A Local-Global Attention Fusion Framework With Tensor Decomposition for Medical Diagnosis

Dear Editor,In this letter,a novel hierarchical fusion framework is proposed to address the imperfect data property in complex medical image analysis(MIA)scenes.In particular,by combining the strengths of convolutional neural networks(CNNs)and transformers,the enhanced feature extraction,spatial modeling,and sequential context learning are realized to provide comprehensive insights on the complex data patterns.Integration of information in different level is enabled via a multi-attention fusion mechanism,and the tensor decomposition methods are adopted so that compact and distinctive representation of the underlying and high-dimensional medical image features can be accomplished[1].It is shown from the evaluation results that the proposed framework is competitive and superior as compared with some other advanced algorithms,which effectively handles the imperfect property of inter-class similarity and intra-class differences in diseases,and meanwhile,the model complexity is reduced within an acceptable level,which benefits the deployment in clinic practice.MIA has assumed a pivotal role in numerous critical clinical scenarios,where sophisticated image analysis techniques have proven instrumental in augmenting medical decision-making,facilitating individualized therapeutic interventions,and enhancing patient prognostication[2]−[4].

Liuwei Dihuang Pill(六味地黄丸)Treats Postmenopausal Osteoporosis with Shen(Kidney) Yin Deficiency via Janus Kinase/Signal Transducer and Activator of Transcription Signal Pathway by Up-regulating Cardiotrophin-Like Cytokine Factor 1 Expression

Objectives： To investigate the mechanism of Liuwei Dihuang Pill （六味地黄丸, LDP） in treating postmenopausal osteoporosis （PMOP） with Shen （Kidney） yin deficiency. Methods： In this study, 205 cases of PMOP were divided into the PMOP Shen-yin deficiency group （Group A）, PMOP Shen-yang deficiency group （Group B）, PMOP without Shen deficiency group （Group C）, and control group （Group N）. Real-time polymerase chain reaction （RT-PCR） and Western blot techniques were used to observe the effects of LDP treatment on the cardiotrophin-like cytokine factor 1 （CLCF1）, ankyrin repeat and SOCS box containing 1 （ASB1）, and proldneticin 2 （PROK2） genes and the Janus kinase/signal transducer and activator of transcription （JAK/STAT） signaling pathway. Results： The mRNA （P〈0.05） and protein （P〈0.01） expression levels of the CLCF1 gone in Group A were significantly lower than the corresponding levels in Group N. After LDP treatment for 3 months, the mRNA expression levels of the CLCF1 gone were obviously up-regulated （P〈0.01）. After 6-month treatment, the expression levels of CLCF1 mRNA and protein were significantly up-regulated （both P〈0.01）, and the average bone density of the top femur had significantly increased （P〈0.05）. In vitro, CLCF1 overexpression resulted in a significant increase in the total protein and phosphorylated protein levels of JAK2 and STAT3. Conclusions： The CLCF1 gone is an important gone associated with PMOP Shen-yin deficiency and the therapeutic effects of LDP may be mediated by up-regulation of CLCF1 gone expression and activation of the JAK/STAT signaling pathway.