Characteristics, Performance and Microbial Response of Aerobic Granular Sludge for Treating Tetracycline Hypersaline Pharmaceutical Wastewater.

Salt-tolerant aerobic granular sludge(AGS) was successfully cultivated under the dual stress of tetracycline and 2.5% salinity, resulting in an average particle size of 435.0 ± 0.5 and exhibiting a chemical oxygen demand(COD) removal rate exceeding 80%, as well as excellent sedimentation performance. The analysis of metagenomics technology revealed a significant pattern of succession in the development of AGS. The proportion of Oleiagrimonas, a type of salt-tolerant bacteria, exhibited a gradual increase and reached 38.07% after 42 days, which indicated that an AGS system based on moderate halophilic bacteria was successfully constructed. The expression levels of targeted genes were found to be reduced across the entire AGS process and formation, as evidenced by qPCR analysis. The presence of int1 (7.67 log10 gene copies g-1 in 0 d sludge sample) enabled microbes to horizontally transfer ARGs genes along the AGS formation under the double pressure of TC and 2.5% salinity. These findings will enhance our understanding of ARG profiles and the development in AGS under tetracycline pressure, providing a foundation for guiding the use of AGS to treat hypersaline pharmaceutical wastewater.

Highly luminescent and stable CsPbBr3 perovskite nanocrystals coated with polyethersulfone for white light-emitting diode applications.

Simultaneously improving the stability and photoluminescence quantum yield (PLQY) of all inorganic perovskite nanocrystals (NCs) is crucial for their practical utilization in various optoelectronic devices. Here, CsPbBr3 NCs coated with polyethersulfone (PES) were prepared via an in-situ co-precipitation method. The sulfone groups in PES bind to undercoordinated lead ion (Pb2+) on the CsPbBr3 NCs, resulting in significant reduction of surface defects, thus enhancing the PLQY from 74.2% to 88.3%. Meanwhile, the PES-coated NCs exhibit high water resistance and excellent heat and light stability, maintaining over 85% of the initial PL intensity under thermal aging (70°C, 4 h) and continuous 365 nm ultraviolet (UV) light irradiation (24 W, 8 h) conditions. By contrast, the PL intensity of the control NCs dramatically dropped to less than 40%. Finally, a diode emitting bright white light was fabricated utilizing the PES-coated CsPbBr3 NCs, which exhibits a color gamut of ~110% NTSC standard.

Biomimetic Nanoporous Transparent Universal Fire-Resistant Coatings.

The inherent flammability of most polymeric materials poses a significant fire hazard, leading to substantial property damage and loss of life. A universal flame-retardant protective coating is considered as a promising strategy to mitigate such risks; however, simultaneously achieving high transparency of the coatings remains a great challenge. Here, inspired by the moth eye effect, we designed a nanoporous structure into a protective coating that leverages a hydrophilic-hydrophobic interactive assembly facilitated by phosphoric acid protonated amino siloxane. The coating demonstrates robust adhesion to a diverse range of substrates, including but not limited to fabrics, foams, paper, and wood. As expected, its moth-eye-inspired nanoporous structure conferred a high visible light transparency of >97% and water vapor transmittance of 96%. The synergistic effect among phosphorus (P), nitrogen (N), and silicon (Si) largely enhanced the char-forming ability and restricted the decomposition of the coated substrates, which successfully endowed the coating with high fire-fighting performance. More importantly, for both flexible and rigid substrates, the coated samples all possessed great mechanical properties. This work provides a new insight for the design of protective coatings, particularly focusing on achieving high transparency.

HGCLAMIR: Hypergraph contrastive learning with attention mechanism and integrated multi-view representation for predicting miRNA-disease associations.

Existing studies have shown that the abnormal expression of microRNAs (miRNAs) usually leads to the occurrence and development of human diseases. Identifying disease-related miRNAs contributes to studying the pathogenesis of diseases at the molecular level. As traditional biological experiments are time-consuming and expensive, computational methods have been used as an effective complement to infer the potential associations between miRNAs and diseases. However, most of the existing computational methods still face three main challenges: (i) learning of high-order relations; (ii) insufficient representation learning ability; (iii) importance learning and integration of multi-view embedding representation. To this end, we developed a HyperGraph Contrastive Learning with view-aware Attention Mechanism and Integrated multi-view Representation (HGCLAMIR) model to discover potential miRNA-disease associations. First, hypergraph convolutional network (HGCN) was utilized to capture high-order complex relations from hypergraphs related to miRNAs and diseases. Then, we combined HGCN with contrastive learning to improve and enhance the embedded representation learning ability of HGCN. Moreover, we introduced view-aware attention mechanism to adaptively weight the embedded representations of different views, thereby obtaining the importance of multi-view latent representations. Next, we innovatively proposed integrated representation learning to integrate the embedded representation information of multiple views for obtaining more reasonable embedding information. Finally, the integrated representation information was fed into a neural network-based matrix completion method to perform miRNA-disease association prediction. Experimental results on the cross-validation set and independent test set indicated that HGCLAMIR can achieve better prediction performance than other baseline models. Furthermore, the results of case studies and enrichment analysis further demonstrated the accuracy of HGCLAMIR and unconfirmed potential associations had biological significance.

Turn Waste Golden Tide into Treasure: Bio-Adsorbent Synthesis for CO2 Capture with K2FeO4 as Catalytic Oxidative Activator.

Converting Sargassum horneri (SH)-a harmful marine stranding that can cause golden tide-to highly porous bio-adsorbent material (via one-step catalytic oxidative pyrolysis with K2FeO4) can be a strategically useful method for obtaining low-cost materials suitable for CO2 capture. In this manuscript, the behavior of different mass ratios of K2FeO4/SH precursor acting on the surface physicochemical properties of carbon materials are reported. The results suggest that specific surface area and total pore volume first increased to the mass ratio of K2FeO4/carbon precursor, then decreased. Among the samples prepared, the highest specific surface area was obtained with a K2FeO4/SH precursor ratio of 1:4 (25%-ASHC), and the CO2 adsorption performance was significantly increased and faster compared with the original biochar. The fitted values of the three kinetic models showed that the double exponential model provided the best description of carbon adsorption, indicating both physical and chemical adsorption; 25%-ASHC also exhibited excellent cyclic stability. The improved CO2 adsorption performance observed after K2FeO4 activation is mainly due to the increase in material porosity, specific surface area, and the enrichment of nitrogen and oxygen functional groups.

The Cross-Communication of Cuproptosis and Regulated Cell Death in Human Pathophysiology.

Copper (Cu) plays a crucial and diverse function in biological systems, acting as a cofactor at numerous sites of enzymatic activity and participating in various physiological processes, including oxidative stress regulation, lipid metabolism, and energy metabolism. Similar to other micronutrients, the body regulates Cu levels to ensure homeostasis; any disruption in Cu homeostasis may result in various illnesses. Cuproptosis causes proteotoxic stress and ultimately results in cell death by the binding of Cu ions to lipid-acylated proteins during the tricarboxylic acid cycle of mitochondrial respiration. Cu is not only involved in regulatory cell death (RCD), but also in exogenous factors that induce cellular responses and toxic outcomes. Cu imbalances also affect the transmission of several RCD messages. Therefore, this article presents a thorough examination of the mechanisms involved in Cu-induced RCD as well as the role of Cu complexes in its pathophysiology.

Mechanistic Study on the Possibility of Converting Dissociated Oxygen into Formic Acid on χ-Fe5C2(510) for Resource Recovery in Fischer-Tropsch Synthesis.

During Fischer-Tropsch synthesis, O atoms are dissociated on the surface of Fe-based catalysts. However, most of the dissociated O would be removed as H2O or CO2, which results in a low atom economy. Hence, a comprehensive study of the O removal pathway as formic acid has been investigated using the combination of density functional theory (DFT) and kinetic Monte Carlo (kMC) to improve the economics of Fischer-Tropsch synthesis on Fe-based catalysts. The results show that the optimal pathway for the removal of dissociated O as formic acid is the OH pathway, of which the effective barrier energy (0.936 eV) is close to that of the CO activation pathway (0.730 eV), meaning that the removal of dissociated O as formic acid is possible. The main factor in an inability to form formic acid is the competition between the formic acid formation pathway and other oxygenated compound formation pathways (H2O, CO2, methanol-formaldehyde); the details are as follows: 1. If the CO is hydrogenated first, then the subsequent reaction would be impossible due to its high effective Gibbs barrier energy. 2. If CO reacts first with O to become CO2, it is difficult for it to be hydrogenated further to become HCOOH because of the low adsorption energy of CO2. 3. When the CO + OH pathway is considered, OH would react easily with H atoms to form H2O due to the hydrogen coverage effect. Finally, the removal of dissociated O to formic acid is proposed via improving the catalyst to increase the CO2 adsorption energy or CO coverage.

The role of LSM1 in breast cancer: Shaping metabolism and tumor-associated macrophage infiltration.

LSM1 is part of the cytoplasmic protein complex Lsm1-7-Pat1 and is likely involved in pre-mRNA degradation by aiding U4/U6 snRNP formation. More research is needed to uncover LSM1's potential in breast cancer (BRCA) clinical pathology, the tumor immune microenvironment, and precision oncology. We discovered LSM1 as a diagnostic marker for advanced BRCA with poor survival, using a multi-omics approach. We studied LSM1 expression across BRCA regions and its link to immune cells through various methods, including spatial transcriptomics and single-cell RNA-sequencing. We also examined how silencing LSM1 affects mitochondrial function and energy metabolism in the tumor environment. These findings were confirmed using 54 BRCA patient biopsies and tissue microarrays. Immunofluorescence and bioinformatics assessed LSM1's connection to clinicopathological features and prognosis. This study uncovers gene patterns linked to breast cancer, with LSM1 linked to macrophage energy processes. Silencing LSM1 in breast cancer cells disrupts mitochondria and energy metabolism. Spatial analysis aligns with previous results, showing LSM1's connection to macrophages. Biopsies confirm LSM1 elevation in advanced breast cancer with increased macrophage presence. To summarize, LSM1 changes may drive BRCA progression, making it a potential diagnostic and prognostic marker. It also influences energy metabolism and the tumor's immune environment during metastasis, showing promise for precision medicine and drug screening in BRCA.

Enhanced Assembling of N-and-K-Riched Macroalgae as Carbon Adsorbent for CO2 Capture with Ni(NO3)2/KOH as Co-Catalysts.

Porous-activated carbons have drawn great attention due to their important role in CO2 capture. Ni(NO3)2/KOH, as co-catalysts under different temperatures, were studied to obtain porous graphitized carbon from Sargassum horneri feedstock. The results indicated that the properties of the porous graphitized carbon generated at 850 °C were greatly enhanced, showing a large specific surface area of 1486.38 cm3·g-1 with narrowly distributed micropores (~0.67 nm) and abundant functional groups, which endowed high CO2 uptake; moreover, the high CO2 uptake was mainly attributed to the synergistic effect of Ni(NO3)2 and KOH, both in chemical modification and pore formation. The fitted values of the four kinetic models showed that the double exponential model provided the best description of carbon adsorption, indicating both physical and chemical adsorption. It is worth noting that carbon could be reused four times in the adsorption/desorption procedure in this research with good stability. This work focuses on the high-value-added comprehensive utilization of macroalgae, which not only is important for high-performance adsorbent preparation but also has positive benefits for the development and utilization of macroalgae resources.

Integration of multi-omics data using adaptive graph learning and attention mechanism for patient classification and biomarker identification.

With the rapid development and accumulation of high-throughput sequencing technology and omics data, many studies have conducted a more comprehensive understanding of human diseases from a multi-omics perspective. Meanwhile, graph-based methods have been widely used to process multi-omics data due to its powerful expressive ability. However, most existing graph-based methods utilize fixed graphs to learn sample embedding representations, which often leads to sub-optimal results. Furthermore, treating embedding representations of different omics equally usually cannot obtain more reasonable integrated information. In addition, the complex correlation between omics is not fully taken into account. To this end, we propose an end-to-end interpretable multi-omics integration method, named MOGLAM, for disease classification prediction. Dynamic graph convolutional network with feature selection is first utilized to obtain higher quality omic-specific embedding information by adaptively learning the graph structure and discover important biomarkers. Then, multi-omics attention mechanism is applied to adaptively weight the embedding representations of different omics, thereby obtaining more reasonable integrated information. Finally, we propose omic-integrated representation learning to capture complex common and complementary information between omics while performing multi-omics integration. Experimental results on three datasets show that MOGLAM achieves superior performance than other state-of-the-art multi-omics integration methods. Moreover, MOGLAM can identify important biomarkers from different omics data types in an end-to-end manner.

The CSN5/HSF/SPI1/PU.1 Axis Regulates Cell Proliferation in Hypocellular Myelodysplastic Syndrome Patients.

OBJECTIVE: This study explored the relationship between the activation of the jak/stat3 signaling pathway and the CSN5 gene transcript and protein expression levels in the hematopoietic stem cells of patients with myelodysplastic syndromes (MDSs). This study also aimed to investigate the correlation between the expression level of CSN5 and the deubiquitination of HSF1, as well as the transcript level of the spi1/pu.1 genes to explore the pathogenesis of MDS. MATERIALS AND METHODS: We isolated cells from normal individuals and MDS patients, and the mRNA and protein expression levels of spi1/pu.1 in cd34+ cells (hematopoietic stem cells) were measured by PCR and western blotting, respectively. A ChIP assay was used to detect the binding of HSF1 to the spi1/pu.1 promoter in cd34+ cells. The ubiquitination of HSF1 in cd34+ cells was detected by CO-IP. The binding of HSF1 and Fbxw7α was detected in in cd34+ cells by CO-IP. The binding of HSF1 and CSN5 was evaluated. A luciferase reporter assay was used to detect the effect of STAT3 on CSN5 promoter activation in cd34+ cells. Western blotting was used to detect the phosphorylation of STAT3 in cd34+ cells of MDS patients. The binding of STAT3 and C/EBP beta in cd34+ cells was detected by CO-IP. RESULTS: Inhibition of SPI1/PU.1 expression was observed in MDS samples with low proliferation ability. Further experiments proved that phosphorylation of STAT3 affected CSN5 function and mediated the ubiquitination of HSF, the upstream regulator of SPI1/PU.1 transcription, which led to the inhibition of SPI1/PU.1 expression. Restoration of CSN5 rescued the inhibition of HSF1 ubiquitination, causing SPI1/PU.1 transcription to resume and increasing SPI1/PU.1 expression, promoting the recovery of cell proliferation in hypocellular MDS. CONCLUSIONS: Our research revealed the regulatory role of the CSN5/HSF/SPI1/PU.1 axis in hypocellular MDS, providing a probable target for clinical intervention.

Combination of venetoclax with BCR-ABL tyrosine kinase inhibitor as a therapeutic strategy for Philadelphia chromosome-positive leukemias.

OBJECTIVES: Venetoclax has shown synergism with BCR-ABL1 tyrosine kinase inhibitors (TKIs) in preclinical studies for patients with Philadelphia chromosome-positive (Ph+) leukemias. This combination may suggest a novel treatment strategy for Ph + leukemias. METHODS: We conducted a retrospective study to summarize the activity of combining venetoclax and BCR-ABL1 TKI-based therapies in Ph + leukemias. RESULT: A total of 18 patients with Ph + leukemias were enrolled in this study. At the time of venetoclax and TKI-based therapy, 5 patients were initially diagnosed, with Ph + acute myeloid leukemia (AML) (n = 1) and mixed phenotype acute leukemia (MPAL) (n = 4), 7 patients had chronic myeloid leukemia at blastic phase (CML-BP), and the remaining 6 patients had relapsed or refractory to prior therapy. The overall response rate (ORR) was 88.9% (9 CR, 2 CRi, 4 MLFS, 1 PR), and a major molecular response (MMR) (or better) was achieved in 7 (38.8%) of all patients. With a median follow-up of 7.0 months (range, 2.3-15.6), 15 (83.3%) were in continuous CR at the time of this analysis, with a 1-year OS of 85.6%, 1-year LFS of 76.7%, and 1-year CIR of 22.4%. Moreover, 10 of 18 patients were treated with venetoclax, TKI and hypomethylating agent (HMA) regimens, which also associated with a high ORR rate (6 CR, 1 CRi, 3 MLFS), and can be used for induction or salvage therapy. CONCLUSION: Venetoclax and TKI-based combination regimens may be a feasible approach for Ph + leukemias, and prospective studies are needed to properly assess the safety, tolerability and efficacy of this regimen.

GDCL-NcDA: identifying non-coding RNA-disease associations via contrastive learning between deep graph learning and deep matrix factorization.

Non-coding RNAs (ncRNAs) draw much attention from studies widely in recent years because they play vital roles in life activities. As a good complement to wet experiment methods, computational prediction methods can greatly save experimental costs. However, high false-negative data and insufficient use of multi-source information can affect the performance of computational prediction methods. Furthermore, many computational methods do not have good robustness and generalization on different datasets. In this work, we propose an effective end-to-end computing framework, called GDCL-NcDA, of deep graph learning and deep matrix factorization (DMF) with contrastive learning, which identifies the latent ncRNA-disease association on diverse multi-source heterogeneous networks (MHNs). The diverse MHNs include different similarity networks and proven associations among ncRNAs (miRNAs, circRNAs, and lncRNAs), genes, and diseases. Firstly, GDCL-NcDA employs deep graph convolutional network and multiple attention mechanisms to adaptively integrate multi-source of MHNs and reconstruct the ncRNA-disease association graph. Then, GDCL-NcDA utilizes DMF to predict the latent disease-associated ncRNAs based on the reconstructed graphs to reduce the impact of the false-negatives from the original associations. Finally, GDCL-NcDA uses contrastive learning (CL) to generate a contrastive loss on the reconstructed graphs and the predicted graphs to improve the generalization and robustness of our GDCL-NcDA framework. The experimental results show that GDCL-NcDA outperforms highly related computational methods. Moreover, case studies demonstrate the effectiveness of GDCL-NcDA in identifying the associations among diversiform ncRNAs and diseases.

Anti-CD19 CAR T-cell consolidation therapy combined with CD19+ feeding T cells and TKI for Ph+ acute lymphoblastic leukemia.

We conducted a single-arm, open-label, single-center phase 1 study to assess the safety and efficacy of multicycle-sequential anti-CD19 chimeric antigen receptor (CAR) T-cell therapy in combination with autologous CD19+ feeding T cells (FTCs) and tyrosine kinase inhibitor (TKI) as consolidation therapy in patients under the age of 65 years with de novo Ph-positive CD19+ B-cell acute lymphoblastic leukemia. Participants were given induction chemotherapy as well as systemic chemotherapy with TKI. Afterward, they received a single cycle of CD19 CAR T-cell infusion and another 3 cycles of CD19 CAR T-cell and CD19+ FTC infusions, followed by TKI as consolidation therapy. CD19+ FTCs were given at 3 different doses. The phase 1 results of the first 15 patients, including 2 withdrawals, are presented. The most common adverse events were cytopenia (13/13) and hypogammaglobinemia (12/13). There was no incidence of cytokine release syndrome above grade 2 or immune effector cell-associated neurotoxicity syndrome or grade 4 nonhematological toxicities. All 13 patients achieved complete remission, including 12 patients with a complete molecular response (CMR) at the data cutoff. The relapse-free survival was 84%, and the overall survival was 83% with a median follow-up of 27 months. The total number of CD19-expressing cells decreased with an increasing CMR rate. CD19 CAR T cells survived for up to 40 months, whereas CD19+ FTCs vanished in 8 patients 3 months after the last infusion. These findings could form the basis for the development of an allo-HSCT-free consolidation paradigm. This trial was registered at www.clinicaltrials.gov as #NCT03984968.

Inguinal Fat Compensates Whole Body Metabolic Functionality in Partially Lipodystrophic Mice with Reduced PPARγ Expression.

Peroxisome proliferator-activated receptor γ (PPARγ) gene mutations in humans and mice lead to whole-body insulin resistance and partial lipodystrophy. It is unclear whether preserved fat depots in partial lipodystrophy are beneficial for whole-body metabolic homeostasis. We analyzed the insulin response and expression of metabolic genes in the preserved fat depots of PpargC/- mice, a familial partial lipodystrophy type 3 (FPLD3) mouse model resulting from a 75% decrease in Pparg transcripts. Perigonadal fat of PpargC/- mice in the basal state showed dramatic decreases in adipose tissue mass and insulin sensitivity, whereas inguinal fat showed compensatory increases. Preservation of inguinal fat metabolic ability and flexibility was reflected by the normal expression of metabolic genes in the basal or fasting/refeeding states. The high nutrient load further increased insulin sensitivity in inguinal fat, but the expression of metabolic genes became dysregulated. Inguinal fat removal resulted in further impairment of whole-body insulin sensitivity in PpargC/- mice. Conversely, the compensatory increase in insulin sensitivity of the inguinal fat in PpargC/- mice diminished as activation of PPARγ by its agonists restored insulin sensitivity and metabolic ability of perigonadal fat. Together, we demonstrated that inguinal fat of PpargC/- mice plays a compensatory role in combating perigonadal fat abnormalities.

NLRP3 inflammasome activation, metabolic danger signals, and protein binding partners.

The NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome is an oligomeric complex that assembles in response to exogenous signals of pathogen infection and endogenous danger signals of non-microbial origin. When NLRP3 inflammasome assembly activates caspase-1, it promotes the maturation and release of the inflammatory cytokines interleukin-1B and IL-18. Aberrant activation of the NLRP3 inflammasome has been implicated in various diseases, including chronic inflammatory, metabolic, and cardiovascular diseases. The NLRP3 inflammasome can be activated through several principal mechanisms, including K+ efflux, lysosomal damage, and the production of mitochondrial reactive oxygen species. Interestingly, metabolic danger signals activate the NLRP3 inflammasome to induce metabolic diseases. NLRP3 contains three crucial domains: an N-terminal pyrin domain, a central nucleotide-binding domain, and a C-terminal leucine-rich repeat domain. Protein-protein interactions act as a 'pedal or brake' to control the activation of the NLRP3 inflammasome. In this review, we present the mechanisms underlying NLRP3 inflammasome activation after induction by metabolic danger signals or via protein-protein interactions with NLRP3 that likely occur in metabolic diseases. Understanding these mechanisms will enable the development of specific inhibitors to treat NLRP3-related metabolic diseases.

Distribution, sources, and risk assessment of polycyclic aromatic hydrocarbons (PAHs) in Kaokaowusu river sediments near a coal industrial zone.

This study systematically analyzed the contents, compositions, and sources of polycyclic aromatic hydrocarbons (PAHs) in river sediments near an important energy and chemical base in northwest China. In addition, their possible adverse effects on the ecology and human health were assessed. The PAH concentrations in this study area ranged from 2641.28 to 16783.72 (ng/g dw). PAHs of medium molecular weight (3-ring and 4-ring) showed the largest proportion, followed by PAHs of higher molecular weight (5-ring and 6-ring). The results of molecular diagnostic ratios and principal component analysis revealed that PAHs in the region have complex sources, with incomplete combustion of local fossil fuels and traffic exhaust factors being the main sources. The total toxic equivalent concentration of PAHs varied from 10.05 to 760.26 ng/g, and according to the sediment quality guidelines, PAHs have high potential ecological risk in the lower reaches of the river. The mean effect range-median quotient for the region was 0.46, and the combined ecological risk was at moderate to high levels (21% probability of toxicity). The lifetime carcinogenic risks for adults and children exposed to PAHs were 2.95 × 10-3 and 1.87 × 10-2, respectively, which are much higher than the limit of 10-4, indicating moderate to high potential cancer risks. Therefore, the local government should consider taking some environmental remediation measures. This study can provide theoretical support for pollution prevention measures and ecological restoration strategies for rivers in resource-rich areas.