The photo-based treatment technology simultaneously removes resistant bacteria and resistant genes from wastewater.

Because of the recent widespread usage of antibiotics, the acquisition and dissemination of antibiotic-resistance genes (ARGs) were prevalent in the majority of habitats. Generally, the biological wastewater treatment processes used in wastewater treatment plants have a limited efficiencies of antibiotics resistant bacteria (ARB) disinfection and ARGs degradation and even promote the proliferation of ARGs. Problematically, ARB and ARGs in effluent pose potential risks if they are not further treated. Photocatalytic oxidation is considered a promising disinfection technology, where the photocatalytic process generates many free radicals that enhance the interaction between light and deoxyribonucleic acid (DNA) for ARB elimination and subsequent degradation of ARGs. This review aims to illustrate the progress of photocatalytic oxidation technology for removing antibiotics resistant (AR) from wastewater in recent years. We discuss the sources and transfer of ARGs in wastewater. The overall removal efficiencies of ultraviolet radiation (UV)/chlorination, UV/ozone, UV/H2O2, and UV/sulfate-radical based system for ARB and ARGs, as well as the experimental parameters and removal mechanisms, are systematically discussed. The contribution of photocatalytic materials based on TiO2 and g-C3N4 to the inactivation of ARB and degradation of ARGs is highlighted, producing many free radicals to attack ARB and ARGs while effectively limiting the horizontal gene transfer (HGT) in wastewater. Finally, based on the reviewed studies, future research directions are proposed to realize specific photocatalytic oxidation technology applications and overcome current challenges.

Bi-Constraints Diffusion: A Conditional Diffusion Model with Degradation Guidance for Metal Artifact Reduction.

In recent years, score-based diffusion models have emerged as effective tools for estimating score functions from empirical data distributions, particularly in integrating implicit priors with inverse problems like CT reconstruction. However, score-based diffusion models are rarely explored in challenging tasks such as metal artifact reduction (MAR). In this paper, we introduce the BiConstraints Diffusion Model for Metal Artifact Reduction (BCDMAR), an innovative approach that enhances iterative reconstruction with a conditional diffusion model for MAR. This method employs a metal artifact degradation operator in place of the traditional metal-excluded projection operator in the data-fidelity term, thereby preserving structure details around metal regions. However, scorebased diffusion models tend to be susceptible to grayscale shifts and unreliable structures, making it challenging to reach an optimal solution. To address this, we utilize a precorrected image as a prior constraint, guiding the generation of the score-based diffusion model. By iteratively applying the score-based diffusion model and the data-fidelity step in each sampling iteration, BCDMAR effectively maintains reliable tissue representation around metal regions and produces highly consistent structures in non-metal regions. Through extensive experiments focused on metal artifact reduction tasks, BCDMAR demonstrates superior performance over other state-of-the-art unsupervised and supervised methods, both quantitatively and in terms of visual results.

Characterization of a novel SCN5A mutation associated with long QT syndrome and arrhythmogenic right ventricular cardiomyopathy in a family.

Sudden cardiac death represents a significant diagnostic challenge for forensic pathologists, particularly in inherited arrhythmia syndromes or cardiomyopathies resulting from genetic defects. Molecular autopsies can reveal the underlying molecular etiology in such cases. In this study, we investigated a family with a history of sudden cardiac death to elucidate the molecular basis responsible for sudden cardiac death. The proband underwent a comprehensive forensic examination. Family members received thorough clinical evaluations, including electrocardiogram, Holter monitoring, echocardiography, and cardiac magnetic imaging. Whole exome sequencing and genetic analysis were performed on the deceased and her parents. In addition, Western blotting and patch-clamp recordings were employed to evaluate the expression and function of the mutant protein in vitro. Forensic examination diagnosed arrhythmogenic right ventricular cardiomyopathy (ARVC) as the cause of sudden death. Genetic analysis identified a novel missense mutation in SCN5A (p.V1323L), which was assessed as likely pathogenic by the ACMG guideline. Another family member carrying the mutation manifested long QT syndrome and mild cardiac fibrosis. The cellular electrophysiological study demonstrated that the mutation resulted in an enhanced late sodium current, suggesting it was a gain-of-function mutation. This study characterizes a novel SCN5A mutation that putatively causes long QT syndrome and may contribute to the development of ARVC. Our work expands the pathogenic spectrum of SCN5A variants and underscores the importance of molecular autopsy in sudden death cases, especially in those with suspected genetic disorders.

Determining high priority disinfection byproducts based on experimental aquatic toxicity data and predictive models: Virtual screening and in vivo study.

Only about 100 disinfection byproducts (DBPs) have been tested for their potential aquatic toxicity. It is not known which specific DBPs, DBP main groups, and DBP subgroups are more toxic due to the lack of experimental toxicity data. Herein, high priority specific DBPs, DBP main groups, DBP subgroups, most sensitive model aquatic species, potential PBT and PMT (persistent, bioaccumulative/mobile, and toxic) DBPs were virtually screened for 1187 updated DBPs inventory. Priority setting based on experimental and predicted acute and chronic aquatic toxicity data found that the aromatic and alicyclic DBPs in four DBPs main groups showed high priority because larger proportions of aromatic and alicyclic DBPs are in high hazard categories (i.e. Acute and/or Chronic Toxic-1 or Toxic-2) according to the criteria in GHS system compared to the aliphatic and heterocyclic DBPs. The halophenols, estrogen-DBPs, nonhalogenated esters, and nonhalogenated aldehydes were recognized as high priority DBPs subgroups. For specific DBPs, 19 and 31 DBPs should be highly concerned in the future study because both acute and chronic toxicity of those DBPs to all of the three aquatic life (algae, Daphnia magna, fish) were classified as Toxic-1 and Toxic-2, respectively. The Daphnia magna and algae were sensitive to the acute toxicity of DBPs, while the fish and Daphnia magna were sensitive to the chronic toxicity of DBPs. One potential PBT (Tetrachlorobisphenol A) and four potential PMT DBPs were identified. For verification, the acute toxicity of four DBPs on three aquatic organism were performed, and their tested acute toxicity data to three aquatic organisms were consistent with the predictions. Our results could be beneficial to government regulators to adopt effective measures to limit the discharge of high priority DBPs and help the scientific community to develop or improve disinfection processes to reduce the production of high priority DBPs.

DCAF15 control of cohesin dynamics sustains acute myeloid leukemia.

The CRL4-DCAF15 E3 ubiquitin ligase complex is targeted by the aryl-sulfonamide molecular glues, leading to neo-substrate recruitment, ubiquitination, and proteasomal degradation. However, the physiological function of DCAF15 remains unknown. Using a domain-focused genetic screening approach, we reveal DCAF15 as an acute myeloid leukemia (AML)-biased dependency. Loss of DCAF15 results in suppression of AML through compromised replication fork integrity and consequent accumulation of DNA damage. Accordingly, DCAF15 loss sensitizes AML to replication stress-inducing therapeutics. Mechanistically, we discover that DCAF15 directly interacts with the SMC1A protein of the cohesin complex and destabilizes the cohesin regulatory factors PDS5A and CDCA5. Loss of PDS5A and CDCA5 removal precludes cohesin acetylation on chromatin, resulting in uncontrolled chromatin loop extrusion, defective DNA replication, and apoptosis. Collectively, our findings uncover an endogenous, cell autonomous function of DCAF15 in sustaining AML proliferation through post-translational control of cohesin dynamics.

Plasma alpha B crystallin as potential biomarker for predicting pre-operative seizures in glioma.

PURPOSE: Glioma-associated epilepsy affects a significant proportion of glioma patients, contributing to disease progression and diminished survival rates. However, the lack of a reliable preoperative seizure predictor hampers effective surgical planning. This study investigates the potential of Alpha B crystallin protein (CRYAB) plasma levels as a predictive biomarker for epilepsy seizures in glioma patients. METHODS: Plasma samples were obtained from 75 participants, including 21 glioma patients with pre-operative epilepsy, 14 glioma patients without pre-operative epilepsy, and 21 age- and sex-matched control subjects. Additionally, 11 idiopathic epilepsy patients and 8 intractable epilepsy patients served as positive disease control groups. The study utilized ELISA to accurately quantify the circulating levels of CRYAB in the plasma samples of all participants. RESULTS: The analysis revealed a significant reduction in plasma CRYAB levels in glioma patients with pre-operative epilepsy and idiopathic epilepsy. The receiver operating characteristic (ROC) curve analysis displayed an impressive performance, indicating an AUC of 0.863 (95% CI, 0.810-0.916) across the entire patient cohort. Furthermore, plasma CRYAB levels exhibited a robust diagnostic capability, with an AUC of 0.9135, a sensitivity of 100.0%, and a specificity of 73.68%, effectively distinguishing glioma patients with preoperative epilepsy from those without epilepsy. The Decision Curve Analysis (DCA) underscored the clinical relevance of plasma CRYAB levels in predicting pre-operative epilepsy in glioma. CONCLUSION: The findings imply that the reduced levels of CRYAB may assist in prediction of seizure occurrence in glioma patients, although future large-scale prospective studies are warranted.

Process Manufacturing Intelligence Empowered by Industrial Metaverse: A Survey.

The intelligent goal of process manufacturing is to achieve high efficiency and greening of the entire production. Whereas the information system it used is functionally independent, resulting to knowledge gaps between each level. Decision-making still requires lots of knowledge workers making manually. The industrial metaverse is a necessary means to bridge the knowledge gaps by sharing and collaborative decision-making. Considering the safety and stability requirements of the process manufacturing, this article conducts a thorough survey on the process manufacturing intelligence empowered by industrial metaverse. First, it analyzes the current status and challenges of process manufacturing intelligence, and then summarizes the latest developments about key enabling technologies of industrial metaverse, such as interconnection technologies, artificial intelligence, cloud-edge computing, digital twin (DT), immersive interaction, and blockchain technology. On this basis, taking into account the characteristics of process manufacturing, a construction approach and architecture for the process industrial metaverse is proposed: a virtual-real fused industrial metaverse construction method that combines DTs with physical avatar, which can effectively ensure the safety of metaverse's application in industrial scenarios. Finally, we conducted preliminary exploration and research, to prove the feasibility of proposed method.

How far has the globe gone in achieving One Health? Current evidence and policy implications based on global One Health index.

Background: In the 21st century, as globalization accelerates and global public health crises occur, the One Health approach, guided by the holistic thinking of human-animal-environment and emphasizing interdisciplinary collaboration to address global health issues, has been strongly advocated by the international community. An immediate requirement exists for the creation of an assessment tool to foster One Health initiatives on both global and national scales. Methods: Built upon extensive expert consultations and dialogues, this follow-up study enhances the 2022 global One Health index (GOHI) indicator system. The GOHI framework is enriched by covering three indices, e.g. external drivers index (EDI), intrinsic drivers index (IDI), and core drivers index (CDI). The comprehensive indicator system incorporates 13 key indicators, 50 indicators, and 170 sub I-indicators, utilizing a fuzzy analytic hierarchy process to ascertain the weight for each indicator. Weighted and summed, the EDI, IDI, and CDI scores contribute to the computation of the overall GOHI 2022 score. By comparing the ranking and the overall scores among the seven regions and across 160 countries/territories, we have not only derived an overall profile of the GOHI 2022 scores, but also assessed the GOHI framework. We also compared rankings of indicators and sub I-indicators to provide greater clarity on the strengths and weaknesses of each region within the One Health domains. Results: The GOHI 2022 performance reveals significant disparities between countries/territories ranged from 39.03 to 70.61. The global average score of the GOHI 2022 is 54.82. The average score for EDI, IDI, and CDI are 46.57, 58.01, and 57.25, respectively. In terms of global rankings, countries from North America, Europe and Central Asia, East Asia and Pacific present higher scores. In terms of One Health domains of CDI, the lowest scores are observed in antimicrobial resistance (median: 43.09), followed by food security (median: 53.78), governance (median: 54.77), climate change (median: 64.12) and zoonotic diseases (median: 69.23). Globally, the scores of GOHI vary spatially, with the highest score in North America while lowest in sub-Saharan Africa. In addition, evidence shows associations between the socio-demographic profile of countries/territories and their GOHI performance in certain One Health scenarios. Conclusion: The objective of GOHI is to guide impactful strategies for enhancing capacity building in One Health. With advanced technology and an annually updated database, intensifying efforts to refine GOHI's data-mining methodologies become imperative. The goal is to offer profound insights into disparities and progressions in practical One Health implementation, particularly in anticipation of future pandemics.

Associations between Unsociability and Peer Problems in Chinese Children and Adolescents: A Meta-Analysis.

Research has shown that unsociability, reflected as a personal choice, is not necessarily associated with socio-emotional problems in Western countries. However, the associations between unsociability and peer problems are consistently evident in Chinese culture, yet the strength and direction in these associations are mixed. The present study aimed to examine whether unsociability is associated with peer problems and explored the potential moderators among the associations. A meta-analysis was conducted using publications that measured unsociability and peer problems. A total of 21 articles involving 43 effect sizes from 12,696 Chinese children and adolescents were included. The results revealed that (1) unsociability was positively associated with peer problems (r = 0.32, p < 0.001) among children and adolescents. (2) Informants (i.e., self-reports, peer nominations, teacher ratings, and parent ratings) and living areas (i.e., urban, suburban, and rural areas) significantly moderated the associations between unsociability and peer problems. Specifically, the associations were stronger for peer-nominated unsociability, self-reported peer problems, and samples in suburban areas. These findings shed light on unsociability linked to higher levels of peer problems among Chinese children and adolescents. Still, the influences are unique to peer problems and moderated by both data sources and environmental factors.

Follicular fluid lipidomics analysis reveals altered lipid signatures in patients with polycystic ovary syndrome.

BACKGROUND: This research investigates the metabolic profiles of follicular fluid (FF) samples from patients with polycystic ovary syndrome (PCOS) undergoing in vitro fertilisation and aims to identify diagnostic and therapeutic biomarkers for PCOS through lipidomic analysis. METHODS: We performed non-targeted lipid analysis of FF samples from women with PCOS (n = 6) and normal controls (n = 6) using ultra-high-performance liquid chromatography-tandem mass spectrometry. Differential lipids between the two groups were screened using multidimensional statistical analysis, followed by fold change analysis and t-tests to identify potential PCOS biomarkers. RESULTS: Multivariate statistical analysis revealed significant differences in FF lipid levels between the PCOS and control groups. Five different lipids were selected as standards, with p < .05. Phosphatidylcholine (PC), the main differentially expressed lipid, was significantly increased in the FF of the POCS group and was closely related to other lipids. CONCLUSIONS: Using ultra-high-performance liquid chromatography-tandem mass spectrometry, we investigated lipid biomarkers based on FF lipidomics to provide useful information for the discovery of diagnostic markers for PCOS. Our study identified five distinct lipids as potential markers of PCOS, with PC being the primary aberrant lipid found in the FF of patients with PCOS.

Follicular fluid (FF) is a complex microenvironment involved in oocyte growth, follicular maturation and germ cell­somatic cell communication. All metabolites during oocyte growth are collected from the FF. This study used lipidomic analysis to identify differences in FF lipids between normal women and those diagnosed with polycystic ovary syndrome (PCOS). The pathogenesis of PCOS is associated with abnormal metabolism of glyceroglycolipids and sphingomyelin. Here, we found that phosphatidylcholine is the main abnormal lipid in FF in patients with PCOS. Our study informs the future research into the development of diagnostic markers for PCOS to be used in clinical practice.

Potential of artificial intelligence in reducing energy and carbon emissions of commercial buildings at scale.

Artificial intelligence has emerged as a technology to enhance productivity and improve life quality. However, its role in building energy efficiency and carbon emission reduction has not been systematically studied. This study evaluated artificial intelligence's potential in the building sector, focusing on medium office buildings in the United States. A methodology was developed to assess and quantify potential emissions reductions. Key areas identified were equipment, occupancy influence, control and operation, and design and construction. Six scenarios were used to estimate energy and emissions savings across representative climate zones. Here we show that artificial intelligence could reduce cost premiums, enhancing high energy efficiency and net zero building penetration. Adopting artificial intelligence could reduce energy consumption and carbon emissions by approximately 8% to 19% in 2050. Combining with energy policy and low-carbon power generation could approximately reduce energy consumption by 40% and carbon emissions by 90% compared to business-as-usual scenarios in 2050.

Genomic characterization of Escherichia coli harbor a polyketide synthase ( pks ) island associated with colorectal cancer (CRC) development.

The E. coli strain harboring the polyketide synthase ( Pks) island encodes the genotoxin colibactin, a secondary metabolite reported to have severe implications for human health and for the progression of colorectal cancer. The present study involved whole-genome-wide comparison and phylogenetic analysis of pks harboring E. coli isolates to gain insight into the distribution and evolution of these organism. Fifteen E. coli strains isolated from patients with ulcerative colitis were sequenced, 13 of which harbored pks islands. In addition, 2,654 genomes from the public database were also screened for pks harboring E. coli genomes, 158 of which were pks -positive isolates. Whole-genome-wide comparison and phylogenetic analysis revealed that 171 (158+13) pks -positive isolates belonged to phylogroup B2, and most of the isolates associated to sequence types ST73 and ST95. One isolate from an ulcerative colitis (UC) patient was of the sequence type ST8303. The maximum likelihood tree based on the core genome of pks -positive isolates revealed horizontal gene transfer across sequence types and serotypes. Virulome and resistome analyses revealed the preponderance of virulence genes and a reduced number of antimicrobial genes in Pks -positive isolates. This study strongly contributes to understanding the evolution of pks islands in E. coli .

Children's oppositional defiant disorder symptoms and neural synchrony in mother-child interactions: An fNIRS study.

Interpersonal neural synchrony (INS) between mothers and children responds to the temporal similarity of brain signals in joint behavior between dyadic partners and is considered an important neural indicator of the formation of adaptive social interaction bonds. Parent-child interactions are particularly important for the development and maintenance of oppositional defiant disorder (ODD) in children, but the underlying neurocognitive mechanisms are unknown. Therefore, in the current study we measured INS between mothers and children in interactions by using simultaneous functional Near-infrared Spectroscopy (fNIRS), and explored its association with ODD symptoms in children. Seventy-two mother-child dyads were recruited to participate in the study, including 35 children with ODD and 37 healthy children to be used as a control. Each mother-child dyad was measured for neural activity in frontal, parietal, and temporal lobe regions while completing free-play as well as positive, and negative topic discussion tasks. We used Phase-locked value to calculate the synchrony strength and then used the K-means algorithm and k-space based alignment tests to confirm the specific patterns of parent-child synchrony in different brain areas. The results showed that, in free-play (right MFG and bilateral SFG), positive (left TPJ and bilateral SFGdor), and negative (bilateral SFGmed, right ANG, and left MFG) topic discussions, the mother-child pairs showed different patterns of INS. These specific INS patterns were significantly lower in the ODD group compared to the control group and were negatively associated with ODD symptoms in children. Network analyses showed that these INS patterns were connected to different nodes in the ODD symptom network. Our findings suggest that ODD mother-child dyads exhibit lower neural synchrony across a wide range of parent-child interactions. Neural synchrony in the context of interpersonal interactions provides new insights into understanding the neural mechanisms of ODD and can be used as an indicator of neural and socio-environmental factors in the network of psychological disorder symptoms.

Netrin-1-engineered endothelial cell exosomes induce the formation of pre-regenerative niche to accelerate peripheral nerve repair.

The formation of vascular niche is pivotal during the early stage of peripheral nerve regeneration. Nevertheless, the mechanisms of vascular niche in the regulation of peripheral nerve repair remain unclear. Netrin-1 (NTN1) was found up-regulated in nerve stump after peripheral nerve injury (PNI). Herein, we demonstrated that NTN1-high endothelial cells (NTN1+ECs) were the critical component of vascular niche, fostering angiogenesis, axon regeneration, and repair-related phenotypes. We also found that NTN1+EC-derived exosomes (NTN1 EC-EXO) were involved in the formation of vascular niche as a critical role. Multi-omics analysis further verified that NTN1 EC-EXO carried a low-level expression of let7a-5p and activated key pathways associated with niche formation including focal adhesion, axon guidance, phosphatidylinositol 3-kinase-AKT, and mammalian target of rapamycin signaling pathway. Together, our study suggested that the construction of a pre-regenerative niche induced by NTN1 EC-EXO could establish a beneficial microenvironment for nerve repair and facilitate functional recovery after PNI.

TRAF6 Inhibitors from Marine Compound Library: Pharmacophore, Virtual Screening, Fragment Replacement, ADMET, and Molecular Dynamics.

TRAF6 is an E3 ubiquitin ligase that plays a crucial role in cell signaling. It is known that MMP is involved in tumor metastasis, and TRAF6 induces MMP-9 expression by binding to BSG. However, inhibiting TRAF6's ubiquitinase activity without disrupting the RING domain is a challenge that requires further research. To address this, we conducted computer-based drug screening to identify potential TRAF6 inhibitors. Using a ligand-receptor complex pharmacophore based on the inhibitor EGCG, known for its anti-tumor properties, we screened 52,765 marine compounds. After the molecular docking of 405 molecules with TRAF6, six compounds were selected for further analysis. By replacing fragments of non-binding compounds and conducting second docking, we identified two promising molecules, CMNPD9212-16 and CMNPD12791-8, with strong binding activity and favorable pharmacological properties. ADME and toxicity predictions confirmed their potential as TRAF6 inhibitors. Molecular dynamics simulations showed that CMNPD12791-8 maintained a stable structure with the target protein, comparable to EGCG. Therefore, CMNPD12791-8 holds promise as a potential inhibitor of TRAF6 for inhibiting tumor growth and metastasis.

The Interactions between Ionic Liquids and Lithium Polysulfides in Lithium-Sulfur Batteries: A Systematic Density Functional Theory Study.

Ionic liquids (ILs) based on hybrid anions have recently garnered attention as beguiling alternative electrolytes for energy storage devices. This attention stems from the potential of these asymmetric anions to reduce the melting point of ILs and impede the crystallization of ILs. Furthermore, they uphold the advantages associated with their more conventional symmetric counterparts. In this study, we employed dispersion-corrected density functional theory (DFT-D) calculations to scrutinize the interplay between two hybrid anions found in ionic liquids [FTFSA]- and [MCTFSA]- and the [C4mpyr]+ cation, as well as in lithium polysulfides in lithium-sulfur batteries. For comparison, we also examined the corresponding ILs containing symmetric anions, [TFSA]- and [FSA]-. We found that the hybrid anion [MCTFSA]- and its ionic liquid exhibited exceptional stability and interaction strength. Additionally, our investigation unveiled a remarkably consistent interaction between ionic liquids (ILs) and anions with lithium polysulfides (and S8) during the transition from octathiocane (S8) to the liquid long-chain Li2Sn (4 ≤ n ≤ 8). This contrasts with the gradual alignment observed between cations and lithium polysulfides during the intermediate state from Li2S4 to the solid short-chain Li2S2 and Li2S1. We thoroughly analyzed the interaction mechanism of ionic liquids composed of different symmetry anions and their interactions with lithium polysulfides.

Plant-Derived Exosomes as Novel Nanotherapeutics Contrive Glycolysis Reprogramming-Mediated Angiogenesis for Diabetic Ulcer Healing.

Reversal of endothelial cell (EC) dysfunction under high-glucose (HG) conditions to achieve angiogenesis has remained a big challenge in diabetic ulcers. Herein, exosomes derived from medicinal plant ginseng (GExos) were shown as excellent nanotherapeutics with biomimetic cell membrane-like structures to be able to efficiently transfer the encapsulated active substances to ECs, resulting in a marked reprogramming of glycolysis by up-regulating anaerobic glycolysis and down-regulating oxidative stress, which further restore the proliferation, migration, and tubule formation abilities of ECs under HG conditions. In vivo, GExos enhance the angiogenesis and nascent vessel network reconstruction in full-thickness diabetic complicated skin ulcer wounds in mice with high biosafety. GExos were shown as promising nanotherapeutics in stimulating glycolysis reprogramming-mediated angiogenesis in diabetic ulcers, possessing wide application potential for reversing hyperglycemic dysangiogenesis and stimulating vascular regeneration.

Synergetic effects during co-pyrolysis of waste textiles and Ca/Fe-rich industrial sewage sludge: Reaction kinetics and product distribution.

Co-pyrolysis is a promising technology for industrial organic waste to utilize their unique resource and energy properties for efficient conversion into valuable products. This study was the first time to characterize the co-pyrolysis of waste textiles with Ca-rich industrial sludge and Fe-rich industrial sludge on a laboratory-scale fixed bed. The properties, mechanisms, gas, oil and carbon production were investigated as a function of temperature and mixing type. Co-pyrolysis increased the total weight loss from 50.05 % to 69.81 % for Ca-rich industrial sludge mixed with 50 % waste textiles and from 49.13 % to 70.01 % for Fe-rich industrial sludge mixed with 50 % waste textiles. The activation energy of co-pyrolysis was approximately 50 % lower compared to the pyrolysis of waste textiles alone. The optimal reaction model for the different reaction stages for all samples was three diffusion (D3). Co-pyrolysis resulted in lower CO and CO2 emission temperatures of about 25-110 °C and produced more short-chain organic compounds (C < 10). Co-pyrolysis produced more aldehydes and ketones organics. Moreover, co-pyrolysis char exhibited an elevated level of fatty alkyl side chains and bridge branching, as well as higher degrees of aromatization and stability. This study offers valuable insights into the potential application of pyrolysis for the management of Ca/Fe-rich industrial sludge and waste textiles, thereby serving as a basis for future utilization endeavors.