Automated extraction of Tridacna shell growth patterns via machine learning for enhanced paleoclimate/paleoweather research.

Tridacna spp. are valuable archives for paleoclimate and paleoweather research due to their distinct daily growth patterns and the sensitivity of the daily growth patterns to environment changes. However, manually identifying daily growth lines and measuring the daily growth increment width (DGIW) of Tridacna shells from Laser Scanning Confocal Microscopy (LSCM) images is a tedious task that has become a significant barrier to Tridacna studies. This paper addresses this challenge by integrating machine learning into Tridacna research for the first time to automate the calculation of the number of daily growth lines and DGIW of Tridacna shells. Specifically, we propose an unsupervised generative adversarial attention network called TriGAN to automatically recognize distinct daily growth lines of Tridacna shells from LSCM images. Utilizing modern Tridacna specimens collected from the South China Sea, our experimental results demonstrate that TriGAN can effectively reconstruct the ambiguous and blurred regions in LSCM images and produce higher quality images of daily growth patterns compared to existing image generation networks. Furthermore, the daily growth line number and DGIW of Tridacna shells can be counted automatically from the images recognized by TriGAN, which are in good agreement with the statistical results obtained manually from the original LSCM images (R = 0.7, p < 0.01 for the DGIW profile of T. gigas specimen MD1 and R = 0.6, p < 0.01 for T. derasa specimen XB10). This automated method provides an efficient solution for researching the laminar chronology of Tridacna.

Multi-task learning for segmentation and classification of breast tumors from ultrasound images.

Segmentation and classification of breast tumors are critical components of breast ultrasound (BUS) computer-aided diagnosis (CAD), which significantly improves the diagnostic accuracy of breast cancer. However, the characteristics of tumor regions in BUS images, such as non-uniform intensity distributions, ambiguous or missing boundaries, and varying tumor shapes and sizes, pose significant challenges to automated segmentation and classification solutions. Many previous studies have proposed multi-task learning methods to jointly tackle tumor segmentation and classification by sharing the features extracted by the encoder. Unfortunately, this often introduces redundant or misleading information, which hinders effective feature exploitation and adversely affects performance. To address this issue, we present ACSNet, a novel multi-task learning network designed to optimize tumor segmentation and classification in BUS images. The segmentation network incorporates a novel gate unit to allow optimal transfer of valuable contextual information from the encoder to the decoder. In addition, we develop the Deformable Spatial Attention Module (DSAModule) to improve segmentation accuracy by overcoming the limitations of conventional convolution in dealing with morphological variations of tumors. In the classification branch, multi-scale feature extraction and channel attention mechanisms are integrated to discriminate between benign and malignant breast tumors. Experiments on two publicly available BUS datasets demonstrate that ACSNet not only outperforms mainstream multi-task learning methods for both breast tumor segmentation and classification tasks, but also achieves state-of-the-art results for BUS tumor segmentation. Code and models are available at https://github.com/qqhe-frank/BUS-segmentation-and-classification.git.

HCTNet: A hybrid CNN-transformer network for breast ultrasound image segmentation.

Automatic breast ultrasound image segmentation helps radiologists to improve the accuracy of breast cancer diagnosis. In recent years, the convolutional neural networks (CNNs) have achieved great success in medical image analysis. However, it exhibits limitations in modeling long-range relations, which is unfavorable for ultrasound images with speckle noise and shadows, resulting in decreased accuracy of breast lesion segmentation. Transformer can obtain sufficient global information, but it is deficient in acquiring local details and needs to be pre-trained on large-scale datasets. In this paper, we propose a Hybrid CNN-Transformer network (HCTNet) for boosting the breast lesion segmentation in ultrasound images. In the encoder of HCTNet, Transformer Encoder Blocks (TEBlocks) are designed to learn the global contextual information, which are combined with CNNs to extract features. In the decoder of HCTNet, a Spatial-wise Cross Attention (SCA) module is developed based on the spatial attention mechanism, which reduces the semantic discrepancy with the encoder. Moreover, residual connection is used between decoder blocks to make the generated features more discriminative by aggregating contextual feature maps at different semantic scales. Extensive experiments on three public breast ultrasound datasets demonstrate that HCTNet outperforms other medical image segmentation methods and the recent semantic segmentation methods on breast ultrasound lesion segmentation.

Reunderstanding the Reaction Mechanism of Aqueous Zn-Mn Batteries with Sulfate Electrolytes: Role of the Zinc Sulfate Hydroxide.

Rechargeable aqueous Zn-Mn batteries have garnered extensive attention for next-generation high-safety energy storage. However, the charge-storage chemistry of Zn-Mn batteries remains controversial. Prevailing mechanisms include conversion reaction and cation (de)intercalation in mild acid or neutral electrolytes, and a MnO2 /Mn2+ dissolution-deposition reaction in strong acidic electrolytes. Herein, a Zn4 SO4 ·(OH)6 ·xH2 O (ZSH)-assisted deposition-dissolution model is proposed to elucidate the reaction mechanism and capacity origin in Zn-Mn batteries based on mild acidic sulfate electrolytes. In this new model, the reversible capacity originates from a reversible conversion reaction between ZSH and Znx MnO(OH)2 nanosheets in which the MnO2 initiates the formation of ZSH but contributes negligibly to the apparent capacity. The role of ZSH in this new model is confirmed by a series of operando characterizations and by constructing Zn batteries using other cathode materials (including ZSH, ZnO, MgO, and CaO). This research may refresh the understanding of the most promising Zn-Mn batteries and guide the design of high-capacity aqueous Zn batteries.

Circular RNA SOX13 promotes malignant behavior and cisplatin resistance in non-small cell lung cancer through targeting microRNA-3194-3p/microtubule-associated protein RP/EB family member 1.

Circular RNA (circRNA) presents an essential regulatory role in affecting the occurrence and acquired resistance in non-small cell lung cancer (NSCLC), but how circSOX13 impacts NSCLC is unclear. In this work it was found that compared with adjacent normal tissues, circSOX13 and the microtubule-associated protein RP/EB family member 1 (MAPRE1) were signally up-regulated in NSCLC while miR-3194-3p was signally lowered. Pulmonary function tests (PETs) revealed that knocking down circSOX13 or overexpressing miR-3194-3p inhibited NSCLC proliferation, invasion and migration but promoted its apoptosis. The promoting effect of overexpressing circSOX13 on NSCLC was reversed via knocking down MAPRE1. Additionally, knocking down circSOX13 reduced cisplatin resistance in NSCLC. Furthermore, circSOX13 mediated MAPRE1 expression via competitively binding miR-3194-3p to exert its tumorigenic impact. To conclude, this work clarified the carcinogenic impact of circSOX13-miR-3194-3p-MAPRE1 axis on NSCLC and DDP resistance. CircSOX13 can be a potential diagnostic marker and therapeutic target for NSCLC, thus providing a new insight for clinically reversing its acquired resistance.

Design of an amperometric glucose oxidase biosensor with added protective and adhesion layers.

Enzymes have demonstrated great potential in the development of advanced electroanalysis devices due to their unique recognition and catalytic properties. However, unsatisfactory stability and limited electron communication of traditional enzyme sensors seriously hinder their large-scale application. In this work, a simple and effective method is proposed to improve the stability of enzyme sensors by using sodium hyaluronate (SH) as a protective film, MXene-Ti3C2/Glucose oxidase (GOD) as the reaction layer, and chitosan (CS) /reduced graphene oxide (rGO) as the adhesion layer. Results demonstrate that the repeatability of the designed sensor increased by 73.3% after improving the adhesion between the reaction layer and the current collector and that its response ability was greatly enhanced. Moreover, the long-term stability of the electrode surface with SH protective film proved to be superior than that without protective film, which suggests that this design can effectively improve the overall performance of the enzyme biosensor. This work proposed a multi-tier synergistic approach for improving the reliability of enzyme sensors. Graphical abstract Our proposed protective and adhesion layer can greatly improve the stability of enzyme sensor and realize the rapid detection of glucose in serum sample.

Self-Template Synthesis of Prussian Blue Analogue Hollow Polyhedrons as Superior Sodium Storage Cathodes.

Prussian blue and its analogues with three-dimensional frame structures have been shown to be of great importance in the research and development of sodium-ion batteries (SIBs). Herein, we develop a simple and convenient self-template method to prepare a hollow-structured Prussian blue analogue (CoFe-PBA). This structure is conducive to buffer the volume changes during ion extraction and insertion processes and shorten the ion diffusion path. When further building a thin polydopamine (PDA) coating, the synthesized CoFe-PBA@PDA exhibits a high discharge capacity of 123.1 mAh g-1 at 0.1 A g-1 with a capacity retention of 71.5% after 500 cycles. Moreover, the capacity retention of CoFe-PBA@PDA after 100 cycles is 14.3% higher than that of the two comparison samples. In addition, the reversible structure of CoFe-PBA@PDA without forming a new phase was verified by in situ X-ray diffraction. This work may provide another design idea or strategy for improving the stability of the PBA cathodes used in SIBs.

Low-Density Lipoprotein Cholesterol 4: The Notable Risk Factor of Coronary Artery Disease Development.

Background: Coronary artery disease (CAD) is the leading cause of death worldwide, which has a long asymptomatic period of atherosclerosis. Thus, it is crucial to develop efficient strategies or biomarkers to assess the risk of CAD in asymptomatic individuals. Methods: A total of 356 consecutive CAD patients and 164 non-CAD controls diagnosed using coronary angiography were recruited. Blood lipids, other baseline characteristics, and clinical information were investigated in this study. In addition, low-density lipoprotein cholesterol (LDL-C) subfractions were classified and quantified using the Lipoprint system. Based on these data, we performed comprehensive analyses to investigate the risk factors for CAD development and to predict CAD risk. Results: Triglyceride, LDLC-3, LDLC-4, LDLC-5, LDLC-6, and total small and dense LDL-C were significantly higher in the CAD patients than those in the controls, whereas LDLC-1 and high-density lipoprotein cholesterol (HDL-C) had significantly lower levels in the CAD patients. Logistic regression analysis identified male [odds ratio (OR) = 2.875, P < 0.001], older age (OR = 1.018, P = 0.025), BMI (OR = 1.157, P < 0.001), smoking (OR = 4.554, P < 0.001), drinking (OR = 2.128, P < 0.016), hypertension (OR = 4.453, P < 0.001), and diabetes mellitus (OR = 8.776, P < 0.001) as clinical risk factors for CAD development. Among blood lipids, LDLC-3 (OR = 1.565, P < 0.001), LDLC-4 (OR = 3.566, P < 0.001), and LDLC-5 (OR = 6.866, P < 0.001) were identified as risk factors. To predict CAD risk, six machine learning models were constructed. The XGboost model showed the highest AUC score (0.945121), which could distinguish CAD patients from the controls with a high accuracy. LDLC-4 played the most important role in model construction. Conclusions: The established models showed good performance for CAD risk prediction, which can help screen high-risk CAD patients in asymptomatic population, so that further examination and prevention treatment might be taken before any sudden or serious event.

Salvianolic acid A blocks vasculogenic mimicry formation in human non-small cell lung cancer via PI3K/Akt/mTOR signalling.

Vasculogenic mimicry (VM) is associated with aggressive cancer cells. Salvianolic acid A (Sal-A), an antioxidant and anti-inflammatory agent, has bioactive properties from Salvia miltiorrhiza Bunge. Current investigation aspired to explore the activity of Sal-A in the VM formation of non-small cell lung cancer (NSCLC) and the mechanism underling this function. The CCK8, the scratch and boyden chemotaxis assay were presented to describe NSCLC cells viability, migration and invasion capabilities, respectively. The protein expression was verified by western blotting. In this report, Sal-A caused a reduction in viability, metastasis and capillaries structure formation of NSCLC cells. Additionally, Sal-A markedly prevented the key VM related proteins, containing EphA2, VE-cadherin and MMP2. Besides, Sal-A significantly diminished p-PI3K, p-Akt and p-mTOR level in NSCLC cells. More importantly, SC79 pretreatment reversed Sal-A inhibits NSCLC cells viability, metastasis and VM formation. These data exhibit that Sal-A could block VM network formation in NSCLC cells through modulating the PI3K/Akt/mTOR signalling pathway.

LncRNA MIR210HG Facilitates Non-Small Cell Lung Cancer Progression Through Directly Regulation of miR-874/STAT3 Axis.

BACKGROUND: Long noncoding RNAs are involved in the progression of multiple cancers. However, the expression and mechanism of microRNA (miR)210HG in non-small cell lung cancer (NSCLC) remain unclear. METHODS: The levels of miR210HG and miR-874 were measured by quantitative real-time polymerase chain reaction in NSCLC tissue samples and cells. Non-small cell lung cancer cell proliferation, migration, and invasion were measured by Cell Counting Kit-8 and transwell assays. Luciferase analysis confirmed the interaction between miR210HG and miR-874. RESULTS: Here, our data showed that miR210HG was overexpressed in NSCLC tissue samples and cells. In vitro functional assays showed that silencing miR210HG blocked NSCLC cell proliferation, migration, and invasion while promoting NSCLC cell radiosensitivity and chemoresistance. Mechanistically, miR-874 was directly regulated by miR210HG. Furthermore, miR-874 expression was reduced in NSCLC tissues and cells. The miR-874 mimic could mitigate the promoting effect of miR210HG on NSCLC cell progression. The data also showed that miR210HG promoted NSCLC cell progression through miR-181a expression by targeting STAT3. CONCLUSIONS: Our observations suggest that miR210HG is associated with NSCLC cell progression by regulating the miR-874/STAT3 axis.

Pulsed electromagnetic fields modify the adverse effects of glucocorticoids on bone architecture, bone strength and porous implant osseointegration by rescuing bone-anabolic actions.

Long-term glucocorticoid therapy is known to induce increased bone fragility and impaired skeletal regeneration potential. Growing evidence suggests that pulsed electromagnetic fields (PEMF) can accelerate fracture healing and increase bone mass both experimentally and clinically. However, how glucocorticoid-treated bone and bone cells respond to PEMF stimulation remains poorly understood. Here we tested the effects of PEMF on bone quantity/quality, bone metabolism, and porous implant osseointegration in rabbits treated with dexamethasone (0.5 mg/kg/day, 6 weeks). The micro-CT, histologic and nanoindentation results showed that PEMF ameliorated the glucocorticoid-mediated deterioration of cancellous and cortical bone architecture and intrinsic material properties. Utilizing the new porous titanium implant (Ti2448) with low toxicity and low elastic modulus, we found that PEMF stimulated bone ingrowth into the pores of implants and enhanced peri-implant bone material quality during osseous defect repair in glucocorticoid-treated rabbits. Dynamic histomorphometric results revealed that PEMF reversed the adverse effects of glucocorticoids on bone formation, which was confirmed by increased circulating osteocalcin and P1NP. PEMF also significantly attenuated osteocyte apoptosis, promoted osteoblast-related osteocalcin, Runx2 and Osx expression, and inhibited osteocyte-specific DKK1 and Sost expression (negative regulators of osteoblasts) in glucocorticoid-treated skeletons, revealing improved functional activities of osteoblasts and osteocytes. Nevertheless, PEMF exerted no effect on circulating bone-resorbing cytokines (serum TRAcP5b and CTX-1) or skeletal gene expression of osteoclast-specific markers (TRAP and cathepsin K). PEMF also significantly upregulated skeletal gene expression of canonical Wnt ligands (Wnt1, Wnt3a and Wnt10b), whereas PEMF did not alter non-canonical Wnt5a expression. This study demonstrates that PEMF treatment improves bone mass, strength and porous implant osseointegration in glucocorticoid-treated rabbits by promoting potent bone-anabolic action, which is associated with canonical Wnt-mediated improvement in osteoblast and osteocyte functions. This study provides a new treatment alternative for glucocorticoid-related bone disorders in a convenient and non-invasive manner.

Long noncoding RNA LINC-PINT inhibits non-small cell lung cancer progression through sponging miR-218-5p/PDCD4.

Long noncoding RNA, long intergenic non-protein-coding RNA p53-induced transcript (LINC-PINT) was showed to be involved in cancer development. However, the biological effect of LINC-PINT on non-small cell lung cancer (NSCLC) remains unknown. Here, we aimed to investigate the role and underlying mechanism of LINC-PINT in NSCLC. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to measure the level of LINC-PINT in NSCLC tissues and cell lines. Cell counting kit-8 (CCK-8), flow cytometry, migration and transwell invasion assays were used to investigate cell proliferation, cell cycle, cell migration and invasion, respectively. The targets of LINC-PINT were verified by both luciferase reporter assay and RNA immunoprecipitation assay. Tumour xenografts were used to reveal the effect of LINC-PINT on tumourigenesis in vivo. We observed that LINC-PINT expression increased in both NSCLC tissues and cell lines. Function assays exhibited that LINC-PINT reduced NSCLC cell proliferation, cell cycle, cell migration and invasion in vitro. We also indicated that LINC-PINT mediated inhibitory effect on cell proliferation, cell cycle, cell migration and invasion by miR-208a-3p/programmed cell death 4 (PDCD4) in NSCLC cells. These findings indicated that LINC-PINT functions as a tumour-suppressor that exerts important regulatory roles in NSCLC progression by sponging miR-208a-3p/PDCD4.