Circadian pattern subtyping unveiling distinct immune landscapes in breast cancer patients for better immunotherapy.

BACKGROUND: While epidemiological studies have established a firm link between circadian disruption and tumorigenesis, the role and mechanism are not fully understood, complicating the design of therapeutic targets related to circadian rhythms (CR). Here, we aimed to explore the intertumoral heterogeneity of CR and elucidate its impact on the tumor microenvironment (TME), drug sensitivity, and immunotherapy. METHODS: Based on unsupervised clustering of 28 CR genes, two distinct CR subtypes (cluster-A and cluster-B) were identified in the TCGA cohort. We further constructed a circadian rhythm signature (CRS) based on the CR genes primarily responsible for clustering to quantify CR activity and to distinguish CR subtypes of individual patients from external datasets. CR subtypes were evaluated by TME characteristics, functional annotation, clinical features, and therapeutic response. RESULTS: The cluster-B (low-CRS) group was characterized by highly enriched immune-related pathways, high immune cell infiltration, and high anti-tumor immunity, while the cluster-A (high-CRS) group was associated with immunosuppression, synaptic transmission pathways, EMT activation, poor prognosis, and drug resistance. Immunohistochemistry (IHC) results demonstrated that high CD8+ T cell infiltration was associated with low-CR-protein expression. Importantly, patients with low CRS were more likely to benefit from immune checkpoint blockade (ICB) treatment, possibly due to their higher tumor mutation burden (TMB), increased immune checkpoint expression, and higher proportion of "hot" immunophenotype. CONCLUSION: In a nutshell, the cross talk in CR could reflect the TME immunoreactivity in breast cancer. Besides providing the first comprehensive pathway-level analysis of CR in breast cancer, this work highlights the potential clinical utility of CR for immunotherapy.

Multi-Physics Mesoscale Substructure Analysis on Stress Wave Measurement within CFST-PZT Coupling Models for Interface Debonding Detection.

In recent years, the development of interface debonding defect detection methods for concrete-filled steel tubes (CFSTs) using stress wave measurement with piezoelectric-lead-zirconate-titanate (PZT) actuator and sensor has received significant attention. Because the concrete core in CFSTs is a heterogeneous material with randomness at the mesoscale, the size, position and distribution of aggregates unavoidably affect the stress wave propagation and the PZT sensor response. In this study, to efficiently investigate the influence of the mesoscale structure of the concrete core of CFSTs on the response of embedded PZT sensors, a multi-physics substructure model of CFST members coupled with a PZT actuator and a PZT sensor, where a single circular aggregate with different size and position and randomly distributed circular aggregates are considered, are established first. Then, multi-physics simulations on the effect of the local mesoscale structure of the concrete core on the response of the embedded PZT sensor excited by both a sinusoidal signal and sweep frequency signal are carried out. Moreover, corresponding multi-physics and mesoscale simulations on the embedded PZT sensor response of substructures with different interface debonding defects are also carried out for comparison. The amplitude and the wavelet packet energy of the embedded PZT sensor response of each mesoscale substructure are employed to distinguish the influence of the concrete core mesoscale structure and interface debonding defect on sensor measurement. The findings from the results with the multi-physics coupling substructure models are compared with those of the full CFST-PZT coupling models and the tested members of the previous studies to verify the rationality of the embedded PZT sensors measurement of the established substructure models. Results from this study show that the effect of interface debonding defect on the amplitude and the wavelet packet energy of the embedded PZT sensor measurement of the CFST members is dominant compared with the mesoscale heterogeneity and randomness of the concrete core.

Interfacial Debonding Detection for Rectangular CFST Using the MASW Method and Its Physical Mechanism Analysis at the Meso-Level.

In this study, the transient multichannel analysis of surface waves (MASW) is proposed to detect the existence, the location and the length of interface debonding defects in rectangular concrete-filled steel tubes (CFST). Mesoscale numerical analysis is performed to validate the feasibility of MASW-based interfacial debonding detection. Research findings indicate that the coaxial characteristics in the Rayleigh wave disperse at the starting point of the debonding area and gradually restores at the end of the defect. For healthy specimens, the surface wave mode in CFST is closer to the Rayleigh wave. However, it can be treated as a Lamb wave since the steel plate is boundary-free on both sides in the debonding area. The displacement curves are further investigated with forward analysis to obtain the dispersion curves. The mesoscale numerical simulation results indicate that the propagation characteristic of the surface wave is dominated by the debonding defect. The detectability of interfacial debonding detection for rectangular CFST using the MASW approach is numerically verified in this study. The proposed MASW-based nondestructive testing technique can achieve bond-slip detection by comparing the variation trend of the coaxial characteristics in the time-history output signals and the dispersion curves obtained from the forward analysis, for avoiding misjudgment of the experimental observations.

Histopathology and molecular pathology confirmed a diagnosis of atypical Caroli's syndrome: a case report.

Caroli's syndrome is a congenital disease characterized by dilation of intrahepatic bile ducts and congenital hepatic fibrosis. It is a rare condition in clinical work. Typically, the diagnosis of this disease is confirmed through medical imaging. Here, we report a case of atypical Caroli's syndrome in a patient who presented with recurrent upper gastrointestinal tract bleeding. The patient underwent imaging examinations, liver biopsy and whole exome sequencing. The results of the imaging examination were non-specific. However, with the aid of pathological examination, the patient was diagnosed with Caroli's syndrome. In conclusion, for cases where the imaging presentation of Caroli's syndrome is inconclusive, an accurate diagnosis should rely on pathology. By discussing this specific case, our aim is to enhance readers' understanding of this disease, provide valuable information that can aid in the early detection and appropriate management of Caroli's syndrome, ultimately improving patient outcomes.

The diagnostic value of a nomogram based on enhanced CT radiomics for differentiating between intrahepatic cholangiocarcinoma and early hepatic abscess.

Objective: This study aimed to investigate the value of a CT-enhanced scanning radiomics nomogram in distinguishing between early hepatic abscess (EHA) and intrahepatic cholangiocarcinoma (ICC) and to validate its diagnostic efficacy. Materials and Methods: Clinical and imaging data on 112 patients diagnosed with EHA and ICC who underwent double-phase CT-enhanced scanning at our hospital were collected. The contours of the lesions were delineated layer by layer across the three phases of CT scanning and enhancement using 3D Slicer software to define the region of interest (ROI). Subsequently, the contours were merged into 3D models, and radiomics features were extracted using the Radiomics plug-in. The data were randomly divided into training (n = 78) and validation (n = 34) cohorts at a 7:3 ratio, using the R programming language. Standardization was performed using the Z-score method, and LASSO regression was used to select the best λ-value for screening variables, which were then used to establish prediction models. The rad-score was calculated using the best radiomics model, and a joint model was constructed based on the rad-score and clinical scores. A nomogram was developed based on the joint model. The diagnostic efficacy of the models for distinguishing ICC and EHA was assessed using receiver operating characteristic (ROC) curve and area under the curve (AUC) analyses. Calibration curves were used to evaluate the reliability and accuracy of the nomograms, while decision curves and clinical impact curves were utilized to assess their clinical value. Results: Compared with the ICC group, significant differences were observed in clinical data and imaging characteristics in the EHA group, including age, centripetal enhancement, hepatic pericardial depression sign, arterial perfusion abnormality, arterial CT value, and arteriovenous enhancement (p < 0.05). Logistic regression analysis identified centripetal enhancement, hepatic pericardial depression sign, arterial perfusion abnormality, arterial CT value, and arteriovenous enhancement as independent influencing factors. Three, five, and four radiomics features were retained in the scanning, arterial, and venous phases, respectively. Single-phase models were constructed, with the radiomics model from the arterial phase demonstrating the best diagnostic efficacy. The rad-score was calculated using the arterial-phase radiomics model, and nomograms were drawn in conjunction with the clinical model. The nomogram based on the combined model exhibited the highest differential diagnostic efficacy between EHA and ICC (training cohort: AUC of 0.972; validation cohort: AUC of 0.868). The calibration curves indicated good agreement between the predicted and pathological results, while decision curves and clinical impact curves demonstrated higher clinical utility of the nomograms. Conclusion: The CT-enhanced scanning radiomics nomogram demonstrates high clinical value in distinguishing between EHA and ICC, thereby enhancing the accuracy of preoperative diagnosis.

Event-Triggered Near-Optimal Control for Unknown Discrete-Time Nonlinear Systems Using Parallel Control.

This article uses parallel control to investigate the problem of event-triggered near-optimal control (ETNOC) for unknown discrete-time (DT) nonlinear systems. First, to achieve parallel control, an augmented nonlinear system (ANS) with an augmented performance index (API) is proposed to introduce the control input into the feedback system. The control stability relationship between the ANS and the original system is analyzed, and it is shown that, by choosing a proper API, optimal control of the ANS with the API can be seen as near-optimal control of the original system with the original performance index (OPI). Second, based on parallel control, a novel event-triggered scheme is proposed, and then a novel ETNOC method is developed using the time-triggered optimal value function of the ANS with the API. The control stability is proved, and an upper bound, which is related to the design parameter, is provided for the actual performance index in advance. Then, to implement the developed ETNOC method for unknown DT nonlinear systems, a novel online learning algorithm is developed without reconstructing unknown systems, and neural network (NN) and adaptive dynamic programming (ADP) techniques are employed in the developed algorithm. The convergence of the signals in the closed-loop system (CLS) is shown using the Lyapunov approach, and the assumption of boundedness of input dynamics is not required. Finally, two simulations justify the theoretical conjectures.

Multi-Scale Stress Wave Simulation for Aggregates Segregation Detection of Concrete Core in Circular CFST Coupled with PZT Patches.

In this study, the numerical investigation of the detectability of concrete aggregate segregation in circular concrete-filled steel tubulars (CCFST) based on piezoelectric lead zirconate titanate (PZT) measurement is performed. The stress wave propagation in the concrete core of circular CCFST excited with a surface-mounted PZT actuator is studied with multi-scale and multi-physical field coupling analysis. The piezoelectric effect of PZT patches and its coupling effect with CFSTs are considered. Numerical concrete modeling technology is employed to construct the concrete core composed of randomly distributed aggregates with and without aggregate segregation at different levels, mortar, and an interfacial transition zone (ITZ). The effects of the random distribution of elliptical aggregates, aggregate segregation, and the existence of ITZ in the concrete core on the wave fields in the cross-section and the corresponding voltage response of the embedded PZT sensor are discussed. An evaluation index based on wavelet packet analysis on the output voltage response is defined, and its sensitivity to concrete aggregate segregation is systematically investigated. The multi-scale and multi-physics coupling simulation results indicate that concrete aggregate segregation in the concrete core of CFST members can be efficiently detected based on the stress wave measurement with a PZT sensor.

Optical bio-chemical sensors based on whispering gallery mode resonators.

Whispering gallery mode (WGM) resonators have attracted extensive attention and their unique characteristics have led to some remarkable achievements. In particular, when combined with optical sensing technology, the WGM reonator-based sensor offers the advantages of small size, high sensitivity and a real-time dynamic response. At present, this type of sensor is widely applied in the bio-chemical sensing field. In this paper, we briefly review the sensing principle, the structures and the sensing applications of optical bio-chemical sensors based on the WGM resonator, with particular focuses on their sensing properties and their advantages and disadvantages. In addition, the existing problems and future development trends of WGM resonator-based optical bio-chemical sensors are discussed.

Over-expression of TOP2A as a prognostic biomarker in patients with glioma.

Topoisomerase (DNA) II alpha (TOP2A), an enzyme that controls and alters the topologic states of DNA during transcription, is aberrantly expressed in many cancers. However, few studies have investigated expression of TOP2A and its clinical significance in glioma. We retrieved six independent investigations from the Oncomine database and found that TOP2A is highly expressed in glioma tissues compared with corresponding normal controls. Similar results were also found in clinical specimens at the protein level. Immunohistochemical analysis indicated that TOP2A over expression was highly correlated with grade stage, KI67 positive percentage, IDH1 mutation, and age, but other clinical parameters such as sex distribution and tumor size were barely associated with high TOP2A gene expression. Meanwhile we used Prognos can to assess the prognostic value of TOP2A expression in glioma patients, and found that high expression was associated with poor prognosis of patients with glioma. Furthermore, we used the Gene-Cloud of Biotechnology Information (GCBI) bioinformatics platform predict the role of TOP2A in glioma. It was not only involved in DNA replication, chromosome condensation, and responses to DNA damage stimuli, but also promoted cancer cell mitotic cell cycle and apoptosis, and phosphatidylinositol-mediated signaling by regulating gene expression. By these approaches we demonstrate that TOP2A may be a reliable prognostic factor or therapeutic target in glioma.

Applications and developments of on-chip biochemical sensors based on optofluidic photonic crystal cavities.

Photonic crystal (PC) cavities, which possess the advantages of compactness, flexible design, and suitability for integration in a lab-on-a-chip system, are able to distinguish slight variations in refractive index with only a small amount of analyte. Combined with the newly proposed optofluidic technology, PC-cavity devices stimulate an emerging class of miniaturized and label-free biochemical sensors. In this review, an overview of optofluidic PC cavities based biochemical sensors is presented. First, the basic properties of the PC, as well as the sensing principle of the PC cavity, are discussed. Second, the applications of the sensors in detecting gas, liquid, and biomolecule concentrations are reviewed, with a focus on their structures, sensing principles, sensing properties, advantages, and disadvantages. Finally, the current challenges and future development directions of optofluidic PC-cavity-based biochemical sensors are discussed.