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Ensuring optimal infant nutrition is crucial for the health and development of children. Many infants aged 0–6 months are fed with infant formula rather than breast milk. Research on cancer cell lines and animal models is limited to examining the nutrition effects of formula and breast milk, as it does not comprehensively consider absorption, metabolism, and the health and social determinants of the infant and its physiology. Our study utilized small intestine organoids induced from human embryo stem cell (ESC) to compare the nutritional effects of breast milk from five donors during their postpartum lactation period of 1–6 months and three types of Stage 1 infant formulae from regular retail stores. Using transcriptomics and untargeted metabolomics approaches, we focused on the differences such as cell growth and development, cell junctions, and extracellular matrix. We also analyzed the roles of pathways including AMPK, Hippo, and Wnt, and identified key genes such as ALPI, SMAD3, TJP1, and WWTR1 for small intestine development. Through observational and in-vitro analysis, our study demonstrates ESC-derived organoids might be a promising model for exploring nutritional effects and underlying mechanisms. [ABSTRACT FROM AUTHOR]

Underwater optics have seen a notable surge of interest in recent years, emerging as a critical medium for conveying information crucial to underwater resource exploration, autonomous underwater vehicle navigation, etc. The intricate dynamics of underwater optical transmission, influenced by factors such as the absorption by the water and scattering by multiple particles, present considerable challenges. One of the most critical issues is that the optical information representation methods fail to take into account the impact of the underwater physical environment. We conducted a comprehensive review and analysis of recent advancements in underwater optical transmission laws and models. We summarized and analyzed relevant research on the effects of underwater particles and turbulence on light and analyzed the polarization effects in various environments. Then, the roles of various types of underwater optical propagation models were analyzed. Although optical models in complex environments are still mostly based on Monte Carlo methods, many underwater optical propagation mechanisms have been revealed and can promote the impacts of optical information expression. We delved into the cutting-edge research findings across three key domains: the enhancement of underwater optical image quality, the 3D reconstruction from monocular images, and the underwater wireless optical communication, examining the pivotal role played by light transmission laws and models in these areas. Drawing upon our extensive experience in underwater optics, including underwater optical sensor development and experiments, we identified and underscored future directions in this field. We advocate for the necessity of further advancements in the comprehension of underwater optical laws and physical models, emphasizing the importance of their expanded application in underwater optical information representations. Deeper exploration into these areas is not only warranted but essential for pushing the boundaries of current underwater optical technologies and unlocking new potential for their application in underwater optical sensor developments, underwater exploration, environmental monitoring, and beyond. [ABSTRACT FROM AUTHOR]

c‐Fos, a member of the immediate early gene, serves as a widely used marker of neuronal activation induced by various types of brain damage. In addition, c‐Fos is believed to play a regulatory role in DNA damage repair. This paper reviews the literature on c‐Fos' involvement in the regulation of DNA damage repair and indicates that genes of the Fos family can be induced by various forms of DNA damage. In addition, cells lacking c‐Fos have difficulties in DNA repair. c‐Fos is involved in tumorigenesis and progression as a proto‐oncogene that maintains cancer cell survival, which may also be related to DNA repair. c‐Fos may impact the repair of DNA damage by regulating the expression of downstream proteins, including ATR, ERCC1, XPF, and others. Nonetheless, the underlying mechanisms necessitate further exploration. [ABSTRACT FROM AUTHOR]

To overcome the challenges of inadequate representation and ineffective information exchange stemming from feature homogenization in underwater acoustic target recognition, we introduce a hybrid network named Mobile_ViT, which synergizes MobileNet and Transformer architectures. The network begins with a convolutional backbone incorporating an embedded coordinate attention mechanism to enhance the local details of inputs. This mechanism captures the long-term temporal dependencies and precise frequency–domain relationships of signals, focusing the features on the time–frequency positions. Subsequently, the Transformer's Encoder is integrated at the end of the backbone to facilitate global characterization, thus effectively overcoming the convolutional neural network's shortcomings in capturing long-range feature dependencies. Evaluation on the Shipsear and DeepShip datasets yields accuracies of 98.50% and 94.57%, respectively, marking a substantial improvement over the baseline. Notably, the proposed method also demonstrates obvious separation coefficients, signifying enhanced clustering effectiveness, and is lighter than other Transformers. [ABSTRACT FROM AUTHOR]

A stochastic nonlinear ray propagation model is proposed to carry out an exploration of the nonlinear ray theory in underwater signal propagation. The recurrence plot method is proposed to quantify the ray chaos and stochastics to optimize the model. Based on this method, the distribution function of the control parameter δ is derived. Experiments and simulations indicate that this stochastic nonlinear ray propagation model provides a good explanation and description on the stochastic frequency shift in underwater signal propagation.

Underwater target detection using optical images is a challenging yet promising area that has witnessed significant progress. However, fuzzy distortions and irregular light absorption in the underwater environment often lead to image blur and color bias, particularly for small targets. Consequently, existing methods have yet to yield satisfactory results. To address this issue, we propose the Underwater-YCC optimization algorithm based on You Only Look Once (YOLO) v7 to enhance the accuracy of detecting small targets underwater. Our algorithm utilizes the Convolutional Block Attention Module (CBAM) to obtain fine-grained semantic information by selecting an optimal position through multiple experiments. Furthermore, we employ the Conv2Former as the Neck component of the network for underwater blurred images. Finally, we apply the Wise-IoU, which is effective in improving detection accuracy by assigning multiple weights between high- and low-quality images. Our experiments on the URPC2020 dataset demonstrate that the Underwater-YCC algorithm achieves a mean Average Precision (mAP) of up to 87.16% in complex underwater environments. [ABSTRACT FROM AUTHOR]

Protein kinases constitute a rich pool of biomarkers and therapeutic targets of tremendous diseases including cancer. However, sensing kinase activity in vivo while implementing treatments according to kinase hyperactivation remains challenging. Herein, we present a nanomediator–effector cascade system that can in situ magnify the subtle events of kinase‐catalyzed phosphorylation via DNA amplification machinery to achieve kinase activity imaging and kinase‐responsive drug release in vivo. In this cascade, the phosphorylation‐mediated disassembly of DNA/peptide complex on the nanomediators initiated the detachment of fluorescent hairpin DNAs from the nanoeffectors via hybridization chain reaction (HCR), leading to fluorescence recovery and therapeutic cargo release. We demonstrated that this nanosystem simultaneously enabled trace protein kinase A (PKA) activity imaging and on‐demand drug delivery for inhibition of tumor cell growth both in vitro and in vivo, affording a kinase‐specific sense‐and‐treat paradigm for cancer theranostics. [ABSTRACT FROM AUTHOR]

Dynamically monitoring intracellular glutathione (GSH), a crucial biomarker of oxidative stress, is of significance for the diagnosis and treatment of certain diseases. Although manganese dioxide (MnO2) based GSH fluorescent sensors have exhibited high sensitivity and good selectivity owing to the specific reactivity between GSH and MnO2, near-infrared (NIR) MnO2 based nanoprobes for GSH detection are scarce. Herein, we have developed a NIR activatable fluorescence nanoprobe for the imaging and determination of intracellular GSH based on a core–shell nanoparticle, consisting of NIR emitted gold nanocluster doped silica as the fluorescent core and manganese dioxide as the GSH-responsive shell (named AuNCs@MnO2). Due to the absorption competition mechanism, the outer MnO2 shell rather than the inner AuNCs core preferentially absorbed the excitation light, thus leading to fluorescence quenching of the inner AuNCs core. Upon addition of GSH, the fluorescence of the nanoprobe restored along with the reduction of MnO2 to Mn2+ because of the absorption competition disappearance-induced emission. The activatable fluorescence linearly increased upon changing the GSH concentration in the range of 2 to 5000 μM with a detection limit of 0.67 μM. The cytotoxicity test shows that the AuNCs@MnO2 nanoprobes have a good biocompatibility. After entering the cancer cells, the intracellular GSH degraded the outermost MnO2 shell and initiated the NIR fluorescence restoration of AuNCs, which can be used to monitor the dynamic change of intracellular GSH. This strategy provides an NIR-activatable way to detect GSH levels in living cells and offers a promising platform for the diagnosis and treatment of GSH-related diseases. [ABSTRACT FROM AUTHOR]

At present, most of the seismic data denoising methods based on deep learning attempt to establish a synthetic seismic data set as the network training set to train network parameters. However, the synthetic data set cannot completely reflect the structural characteristics of the field seismic data, resulting in some false seismic reflections in field denoised results. For this reason, this article proposes an attribute-based denoising algorithm for seismic data called attribute-based double constraint denoising network (Att-DCDN). This method applies encoder–decoder and attribute classifier to constitute the generative adversarial network (GAN) and attenuates seismic noise by controlling with/without target attributes (noise attribute and signal attribute). Compared with the noise-free field seismic data, attribute vectors of the field data are easier to obtain. Therefore, our training set includes not only the synthetic seismic data but also the field seismic data, so as to reduce accuracy requirement of the synthetic noise-free data. In addition, we propose a double-constraint training way to reduce the losses of effective reflections during the denoising process. Specifically, we consider both noise attenuation and signal retention, i.e., reconstruction loss and residual loss are introduced to constrain recovery of effective reflections, and attribute classification loss and adversarial loss are applied to constrain the attenuation of seismic noise. Both the experimental results of synthetic and field seismic records show that our algorithm can effectively suppress the seismic noise and recover the effective reflections almost completely, even the weak signal areas that are seriously polluted by the seismic noise. [ABSTRACT FROM AUTHOR]

Fractional Fourier transform (FrFT) is a useful tool to detect linear frequency modulated (LFM) signal. However, the detection performance of the FrFT-based method will deteriorate drastically in underwater multi-path environment. This paper proposes a novel method based on time-reversal and fractional Fourier transform (TR-FrFT) to solve this problem. We make use of the focusing ability of time-reversal to mitigate the influence of multi-path, and then improve the detection performance of FrFT. Simulated results show that, compared to FrFT, the difference between peak value and maximum pseudo-peak value of the signal processed by TR-FrFT is improved by 8.75 dB. Lake experiments results indicate that, the difference between peak value and maximum pseudo-peak value of the signal processed by TR-FrFT is improved by 7.6 dB. The detection performance curves of FrFT and TR-FrFT detectors with simulated data and lake experiments data verify the effectiveness of proposed method. [ABSTRACT FROM AUTHOR]

The convolutional neural network (CNN) has achieved excellent performance in many fields, which has attracted much attention. CNN is a kind of feedforward neural network with convolution computation and depth structure. In this letter, aiming at the intense interference of seismic exploration noise in the desert of China, a desert seismic noise reduction system based on deep residual encoder–decoder network is proposed. In order to extract the characteristics and variation law of desert seismic noise, a noise set containing a large number of desert seismic noise is utilized for training the network so that the network forms the end-to-end mapping between the noisy records and the noise. Consequently, the effective signals are obtained by subtracting noise from the noisy records so as to achieve a satisfactory denoising performance. Compared with the traditional random noise suppression methods, the advantages of the proposed method are fully demonstrated in the processing of the synthetic records and the field records. Especially when the signal-to-noise ratio (SNR) is very low, this proposed method can still have a very good denoising effect. [ABSTRACT FROM AUTHOR]

In this paper, temperature and pH‐sensitive interpenetrating polymer network (IPN) nanogels (NGs) were firstly prepared, and magnetic hybrid NGs were made through in‐situ precipitation of Fe2+ and Fe3+ into the IPN NGs. Under the optimized condition, the resulting hybrid NG dispersion with up to 17.3 wt% magnetite was stable, while the size distribution of the NGs is broad due to the formation of Fe3O4 nanoparticles outside the NGs. In order to synthesize relatively uniform magnetic NGs, magnetite content was reduced to 8.1 wt% magnetite. The NGs with 8.1 wt% magnetite can quickly self‐assemble into colloidal crystals induced by magnet, while such NGs slowly self‐assembled into colloidal crystals without external magnetic field. Furthermore, the reflection wavelength of the self‐assembled magnetic NGs showed red‐shift with increasing pH and temperature. [ABSTRACT FROM AUTHOR]

Aiming at improving the accuracy of pulse ranging measurement in underwater multi-path environment, this paper proposes a novel pulse ranging algorithm based on active virtual time reversal (AVTR). By using the focusing characteristics of AVTR, the received signal can be focused at the receiving end, which eliminates the negative influence of multiple pseudo-peaks. In order to extract the received signal, we propose an energy-based adaptive windowed method which preserves the signal focus peak while truncates the side peak component. Numerical simulations are provided and outfield experiments are conducted. The results demonstrate the effectiveness of the proposed method comparing with correlation-based method. [ABSTRACT FROM AUTHOR]

Fluorescent silicon nanodots have shown great prospects for bioimaging and biosensing applications. Although various fluorescent silicon-containing nanodots (SiNDs) have been developed, there are few reports about renal-clearable multicolor SiNDs. Herein, renal-clearable multicolor fluorescent SiNDs are synthesized by using silane molecules and organic dyes through a facile one-step hydrothermal method. The fluorescence of the resulting SiNDs can be tuned to blue (bSiNDs), green (gSiNDs), and red (rSiNDs) by simply changing the categories of silane reagents or dye molecules. The as-prepared SiNDs exhibit strong fluorescence with a quantum yield up to 72%, excellent photostability, and good biocompatibility with 12 h renal clearance rate as high as 86% ID. These properties enabled the SiNDs for tumor fluorescence imaging and H 2 O 2 imaging in living cells and tissue through in situ reduction reaction-lighted fluorescence of the nanoprobe. Our results provide an invaluable methodology for the synthesis of renal-clearable multicolor SiNDs and their potential applications for fluorescence imaging and biomarker sensing. These SiNDs are also promising for various biological and biomedical applications.

Protein kinases constitute a rich pool of biomarkers and therapeutic targets of tremendous diseases including cancer. However, sensing kinase activity in vivo while implementing treatments according to kinase hyperactivation remains challenging. Herein, we present a nanomediator-effector cascade system that can in situ magnify the subtle events of kinase-catalyzed phosphorylation via DNA amplification machinery to achieve kinase activity imaging and kinase-responsive drug release in vivo. In this cascade, the phosphorylation-mediated disassembly of DNA/peptide complex on the nanomediators initiated the detachment of fluorescent hairpin DNAs from the nanoeffectors via hybridization chain reaction (HCR), leading to fluorescence recovery and therapeutic cargo release. We demonstrated that this nanosystem simultaneously enabled trace protein kinase A (PKA) activity imaging and on-demand drug delivery for inhibition of tumor cell growth both in vitro and in vivo, affording a kinase-specific sense-and-treat paradigm for cancer theranostics., (© 2021 Wiley-VCH GmbH.)

Dynamically monitoring intracellular glutathione (GSH), a crucial biomarker of oxidative stress, is of significance for the diagnosis and treatment of certain diseases. Although manganese dioxide (MnO2) based GSH fluorescent sensors have exhibited high sensitivity and good selectivity owing to the specific reactivity between GSH and MnO2, near-infrared (NIR) MnO2 based nanoprobes for GSH detection are scarce. Herein, we have developed a NIR activatable fluorescence nanoprobe for the imaging and determination of intracellular GSH based on a core-shell nanoparticle, consisting of NIR emitted gold nanocluster doped silica as the fluorescent core and manganese dioxide as the GSH-responsive shell (named AuNCs@MnO2). Due to the absorption competition mechanism, the outer MnO2 shell rather than the inner AuNCs core preferentially absorbed the excitation light, thus leading to fluorescence quenching of the inner AuNCs core. Upon addition of GSH, the fluorescence of the nanoprobe restored along with the reduction of MnO2 to Mn2+ because of the absorption competition disappearance-induced emission. The activatable fluorescence linearly increased upon changing the GSH concentration in the range of 2 to 5000 μM with a detection limit of 0.67 μM. The cytotoxicity test shows that the AuNCs@MnO2 nanoprobes have a good biocompatibility. After entering the cancer cells, the intracellular GSH degraded the outermost MnO2 shell and initiated the NIR fluorescence restoration of AuNCs, which can be used to monitor the dynamic change of intracellular GSH. This strategy provides an NIR-activatable way to detect GSH levels in living cells and offers a promising platform for the diagnosis and treatment of GSH-related diseases.