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The influence of inclusions corrosion behavior under multi-factor local corrosion mechanisms was researched by SKPFM, TOF-SIMS, EBSD, and in-situ corrosion tests. The model of the local corrosion behavior of CaO/CaS–MgO–Al2O3 inclusion under the multifactor mechanism was established. The structural defect area at the boundary of the inclusions acted as the anodic phase where corrosion occurs preferentially, and the CaS of the inclusion underwent a chemical dissolution process. TiN, TiS2 and TiO2 were gradually shed, and the MgO, Al2O3 and CaO inside the local corrosion area were not completely shed. The gap defect of inclusion was the preferred condition to induce local corrosion when the matrix contains galvanic corrosion effect, dislocation region and the gap defect, and the process of anodic dissolution occurred in the dislocation region. There was no gap defect, the environment could not completely provide the driving force for local corrosion, and the possibility of non-local corrosion existed. The existence of gap defect provided the condition for the existence of solution, and provided the double layer contribution of potential difference of inclusion/matrix and solution.

Abstract Corrosion jeopardizes the materials longevity and engineering safety, hence the corrosion rate needs to be forecasted so as to better guide materials selection. Although field exposure experiments are dependable, the prohibitive cost and their time-consuming nature make it difficult to obtain large dataset for machine learning. Here, we propose a strategy Integrating Ab-initio Calculations with Random Forest (IACRF) to optimize the model, thereby estimating the corrosion rate of Al alloys in diverse environments. Based on the thermodynamic assessment of the secondary phases, the ab-initio calculation quantities, especially the work function, significantly improved the prediction accuracy with respect to small-sample Al alloys corrosion dataset. To build a better generic prediction model, the most accessible and effective features are identified to train IACRF. Finally, the independent field exposure experiments in Southeast Asia have proven the generalization ability of IACRF in which the average prediction accuracy is improved up to 91%.

The catalytic partial oxidation of methane (CPOM) to methanol has been regarded as a promising approach for methane utilization, despite that the conversion remains a formidable challenge in the perspective of catalysts. A novel catalyst system of multi-wall carbon nanotubes (MWCNTs) that supported Fe2O3 with existing I2, consisting of non-noble metal and working in weak acid at an ambient temperature, was investigated for CPOM. MWCNTs supported the Fe2O3 catalyst, which was prepared by the impregnation method and characterized via HRTEM, XRD, XPS, FT-IR, and BET techniques. The characterization results reveal that, as a non-noble metal catalyst, the Fe2O3/MWCNTs catalyst had a good catalytic performance and stability in the CPOM. With the variation of reaction pressure and the dosage of Fe2O3/MWCNTs, the catalyst system obtained the highest methane conversion rate of 7.41% and methanol selectivity of 86.3%, which is analogous to that of the equivalently strong acid catalyst system. The I2-Fe2O3/MWCNTs catalyst system has great potential in the application of CPOM under mild, environmentally benign conditions, such as non-noble metal requirement, ambient temperature, and weak acid. The reaction mechanism was discussed.

Introns, as important vectors of biological functions, can influence many stages of mRNA metabolism. However, in recent research, post-spliced introns are rarely considered. In this study, the optimal matched regions between introns and their mRNAs in nine model organism genomes were investigated with improved Smith–Waterman local alignment software. Our results showed that the distributions of mRNA optimal matched frequencies were highly consistent or universal. There are optimal matched frequency peaks in the UTR regions, which are obvious, especially in the 3′-UTR. The matched frequencies are relatively low in the CDS regions of the mRNA. The distributions of the optimal matched frequencies around the functional sites are also remarkably changed. The centers of the GC content distributions for different sequences are different. The matched rate distributions are highly consistent and are located mainly between 60% and 80%. The most probable value of the optimal matched segments is about 20 bp for lower eukaryotes and 30 bp for higher eukaryotes. These results show that there are abundant functional units in the introns, and these functional units are correlated structurally with all kinds of sequences of mRNA. The interaction between the post-spliced introns and their corresponding mRNAs may play a key role in gene expression.

Abstract Background Sexually transmitted infections (STIs) are a serious public health problem worldwide. Patients with STIs have a high rate of psychosocial problems and may perceive unmet interpersonal needs, which is considered a proximal and sufficient cause of suicidal thoughts and behaviors. The present study examined the construct validity and psychometric properties of the 15-item Interpersonal Needs Questionnaire among patients with STIs in Shanghai, China. Methods We recruited 910 patients with STIs (438 males and 472 females; mean age = 38.72, standard deviation [SD] = 13.034) from the Shanghai Skin Disease Hospital using accidental sampling. Baseline descriptive statistics were calculated using R 4.0.0, and a latent variable model was developed using Mplus 7.4. Results The construct validity results supported a latent variable measurement model with three distinct but related constructs (thwarted belongingness, perceived burdensomeness, and social exclusion) (p

The use of metallographic images to predict the mechanical properties of materials and their corrosion behavior is helpful in achieving nondestructive detection and quality control. However, after a long-term attempt, the traditional methods cannot accurately correlate the mechanical properties and corrosion behavior of materials with the corresponding microstructure images. In this study, we propose a deep learning strategy to predict the mechanical property and corrosion behavior of large-scale extruded aluminum profiles using surface optical microstructure images. The proposed models with remarkable properties were established through experimental dataset collection, dataset preprocessing, deep learning network modification, and key parameter screening. Taking extruded Al-Zn-Mg alloys with different surface microstructures as example materials, 4,800 sets of “metallographic image – hardness (HV) – corrosion potential (Ecorr)” data were experimentally collected to establish the HV and Ecorr models with prediction accuracies of 90% and 82%, respectively. The proposed HV and Ecorr models exhibit great generalization ability with mean average errors of 1.8 HV and 7.0 mV on experimental validation sets, respectively. The proposed model can accurately correlate the metallographic images, mechanical property, and corrosion behavior, which can provide theoretical support for intelligent and nondestructive testing methods to further prevent unexpected material failure.

Abstract Background Breast cancer subtypes are statistically associated with prognosis. The search for markers of breast tumor heterogeneity and the development of precision medicine for patients are the current focuses of the field. Methods We used a bioinformatic approach to identify key disease-causing genes unique to the luminal A and basal-like subtypes of breast cancer. First, we retrieved gene expression data for luminal A breast cancer, basal-like breast cancer, and normal breast tissue samples from The Cancer Genome Atlas database. The differentially expressed genes unique to the 2 breast cancer subtypes were identified and subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. We constructed protein–protein interaction networks of the differentially expressed genes. Finally, we analyzed the key modules of the networks, which we combined with survival data to identify the unique cancer genes associated with each breast cancer subtype. Results We identified 1114 differentially expressed genes in luminal A breast cancer and 1042 differentially expressed genes in basal-like breast cancer, of which the subtypes shared 500. We observed 614 and 542 differentially expressed genes unique to luminal A and basal-like breast cancer, respectively. Through enrichment analyses, protein–protein interaction network analysis, and module mining, we identified 8 key differentially expressed genes unique to each subtype. Analysis of the gene expression data in the context of the survival data revealed that high expression of NMUR1 and NCAM1 in luminal A breast cancer statistically correlated with poor prognosis, whereas the low expression levels of CDC7, KIF18A, STIL, and CKS2 in basal-like breast cancer statistically correlated with poor prognosis. Conclusions NMUR1 and NCAM1 are novel key disease-causing genes for luminal A breast cancer, and STIL is a novel key disease-causing gene for basal-like breast cancer. These genes are potential targets for clinical treatment.

In this paper, we proposed a micro-getter unit with a square thin-film getter formed atop a thin-film heater for vacuum packaging of a Micro-Electro-Mechanical System (MEMS) device. This innovation through an integrated module unit can be fabricated by MEMS compatible processes and can be sealed together with a MEMS device by wafer level package technology sequentially. It has the advantage of locally and repeatedly activating the getter by supplying a DC power to the micro-thin-film heater. Two models have been studied comparatively in this work, in which a conventional solid structure (SS) model with a micro-heater directly above a silica glass substrate was used as a reference model for comparison with the newly designed innovative floating structure (FS) model with a micro-heater floating over a cavity in a silicon substrate. According to a finite element method simulation based on Fourier’s law of heat conduction, the FS model showed better thermal efficiency than the SS model during the activation process. For a square micron thin-film getter with a size as 1000 × 1000 × 5 µm3, a rather low input voltage as 2 V can raise the temperature of the getter up to 300 °C calculated by the FS Model, while the SS model requires a much higher input voltage as 18 V to reach the same temperature.

To achieve a wide range and high accuracy detection of the vacuum level, for example, in an encapsulated vacuum microcavity, a composite-type MEMS Pirani gauge has been designed and fabricated. The Pirani gauge consists of two gauges of different sizes connected in series, with one gauge having a larger heat-sensitive area and a larger air gap for extending the lower measurable limit of pressure (i.e., the high vacuum end) and the other gauge having a smaller heat-sensitive area and a smaller air gap for extending the upper measurable limit. The high-resistivity titanium metal was chosen as the thermistor; SiNx was chosen as the dielectric layer, considering the factors relevant to simulation and manufacturing. By simulation using COMSOL Multiphysics and NI Multisim, a range of measurement of 2 × 10−2 to 2 × 105 Pa and a sensitivity of 52.4 mV/lgPa were obtained in an N2 environment. The performance of the fabricated Pirani gauge was evaluated by using an in-house made vacuum test system. In the test, the actual points of measurement range from 6.6 × 10−2 to 1.12 × 105 Pa, and the highest sensitivity is up to 457.6 mV/lgPa. The experimental results are better in the range of measurement, sensitivity, and accuracy than the simulation results. The Pirani gauge proposed in this study is simple in structure, easy to manufacture, and suitable for integration with other MEMS devices in a microcavity to monitor the vacuum level therein.

A MEMS thin-film getter–heater unit has been previously proposed for the vacuum packaging of a Micro-Electro-Mechanical System (MEMS) device, where the floating structure (FS) design is found to be obviously more power-efficient than the solid structure (SS) one by heat transfer capacity simulation. However, the mechanical strength of the FS is weaker than the SS by nature. For high temperature usage, the unit structure must be optimized in order to avoid fracture of the cantilever beam or film delamination due to strong excessive stress caused by heating. In this paper, COMSOL is used to simulate the stress and deformation of the MEMS thin-film getter–heater unit with the cantilever structure. By comparing various cantilever structures, it is found that a model with a symmetrically-shaped heater and edge–center-located cantilever model (II-ECLC model) is the most suitable. In this model, even when the structure is heated to about 600 °C, the maximum stress of the cantilever beam is only 455 MPa, much lower than the tensile strength of silicon nitride (Si3N4, 12 GPa), and the maximum deformation displacement is about 200 μm. Meanwhile, the interfacial stress between the getter and the insulating layer is 44 MPa, sufficiently lower than the adhesion strength between silicon nitride film and titanium film (400–1850 MPa). It is further found that both the stress of the cantilever structure and the interfacial stress between the getter and the insulating layer beneath increase linearly with temperature; and the deformation of the cantilever structure is proportional to its stress. This work gives guidance on the design of MEMS devices with cantilever structures and works in high temperature situations.

In order to obtain high-quality through-silicon via (TSV) arrays for high voltage applications, we optimized the fabrication processes of the Si holes, evaluated the dielectric layers, carried out hole filling by Cu plating, and detected the final structure and electric properties of the TSVs. The Si through-hole array was fabricated in an 8-inch Si substrate as follows: First, a blind Si hole array was formed by the Si deep reactive etching (DRIE) technique using the Bosch process, but with the largest width of the top scallops reduced to 540 nm and the largest notch elimidiameternated by backside grinding, which also opens the bottom ends of the Si blind holes and forms 500-μm-deep Si through holes. Then, the sidewalls of the Si holes were further smoothed by a combination of thermal oxidation and wet etching of the thermal oxide. The insulating capability of the dielectric layers was evaluated prior to metal filling by using a test kit. The metal filling of the through holes was carried out by bottom-up Cu electroplating and followed by annealing at 300 °C for 1 h to release the electroplating stress and to prevent possible large metal thermal expansion in subsequent high-temperature processes. The TSV arrays with different hole diameters and spacing were detected: no visible defects or structure peeling was found by scanning electron microscopy (SEM) observations, and no detectable interdiffusion between Cu and the dielectric layers was detected by energy dispersive X-ray (EDX) analyses. Electric tests indicated that the leakage currents between two adjacent TSVs were as low as 6.80 × 10−10 A when a DC voltage was ramped up from 0 to 350 V, and 2.86 × 10−9 A after a DC voltage was kept at 100 V for 200 s.

We have designed a hot-plate-type micro-Pirani vacuum gauge with a simple structure and compatibility with conventional semiconductor fabrication processes. In the Pirani gauge, we used a vanadium oxide (VOx) membrane as the thermosensitive component, taking advantage of the high temperature coefficient of resistance (TCR) of VOx. The TCR value of VOx is −2%K−1∼−3%K−1, an order of magnitude higher than those of other thermal-sensitive materials, such as platinum and titanium (0.3%K−1∼0.4%K−1). On one hand, we used the high TCR of VOx to increase the Pirani sensitivity. On the other hand, we optimized the floating structure to decrease the thermal conductivity so that the detecting range of the Pirani gauge was extended on the low-pressure end. We carried out simulation experiments on the thermal zone of the Pirani gauge, the width of the cantilever beam, the material and thickness of the supporting layer, the thickness of the thermal layer (VOx), the depth of the cavity, and the shape and size. Finally, we decided on the basic size of the Pirani gauge. The prepared Pirani gauge has a thermal sensitive area of 130 × 130 μm2, with a cantilever width of 13 μm, cavity depth of 5 μm, supporting layer thickness of 300 nm, and VOx layer thickness of 110 nm. It has a dynamic range of 10−1~104 Pa and a sensitivity of 1.23 V/lgPa. The VOx Pirani was designed using a structure and fabrication process compatible with a VOx-based uncooled infrared microbolometer so that it can be integrated by wafer level. This work contains only our MEMS Pirani gauge device design, preparation process design, and readout circuit design, while the characterization and relevant experimental results will be reported in the future.

In this study, a kind of crabapple vinegar was developed by the method of mixed bacteria fermentation. It showed that the total acids and total esters in the vinegar increased by 30.51% and 22.67%, respectively. Simultaneously, ultrasound was used to treat the vinegar to shorten the time of aging. In addition, the HS-SPME-GC-MS results show that some volatile components had increased significantly, such as total esters, aldehydes and heterocycles. Combining OAV with radar chart of aroma active ingredients, the order of contribution to the characteristic aroma of crabapple vinegar was esters > alcohols > others > acids. Finally, ultrasonic cavitation and hydroxyl radicals were measured to further prove it could accelerate chemical reaction of crabapple vinegar. The results of FTIR showed that the hydrogen-bonded molecules had increased, while free molecules with irritating taste (such as ethanol and acetic acid) had decreased, which made the taste of crabapple vinegar softer. Results have showed that ultrasound is a promising technique for shortening aging time and it also provides the possibility to improve the taste of fruit vinegar.

Human epidermal growth factor 2 (HER2)+ breast cancer is considered the most dangerous type of breast cancers. Herein, we used bioinformatics methods to identify potential key genes in HER2+ breast cancer to enable its diagnosis, treatment, and prognosis prediction. Datasets of HER2+ breast cancer and normal tissue samples retrieved from Gene Expression Omnibus and The Cancer Genome Atlas databases were subjected to analysis for differentially expressed genes using R software. The identified differentially expressed genes were subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses followed by construction of protein-protein interaction networks using the STRING database to identify key genes. The genes were further validated via survival and differential gene expression analyses. We identified 97 upregulated and 106 downregulated genes that were primarily associated with processes such as mitosis, protein kinase activity, cell cycle, and the p53 signaling pathway. Visualization of the protein-protein interaction network identified 10 key genes ( CCNA2 , CDK1 , CDC20 , CCNB1 , DLGAP5 , AURKA , BUB1B , RRM2 , TPX2 , and MAD2L1 ), all of which were upregulated. Survival analysis using PROGgeneV2 showed that CDC20 , CCNA2 , DLGAP5 , RRM2 , and TPX2 are prognosis-related key genes in HER2+ breast cancer. A nomogram showed that high expression of RRM2 , DLGAP5 , and TPX2 was positively associated with the risk of death. TPX2 , which has not previously been reported in HER2+ breast cancer, was associated with breast cancer development, progression, and prognosis and is therefore a potential key gene. It is hoped that this study can provide a new method for the diagnosis and treatment of HER2 + breast cancer.

Abstract Liver metastasis remains the primary cause of mortality in patients with colon cancer. Identifying specific driver gene mutations that contribute to metastasis may offer viable therapeutic targets. To explore clonal evolution and genetic heterogeneity within the metastasis, we conducted single-cell exome sequencing on 150 single cells isolated from the primary tumor, liver metastasis, and lymphatic metastasis from a stage IV colon cancer patient. The genetic landscape of the tumor samples revealed that both lymphatic and liver metastases originated from the same region of the primary tumor. Notably, the liver metastasis was derived directly from the primary tumor, bypassing the lymph nodes. Comparative analysis of the sequencing data for individual cell pairs within different tumors demonstrated that the genetic heterogeneity of both liver and lymphatic metastases was also greater than that of the primary tumor. This finding indicates that liver and lymphatic metastases arose from clusters of circulating tumor cell (CTC) of a polyclonal origin, rather than from a single cell from the primary tumor. Single-cell transcriptome analysis suggested that higher EMT score and CNV scores were associated with more polyclonal metastasis. Additionally, a mutation in the TRPS1 (Transcriptional repressor GATA binding 1) gene, TRPS1 R544Q, was enriched in the single cells from the liver metastasis. The mutation significantly increased CRC invasion and migration both in vitro and in vivo through the TRPS1R544Q/ZEB1 axis. Further TRPS1 mutations were detected in additional colon cancer cases, correlating with advanced-stage disease and inferior prognosis. These results reveal polyclonal seeding and TRPS1 mutation as potential mechanisms driving the development of liver metastases in colon cancer.

Abstract Ferroelectrics are essential in memory devices for multi-bit storage and high-density integration. Ferroelectricity mainly exists in compounds but rare in single-element materials due to their lack of spontaneous polarization in the latter. However, we report a room-temperature ferroelectricity in quasi-one-dimensional Te nanowires. Piezoelectric characteristics, ferroelectric loops and domain reversals are clearly observed. We attribute the ferroelectricity to the ion displacement created by the interlayer interaction between lone-pair electrons. Ferroelectric polarization can induce a strong field effect on the transport along the Te chain, giving rise to a self-gated ferroelectric field-effect transistor. By utilizing ferroelectric Te nanowire as channel, the device exhibits high mobility (~220 cm2·V−1·s−1), continuous-variable resistive states can be observed with long-term retention (>105 s), fast speed (1.92 TB/cm2). Our work provides opportunities for single-element ferroelectrics and advances practical applications such as ultrahigh-density data storage and computing-in-memory devices.

In low-pressure gas reservoirs, water-based fracture fluid is difficult to flowback, which is unfavorable for several tight sandstone gas reservoirs in the Sichuan Basin with low pressure and high permeability geological characteristics. Supercritical CO2 possesses a number of remarkable physical and chemical features, including a density near to water, a viscosity close to gas, and high diffusion. Supercritical CO2 fracturing is a new type of non-aqueous fracturing method that is favorable to fracturing flowback in low-pressure tight sandstone and has a wide range of applications. To discuss on whether supercritical CO2 fracturing with low pressure tight sandstone is feasible. Tight sandstone cores from the Jinqiu gas field in the Sichuan Basin were used to study the influence of supercritical CO2 on the physical properties of sandstone reservoirs. Supercritical CO2 was used to interact with tight sandstone samples, and then the changes in porosity, permeability, and rock microstructure of tight sandstone were observed under various time, pressure, and temperature conditions. After the interaction between tight sandstone and supercritical CO2, new dissolution pores will appear, or the original pores will be increased, and the width of some natural fractures will also be increased, and the porosity will increase by 1.09%–8.85%, and the permeability will increase by 2.34%–21.26%, quantifying the influence of supercritical CO2 on physical properties of tight sandstone, and further improving the interaction mechanism between supercritical CO2 and tight sandstone. This study improves in the understanding of the tight sandstone-supercritical CO2 interaction mechanism, as well as providing an experimental foundation and technological guarantee for field testing and use of supercritical CO2 in low-pressure tight sandstone gas reservoirs.

Abstract Background Nonalcoholic fatty liver disease (NAFLD) is a chronic disease with an increasing incidence, which can further develop into liver fibrosis and hepatocellular carcinoma at the end stage. Alantolactone (Ala), a sesquiterpene lactone isolated from Asteraceae, has shown anti-inflammatory effects in different models. However, the therapeutic effect of Ala on NAFLD is not clear. Methods C57BL/6 mice were fed a high-fat diet (HFD) to induce NAFLD. After 16 weeks, Ala was administered by gavage to observe its effect on NAFLD. RNA sequencing of liver tissues was performed to investigate the mechanism. In vitro, mouse cell line AML-12 was pretreated with Ala to resist palmitic acid (PA)-induced inflammation, oxidative stress and fibrosis. Results Ala significantly inhibited inflammation, fibrosis and oxidative stress in HFD-induced mice, as well as PA-induced AML-12 cells. Mechanistic studies showed that the effect of Ala was related to the induction of Nrf2 and the inhibition of NF-κB. Taken together, these findings suggested that Ala exerted a liver protective effect on NAFLD by blocking inflammation and oxidative stress. Conclusions The study found that Ala exerted a liver protective effect on NAFLD by blocking inflammation and oxidative stress, suggesting that Ala is an effective therapy for NAFLD.

Abstract Magnetoelectric materials, which encompass coupled magnetic and electric polarizabilities within a single phase, hold great promises for magnetic controlled electronic components or electric-field controlled spintronics. However, the realization of ideal magnetoelectric materials remains tough due to the inborn competion between ferroelectricity and magnetism in both levels of symmetry and electronic structure. Herein, we introduce a methodology for constructing single phase paramagnetic ferroelectric molecule [TMCM][FeCl4], which shows low-magnetic-field magnetoelectricity at room temperature. By applying a low magnetic field (≤1 kOe), the halogen Cl‧‧‧Cl distance and the volume of [FeCl4]− anions could be manipulated. This structural change causes a characteristic magnetostriction hysteresis, resulting in a substantial deformation of ~10−4 along the a-axis under an in-plane magnetic field of 2 kOe. The magnetostrictive effect is further qualitatively simulated by density functional theory calculations. Furthermore, this mechanical deformation significantly dampens the ferroelectric polarization by directly influencing the overall dipole configuration. As a result, it induces a remarkable α 31 component (~89 mV Oe−1 cm−1) of the magnetoelectric tensor. And the magnetoelectric coupling, characterized by the change of polarization, reaches ~12% under 40 kOe magnetic field. Our results exemplify a design methodology that enables the creation of room-temperature magnetoelectrics by leveraging the potent effects of magnetostriction.

Abstract Global riverine nitrous oxide (N2O) emissions have increased more than 4-fold in the last century. It has been estimated that the hyporheic zones in small streams alone may contribute approximately 85% of these N2O emissions. However, the mechanisms and pathways controlling hyporheic N2O production in stream ecosystems remain unknown. Here, we report that ammonia-derived pathways, rather than the nitrate-derived pathways, are the dominant hyporheic N2O sources (69.6 ± 2.1%) in agricultural streams around the world. The N2O fluxes are mainly in positive correlation with ammonia. The potential N2O metabolic pathways of metagenome-assembled genomes (MAGs) provides evidence that nitrifying bacteria contain greater abundances of N2O production-related genes than denitrifying bacteria. Taken together, this study highlights the importance of mitigating agriculturally derived ammonium in low-order agricultural streams in controlling N2O emissions. Global models of riverine ecosystems need to better represent ammonia-derived pathways for accurately estimating and predicting riverine N2O emissions.

Abstract Raman spectroscopy is a nondestructive and highly effective technique for analyzing biological tissues and diagnosing diseases by providing detailed spectral information about the specific molecular structures of substances. Its efficacy in these applications has been widely recognized, making it a powerful tool in the field. This article presents a comprehensive overview of the latest developments in Raman spectroscopy and its wide‐ranging applications in the diagnosis of critical diseases, such as cancer, infections, neurodegenerative diseases, and predicting surgical outcomes. It highlights the significant contributions of Raman spectroscopy in these areas, shedding light on its potential as a valuable diagnostic tool. This article delves into the advancements of Raman spectroscopy in biomedical sciences, with a specific focus on state‐of‐the‐art techniques such as surface‐enhanced Raman spectroscopy, resonance Raman spectroscopy, and tip‐enhanced Raman spectroscopy. These techniques have shown great potential in various applications within the field. The article explores their use in ex vivo and in vivo medical diagnosis, covering topics such as sample collection, data processing, and the successful establishment of correlations between Raman spectra and biochemical information in specific diseases. Furthermore, the article discusses the limitations of the current research and offers insights into potential future directions for further exploration in the field of Raman spectroscopy in biomedical sciences.

In the process of ascending and descending in deep-sea submerging and lifting cage nets, accompanied by changes in water pressure, pressure is one of the crucial environmental factors affecting the physiology and growth of fish. It directly relates to the comfort of farmed fish in the cage, thereby influencing the quality of aquaculture, especially for high-demanding species on the culture environment like the Larimichthys crocea. Investigating the stress level changes exhibited by L.crocea under environmental pressure variations, understanding the limit tolerance pressure, and its changes, can provide a theoretical basis for the design, application, and increased production of deep-sea submersible cage nets and L.crocea aquaculture. This study explores the effects of varying submersion depths (0–20 m) and speeds (0.6, 1, 1.3, 2, 4 m/min) on the behavioral responses of L.crocea in deep-sea cage environments. Key findings demonstrate that increased submersion depths and speeds significantly influence the physical behaviors and stress responses of the species. At submersion depths of 15 meters and 20 meters, the average swimming speed of the L.crocea exceeds 0.05 meters per second, the tail movement frequency is 1.42 times that of normal pressure, and the gasping frequency exceeds 20%., and at the highest speed of 4 m/min, the swimming speed reaches 0.0902 m/s—3.76 times greater than under normal pressure. The study determines that a submersion depth of 10 meters and a submersion speed of 0.6 meters per minute can minimize stress responses, providing critical insights for optimizing deep-sea aquaculture operations of L.crocea. These results offer valuable guidelines for the design and management of submersible cage systems.

Abstract Realization of stable and industrial-level H2O2 electroproduction still faces great challenge due large partly to the easy decomposition of H2O2. Herein, a two-dimensional dithiine-linked phthalocyaninato cobalt (CoPc)-based covalent organic framework (COF), CoPc-S-COF, was afforded from the reaction of hexadecafluorophthalocyaninato cobalt (II) with 1,2,4,5-benzenetetrathiol. Introduction of the sulfur atoms with large atomic radius and two lone-pairs of electrons in the C-S-C linking unit leads to an undulated layered structure and an increased electron density of the Co center for CoPc-S-COF according to a series of experiments in combination with theoretical calculations. The former structural effect allows the exposition of more Co sites to enhance the COF catalytic performance, while the latter electronic effect activates the 2e− oxygen reduction reaction (2e− ORR) but deactivates the H2O2 decomposition capability of the same Co center, as a total result enabling CoPc-S-COF to display good electrocatalytic H2O2 production performance with a remarkable H2O2 selectivity of >95% and a stable H2O2 production with a concentration of 0.48 wt% under a high current density of 125 mA cm−2 at an applied potential of ca. 0.67 V versus RHE for 20 h in a flow cell, representing the thus far reported best H2O2 synthesis COFs electrocatalysts.