The crosstalk between copper-induced oxidative stress and cuproptosis: a novel potential anticancer paradigm.

Copper is a crucial trace element that plays a role in various pathophysiological processes in the human body. Copper also acts as a transition metal involved in redox reactions, contributing to the generation of reactive oxygen species (ROS). Under prolonged and increased ROS levels, oxidative stress occurs, which has been implicated in different types of regulated cell death. The recent discovery of cuproptosis, a copper-dependent regulated cell death pathway that is distinct from other known regulated cell death forms, has raised interest to researchers in the field of cancer therapy. Herein, the present work aims to outline the current understanding of cuproptosis, with an emphasis on its anticancer activities through the interplay with copper-induced oxidative stress, thereby providing new ideas for therapeutic approaches targeting modes of cell death in the future.

Efficacy and safety of multikinase inhibitors for patients with refractory thyroid cancer: Systematic review and network meta-analysis.

CONTEXT: Multikinase inhibitors (MKIs) improve the treatment of refractory thyroid cancer, included radioactive iodine-refractory differentiated thyroid cancer (RAIR-DTC) and advanced medullary thyroid carcinoma (aMTC). OBJECTIVE: This study aims to compare the efficacy of MKIs in improving survival outcomes and safety. DATA SOURCES: Comprehensive database searches of MEDLINE via PubMed, EMBASE and Cochrane performed from inception to December 2023. STUDY SELECTION: Three independent authors selected these studies. Randomised-controlled trials that compared the use of a MKI to other MKIs or placebo were included. DATA EXTRACTION AND SYNTHESIS: This review followed PRISMA guidelines. Risk of bias was analyzed using the Cochrane RoB 2 tool. Bayesian network meta-analysis was performed. Treatments were grouped into common nodes based on the type of MKI. MAIN OUTCOMES AND MEASURES: Primary outcomes were progression-free survival (PFS) and overall survival (OS). Secondary outcomes included objective response rate, disease control rate, clinical benefit rate, and adverse events. RESULTS: Cabozantinib 60 mg/d (CAB60) was associated with the highest prolonged PFS in RAIR-DTC patients, followed by lentivatinib 18 or 24 mg/d (LEN18 or LEN24), and apatinib. PFS was also improved in in aMTC patients received CAB 140 mg/d (CAB140), CAB60, or anlotinib. A significantly greater improvement on the performance of OS was seen in CAB60, LEN24, anlotinib, and sorafenib in RAIR-DTC patients, but which in aMTC patients were lack of statistical differences. Compared with the low-dose of MKIs, high-dose of MKIs such as CAB, LEN, and vandetanib increased the incidence of adverse events. CONCLUSION: CAB60, LEN, and apatinib are promising topical MKIs with statistically significant primary outcomes in RAIR-DTC patients, while CAB and anlotinib are effective in prolonging PFS in aMTC patients.

Dissecting the Interplay Mechanism among Process Parameters toward the Biofabrication of High-Quality Shapes in Embedded Bioprinting.

Embedded bioprinting overcomes the barriers associated with the conventional extrusion-based bioprinting process as it enables the direct deposition of bioinks in 3D inside a support bath by providing in situ self-support for deposited bioinks during bioprinting to prevent their collapse and deformation. Embedded bioprinting improves the shape quality of bioprinted constructs made up of soft materials and low-viscosity bioinks, leading to a promising strategy for better anatomical mimicry of tissues or organs. Herein, the interplay mechanism among the printing process parameters toward improved shape quality is critically reviewed. The impact of material properties of the support bath and bioink, printing conditions, cross-linking mechanisms, and post-printing treatment methods, on the printing fidelity, stability, and resolution of the structures is meticulously dissected and thoroughly discussed. Further, the potential scope and applications of this technology in the fields of bioprinting and regenerative medicine are presented. Finally, outstanding challenges and opportunities of embedded bioprinting as well as its promise for fabricating functional solid organs in the future are discussed.

Self-Adapting Biomass Hydrogel Embodied with miRNA Immunoregulation and Long-Term Bacterial Eradiation for Synergistic Chronic Wound Therapy.

Chronic wound rescue is critical for diabetic patients but is challenging to achieve with a specific and long-term strategy. The prolonged bacterial inflammation is particularly prevalent in hyperglycemia-induced wounds, usually leading to severe tissue damage. Such a trend could further suffer from an environmental suitability provided by macrophages for persisting Staphylococcus aureus (S. aureus) and even deteriorate by their mutual reinforcement. However, the strategy of both suppressing bacteria growth and immunoreprogramming the inflammatory type of macrophages to break their vicious harm to wound healing is still lacking. Here, a self-adapting biomass carboxymethyl chitosan (CMC) hydrogel comprising immunomodulatory nanoparticles is reported to achieve Gram-negative/Gram-positive bacteria elimination and anti-inflammatory cytokines induction to ameliorate the cutaneous microenvironment. Mechanistically, antibacterial peptides and CMCs synergistically result in a long-term inhibition against methicillin-resistant S. aureus (MRSA) over a period of 7 days, and miR-301a reprograms the M2 macrophage via the PTEN/PI3Kγ/mTOR signaling pathway, consequently mitigating inflammation and promoting angiogenesis for diabetic wound healing in rats. In this vein, immunoregulatory hydrogel is a promising all-biomass dressing ensuring biocompatibility, providing a perspective to regenerate cutaneous damaged tissue, and repairing chronic wounds on skin.

Surgical results, technical notes and complications of jugular foramen lesions via retroauricular infratemporal fossa approach.

OBJECTIVE: The objective of this study was to evaluate the clinical effect and safety of the postauricular infratemporal fossa approach (ITFA) in resecting jugular foramen lesions. METHODS: All 25 patients undergoing microsurgery via postauricular ITFA from March 2015 to May 2023 in the Department of Neurosurgery, Tangdu Hospital, Air Force Military Medical University were included. The clinical and radiological data were retrospectively analyzed. Regular follow-up was carried out. RESULTS: The mean age of all patients was 50.5±8.9 years, and 14 of them were female and 11 were male. Among the cases, lower cranial nerve schwannoma accounted for 60 % (15/25) of all tumors, jugular foramen paraganglioma accounted for 20 % (5/25), and the remaining 20 % included meningioma, chondrosarcoma, plasmacytoma, and salivary gland tumors. Total tumor resection was performed in 18 cases, subtotal tumor resection in 7 cases and partial resection in 1 case. Seven patients underwent gamma knife radiotherapy after surgery. Transient lower cranial nerve dysfunction occurred in 8 patients, and permanent lower cranial nerve dysfunction occurred in 2 patients after surgery. One patient developed facial paralysis, and one patient presented hearing loss. CONCLUSIONS: The postauricular ITFA achieved a relatively high total tumor resection rate and a lower incidence of neurological functional disorders. It is an alternative and suitable surgical approach for resecting jugular foramen lesions. Maximizing the preservation of neurological function is preferred, especially when radical resection cannot be achieved. Stereotactic radiotherapy could be used for residual tumors.

Realizing the Efficient Dissolution of Drag Reducer upon pH-Induced Demulsification of Inverse Polymer Emulsion.

The increasing exploitation of fossil resources needs to shift people's attention to developing unconventional reservoir resources. Polyacrylamide-based emulsion drag reducers can effectively reduce the turbulence of fracturing fluid and improve oil recovery, but their release effect is poor, which limits their practical application. Here, we constructed a pH-responsive inverse polymer emulsion of poly(acrylamide-2-acrylamido-2-methylpropanesulfonic acid). Interestingly, HOA/Tween 80 exhibits remarkable pH-responsive behavior, which enables the monomer emulsion to change the type of emulsion under pH stimulation. Our results propose that the P(AM-AMPS) polymer emulsion is eluted with the same aqueous phase as the W/O P(AM-AMPS) polymer emulsion, thereby achieving the effect of drag reduction. P(AM-AMPS) can be rapidly released from the inverse polymer emulsion within 70 s upon pH stimulation, the drag reduction rate of which was 60.4%. Obviously, the inverse polymer emulsion prepared by a pH-responsive surfactant not only has good stability but also can achieve rapid release of the polymer upon pH stimulation, which supplies an interesting indication to explain why a balance exists between the stability of the emulsion and release of P(AM-AMPS).

PhieDBEs: a DBD-containing, PAM-flexible, high-efficiency dual base editor toolbox with wide targeting scope for use in plants.

Dual base editors (DBEs) enable simultaneous A-to-G and C-to-T conversions, expanding mutation types. However, low editing efficiency and narrow targeting range limit the widespread use of DBEs in plants. The single-strand DNA binding domain of RAD51 DBD can be fused to base editors to improve their editing efficiency. However, it remains unclear how the DBD affects dual base editing performance in plants. In this study, we generated a series of novel plant DBE-SpGn tools consisting of nine constructs using the high-activity cytidine deaminase evoFERNY, adenosine deaminase TadA8e and DBD in various fusion modes with the PAM-flexible Streptococcus pyogenes Cas9 (SpCas9) nickase variant SpGn (with NG-PAM). By analysing their editing performance on 48 targets in rice, we found that DBE-SpGn constructs containing a single DBD and deaminases located at the N-terminus of SpGn exhibited the highest editing efficiencies. Meanwhile, constructs with deaminases located at the C-terminus and/or multiple DBDs failed to function normally and exhibited inhibited editing activity. We identified three particularly high-efficiency dual base editors (C-A-SpGn, C-A-D-SpGn and A-C-D-SpGn), named PhieDBEs (Plant high-efficiency dual base editors), capable of producing efficient dual base conversions within a narrow editing window (M5 ~ M9, M = A/C). The editing efficiency of C-A-D-SpGn was as high as 95.2% at certain target sites, with frequencies of simultaneous C-to-T and A-to-G conversions as high as 81.0%. In summary, PhieDBEs (especially C-A-D-SpGn) can produce diverse mutants and may prove useful in a wide variety of applications, including plant functional genomics, precise mutagenesis, directed evolution and crop genetic improvement, among others.

Robust and Lubricating Interface Semi-Interpenetrating Network on Inert Polymer Substrates Enabled by Subsurface-Initiated Polymerization.

Lubricating hydrogel coatings on inert rubber and plastic surfaces significantly reduce friction and wear, thus enhancing material durability and lifespan. However, achieving optimal hydration lubrication typically requires a porous polymer network, which unfortunately reduces their mechanical strength and limits their applicability where robust durability and wear-resistance are essential. In the research, a hydrogel coating with remarkable wear resistance and surface stability is developed by forming a semi-interpenetrating polymer network with polymer substrate at the interface. By employing a good solvent swelling method, monomers, and photoinitiators are embedded within the substrates' subsurface, followed by in situ polymerization under ultraviolet light, creating a robust semi-interpenetrating and entangled network structure. This approach, offering a thicker energy-dissipating layer, outperforms traditional surface modifications in wear resistance while preserving anti-fatigue, hydrophilicity, oleophobicity, and other properties. Adaptable to various rubber and plastic substrates by using suitable solvents, this method provides an efficient solution for creating durable, lubricating surfaces, broadening the potential applications in multiple industries.

Exploring the neurocognitive correlates of suicidal ideation in major depressive disorder: The role of frontoparietal and default mode networks.

Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD), often accompanied by cognitive alterations and emotional dysregulation. However, it is unclear whether cognitive dysfunction in patients with MDD is related to the presence or absence of SI and impaired connectivity within or between large-scale neurocognitive networks. Previous studies have shown that the frontoparietal network (FPN) and default mode network (DMN) are critical for cognitive control and emotional regulation. Participants were 51 MDD patients with suicidal ideation (MDDSI), 52 MDD patients without suicidal ideation (MDDNSI), and 55 healthy controls (HC). Using areas located within FPN and DMN networks as regions of interest (ROIs), we compared the cognitive performance of the three groups and the strength of the resting state functional connections (RSFC) within and between the FPN and DMN networks. Additionally, we examined the correlation between the strength of FC within the FPN and cognitive function in the SI group. Furthermore, network-based statistics (NBS) were used to correct for the strength of FPN and DMN functional connections. The study identified significant cognitive deficits in MDD patients. Reduced strength of FC was observed within the FPN and DMN networks in the SI group compared to the NSI group. In the SI group, the strength of FC within the FPN network was positively correlated with attention/vigilance. These insights underscore the critical roles of the FPN and DMN in the suicidal ideation, shedding light on the cognitively relevant neurobiological characteristics of MDDSI, providing new insights into the neural mechanisms of MDDSI. URL: https://www.chictr.org.cn/bin/project/edit?pid=131537. Registration number: ChiCTR2100049646.

Mechanisms of exacerbation of Th2-mediated eosinophilic allergic asthma induced by plastic pollution derivatives (PPD): A molecular toxicological study involving lung cell ferroptosis and metabolomics.

Polystyrene microplastics (PS-MP) and dibutyl phthalate (DBP) are plastic pollution derivatives (PPDs) commonly found in the natural environment. To investigate the effects of PPD exposure on the risk of allergic asthma, we established a PPD exposure group in a mouse model. The dose administered for PS-MP was 0.1 mg/d and for DBP was 30 mg/kg/d, with a 5-week oral administration period. The pathological changes of airway tissue and the increase of oxidative stress and inflammatory response confirmed that PPD aggravated eosinophilic allergic asthma in mice. The mitochondrial morphological changes and metabolomics of mice confirmed that ferrotosis and oxidative stress played key roles in this process. Treatment with 100 mg/Kg deferoxamine (DFO) provided significant relief, and metabolomic analysis of lung tissue supported the molecular toxicological. Our findings suggest that the increased levels of reactive oxygen species (ROS) in the lungs lead to Th2-mediated eosinophilic inflammation, characterized by elevated IL-4, IL-5, and eosinophils, and reduced INF-γ levels. This inflammatory response is mediated by the NFκB pathway and exacerbates type I hypersensitivity through increased IL-4 production. In this study, the molecular mechanism by which PPD aggravates asthma in mice was elucidated, which helps to improve the understanding of the health effects of PPD and lays a theoretical foundation for addressing the health risks posed by PPD.

Visual and refractive outcomes of opposite clear corneal incision combined with rotationally asymmetric multifocal intraocular lens implantation.

Purpose: To evaluate the visual and refractive outcomes of astigmatic cataract patients following opposite clear corneal incision (OCCI) combined with rotationally asymmetric multifocal intraocular lens (IOL) implantation. Setting: Department of Ophthalmology, Zhongshan Hospital (Xiamen), Fudan University, People's Republic of China. Design: Retrospective cohort study. Methods: This study comprised 58 cataract eyes of 54 patients with corneal astigmatism who underwent phacoemulsification and rotationally asymmetric multifocal IOL implantation which received either OCCI (OCCI group) or a single clear corneal incision (SCCI group). The follow-up period was 3 months after surgery. Distance, intermediate and near visual acuity, refractive outcomes, and corneal anterior keratometry were compared between the two groups. Vector analysis was used to evaluate astigmatism correction. Results: Three months after surgery, the distance, intermediate and near visual acuity, and sphere remained comparable between the two groups, but a significant difference was detected in residual astigmatism and anterior corneal keratometric astigmatism. In the OCCI group, the residual astigmatism and keratometric astigmatism were -0.60 ± 0.29 D and 0.59 ± 0.28 D, respectively, which were lower than those in SCCI groups (-1.18 ± 0.47 D and 1.15 ± 0.45 D, both p < 0.05). In vector analysis, the difference vector (DV), angle of error (AoE), absolute AoE, index of success (IoS) and correction index (CI) were statistically significantly different between the two groups (p < 0.05). Conclusion: OCCI combined with rotationally asymmetric multifocal intraocular lens implantation showed predictable and desirable efficacy in treating cataract patients with astigmatism.

Fertilization regime changes rhizosphere microbial community assembly and interaction in Phoebe bournei plantations.

Fertilizer input is one of the effective forest management practices, which improves soil nutrients and microbial community compositions and promotes forest productivity. However, few studies have explored the response of rhizosphere soil microbial communities to various fertilization regimes across seasonal dynamics. Here, we collected the rhizosphere soil samples from Phoebe bournei plantations to investigate the response of community assemblages and microbial interactions of the soil microbiome to the short-term application of four typical fertilizer practices (including chemical fertilizer (CF), organic fertilizer (OF), compound microbial fertilizer (CMF), and no fertilizer control (CK)). The amendments of organic fertilizer and compound microbial fertilizer altered the composition of rhizosphere soil bacterial and fungal communities, respectively. The fertilization regime significantly affected bacterial diversity rather than fungal diversity, and rhizosphere fungi responded more sensitively than bacteria to season. Fertilization-induced fungal networks were more complex than bacterial networks. Stochastic processes governed both rhizosphere soil bacterial and fungal communities, and drift and dispersal limitation dominated soil fungal and bacterial communities, respectively. Collectively, these findings demonstrate contrasting responses to community assemblages and interactions of rhizosphere bacteria and fungi to fertilizer practices. The application of organic fertilization strengthens microbial interactions and changes the succession of key taxa in the rhizosphere habitat. KEY POINTS: • Fertilization altered the key taxa and microbial interaction • Organic fertilizer facilitated the turnover of rhizosphere microbial communities • Stochasticity governed soil fungal and bacterial community assembly.

Real biofuel and fossil-fuel soot combustion activities in active and passive regeneration of diesel/gasoline particulate filters under different O2/NOx concentrations.

In this work, we aim to investigate and compare the combustion reactivities of real biofuel soot and fossil-fuel soot in the active and passive regeneration conditions of DPF and GPF through temperature-programmed oxidation (TPO). Higher reactivity of biofuel soot is achieved even under GPF conditions with extremely low oxygen concentration (~ 1%), which provides a great potential for low-temperature regeneration of GPF. Such a result is mainly attributed to the low graphitization and less surface C = C groups of biofuel soot. Unfortunately, the presence of high-content ashes (~ 47%) and P impurity in real biofuel soot hinder its combustion reactivity. TPO evidences that the O2/NOX-lacking conditions in GPF are key factors to impact the combustion of soot, especially fossil-fuel soot. This work provides some useful information for understanding real biofuel and fossil-fuel soot combustion in GPF and DPF regeneration and further improvement in filter regeneration process.

Causal association between circulating inflammatory markers and sciatica development: a Mendelian randomization study.

Background: This research explores the causal association between circulating inflammatory markers and the development of sciatica, a common and debilitating condition. While previous studies have indicated that inflammation may be a factor in sciatica, but a thorough genetic investigation to determine a cause-and-effect relationship has not yet been carried out. Gaining insight into these interactions may uncover novel treatment targets. Methods: We utilized data from the OpenGWAS database, incorporating a large European cohort of 484,598 individuals, including 4,549 sciatica patients. Our study focused on 91 distinct circulating inflammatory markers. Genetic variations were employed as instrumental variables (IVs) for these markers. The analysis was conducted using inverse variance weighting (IVW) as the primary method, supplemented by weighted median-based estimation. Validation of the findings was conducted by sensitivity studies, utilizing the R software for statistical computations. Results: The analysis revealed that 52 out of the 91 inflammatory markers studied showed a significant causal association with the risk of developing sciatica. Key markers like CCL2, monocyte chemotactic protein-4, and protein S100-A12 demonstrated a positive correlation. In addition, there was no heterogeneity or horizontal pleiotropy in these results. Interestingly, a reverse Mendelian randomization analysis also indicated potential causative effects of sciatica on certain inflammatory markers, notably Fms-related tyrosine kinase 3 ligands. Discussion: The study provides robust evidence linking specific circulating inflammatory markers with the risk of sciatica, highlighting the role of inflammation in its pathogenesis. These findings could inform future research into targeted treatments and enhance our understanding of the biological mechanisms underlying sciatica.

Enterprise financial sharing and risk identification model combining recurrent neural networks with transformer model supported by blockchain.

The objective of this study is to investigate methodologies concerning enterprise financial sharing and risk identification to mitigate concerns associated with the sharing and safeguarding of financial data. Initially, the analysis examines security vulnerabilities inherent in conventional financial information sharing practices. Subsequently, blockchain technology is introduced to transition various entity nodes within centralized enterprise financial networks into a decentralized blockchain framework, culminating in the formulation of a blockchain-based model for enterprise financial data sharing. Concurrently, the study integrates the Bi-directional Long Short-Term Memory (BiLSTM) algorithm with the transformer model, presenting an enterprise financial risk identification model referred to as the BiLSTM-fused transformer model. This model amalgamates multimodal sequence modeling with comprehensive understanding of both textual and visual data. It stratifies financial values into levels 1 to 5, where level 1 signifies the most favorable financial condition, followed by relatively good (level 2), average (level 3), high risk (level 4), and severe risk (level 5). Subsequent to model construction, experimental analysis is conducted, revealing that, in comparison to the Byzantine Fault Tolerance (BFT) algorithm mechanism, the proposed model achieves a throughput exceeding 80 with a node count of 146. Both data message leakage and average packet loss rates remain below 10 %. Moreover, when juxtaposed with the recurrent neural networks (RNNs) algorithm, this model demonstrates a risk identification accuracy surpassing 94 %, an AUC value exceeding 0.95, and a reduction in the time required for risk identification by approximately 10 s. Consequently, this study facilitates the more precise and efficient identification of potential risks, thereby furnishing crucial support for enterprise risk management and strategic decision-making endeavors.

Identifying drug candidates for pancreatic ductal adenocarcinoma based on integrative multiomics analysis.

Background: Due to a lack of early diagnosis methods and effective drugs, pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis. DNA methylation, transcriptome expression and gene copy number variation (CNV) have critical relationships with development and progression of various diseases. The purpose of the study was to screen reliable early diagnostic biomarkers and potential drugs based on integrative multiomics analysis. Methods: We used methylation, transcriptome and CNV profiles to build a diagnostic model for PDAC. The protein expression of three model-related genes were externally validated using PDAC samples. Then, potential therapeutic drugs for PDAC were identified by interaction information related to existing drugs and genes. Results: Four significant differentially methylated regions (DMRs) were selected from 589 common DMRs to build a high-performance diagnostic model for PDAC. Then, four hub genes, PHF12, FXYD3, PRKCB and ZNF582, were obtained. The external validation results showed that PHF12, FXYD3 and PRKCB protein expression levels were all upregulated in tumor tissues compared with adjacent normal tissues (P<0.05). Promising candidate drugs with activity against PDAC were screened and repurposed through gene expression analysis of online datasets. The five drugs, including topotecan, PD-0325901, panobinostat, paclitaxel and 17-AAG, with the highest activity among 27 PDAC cell lines were filtered. Conclusions: Overall, the diagnostic model built based on four significant DMRs could accurately distinguish tumor and normal tissues. The five drug candidates might be repurposed as promising therapeutics for particular PDAC patients.

Covalent Triazine Based Frameworks with Donor-Donor-π-Acceptor Structures for Dendrite-Free Lithium Metal Batteries.

The appearance of disordered lithium dendrites and fragile solid electrolyte interfaces (SEI) significantly hinder the serviceability of lithium metal batteries. Herein, guided by theoretical predictions, a multi-component covalent triazine framework with partially electronegative channels (4C-TA0.5TF0.5-CTF) is incorporated as a protective layer to modulate the interface stability of the lithium metal batteries. Notably, the 4C-TA0.5TF0.5-CTF with optimized electronic structure at the molecular level by fine-tuning the local acceptor-donor functionalities not only enhances the intermolecular interaction thereby providing larger dipole moment and improved crystallinity and mechanical stress, but also facilitates the beneficial effect of lithiophilic sites (C-F bonds, triazine cores, C=N linkages and aromatic rings) to further regulate the migration of Li+ and achieve a uniform lithium deposition behavior as determined by various in-depth in/ex situ characterizations. Due to the synergistic effect of multi-component organic functionalities, the 4C-TA0.5TF0.5-CTF modified full cells perform significantly better than the common two/three-component 2C-TA-CTF and 3C-TF-CTF electrodes, delivering an excellent capacity of 116.3 mAh g-1 (capacity retention ratio: 86.8%) after 1000 cycles at 5 C and improved rate capability. This work lays a platform for the prospective molecular design of improved organic framework relative artificial SEI for highly stable lithium metal batteries.

Parachlorometaxylenol stress caused multidrug-type antibiotic resistance genes proliferation via simultaneously reshaping microbial community and interfering metabolic traits during wastewater treatment process.

Despite biological wastewater treatment processes (e.g., sequencing batch reactors (SBR)) being able to reduce the dissemination of antibiotic resistance genes (ARGs), the variation of ARGs under exogenous pollutant stress is an open question. This work investigated the impacts of para-chloro-meta-xylenol (PCMX, typical antibacterial contaminants) on ARGs spread in long-term SBR operation. Although the SBR process inherently decreased ARGs abundance, the presence of PCMX substantially amplified both the prevalence (mainly multidrug) and abundance of total ARGs (1.17-fold of the control). Further analysis demonstrated that PCMX disintegrated sludge structures as well as increased membrane permeability, facilitating the release of mobile genetic elements and subsequent horizontal transfer of ARGs. In addition, PCMX selectively enriched potential ARG hosts, notably Nitrospira and Candidatus Accumulibacter, which predominantly served as multidrug ARG hosts. Concurrently, the self-adaptive functions of ARGs hosts in the PCMX-exposed SBR system were activated via quorum sensing, two-component regulatory system, ATP-binding cassette transporters, and bacterial secretion system. The upregulation of these metabolic pathways also contributed to the dissemination of ARGs.

Automatic Electrochemiluminescence Method for the Detection of Cancerous Exosomes Incorporating Specific Aptamer-Magnetic Beads and Signal Nanoprobes.

Exosomes, as an emerging biomarker, have exhibited remarkable promise in early cancer diagnosis. Here, a highly sensitive, selective, and automatic electrochemiluminescence (ECL) method for the detection of cancerous exosomes was developed. Specific aptamer-(EK)4 peptide-tagged magnetic beads (MBs-(EK)4-aptamer) were designed as a magnetic capture probe in which the (EK)4 peptide was used to reduce the steric binding hindrance of cancerous exosomes with a specific aptamer. One new universal ECL signal nanoprobe (CD9 Ab-PEG@SiO2ϵRu(bpy)32+) was designed and synthesized by using microporous SiO2 nanoparticles as the carrier for loading ECL reagent Ru(bpy)32+, polyethylene glycol (PEG) layer, and anticluster of differentiation 9 antibody (CD9 Ab). A "sandwich" biocomplex was formed on the surface of the magnetic capture probe after mixing the capture probe, target exosomes, and ECL signal nanoprobe, and then it was introduced into an automated ECL analyzer for rapid and automatic ECL measurement. It was found that the designed signal nanoprobe shows a 270-fold improvement in the signal-to-noise ratio than that of the ruthenium complex-labeled CD9 antibody signal probe. The relative ECL intensity was proportional to MCF-7 exosomes as a model in the range of 102 to 104 particle/µL, with a detection limit of 11 particle/µL. Furthermore, the ECL method was employed to discriminate cancerous exosomes based on fingerprint responses using the designed multiple magnetic capture probes and the universal ECL signal nanoprobe. This work demonstrates that the utilization of a designed automated ECL tactic using the MBs-(EK)4-aptamer capture probe and the CD9 Ab-PEG@SiO2ϵRu(bpy)32+ signal nanoprobe will provide a unique and robust method for the detection and discrimination of cancerous exosomes.

Multi-Condition Latent Diffusion Network for Scene-Aware Neural Human Motion Prediction.

Inferring 3D human motion is fundamental in many applications, including understanding human activity and analyzing one's intention. While many fruitful efforts have been made to human motion prediction, most approaches focus on pose-driven prediction and inferring human motion in isolation from the contextual environment, thus leaving the body location movement in the scene behind. However, real-world human movements are goal-directed and highly influenced by the spatial layout of their surrounding scenes. In this paper, instead of planning future human motion in a "dark" room, we propose a Multi-Condition Latent Diffusion network (MCLD) that reformulates the human motion prediction task as a multi-condition joint inference problem based on the given historical 3D body motion and the current 3D scene contexts. Specifically, instead of directly modeling joint distribution over the raw motion sequences, MCLD performs a conditional diffusion process within the latent embedding space, characterizing the cross-modal mapping from the past body movement and current scene context condition embeddings to the future human motion embedding. Extensive experiments on large-scale human motion prediction datasets demonstrate that our MCLD achieves significant improvements over the state-of-the-art methods on both realistic and diverse predictions.