Dual-Reference Source-Free Active Domain Adaptation for Nasopharyngeal Carcinoma Tumor Segmentation across Multiple Hospitals

Nasopharyngeal carcinoma (NPC) is a prevalent and clinically significant malignancy that predominantly impacts the head and neck area. Precise delineation of the Gross Tumor Volume (GTV) plays a pivotal role in ensuring effective radiotherapy for NPC. Despite recent methods that have achieved promising results on GTV segmentation, they are still limited by lacking carefully-annotated data and hard-to-access data from multiple hospitals in clinical practice. Although some unsupervised domain adaptation (UDA) has been proposed to alleviate this problem, unconditionally mapping the distribution distorts the underlying structural information, leading to inferior performance. To address this challenge, we devise a novel Sourece-Free Active Domain Adaptation (SFADA) framework to facilitate domain adaptation for the GTV segmentation task. Specifically, we design a dual reference strategy to select domain-invariant and domain-specific representative samples from a specific target domain for annotation and model fine-tuning without relying on source-domain data. Our approach not only ensures data privacy but also reduces the workload for oncologists as it just requires annotating a few representative samples from the target domain and does not need to access the source data. We collect a large-scale clinical dataset comprising 1057 NPC patients from five hospitals to validate our approach. Experimental results show that our method outperforms the UDA methods and achieves comparable results to the fully supervised upper bound, even with few annotations, highlighting the significant medical utility of our approach. In addition, there is no public dataset about multi-center NPC segmentation, we will release code and dataset for future research

Systematic Performance Analysis of Hybrid FSO/RF System over Generalized Fading Channels with Pointing Errors

Hybrid free space optical (FSO)/radio frequency (RF) system has attracted extensive attention because of its advantages of both the FSO and RF links. From the viewpoint of overall system performance, this paper presents a systematic analysis method of communication performance and security performance of the hybrid FSO/RF system with the Málaga turbulence channel and the α−μ fading channel. The hybrid FSO/RF system adopts the diversity method of maximum ratio combining (MRC) to receive signals. The new expressions of communication performance parameters (i.e., the bit error rate, the outage probability, the ergodic channel capacity) of the only FSO system and the hybrid system are obtained. Then, the new expressions of the security performance parameters (i.e., the security outage probability and the strictly positive secrecy capacity) of the hybrid system with the FSO or RF links eavesdropping are derived, respectively. Our derived analytical expressions present an efficient tool to investigate the impact of system parameters on the overall performance of the hybrid system, namely modulation scheme, turbulence intensity, pointing errors, target rate, and eavesdropper output signal-to-noise ratio. The simulation results show that compared with the only FSO system, the hybrid system can significantly improve the communication performance of the system; the communication performance of the hybrid system using coherent binary phase shift keying (CBPSK) modulation is obviously better than the other two modulation technologies; with the deterioration of atmospheric environment (increasing turbulence intensity and pointing errors), the communication performance and security performance of the hybrid system will decline; both RF link eavesdropping and FSO link eavesdropping have a greater impact on the security performance of the hybrid systems; whether it is FSO link eavesdropping or RF link eavesdropping, the reduction of target rate and output signal-to-noise ratio of the eavesdropper can improve the security performance of the hybrid system

Macrophages in Glioblastoma Development and Therapy: A Double-Edged Sword

Glioblastoma (GBM) is one of the leading lethal tumors, featuring aggressive malignancy and poor outcome to current standard temozolomide (TMZ) or radio-based therapy. Developing immunotherapies, especially immune checkpoint inhibitors, have improved patient outcomes in other solid tumors but remain fatigued in GBM patients. Emerging evidence has shown that GBM-associated macrophages (GAMs), comprising brain-resident microglia and bone marrow-derived macrophages, act critically in boosting tumor progression, altering drug resistance, and establishing an immunosuppressive environment. Based on its crucial role, evaluations of the safety and efficacy of GAM-targeted therapy are ongoing, with promising (pre)clinical evidence updated. In this review, we summarized updated literature related to GAM nature, the interplay between GAMs and GBM cells, and GAM-targeted therapeutic strategies

A Benign and Malignant Breast Tumor Classification Method via Efficiently Combining Texture and Morphological Features on Ultrasound Images

The classification of benign and malignant based on ultrasound images is of great value because breast cancer is an enormous threat to women’s health worldwide. Although both texture and morphological features are crucial representations of ultrasound breast tumor images, their straightforward combination brings little effect for improving the classification of benign and malignant since high-dimensional texture features are too aggressive so that drown out the effect of low-dimensional morphological features. For that, an efficient texture and morphological feature combing method is proposed to improve the classification of benign and malignant. Firstly, both texture (i.e., local binary patterns (LBP), histogram of oriented gradients (HOG), and gray-level co-occurrence matrixes (GLCM)) and morphological (i.e., shape complexities) features of breast ultrasound images are extracted. Secondly, a support vector machine (SVM) classifier working on texture features is trained, and a naive Bayes (NB) classifier acting on morphological features is designed, in order to exert the discriminative power of texture features and morphological features, respectively. Thirdly, the classification scores of the two classifiers (i.e., SVM and NB) are weighted fused to obtain the final classification result. The low-dimensional nonparameterized NB classifier is effectively control the parameter complexity of the entire classification system combine with the high-dimensional parametric SVM classifier. Consequently, texture and morphological features are efficiently combined. Comprehensive experimental analyses are presented, and the proposed method obtains a 91.11% accuracy, a 94.34% sensitivity, and an 86.49% specificity, which outperforms many related benign and malignant breast tumor classification methods

Additional file 2: of A new mechanism of trastuzumab resistance in gastric cancer: MACC1 promotes the Warburg effect via activation of the PI3K/AKT signaling pathway

Tables S1 to S4. Table S1: IC50 of different GC cell lines. Table S2: IC50 and RI (resistance index) of MKN45 cells after treatment with trastuzumab at different inducing concentrations. Table S3: Fa and CI for trastuzumab and glucolysis inhibitor combinations on inhibition of cell viability. Table S4: Fa and CI for trastuzumab and glucolysis inhibitor combinations on inhibition of glucose uptake. (DOCX 45 kb

Regulation of HIF-1α and p53 in stress responses in the subterranean rodents Lasiopodomys mandarinus and Lasiopodomys brandtii (Rodentia: Cricetidae)

The response mechanism and interaction patterns of HIF-1α and p53 in animals in an hypoxic environment are crucial for their hypoxic tolerance and adaptation. Many studies have shown that underground rodents have better hypoxic adaptation characteristics. However, the mechanism by which HIF-1α and p53 in underground rodents respond to hypoxic environments compared with in ground rodents remains unclear. Further, whether a synergy between HIF-1α and p53 enables animals tolerate extremely hypoxic environments is unclear. We studied HIF-1α and p53 expression in the brain tissue and cell apoptosis in the hippocampal CA1 region during 6 hours of acute hypoxia (5% oxygen) in Lasiopodomys mandarinus (Milne-Edwards, 1871) and Lasiopodomys brandtii (Radde, 1861), two closely related small rodents with different life characteristics (underground and aboveground, respectively), using a comparative biology method to determine the mechanisms underlying their adaptation to this environment. Our results indicate that HIF-1α and p53 expression is more rapid in L. mandarinus than in L. brandtii under acute hypoxic environments, resulting in a significant synergistic effect in L. mandarinus. Correlation analysis revealed that HIF-1α expression and the apoptotic index of the hippocampal CA1 regions of the brain tissues of L. mandarinus and L. brandtii, both under hypoxia, were significantly negatively and positively correlated, respectively. Long-term existence in underground burrow systems could enable better adaptation to hypoxia in L. mandarinus than in L. brandtii. We speculate that L. mandarinus can quickly eliminate resulting damage via the synergistic effect of p53 and HIF-1α in response to acute hypoxic environments, helping the organism quickly return to a normal state after the stress

Aberrant temporal-spatial complexity of intrinsic fluctuations in major depression

Accumulating evidence suggests that the brain is highly dynamic; thus, investigation of brain dynamics especially in brain connectivity would provide crucial information that stationary functional connectivity could miss. This study investigated temporal expressions of spatial modes within the default mode network (DMN), salience network (SN) and cognitive control network (CCN) using a reliable data-driven co-activation pattern (CAP) analysis in two independent data sets. We found enhanced CAP-to-CAP transitions of the SN in patients with MDD. Results suggested enhanced flexibility of this network in the patients. By contrast, we also found reduced spatial consistency and persistence of the DMN in the patients, indicating reduced variability and stability in individuals with MDD. In addition, the patients were characterized by prominent activation of mPFC. Moreover, further correlation analysis revealed that persistence and transitions of RCCN were associated with the severity of depression. Our findings suggest that functional connectivity in the patients may not be simply attenuated or potentiated, but just alternating faster or slower among more complex patterns. The aberrant temporal-spatial complexity of intrinsic fluctuations reflects functional diaschisis of resting-state networks as characteristic of patients with MDD