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Background: Gangba sheep as a famous breed of Tibetan sheep, its wool color is mainly white and black. Gangba wool is economically important as a high-quality raw material for Tibetan blankets and Tibetan serge. However, relatively few studies have been conducted on the wool color of Tibetan sheep. Results: To fill this research gap, this study conducted an in-depth analysis of two populations of Gangba sheep (black and white wool color) using whole genome resequencing to identify genetic variation associated with wool color. Utilizing PCA, Genetic Admixture, and N-J Tree analyses, the present study revealed a consistent genetic relationship and structure between black and white wool colored Gangba sheep populations, which is consistent with their breed history. Analysis of selection signatures using multiple methods (FST, π ratio, Tajima's D), 370 candidate genes were screened in the black wool group (GBB vs GBW); among them, MC1R, MLPH, SPIRE2, RAB17, SMARCA4, IRF4, CAV1, USP7, TP53, MYO6, MITF, MC2R, TET2, NF1, JAK1, GABRR1 genes are mainly associated with melanin synthesis, melanin delivery, and distribution. The enrichment results of the candidate genes identified 35 GO entries and 19 KEGG pathways associated with the formation of the black phenotype. 311 candidate genes were screened in the white wool group (GBW vs GBB); among them, REST, POU2F1, ADCY10, CCNB1, EP300, BRD4, GLI3, and SDHA genes were mainly associated with interfering with the differentiation of neural crest cells into melanocytes, affecting the proliferation of melanocytes, and inhibiting melanin synthesis. 31 GO entries and 22 KEGG pathways were associated with the formation of the white phenotype. Conclusions: This study provides important information for understanding the genetic mechanism of wool color in Gangba, and provides genetic knowledge for improving and optimizing the wool color of Tibetan sheep. Genetic improvement and selective breeding to produce wool of specific colors can meet the demand for a diversity of wool products in the Tibetan wool textile market. [ABSTRACT FROM AUTHOR]

BACKGROUND: The maternal diet during gestation and lactation affects the health of the offspring. Konjac glucomannan (KGM) is a significantly functional polysaccharide in food research, possessing both antioxidant and prebiotic properties. However, the mechanisms of how KGM regulates maternal nutrition remain insufficient and limited. This study aimed to investigate maternal supplementation with KGM during late gestation and lactation to benefit both maternal and offspring generations. RESULTS: Our findings indicate that KGM improves serum low density lipoprotein cholesterol (LDL‐C) and antioxidant capacity. Furthermore, the KGM group displayed a significant increase in the feed intake‐related hormones neuropeptide tyrosine (NPY), Ghrelin, and adenosine monophosphate‐activated kinase (AMPK) levels. KGM modified the relative abundance of Clostridium, Candidatus Saccharimonas, unclassified Firmicutes, and unclassified Christensenellaceae in sow feces. Acetate, valerate, and isobutyrate were also improved in the feces of sows in the KGM group. These are potential target bacterial genera that may modulate the host's health. Furthermore, Spearman's correlation analysis unveiled significant correlations between the altered bacteria genus and feed intake‐related hormones. More importantly, KGM reduced interleukin‐6 (IL‐6) levels in milk, further improved IL‐10 levels, and reduced zonulin levels in the serum of offspring. CONCLUSION: In conclusion, maternal dietary supplementation with KGM during late gestation and lactation improves maternal nutritional status by modifying maternal microbial and increasing lactation feed intake, which benefits the anti‐inflammatory capacity of the offspring serum. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

This study integrates geophysical‐geochemical data to investigate the thermochemical structure of the lithosphere and sublithospheric mantle, along the Southern Tyrrhenian Basin, Apennines, Adriatic Sea, Dinarides, and Carpathians‐Balkanides. We present the lithospheric structure of the Adria microplate and the two opposing mantle slabs along its NE and SW margins. The modeling shows the presence of two asthenospheric mantle wedges aligning with the Apenninic and Dinaric continental mantle slab rollback, along with cold (−200°C) sublithospheric anomalies beneath Adria's NE and SW margins. In the northern Adria region, the lithosphere undergoes synchronous thinning in the Tyrrhenian domain and thickening toward the forefront of the northern Apennines. This is associated with the northeastward rollback of the SW Adriatic slab, leading to subsequent delamination of the continental mantle. In the southern Adria region, the complex deep structure results from the variably oriented lithospheric slabs, and nearly 90‐degree shift of the tectonic grain between the southern Apennines and the Calabrian Arc. At the SW Adria margin, beneath the northern Apennines, the thermal sublithospheric anomaly is attached to the shallower lithosphere, while a slab gap is modeled in the southern Apennines. One possibility is that the gap is due to a recent horizontal slab tear. Along the NE margin of Adria, the thermal anomaly penetrates to depths of about 200 km in the northern Dinarides and 280 km in the southern Dinarides, shallower than the SW Adria anomaly, which extends to at least 400 km depth. Plain Language Summary: We integrate geological and geophysical data (e.g., elevation, gravity, geoid, seismic tomography) to investigate the density and temperature distribution of the crust and lithospheric mantle down to 400 km, along a profile that extends from the Southern Tyrrhenian Basin and Apennines in Italy to the Southern Dinarides and Carpathians‐Balkanides in southern Europe. Taking advantage of our previous research in this region, we provide an integrated view of the lithospheric structure and the uppermost mantle of the Tyrrhenian Basin, Apennines, Adriatic Sea and Dinarides. Our results show notable variations in both the crust and the base of the lithosphere. These variations are observed to be shallower beneath the basins and deeper beneath the mountain belts, particularly in areas with elevated topography. Additionally, our observations highlight the presence of two cold and dense zones situated in the distal margins of the Adria microplate, specifically beneath the Apennines and Dinarides. The thermal anomalies indicate the presence of two oppositely subducting slabs with different geometries and depth of penetration. Their current location, depth and shape have largely controlled the geodynamic evolution of the study region in the last 30 My. Key Points: We unveil the thermochemical structure of the lithosphere and uppermost mantle of the Adria Microplate and its marginsResults reveal mantle wedges aligning with Apenninic and Dinaric slabs, and cold sublithospheric anomalies beneath NE and SW Adria marginsIn N Apennines the slab is attached while a gap is observed in S Apennines. At Adria's NE margin, the slab penetrates deeper southward [ABSTRACT FROM AUTHOR]

Idiopathic granulomatous mastitis (IGM) is a rare, benign inflammatory breast disease. Corticosteroids and surgery are the primary treatment options, and a growing number of publications have shown the effectiveness of local steroid administration (intralesional injection and topical corticosteroids). However, less is known about the specific details and effects of this treatment approach. The purpose of this meta-analysis was to summarize the details and evaluate the efficacy of local steroid administration for IGM. The PubMed, Embase, Cochrane Library, and SinoMed databases were systematically searched from inception to July 2023 to identify relevant randomized controlled trials. The quality of the included studies was assessed, and meta-analysis and subgroup analysis were conducted to obtain the pooled effect sizes of the outcomes of interest. Eight trials comprising 613 patients were included. Local steroid administration included intralesional injection and topical steroid ointment, and control groups were mainly given systemic therapy (oral steroid) and surgical treatment. The meta-analysis showed that local steroid administration had a significant effect on the response rate (risk ratio [RR] = 1.35, 95% CI = [1.14-1.59], P = 0.0004). The incidence of side effects was also lower than that of systemic treatment (RR = 0.24, 95% CI = [0.13-0.43], P ＜0.0001). There was no difference in the recurrence rate (RR = 0.8, 95% CI = [1.42-1.51], P = 0.48). Local steroid administration can increase the RR and decrease the incidence of side effects for IGM patients. There is no significant difference in the recurrence rate between the local steroid administration group and the control group. Further studies are needed to identify the effect in different stages and among pregnant women. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is one of the deadliest tumours. This study aimed to construct radiogenomic prognostic models of glioblastoma overall survival (OS) based on magnetic resonance imaging (MRI) Gd-T1WI images and deoxyribonucleic acid (DNA) methylation-seq and to understand the related biological pathways. The ResNet3D-18 model was used to extract radiomic features, and Lasso-Cox regression analysis was utilized to establish the prognostic models. A nomogram was constructed by combining the radiogenomic features and clinicopathological variables. The DeLong test was performed to compare the area under the curve (AUC) of the models. We screened differentially expressed genes (DEGs) with original ribonucleic acid (RNA)-seq in risk stratification and used Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) annotations for functional enrichment analysis. For the 1-year OS models, the AUCs of the radiogenomic set, methylation set and deep learning set in the training cohort were 0.864, 0.804 and 0.787, and those in the validation cohort were 0.835, 0.768 and 0.651, respectively. The AUCs of the 0.5-, 1- and 2-year nomograms in the training cohort were 0.943, 0.861 and 0.871, and those in the validation cohort were 0.864, 0.885 and 0.805, respectively. A total of 245 DEGs were screened; functional enrichment analysis showed that these DEGs were associated with cell immunity. The survival risk-stratifying radiogenomic models for glioblastoma OS had high predictability and were associated with biological pathways related to cell immunity. [ABSTRACT FROM AUTHOR]

Light-induced electron transfer can broaden the substrate range of metalloenzyme. However, the efficiency of photo-enzyme coupling is limited by the poor combination of photosensitizer or photocatalyst with enzyme. Herein, we prepared the nano-photocatalyst MIL-125-NH 2 @Ru(bpy) by in site embedding ruthenium pyridine-diimine complex [Ru(bpy) 3 ]2+ into metal organic frameworks MIL-125-NH 2 and associated it with multicopper oxidase (MCO) laccase. Compared to [Ru(bpy) 3 ]2+, the coupling efficiency of MIL-125-NH 2 @Ru(bpy) 3 for enzymatic oxygen reduction increased by 35.7%. A series of characterizations confirmed that the amino group of laccase formed chemical bonds with the surface defects or hydrophobic groups of MIL-125-NH 2 @Ru(bpy) 3. Consequently, the tight binding accelerated the quenching process and electron transfer between laccase and the immobilized ruthenium pyridine-diimine complex. This work would open an avenue for the synthesis of MOFs photocatalyst towards photo-enzyme coupling. [ABSTRACT FROM AUTHOR]

A single-component Ca 7 Mg 2 (PO 4) 6 :Dy3+, Eu3+ white-emitting phosphor was synthesized by a sol-gel approach. The effects of the amounts of Dy3+ ions and Eu3+ ions on the luminescence characteristics and crystal structure of Ca 7 Mg 2 (PO 4) 6 :Dy3+, Eu3+ were systematically investigated. The Ca 7 Mg 2 (PO 4) 6 :Dy3+, Eu3+ phosphors had a Ca 7 Mg 2 (PO 4) 6 structure with an R3c (161) space group. The Ca 7 Mg 2 (PO 4) 6 :Dy3+ phosphor showed emission peaks at both 484 nm (blue) and 576 nm (yellow), which led to the realization of white light. Furthermore, after codoping Eu3+ ions into the structure, a red emission peak (∼617 nm) appeared in the spectrum as a supplementary red component. A warm white light with a low correlated colour temperature (CCT) is obtained from Dy3+/Eu3+-codoped Ca 7 Mg 2 (PO 4) 6. The luminescence intensity at 483 K still reaches more than 73 % of that at 303 K. The packaged LEDs display a bright warm white light with CCT value and colour rendering index (CRI) of 3878 K and 86.7, respectively, which is comfortable for the human eye. With excellent luminescence performances, the white-emitting Ca 7 Mg 2 (PO 4) 6 :Dy3+, Eu3+ phosphor had a significant application potential in the w -LED field. [ABSTRACT FROM AUTHOR]

In recent years, Mixed-Integer Linear Programming (MILP)-based automatic tools have played a significant role in providing security evaluations of symmetric-key primitives. Differential and linear cryptanalysis are the two most important cryptographic techniques. Although some methods have conducted a great effort in exploiting MILP-aided tools in searching for differential (linear) characteristics, traditional methods still suffer from primitives with strong diffusion layers and large sizes, such as NOEKEON. Typically, searching for differential (linear) characteristics of such primitives is difficult, and the corresponding MILP models are too heavy to be solved efficiently. To this end, we propose a simple yet efficient approach to employ MILP to evaluate the security against differential and linear cryptanalysis of such primitives. The core of our approach is to reduce the complex problem to a set of simpler subproblems and obtain the optimal solution of the complex problem by combining all the subproblems. A subproblem is equivalent to searching for all differential (linear) characteristics with a fixed number of active S-boxes in each round. Furthermore, we design an elaborate algorithm consisting of three MILP-aided methods to solve various subproblems and adopt some techniques to improve efficiency further. Applying our new algorithm to three SPN primitives Serpent, NOEKEON and ASCON, we obtain the tightest security bounds against differential and linear cryptanalysis for all three primitives so far and find improved differential and linear characteristics for Serpent and NOEKEON. For Serpent, we improve the upper bound of the maximum probability of 7-round differential characteristics from |$2^{-71}$| to |$2^{-76}$| and find for the first time 7-round differential characteristics. For NOEKEON, our results show that there is no 9-round (10-round) differential (linear) characteristic with a probability (correlation) higher than |$2^{-128}$| (⁠|$2^{-64}$|⁠), whereas it needs 10 rounds (11 rounds) according to the previous results. In addition, we find an 8-round (9-round) differential (linear) characteristic with a probability (correlation) of |$2^{-127}$| (⁠|$2^{-60}$|⁠). For ASCON permutation, we provide for the first time an upper bound of the maximum probability (correlation) of 5-round differential (linear) characteristics as |$2^{-70}$| (⁠|$2^{-33}$|⁠). [ABSTRACT FROM AUTHOR]

A method for identifying vulnerable nodes in distribution networks is proposed, which is based on complex networks and optimized TOPSIS. This method aims to address the issues of one‐sided evaluation indicators and inaccurate indicator weights that are present in existing methods for identifying vulnerable nodes in distribution networks. Based on the theory of complex networks, a comprehensive set of vulnerability indicators for distribution network nodes is constructed by considering both the topology structure and system operation status of the distribution network. The TOPSIS comprehensive evaluation model for optimization is proposed to enhance the selection process of optimal and worst indicator values. The advantages and disadvantages of each indicator are characterized using Mahalanobis distance. The calculation of proximity is optimized by establishing a virtual negative ideal solution, which makes the identification of vulnerable nodes more reasonable. The simulation results demonstrate that this method is more effective in identifying vulnerable nodes in the power grid compared to traditional methods, and has significant practical applications. [ABSTRACT FROM AUTHOR]

Antimicrobial peptides (AMPs) are promising candidates for the development of new antibiotics due to their broad-spectrum activity against a range of pathogens. However, identifying AMPs through a huge bunch of candidates is challenging due to their complex structures and diverse sequences. In this study, we propose SenseXAMP, a cross-modal framework that leverages semantic embeddings of and protein descriptors (PDs) of input sequences to improve the identification performance of AMPs. SenseXAMP includes a multi-input alignment module and cross-representation fusion module to explore the hidden information between the two input features and better leverage the fusion feature. To better address the AMPs identification task, we accumulate the latest annotated AMPs data to form more generous benchmark datasets. Additionally, we expand the existing AMPs identification task settings by adding an AMPs regression task to meet more specific requirements like antimicrobial activity prediction. The experimental results indicated that SenseXAMP outperformed existing state-of-the-art models on multiple AMP-related datasets including commonly used AMPs classification datasets and our proposed benchmark datasets. Furthermore, we conducted a series of experiments to demonstrate the complementary nature of traditional PDs and protein pre-training models in AMPs tasks. Our experiments reveal that SenseXAMP can effectively combine the advantages of PDs to improve the performance of protein pre-training models in AMPs tasks. [ABSTRACT FROM AUTHOR]

In order to ensure the security of power grids and control the level of short-circuit currents, a multi-objective optimization method for power grid partitioning is proposed. This method takes into consideration both short-circuit currents and multi-scenario safety constraints. A power grid partitioning optimization model is established to achieve objectives such as minimizing disconnected lines, maximizing safety margins, and ensuring load balance in the main transformers. The model aims to satisfy constraints related to short-circuit current levels, base-case power flow, and N − 1 security. To address the significant deviation in the static security constraint model caused by large amounts of active power losses in large-scale power grids, an improved direct current model is proposed to reduce these errors and meet the accuracy requirements for grid partitioning optimization. Additionally, to adapt to the variability of renewable energy output, an optimization method is proposed, combining three scenarios of renewable energy generation while satisfying short-circuit current and static security constraints. The power grid partitioning model is mathematically formulated as a large-scale mixed-integer linear programming problem, which presents challenges in terms of hardware requirements and computational complexity when solved directly. To mitigate these challenges, equivalent WARD values are assigned to the short-circuit current constraints, base-case constraints, and anticipated fault-induced power flow constraints. Anticipated faults and bottleneck branches are accurately incorporated, and the problem is decomposed into smaller-scale mixed-integer linear programming problems, solved in a stepwise iterative manner. This approach significantly improves computational efficiency and meets the requirements of practical large-scale power grid applications. To validate the proposed model and algorithm, a simulation program is developed using C++, and a simulation analysis of a regional transmission network is conducted. The program ensures the correctness of the proposed model and demonstrates the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

A random fiber laser does not need a traditional resonant cavity and only uses the multiple scattering of disordered media to provide feedback to achieve laser output. Therefore, it has the advantages of a simple structure, narrow linewidth, and low noise and is particularly suitable for fiber optic sensors. This paper provides an introduction to the categories and corresponding principles of random fiber lasers. The research progress of random fiber lasers in the sensing field in recent years, including various aspects of random fiber lasers as low-noise light sources or sensitive elements for fiber sensing systems, is the main focus. Finally, the future development trend of random fiber lasers for optical fiber sensors is explored. [ABSTRACT FROM AUTHOR]

Simple Summary: The color of wool is an essential trait in sheep which plays a significant role in the textile industry. The color of wool is determined by the presence of various pigments, which can range from white to various shades of brown, gray, black, etc. Understanding the genetics behind wool color is crucial for selective breeding and producing desirable colors for different textile products. By studying the genetic basis of wool color, researchers can identify genes related to pigmentation and develop strategies to enhance or modify wool color. This knowledge contributes to the improvement of wool quality, diversification of textile options, and economic development in the wool industry. Wool color is controlled by a variety of genes. Although the gene regulation of some wool colors has been studied in relative depth, there may still be unknown genetic variants and control genes for some colors or different breeds of wool that need to be identified and recognized by whole genome resequencing. Therefore, we used whole genome resequencing data to compare and analyze sheep populations of different breeds by population differentiation index and nucleotide diversity ratios (Fst and θπ ratio) as well as extended haplotype purity between populations (XP-EHH) to reveal selection signals related to wool coloration in sheep. Screening in the non-white wool color group (G1 vs. G2) yielded 365 candidate genes, among which PDE4B, GMDS, GATA1, RCOR1, MAPK4, SLC36A1, and PPP3CA were associated with the formation of non-white wool; an enrichment analysis of the candidate genes yielded 21 significant GO terms and 49 significant KEGG pathways (p < 0.05), among which 17 GO terms and 21 KEGG pathways were associated with the formation of non-white wool. Screening in the white wool color group (G2 vs. G1) yielded 214 candidate genes, including ABCD4, VSX2, ITCH, NNT, POLA1, IGF1R, HOXA10, and DAO, which were associated with the formation of white wool; an enrichment analysis of the candidate genes revealed 9 significant GO-enriched pathways and 19 significant KEGG pathways (p < 0.05), including 5 GO terms and 12 KEGG pathways associated with the formation of white wool. In addition to furthering our understanding of wool color genetics, this research is important for breeding purposes. [ABSTRACT FROM AUTHOR]

The rising global diabetic population has ignited significant interest in enzyme-free electrochemical glucose sensors. However, their widespread usage has been severely impeded by the lack of sensing probes with both high sensitivity and stability. In this work, we present a novel approach for conformally depositing a Ni–Mo–Nb metallic-glass film onto a three-dimensional printed polymer skeleton for glucose detection. The printing template is designed based on a six-membered tricapped trigonal prism (6M-TTP) structure, which is derived from a medium-range order structure motif observed in amorphous alloys. The fabricated composite combines the high electrochemical activity of Ni–Mo–Nb amorphous alloy with the stability afforded by the micro-nano lattice structure, resulting in a high sensitivity (482 ​μA mM−1cm−2), a wide linear range (0–1 ​mM and 1–5 ​mM), a low detection limit (2.94 ​μM), and good long-term stability and selectivity in alkaline solution. Our work has proposed a new avenue to fabricate complex micro-nano electrodes, potentially offering significant versatility and great promise for widespread applications in the field of electrochemistry. [ABSTRACT FROM AUTHOR]

Simple Summary: Wool is a very important agricultural product and an ideal raw material for the production of high-quality textiles and clothing. In addition, the wool industry provides important support for economic development and the livelihoods of rural communities, creating employment opportunities and sources of income for farmers. Whole-genome sequencing technology has important applications in the study of genetic diversity, population structure, and selection pressure in the sheep genome. In this study, we analyzed the population structure and genomic differences of eight breeds. In addition, we identified a series of candidate genes that may be related to hair follicle development, wool traits, lipid metabolism, and androgen metabolism. This study provides valuable genomic resources and a theoretical basis for future wool improvement. Wool fineness affects the quality of wool, and some studies have identified about forty candidate genes that affect sheep wool fineness, but these genes often reveal only a certain proportion of the variation in wool thickness. We further explore additional genes associated with the fineness of sheep wool. Whole-genome resequencing of eight sheep breeds was performed to reveal selection signals associated with wool fineness, including four coarse wool and four fine/semi-fine wool sheep breeds. Multiple methods to reveal selection signals (Fst and θπ Ratio and XP-EHH) were applied for sheep wool fineness traits. In total, 269 and 319 genes were annotated in the fine wool (F vs. C) group and the coarse wool (C vs. F) group, such as LGR4, PIK3CA, and SEMA3C and NFIB, OPHN1, and THADA. In F vs. C, 269 genes were enriched in 15 significant GO Terms (p < 0.05) and 38 significant KEGG Pathways (p < 0.05), such as protein localization to plasma membrane (GO: 0072659) and Inositol phosphate metabolism (oas 00562). In C vs. F, 319 genes were enriched in 21 GO Terms (p < 0.05) and 16 KEGG Pathways (p < 0.05), such as negative regulation of focal adhesion assembly (GO: 0051895) and Axon guidance (oas 04360). Our study has uncovered genomic information pertaining to significant traits in sheep and has identified valuable candidate genes. This will pave the way for subsequent investigations into related traits. [ABSTRACT FROM AUTHOR]

Zeolites are porous materials with plentiful and adjustable pore structures, which are widely applied in various fields such as fossil fuel energy conversion, preparation of clean energy, chemical product conversion, CO2 capture, VOC treatment, and so on. Zeolites exhibited advantageous adsorption compared with traditional adsorbents such as activated carbon; in addition, they can also provide abundant reaction sites for various molecules. The chemical composition, structural acidity, and distribution of pore size can distinctly affect the efficiency of the reaction. The modification of zeolite structure, the development of novel and efficient preparation methods, as well as the improvement of reaction efficiency, have always been the focus of research for zeolites. [ABSTRACT FROM AUTHOR]

The characteristic absorption spectra of three positional isomers of hydroxybenzoic acid are measured using a terahertz time-domain spectroscopy system (THz-TDS) in the 0.6–2.0 THz region at room temperature. Significant differences in their terahertz spectra are discovered, which indicates that THz-TDS is an effective means to identify positional isomers. In order to simulate their spectra, the seven molecular clusters of 2-, 3-, and 4-hydroxybenzoic acid (2-, 3-, and 4-HA) are calculated using the DFT-D3 method. Additionally, the potential energy distribution (PED) method is used to analyze their vibration modes. The analysis indicates that the vibration modes of 2-HA are mainly out-of-plane angle bending and bond angle bend in plane. The vibration modes of 3-HA are mainly bond length stretch and dihedral angle torsion. The vibration modes of 4-HA are mainly bond angle bend in plane and dihedral angle torsion. Interaction region indicator (IRI) analysis is used to visualize the location and type of intermolecular interactions in 2-, 3-, and 4-HA crystals. The results show that the weak interaction type of 2-, 3-, and 4-HA is dominated by van der Waals (vdW) interaction. Therefore, we can confirm that terahertz spectroscopy detection technology can be used as an effective means to identify structural isomers and detect the intermolecular interactions in these crystals. In addition, it can explain the absorption mechanism of terahertz waves interacting with matter. [ABSTRACT FROM AUTHOR]

Due to large specific surface area, abundant functional groups and low cost, biochar is widely used for pollutant removal. The adsorption performance of biochar is related to biochar synthesis and adsorption parameters. But the influence factor is numerous, the traditional experimental enumeration is powerless. In recent years, machine learning has been gradually employed for biochar, but there is no comprehensive review on the whole process regulation of biochar adsorbents, covering synthesis optimization and adsorption modeling. This review article systematically summarized the application of machine learning in biochar adsorbents from the perspective of all-round regulation for the first time, including the synthesis optimization and adsorption modeling of biochar adsorbents. Firstly, the overview of machine learning was introduced. Then, the latest advances of machine learning in biochar synthesis for pollutant removal were summarized, including prediction of biochar yield and physicochemical properties, optimal synthetic conditions and economic cost. And the application of machine learning in pollutant adsorption by biochar was reviewed, covering prediction of adsorption efficiency, optimization of experimental conditions and revelation of adsorption mechanism. General guidelines for the application of machine learning in whole-process optimization of biochar from synthesis to adsorption were presented. Finally, the existing problems and future perspectives of machine learning for biochar adsorbents were put forward. We hope that this review can promote the integration of machine learning and biochar, and thus light up the industrialization of biochar. Highlights: All-round regulation of biochar by machine learning (ML) was reviewed for the first time. Optimization of pyrolysis process and cost assessment by ML were summarized. Modeling of pollutant adsorption via ML was reviewed. General guidelines of ML for biochar pyrolysis and pollutant adsorption were proposed. Challenges and perspectives of ML for biochar adsorbents were put forward. [ABSTRACT FROM AUTHOR]

With the dangerous and troublesome nature of hollow defects inside building structures, hollowness inspection has always been a challenge in the field of construction quality assessment. Several methods have been proposed for inspecting hollowness inside concrete structures. These methods have shown great advantages compared to manual inspection but still lack autonomy and have several limitations. In this paper, we propose a range-point migration-based non-contact hollowness inspection system with sensor fusion of ultra-wide-band radar and laser-based depth camera to extract both outer surface and inner hollowness information accurately and efficiently. The simulation result evaluates the performance of the system based on the original range-point migration algorithm, and our proposed one and the result of our system show great competitiveness. Several simulation experiments of structures that are very common in reality are carried out to draw more convincing conclusions about the system. At the same time, a set of laboratory-made concrete components were used as experimental objects for the robotic system. Although still accompanied by some problems, these experiments demonstrate the availability of an automated hollow-core detection system. [ABSTRACT FROM AUTHOR]

Optical fiber interferometric magnetic field sensors based on magnetostrictive effects have several advantages, e.g., high sensitivity, strong adaptability to harsh environments, long distance transmission, etc. They also have great application prospects in deep wells, oceans, and other extreme environments. In this paper, two optical fiber magnetic field sensors based on iron-based amorphous nanocrystalline ribbons and a passive 3 × 3 coupler demodulation system were proposed and experimentally tested. The sensor structure and the equal-arm Mach–Zehnder fiber interferometer were designed, and the experimental results showed that the magnetic field resolutions of the optical fiber magnetic field sensors with sensing length of 0.25 m and 1 m were 15.4 nT/√Hz @ 10 Hz and 4.2 nT/√Hz @ 10 Hz, respectively. This confirmed the sensitivity multiplication relationship between the two sensors and the feasibility of improving the magnetic field resolution to the pT level by increasing the sensing length. [ABSTRACT FROM AUTHOR]

The capacity is an important parameter in multidimensional linear attack. In this paper, we firstly explore the distribution of the key-dependent capacity. Based on the magnitude of the correlation contributions, we divide the linear approximations subspace into two sets: one set consists of the strong linear approximations, and the other set consists of the weak linear approximations. We construct two statistics using the linear approximations in the two sets, respectively. Under reasonable assumptions, both of the two statistics follow Gamma distribution. Thus, the capacity is the sum of two statistics that follow Gamma distribution. Secondly, the accuracy of the model is verified by experiments on SMALLPRESENT[4]. Our experimental results show that this model can estimate the variance of the key-dependent capacity more accurately. Thus, we obtain more precise knowledge of the data complexity of the multidimensional linear attack. We derive the upper bound of the data complexity for multidimensional linear attack. Finally, based on our theoretical results, we explore the data complexity of Cho's multidimensional linear attack on PRESENT. Our results are the smallest data complexity for the same round attack so far. [ABSTRACT FROM AUTHOR]

Solving the dendrite growth problem is critical for the development of lithium metal anode for high‐capacity batteries. In this work, a machine learning force field model in combination with a self‐consistent continuum solvation model is used to simulate the morphology evolution of dendrites in a working electrolyte environment. The dynamic evolution of the dendrite morphology can be described in two stages. In the first stage, the energy reduction of the surface atoms induces localized reorientation of the originally single‐crystal dendrite and the formation of multiple domains. In the second stage, the energy reduction of internal atoms drives the migration of grain boundaries and the slipping of crystal domains. The results indicate that the formation of multiple domains might help to stabilize the dendrite, as a higher temperature trajectory in a single crystal dendrite without domains shows a higher dendrite collapsing rate. Several possible modes of morphological evolutions are also investigated, including surface diffusion of adatoms and configuration twists from [100] exposed surfaces to [110] exposed surfaces. In summary, reducing the surface and grain boundary energy drives the morphology evolution. Based on the analysis of these driving forces, some guidelines are suggested for designing a more stable lithium metal anode. [ABSTRACT FROM AUTHOR]

Simple Summary: At present, the immunotherapy and immune microenvironment of bladder cancer have attracted more and more attention from clinicians and researchers. In this study, the high expression of SULF2 by RNA sequencing of tissues from 90 bladder cancer patients was associated with poor prognosis in patients. We further found that a high expression of SULF2 can promote the polarization of macrophages to M2. In mechanistic studies, we found that SULF2 can promote the secretion of IL-8 through Wnt/β-catenin. IL-8 promotes the transcription of CD163 and CD206 in the microenvironment, ultimately leading to the polarization of macrophages to M2 macrophages. This study elucidates the effect of SULF2 on the polarization of macrophages in the tumor microenvironment. Sulfatase 2 (SULF2) affects the occurrence and development of cancer by regulating HSPG-binding factors. However, the mechanism of SULF2 in bladder cancer (BCa) is unknown. To determine this, we analyzed the RNA sequencing of 90 patients with BCa. The results showed that the expression of SULF2 was closely related to the prognosis of BCa. Moreover, in vivo and in vitro experiments revealed that SULF2 promotes tumor proliferation and invasion. Furthermore, using a mouse orthotopic BCa model and flow cytometric analysis, we identified that SULF2 affects the polarization of macrophages. Mechanism studies clarified that SULF2 promoted the release of HSPG-binding factors, such as IL-8, in the microenvironment through β-catenin. Meanwhile, IL-8 activated the JAK2/STAT3 pathway of macrophages to promote the expression of CD163 and CD206, thereby regulating the polarization of macrophages to the M2-type. Conclusively, these results indicate that SULF2 plays an important role in regulating the microenvironment of BCa and promotes the polarization of macrophages to the M2-type by secreting IL-8, which further deepens the malignant progression of BCa. [ABSTRACT FROM AUTHOR]

The impacts of the ice-crystal size distribution shape parameter (μi) were considered in the two-moment bulk cloud microphysics scheme of the Community Atmosphere Model Version 6 (CAM6). The μi 's impact on the statistical mean radii of ice crystals can be analyzed based on their calculating formulas. Under the same mass (qi) and number (Ni), the ratios of the mass-weighted radius (Rqi , not related to μi) to other statistical mean radii (e.g., effective radiative radius) are completely determined by μi. Offline tests show that μi has a significant impact on the cloud microphysical processes owing to the μi -induced changes in ice-crystal size distribution and statistical mean radii (excluding Rqi). Climate simulations show that increasing μi would lead to higher qi and lower Ni in most regions, and these impacts can be explained by the changes in cloud microphysical processes. After increasing μi from 0 to 5, the longwave cloud radiative effect increases (stronger warming effect) by 5.58 W m -2 (25.11 %), and the convective precipitation rate decreases by - 0.12 mm d -1 (7.64 %). In short, the impacts of μi on climate simulations are significant, and the main influence mechanisms are also clear. This suggests that the μi -related processes deserve to be parameterized in a more realistic manner. [ABSTRACT FROM AUTHOR]

In this study, the terahertz (THz) spectra of C3S were obtained in the 0.4–2.3 THz frequency range using different sample preparation methods. In the spectra, a sharp absorption peak of C3S was found at 2.03 THz. Under controlled conditions, the mass ratio of C3S was the most critical factor affecting the strength of the absorption peak, and the absorption coefficient followed the Beer–Lambert law, exhibiting a linear relationship with the mass ratio of C3S. The intrinsic dielectric constants of C3S and polyethylene (PE) were calculated in accordance with the Maxwell–Garnett (MG), Bruggeman (BM), and Landau–Lifshitz–Loovenga (LLL) models, using two-phase composite samples. The results show that the LLL model had the highest accuracy. [ABSTRACT FROM AUTHOR]

Metamaterials such as architected lattice structures have aroused broad interest in being applied as mechanical supports for their lightweight and custom-shaped capabilities. Although various prior efforts have been devoted, a multiscale fabrication of micro-nano lattice structures without penalizing the mechanical properties is still a challenging but highly desirable task. Here we put forward a strategy to produce a mechanically enhanced micro-nano lattice structure by conformally depositing a CoCrFeNiTi high-entropy alloy (HEA) coating layer onto a three-dimensional (3D) printed polymer skeleton. The template for the 3D printing employs a six-membered tricapped trigonal prism (6M-TTP) structure derived from a medium-range order structure motif in amorphous alloys. The topological complexity of the 6M-TTP can substantially avoid the stress concentration by offering stress-release channels, while the HEA film incorporating with amorphous and nanocrystalline constituents can further reinforce the lattice architecture through its size hardening effect. Benefitting from the above, the fabricated polymer/HEA-hybrid lattice exhibits a high specific compressive strength (∼0.055 ​MPa ​kg-1 m3 at a density below 500 ​kg ​m-3), a superior elastic recoverability (∼70% recovery rate under >30% compression), an enhanced plasticity (40% strain) and a high specific modulus (0.135 ​MPa ​kg-1 m3). Our strategy initiates a perspective way to fabricate multiscale micro-nano lattice structures with improved mechanical properties, which could be extended to widespread metamaterial research. [ABSTRACT FROM AUTHOR]

This study presents a geophysical‐geochemical integrated model of the thermochemical structure of the lithosphere and uppermost mantle along a transect from the Northern Tyrrhenian Sea to the Pannonian Basin, crossing the northern Apennines, the Adriatic Sea, and the Dinarides fold‐thrust belt. The objectives are to image crustal thickness variations and characterize the different mantle domains. In addition, we evaluate the topographic response of opposed subductions along this transect and discuss their implications in the evolution of the region. Results show a more complex structure and slightly higher average crustal density of Adria compared to Tisza microplate. Below the Tyrrhenian Sea and Western Apennines, Moho lays at <25 km depth while along the Eastern Apennines it is as deep as 55 km. The modeled lithosphere‐asthenosphere boundary (LAB) below the Tyrrhenian Sea and Pannonian Basin is flat lying at ∼75 and 90 km, respectively. Below the External Apennines and Dinarides the LAB deepens to 150 km, slightly shallowing toward the Adriatic foreland basin at 125 km depth. Our results are consistent with the presence of two mantle wedges, resulting from the rollback of the Ligurian‐Tethys and Vardar‐NeoTethys oceanic slabs followed by continental mantle delamination of the eastern and western distal margins of Adria. These two opposed slabs beneath the Apennines and Dinarides are modeled as two thermal sublithospheric anomalies of −200°C. Most of the elevation along the profile is under thermal isostasy and departures can be explained by regional isostasy with an elastic thickness between 10 and 20 km. Plain Language Summary: This study integrates a wide range of geological and geophysical observations (e.g., elevation, gravity, geoid, seismic tomography) to investigate the density and temperature variations down to 400 km along a transect that extends from the Tyrrhenian Sea and northern Apennines in Italy to the Dinarides and Pannonian Basin in southern Europe. The main objectives are to study the present‐day structure and composition of the lithosphere and uppermost mantle, and to evaluate the resulting topography, and finally to discuss their implications in the tectonic evolution of the region. Our results show that the crust and the base of the lithosphere vary significantly in the study region, lying shallow below the basins to much deeper underneath the mountain belts where topography is higher. We also observe two cold and dense zones sitting in the distal margins of the Adria microplate, beneath the northern Apennines and Dinarides, that are interpreted as two opposed subducting slabs that have largely controlled the geodynamic evolution of the study region in the last 30 My. Key Points: A new thermochemical structure of the crust and uppermost mantle is obtained along the northern Apennines, Dinarides, and Pannonian BasinThe model distinguishes Adria and Tisza microplates with different crustal structures and lithosphere mantle compositionsTwo mantle wedges occur below the northern Apennines and Dinarides, resulting from the mantle delamination of Adria beneath its margins [ABSTRACT FROM AUTHOR]

Intervertebral disc degeneration is the main cause of low back pain. Traditional treatment methods cannot repair degenerated intervertebral disc tissue. The emergence of stem cell therapy makes it possible to regenerate and repair degenerated intervertebral disc tissue. At present, mesenchymal stem cells are the most studied, and different types of mesenchymal stem cells have their own characteristics. However, due to the harsh and complex internal microenvironment of the intervertebral disc, it will affect the biological behaviors of the implanted mesenchymal stem cells, such as viability, proliferation, migration, and chondrogenic differentiation, thereby affecting the therapeutic effect. This review is aimed at summarizing the influence of each intervertebral disc microenvironmental factor on the biological behavior of mesenchymal stem cells, so as to provide new ideas for using tissue engineering technology to assist stem cells to overcome the influence of the microenvironment in the future. [ABSTRACT FROM AUTHOR]

Colon cancer is the most common malignant tumor of the gastrointestinal tract, and approximately 80%–90% of colon cancers are colon adenocarcinomas (COADs). This study aimed to screen key microRNAs (miRNAs) associated with COAD. Differentially expressed (DE) miRNAs were screened between COAD and adjacent cancer samples based on the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas obtained from datasets. The miRNAs of interest were validated using quantitative real-time polymerase chain reaction. Moreover, the effects of hsa-miR-135b-5p on the biological behavior of COAD cells were observed. To obtain the target genes of hsa-miR-135b-5p, transcriptome sequencing of the SW480 cells was performed, followed by protein-protein interaction (PPI) network and hsa-miR-135b-5p-target gene regulatory network construction and prognostic analysis. Downregulation of hsa-miR-135b-5p significantly inhibited SW480 cell proliferation, migration, and invasion and significantly facilitated apoptosis (P  < 0.05). A total of 3384 DEmRNAs were screened, and enrichment analysis showed that the upregulated mRNAs were enriched in 25 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 326 Gene Ontology Biological Processes (GO-BPs) while the downregulated mRNAs were enriched in 20 KEGG pathways and 276 GO-BPs. A PPI network was then constructed, and H2BC14, H2BC3, and H4C11 had a higher degree. In addition, a total of 352 hsa-miR-135b-5p-gene regulatory relationships were identified. Prognostic analysis showed that FOXN2 , NSA2 , MYCBP , DIRAS2 , DESI1 , and RAB33B had prognostic significance (P  < 0.05). In addition, the validation analysis results showed that FOXN2 , NSA2 , and DESI1 were significantly expressed between the miR-135b-5p-inhibitor and negative control groups (P  < 0.05). Therefore, downregulation of hsa-miR-135b-5p inhibits cell proliferation, migration, and invasion in COAD, and carcinogenesis may function by targeting FOXN2 , NSA2 , MYCBP , DIRAS2 , DESI1 , and RAB33B. [ABSTRACT FROM AUTHOR]

Colon cancer is the most common malignant tumor of the gastrointestinal tract, and approximately 80%–90% of colon cancers are colon adenocarcinomas (COADs). This study aimed to screen key microRNAs (miRNAs) associated with COAD. Differentially expressed (DE) miRNAs were screened between COAD and adjacent cancer samples based on the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas obtained from datasets. The miRNAs of interest were validated using quantitative real-time polymerase chain reaction. Moreover, the effects of hsa-miR-135b-5p on the biological behavior of COAD cells were observed. To obtain the target genes of hsa-miR-135b-5p, transcriptome sequencing of the SW480 cells was performed, followed by protein-protein interaction (PPI) network and hsa-miR-135b-5p-target gene regulatory network construction and prognostic analysis. Downregulation of hsa-miR-135b-5p significantly inhibited SW480 cell proliferation, migration, and invasion and significantly facilitated apoptosis (P  < 0.05). A total of 3384 DEmRNAs were screened, and enrichment analysis showed that the upregulated mRNAs were enriched in 25 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 326 Gene Ontology Biological Processes (GO-BPs) while the downregulated mRNAs were enriched in 20 KEGG pathways and 276 GO-BPs. A PPI network was then constructed, and H2BC14, H2BC3, and H4C11 had a higher degree. In addition, a total of 352 hsa-miR-135b-5p-gene regulatory relationships were identified. Prognostic analysis showed that FOXN2, NSA2, MYCBP, DIRAS2, DESI1, and RAB33B had prognostic significance (P  < 0.05). In addition, the validation analysis results showed that FOXN2, NSA2, and DESI1 were significantly expressed between the miR-135b-5p-inhibitor and negative control groups (P  < 0.05). Therefore, downregulation of hsa-miR-135b-5p inhibits cell proliferation, migration, and invasion in COAD, and carcinogenesis may function by targeting FOXN2, NSA2, MYCBP, DIRAS2, DESI1, and RAB33B. [ABSTRACT FROM AUTHOR]

Despite impressive merits of complementary charge‐storage mechanisms for aqueous Zn‐ion hybrid micro‐supercapacitors (ZHMSCs), it remains a challenge to solve dendrite and parasitic reactions issues of Zn anodes. Herein, a kinetics‐boosted strategy of Zn2+ transport and desolvation of hydrated Zn2+ is proposed by engineering zwitterionic P(AM‐co‐SBMA) hydrogel electrolyte (PASHE) for highly reversible Zn plating/stripping. Mechanically robust and chemically anchored PASHE features zwitterionic groups for constructing ion migration channels and immobilizing water molecules, which accelerates Zn2+ migration for an ultrahigh transfer number (0.84) and alleviates water‐related parasitic reactions. Theoretical calculations combined with experimental results reveal that sulfobetaine sulfonate anions endow PASHE with improved desolvation kinetics and the ability to coordinate Zn2+ flux and electric field distributions at the electrolyte–electrode interface. Thus, Zn anodes exhibit excellent electrochemical performance involving high average coulombic efficiency of 99.4% in Zn|PASHE|Cu cell as well as high cumulative capacity of 2000 mAh cm−2 (20 mA cm−2, 1 mAh cm−2) and depth of discharge of 80.9% (20 mA cm−2, 10 mAh cm−2) in Zn|PASHE|Zn cells. Furthermore, ZHMSCs based on PASHE deliver excellent flexibility and cyclability for energy‐storage applications. This work provides useful insights on hydrogel electrolyte engineering for developing high‐performance Zn anodes and derived energy‐storage devices. [ABSTRACT FROM AUTHOR]

Colon cancer is the most common malignant tumor of the gastrointestinal tract, and approximately 80%–90% of colon cancers are colon adenocarcinomas (COADs). This study aimed to screen key microRNAs (miRNAs) associated with COAD. Differentially expressed (DE) miRNAs were screened between COAD and adjacent cancer samples based on the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas obtained from datasets. The miRNAs of interest were validated using quantitative real-time polymerase chain reaction. Moreover, the effects of hsa-miR-135b-5p on the biological behavior of COAD cells were observed. To obtain the target genes of hsa-miR-135b-5p, transcriptome sequencing of the SW480 cells was performed, followed by protein-protein interaction (PPI) network and hsa-miR-135b-5p-target gene regulatory network construction and prognostic analysis. Downregulation of hsa-miR-135b-5p significantly inhibited SW480 cell proliferation, migration, and invasion and significantly facilitated apoptosis (P  < 0.05). A total of 3384 DEmRNAs were screened, and enrichment analysis showed that the upregulated mRNAs were enriched in 25 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 326 Gene Ontology Biological Processes (GO-BPs) while the downregulated mRNAs were enriched in 20 KEGG pathways and 276 GO-BPs. A PPI network was then constructed, and H2BC14, H2BC3, and H4C11 had a higher degree. In addition, a total of 352 hsa-miR-135b-5p-gene regulatory relationships were identified. Prognostic analysis showed that FOXN2, NSA2, MYCBP, DIRAS2, DESI1, and RAB33B had prognostic significance (P  < 0.05). In addition, the validation analysis results showed that FOXN2, NSA2, and DESI1 were significantly expressed between the miR-135b-5p-inhibitor and negative control groups (P  < 0.05). Therefore, downregulation of hsa-miR-135b-5p inhibits cell proliferation, migration, and invasion in COAD, and carcinogenesis may function by targeting FOXN2, NSA2, MYCBP, DIRAS2, DESI1, and RAB33B. [ABSTRACT FROM AUTHOR]

A stabilized narrow-linewidth random fiber laser for strain detection, based on a three-grating ring (TGR) resonator and half-open-cavity structure, is proposed and investigated experimentally. The half-open-cavity structure proved to provide double optical gain of erbium-doped fiber, which was beneficial to increase the photon lifetime as well as further narrow the linewidth. Meanwhile, the stability and frequency noise of narrow lasing output was improved by suppressing the competition-induced undesired residual random lasing modes with the TGR resonator. The TGR resonator is composed of a double-cavity fiber Bragg grating Fabry–Perot (FBG-FP) interferometer, a section of single-mode fiber, and a circulator. The specially designed double-cavity FBG-FP interferometer embedded in the TGR resonator acted as the strain-sensing element and improved the resolution of the dynamic strain. A stable ultra-narrow linewidth of about 205 Hz was obtained. The frequency noise was reduced to about 2 Hz/√Hz. A high dynamic strain measuring resolution of 35 femto-strain (fε)/√Hz was achieved. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the application of deep learning combined with traditional radiomics methods for classifying enlarged cervical lymph nodes. Methods: The clinical and computed tomography (CT) imaging data of 276 patients with enlarged cervical lymph nodes (150 with lymph-node metastasis, 65 with lymphoma, and 61 with benign lymphadenopathy) who were treated at the hospital from January 2015 to January 2021 were retrospectively analysed. The patients were randomly divided into a training group and a test group at a ratio of 8:2. The radiomics features were extracted using one-by-one convolution and neural network activation, filtered with the least absolute shrinkage and selection operator (LASSO) model, and used to construct a discrimination model with PyTorch. Then, the performance of the model was compared with the radiologists' diagnostic performance. The neural network model was evaluated using the area under the receiver-operator characteristic curve (AUC), and the accuracy, sensitivity, and specificity were analysed. Results: A total of 102 features, comprising five traditional radiomic features and 97 deep learning features, were selected with LASSO and used to construct a discrimination model, which achieved a total accuracy of 87.50%. The AUC value, specificity, and sensitivity were, respectively, 0.92, 92.30%, and 90.00% for metastatic lymph nodes, 0.87, 95.45%, and 83.33% for benign lymphadenopathy, and 0.88, 90.47%, and 85.71% for lymphoma. The accuracies of the radiologists' diagnoses were 62.68% and 62.68%. The diagnostic performance of the model was significantly different from that of the radiologists (p < 0.05). Conclusion: CT-based deep learning combined with the traditional radiomics methods has a high diagnostic value for the classification of cervical enlarged lymph nodes. [ABSTRACT FROM AUTHOR]

Urological cancers are common malignant cancers worldwide, with annually increasing morbidity and mortality rates. For decades, two-dimensional cell cultures and animal models have been widely used to study the development and underlying molecular mechanisms of urological cancers. However, they either fail to reflect cancer heterogeneity or are time-consuming and labour-intensive. The recent emergence of a three-dimensional culture model called organoid has the potential to overcome the shortcomings of traditional models. For example, organoids can recapitulate the histopathological and molecular diversity of original cancer and reflect the interaction between cancer and surrounding cells or stroma by simulating tumour microenvironments. Emerging evidence suggests that urine-derived organoids can be generated, which could be a novel non-invasive liquid biopsy method that provides new ideas for clinical precision therapy. However, the current research on organoids has encountered some bottlenecks, such as the lack of a standard culture process, the need to optimize the culture medium and the inability to completely simulate the immune system in vivo. Nonetheless, cell co-culture and organoid-on-a-chip have significant potential to solve these problems. In this review, the latest applications of organoids in drug screening, cancer origin investigation and combined single-cell sequencing are illustrated. Furthermore, the development and application of organoids in urological cancers and their challenges are summarised. [ABSTRACT FROM AUTHOR]

Sleep is a highly intricate biological phenomenon, and its disorders play a pivotal role in numerous diseases. However, the specific regulatory mechanisms remain elusive. In recent years, the role of mitochondria in sleep disorders has gained considerable attention. Sleep deprivation not only impairs mitochondrial morphology but also decreases the number of mitochondria and triggers mitochondrial dysfunction. Furthermore, mitochondrial dysfunction has been implicated in the onset and progression of various sleep disorder-related neurological diseases, especially neurodegenerative conditions. Therefore, a greater understanding of the impact of sleep disorders on mitochondrial dysfunction may reveal new therapeutic targets for neurodegenerative diseases. In this review, we comprehensively summarize the recent key findings on the mechanisms underlying mitochondrial dysfunction caused by sleep disorders and their role in initiating or exacerbating common neurodegenerative diseases. In addition, we provide fresh insights into the diagnosis and treatment of sleep disorder-related diseases. • Sleep disorders play a pivotal role in numerous diseases; however, the specific regulatory mechanisms remain elusive. • Sleep deprivation causes aberrant mitochondrial morphology, decreases mitochondrial numbers, and induces various dysfunctions. • This review aims to summarize how sleep disorders cause mitochondrial dysfunction, thereby exacerbating neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

• Developed Semi-analytic Monte Carlo Method for solid rocket plume polarized radiation. • Simulated solid rocket plume polarized characteristics. • The effects of different light sources on the polarized characteristics of the plume were analyzed. Polarization optical detection has been widely used in the detection and identification of particle containing media such as clouds, aerosols, fire plumes, and volcanic smoke. Solid rocket plume is a typical high-temperature gas–solid two-phase medium. Polarization optical detection of solid rocket plume has attracted much attention in recent years. The polarized radiation transfer mechanism of solid rocket plume is complex, especially in the infrared band, with both the scattering radiation transfer from external incident light and the scattering radiation transfer from the high-temperature region inside the jet flame to the outside. The research on the polarization scattering characteristics of solid jet flame still needs to be further developed. Therefore, this study focuses on modeling the infrared polarization scattering mechanism and the simulation of polarization transfer characteristics of a solid rocket gas–solid two-phase plume, which can guide the usability analysis of solid rocket plume polarization detection. A novel model based on Semi-analytic Monte Carlo Method is proposed to simulate polarized radiation transfer of solid rocket plume. The wavelength and angle dependence of the self-radiation polarization characteristic of a solid rocket plume is simulated based on the proposed model. Note that the overall polarization degree of the plume shows wavelength selectivity and angle sensitivity at different wavelengths. The spatial distribution of polarization degree at 1.55 μm, 2.2 μm, and 2.75 μm shows that the plume edge's polarization degree is higher than the plume center. The findings suggest that the ratios of the relative contribution of self-radiation, direct solar radiation, and background polarization radiation components to the total polarization characteristics are 0.47 %, 70.50 %, 29.03 % at 1.55 μm and 20.43 %, 79.55 %, 0.02 % at 2.75 μm. [ABSTRACT FROM AUTHOR]

Quail, as an advantageous avian model organism due to its compact size and short reproductive cycle, holds substantial potential for enhancing our understanding of skeletal muscle development. The quantity of skeletal muscle represents a vital economic trait in poultry production. Unraveling the molecular mechanisms governing quail skeletal muscle development is of paramount importance for optimizing meat and egg yield through selective breeding programs. However, a comprehensive characterization of the regulatory dynamics and molecular control underpinning quail skeletal muscle development remains elusive. In this study, through the application of HE staining on quail leg muscle sections, coupled with preceding fluorescence quantification PCR of markers indicative of skeletal muscle differentiation, we have delineated embryonic day 9 (E9) and embryonic day 14 (E14) as the start and ending points, respectively, of quail skeletal muscle differentiation. Then, we employed whole transcriptome sequencing to investigate the temporal expression profiles of leg muscles in quail embryos at the initiation of differentiation (E9) and upon completion of differentiation (E14). Our analysis revealed the expression patterns of 12,012 genes, 625 lncRNAs, 14,457 circRNAs, and 969 miRNAs in quail skeletal muscle samples. Differential expression analysis between the E14 and E9 groups uncovered 3,479 differentially expressed mRNAs, 124 lncRNAs, 292 circRNAs, and 154 miRNAs. Furthermore, enrichment analysis highlighted the heightened activity of signaling pathways related to skeletal muscle metabolism and intermuscular fat formation, such as the ECM-receptor interaction, focal adhesion, and PPAR signaling pathway during E14 skeletal muscle development. Conversely, the E9 stage exhibited a prevalence of pathways associated with myoblast proliferation, exemplified by cell cycle processes. Additionally, we constructed regulatory networks encompassing lncRNA‒mRNA, miRNA‒mRNA, lncRNA‒miRNA-mRNA, and circRNA-miRNA‒mRNA interactions, thus shedding light on their putative roles within quail skeletal muscle. Collectively, our findings illuminate the gene and non-coding RNA expression characteristics during quail skeletal muscle development, serving as a foundation for future investigations into the regulatory mechanisms governing non-coding RNA and quail skeletal muscle development in poultry production. [ABSTRACT FROM AUTHOR]

The Ca 5 (PO 4) 2 SiO 4 :Eu3+ and Ca 5 (PO 4) 2 SiO 4 :Sm3+ phosphors were obtained via solid-state reaction, and A3+ (A = La, Bi) ions were further co-doped in the host for luminescence enhancement. The XRD results showed that the samples have a Ca 5 (PO 4) 2 SiO 4 structure with good crystallinity. The characteristic peaks of Ca 5 (PO 4) 2 SiO 4 :Eu3+, A3+ and Ca 5 (PO 4) 2 SiO 4 :Sm3+, A3+ phosphors severely appeared at 616 nm and 605 nm, which is originating from the 4f-4f transitions of Eu3+ and Sm3+ ions. Compared with Ca 4.8 (PO 4) 2 SiO 4 :0.2Eu3+, the luminescence intensity of Ca 4.8- y (PO 4) 2 SiO 4 :0.2Eu3+, y A3+ was increased by 1.34- and 1.65-fold with La3+/Bi3+ co-doping, respectively. And the luminescence intensity reached 1.77- and 1.49-fold that of Ca 4.9 (PO 4) 2 SiO 4 :0.1Sm3+ for Ca 4.9- y (PO 4) 2 SiO 4 :0.1Sm3+, y A3+, Meanwhile, Ca 4.7 (PO 4) 2 SiO 4 :0.2Eu3+, 0.1Bi3+ and Ca 4.75 (PO 4) 2 SiO 4 :0.1Sm3+, 0.15La3+ phosphors had excellent thermal stability and the luminescence intensity at 210 °C still maintained at 75.16% and 93.02% of that at room temperature. In addition, some w -LEDs were manufactured via mixing the as-prepared phosphor with others, which exhibited a white light with excellent chromaticity parameters (CCT = 4726 K, Ra = 89.3). All results manifested that the excellent Ca 5 (PO 4) 2 SiO 4 :Eu3+, Bi3+ phosphor was expected to be used as a red component in solid-state lighting devices. [ABSTRACT FROM AUTHOR]

The specific activities of 226Ra, 232Th and 40K of seven different color classification of nephrite samples from Xinjiang of China were measured by gamma spectrometry, and their radiological hazard indices such as radium equivalent (Raeq), external hazard index (Hex), internal hazard index (Hin), alpha index (Iα), absorbed dose rate (D) and annual effective dose rate (AED) were investigated and assessed. According to the experimental results, the specific activity level of 226Ra, 232Th, 40K in all nephrite samples was between 13.56 and 116.39 Bq·kg−1 with an average of 44.72 Bq·kg−1, between 2.19 and 10.89 Bq·kg−1 with an average of 4.90 Bq·kg−1, and between 21.06 and 94.32 Bq·kg−1 with an average of 52.24 Bq·kg−1, respectively. The mean values of radiological indicators, such as Raeq, Hex, Hin, Iα and AED were 55.75 Bq·kg−1, 0.15, 0.27, 0.22, 0.16 mSv·y-1 (worn) and 0.13 mSv·y−1 (indoor), respectively, are lower than the international recommended value. The values of D range from 10.13 to 54.46 nGy·h−1 with an average of 25.80 nGy·h−1. In the end, it can be concluded that the use of the seven different color categories of nephrites as ornament is considered to be safe and unlikely to cause any significant biological radiation hazard to the public. [ABSTRACT FROM AUTHOR]

Freight consolidation is a logistics practice that improves the cost-effectiveness and efficiency of transportation operations, and also reduces energy consumption and carbon footprint. A "fair" shipping cost-sharing scheme is indispensable to help establish and sustain the cooperation of a group of suppliers in freight consolidation. In this paper, we design a truthful acyclic mechanism to solve the cost-sharing problem in a freight consolidation system with one consolidation center and one common destination. Applying the acyclic mechanism, the consolidation center decides which suppliers' demands ship via the consolidation center and their corresponding cost shares based on their willingness to pay for the service. The proposed acyclic mechanism is designed based on bin packing solutions that are also strong Nash equilibria for a related noncooperative game. We study the budget-balance of the mechanism both theoretically and numerically. We prove a 2-budget-balance guarantee for the mechanism in general and better budget-balance guarantees under specific problem settings. Empirical tests on budget-balance show that our mechanism performs much better than the guaranteed budget-balance ratio. We also study the economic efficiency of our mechanism numerically to investigate its impact on social welfare under different conditions. [ABSTRACT FROM AUTHOR]

Laccase, as an important biocatalyst, has aroused wide public interests in the field of environment and catalysis. However, the application of laccase in large-scale is still limited due to its high solubility and poor stability. In order to improve the reusability of laccase, immobilization with functional materials has attracted increasing attention. Metal-organic frameworks (MOFs) stand out as a promising carrier for its high adsorption capacity and flexible structure. The present paper reviews the current status and remaining challenges in the immobilization of laccase with MOFs. Furthermore, three methods are proposed to further improve the immobilization of laccase with MOFs, including co-immobilization of laccase and mediator, co-immobilization of laccase and other enzymes, and coupling of biocatalysis with photochemical reactions. This work, as the first review article on the immobilization of laccase with MOFs, will provide a navigation map for the subsequent selection and design of MOFs for more targeted immobilization of laccase. [ABSTRACT FROM AUTHOR]

The dynamic roles of T cells in the immune system to recognize and destroy the infected or mutated cells render T cell therapy a prospective treatment for a variety of diseases including cancer, autoimmune diseases, and allograft rejection. However, the clinical applications of T cell therapy remain unsatisfactory due to the tedious manufacturing process, off-target cytotoxicity, poor cell persistence, and associated adverse effects. To this end, various biomaterials have been introduced to enhance T cell therapy by facilitating proliferation, enhancing local enrichment, prolonging retention, and alleviating side effects. This review highlights the design strategies of biomaterials developed for T cell expansion, enrichment, and delivery as well as their corresponding therapeutic effects. The prospects of biomaterials for enhancing T cell immunotherapy are also discussed in this review. [Display omitted] [ABSTRACT FROM AUTHOR]

Leukemia is a hematological malignancy associated with the uncontrolled proliferation of mutant progenitors, suppressing the production of normal blood cells. Current treatments, including chemotherapy, radiotherapy, and immunotherapy, still lead to unsatisfactory results with a 5 year survival rate of only 30–50%. The poor prognosis is related to both disease relapse and treatment-associated toxicity. Delivery strategies can improve the in vivo pharmacokinetics of drugs, navigating the therapeutics to target cells or the tumor microenvironment and reversing drug resistance, which maximizes tumor elimination and alleviates systematic adverse effects. This review discusses available FDA-approved anti-leukemia drugs and therapies with a focus on the advances in the development of anti-leukemia drug delivery systems. Additionally, challenges in clinical translation of the delivery strategies and future research opportunities in leukemia treatment are also included. [ABSTRACT FROM AUTHOR]

Stator axial pairing of tooth tips is proposed in this article to suppress the open-circuit dc winding induced voltage and torque pulsation in the wound field switched flux machine. In the proposed method, the stator is divided into two segments axially and these two segments have different arcs of tooth tip. The finite element analysis results show that the proposed technique can reduce the on-load torque ripple from 17.91% to 6.99%, reduce the peak-to-peak value of cogging torque by 90.66% from 5.14 N·m to 0.48 N·m, and reduce the peak-to-peak value of open-circuit dc winding induced voltage at 1500 r/min by 84.39% from 79.58 to 12.42 V. Although the efficiency of the paired machine is slightly reduced from 84.93% to 84.11%, the average electromagnetic torque does not deteriorate by more than 5%. The paired machine is prototyped and tested, and the experimental results validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, the direct current (dc) winding induced voltage in wound-field flux-switching machines is qualitatively analyzed with air-gap field modulation principle. Operation principle and effective harmonics of dc winding induced voltage are modelled and deduced. It is found that only air-gap field harmonics with specific spatial orders, which numerically equals to odd times of half stator poles, can contribute to dc winding induced voltage. Harmonic order of dc winding induced voltages under open-circuit only, armature reaction only, and on-load condition, are predicted for m-phase WFFS machines with any feasible stator/rotor pole number combinations. Different armature winding configurations, including concentrated winding and distributed winding, are also analyzed and compared using the winding factor. Finite element analysis is employed to verify the prediction results. Finally, a prototype is built and tested for validation. [ABSTRACT FROM AUTHOR]

Predicting urban traffic is of great importance to intelligent transportation systems and public safety, yet is very challenging in three aspects: 1) complex spatio-temporal correlations of urban traffic, including spatial correlations between locations along with temporal correlations among timestamps; 2) spatial diversity of such spatio-temporal correlations, which varies from location to location and depends on the surrounding geographical information, e.g., points of interests and road networks; and 3) temporal diversity of such spatio-temporal correlations, which is highly influenced by dynamic traffic states. To tackle these challenges, we proposed a deep meta learning based model, entitled ST-MetaNet $^+$ + , to collectively predict traffic in all locations at the same time. ST-MetaNet $^+$ + employs a sequence-to-sequence architecture, consisting of an encoder to learn historical information and a decoder to make predictions step by step. Specifically, the encoder and decoder have the same network structure, consisting of meta graph attention networks and meta recurrent neural networks, to capture diverse spatial and temporal correlations, respectively. Furthermore, the weights (parameters) of meta graph attention networks and meta recurrent neural networks are generated from the embeddings of geo-graph attributes and the traffic context learned from dynamic traffic states. Extensive experiments were conducted based on three real-world datasets to illustrate the effectiveness of ST-MetaNet $^+$ + beyond several state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Given that heterogeneous information networks (HIN) encompass nodes and edges belonging to different semantic types, they can model complex data in real-world scenarios. Thus, HIN embedding has received increasing attention, which aims to learn node representations in a low-dimensional space, in order to preserve the structural and semantic information on the HIN. In this regard, metagraphs, which model common and recurring patterns on HINs, emerge as a powerful tool to capture semantic-rich and often latent relationships on HINs. Although metagraphs have been employed to address several specific data mining tasks, they have not been thoroughly explored for the more general HIN embedding. In this paper, we leverage metagraphs to learn relationship-preserving HIN embedding in a self-supervised setting, to support various relationship mining tasks. In particular, we observe that most of the current approaches often under-utilize metagraphs, which are only applied in a pre-processing step and do not actively guide representation learning afterwards. Thus, we propose the novel framework of mg2vec, which learns the embeddings for metagraphs and nodes jointly. That is, metagraphs actively participates in the learning process by mapping themselves to the same embedding space as the nodes do. Moreover, metagraphs guide the learning through both first- and second-order constraints on node embeddings, to model not only latent relationships between a pair of nodes, but also individual preferences of each node. Finally, we conduct extensive experiments on three public datasets. Results show that mg2vec significantly outperforms a suite of state-of-the-art baselines in relationship mining tasks including relationship prediction, search and visualization. [ABSTRACT FROM AUTHOR]