Graphene has attracted the attention of the entire scientific community due to its unique mechanical and electrochemical, electronic, biomaterial, and chemical properties. The water-soluble ...derivative of graphene, graphene oxide, is highly prized and continues to be intensely investigated by scientists around the world. This review seeks to provide an overview of the currents applications of graphene oxide in nanomedicine, focusing on delivery systems, tissue engineering, cancer therapies, imaging, and cytotoxicity, together with a short discussion on the difficulties and the trends for future research regarding this amazing material.
Background
The preservation of parathyroid glands is crucial in endoscopic thyroid surgery to prevent hypocalcemia and related complications. However, current methods for identifying and protecting ...these glands have limitations. We propose a novel technique that has the potential to improve the safety and efficacy of endoscopic thyroid surgery.
Purpose
Our study aims to develop a deep learning model called PTAIR 2.0 (Parathyroid gland Artificial Intelligence Recognition) to enhance parathyroid gland recognition during endoscopic thyroidectomy. We compare its performance against traditional surgeon‐based identification methods.
Materials and methods
Parathyroid tissues were annotated in 32 428 images extracted from 838 endoscopic thyroidectomy videos, forming the internal training cohort. An external validation cohort comprised 54 full‐length videos. Six candidate algorithms were evaluated to select the optimal one. We assessed the model's performance in terms of initial recognition time, identification duration, and recognition rate and compared it with the performance of surgeons.
Results
Utilizing the YOLOX algorithm, we developed PTAIR 2.0, which demonstrated superior performance with an AP50 score of 92.1%. The YOLOX algorithm achieved a frame rate of 25.14 Hz, meeting real‐time requirements. In the internal training cohort, PTAIR 2.0 achieved AP50 values of 94.1%, 98.9%, and 92.1% for parathyroid gland early prediction, identification, and ischemia alert, respectively. Additionally, in the external validation cohort, PTAIR outperformed both junior and senior surgeons in identifying and tracking parathyroid glands (p < 0.001).
Conclusion
The AI‐driven PTAIR 2.0 model significantly outperforms both senior and junior surgeons in parathyroid gland identification and ischemia alert during endoscopic thyroid surgery, offering potential for enhanced surgical precision and patient outcomes.
Objectives
Recent studies have revealed the change of molecular subtypes in breast cancer (BC) after neoadjuvant therapy (NAT). This study aims to construct a non-invasive model for predicting ...molecular subtype alteration in breast cancer after NAT.
Methods
Eighty-two estrogen receptor (ER)–negative/ human epidermal growth factor receptor 2 (HER2)–negative or ER-low-positive/HER2-negative breast cancer patients who underwent NAT and completed baseline MRI were retrospectively recruited between July 2010 and November 2020. Subtype alteration was observed in 21 cases after NAT. A 2D-DenseUNet machine-learning model was built to perform automatic segmentation of breast cancer. 851 radiomic features were extracted from each MRI sequence (T2-weighted imaging, ADC, DCE, and contrast-enhanced T1-weighted imaging), both in the manual and auto-segmentation masks. All samples were divided into a training set (
n
= 66) and a test set (
n
= 16). XGBoost model with 5-fold cross-validation was performed to predict molecular subtype alterations in breast cancer patients after NAT. The predictive ability of these models was subsequently evaluated by the AUC of the ROC curve, sensitivity, and specificity.
Results
A model consisting of three radiomics features from the manual segmentation of multi-sequence MRI achieved favorable predictive efficacy in identifying molecular subtype alteration in BC after NAT (cross-validation set: AUC = 0.908, independent test set: AUC = 0.864); whereas an automatic segmentation approach of BC lesions on the DCE sequence produced good segmentation results (Dice similarity coefficient = 0.720).
Conclusions
A machine learning model based on baseline MRI is proven useful for predicting molecular subtype alterations in breast cancer after NAT.
Key Points
• Machine learning models using MRI-based radiomics signature have the ability to predict molecular subtype alterations in breast cancer after neoadjuvant therapy, which subsequently affect treatment protocols.
• The application of deep learning in the automatic segmentation of breast cancer lesions from MRI images shows the potential to replace manual segmentation..
An optimized metastructure (MS) switchable between ultra-wideband (UWB) angle-insensitive absorption, and transmissive linear-to-circular (LTC) polarization conversion (PC), is proposed, which is a ...theoretical study. The structural parameters of this MS are optimized by the thermal exchange optimization algorithm. By modulating the chemical potential (
μ
c
) of the graphene-based hyperbolic metamaterial embedded in the MS, the MS can achieve UWB absorption in the absorption state and LTC PC in the transmission state. At normal incidence, in the absorption state, the MS exhibits absorptivity exceeding 0.9 within 7-15.45 THz, with a relative bandwidth (RBW) of 75.28%. By elevating
μ
c
, an UWB LTC PC is realized, with a RBW of 118.8%, achieving transmittance above 0.9 and the axial ratio below 3 dB. When prioritizing the angular stability, in the absorption state, the MS secures the angular stability of 75° for TE waves and 65° for TM ones. In the transmission state, the angular stability of PC reaches 60°, with RBW = 100.7%. Moreover, by manipulating
μ
c
, the tunability of UWB absorption is realized. The optimized MS provides a reference for designing multifunctional intelligent terahertz modulators, with promising application potential in domains like electromagnetic shielding, communication systems, and THz modulation.
An optimized metastructure (MS) switchable between ultra-wideband (UWB) angle-insensitive absorption, and transmissive linear-to-circular (LTC) polarization conversion (PC), is proposed, which is a theoretical study.
Background and Purpose
Protein palmitoylation is involved in learning and memory, and in emotional disorders. Yet, the underlying mechanisms in these processes remain unclear. Herein, we describe ...that A‐kinase anchoring protein 150 (AKAP150) is essential and sufficient for depressive‐like behaviours in mice via a palmitoylation‐dependent mechanism.
Experimental Approach
Depressive‐like behaviours in mice were induced by chronic restraint stress (CRS) and chronic unpredictable mild stress (CUMS). Palmitoylated proteins in the basolateral amygdala (BLA) were assessed by an acyl‐biotin exchange assay. Genetic and pharmacological approaches were used to investigate the role of the DHHC2‐mediated AKAP150 palmitoylation signalling pathway in depressive‐like behaviours. Electrophysiological recording, western blotting and co‐immunoprecipitation were performed to define the mechanistic pathway.
Key Results
Chronic stress successfully induced depressive‐like behaviours in mice and enhanced AKAP150 palmitoylation in the BLA, and a palmitoylation inhibitor was enough to reverse these changes. Blocking the AKAP150‐PKA interaction with the peptide Ht‐31 abolished the CRS‐induced AKAP150 palmitoylation signalling pathway. DHHC2 expression and palmitoylation levels were both increased after chronic stress. DHHC2 knockdown prevented CRS‐induced depressive‐like behaviours, as well as attenuating AKAP150 signalling and synaptic transmission in the BLA in CRS‐treated mice.
Conclusion and Implications
These results delineate that DHHC2 modulates chronic stress‐induced depressive‐like behaviours and synaptic transmission in the BLA via the AKAP150 palmitoylation signalling pathway, and this pathway may be considered as a promising novel therapeutic target for major depressive disorder.
From first-principles calculations, the transition-metal (TM) atom (Fe, Co and Ni) adsorbed Janus MoSSe monolayer, toxic gas molecules (CO, NH
3
and H
2
S) adsorbed on the Ni-MoSSe monolayer and CO ...catalytic oxidation on the Fe-MoSSe monolayer are systematically investigated. An increasing order (Fe-MoSSe < Co-MoSSe < Ni-MoSSe) is found for the stability and band gap of the TM atom adsorbed Janus MoSSe monolayer. These toxic gas molecules are found to be weakly physisorbed and strongly chemisorbed on the pristine and Ni-MoSSe monolayers, respectively. The electronic structure and gas molecular adsorption properties of the Janus MoSSe monolayer can be modulated by adsorbing different TM atoms and gas molecules. Particularly, the CO catalytic oxidation can be realized on the Fe-MoSSe monolayer in light of the more preferable Eley-Rideal (ER) mechanism with the two-step route (CO + O
2
→ OOCO → CO
2
+ O
ads
, CO + O
ads
→ CO
2
) with highly exothermic processes in each step. The adsorption of TM atoms which may greatly enhance gas sensing performance and catalytic performance of CO oxidation based on the Janus MoSSe monolayer is further discussed.
From first-principles calculations, the transition-metal (TM) atom (Fe, Co and Ni) adsorbed Janus MoSSe monolayer, toxic gas molecules (CO, NH
3
and H
2
S) adsorbed on Ni-MoSSe monolayers and CO catalytic oxidation on Fe-MoSSe monolayers are systematically investigated.
A more general class of stochastic nonlinear systems with unmodeled dynamics and uncertain nonlinear functions are considered in this paper. With the concept of input-to-state practical stability ...(ISpS) and nonlinear small-gain theorem being extended to stochastic case, by combining stochastic small-gain theorem with backstepping design technique, an adaptive output-feedback controller is proposed. It is shown that the closed-loop system is practically stable in probability. A simulation example demonstrates the control scheme.
Quantitative analysis is a significant step forward for expanding the applications of surface‐enhanced Raman spectroscopy (SERS) in various fields. The reproducibility of the SERS measurement relies ...on the quality of the SERS substrates. Therefore, high enhancement SERS substrate with high uniformity and reproducibility is highly demanded for quantitative analysis. However, it remains a challenge to realize all the requirements of the SERS substrate. Here, we report 2 types (solution and solid) of SERS substrates with built‐in calibration for quantitative analysis. To prepare the substrates, high monodisperse Au@Ag nanocuboids (NCs) with internal standards trapped between the Au core and Ag shell are synthesized through the Au‐nanorod‐mediated method. It is demonstrated that at least 2 types of SERS tags can be trapped to synthesize the core‐internal standard‐shell (CISS) NCs. The SERS quantitative ability of the CISS NCs in solution is proved by detecting Rhodamine 6G, where a good linear relationship in a wide concentration range from 3 × 10−11 M to 1 × 10−8 M is achieved through the built‐in calibration. Besides the solution‐SERS substrate, CISS NCs are self‐assembled at the air–water interface to form uniform monolayer as the solid SERS substrate. SERS mapping reveals that the uniformity of the enhancement is improved through the built‐in calibration. The quantitative detection of concentration of Rhodamine 6G is achieved through the calibrated SERS mapping of the substrate. The internal and external enhancement factor calculation of the 2 types of SERS substrates indicates the promising method to further improve the reliability of the SERS analysis.
Highly uniform core‐internal standard‐shell (CISS) nanocuboids (NCs) are first synthesized by using internal‐standard‐modified Au nanorods as seeds to assist the growth of the Ag nanoshells. The CISS NC solution shows excellent SERS quantitative analysis capability by performing the calibration through the built‐in internal standard. The CISS NCs are assembled at the air–liquid interface to prepare the solid SERS substrates, by which the improved SERS quantitative detection is achieved through the calibrated SERS mapping analysis.
The bidirectional communication between the central nervous system (CNS) and the gut microbiota plays a pivotal role in human health. Increasing numbers of studies suggest that the gut microbiota can ...influence the brain and behavior of patients. Various metabolites secreted by the gut microbiota can affect the cognitive ability of patients diagnosed with neurodegenerative diseases. Nearly one in every ten Korean senior citizens suffers from Alzheimer's disease (AD), the most common form of dementia. This review highlights the impact of metabolites from the gut microbiota on communication pathways between the brain and gut, as well as the neuroinflammatory roles they may have in AD patients. The objectives of this review are as follows: (1) to examine the role of the intestinal microbiota in homeostatic communication between the gut microbiota and the brain, termed the microbiota⁻gut⁻brain (MGB) axis; (2) to determine the underlying mechanisms of signal dysfunction; and (3) to assess the impact of signal dysfunction induced by the microbiota on AD. This review will aid in understanding the microbiota of elderly people and the neuroinflammatory roles they may have in AD.
Cerebral cortical vein thrombosis (CCVT) is a rare type of cerebral venous thrombosis, which is frequently combined with cerebral venous sinus thrombosis (CVST). We aimed to compare the difference of ...clinical features between the isolated and the combined subtypes of CCVT. A literature search was conducted utilizing the PubMed Central and EMBASE databases to identify studies up to Dec 2019. Clinical manifestations, presumable risk factors, imaging modalities, radiological findings, treatment, and prognosis in patients with CCVT were recorded. 335 publications were identified (n = 325, 141 males and 184 females, mean age 40.24 ± 16.26 years). Headaches (46.8%), motor/sensory disorders (43.3%), and seizures (42.5%) were commonly seen. Pregnancy/postpartum (n = 29), oral contraception use (n = 15), fertility drug use (n = 4) ranked the top three comorbidities of CCVT in female patients, while for general populations, thrombophilia, invasive interventions in the cerebrospinal system, as well as malignancy, would be the common risk factors. MRV and DSA were more likely to confirm diagnosis. More than 30% of CCVT presented brain lesions, including infarction (6.5%) and hemorrhage (24.0%). Isolated CCVT was prone to develop hemorrhagic infarction while combined CCVT was more likely to have ischemic lesions. More than 90% of the patients acquired good outcomes at discharge or short-term follow-up (within one year). There is a difference between Isolated CCVT and CCVT combined CVST on the sites and types of brain lesions. MRV and DSA may contribute to the final diagnosis. Most patients acquired complete or partial recovery of clinical symptoms or imaging presentations after long-term anticoagulation (3–6 months).
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