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Abstract Referring to the intestinal ischemic injury caused by sudden interruption of the blood supply, acute mesenteric ischemia (AMI) is a highly fatal emergency with mortality rates varying from 58 to 80%. The aim of this study was to explore the effect of temperature on AMI admission. This was a retrospective, multicentric study. The medical records of 1477 patients with verified AMI who were consecutively admitted to 3 hospitals anytime between January 2010 and December 2020 were included in the study. Distributed lag non-linear model was applied, the model was adjusted for temperature, atmospheric pressure, relative humidity, year, holiday, day of the week, time and seasonality. AMI exhibited obvious sex preference, AMI patients tended to be male (M/F ratio = 2.3:1) and in their late 50 s. Hospital admissions of acute mesenteric arterial thromboembolism (AMAT) increased significantly with high temperatures on day of exposure and lag 0–14 day. The effect curve of daily average temperature on acute mesenteric venous thromboembolism (AMVT) admission was J-shaped, and the duration of cold effect was longer, while the duration of heat effect was shorter. An increase in hospital admissions of AMVT was found above 20 °C at lag 0–30. For the first time, our study indicated that temperature is significantly associated with the risk of AMI. Although it is not possible to always avoid exposure to extreme temperatures, one should be aware of dramatic temperature fluctuations and take appropriate precautions.

Abstract Low‐light images are captured in environments with minimal lighting, such as nighttime or underwater conditions. These images often suffer from issues like low brightness, poor contrast, lack of detail, and overall darkness, significantly impairing human visual perception and subsequent high‐level visual tasks. Enhancing low‐light images holds great practical significance. Among the various existing methods for Low‐Light Image Enhancement (LLIE), those based on the Retinex theory have gained significant attention. However, despite considerable efforts in prior research, the challenge of Retinex decomposition remains unresolved. In this study, an LLIE network based on the Retinex theory is proposed, which addresses these challenges by integrating attention mechanisms and a U‐Net‐like architecture. The proposed model comprises three modules: the Decomposition module (DECM), the Reflectance Recovery module (REFM), and the Illumination Enhancement module (ILEM). Its objective is to decompose low‐light images based on the Retinex theory and enhance the decomposed reflectance and illumination maps using attention mechanisms and a U‐Net‐like architecture. We conducted extensive experiments on several widely used public datasets. The qualitative results demonstrate that the approach produces enhanced images with superior visual quality compared to the existing methods on all test datasets, especially for some extremely dark images. Furthermore, the quantitative evaluation results based on metrics PSNR, SSIM, LPIPS, BRISQUE, and MUSIQ show the proposed model achieves superior performance, with PSNR and BRISQUE significantly outperforming the baseline approaches, where (PSNR, mean BRISQUE) values of the proposed method and the second best results are (17.14, 17.72) and (16.44, 19.65). Additionally, further experimental results such as ablation studies indicate the effectiveness of the proposed model.

Abstract Leukemia is an abnormal proliferation of white blood cells that occurs in bone marrow and expands through the blood. It arises from dysregulated differentiation, uncontrolled growth, and inhibition of apoptosis. Glutamine (GLN) is a "conditionally essential" amino acid that promotes growth and proliferation of leukemic cells. Recently, details about the role of GLN and its metabolism in the diagnosis and treatment of acute myeloid, chronic lymphocytic, and acute lymphoblastic leukemia have emerged. The uptake of GLN by leukemia cells and the dynamic changes of glutamine-related indexes in leukemia patients may be able to assist in determining whether the condition of leukemia is in a state of progression, remission or relapse. Utilizing the possible differences in GLN metabolism in different subtypes of leukemia may help to differentiate between different subtypes of leukemia, thus providing a basis for accurate diagnosis. Targeting GLN metabolism in leukemia requires simultaneous blockade of multiple metabolic pathways without interfering with the normal cellular and immune functions of the body to achieve effective leukemia therapy. The present review summarizes recent advances, possible applications, and clinical perspectives of GLN metabolism in leukemia. In particular, it focuses on the prospects of GLN metabolism in the diagnosis and treatment of acute myeloid leukemia. The review provides new directions and hints at potential roles for future clinical treatments and studies.

Abstract Aims Surveys and research on the applications of the hepatic venous pressure gradient (HVPG) are important for understanding the current status and future development of this technology in China. This article aimed to investigate the status of hepatic venous pressure gradient measurement in China in 2022. Methods We investigated the overall status of HVPG technology in China—including hospital distribution, hospital level, annual number of cases, catheters used, average cost, indications, and current challenges by using online questionnaire. By counting the number and percentages of cases of these results, we hope to clarify the current status of HVPG measurements in China. Results According to the survey, 85 hospitals in China used HVPG technology in 2022 distributed across 29 provinces. A total of 4989 HVPG measurements were performed in all of the surveyed hospitals in 2022, of which 2813 cases (56.4%) were measured alone. The average cost of HVPG measurement was 5646.8 ± 2327.9 CNY. Of the clinical teams who performed the measurements (sometimes multiple per hospital), 94.3% (82/87) used the balloon method, and the majority of the teams (72.4%, 63/87) used embolectomy catheters. Conclusions This survey clarified the clinical application status of HVPG in China and confirmed that some medical institutions in China have established a foundation for this technology. It is still necessary to continue promoting and popularizing this technology in the future.

To better meet the requirements in loss-of-coolant accidents (LOCA) and conventional operating conditions in nuclear applications, this work prepared Cr, FeCrAl, and Cr/FeCrAl composite coatings on Zr alloys using plasma spraying technology. The microstructures, hardness, and high-temperature oxidation resistance of coatings are examined. The high-temperature oxidation of coatings was conducted at 1200 °C in air for 20, 40, and 60 min. All coatings exhibited characteristic lamellar microstructures accompanied by small pores. The inner layers of the coatings, benefiting from the “compacting effect” of subsequently deposited particles, displayed lower porosity and higher hardness. The order of high-temperature oxidation resistance among the coatings was determined as follows: Cr/FeCrAl coating > Cr coating > FeCrAl coating. Notably, the Cr/FeCrAl composite coating demonstrated exceptional durability even after a 60-min exposure, with no ZrO2 formation and negligible Fe and Cr diffusion. However, oxygen could still reach the Zr substrate due to inherent pores and the lamellar structure in the as-sprayed coatings. Therefore, post-treatments are suggested to mitigate or eliminate these pores, thereby improving high-temperature oxidation resistance.

Abstract Efficient and rapid auxiliary diagnosis of different grades of lung adenocarcinoma is conducive to helping doctors accelerate individualized diagnosis and treatment processes, thus improving patient prognosis. Currently, there is often a problem of large intra-class differences and small inter-class differences between pathological images of lung adenocarcinoma tissues under different grades. If attention mechanisms such as Coordinate Attention (CA) are directly used for lung adenocarcinoma grading tasks, it is prone to excessive compression of feature information and overlooking the issue of information dependency within the same dimension. Therefore, we propose a Dimension Information Embedding Attention Network (DIEANet) for the task of lung adenocarcinoma grading. Specifically, we combine different pooling methods to automatically select local regions of key growth patterns such as lung adenocarcinoma cells, enhancing the model's focus on local information. Additionally, we employ an interactive fusion approach to concentrate feature information within the same dimension and across dimensions, thereby improving model performance. Extensive experiments have shown that under the condition of maintaining equal computational expenses, the accuracy of DIEANet with ResNet34 as the backbone reaches 88.19%, with an AUC of 96.61%, MCC of 81.71%, and Kappa of 81.16%. Compared to seven other attention mechanisms, it achieves state-of-the-art objective metrics. Additionally, it aligns more closely with the visual attention of pathology experts under subjective visual assessment.

Since the 21st century, the closure of domestic uranium mines in Europe has made it one of the world's leading importers of uranium. In recent years, a series of policy adjustments have led to an improving situation for enriched uranium supply, yet the challenge of natural uranium supply remains unresolved. This work divides Europe into five uranium metallogenic provinces based on its geological background and the distribution characteristics of various types of uranium deposits. The intrusive type uranium deposits in Greenland U metallogenic province, the metasomatite type uranium deposits in Ukraine U metallogenic province, and the granite-related type uranium deposits in Central Europe U metallogenic province contain a considerable amount of uranium resources, but their mining activities are difficult to continue due to a series of reasons. Benefited from the unique advantages of in-site leaching and exploitation, sandstone type uranium deposit is the most promising targets for mining among conventional uranium resource types, contains significant uranium resources in the Central Europe U metallogenic province and the Alpine orogenic belt U metallogenic province (378 × 103 t). In terms of unconventional uranium resources, the black shale type uranium deposits and the phosphate type uranium deposits (resources) are equally high potential development targets. Estimates suggest that black shale in Sweden contains 6535 × 103 t of uranium resources, and uranium can be recovered as a by-product from millions of tonnes of phosphate imported annually by EU. Sandstone type, black shale type and phosphate type, these three types of uranium resources hold significant strategic importance for Europe in the coming years, as they can provide ''local solutions'' to the energy crisis.

Investigating fish diversity in canyon rivers through conventional fish surveys is challenging due to precipitous conditions, including steep slopes, rapid water flow, and complex habitats. Additionally, intensive construction of dams has further complicated the understanding of contemporary fish diversity in these rivers. In this study, we used the environmental DNA (eDNA) technique to assess fish diversity and examine the effects of dams on fish diversity in the Mabiehe River, a canyon river in the upper reaches of the Pearl River drainage. Water samples from 15 sampling sites were collected, yielding 9,356,148 valid sequences. Utilizing the NCBI public database, a total of 60 freshwater fish species were identified, with Carassius auratus, Cyprinus carpio, and Pelteobagrus fulvidraco being the most dominant species in the Mabiehe River. We also detected one nationally protected fish species, three provincially protected fish species, and six exotic species in this river. Furthermore, eDNA analyses demonstrated that the lotic river sections harbor more species and greater diversity than dammed sections, suggesting that dams might exert significant impacts on local fish diversity. Overall, this study supports the effectiveness of the eDNA technique as a complementary tool to traditional field surveys for monitoring fish biodiversity in canyon rivers.

In the context of ecological civilization construction in China, interregional ancient trees are important natural and cultural resources, and it is vital that they are effectively protected and utilized according to their spatial distribution and regional conditions in order to provide a balance between local economic development and the ecological environment. This article analyzes the spatial heterogeneity of 26,842 ancient trees and explores the underlying natural and human factors by using geoinformatics–based techniques (i.e., the nearest neighbor index, kernel density, spatial autocorrelation, and the geographically weighted regression model) in Henan Province, Central China. The research findings conclude that: (1) The interregional ancient trees show positive spatial autocorrelation, and the aggregation effect in Western Henan is the most significant. (2) The growing environment and elevation exert a more obvious influence on the spatial pattern of interregional ancient trees. (3) The main influencing factors per region are different, for example, historical culture in Western Henan, water source and elevation in Southern Henan, and the growing environment in Eastern Henan, while ancient trees in Northern Henan have a weak relationship with each factor. This research facilitates political strategy making for sustainable development and the protection of interregional ancient trees.

Spectral collinearity and limited spectral datasets are the problems influencing Chemical Oxygen Demand (COD) modeling. To address the first problem and obtain optimal modeling range, the spectra are preprocessed using six methods including Standard Normal Variate, Savitzky-Golay Smoothing Filtering (SG) etc. Subsequently, the 190-350 nm spectral range is divided into 10 subintervals, and Interval Partial Least Squares (IPLS) is used to perform PLS modeling on each interval. The results indicate that it is best modeled in the 7th range (238~253 nm). The values of Mean Square Error (MSE), Mean Absolute Error (MAE) and R2score of the model without pretreatment are 1.6489, 1.0661, and 0.9942. After pretreatment, the SG is better than others, with MSE and MAE decreasing to 1.4727, 1.0318 and R2score improving to 0.9944. Using the optimal model, the predicted COD for three samples are 10.87 mg/L, 14.88 mg/L, and 19.29 mg/L. To address the problem of the small dataset, using Generative Adversarial Networks for data augmentation, three datasets are obtained for Support Vector Machine (SVM) modeling. The results indicate that, compared to the original dataset, the SVM's MSE and MAE have decreased, while its accuracy has improved by 2.88%, 11.53%, and 11.53%, and the R2score has improved by 18.07%, 17.40%, and 18.74%.

Abstract The artificial synapse array with an electrolyte‐gated transistor (EGT) as an array unit presents considerable potential for neuromorphic computation. However, the integration of EGTs faces the drawback of the conflict between the polymer electrolytes and photo‐lithography. This study presents a scheme based on a lateral‐gate structure to realize high‐density integration of EGTs and proposes the integration of 100 × 100 EGTs into a 2.5 × 2.5 cm2 glass, with a unit density of up to 1600 devices cm−2. Furthermore, an electrolyte framework is developed to enhance the array performance, with ionic conductivity of up to 2.87 × 10−3 S cm−1 owing to the porosity of zeolitic imidazolate frameworks‐67. The artificial synapse array realizes image processing functions, and exhibits high performance and homogeneity. The handwriting recognition accuracy of a representative device reaches 92.80%, with the standard deviation of all the devices being limited to 9.69%. The integrated array and its high performance demonstrate the feasibility of the scheme and provide a solid reference for the integration of EGTs.

BackgroundSuicidal and self-injurious-related behaviors (SSIRBs) are a serious public health challenge in China. However, a comprehensive systematic review of psychosocial interventions for SSIRBs among Chinese adolescents has not been performed. To fill this gap, this systematic review and meta-analysis aimed to examine psychosocial interventions for SSIRBs among Chinese adolescents.MethodsEight international (PubMed, EMBASE, Cochrane Library, ScienceDirect, Clinical Trial, CINAHL, PsycINFO, and Web of Science) and four Chinese (Wanfang, SinoMed, CEPS, and CNKI) databases were searched from inception to 31 January 2023. Data extraction and quality assessment were independently conducted by two groups of researchers. Qualitative synthesis and meta-analysis were both used.ResultsThe initial search yielded 16,872 titles. Of the 649 full texts reviewed, 19 intervention articles focusing on SSIRBs met the inclusion criteria. Thirteen out of the 19 included studies involved cognitive–behavioral therapy (CBT). Seven non-suicidal self-injury (NSSI) studies assessing self-injurious behaviors were included (six short-term studies and three long-term studies). Compared with long-term interventions [−1.30 (95% CI: –1.84, −0.76)], short-term psychosocial interventions had a higher standardized mean difference (SMD) value [1.86 (95% CI: –2.72, −0.99)]. Meta-regression showed an inverse relationship between the treatment response and sample size (slope = 0.068, Z = 2.914, p = 0.004) and proportion of females (slope = 1.096, Z = 5.848, p

White pepper, used both as a seasoning in people’s daily diets and as a medicinal herb, is typically produced by removing the pericarp of green pepper through the retting process. However, the mechanism of the retting process for peeling remains unclear. Therefore, this study aimed to investigate the changes in physicochemical factors, microbial community succession effects, and metabolites of the pepper pericarp during the pepper peeling process. The findings indicated that pre-treatment involving physical friction before the retting process effectively reduced the production time of white pepper. During the retting process, the pectinase activity increased, leading to a decrease in the pectin content in the pepper pericarp. There was a significant correlation observed between the changes in pH, pectin content, and peeling rate and the Shannon diversity index of bacteria and fungi. Prevotella, Lactococcus, and Candida were the dominant microbial genera during the retting. The functional predictions suggested that the monosaccharides degraded from the pepper pericarp could have been utilized by microbes through sugar metabolism pathways. Metabolomic analysis showed that the metabolic pathways of carbohydrates and amino acids were the main pathways altered during the pepper peeling process. The verification experiment demonstrated that the degradation of pectin into galacturonic acid by polygalacturonase was identified as the key enzyme in shortening the pepper peeling time. The structure of the pepper pericarp collapsed after losing the support of pectin, as revealed by scanning electron microscopy. These results suggest that the decomposition of the pepper pericarp was driven by key microbiota. The succession of microbial communities was influenced by the metabolites of the pepper pericarp during retting. These findings provide new insights into the retting process and serve as an important reference for the industrial production of white pepper.

The strengthening phases characteristics in the alloy determine the mechanical properties of the alloy, but it is a hard task to predict the precipitation of complex alloys. In this work, we quickly detected 33,484 groups of Ni-based superalloys composition information and microstructure image by integrating high-throughput experiment and a nested UNet 3+ architecture for image recognition, and established a database of γ′ precipitation. Based on the database, a high-confidence prediction model was established, which could accurately predict the volume fraction, average size and size distribution of γ′ prediction in different alloys. Compared with the traditional methods, the proposed approach has a remarkable advantage in acquiring and analyzing the experimental data, which can also be applied to other multi-component alloys.

Colorectal adenocarcinoma (CRC) is the third most common malignancy worldwide. Metastatic CRC has a poor prognosis because of chemotherapy resistance. Our previous study demonstrated that semaphorin 3F (SEMA3F) signaling may contribute to reversing chemotherapy resistance in CRC cells by reducing E-cadherin and integrin αvβ3 expression levels. Another study showed that upregulation of p27 significantly increase the expression of E-cadherin and integrin. This study aimed to evaluate the effect of SEMA3F on P27 and whether it can reverse resistance in CRC cells. We compared the chemosensitivity of human colorectal cancer cell lines with different SEMA3F expression levels to 5-Fu through cell experiment and animal experiment. Then the interaction between SEMA3F and p27 and its possible mechanism were explored by Western Blot, immunofluorescence and immunocoprecipitation. We also compared the disease-free survival of 118 CRC patients with high or low expression of SEMA3F.The results showed that overexpresstion of SEMA3F enhanced the chemotherapy sensitivity and apoptosis of CRC cells in vitro and in vivo. Among 118 postoperative CRC specimens, the disease-free survival of patients with positive SEMA3F expression was significantly longer than that with negative SEMA3F expression after adjuvant treatment. Upregulation of SEMA3F in multicellular spheroid culture (MSC) could increase p27 phosphorylation at serine 10 (Ser10), subsequently promote the cytosolic translocation of P27. Overall, our results reveal a novel molecular mechanism: SEMA3F mediates the degradation of p27 and regulates its subcellular localization to enhance chemosensitivity to 5-Fu in CRC cells, rather than inhibits p27 expression.

Considering the resource limitations of low-cost wireless sensors, there is a growing inclination to utilize cryptographic primitives that are optimized for efficiency, such as symmetric key encryption/decryption and hash functions, when designing authentication schemes. However, designing a lightweight authentication scheme that can meet various security requirements poses a significant challenge. In recent years, numerous lightweight authentication schemes have been proposed in order to address these security needs. Nevertheless, recent research has revealed that many of these schemes exhibit security vulnerabilities and design deficiencies, including challenges related to asynchronization and impractical gateway-node search operations. Due to the inadequate security of existing schemes, this study introduces a novel privacy-preserving authentication scheme that aims to provide adaptive resilience against desynchronization attacks in wireless body area networks (WBANs). The proposed scheme utilizes lightweight cryptographic modules to optimize efficiency. To ensure user anonymity, the Chinese Remainder Theorem technique is employed, whereas forward secrecy and resistance to desynchronization attacks are achieved through the use of one-way hash chains and serial numbers, respectively. Through extensive analysis and comparisons, the proposed scheme is demonstrated to strike a fine balance between security and efficiency.

Predicting the phase precipitation of multicomponent alloys, especially the Ni-base superalloys, is a difficult task. In this work, we introduced a dependable and efficient way to establish the relationship between composition and detrimental phases in Ni-base superalloys, by integrating high throughput experiments and machine learning algorithms. 8371 sets of data about composition and phase information were obtained rapidly, and analyzed by machine learning to establish a high-confidence phase prediction model. Compared with the traditional methods, the proposed approach has remarkable advantage in acquiring and analyzing the experimental data, which can also be applied to other multicomponent alloys. IMPACT STATEMENT By integrating the high throughput experiments and machine learning algorithms, it is hopeful to facilitate the design of new Ni-base superalloys, and even other multicomponent alloys.

Aggregation-induced emission (AIE) has attracted much attention in the past 2 decades. To develop novel AIE-active materials, ACQ-to-AIE transformation via regioisomerization is one of the most straightforward method. However, most of the reported ACQ-to-AIE transformations are achieved by migrating bulky units. In this work, a facile conversion was realized by migrating a small pyrrolidinyl group from para- to ortho-position on the rofecoxib scaffold. As a result, a pair of new isomers named MOX2 and MOX4 exhibited AIE behavior and ACQ activity, respectively. Moreover, MOX2 also showed solvatochromic, mechanochromic, and acidochromic properties with reversible multi-stimulus behavior. Single crystal X-ray analysis of MOX2 revealed that the molecular conformation and its packing mode were responsible for the AIE emission behavior. Further investigation indicated that MOX2 showed high lipid droplets staining selectivity. Taken together, the current work not only provides a new design philosophy for achieving ACQ-to-AIE conversion by migrating a small pyrrolidinyl group but also presents a promising candidate MOX2 for potential applications such as in security ink, optical recording and biological applications.

Lipid-related cancers cause a large number of deaths worldwide. Therefore, development of highly efficient Lipid droplets (LDs) fluorescent imaging probes will be beneficial to our understanding of lipid-related cancers by allowing us to track the metabolic process of LDs. In this work, a LDs-specific NIR (λmax = 698 nm) probe, namely BY1, was rationally designed and synthesized via a one-step reaction by integrating triphenylamine (electron–donor group) unit into the structure of rofecoxib. This integration strategy enabled the target BY1 to form a strong Donor–Acceptor (D-A) system and endowed BY1 with obvious aggregation-induced emission (AIE) effect. Meanwhile, BY1 also showed observable solvent effect and reversible mechanochromatic luminescent property, which could be interpreted clearly via density functional theory (DFT) calculations, differential scanning calorimetry (DSC), powder X-ray diffraction (XPRD), and single crystal X-ray data analysis. More importantly, BY1 exhibited highly specific fluorescent imaging ability (Pearson’s correlation = 0.97) towards lipid droplets in living HeLa cells with low cytotoxicity. These results demonstrated that BY1 is a new promising fluorescent probe for lipid droplets imaging, and it might be beneficial to facilitate biological research of lipid-related cancers.

It becomes a common practice to adopt high-throughput experiments on superalloys, which can generate a large amount of data. To address this large amount of data, we designed a machine learning (ML) based model to automate the experimental analysis process. More specifically, we adopted the Unet algorithm to segment the precipitated phases from superalloy images and subsequently used a regression algorithm to predict the morphological parameters of the microstructure of the segmented precipitated phases according to their composition. The method proposed in this work may provide guidance for the future design of the superalloy composition.

This paper proposes a unified attitude controller based on the modified linear active disturbance rejection control (LADRC) for a dual-tiltrotor unmanned aerial vehicle (UAV) with cyclic pitch to achieve accurate attitude control despite its nonlinear and time-varying characteristics during flight mode transitions. The proposed control algorithm has higher robustness against model mismatch compared with the model-based control algorithms. The modified LADRC utilizes the state feedbacks from the onboard sensors like IMU and Pitot tube instead of the mathematical model of the plane. It has less dependency on the accurate dynamics model of the dual-tiltrotor UAV, which can hardly be built. In contrast to the original LADRC, an actuator model is integrated into the modified LADRC to compensate for the non-negligible slow rotor flapping dynamics and servo dynamics. This modification eliminates the oscillation of the original LADRC when applied on the plant with slow-response actuators, such as propeller and rotors of the helicopter. In this way, the stability and performance of the controller are improved. The controller replaces the gain-scheduling or the control logic switching by a unified controller structure, which simplifies the design approach of the controller for different flight modes. The effectiveness of the modified LADRC and the performance of the unified attitude controller are demonstrated in both simulation and flight tests using a dual-tiltrotor UAV. The attitude control error is less than ±4° during the conversion flight. The control rising time in different flight modes is all about 0.5 s, despite the variations in the airspeed and tilt angle. The flight results show that the controller guarantees high control accuracy and uniform control quality in different flight modes.

In this work, we synthesized a pair of positional isomers by attaching a small electron-donating pyrrolidinyl group at ortho- and para-positions of a conjugated core. These isomers exhibited totally different fluorescent properties. PDB2 exhibited obvious aggregation-induced emission properties. In contrast, PDB4 showed the traditional aggregation-caused quenching effect. Their different fluorescent properties were investigated by absorption spectroscopy, fluorescence spectroscopy, density functional theory calculations and single-crystal structural analysis. These results indicated that the substituent position of the pyrrolidinyl groups affects the twisted degree of the isomers, which further induces different molecular packing modes, thus resulting in different fluorescent properties of these two isomers. This molecular design concept provided a new accurate strategy for designing new aggregation-induced emission luminogens.

Nutrient sensing and adaptation in the placenta are essential for pregnancy viability and proper fetal growth. Our recent study demonstrated that the placenta adapts to nutrient insufficiency through mechanistic target of rapamycin (mTOR) inhibition-mediated trophoblast differentiation toward syncytiotrophoblasts (STBs), a highly specialized multinucleated trophoblast subtype mediating extensive maternal-fetal interactions. However, the underlying mechanism remains elusive. Here, we unravel the indispensable role of the mTORC1 downstream transcriptional factor TFEB in STB formation both in vitro and in vivo. TFEB deficiency significantly impaired STB differentiation in human trophoblasts and placenta organoids. Consistently, systemic or trophoblast-specific deletion of Tfeb compromised STB formation and placental vascular construction, leading to severe embryonic lethality. Mechanistically, TFEB conferred direct transcriptional activation of the fusogen ERVFRD-1 in human trophoblasts and thereby promoted STB formation, independent of its canonical function as a master regulator of the autophagy-lysosomal pathway. Moreover, we demonstrated that TFEB directed the trophoblast syncytialization response driven by mTOR complex 1 (mTORC1) signaling. TFEB expression positively correlated with the reinforced trophoblast syncytialization in human fetal growth-restricted placentas exhibiting suppressed mTORC1 activity. Our findings substantiate that the TFEB-fusogen axis ensures proper STB formation during placenta development and under nutrient stress, shedding light on TFEB as a mechanistic link between nutrient-sensing machinery and trophoblast differentiation. [ABSTRACT FROM AUTHOR]

On 6 February 2023, two large earthquakes (moment magnitude 7.8 and 7.6) shocked a vast area of southeastern Türkiye and northern Syria, leading to heavy casualties and economic loss. To investigate the rupture process over multiple fault segments, we performed a comprehensive analysis of local seismic and geodetic data and determined supershear ruptures on the initial branch and the Pazarcık and Erkenek segments and subshear ruptures on the Amanos segment of event 1. The bilateral rupture of event 2 also presents distinct sub- and supershear velocities. The dynamic stress of the branch fault rupture triggered the Pazarcık segment initial rupture at a point 9 kilometers west of the junction of these two faults, boosting the supershear rupture of the Pazarcık segment of the main fault. The geometry and prestress level of multiple segments controlled the rupture behaviors and influenced the ground shaking intensity. [ABSTRACT FROM AUTHOR]

Solid solution strengthening (SSS) is one of the main contributions to the desired tensile properties of nickel-based superalloys for turbine blades and disks. The value of SSS can be calculated by using Fleischer's and Labusch's theories, while the model parameters are incorporated without fitting to experimental data of complex alloys. In thiswork, four diffusionmultiples consisting ofmulticomponent alloys and pureNi are prepared and characterized. The composition and microhardness of single γ phase regions in samples are used to quantify the SSS. Then, Fleischer's and Labusch's theories are examined based on high-throughput experiments, respectively. The fitted solid solution coefficients are obtained based on Labusch's theory and experimental data, indicating higher accuracy. Furthermore, six machine learning algorithms are established, providing a more accurate prediction compared with traditional physical models and fitted physical models. The results show that the coupling of highthroughput experiments and machine learning has great potential in the field of performance prediction and alloy design. [ABSTRACT FROM AUTHOR]

Colorectal cancer is one of the major public health issues worldwide due to its high mortality and morbidity. Angiogenesis is the fundamental step of tumors transition from dormant to malignant state and it is recognized as one of the hallmarks of cancer. High mobility group AT-hook 2 encodes a small non-histone chromatin-associated protein that can modulate transcription by altering the chromatin architecture. Currently the mechanism by which high mobility group AT-hook 2 involved in angiogenesis in colorectal cancer has not been clarified. The expression of High mobility group AT-hook 2 was analyzed by immunohistochemistry, Western blotting and bioinformatics methods. cBioPortal and mExpress online tools were applied to explore the copy-number variation and methylation of high mobility group AT-hook 2 in colorectal cancer patients. Single cell data from gene expression omnibus was used to examine the specific cell type that contributed to the high mobility group AT-hook 2 expression in colorectal cancer. Lentivirus was used to knock down high mobility group AT-hook 2 in colorectal cancer cells and human umbilical vein endothelial cells was used to study angiogenesis. In the current study, we first detected the expression pattern of high mobility group AT-hook 2 in colorectal cancer patients and evaluated its clinical values and for the first time showed that copy number amplification contributed to the up regulation of high mobility group AT-hook 2 in colorectal cancer patients. By analyzing colorectal cancer single cell data we found that high mobility group AT-hook 2 was specifically up regulated in the colorectal epithelial cells. Furthermore, knocking down of high mobility group AT-hook 2 in colorectal cancer epithelial cells suppresses angiogenesis via dual regulation of vascular endothelial growth factor-A and semaphorin 3A in colorectal cancer through inactivating vascular endothelial growth factor receptor 2 pathway in human umbilical vein endothelial cells. High mobility group AT-hook 2 might be a promising prognostic marker and target for treating advanced colorectal cancer patients. [ABSTRACT FROM AUTHOR]

A further study of the molecular system of O2-Pd based on the investigation of the atomic system of O-Pd is conducted and the extended LEPS constructed by 5-MP is adopted. The conceptions of the molecular dissociation limit and the surface dissociation distance that are used to analyze the systems of O(sub 2)-Pd(100) and (110) is presented.

1,3-Diacylglycerol (DAG) has been well recognized as a safe food component. The metabolic pathway of DAG in the body is different from that of triacylglycerol, and DAG has been demonstrated to contribute to improving metabolism and preventing obesity and cardiovascular diseases. However, the mass fraction of natural DAG in edible oils and fats is less than 10%, so the preparation of high-purity DAG has received widespread attention in recent years. Enzymatic synthesis is the method of choice for the industrial preparation of DAG due to the advantages of eco-friendliness, safety and desirable selectivity over chemical synthesis. Edible livestock and poultry fats, as by-products of slaughter and processing, have a special flavor and nutritional value. However, their undesirable physicochemical properties, especially high melting points and high levels of saturated fatty acids and cholesterols, highly limit their applications in the food industry. In light of this, the synthesis of DAG from edible livestock and poultry fats is a promising approach for their high-value utilization. The current status of the enzymatic synthesis and the potential application of DAG from livestock and poultry fats are reviewed in this article. It is anticipated that this review will provide new ideas for researchers interested in the enzymatic preparation and high-value utilization of DAG from livestock and poultry fats.