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Simple Summary: The aim of this study was to evaluate the effect of conjugated linoleic acid on the milk fat globule size and the ruminal microbiome of goats. In the present study, we found that dietary conjugated linoleic acid supplementation significantly and dose-dependently decreased the milk fat content and fat globule size in Saanen dairy goats, accompanied by an increase in the proportion of small-sized fat globules. Moreover, the dairy goats occurred in parallel with significant changes in the relative abundance of some ruminal bacterial populations. The milk fat content and fat globule size were correlated with the relative abundance of some bacteria, including members of Firmicutes and Bacteroidetes. Notably, our study was the first to analyze the correlation between the ruminal microbiota and fat globule size. These results constitute the first evidence for explaining the mechanism underlying diet-induced fat globules from the perspective of the ruminal microbiome in dairy goats. The aim of this study was to evaluate the effect of conjugated linoleic acid (CLA) on milk fat globule (MFG) size and the ruminal microbiome of goats. Twenty-four mid-lactation Saanen dairy goats weighing 49 ± 4.5 kg (168 ± 27 d in milk, 1.2 ± 0.1 kg milk/d, 2–3 years old) were randomly divided into four groups—a control (CON) group, which was fed a basal diet, and three CLA supplementation groups, in which 30 g CLA (low-dose group, L-CLA), 60 g CLA (medium-dose group, M-CLA), or 90 g CLA (high-dose group, H-CLA) was added to the basal diet daily. The experiment lasted for 21 days, during which time goat milk was collected for composition and MFG size analysis. On day 21 of feeding, ruminal fluid was collected from the CON and H-CLA groups for analysis of the changes in microorganismal abundance. The results showed that CLA supplementation did not affect milk production, milk protein, or lactose content in the dairy goats (p > 0.05), but significantly reduced the milk fat content (p < 0.01) compared with the CON group. The CLA supplementation significantly decreased the D[3,2] and D[4,3] of the MFGs in a dose-dependent manner (p < 0.01). Moreover, dietary CLA inclusion increased the proportion of small-sized MFGs and decreased that of large-sized ones. The results of 16S rRNA gene sequencing showed that CLA-induced milk fat depression in dairy goats was accompanied by significant changes in the relative abundance of ruminal bacterial populations, most of which belonged to the Firmicutes and Bacteroidetes phyla. The relative abundance of Rikenellaceae_RC9_gut_group and Prevolellaceae_UCG-003 in Bacteroidetes and UCG-002, Succiniclasticum, and norank_f__norank_o__Clostridia_vadinBB60_group in Firmicutes was significantly higher in the CON group than in the H-CLA group. In contrast, the relative abundance of norank_f__UCG-011, norank_f_Eubacterium_coprostanoligenes_group, unclassified_f__Lachnospiraceae, and UCG-001 in Firmicutes and norank_f__Muribaculaceae in Bacteroidetes was significantly higher in the H-CLA group than in the CON group. Correlation analysis showed that the milk fat content was negatively correlated with the relative abundance of some bacteria, including members of Firmicutes and Bacteroidetes. Similarly, MFG size (D[3,2] and D[4,3]) was negatively correlated with several members of Firmicutes and Bacteroidetes, including Lachnospiraceae, norank_f__UCG-011, UCG-001, norank_f__Eubacterium_coprostanoligenes_group (Firmicutes), and norank_f__Muribaculaceae (Bacteroidetes), while positively correlated with the relative abundance of some members of Firmicutes and Bacteroidetes, including Mycoplasma, Succiniclasticum, norank_f__norank_o__Clostridia_vadinBB60_group, UCG-002 (Firmicutes), and Rikenellaceae_RC9_gut_group (Bacteroidetes). Overall, our data indicated that CLA treatment affected milk fat content and MFG size in dairy goats, and these effects were correlated with the relative abundance of ruminal bacterial populations. These results provide the first evidence to explain the mechanism underlying diet-induced MFG from the perspective of the ruminal microbiome in dairy goats. [ABSTRACT FROM AUTHOR]

Porous carbon derived from biomass is considered a promising material for supercapacitors. However, improving the wettability and electrical conductivity of porous carbon materials remains a great challenge. Herein, a bidirectional pore‐creating strategy is proposed to construct N/O‐doped Walnut‐shells‐based hierarchical porous carbon materials (WSC‐N/O‐900). The high specific surface area (981 m2 g−1) and heteroatom content of WSC‐N/O‐900 enhance the wettability and electrical conductivity. Thus, WSC‐N/O‐900 shows a high capacitance of 431 F g−1 at 1.0 A g−1. Additionally, the capacitance retention rate of WSC‐N/O‐900//WSC‐N/O‐900 (SSC) remains 88.4 % after 9000 cycles and achieves an energy density of 14.8 Wh kg−1 with a power density of 300 W kg−1. Overall, this work can provide an effective strategy to prepare advanced biomass derived porous carbon for electrochemical energy storage. [ABSTRACT FROM AUTHOR]

Abstract Background The tumor microenvironment is associated with prognosis in advanced non‐small cell lung carcinoma (NSCLC). The aim of this study was to explore the relationship between blood T cell diversity and survival of patients treated with pemetrexed‐based chemotherapy for nonsquamous NSCLC. Methods This prospective clinical study enrolled 26 patients with advanced NSCLC treated with 4–6 cycles of first‐line pemetrexed combined with platinum‐based therapy. The complementarity‐determining region 3 (CDR3) located in the T cell receptor beta chain (TCR β chain) was captured and deeply sequenced using next‐generation sequencing (NGS) technology, and the correlation between TCR changes and efficacy after chemotherapy was analyzed. Results Patients with an inferior quarter diversity index showed a significantly shorter progression‐free survival (PFS) than the others (median, 5.0 months vs. 8.1 months, P = 0.014). After two cycles of chemotherapy, the TCR diversity was significantly higher than the baseline (P = 0.034). Just as with the baseline, patients with an inferior quarter diversity index at the endpoint of cycle 2 showed a shorter progression‐free survival (PFS) than the others (median, 5.0 months vs. 8.4 months, P = 0.024). Conclusions In advanced NSCLC patients treated with first‐line pemetrexed combined with platinum, the low level of blood TCR diversity at baseline with an endpoint of two cycles of chemotherapy was correlated with a poor prognosis.

Simple Summary: Metastasis, the spread of cancer cells to other parts of the body, is the leading cause of cancer-related deaths despite medical advances. The current methods used to study metastatic cancer face challenges in gathering enough data. To tackle this issue, we developed MetGen, a deep learning model that generates metastatic gene expression files using cancer and tissue samples. Our results show that the proposed model generated samples comparable to real data. The interpretability of the model could help researchers better understand cancer metastasis and lead to the discovery of new treatments to combat metastatic cancer. Despite significant advances in tumor biology and clinical therapeutics, metastasis remains the primary cause of cancer-related deaths. While RNA-seq technology has been used extensively to study metastatic cancer characteristics, challenges persist in acquiring adequate transcriptomic data. To overcome this challenge, we propose MetGen, a generative contrastive learning tool based on a deep learning model. MetGen generates synthetic metastatic cancer expression profiles using primary cancer and normal tissue expression data. Our results demonstrate that MetGen generates comparable samples to actual metastatic cancer samples, and the cancer and tissue classification yields performance rates of 99.8 ± 0.2% and 95.0 ± 2.3%, respectively. A benchmark analysis suggests that the proposed model outperforms traditional generative models such as the variational autoencoder. In metastatic subtype classification, our generated samples show 97.6% predicting power compared to true metastatic samples. Additionally, we demonstrate MetGen's interpretability using metastatic prostate cancer and metastatic breast cancer. MetGen has learned highly relevant signatures in cancer, tissue, and tumor microenvironments, such as immune responses and the metastasis process, which can potentially foster a more comprehensive understanding of metastatic cancer biology. The development of MetGen represents a significant step toward the study of metastatic cancer biology by providing a generative model that identifies candidate therapeutic targets for the treatment of metastatic cancer. [ABSTRACT FROM AUTHOR]

With the rapid increase in smart grid users and the increasing cost of user data transmission, proposing an encryption method that does not increase the construction cost while increasing the user ceiling has become the focus of many scholars. At the same time, the increase in users will also lead to more security problems, and it is also necessary to solve the privacy protection for users during information transmission. In order to solve the above problems, this paper proposes an aggregated ring encryption scheme based on the SM2 algorithm with special features, referred to as SM2-CLARSC, based on the certificateless ring signcryption mechanism and combining with the aggregate signcryption. SM2-CLARSC is designed to satisfy the basic needs of the smart grid, and it can be resistant to replay attacks, forward security and backward security, etc. It has better security and higher efficiency than existing solutions. Comparing SM2-CLARSC with existing typical solutions through simulation, the result proves that this solution has more comprehensive functions, higher security, and significant computational efficiency improvement. [ABSTRACT FROM AUTHOR]

The automotive air conditioning (AC) electromagnetic clutch plays a crucial role in accurately controlling power transmission between the engine and the compressor, ensuring the proper operation of the AC system. The aim of this paper is to provide high-quality experimental data for researchers who are interested in simulating the dynamic process of an AC electromagnetic clutch and also to assess the adaptiveness of empirical equations to describe the AC electromagnetic clutch performance that is limited in discussion in existing studies. In this study, an automotive AC electromagnetic clutch characteristic test system was employed along with an infrared (IR) camera to conduct comprehensive experimental analyses. The test system enabled the evaluation of various parameters, including the clutch torque output, compressor exhaust pressure, and temperature of the friction surface. The results revealed that the torque and exhaust pressure were closely associated with the on/off time and rotational speed, with a peak value observed around 3000 rpm. Additionally, longer break-in time, higher rotational speeds, and shorter on/off time led to varying increases in the temperature of the friction surface. These findings provided a theoretical foundation for optimizing the design and control of automotive AC electromagnetic clutches. By enhancing design or adjusting control strategies, these clutches can better handle high-load and high-frequency working conditions. [ABSTRACT FROM AUTHOR]