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Abstract Sclerotinia sclerotiorum could cause significant yield losses of up to 70% in rapeseed cultivation. Nevertheless, the availability of immune or highly resistant germplasm and mechanisms to combat S. sclerotiorum, particularly in B. juncea, remains insufficient. Transcription factors (TFs) are recognized for their critical role in plant defense against S. sclerotiorum. In the present study, a total of 4807 TFs from 48 families were expressed and identified at 12, 24, and 36 h after inoculation (HAI) in two B. juncea lines: G21-912, exhibiting higher S. sclerotiorum resistance (HR), and G21-853, displaying lower S. sclerotiorum resistance (LR). The number of differentially expressed TFs (DETs) between the HR and the LR lines peaked at 24 HAI, with 202 upregulated and 105 downregulated TFs. Through expression and subcellular localization analyses, three candidate DETs, namely BjuA037408 (ETHYLENE RESPONSIVE FACTOR 59, ERF59), BjuB028842 (RELATED TO ABI3/VP1 1, RAV1), and BjuA016484 (WRKY25), were identified as the primary TFs in defense against S. sclerotiorum inoculation. The expression of these three genes was validated in the double haploid lines of BC3 (the third backcrossing generation) derived from the HR×LR cross. This study serves as a valuable case study for the characterization of TFs associated with defense mechanisms against S. sclerotiorum in B. juncea. The confirmed resistant B. juncea line of HR, along with the three key DETs, is expected to significantly contribute to future breeding efforts aimed at developing Sclerotinia-resistant varieties.

Abstract Effective classification and identification algorithms of small fishing vessels are the key to strengthen ship management. This paper proposes a classification and recognition method for small fishing boats based on GASF sequence diagram coding, addressing the complex and challenging recognition environment. The method focuses on four typical small fishing vessels, utilizing Gramian Summation Angular Field (GASF) time series images and the Efficiency MPViT (EMPViT) model. Unlike traditional approaches, this study initially employs a high-precision laser sensor to gather one-dimensional contour data of fishing boats. Subsequently, the polynomial fitting method is used to delineate the shape of the fishing boat contour, which is then encoded into a two-dimensional time series image using the GASF encoding method. The enhanced EMPViT model is then applied to classify and identify small fishing vessels, with the results verified through ablation experiments. These experiments demonstrate that the EMPViT model surpasses traditional neural network models such as CNN and ViT in both accuracy and performance, achieving a peak accuracy of 99.98%.

Abstract Optical observations play a crucial role in monitoring space debris, and long exposure large field-of-view telescopes exhibit robust detection capabilities for identifying space debris. Nevertheless, a substantial volume of data, intricate noise, nonlinearity, and target discontinuities significantly affect the observational process. To address these intricate celestial background conditions, an enhanced YOLOv8-based method for spatial debris detection is introduced into this study. Initially, a cross-scale feature fusion module is incorporated into the neck network, followed by a subtle processing step for the feature fusion component. Finally, the content-aware reassembly of features module is employed to replace the original upsampling module, which enhances the efficiency and accuracy of feature reconstruction, thereby achieving effective detection and identification of spatial debris targets. The study utilized a dataset comprising astronomical images captured by an open-source large-field-of-view optical telescope. The experimental results show that the detection accuracy and speed of the method are improved, and that they can meet the requirements of space debris detection in complex backgrounds.

Abstract Persistent Postural-Perceptual Dizziness (PPPD) is a common cause of chronic vestibular syndrome. Although previous studies have identified central abnormalities in PPPD, the specific neural circuits and the alterations in brain network topological properties, and their association with dizziness and postural instability in PPPD remain unclear. This study includes 30 PPPD patients and 30 healthy controls. Resting-state functional magnetic resonance imaging is used to construct whole-brain functional connectivity matrices, followed by network-based statistic and graph theoretical analysis. Network-based statistic results reveal an abnormal neural network in PPPD patients with key nodes in the occipital visual cortex, precuneus, sensorimotor cortex, multisensory vestibular cortex and cerebellum. The graph theoretical analysis shows less efficient information transmission at both local and global levels, indicating a state of disconnection between regions of the brain network. Decreased connections between the visual cortex, sensorimotor cortex, and multisensory vestibular cortex, and changes in brain network topological properties are correlated with the Dizziness Handicap Inventory score. Our study unveils the potential abnormal neural circuits, with the presence of multisensory and sensorimotor integration abnormalities and reveals altered brain network topological properties in PPPD patients. Our findings provide new insights for understanding the neural mechanisms of PPPD.

Abstract Mining-induced earthquake (MIE) is a non-natural earthquake induced by mining activities. In Ordos mining area, super-thick and weak cementation overburden strata (STWCS) are common occurrence in Jurassic coal seam overlying strata. To explain and quantify the focal mechanism and roof fracture characteristics of MIE under the STWCS, the surface subsidence, ground borehole televiewer imaging and microseismic monitoring technologies were used to observe the fracturing of STWCS. The relative moment tensor method was also used to explore quantify focal mechanism of MIE. The results show that the development height of rock fractures increases, and the STWCS start to break when the panel below retreats along goafs. During this period, the surface stepped subsidence increases rapidly, and MIEs with magnitude above 2.0 begin to appear. The inversion matrix is constructed with the relative moment tensor method to solve the source mechanism of coal mining microearthquakes. The matrix improves the inversion efficiency and accuracy, thus being suitable for solving the focal mechanism of MIE by roof breaking. When coal seam is mined under the STWCS, the dip angle of focal rupture surface is mainly between 0° and 30°, accounting for about 50% of the total. The seismic source is mainly featured with roof horizontal separation tension and roof rotation compression instability. During mining along goafs, the seismic sources displayed a tendency of upward expansion and the shear slip ruptures were more than that in the solid coal mining stage. The focal mechanism of the MIEs in Shilawusu Coal mine was caused by the primary and periodic tension rupture of the STWCS and shear slip rupture. With the continuous mining of the panel, there is still the possibility of another round of MIEs. The research results provide a reference for the prediction, risk assessment and disaster control of MIEs under extremely thick overburden strata.

Abstract Background Anti-CD19 chimeric antigen receptor (CAR) T cell therapy is a common, yet highly efficient, cellular immunotherapy for lymphoma. However, many recent studies have reported on its cardiovascular (CV) toxicity. This study analyzes the cardiotoxicity of CD19 CAR T cell therapy in the treatment of lymphoma for providing a more valuable reference for clinicians. Methods The PubMed, Embase, Cochrane library, and Web of Science databases were comprehensively searched from the time of their establishment to May 2024. The ClinicalTrials.gov English database is a comprehensive repository of the original studies of CD19 CAR T cell therapy and associated adverse outcomes, such as arrhythmia, CV events, and hypotension, in patients with lymphoma. The Cochrane Collaboration tool and the Newcastle–Ottawa Scale (NOS) were used to assess the quality of the included original studies. For RCTs, the Cochrane Collaboration tool was used to assess the risk of bias. For non-randomized studies, the risk of bias was assessed using the NOS quality assessment scale. Results A risk analysis of two randomized controlled trials and nine cohort studies, totaling 1379 patients with lymphoma receiving CD19 CAR-T, is conducted. The incidences for all-cause mortality, CV events, and hypotension were found to be 17.8%, 17.8%, and 52.8%, respectively. Additionally, the incidences of heart failure (HF), cardiomyopathy, cardiac arrest, and other CV events are 3%, 0.6%, 1.3%, and 2.5%, respectively. In addition to cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) as adverse events, patients treated with CD19 CAR T cells are also at risk of CV events. The most common CV events are arrhythmia and HF. Our further analysis showed that the incidence of CV events was 28.7% in the elderly and 13.5% in adults. The incidence of CV events in the elderly was higher than that in adults, and it was statistically significant. Furthermore, the incidence of CV events and hypotension is strongly associated with patients with CRS. Conclusion Therefore, clinicians should pay close attention to the occurrence of such CV events and take timely prevention and intervention measures to further improve the safety of CD19 CAR T cell therapy.

To tackle the efficiency droop, we employed an epitaxial structure engineering approach and utilized SimuLED software to thoroughly investigate the influence of the quantum barrier (QB) thickness on the performance of Micro-LEDs, and delve into the corresponding carrier transport behavior. The results demonstrate that the effect of QB thickness on the performance of Micro-LEDs is closely related to injection current density. Within the current density range of 0–30 A/cm2, a thicker QB layer leads to a higher internal quantum efficiency (IQE) for Micro-LEDs. Conversely, when the current density is in the range of 30–100 A/cm2, employing a thinner QB layer in the LED structure can yield higher IQE values. In addition, this work suggests that tunneling effects and Quantum Confined Stark Effect (QCSE) dominate at different current densities, resulting in an opposite dependency of IQE on QB thickness. Furthermore, our findings indicate that adjusting QB thickness can significantly affect both the peak external quantum efficiency (EQE) and peak current density of Micro-LEDs.

Abstract Purpose This study aimed to investigate the accuracy of three fixation methods in patients with left breast cancer receiving whole breast radiotherapy: conventional breast bracket (BB), breast bracket combined with deep inspiration breath holding (DIBH), and cervical‐thoracic integrated bracket (CTIB) combined with DIBH. Methods From January 2023 to September 2023, 84 patients who underwent left breast cancer radiotherapy with supraclavicular radiation after conservative surgery were included in this study, of which 25 patients were fixed by conventional BB, 34 patients by BB & DIBH, and 25 patients by CTIB & DIBH. Image registration was conducted around the treatment area, using the sternoclavicular joint and acromioclavicular joint as landmarks. Systematic and random errors were calculated to assess the accuracy of these fixation methods. Results Compared to the conventional BB group, the CTIB & DIBH group demonstrated significant improvements in accuracy across multiple dimensions, including left–right, superior‐posterior, and anterior–posterior directions, as well as rotational errors in the sagittal and coronal planes. The CTIB & DIBH group showed a significant reduction of setup error in the anterior–posterior direction compared to the BB & DIBH group. The displacement of the acromioclavicular joint varied, with the CTIB & DIBH method showing more favorable outcomes. Conclusion DIBH method exhibited lower setup errors and more effective fixation of the acromioclavicular joint, especially when combined with CTIB, making it a recommended fixation method in adjuvant radiotherapy following breast‐conserving surgery.

Abstract Lines of evidence have indicated that type 2 diabetes mellitus (T2DM) is an independent risk factor for osteoarthritis (OA) progression. However, the study focused on the relationship between T2DM and OA at the transcriptional level remains empty. We downloaded OA- and T2DM-related bulk RNA-sequencing and single-cell RNA sequencing data from the Gene Expression Omnibus (GEO) dataset. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to screen out hub genes between OA and T2DM, and functional enrichment was done. Single-cell sequencing analysis was further used to screen key genes on OA and T2DM datasets. Rat chondrocytes and human articular cartilage were used to validate biomarkers among OA and T2DM. Sixty-eight hub genes were obtained, which were mainly enriched in the inflammatory response. We found that the hub gene TNFAIP6 is not only closely related to OA and T2DM but also a marker of prehypertrophic chondrocytes, which are closely related to the progression of OA. TNFAIP6 was found to be significantly elevated in CD14 + monocytes in T2DM patients, and this group of cells can promote inflammation. Validation on rat chondrocytes and human cartilage showed that TNFAIP6 was highly expressed in OA and further increased in the presence of T2DM or high glucose. Our study identified several characteristic modules and hub genes in the pathogenesis of T2DM-induced OA, which may facilitate further investigation of its molecular mechanisms. Up-regulated TNFAIP6 may contribute to OA in patients with T2DM by the recruitment of pro-inflammatory CD14 + monocytes in the OA synovium, which provides a potential target for the diagnosis and treatment of T2DM-associated OA.

Abstract Thyroid nodules are a common thyroid disorder, and ultrasound imaging, as the primary diagnostic tool, is susceptible to variations based on the physician’s experience, leading to misdiagnosis. This paper constructs an end-to-end thyroid nodule detection framework based on YOLOv8, enabling automatic detection and classification of nodules by extracting grayscale and elastic features from ultrasound images. First, an attention-weighted DCN is introduced to enhance superficial feature extraction and capture local information. Next, the CPCA mechanism is employed to reduce the interference of redundant information. Finally, a feature fusion network based on an aggregation-distribution mechanism is utilized to improve the learning capability of fine-grained features, enhancing the performance of early nodule detection. Experimental results demonstrate that our method is accurate and effective for thyroid nodule detection, achieving diagnostic rates of 89.3% for benign and 90.4% for malignant nodules based on tests conducted on 611 clinical ultrasound images, with a mean Average Precision at IoU = 0.5 (mAP@50) of 95.5%, representing a 6.6% improvement over baseline models.

Abstract Depth cameras and LiDARs are commonly used sensing devices widely applied in fields such as autonomous driving, navigation, and robotics. Precise calibration between the two is crucial for accurate environmental perception and localization. Methods that utilize the point cloud features of both sensors to estimate extrinsic parameters can also be extended to calibrate limited Field-of-View (FOV) LiDARs and panoramic LiDARs, which holds significant research value. However, calibrating the point clouds from two sensors with different fields of view and densities presents challenges. This paper proposes methods for automatic calibration of the two sensors by extracting and registering features in three scenarios: environments with one plane, two planes, and three planes. For the one-plane and two-plane scenarios, we propose constructing feature histogram descriptors based on plane constraints for the remaining points, in addition to planar features, for registration. Experimental results on simulation and real-world data demonstrate that the proposed methods in all three scenarios achieve precise calibration, maintaining average rotation and translation calibration errors within 2 degrees and 0.05 meters respectively for a $$360^{\circ }$$ 360 ∘ linear LiDAR and a depth camera with a field of view of $$100^{\circ }$$ 100 ∘ vertically and $$70^{\circ }$$ 70 ∘ degrees horizontally.

Background: Active recruitment of osteogenic cells by secreted signaling factors, such as stromal-cell-derived factor 1 (SDF-1), has recently been proposed as a novel strategy to enhance osseointegration. However, the intrinsic importance of the SDF-1/C-X-C chemokine receptor type 4 (CXCR4) axis in promoting osseointegration is unknown. To study the role of SDF-1/CXCR4 in osseointegration, we blocked the SDF-1/CXCR4 pathway in a murine tibial implant model through repeated administrations of an antibody against SDF-1. Methods: Using our previously described murine tibial implant model (N = 24), mice were randomized into an anti-SDF-1 group and a control group (N = 12/group). Intraperitoneal injections of CXCL12/SDF-1 monoclonal antibody (84 µg/mouse) or mouse IgG1 isotype were administered on days 2, 4, 7, 10, 13, 16, 19, 22, and 25 post-surgery. Mice were euthanized 4 weeks post-surgery. Peri-implant bone mass and architecture were determined through microcomputed tomography (µ-CT). Bone implant strength was detected through implant pull-out testing. Results: Inhibition of the SDF-1/CXCR4 pathway significantly reduced host bone–implant interface strength but did not significantly change the cancellous architecture surrounding the implant. Conclusion: SDF-1/CXCR4 is an important pathway to achieve maximum implant osseointegration. However, inhibition of the pathway did not completely eliminate osseointegration.

High-copper alloy/nickel-based high-temperature alloy bimetallic structures are widely utilized in critical components, such as thrust chambers of liquid rocket engines, water cooling circuits for fusion reactor deflectors, and electromagnetic railguns. Among various methods for fabricating Cu/Ni bimetallic structures, laser directed energy deposition (LDED) is considered one of the most promising techniques for depositing nickel-based high-temperature alloys onto high-copper alloy surfaces. In the LDED fabrication process, substrates with uneven thicknesses are a common. The process is characterized by its multi-parameter, high-sensitivity, and non-equilibrium solidification characteristics. Consequently, variations in substrate size can significantly affect molten pool morphology and fabrication stability. This study examines the size effect of a single track of LDED Inconel 718 (In718) on a CuCr0.8 high-copper alloy substrate. The results indicate a pronounced size effect when using a high thermal conductivity CuCr0.8 substrate, particularly regarding substrate thickness. By reducing the thermal conductivity of the CuCr0.8 substrate, the size effect is mitigated, improving the process adaptability of LDED. These findings provide valuable data for the laser processing of surfaces with uneven thickness and high thermal conductivity. They are expected to support the fabrication of variable thrust liquid rocket engines and advance the field of interplanetary exploration.

Bladder cancer, a significant health concern worldwide, often necessitates diverse surgical interventions and postoperative treatments. Understanding the complications arising from these procedures is vital for enhancing patient outcomes and quality of life.

Abstract In recent years, the incidence of nodular thyroid diseases has been increasing annually. Ultrasonography has become a routine diagnostic tool for thyroid nodules due to its high real-time capabilities and low invasiveness. However, thyroid images obtained from current ultrasound tests often have low resolution and are plagued by significant noise interference. Regional differences in medical conditions and varying levels of physician experience can impact the accuracy and efficiency of diagnostic results. With the advancement of deep learning technology, deep learning models are used to identify whether a nodule in a thyroid ultrasound image is benign or malignant. This helps to close the gap between doctors’ experience and equipment differences, improving the accuracy of the initial diagnosis of thyroid nodules. To cope with the problem that thyroid ultrasound images contain complex background and noise as well as poorly defined local features. in this paper, we first construct an improved ResNet50 classification model that uses a two-branch input and incorporates a global attention lightening module. This model is used to improve the accuracy of benign and malignant nodule classification in thyroid ultrasound images and to reduce the computational effort due to the two-branch structure.We constructed a U-net segmentation model incorporating our proposed ACR module, which uses hollow convolution with different dilation rates to capture multi-scale contextual information for feature extraction of nodules in thyroid ultrasound images and uses the results of the segmentation task as an auxiliary branch for the classification task to guide the classification model to focus on the lesion region more efficiently in the case of weak local features. The classification model is guided to focus on the lesion region more efficiently, and the classification and segmentation sub-networks are respectively improved specifically for this study, which is used to improve the accuracy of classifying the benign and malignant nature of the nodules in thyroid ultrasound images. The experimental results show that the four evaluation metrics of accuracy, precision, recall, and f1 of the improved model are 96.01%, 93.3%, 98.8%, and 96.0%, respectively. The improvements were 5.7%, 1.6%, 13.1%, and 7.4%, respectively, compared with the baseline classification model.

Abstract At present, most of the analyses or studies about inductive power transfer (IPT) with constant current (CC) output and constant voltage (CV) output are carried out without considering misalignment conditions or different gaps. An IPT system satisfying battery charging demand and anti‐misalignment requirements simultaneously is infrequent. This paper proposes a multi‐objective particle swarm optimization method of IPT reconfigurable topology to realize CC and CV modes at varying resistance conditions and wide coupling ranges. The output characteristics of an inductor–capacitor–capacitor (LCC)–LCC compensation circuit have been explored, and it is found that the secondary‐side compensated capacitors have a greater impact on the output power, which can be used to improve power regulation ability accompanied by coupling varying. Eight optimization compensated parameters of the reconfigurable topology are obtained from the Pareto front to achieve the required CC and CV charging outputs. By switching the compensated capacitors, the selected parameters can make the current and voltage fluctuation less than 9.3% and 7.9%, respectively, during the coupling charging range from 0.3 to 0.22. Moreover, primary zero voltage switching operation is achieved to enable high efficiency. The simulation and the experimental verification are carried out to verify the validity of the proposed method.

Abstract Background Sepsis-induced myocardial dysfunction (SIMD) may contribute to the poor prognosis of septic patients. Carvacrol (2-methyl-5-isopropyl phenol), a phenolic monoterpene compound extracted from various aromatic plants and fragrance essential oils, has multiple beneficial effects such as antibacterial, anti-inflammatory, and antioxidant properties. These attributes make it potentially useful for treating many diseases. This study aims to investigate the effects of CAR on LPS-induced myocardial dysfunction and explore the underlying mechanism. Results H9c2 cells were stimulated with 10 µg/ml LPS for 12 h, and c57BL/6 mice were intraperitoneally injected with 10 mg/kg LPS to establish a septic-myocardial injury model. Our results showed that CAR could improve cardiac function, significantly reduce serum levels of inflammatory cytokines (including TNF-α, IL-1β, and IL-6), decrease oxidative stress, and inhibit cardiomyocyte apoptosis in LPS-injured mice. Additionally, CAR significantly downregulated the expression of TLR4, MyD88, and NF-κB in LPS-injured mice and H9c2 cells. It also inhibited the upregulation of inflammasome components (such as NLRP3, GSDMD, and IL-1β) in H9c2 cells triggered by LPS. Conclusion Taken together, CAR exhibited potential cardioprotective effects against sepsis, which may be mainly attributed to the TLR4/MyD88/NF-κB pathway and the NLRP3 inflammasome.

Abstract Background Antimicrobial resistance and bacterial hypermucoviscosity, associated with escalating production of capsules, constitute major challenges for the clinical management of Klebsiella pneumoniae (K. pneumoniae) infections. This study investigates the association and underlying mechanism between ceftazidime-avibactam (CAZ-AVI) resistance and bacterial hypermucoviscosity in Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae (KPC-Kp). Results The proportion of CAZ-AVI-sensitive clinical isolates exhibiting the hypermucoviscous phenotype was significantly lower than that of the resistant strains (5.6% vs. 46.7%, P

Oxidative stress is intricately related to gastrointestinal diseases. Although both lactobacillus (LAB) and carnosine (CAR) contribute to combating oxidative stress and attenuating gastrointestinal disorders, little is known about the effects and mechanisms of their combined treatment. Here, we report the protective effects of LAB and/or CAR on the gastrointestinal tissues in normal or dexamethasone (Dex)-induced stress mice. The combination of LAB and CAR protected the structures of stomach and small intestine, alleviating the Dex-induced tissue damages. Additionally, this combined treatment increased the activity of antioxidant enzymes and up-regulated the expression of antioxidant genes in the Nrf2 signaling pathway in stress mice. Our study sheds light on the synergetic and complementary roles of LAB and CAR in maintaining the structural and functional integrity of stomach and small intestine, offering clues for understanding the regulation of antioxidant enzyme genes through the Nrf2 pathway as a potential mechanism.

Oxidative damage, oxidative inflammation, and a range of downstream diseases represent significant threats to human health. The application of natural antioxidants and anti-inflammatory agents can help prevent and mitigate these associated diseases. In this study, we aimed to investigate the effectiveness of walnut green husk (WNGH) as an antioxidant and anti-inflammatory agent in an in vitro setting. HepG2 cells were treated with tert-butyl hydroperoxide (t-BHP) to establish a cellular model of oxidative damage and inflammation. We assessed the biocompatibility of walnut green husk aqueous extract (WNGH-AE) on HepG2 cells using MTT and LDH assays (WNGH-AE concentration: 0.05, 0.1, 0.2, 0.4, 0.8, 1.6, 3.2, 6.4, and 12.8 mg/mL). Additionally, we measured intracellular oxidative stress indicators, such as ROS and 8-OHdG, along with inflammatory factors TNF-α and IL-1β through ELISA to evaluate the antioxidant and anti-inflammatory capacity of WNGH-AE (concentration: 0.025, 0.05, 0.1 mg/mL) in HepG2 cells. We also determined the free radical scavenging capacity of various extracts of WNGH using DPPH and ·OH methods. The total phenols, total polysaccharides, and total flavonoids in WNGH-AE were analyzed using the Folin-Ciocalteu's reagent, the phenol-sulfuric acid method, and the spectrophotometry, respectively. The bioactive components of WNGH-AE were analyzed using LC-MS/MS. Our results demonstrated that WNGH-AE was highly biocompatible with HepG2 cells. The antioxidant effect of WNGH-AE involved the scavenging of intracellular ROS, while its anti-inflammatory effect was linked to the down-regulation of the NF-κB pathway. Compared to other extractants (ethyl acetate, n-butanol, 75% ethanol, and petroleum ether), WNGH-AE exhibited the strongest free radical scavenging ability. Through LC-MS/MS analysis, we identified 403 compounds in WNGH-AE, with gentisic acid being the most abundant and possessing high antioxidant capacity, suggesting it may be a key active component contributing to the antioxidant activity of WNGH-AE. In conclusion, our findings indicate that WNGH-AE is a natural, high-quality antioxidant and anti-inflammatory biomaterial deserving further research and development, with significant potential applications in healthcare. (311 words).

Pathological imaging of surgically excised specimens is the gold standard in clinical practice for diagnosing diseases and making treatment decisions. However, the limited depth of field (DOF) of conventional optical microscopy requires fixing and sectioning of excised samples, which is a cumbersome and lengthy process that significantly increases the time cost of acquiring pathological images. In this study, we propose deep-learning-powered, extended-DOF, dark-field reflectance ultraviolet microscopy (DE-DRUM) for rapid and large-DOF imaging of surgically resected tissues. The system first integrates two cameras positioned at two distinct imaging planes to simultaneously acquire images and then combines the images with a self-calibrated diplane network. The overall DOF of the system is enhanced over eight-folds, and the image acquisition speed is increased by more than seven times. By incorporating the diplane network into a custom-made vacuum compression device, intact and unprocessed mouse brain and human glioma samples are imaged. The results show that DE-DRUM captures pathological features across highly uneven tissue surfaces. DE-DRUM is a rapid, large-DOF, and label-free histological imaging method that holds great potential for application in clinical histopathological diagnosis. In addition, the design of the diplane imaging setup and network provides a plug-and-play solution for large-DOF imaging of various wide-field imaging modalities.

We analyze high-resolution observations of an X-1.0 white-light flare, triggered by a filament eruption, on 2022 October 2. The full process of filament formation and subsequent eruption was captured in the H α passband by the Visible Imaging Spectrograph (VIS) on board the Goode Solar Telescope (GST) within its center field of view. White-light emissions appear in flare ribbons following the filament eruption and H α ribbon brightening. GST Broadband Filter Imager data show that the continuum intensity, as compared to the nearby quiet-Sun area, has increased by up to 20% in the photospheric TiO band around 7057 Å. The Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory reported 10% contrast enhancement in the continuum near Fe i 6173 Å line. The separation motion of two white-light kernels is recorded by the high-cadence GST/TiO images and is well accompanied by the motion of the VIS H α flare ribbon leading edge. One kernel, located in a 150 Gauss field within a granulation area, exhibited an average apparent motion speed of 55 km s ^−1 , which is the highest average speed ever reported. The other kernel drifted at 9 km s ^−1 in an 800 Gauss magnetic field area. Hard X-ray (HXR) emissions reaching up to 300 keV have been observed for this flare. The simultaneous occurrence of high-cadence HXR, microwave, and white-light emissions strongly suggests that the energetic particles from the flare directly contribute to the heating. The inverted HXR energy flux density corresponding to 10% TiO brightening is 2.07 ± 0.23 × 10 ^11 erg cm ^−2 s ^−1 during the flare peak.

ObjectiveTo investigate the etiology, clinical manifestations, treatment methods, and prognosis of urethral diverticulum cancer to enhance understanding of this disease.MethodsThis paper reports a case of urethral diverticulum cancer with “hematuria and dysuria” as the main clinical manifestations. The case is discussed in conjunction with relevant literature.ResultsThe patient initially presented to the gynecology department due to postmenopausal bleeding but was not diagnosed with the disease. Subsequently, the patient developed hematuria and dysuria and was referred to the urology department. MRI indicated urethral diverticulum-like changes with suspected tumorous lesions. Cystourethroscopic biopsy confirmed urethral diverticulum cancer. The patient underwent urethrectomy, and postoperative pathological diagnosis was poorly differentiated urothelial adenocarcinoma.ConclusionUrethral diverticulum cancer is a rare and highly aggressive malignant tumor of the urethra with a poor prognosis. The onset of urethral diverticulum cancer is concealed, and its clinical manifestations are nonspecific and diverse. Preoperative diagnosis is challenging, and imaging studies and cystourethroscopy are the primary preoperative diagnostic methods for urethral diverticulum cancer. Pathology and immunohistochemistry serve as the basis for confirmation of diagnosis. Currently, there is no unified treatment protocol for female urethral diverticulum cancer internationally. For female patients with urethral diverticulum cancer without distant metastasis, surgery remains the primary treatment. For patients with distant metastasis, a combination of surgery, chemotherapy, and radiotherapy may be considered.Genetic testing and targeted immunotherapy offer new approaches for future treatment.

Abstract Colorectal cancer (CRC) is the third most common cancer type and the second highest mortality rate among cancers. However, the mechanisms underlying CRC progression remain to be fully understood. In this work, a recently identified m6A‐modified RNA reader protein Proline‐rich Coiled‐coil 2a (PRRC2A) is markedly upregulated in CRC, and intestinal epithelium‐specific deletion of Prrc2a significantly suppressed tumor cell growth, stemness, and migratory capacity, while its overexpression promoted these behaviors. Through multiomics analysis, PRRC2A directly targeted CSNK1E (encoding CK1ε), maintaining its RNA stability in an m6A‐dependent manner, and that elevated CK1ε can concomitantly result in activation of the WNT and YAP signaling pathways. Interestingly, PRRC2A is directly regulated by the transcription factor ATF1 in its promoter. In summary, the work reveals a novel mechanism by which m6A reader PRRC2A promotes colorectal cancer progression via CK1ε and aberrant upregulation of WNT and YAP signaling. Therefore, PRRC2A and CK1ε can be potential therapeutic targets for treating CRC.

Environmental pollutants including ultrafine particulate matter (UFPs) and adverse meteorological conditions pose significant public health impacts, particularly affecting respiratory health. This study aims to elucidate the synergistic effects of cold-humid conditions and UFPs exposure on respiratory health, utilizing Carbon Black Nanoparticles (CB-NPs) as surrogates for UFPs. Through comprehensive lung function tests, histopathological examinations, and biomarker analyses, this research focuses on the modulation of oxidative stress signaling pathways and NF-κB activation. Male Balb/c mice were exposed to specific concentrations of CB-NPs (30–50 nm in diameter, 0.184 mg/(kg·day)) in a controlled environmental chamber mimicking cold (10°C/14°C) and humid (90 % RH) conditions over three weeks. The results indicate that exposure to CB-NPs alone increased lung function, oxidative stress (ROS, GSH, MDA), inflammation (IL-6, TNF-α, IL-1β), apoptosis (Caspase 3, Caspase 8, Caspase 9), and histopathological alterations in lung tissue. Furthermore, these effects were notably more severe under combined exposure with cold-humid conditions. These results suggest that the adverse effects of pollutants are not solely concentration-dependent but are exacerbated by specific environmental contexts. It is evident that Vitamin E (100 mg/kg/day) can attenuate these adverse effects, underscoring its potential as a protective agent against environmental stressor-induced air pollutants and cold humid conditions. Our findings suggest that the synergistic effects of environmental factors and pollutant exposure significantly impact respiratory health, providing valuable insights for the design of healthier indoor environments and the development of strategies to mitigate these risks.

Introduction Preoperative patients with knee osteoarthritis have a significantly increased risk of venous thromboembolism (VTE). While the Caprini risk assessment model offers some clinical guidance in predicting deep vein thrombosis (DVT), it has a relatively low predictive accuracy. Enhancing the model by integrating biomarkers, such as D-dimers, can potentially improve its accuracy. In this study, we explored the effectiveness of combining the Caprini risk model with D-dimer levels for individualized DVT risk assessment in patients with knee osteoarthritis. Materials and Methods This retrospective cohort study included 1605 knee osteoarthritis patients scheduled for total knee arthroplasty from Peking Union Medical College Hospital, screened between January 2015 and December 2018. A revised Caprini risk stratification model was developed, and a predictive DVT model was developed based on this revised system. The sensitivity, specificity, and the area under the curve (AUC) were used to determine predictive effectiveness of the model. Results In the revised Caprini risk stratification, the incidence of DVT increased with higher risk levels: 2.52% in the low-risk group (scores 0-2), 2.88% in the moderate-risk group (score 3), 6.47% in the high-risk group (score 4), and 9.09% in the highest-risk group (score ≥ 5). The incidence of DVT was 3.869-fold higher in the highest-risk group and 2.676-fold higher in the high-risk group compared to the low-risk group (p = 0.013 and p = 0.014, respectively). Combining the revised Caprini risk stratification with D-dimer level demonstrated an improved AUC of 0.792, compared to D-dimer level alone (AUC 0.774) and the revised Caprini model alone (AUC 0.598). Furthermore, applying specific D-dimer thresholds across the four Caprini risk stratifications outperformed the combination of the revised Caprini model and D-dimer level in terms of AUC, specificity, and reduction in unnecessary ultrasonography. Using the Youden index, the AUC for the threshold-based method was slightly higher (0.775 vs 0.754, p = 0.310), with significantly better specificity (76.8% vs 63.6%, p

Studies have determined that soil biota have distinct responses to plant richness. However, the potential mechanisms that regulate soil biota (microbes and fauna) attributes (biomass, activity, and abundance) to plant mixtures over experimental time are still unclear. By conducting 1594 paired observations of the impacts of plant mixture on soil biota attributes and its corresponding potential drivers from 179 studies, we found that plant above- and belowground biomass and total biomass were significantly increased by 35.0%, 52.9%, and 48.6% under plant mixture, respectively. Soil pH decreased significantly by 0.8% with experimental time. The responses of soil microbial attributes were more sensitive than soil fauna abundances under plant mixture over time. On average, soil microbial respiration and microbial biomass increased by 11.6% and 12.1%, respectively, in plant mixtures across all ecosystem types. For soil fauna community, only the abundance of herbivores showed a significant increase of 20.4% to plant mixtures. The response of above- and belowground biomass, total biomass, the ratio of carbon to nitrogen, and pH showed positive relationships with most specific microbial attributes, while mean annual precipitation, mean annual temperature, and the response of soil total nitrogen and NO3–-N showed negative relationships with them in response to plant mixtures. The abundance of soil fauna was secondarily affected by the changes of soil abiotic properties. Taken together, the response of soil total carbon had a strong effect on soil biota attributes. Changes in belowground biomass and total biomass showed negative relationships with specific soil fauna abundance, while soil total carbon, nitrogen, pH, and soil moisture showed positive relationships with specific soil fauna abundance. However, only herbivore abundance showed significant differences across different ecosystems. Our analysis illustrates the distinct responses of soil biota attributes to plant mixtures and their potential influencing factors, thereby benefiting the sustainability of soil biota biodiversity in the face of plant richness loss.

BackgroundClinical studies have demonstrated the high efficacy of using chimeric antigen receptor (CAR)-T cells targeting B-cell maturation antigen (BCMA) and orphan G protein-coupled receptor, class C group 5 member D (GPRC5D) to treat relapsed or refractory multiple myeloma (RRMM). In this study, we compared the efficacy and safety of BCMA CAR-T-cell therapy (BCMA CAR-T) and GPRC5D CAR T-cell therapy (GPRC5D CAR-T) in patients with RRMM.MethodsWe retrieved and included eligible clinical trials of BCMA or GPRC5D CAR-T for RRMM patients. The primary outcomes for efficacy were overall response rate (ORR), complete response rate (CRR), minimal residual disease (MRD) negativity, and relapse rate. The primary outcomes for safety were cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS).ResultsWe incorporated 18 early-phase, single-arm clinical trials, which included 503 and 133 patients receiving BCMA CAR-T and GPRC5D CAR-T, respectively. For the GPRC5D CAR-T cohort, the estimated ORR, CRR, MRD negativity rate, and relapse rate were found to be 89.8% [95% confidence interval (CI), 82.8%–96.9%], 50.5% (95% CI, 38.0%–62.9%), 78.8% (95% CI, 53.0%–100%), and 26.0% (95% CI, 7.4%–44.6%), respectively. In the BCMA CAR-T group, the ORR was 76.3% (95% CI, 67.9%–84.7%), the CRR was 34.3% (95% CI, 25.9%–42.7%), the MRD negativity rate was 76.5% (95% CI, 63.1%–90.0%), and the recurrence rate was 57.3% (95% CI, 47.7%–66.9%). These values were significantly lower than those observed in the GPRC5D CAR-T cohort. Both BCMA and GPRC5D CAR-T demonstrated acceptable safety. The estimated incidence of BCMA CAR-T resulting in grade 3–5 CRS and ICANS was only 5.4% (95% CI, 2.0%–10.4%) and 3.3% (95% CI, 0.6%–8.0%), respectively. The estimated incidence of GPRC5D CAR-T resulting in grade 3–5 CRS and ICANS was only 1.6% (95% CI, 0.0%–6.5%) and 2.7% (95% CI, 0.7%–6.2%), respectively.ConclusionGPRC5D CAR-T potentially demonstrates enhanced effectiveness relative to BCMA CAR-T in treating patients with RRMM. Therefore, GPRC5D CAR-T can be regarded as the preferred therapeutic option for RRMM, particularly among patients who have undergone relapse subsequent to BCMA CAR-T treatment.

Deep learning methods are increasingly being applied in fault diagnosis because of the capability of representing internal correlations through network structures and extracting hidden features from original data. Convolutional neural networks (CNNs) can perceive local features through convolutional kernels and obtain more advanced features through iteration, which significantly improved the accuracy of fault diagnosis. However, the randomness of feature extraction will cause the insufficient use of the input information and also limiting the network training for specific faults. In this paper, a multi-channel CNN based on Squeeze-and-Convolution attention is introduced to enhance the efficiency of fault diagnosis for rotating machinery. A multi-channel CNN is used to enhance the input information which reduces the input loss, then a new channel attention mechanism based on squeeze-and-excitation module is proposed to reduce the computational complexity of network while focusing on key features. To combine the multi-channel CNN and SC module, the proposed ISC structure enables basic CNN to extract more comprehensive and important features. The fault diagnosis results, which based on two bearing databases named MFPT datasets and Paderborn University datasets, have demonstrated that the ISC-CNN proposed in this study outperforms most commonly used methods. The method exhibits strong performance on both conventional datasets and small sample datasets, which validates its effectiveness.

The IncRNA Malat1 was initially believed to be dispensable for physiology due to the lack of observable phenotypes in Malat1 knockout (KO) mice. However, our study challenges this conclusion. We found that both Malat1 KO and conditional KO mice in the osteoblast lineage exhibit significant osteoporosis. Mechanistically, Malat1 acts as an intrinsic regulator in osteoblasts to promote osteogenesis. Interestingly, Malat1 does not directly affect osteoclastogenesis but inhibits osteoclastogenesis in a non-autonomous manner in vivo via integrating crosstalk between multiple cell types, including osteoblasts, osteoclasts, and chondrocytes. Our findings substantiate the existence of a novel remodeling network in which Malat1 serves as a central regulator by binding to β-catenin and functioning through the β-catenin-OPG/Jagged1 pathway in osteoblasts and chondrocytes. In pathological conditions, Malat1 significantly promotes bone regeneration in fracture healing. Bone homeostasis and regeneration are crucial to well-being. Our discoveries establish a previous unrecognized paradigm model of Malat1 function in the skeletal system, providing novel mechanistic insights into how a lncRNA integrates cellular crosstalk and molecular networks to fine tune tissue homeostasis, remodeling and repair.

Advances in bacteriophage genome sequencing and regulatory approvals of some bacteriophages in various applications have renewed interest in these antibacterial viruses as a potential solution to persistent food safety challenges. Here, we analyzed in depth the genome of the previously studied Escherichia bacteriophage OSYSP (phage OSYSP), revealed its application-related characteristics, and optimized its enumeration techniques for facilitating industrial implementation. We previously sequenced phage OSYSP genome completely by combining results from Illumina Miseq and Ion Torrent sequencing platforms and completing the remaining sequence gaps using PCR. Based on the genomics analysis completed herein, phage OSYSP was confirmed as an obligate lytic phage of the Caudoviricetes class. The genome encodes 81 proteins of identifiable functions, including two endolysins and 45 proteins that support host-independent DNA replication, transcription, and repair. Despite its similarities to T5-like phages, unique genome arrangements confirm phage OSYSP’s novelty. The genomic analysis also confirmed the absence of DNA sequences encoding virulence or antibiotic resistance factors. For optimizing phage detection and quantification in the conventional plaque assay, it was observed that decreasing the concentration of agar or agarose, when used as a medium gelling agent, increased phage recovery (p 0.05) on phage infectivity. In vitro application of phage OSYSP against E. coli O157:H7 EDL933 decreased the pathogen’s viable population by >5.7-log CFU/mL within 80 min, at a multiplicity of infection as low as 0.01. The favorable genome characteristics, combined with improved enumeration methodology, and the proven infectivity stability, make phage OSYSP a promising biocontrol agent against pathogenic E. coli for food or therapeutic applications.

ABSTRACTInterferometric Synthetic Aperture Radar (InSAR) is capable of detecting crust deformation. However, the accuracy is limited by spatiotemporal changes in the lower troposphere. In this paper, we constructed a periodic zenith total delay negative exponential function (PZTD-NEF) model of atmospheric spatiotemporal variation characteristics based on ERA-5 data to alleviate the temporal oscillation bias introduced by tropospheric delay and improve the accuracy of time series InSAR (TS-InSAR) inversion of surface deformation. We evaluated the model’s performance using the phase standard deviation (STD), atmospheric delay correlation coefficient with topography and the spatial structure function. The results were compared with a linear topography-dependent empirical model, generic atmospheric correction online service (GACOS) and ERA-5 methods. Our method reduces the STD of the phase of 83% of the interferograms by 12.8%. For vertical stratification delay correction, the correlation between the proposed method and the Linear, GACOS, and ERA-5 reached 0.734, 0.708, and 0.729, respectively. We found that accounting for spatiotemporal variation characteristics of tropospheric delay can alleviate the seasonal oscillations of vertical stratification delay and improve the accuracy of the deformation time series solution by 40.04%. We also used the Kunming continuous operation reference station system (KMCORS) to verify the displacement results of our method.

Background Inflammation plays a crucial role in occurrence of kidney injury, and specific dietary patterns can influence systemic inflammation levels. However, the relationship between dietary inflammatory potential and early-stage kidney damage remains unclear.Method 2,108 participants was recruited from 2001–2002 National Health and Nutrition Examination Survey (NHANES). Dietary Inflammatory Index (DII) is utilized to assess dietary inflammatory potential, calculated through a 24-h dietary recall questionnaire. Early renal injury was evaluated using urinary albumin to creatinine (UACR), cystatin C (CysC), β-2 microglobulin (β2M), and estimated glomerular filtration rate (eGFR) based on serum creatinine (eGFRs), cystatin C (eGFRc), and both Scr and CysC (eGFRs&c). Participant characteristics were analyzed, and association between DII, hypertension, and early renal injury markers was explored using multiple linear and logistic regression models.Results The average age of participants was 53.9 years. DII exhibited a positive correlation with UACR (β = −0.048[0.017,0.078]), β2M (β = 0.019[0.010,0.027]), CysC (β = 0.012 [0.004,0.021]). Conversely, a negative correlation was observed between DII and eGFRc (β = −1.126[−1.554, −0.699]), eGFRs&c (β=-1.101[−1.653, −0.549]). A significant association was observed between hypertension and abnormality of early kidney damage markers. Subgroup analysis reveals that the positive correlation between DII and the occurrence of abnormal markers of early kidney damage is only observed in individuals with hypertension. Furthermore, an interaction between DII and hypertension was detected in eGFRs&c (OR:1.250[1.042, 1.499], p for interaction = 0.03).Conclusion Higher levels of DII may be associated with occurrence of early kidney damage. For individuals with hypertension, avoiding excessive consumption of pro-inflammatory foods may reduce the risk of renal injury.

Aims This study aims to explore the alterations of dendritic cells (DCs) subpopulations in ectopic endometrial lesions and unveil the underlying mechanisms.Materials and methods Patients with endometriosis (n = 81) and women without endometriosis (n = 19) were recruited in this study. Dendritic cells (DCs) in the endometrial samples were counted after immunohistochemistry staining. The proportion of myeloid DCs and plasmacytoid DCs was calculated by flow cytometry. Primary DCs were isolated from tissues, and the cell viability and apoptosis were examined by MTT assay and flow cytometry. Cytokines were detected by the enzyme-linked immunosorbent assay. Differentially expressed genes were filtered by analyzing two datasets that were downloaded from GEO database and detected by RT-qPCR in tissues and isolated DCs. The function of HSD11B1 was examined in an endometrial stromal cell-DCs co-culture system and in vitro cultured DCs.Results Reduced myeloid DCs and increased CD11c-CD304-DCs were found in ectopic endometrium compared to control endometrium and eutopic endometrium from endometriosis patients. Myeloid DCs isolated from ectopic endometrium expressed less CD80, CD83, CD86 and had reduced proliferation, increased apoptosis, and reduced cytokine production. The expression of HSD11B1 was significantly increased in both ectopic endometrium and isolated myeloid DCs. Overexpression of HSD11B1 in immature DCs could repress DCs maturation and cytokine production. Endometrial stromal cells overexpressing HSD11B1 secreted increased cortisol, which repressed DCs maturation.Conclusions HSD11B1 is upregulated in ectopic endometrial lesions, which may contribute to endometriosis through repressing myeloid DCs maturation.

Rockbursts have become one of the most serious hazards in underground mines worldwide. While the characteristics of ground motions before rockbursts (or high-magnitude events (HMEs)) have not been studied. In this study, the peak ground velocity (PGV) and cumulative absolute displacement (CAD) before HMEs were examined based on seismic monitoring in a coal mine. It’s found that the source mechanisms vary significantly across different zones of the longwall, attributed to the low correlation between rock fracture types, stress levels, and seismic intensity. This correlation is mainly related to the distribution of primary fractures within the rock mass. The non-overlap of CAD peak with HME and the induction of delayed rockbursts are mainly caused by the unavoidable creep and additional energy input into the coal mass under disturbances before instability. The energy conversion process of the entire system is determined to be controlled by the stiffness ratio between the roof-floor system and the loaded coal, in accordance with the concept of dynamic and static load superposition. A high static load, strong dynamic disturbances, and a low rigidity ratio between surrounding rock and coal are identified as the most hazardous factors.

Abstract Introduction The estimated dose of radiation to immune cells (EDRIC) has been shown to correlate with the overall survival (OS) of patients who receive definitive thoracic radiotherapy. However, the planning target volume (PTV) may be a confounding factor. We assessed the prognostic value of EDRIC for non-small cell lung cancer (NSCLC) in patients who underwent postoperative radiotherapy (PORT) with homogeneous PTV. Methods Patients with NSCLC who underwent PORT between 2004 and 2019 were included. EDRIC was computed as a function of the number of radiation fractions and mean doses to the lungs, heart, and remaining body. The correlations between EDRIC and OS, disease-free survival (DFS), locoregional-free survival (LRFS), and distant metastasis-free survival (DMFS) were analyzed using univariate and multivariate Cox models. Kaplan–Meier analysis was performed to assess the survival difference between low- and high-EDRIC groups. Results In total, 345 patients were analyzed. The mean EDRIC was 6.26 Gy. Multivariate analysis showed that higher EDRIC was associated with worse outcomes in terms of OS (hazard ratio [HR] 1.207, P = .007), DFS (HR 1.129, P = .015), LRFS (HR 1.211, P = .002), and DMFS (HR 1.131, P = .057). In the low- and high-EDRIC groups, the 3-year OS was 81.2% and 74.0%, DFS 39.8% and 35.0%, LRFS 70.4% and 60.5%, and DMFS 73.9% and 63.1%, respectively. Conclusions EDRIC is an independent prognostic factor for survival in patients with NSCLC undergoing PORT. Higher doses of radiation to the immune system are associated with tumor progression and poor survival. Organs at risk for the immune system should be considered during radiotherapy planning.

Abstract Background The hyperinflammatory condition and lymphoproliferation due to Epstein-Barr virus (EBV)-associated hemophagocytic lymphohistiocytosis (HLH) affect the detection of lymphomas by 18F-FDG PET/CT. We aimed to improve the diagnostic capabilities of 18F-FDG PET/CT by combining laboratory parameters. Methods This retrospective study involved 46 patients diagnosed with EBV-positive HLH, who underwent 18F-FDG PET/CT before beginning chemotherapy within a 4-year timeframe. These patients were categorized into two groups: EBV-associated HLH (EBV-HLH) (n = 31) and EBV-positive lymphoma-associated HLH (EBV + LA-HLH) (n = 15). We employed multivariable logistic regression and regression tree analysis to develop diagnostic models and assessed their efficacy in diagnosis and prognosis. Results A nomogram combining the SUVmax ratio, copies of plasma EBV-DNA, and IFN-γ reached 100% sensitivity and 81.8% specificity, with an AUC of 0.926 (95%CI, 0.779–0.988). Importantly, this nomogram also demonstrated predictive power for mortality in EBV-HLH patients, with a hazard ratio of 4.2 (95%CI, 1.1–16.5). The high-risk EBV-HLH patients identified by the nomogram had a similarly unfavorable prognosis as patients with lymphoma. Conclusions The study found that while 18F-FDG PET/CT alone has limitations in differentiating between lymphoma and EBV-HLH in patients with active EBV infection, the integration of a nomogram significantly improves the diagnostic accuracy and also exhibits a strong association with prognostic outcomes.

Hyperoside and quercetin are similar in molecular structures. In this study, the antioxidant regulatory targets of hyperoside and quercetin are mainly in the nuclear factor (erythroid-2-derived)-related factor 2 (Nrf2) pathway predicted by network pharmacology. And the antioxidant effect and mechanism of hyperoside and quercetin were measured and compared in H2O2-induced HepG2 cells and Caenorhabditis elegans. The findings indicated that quercetin was more effective than hyperoside in reducing oxidative damage, which was proved by improved cell viability, decreased reactive oxygen species (ROS) production, decreased cellular apoptosis, and alleviated mitochondrial damage. In addition, quercetin was more efficient than hyperoside in enhancing the expression of Nrf2-associated mRNAs, increasing the activities of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT), and reducing the cellular malondialdehyde (MDA) content. Quercetin was superior to hyperoside in prolonging the lifespan of worms, decreasing the accumulation of lipofuscin, inhibiting ROS production, and increasing the proportion of skn-1 in the nucleus. With the Nrf2 inhibitor ML385, we verified that quercetin and hyperoside primarily protected the cells against oxidative damage via the Nrf2 signalling pathway. Furthermore, molecular docking and dynamics simulations demonstrated that the quercetin- Kelch-like ECH-associated protein 1 (Keap1) complex was more stable than the hyperoside-Keap1 complex. The stable structure of the complex might hinder the binding of Nrf2 and Keap1 to release Nrf2 and facilitate its entry into the nucleus to play an antioxidant role. Overall, quercetin had a better antioxidant than hyperoside.

Abstract Background Gene expression profiles in breast tissue biopsies contain information related to chemotherapy efficacy. The promoter profiles in cell-free DNA (cfDNA) carrying gene expression information of the original tissues may be used to predict the response to neoadjuvant chemotherapy in breast cancer as a non-invasive biomarker. In this study, the feasibility of the promoter profiles in plasma cfDNA was evaluated as a novel clinical model for noninvasively predicting the efficacy of neoadjuvant chemotherapy in breast cancer. Method First of all, global chromatin (5 Mb windows), sub-compartments and promoter profiles in plasma cfDNA samples from 94 patients with breast cancer before neoadjuvant chemotherapy (pCR = 31 vs. non-pCR = 63) were analyzed, and then classifiers were developed for predicting the efficacy of neoadjuvant chemotherapy in breast cancer. Further, the promoter profile changes in sequential cfDNA samples from 30 patients (pCR = 8 vs. non-pCR = 22) during neoadjuvant chemotherapy were analyzed to explore the potential benefits of cfDNA promoter profile changes as a novel potential biomarker for predicting the treatment efficacy. Results The results showed significantly distinct promoter profile in plasma cfDNA of pCR patients compared with non-pCR patients before neoadjuvant chemotherapy. The classifier based on promoter profiles in a Random Forest model produced the largest area under the curve of 0.980 (95% CI: 0.978–0.983). After neoadjuvant chemotherapy, 332 genes with significantly differential promoter profile changes in sequential cfDNA samples of pCR patients was observed, compared with non-pCR patients, and their functions were closely related to treatment response. Conclusion These results suggest that promoter profiles in plasma cfDNA may be a powerful, non-invasive tool for predicting the efficacy of neoadjuvant chemotherapy breast cancer patients before treatment, and the on-treatment cfDNA promoter profiles have potential benefits for predicting the treatment efficacy.

Abstract This study assessed the knowledge, attitude, and practice (KAP) of non-ophthalmic medical staff towards myopia-related fundus lesions. This multicenter, cross-sectional study enrolled non-ophthalmic medical staff of Suining City between January and May 2023 using a self-designed questionnaire. A total of 505 (93.19%) valid questionnaires were included. Their mean KAP scores were 8.10 ± 2.32 (range: 0–12), 20.27 ± 2.68 (range: 0–24), and 17.77 ± 5.04 (range: 0–28), respectively. Structural equation modeling indicated that knowledge has a positive effect on attitude (β = 0.307, P

Developing a feasible and low-cost strategy for the recovery of calcium fluoride efficiently from fluoride-containing wastewater is very essential for the recycle of fluoride resources. Herein, a modified lime precipitation method was employed to recover CaF2 from fluorinated wastewater using a special icy lime solution. Intriguingly, the highest F– removal was greater than 95% under the optimal condition, leaving a fluoride concentration from 200 to 8.64 mg/L, while the lime dosage was much lower than that of industry. Importantly, spherical-shaped CaF2 particles with a 93.47% purity and size smaller than 600 nm were recovered, which has a high potential for the production of hydrofluoric acid. Besides, the precipitation was significantly affected by Ca/F molar ratio, stirring time, temperature, and solution pH. Furthermore, the thermodynamics and kinetics were investigated in detail to reveal the crystallization process. As a result, the defluorination reaction followed the pseudo-second order reaction kinetics model. Also, CO2 in the air adversely influenced the CaF2 purity. Based on this facile method, a high lime utilization efficiency was applied to defluorination, which contributed to protecting the environment and saving costs. This study, therefore, provides a feasible approach for the green recovery of fluorine resources and has significance for related research. HIGHLIGHTS A facile icy lime precipitation method was employed to remove F−.; Highly pure spherical particles with CaF2 of more than 93% were recovered.; Thermodynamics implied that CO2 had an inhibitory effect on the purity of CaF2.; Change in F fitted well with the pseudo-second order reaction kinetics model.; The co-precipitation of CaF2 and CaCO3 occurred.;

Abstract Background Accumulating evidence suggests that the gut microbiota and metabolites can modulate tumor responses to immunotherapy; however, limited data has been reported on biliary tract cancer (BTC). This study used metagenomics and metabolomics to identify characteristics of the gut microbiome and metabolites in immunotherapy-treated BTC and their potential as prognostic and predictive biomarkers. Methods This prospective cohort study enrolled 88 patients with BTC who received PD-1/PD-L1 inhibitors from November 2018 to May 2022. The microbiota and metabolites significantly enriched in different immunotherapy response groups were identified through metagenomics and LC-MS/MS. Associations between microbiota and metabolites, microbiota and clinical factors, and metabolites and clinical factors were explored. Results Significantly different bacteria and their metabolites were both identified in the durable clinical benefit (DCB) and non-durable clinical benefit (NDB) groups. Of these, 20 bacteria and two metabolites were significantly associated with survival. Alistipes were positively correlated with survival, while Bacilli, Lactobacillales, and Pyrrolidine were negatively correlated with survival. Predictive models based on six bacteria, four metabolites, and the combination of three bacteria and two metabolites could all discriminated between patients in the DCB and NDB groups with high accuracy. Beta diversity between two groups was significantly different, and the composition varied with differences in the use of immunotherapy. Conclusions Patients with BTC receiving immunotherapy have specific alterations in the interactions between microbiota and metabolites. These findings suggest that gut microbiota and metabolites are potential prognostic and predictive biomarkers for clinical outcomes of anti-PD-1/PD-L1-treated BTC.

Abstract Introduction About 17–80% stroke survivors experience the deficit of upper limb function, which strongly influences their independence and quality of life. Robot-assisted training and functional electrical stimulation are commonly used interventions in the rehabilitation of hemiplegia upper extremities, while the effect of their combination remains unclear. The aim of this trial is to explore the effect of robot-assisted upper limb training combined with functional electrical stimulation, in terms of neuromuscular rehabilitation, compared with robot-assisted upper limb training alone. Methods Individuals (n = 60) with the first onset of stroke (more than 1 week and less than 1 year after stroke onset) will be considered in the recruitment of this single-blinded, three-arm randomized controlled trial. Participants will be allocated into three groups (robot-assisted training combined with functional electrical stimulation group, robot-assisted training group, and conventional rehabilitation therapies group) with a ratio of 1:1:1. All interventions will be executed for 45 min per session, one session per day, 5 sessions per week for 6 weeks. The neuromuscular function of the upper limb (Fugl-Meyer Assessment of upper extremity), ability of daily life (modified Barthel Index), pain (visual analogue scale), and quality of life (EQ-5D-5L) will be assessed at the baseline, at the end of this trial and after 3 months follow-up. Two-way repeated measures analysis of variance will be used to compare the outcomes if the data are normally distributed. Simple effects tests will be used for the further exploration of interaction effects by time and group. Scheirer-Ray-Hare test will be used if the data are not satisfied with normal distribution. Discussion We expect this three-arm randomized controlled trial to explore the effectiveness of robot-assisted training combined with functional electrical stimulation in improving post-stroke upper limb function compared with robot-assisted training alone. Trial registration Effect of upper limb robot on improving upper limb function after stroke, identifier: ChiCTR2300073279. Registered on 5 July 2023.

Abstract Background Neuroblastoma (NB) is a highly heterogeneous tumor, and more than half of newly diagnosed NB are associated with extensive metastases. Accurately characterizing the heterogeneity of whole-body tumor lesions remains clinical challenge. This study aims to quantify whole-tumoral metabolic heterogeneity (WMH) derived from whole-body tumor lesions, and investigate the prognostic value of WMH in NB. Methods We retrospectively enrolled 95 newly diagnosed pediatric NB patients in our department. Traditional semi-quantitative PET/CT parameters including the maximum standardized uptake value (SUVmax), the mean standardized uptake value (SUVmean), the peak standardized uptake value (SUVpeak), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured. These PET/CT parameters were expressed as PSUVmax, PSUVmean, PSUVpeak, PMTV, PTLG for primary tumor, WSUVmax, WSUVmean, WSUVpeak, WMTV, WTLG for whole-body tumor lesions. The metabolic heterogeneity was quantified using the areas under the curve of the cumulative SUV-volume histogram index (AUC-CSH index). Intra-tumoral metabolic heterogeneity (IMH) and WMH were extracted from primary tumor and whole-body tumor lesions, respectively. The outcome endpoints were overall survival (OS) and progression-free survival (PFS). Survival analysis was performed utilizing the univariate and multivariate Cox proportional hazards regression. The optimal cut-off values for metabolic parameters were obtained by receiver operating characteristic curve (ROC). Results During follow up, 27 (28.4%) patients died, 21 (22.1%) patients relapsed and 47 (49.5%) patients remained progression-free survival, with a median follow-up of 35.0 months. In survival analysis, WMTV and WTLG were independent indicators of PFS, and WMH was an independent risk factor of PFS and OS. However, IMH only showed association with PFS and OS. In addition to metabolic parameters, the International Neuroblastoma Staging System (INSS) was identified as an independent risk factor for PFS, and neuron-specific enolase (NSE) served as an independent predictor of OS. Conclusion WMH was an independent risk factor for PFS and OS, suggesting its potential as a novel prognostic marker for newly diagnosed NB patients.

Abstract Background Because spontaneous remission is common in IMN, and there are adverse effects of immunosuppressive therapy, it is important to assess the risk of progressive loss of renal function before deciding whether and when to initiate immunosuppressive therapy. Therefore, this study aimed to establish a risk prediction model to predict patient prognosis and treatment response to help clinicians evaluate patient prognosis and decide on the best treatment regimen. Methods From September 2019 to December 2020, a total of 232 newly diagnosed IMN patients from three hospitals in Liaoning Province were enrolled. Logistic regression analysis selected the risk factors affecting the prognosis, and a dynamic online nomogram prognostic model was constructed based on extreme gradient boost, random forest, logistic regression machine learning algorithms. Receiver operating characteristic and calibration curves and decision curve analysis were utilized to assess the performance and clinical utility of the developed model. Results A total of 130 patients were in the training cohort and 102 patients in the validation cohort. Logistic regression analysis identified four risk factors: course ≥ 6 months, UTP, D-dimer and sPLA2R-Ab. The random forest algorithm showed the best performance with the highest AUROC (0.869). The nomogram had excellent discrimination ability, calibration ability and clinical practicability in both the training cohort and the validation cohort. Conclusions The dynamic online nomogram model can effectively assess the prognosis and treatment response of IMN patients. This will help clinicians assess the patient’s prognosis more accurately, communicate with the patient in advance, and jointly select the most appropriate treatment plan.

Abstract The prevalence of papillary thyroid cancer (PTC) has been rising in recent years. Despite its relatively low mortality, PTC frequently metastasizes to lymph nodes and often recurs, posing significant health and economic burdens. The role of iodine in the pathogenesis and advancement of thyroid cancer remains poorly understood. Circular RNAs (circRNAs) are recognized to function as competing endogenous RNAs (ceRNAs) that modulate gene expression and play a role in various cancer stages. Consequently, this research aimed to elucidate the mechanism by which circRNA influences the impact of iodine on PTC. Our research indicates that high iodine levels can exacerbate the malignancy of PTC via the circ_0004851/miR-296-3p/FGF11 axis. These insights into iodine’s biological role in PTC and the association of circRNA with the disease could pave the way for novel biomarkers and potentially effective therapeutic strategies to mitigate PTC progression.

In high-power hybrid AC/DC distribution systems, multi-port power electronic transformer (PET) encounters challenges such as energy coordination, transient switching, and submodule balancing. In order to address these issues, especially improving transient dynamic performance, this paper proposes a global inertia sharing (GIS) control scheme for a hybrid five-port PET based on modular multilevel converter (MMC), dual active bridge (DAB), and energy storage system (ESS). Firstly, the scheme introduces an inertia sharing (IS) characteristic among internal submodules and external ports based on the capacitor’s properties, analyzing the control quantities and degrees of freedom for controlling IS. Next, according to the mathematical model of the PET, four IS controllers and three balancing controllers are designed for the GIS control scheme to achieve coordinated energy control, optimization of transient performance of the system, balance between submodules, and effectively reduce the number of control parameters and sampling hardware circuits. Additionally, the operation region of the system, power flow modes, and controller parameter selection are analyzed. Validation results in extreme conditions and numerous operating mode switching demonstrate that the proposed GIS control scheme enables seamless switching and submodule balancing under uninterrupted power supply, significantly enhancing system transient dynamic performance and enriching power flow modes.

To obtain the ignition performance of an integrated inclined combustor, we perform an experimental study on the ignition performance of an inclined combustor under various ignition positions, inlet flow rates, and fuel air ratios (FARs). The experimental results reveal the following. 1) During ignition at I1, the inclined combustor presents the best ignition performance. 2) The forward propagation process of flame along the swirler's inclined direction easily realizes flame propagation, whereas the backward flame propagation process in the swirler's inclined direction is difficult to achieve; forward and backward flame propagations exhibit evident differences. 3) The diffusion propagation of swirl flames at the ignition head is the main means swirl flames are generated at the nonignition head. 4) During the ignition process, the combustion intensity increases with the increase in FAR and decreases with the increase in inlet flow rate. 5) The successful ignition time decreases with the increase in inlet flow rate and FAR.

Background Fetal arrhythmias frequently co-occur with congenital heart disease in fetuses. The peaks observed in M-mode fetal echocardiograms serve as pivotal diagnostic markers for fetal arrhythmias. However, speckles, artifacts, and noise pose notable challenges for accurate image analysis. While current deep learning networks mainly overlook cardiac cyclic information, this study concentrated on the integration of such features, leveraging contextual constraints derived from cardiac cyclical features to improve diagnostic accuracy. Methods This study proposed a novel deep learning architecture for diagnosing fetal arrhythmias. The architecture presented a loss function tailored to the cardiac cyclical information and formulated a diagnostic algorithm for classifying fetal arrhythmias. The training and validation processes utilized a dataset comprising 4440 patches gathered from 890 participants. Results Incorporating cyclic loss significantly enhanced the performance of deep learning networks in predicting peak points for diagnosing fetal arrhythmia, resulting in improvements ranging from 7.11% to 14.81% in F 1-score across different network combinations. Particularly noteworthy was the 18.2% improvement in the F 1-score for the low-quality group. Additionally, the precision of diagnosing fetal arrhythmia across four categories exhibited improvement, with an average improvement rate of 20.6%. Conclusion This study introduced a cyclic loss mechanism based on the cardiac cycle information. Comparative evaluations were conducted using baseline methods and state-of-the-art deep learning architectures with the fetal echocardiogram dataset. These evaluations demonstrated the proposed framework’s superior accuracy in diagnosing fetal arrhythmias. It is also crucial to note that further external testing is essential to assess the model’s generalizability and clinical value.