meeting law to plan to revise the first draft, and form a self-management scheme for osteoporosis related to endocrine therapy in patients with early-stage breast cancer.Results:A total of 10 experts were included, aged 37-47 (42.70 ± 3.43) years. The recovery rate of the expert questionnaire was 10/10, the expert authority coefficient was 0.93, and the coefficient of variation of each item ranged from 0.06 to 0.19. The final formed self-management scheme for osteoporosis related to endocrine therapy in patients with early-stage breast cancer includes three intervention modules: self-prevention, self-monitoring, and self-coping. It encompasses six intervention themes: enhancing knowledge reserves, non-pharmacological prevention, pharmacological prevention, risk assessment and self-reporting of symptoms, non-pharmacological intervention, and pharmacological intervention.Conclusions:The construction of the self-management scheme for osteoporosis related to endocrine therapy in patients with early-stage breast cancer is of great significance. The content of the scheme is scientific, reliable and targeted, which can provide guidance for the self-management of osteoporosis in patients with early breast cancer during endocrine therapy.

Objective:To construct a self-management scheme for osteoporosis related to endocrine therapy in patients with early-stage breast cancer, so as to provide a reference for clinical nursing intervention.Methods:In the chronic disease self-management domain theory as the instruction, using literature research, the semi-structured interview to build the first draft of the plan, through the expert meeting law to plan to revise the first draft, and form a self-management scheme for osteoporosis related to endocrine therapy in patients with early-stage breast cancer.Results:A total of 10 experts were included, aged 37-47 (42.70 ± 3.43) years. The recovery rate of the expert questionnaire was 10/10, the expert authority coefficient was 0.93, and the coefficient of variation of each item ranged from 0.06 to 0.19. The final formed self-management scheme for osteoporosis related to endocrine therapy in patients with early-stage breast cancer includes three intervention modules: self-prevention, self-monitoring, and self-coping. It encompasses six intervention themes: enhancing knowledge reserves, non-pharmacological prevention, pharmacological prevention, risk assessment and self-reporting of symptoms, non-pharmacological intervention, and pharmacological intervention.Conclusions:The construction of the self-management scheme for osteoporosis related to endocrine therapy in patients with early-stage breast cancer is of great significance. The content of the scheme is scientific, reliable and targeted, which can provide guidance for the self-management of osteoporosis in patients with early breast cancer during endocrine therapy.

Mechanical pain is one of the most common causes of clinical pain, but there remains a lack of effective treatment for debilitating mechanical and chronic forms of neuropathic pain. Recently, neurotoxin GsMTx4, a selective mechanosensitive (MS) channel inhibitor, has been found to be effective, while the underlying mechanism remains elusive. Here, with multiple rodent pain models, we demonstrated that a GsMTx4-based 17-residue peptide, which we call P10581, was able to reduce mechanical hyperalgesia and neuropathic pain. The analgesic effects of P10581 can be as strong as morphine but is not toxic in animal models. The anti-hyperalgesic effect of the peptide was resistant to naloxone (an μ-opioid receptor antagonist) and showed no side effects of morphine, including tolerance, motor impairment, and conditioned place preference. Pharmacological inhibition of TRPV4 by P10581 in a heterogeneous expression system, combined with the use of Trpv4 knockout mice indicates that TRPV4 channels may act as the potential target for the analgesic effect of P10581. Our study identified a potential drug for curing mechanical pain and exposed its mechanism.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Systemic lupus erythematosus (SLE) is an autoimmune disease accompanied by various complications, and the exact etiology remains unclear. Treatments for SLE encompass hormone therapy, plasma exchange and immunoadsorption, and targeted biological therapies. Berbamine (BBM), a cellular immunopotentiator with diverse biological functions, has not been reported to have immunomodulatory and therapeutic effects on SLE. The mice were divided into control group, model group, positive control group, low, medium and high BBM groups. In control group, C57BL/6J wild mice received intraperitoneal injection of saline. In model group, MRL/lpr lupus mice were treated with intraperitoneal injection of saline. In positive control group, MRL/lpr lupus mice received intragastric administration of hydroxychloroquine sulfate tablets [Plaquenil, 150 mg/(kg·d)]. In BBM groups, MRL/lpr lupus mice received intragastric administration of different concentration of BBM respectively [20 mg/(kg·d), 50 mg/(kg·d), 100 mg/(kg·d)]. After 8 weeks of treatment, blood was collected from the retro-orbital venous plexus, and ELISA was used to detect the levels of anti-double-stranded DNA (dsDNA) antibodies, antinuclear antibodies (ANA), and anti-small nuclear ribonucleoprotein/Sm (snRNP/Sm) antibodies. Spleen tissues were collected for analysis of Th1/Th2 ratio by flow cytometry. The RNA and protein of spleen were extracted, and the levels of T-box transcription factor T-bet and GATA3 (GATA binding protein 3) mRNA and protein were detected by qRT-PCR and Western blot. The proliferation of white blood cells in the blood was tested by blood routine test. The histopathological changes of kidneys of each group were detected by HE staining. Compared with the model group, the levels of ANA, anti-dsDNA, and anti-snRNP/Sm antibodies were significantly reduced in the BBM-treated groups. The Th1/Th2 ratio was significantly decreased in the model group, but reversed by BBM. Compared with the control group, T-bet expression was significantly downregulated, while GATA3 expression was significantly upregulated in the model group. After BBM intervention, T-bet expression significantly increased, while GATA3 expression decreased compared with the model group. The number of white blood cells significantly decreased in the model group, and increased in the BBM-treated groups. In the model group, the glomerular mesangial and endothelial cells showed significant hyperplasia, clear thrombus was observed in the dilated capillaries, and inflammatory cells infiltrated in the renal interstitium. In medium and high BBM groups, the infiltration of inflammatory cells and capillary thrombosis were significantly decreased. In conclusion, BBM exhibits certain immunomodulatory effects on SLE and promotes the proliferation of white blood cells.
Animals ; Lupus Erythematosus, Systemic/immunology* ; Mice ; Mice, Inbred C57BL ; Mice, Inbred MRL lpr ; Female ; Benzylisoquinolines/pharmacology*

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

The subcortical visual pathway is generally thought to be involved in dangerous information processing, such as fear processing and defensive behavior. A recent study, published in Human Brain Mapping, shows a new function of the subcortical pathway involved in the fast processing of non-emotional object perception. Rapid object processing is a critical function of visual system. Topological perception theory proposes that the initial perception of objects begins with the extraction of topological property (TP). However, the mechanism of rapid TP processing remains unclear. The researchers investigated the subcortical mechanism of TP processing with transcranial magnetic stimulation (TMS). They find that a subcortical magnocellular pathway is responsible for the early processing of TP, and this subcortical processing of TP accelerates object recognition. Based on their findings, we propose a novel training approach called subcortical magnocellular pathway training (SMPT), aimed at improving the efficiency of the subcortical M pathway to restore visual and attentional functions in disorders associated with subcortical pathway dysfunction.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Viral infectious diseases, characterized by their intricate nature and wide-ranging diversity, pose substantial challenges in the domain of data management. The vast volume of data generated by these diseases, spanning from the molecular mechanisms within cells to large-scale epidemiological patterns, has surpassed the capabilities of traditional analytical methods. In the era of artificial intelligence (AI) and big data, there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information. Despite the rapid accumulation of data associated with viral infections, the lack of a comprehensive framework for integrating, selecting, and analyzing these datasets has left numerous researchers uncertain about which data to select, how to access it, and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels, from the molecular details of pathogens to broad epidemiological trends. The scope extends from the micro-scale to the macro-scale, encompassing pathogens, hosts, and vectors. In addition to data summarization, this review thoroughly investigates various dataset sources. It also traces the historical evolution of data collection in the field of viral infectious diseases, highlighting the progress achieved over time. Simultaneously, it evaluates the current limitations that impede data utilization.Furthermore, we propose strategies to surmount these challenges, focusing on the development and application of advanced computational techniques, AI-driven models, and enhanced data integration practices. By providing a comprehensive synthesis of existing knowledge, this review is designed to guide future research and contribute to more informed approaches in the surveillance, prevention, and control of viral infectious diseases, particularly within the context of the expanding big-data landscape.
Big Data ; Humans ; Virus Diseases/virology* ; Artificial Intelligence