Immunotherapy in liver cancer: overcoming the tolerogenic liver microenvironment.

Liver cancer is a major global health concern, ranking among the top causes of cancer-related deaths worldwide. Despite advances in medical research, the prognosis for liver cancer remains poor, largely due to the inherent limitations of current therapies. Traditional treatments like surgery, radiation, and chemotherapy often fail to provide long-term remission and are associated with significant side effects. Immunotherapy has emerged as a promising avenue for cancer treatment, leveraging the body's immune system to target and destroy cancer cells. However, its application in liver cancer has been limited. One of the primary challenges is the liver's unique immune microenvironment, which can inhibit the effectiveness of immunotherapeutic agents. This immune microenvironment creates a barrier, leading to drug resistance and reducing the overall efficacy of treatment. Recent studies have focused on understanding the immunological landscape of liver cancer to develop strategies that can overcome these obstacles. By identifying the specific factors within the liver that contribute to immune suppression and drug resistance, researchers aim to enhance the effectiveness of immunotherapy. Prospective strategies include combining immunotherapy with other treatments, using targeted therapies to modulate the immune microenvironment, and developing new agents that can bypass or counteract the inhibitory mechanisms in the liver. These advancements hold promise for improving outcomes in liver cancer treatment.

A scoring model for the expression of genes related to programmed cell death predicts immunotherapy response and prognosis in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) continues to be the leading cause of cancer death worldwide, driven by environmental factors like smoking and genetic predispositions. LUAD has a high mortality rate, and new biomarkers are urgently needed to improve treatment strategies and patient management. Programmed cell death (PCD) is involved in tumor progression and response to treatment. Therefore, there is a need for an extensive study of the role and functions of PCD-related genes (PCDRGs) in lung adenocarcinoma so as to understand the pathophysiologic features of lung adenocarcinoma. METHODS: Based on TCGA and GEO databases, this research is aimed at screening differentially expressed PCD-related genes in lung adenocarcinoma. We conducted GO, and KEGG analysis to establish the link between these genes and biological processes. By applying various machine learning algorithms such as CoxBoost analysis, we developed PCD-related indices (PCDI) that were used to verify their ability to predict prognosis with the use of other datasets. This was done in addition to exploring the biological functions of PCD genes associated with lung adenocarcinoma by assessing the relationship between immune cell components of tumor microenvironment and PCD genes together with examining how they affect drug sensitivity. RESULTS: The research presented in this article offers significant insights into LUAD. The authors identified 113 PCDRGs that were differentially expressed in LUAD. These genes are implicated in various biological functions, including High risk ing apoptosis, ferroptosis, and pathways specific to non-small cell lung cancer. Notably, the PCDI proved effective in distinguishing between High risk and Low risk LUAD patients, demonstrating a higher accuracy in prognosis prediction compared to traditional clinical indicators such as age and gender. This high prediction accuracy was validated in both test and validation cohorts. Additionally, these genes showed significant correlations with immune cell infiltration and drug sensitivity in LUAD patients. CONCLUSION: We analysed the expression and function of PCDRGs in LUAD and revealed their correlation with patient survival, the immune microenvironment and drug sensitivity. The constructed PCDI model provides a scientific basis for the personalised treatment of lung adenocarcinoma, and future optimisation of treatment strategies based on these genes may improve patient clinical outcomes.

In situ evolution of bulk-active γ-CoOOH with immobilized Gd dopants enabling efficient oxygen evolution electrocatalysis.

Promoting the in situ reconstruction of transition metal (TM)-based precatalysts into low-crystalline and well-modified TM (oxy)hydroxides (TMOxHy) during the alkaline oxygen evolution reaction (OER) is crucial for enhancing their catalytic performances. In this study, we incorporated gadolinium (Gd) into a cobalt hydroxide precatalyst, achieving a deep reconstruction into cobalt oxyhydroxide (γ-CoOOH) while retaining the incorporated Gd during the activation process of the alkaline OER. The unconventional non-leaching Gd dopants endow γ-CoOOH with reduced crystallinity, increasing the exposure of electrolyte-accessible Co atoms and enhancing its bulk activity. Furthermore, the modulation of the electronic structure of γ-CoOOH substantially boosts the intrinsic activity of the active Co sites. As a result, when supported on nickel foam, the catalyst exhibits remarkable alkaline OER performance, achieving a current density of 100 mA cm-2 at a low overpotential of approximately 327 mV. Notably, an ultrahigh current density of 1000 mA cm-2 is robustly maintained for 5 days, highlighting its immense potential for practical applications in large-scale hydrogen production.

Impact of Varying Dietary Calcium Contents on the Gut Metabolomics of Yunnan Semi-Fine Wool Sheep (Ovis aries).

Yunnan semi-fine wool (YSFW) is a recently developed dual-purpose (meat and wool) sheep breed mainly found in Yunnan Province, China. Moreover, dietary calcium is essential for animal health and productivity. The current experiment aimed to investigate the impact of dietary calcium on sheep gut metabolite profile. For this, thirty YSFW rams (male, age = 10 months, and body weight = 40.37 ± 0.49 kg) were randomized into three groups (n = 10 rams/group), followed by a completely randomized design, and the groups were allotted to one of three dietary calcium levels (Q_1 = 0.50%, Q_3 = 0.73%, and Q_5 = 0.98% on a dry basis). The rams were fed ad libitum by feeding twice a day (at 08:00 and 17:00 h/day) throughout the experimental period (44 day). On the 21st day of the experiment, fecal samples were collected from 27 rams (9/group) and untargeted metabolite profiling was performed by using ultra-performance liquid chromatography. The PCA plot showed that the Q_5 group metabolites were clustered more tightly than for Q_1 and Q_3, respectively. The tightly clustering molecules were mainly alkaloids and their derivatives, benzenoids, lignans and related compounds, lipids, nucleotides, organic acids, and nitrogenous-based derivatives. According to the Kyoto Encyclopedia of Genes and Genomes pathway analysis, these molecules potentially contribute to metabolic pathways, biosynthesis of secondary metabolites, proteinaceous compounds, and the metabolism of the protein derivatives, particularly amino acids. The PLS-DA plots revealed a significant difference between the Q_1, Q_3, and Q_5 groups, suggesting that Q_5 had a clear separation across the groups. Based on the metabolomic analysis, feeding different levels of dietary calcium significantly changed the metabolomic profile of YSFW rams, which primarily entails metabolic pathways such as energy, protein, and lipid metabolism.

Association of litter size with the ruminal microbiome structure and metabolomic profile in goats.

The Yunshang black goat is a renowned mutton specialist breed mainly originating from China that has excellent breeding ability with varying litter sizes. Litter size is an important factor in the economics of goat farming. However, ruminal microbiome structure might be directly or indirectly regulated by pregnancy-associated factors, including litter sizes. Therefore, the current experiment aimed to evaluate the association of different litter sizes (low versus high) with ruminal microbiome structure by 16S rRNA gene sequencing and metabolomic profiling of Yunshang black does. A total of twenty does of the Yunshang Black breed, approximately aged between 3 and 4 years, were grouped (n = 10 goats/group) into low (D-l) and high (D-h) litter groups according to their litter size (the lower group has ≤ 2 kids/litter and the high group has ≧ 3 kids/litter, respectively). All goats were sacrificed, and collected ruminal fluid samples were subjected to 16S rRNA sequencing and LC-MS/MC Analysis for ruminal microbiome and metabolomic profiling respectively. According to PCoA analysis, the ruminal microbiota was not significantly changed by the litter sizes among the groups. The Firmicutes and Bacteroidetes were the most dominant phyla, with an abundance of 55.34% and 39.62%, respectively. However, Ruminococcaceae_UCG-009, Sediminispirochaeta, and Paraprevotella were significantly increased in the D-h group, whereas Ruminococcaceae_UCG-010 and Howardella were found to be significantly decreased in the D-l group. The metabolic profiling analysis revealed that litter size impacts metabolites as 29 and 50 metabolites in positive and negative ionic modes respectively had significant differences in their regulation. From them, 16 and 24 metabolites of the D-h group were significantly down-regulated in the positive ionic mode, while 26 metabolites were up-regulated in the negative ionic mode for the same group. The most vibrant identified metabolites, including methyl linoleate, acetylursolic acid, O-desmethyl venlafaxine glucuronide, melanostatin, and arginyl-hydroxyproline, are involved in multiple biochemical processes relevant to rumen roles. The identified differential metabolites were significantly enriched in 12 different pathways including protein digestion and absorption, glycerophospholipid metabolism, regulation of lipolysis in adipocytes, and the mTOR signaling pathway. Spearman's correlation coefficient analysis indicated that metabolites and microbial communities were tightly correlated and had significant differences between the D-l and D-h groups. Based on the results, the present study provides novel insights into the regulation mechanisms of the rumen microbiota and metabolomic profiles leading to different fertility in goats, which can give breeders some enlightenments to further improve the fertility of Yunshang Black goats.

Synergistic Active Heterostructure Design for Enhanced Two Electron Oxygen Reduction via Chemical and Electrochemical Reconstruction of Heterosulfides.

Transition metal sulfides, particularly heterostructures, represent a promising class of electrocatalysts for two electron oxygen reduction (2e- ORR), however, understanding the dynamic structural evolution of these catalysts during alkaline ORR remains relatively unexplored. Herein, NiS2/In2.77S4 heterostructure was synthesized as a precatalyst and through a series of comprehensive ex-situ and in-situ characterizations, including X-ray absorption spectroscopy, Raman spectroscopy, transient photo-induced voltage measurements, electron energy loss spectroscopy, and spherical aberration-corrected electron microscopy, it was revealed that nickel/indium (oxy)hydroxides (NiOOH/In(OH)3) could be evolved from the initial NiS2/In2.77S4 via both electrochemical and chemical-driven methods. The electrochemical-driven phase featured abundant bridging oxygen-deficient [NiO6]-[InO6] units at the interfaces of NiOOH/In(OH)3, facilitating a synergistic effect between active Ni and In sites, thus enabling an enhanced alkaline 2e- ORR capability than that of chemical-driven process. Remarkably, electrochemically induced NiOOH/In(OH)3 exhibited exceptional performance, achieving H2O2 selectivity of >90% across the wide potential window (up to 0.4 V) with a peak selectivity of >99%. Notably, within the flow cell, a current density exceeding 200 mA cm-2 was sustained for over 20 h, together with an impressive Faradaic efficiency of approximately 90% and a hydrogen peroxide production rate surpassing 4 mol g-1 h-1.

Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response in mice and humans.

Identifying host genetic factors modulating immune checkpoint inhibitor (ICI) efficacy has been experimentally challenging because of variations in both host and tumor genomes, differences in the microbiome, and patient life exposures. Utilizing the Collaborative Cross (CC) multi-parent mouse genetic resource population, we developed an approach that fixes the tumor genomic configuration while varying host genetics. With this approach, we discovered that response to anti-PD-1 (aPD1) immunotherapy was significantly heritable in four distinct murine tumor models (H2 between 0.18-0.40). For the MC38 colorectal carcinoma system (H2 = 0.40), we mapped four significant ICI response quantitative trait loci (QTL) localized to mouse chromosomes (mChr) 5, 9, 15 and 17, and identified significant epistatic interactions between specific QTL pairs. Differentially expressed genes within these QTL were highly enriched for immune genes and pathways mediating allograft rejection and graft vs host disease. Using a cross species analytical approach, we found a core network of 48 genes within the four QTLs that showed significant prognostic value for overall survival in aPD1 treated human cohorts that outperformed all other existing validated immunotherapy biomarkers, especially in human tumors of the previously defined immune subtype 4. Functional blockade of two top candidate immune targets within the 48 gene network, GM-CSF and high affinity IL-2/IL-15 signaling, completely abrogated the MC38 tumor transcriptional response to aPD1 therapy in vivo. Thus, we have established a powerful cross species in vivo platform capable of uncovering host genetic factors that establish the tumor immune microenvironment configuration propitious for ICI response.

Calcium Requirement of Yunnan Semi-fine Wool Rams (Ovis aries) Based on Growth Performance, Calcium Utilization, and Selected Serum Biochemical Indexes.

Calcium (Ca) is required for the growth and development of sheep, but the requirement of Yunnan semi-fine wool (YSW) rams remains uncovered. The current study aims to estimate the Ca requirement of growing YSW rams based on their growth performance, Ca utilization, and serum biochemical indexes. Forty-five YSW rams (10-month-olds) were randomly allocated to five dietary treatments with varying Ca levels of 0.50% (D1), 0.68% (D2), 0.73% (D3), 0.89% (D4), and 0.98% (D5). A higher value for average daily gain and a lower value for the feed conversion ratio were observed in the D3 group compared to the D5 group (p < 0.05). The dry matter intake amount changed quadratically with the increased Ca levels (p < 0.05). The levels of Ca intake, fecal Ca, and excreted Ca were significantly higher in the D5 group than those in the D1 group (p < 0.05). The apparent Ca digestibility rate and the Ca retention rate were significantly higher in the D4 group than in the D1 group (p < 0.05). The serum Ca concentration increased linearly with the incremental levels of dietary Ca (p < 0.05). The activity of alkaline phosphatase was significantly higher in the D1 group than in the D2 group (p < 0.05). The serum levels of hydroxyproline, osteocalcin, and calcitonin decreased from the D1 group to the D2 group, and then significantly ascended (p < 0.05) with the dietary Ca levels from the D3 group to the D5 group. The serum parathyroid hormone content was elevated from the D1 group to the D3 group and then decreased from the D4 group to the D5 group. After calculation, the daily net Ca requirement for the maintenance of YSW rams was 0.073 g/kg of BW0.75, and the daily total Ca requirement was 0.676 g/kg of BW0.75. To optimize the growth performance and the Ca utilization of YSW rams, the recommended dietary Ca level ranges from 0.73% to 0.89% based on this study.

BERT4FCA: A method for bipartite link prediction using formal concept analysis and BERT.

Link prediction in bipartite networks finds practical applications in various domains, including friend recommendation in social networks and chemical reaction prediction in metabolic networks. Recent studies have highlighted the potential for link prediction by maximal bi-cliques, which is a structural feature within bipartite networks that can be extracted using formal concept analysis (FCA). Although previous FCA-based methods for bipartite link prediction have achieved good performance, they still have the problem that they cannot fully capture the information of maximal bi-cliques. To solve this problem, we propose a novel method for link prediction in bipartite networks, utilizing a BERT-like transformer encoder network to enhance the contribution of FCA to link prediction. Our method facilitates bipartite link prediction by learning more information from the maximal bi-cliques and their order relations extracted by FCA. Experimental results on five real-world bipartite networks demonstrate that our method outperforms previous FCA-based methods, a state-of-the-art Graph Neural Network(GNN)-based method, and classic methods such as matrix-factorization and node2vec.

Construction of coherent interface between Cu2O and CeO2via electrochemical reconstruction for efficient carbon dioxide reduction to methane.

Developing an efficient electrocatalyst that enables the efficient electrochemical conversion from CO2 to CH4 across a wide potential range remains a formidable challenge. Herein, we introduce a precatalyst strategy that realizes the in situ electrochemical reconstruction of ultrafine Cu2O nanodomains, intricately coupled on the CeO2 surface (Cu2O/CeO2), originating from the heterointerface comprised of ultrafine CuO nanodomains on the CeO2 surface (CuO/CeO2). When served as the electrocatalyst for the electrochemical CO2 reduction reaction, Cu2O/CeO2 delivers a selectivity higher than 49 % towards CH4 over a broad potential range from -1.2 V to -1.7 V vs. RHE, maintaining negligible activity decay for 20 h. Notably, the highest selectivity for CH4 reaches an impressive 70 % at -1.5 V vs. RHE. Through the combination of comprehensive analysis including synchrotron X-ray absorption spectroscopy, spherical aberration-corrected high-angle annular dark field scanning transmission electron microscope as well as the density functional theoretical calculation, the efficient production of CH4 is attributed to the coherent interface between Cu2O and CeO2, which could converted from the original CuO and CeO2 interface, ensuring abundant active sites and enhanced intrinsic activity and selectivity towards CH4.

The constitutively active form of a key cholesterol synthesis enzyme is lipid droplet-localized and upregulated in endometrial cancer tissues.

Cholesterol is essential for both normal cell viability and cancer cell proliferation. Aberrant activity of squalene monooxygenase (SM, also known as squalene epoxidase), the rate-limiting enzyme of the committed cholesterol synthesis pathway, is accordingly implicated in a growing list of cancers. We previously reported that hypoxia triggers the truncation of SM to a constitutively active form, thus preserving sterol synthesis during oxygen shortfalls. Here, we show SM truncation is upregulated and correlates with the magnitude of hypoxia in endometrial cancer tissues, supporting the in vivo relevance of our earlier work. To further investigate the pathophysiological consequences of SM truncation, we examined its lipid droplet-localized pool using complementary immunofluorescence and cell fractionation approaches and found that it exclusively comprises the truncated enzyme. This partitioning is facilitated by the loss of an endoplasmic reticulum-embedded region at the SM N terminus, whereas the catalytic domain containing membrane-associated C-terminal helices is spared. Moreover, we determined multiple amphipathic helices contribute to the lipid droplet localization of truncated SM. Taken together, our results expand on the striking differences between the two forms of SM and suggest upregulated truncation may contribute to SM-related oncogenesis.

Phosphatidylserine regulates plasma membrane repair through tetraspanin-enriched macrodomains.

The integrity of the plasma membrane is critical to cell function and survival. Cells have developed multiple mechanisms to repair damaged plasma membranes. A key process during plasma membrane repair is to limit the size of the damage, which is facilitated by the presence of tetraspanin-enriched rings surrounding damage sites. Here, we identify phosphatidylserine-enriched rings surrounding damaged sites of the plasma membrane, resembling tetraspanin-enriched rings. Importantly, the formation of both the phosphatidylserine- and tetraspanin-enriched rings requires phosphatidylserine and its transfer proteins ORP5 and ORP9. Interestingly, ORP9, but not ORP5, is recruited to the damage sites, suggesting cells acquire phosphatidylserine from multiple sources upon plasma membrane damage. We further demonstrate that ORP9 contributes to efficient plasma membrane repair. Our results thus unveil a role for phosphatidylserine and its transfer proteins in facilitating the formation of tetraspanin-enriched macrodomains and plasma membrane repair.

Understanding Advanced Transition Metal-Based Two Electron Oxygen Reduction Electrocatalysts from the Perspective of Phase Engineering.

Non-noble transition metal (TM)-based compounds have recently become a focal point of extensive research interest as electrocatalysts for the two electron oxygen reduction (2e- ORR) process. To efficiently drive this reaction, these TM-based electrocatalysts must bear unique physiochemical properties, which are strongly dependent on their phase structures. Consequently, adopting engineering strategies toward the phase structure has emerged as a cutting-edge scientific pursuit, crucial for achieving high activity, selectivity, and stability in the electrocatalytic process. This comprehensive review addresses the intricate field of phase engineering applied to non-noble TM-based compounds for 2e- ORR. First, the connotation of phase engineering and fundamental concepts related to oxygen reduction kinetics and thermodynamics are succinctly elucidated. Subsequently, the focus shifts to a detailed discussion of various phase engineering approaches, including elemental doping, defect creation, heterostructure construction, coordination tuning, crystalline design, and polymorphic transformation to boost or revive the 2e- ORR performance (selectivity, activity, and stability) of TM-based catalysts, accompanied by an insightful exploration of the phase-performance correlation. Finally, the review proposes fresh perspectives on the current challenges and opportunities in this burgeoning field, together with several critical research directions for the future development of non-noble TM-based electrocatalysts.

A Novel Underwater Acoustic Target Recognition Method Based on MFCC and RACNN.

In ocean remote sensing missions, recognizing an underwater acoustic target is a crucial technology for conducting marine biological surveys, ocean explorations, and other scientific activities that take place in water. The complex acoustic propagation characteristics present significant challenges for the recognition of underwater acoustic targets (UATR). Methods such as extracting the DEMON spectrum of a signal and inputting it into an artificial neural network for recognition, and fusing the multidimensional features of a signal for recognition, have been proposed. However, there is still room for improvement in terms of noise immunity, improved computational performance, and reduced reliance on specialized knowledge. In this article, we propose the Residual Attentional Convolutional Neural Network (RACNN), a convolutional neural network that quickly and accurately recognize the type of ship-radiated noise. This network is capable of extracting internal features of Mel Frequency Cepstral Coefficients (MFCC) of the underwater ship-radiated noise. Experimental results demonstrate that the proposed model achieves an overall accuracy of 99.34% on the ShipsEar dataset, surpassing conventional recognition methods and other deep learning models.

The efficacy and safety of continuous blood purification in neonates with septic shock and acute kidney injury: a two-center retrospective study.

To investigate the efficacy and safety of continuous blood purification (CBP) in neonates with septic shock and acute kidney injury (AKI). This retrospective study was conducted at two tertiary care children's hospitals between January 2015 and May 2022. A total of 26 neonates with septic shock and AKI were included in this study, with a mortality rate of 50%. Fourteen neonates (53.8%) received continuous veno-venous hemodiafiltration, and 12 (46.2%) received continuous veno-venous hemofiltration. Compared with the indices before CBP, urine output increased 12 h after CBP initiation (P = 0.003) and serum creatinine decreased (P = 0.019). After 24 h of CBP, blood urea nitrogen had decreased (P = 0.006) and mean arterial pressure had increased (P = 0.007). At the end of CBP, the vasoactive-inotropic score and blood lactate were decreased (P = 0.035 and 0.038, respectively) and PH was increased (P = 0.015). Thrombocytopenia was the most common complication of CBP.  Conclusion: CBP can efficiently maintain hemodynamic stability, improve renal function, and has good safety in neonates with septic shock and AKI. However, the mortality rate remains high, and whether CBP improves the prognosis of neonates with septic shock and AKI remains unclear. What is Known: • Over 50% of children with septic shock have severe AKI, of which 21.6% required CBP. • The clinical application of CBP in septic shock has attracted increasing attention. What is New: • CBP can efficiently maintain hemodynamic stability, improve renal function, and has good safety in neonates with septic shock and AKI. • The mortality rate in neonates with septic shock and AKI receiving CBP remains high.

Dietary protein levels modulate the gut microbiome composition through fecal samples derived from lactating ewes.

In ruminants, the digestion and utilization of dietary proteins are closely linked to the bacterial populations that are present in the gastrointestinal tract. In the present study, 16S rDNA sequencing, together with a metagenomic strategy was used to characterize the fecal bacteria of ewes in the early lactation stage after feeding with three levels of dietary proteins 8.58%, 10.34%, and 13.93%, in three different groups (H_1), (H_m) and (H_h), respectively. A total of 376,278,516 clean data-points were obtained by metagenomic sequencing. Firmicutes and Bacteroidetes were the dominant phyla, regardless of the dietary protein levels. In the H_h group, the phyla Proteobacteria, Caldiserica, and Candidatus_Cryosericota were less abundant than those in the H_I group. In contrast, Lentisphaerae, Chlamydiae, and Planctomycetes were significantly more abundant in the H_h group. Some genera, such as Prevotella, Roseburia, and Firmicutes_unclassified, were less abundant in the H_h group than those in the H_I group. In contrast, Ruminococcus, Ruminococcaceae_noname, Anaerotruncus, Thermotalae, Lentisphaerae_noname, and Paraprevotella were enriched in the H_h group. The acquired microbial genes were mainly clustered into biological processes; molecular functions; cytosol; cellular components; cytoplasm; structural constituents of ribosomes; plasma membranes; translation; and catalytic activities. 205987 genes were significantly enriched in the H_h group. In contrast, 108129 genes were more abundant in the H_I group. Our findings reveal that dynamic changes in fecal bacteria and their genes are strongly influenced by the levels of dietary proteins. We discovered that differentially expressed genes mainly regulate metabolic activity and KEGG demonstrated the primary involvement of these genes in the metabolism of carbohydrates, amino acids, nucleotides, and vitamins. Additionally, genes responsible for metabolism were more abundant in the H_h group. Investigating fecal bacterial characteristics may help researchers develop a dietary formula for lactating ewes to optimize the growth and health of ewes and lambs.

Effects of graded levels of dietary protein supplementation on milk yield, body weight gain, blood biochemical parameters, and gut microbiota in lactating ewes.

Diet-associated characteristics such as dietary protein levels can modulate the composition and diversity of the gut microbiota, leading to effects on the productive performance and overall health of animals. The objective of this study was to see how changes in dietary protein levels affect milk yield, body weight gain, blood biochemical parameters, and gut microbiota in lactating ewes. In a completely randomized design, eighteen ewes were randomly assigned to three groups (n = 6 ewes/group), and each group was assigned to one of three dietary treatments with different protein contents. The ewes' groups were fed on 8.38% (S-I), 10.42% (S-m), and 13.93% (S-h) dietary protein levels on a dry basis. The body weight gain and milk yield were greater (p < 0.05) in ewes fed the S-h dietary treatment than in those fed the S-m and S-1 diets, respectively. However, milk protein contents were similar (p > 0.05) across the treatments. The blood glucose, total protein, cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein, lactate, creatinine, and C-reactive protein contents of lactating ewes were not influenced (p > 0.05) by different dietary protein levels. The alanine transaminase, aminotransferase, and lactate dehydrogenase activities were also not changed (p > 0.05) across the groups. However, blood urea nitrogen and albumin contents of lactating ewes were changed (p < 0.05) with increasing levels of dietary protein, and these metabolite concentrations were higher (p < 0.05) for S-h than the rest of the treatments. In the different treatment groups, Firmicutes and Bacteroidetes were found to be the most dominant phyla. However, the abundance of Lachnospiraceae species decreased as dietary protein levels increased. Within the Bacteroidetes phylum, Rikenellaceae were more abundant, followed by Prevotellaceae, in ewes fed the S-m diet compared to those fed the other diets. Based on the results, feeding at an optimal protein level improved milk yield and body weight gain through modifying the digestive tract's beneficial bacterial communities. The results of blood metabolites suggested that feeding higher-protein diets has no negative impact on health.

Oxysterol-Binding Protein: new insights into lipid transport functions and human diseases.

Oxysterol-binding protein (OSBP) mediates lipid exchange between organelles at membrane contact sites, thereby regulating lipid dynamics and homeostasis. How OSBP's lipid transfer function impacts health and disease remain to be elucidated. In this review, we first summarize the structural characteristics and lipid transport functions of OSBP, and then focus on recent progresses linking OSBP with fatty liver disease, diabetes, lysosome-related diseases, cancer and viral infections, with the aim of discovering novel therapeutic strategies for common human diseases.

Immobilization of Oxyanions on the Reconstructed Heterostructure Evolved from a Bimetallic Oxysulfide for the Promotion of Oxygen Evolution Reaction.

Efficient and durable oxygen evolution reaction (OER) requires the electrocatalyst to bear abundant active sites, optimized electronic structure as well as robust component and mechanical stability. Herein, a bimetallic lanthanum-nickel oxysulfide with rich oxygen vacancies based on the La2O2S prototype is fabricated as a binder-free precatalyst for alkaline OER. The combination of advanced in situ and ex situ characterizations with theoretical calculation uncovers the synergistic effect among La, Ni, O, and S species during OER, which assures the adsorption and stabilization of the oxyanion [Formula: see text] onto the surface of the deeply reconstructed porous heterostructure composed of confining NiOOH nanodomains by La(OH)3 barrier. Such coupling, confinement, porosity and immobilization enable notable improvement in active site accessibility, phase stability, mass diffusion capability and the intrinsic Gibbs free energy of oxygen-containing intermediates. The optimized electrocatalyst delivers exceptional alkaline OER activity and durability, outperforming most of the Ni-based benchmark OER electrocatalysts.