Gene expression biomarkers have the potential to identify genotoxic and nongenotoxic carcinogens, providing opportunities for integrated testing and reducing animal use. In August 2022, an International Workshops on Genotoxicity Testing (IWGT) workshop was held to critically review current methods to identify genotoxicants using transcriptomic profiling. Here, we summarize the workgroup’s findings on the state of the science regarding the use of transcriptomic biomarkers to identify genotoxic chemicals in vitro and in vivo. A total of 1341 papers were examined to identify the biomarkers that show the most promise for identifying genotoxicants. This revealed two independently derived in vivo biomarkers and three in vitro biomarkers that, when used in conjunction with standard computational techniques, can identify genotoxic chemicals in vivo (rat or mouse liver) or in human cells in culture using different gene expression profiling platforms, with predictive accuracies of ≥ 92%. These biomarkers have been validated to differing degrees, but typically show high reproducibility across transcriptomic platforms and model systems. They offer several advantages for applications in different contexts of use in genotoxicity testing including: early signal detection, moderate to high-throughput screening capacity, adaptability to different cell types and tissues, and insights on mechanistic information on DNA-damage response. Workshop participants agreed on consensus statements to advance the regulatory adoption of transcriptomic biomarkers for genotoxicity. The participants agreed that transcriptomic biomarkers have the potential to be used in conjunction with other biomarkers in integrated test strategies in vitro and using short-term rodent exposures to identify genotoxic and nongenotoxic chemicals that may……………….

Neurodegenerative diseases like Alzheimer's, Parkinson's, Amyotrophic Lateral Sclerosis, and Huntington's share common underlying mechanisms driving progressive neuronal dysfunction and death. Key pathological features include protein aggregation, oxidative stress, mitochondrial dysfunction, and neuroinflammation. In Parkinson's disease, disruption of cellular homeostasis results from alpha-synuclein aggregation, whereas Amyotrophic Lateral Sclerosis is characterized by TDP-43 and superoxide dismutase 1 aggregates leading to motor neuron degeneration. Alzheimer's disease exhibits beta-amyloid plaques and hyperphosphorylated tau-related neurofibrillary tangles, impairing synaptic function and causing cognitive decline. Huntington's disease involves CAG repeat expansion in the HTT gene, causing mutant huntingtin protein aggregation and neuronal toxicity. Current therapeutic approaches provide symptomatic relief rather than targeting underlying disease mechanisms directly to potentially halt neuropathological progression or achieve neurorestoration. However, emerging therapies aim to intervene at these mechanistic levels. For example, in Parkinson's disease, treatments involving alpha-synuclein antibodies and small molecule inhibitors aim to mitigate protein aggregation. Amyotrophic Lateral Sclerosis therapies focus on reducing oxidative stress and inflammation, while Alzheimer's treatments aim to clear beta-amyloid plaques and tau tangles. Potential therapies for Huntington's disease include gene silencing and antisense oligonucleotides to reduce mutant huntingtin protein levels. Future directions include advancing personalized medicine approaches tailored to individual genetic and molecular profiles, alongside combination therapies targeting multiple pathological processes concurrently. Enhanced understanding of these shared mechanisms holds promise for developing effective disease-modifying treatments. Efforts towards neuroprotection and neurorestoration aim to not only alleviate symptoms but also slow or halt disease progression, offering hope for improved outcomes and quality of life for patients.

A Modern Occupation for Women: Feminization and the Professionalization of Nursing in China, 1920–1950

Posttraumatic stress disorder (PTSD) may develop following trauma exposure; however, not all trauma-exposed individuals develop PTSD, suggesting the presence of susceptibility and resilience factors. The gut microbiome and host genome, which are interconnected, have been implicated in the aetiology of PTSD. However, their interaction has yet to be investigated in a South African population. Using genome-wide genotype data and 16S rRNA gene V4 sequencing data from 53 trauma-exposed controls and 74 PTSD cases, we observed no significant association between the host genome and summed abundance of Mitsuokella, Odoribacter, Catenibacterium, and Olsenella, previously reported as associated with PTSD status in this cohort. However, PROM2 rs2278067 was found to interact with PTSD status to influence the summed abundance of these genera ( p < 0.014). Polygenic risk scores generated using genome-wide association study summary statistics from the PGC-PTSD Overall Freeze 2 were not predictive of gut microbial composition in this cohort. These preliminary results suggest a potential role for the interaction between genetic variation and gut microbial composition in the context of PTSD, underscoring the need for further investigation.

In contrast, but complementary to previous studies, this study examines the fatigue behaviour in Ti-6Al-4V obtained by electron beam powder bed fusion, focusing on damage initiation sites, fatigue damage progression, and correlating these with fatigue life curves. Three material conditions were considered: as-built specimens with original surfaces after printing (AB), as-built specimens with a machined and polished surface (MP), and hot isostatic pressed specimens with a machined and polished surface (H). Fatigue fracture surface topography was analysed using scanning electron microscopy and surface metrology microscopy. Different fatigue responses were observed, with crack initiation at surface roughness in AB, lack of fusion defects in MP, and phase facet formation in H specimens. Interaction between cracks and manufacturing defects was investigated. Kitagawa-Takahashi diagrams were applied successfully to AB and MP specimens. This study aims to enhance understanding of crack initiation and interaction mechanisms, improving life prediction capabilities through microstructure and defect-sensitive modelling.

A novel approach is proposed in this paper to reconstruct the far-field radiation pattern from the phaseless electric field of an antenna scanned on a single near-field sphere. It adopts the dipole equivalence approach to project the near-field electric field into a spherically distributed array of electric dipoles. We introduce a term representing the residue from the linearly correlated portion in the least-square problem associated with the dipole equivalence, namely the linear correlation residue (LCR). It is demonstrated that by iterative search to minimize the LCR using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), near-field phase distributions can be found efficiently from the magnitude-only near-field, and the far-field radiation pattern can be computed. Two representative case studies are given here to validate the proposed method. Results demonstrate good agreements between computations and simulations.

Ransomware is capable of causing significant damage through the encryption of critical data and the disruption of essential services. The novel concept of utilizing processor and disk usage data for real-time detection introduces a systemlevel perspective, enhancing the ability to detect and respond to ransomware activities with greater accuracy. The proposed methodology employs a random forest classifier to analyze high-resolution system metrics, such as CPU and disk usage patterns, to differentiate between normal and malicious behaviors. Experimental results demonstrate the model's effectiveness, achieving an accuracy of 96.7% while maintaining a low false positive rate. Feature importance analysis further reveals the critical role of entropy-based measures and peak CPU usage in identifying ransomware signatures. Comparative evaluation against other machine learning models, including Support Vector Machines and neural networks, demonstrates the superiority of the random forest approach in both predictive performance and computational efficiency. The research provides valuable insights into the potential of machine learning in enhancing cybersecurity measures and offers a foundation for future advancements in ransomware detection.

A document by Luciana Correa . Click on the document to view its contents.

not-yet-known not-yet-known not-yet-known unknown Aim: The current knowledge of salt-affected vegetation has been advanced in Europe, calling for a supra-regional assessment. We aim to evaluate the drivers of spatial variability and species diversity of inland saline habitats of the North German Plain, Pannonian Lowland and Transylvanian Basin. Location: Central Europe Methods: We compare the floristic and vegetation composition in 13 delineated subregions with high occurrence of salt steppes and marshes. We analyse data from extensive field surveys in the past 20 years and bioclimatic variables by descriptive statistics and ANOVA. Principal components analysis was performed to reduce the number of dimensions for each dataset, and correlation analysis to identify the statistical dependence between the species diversity of subregions and observed factors. Results: Despite the general uniformity typical for saline habitats, the subregions are more distinct than similar. Among the 107 native halophytic plant specialists, they have in common one obligate halophyte, Puccinellia distans agg., and seven facultative halophytes: Carex distans, Juncus gerardi, Lotus tenuis, Plantago maritima, Schoenoplectus lacustris subsp. glaucus and Trifolium fragiferum. The highest number of halophytes have Alföld (88), Dunántúl (75), Seewinkel (68), Podunajská nížina (65) and Câmpia Transilvaniei (65). Subregions Sachsen-Anhalt, Kujawy, Thüringen, Mostecká pánev, Harghita and Spiš hold on average half. The leading position in plant communities has Alföld. On larger scale, Pannonian Lowland and Transylvanian Basin share 63 halophytes, with the North German Plain 36 and 34 halophytes, respectively. A high proportion of coastal species (71%) was revealed, high representation have species of the Black Sea coast in the Pannonian region. Main conclusions: We confirmed only three endemic halophytes compared to the earlier assessments. The size of the subregion and its distance from the nearest seas did not affect the overall variability; the high diversity pattern is driven by the broader range of abiotic and biotic prerequisites.

Understanding codon usage has been vital for optimizing biotechnological applications across various domains. In response to this necessity, this review examines the impact of codon usage on protein expression systems, highlighting strategies to enhance yield and solubility in prokaryotic and eukaryotic hosts. We have discussed the role of codon usage in vaccine development, emphasizing how tailored codon sequences improve antigen expression and immune responses. In therapeutic protein production, optimizing codon preferences is shown to increase yields and reduce misfolding, facilitating the cost-effective manufacture of complex proteins. The review further explores the significance of codon usage in gene therapy, metabolic engineering, and synthetic biology, where precise codon design can drive innovations in genetic circuits and metabolic pathways. Additionally, we addressed emerging technologies and methodologies that enhance our understanding of codon optimization, paving the way for future advancements in biotechnology. By integrating insights from most recent studies, this paper underscores the importance of codon usage and its optimization, highlighting its transformative potential in enhancing the efficacy and scalability of biotechnological processes. Overall, we propose future directions for research, advocating for a multidisciplinary approach that combines computational tools and experimental validation to unlock the full potential of codon usage in biotechnology.

Wetland resources are crucial for sustaining human, plant, and animal life and maintaining climatic and hydrological cycles. However, wetlands have diminished over time. This study examined wetland dynamics, driving forces, and mitigation measures of wetland depletion over 35 years (1986-2021) in the Muga watershed, upper Abay basin, North East Ethiopia.. Landsat images from 1986, 1998, 2010, and 2021 and supervised classification methods were used to assess changes. Focus group discussions (FGDs), Key informants and household surveys through interviews and questionnaires identified the driving forces and mitigation activities of wetland depletion. Findings revealed significant land cover changes, with wetlands, forests, and grasslands declining by 12.42%, 9.62%, and 5.58% respectively, while agricultural land and built-up areas increased by 26.54% and 1.09%. Surveys, FGDs, and key informants indicated that 98.1%, 92.5%, and 93.8% attributed wetland depletion to population growth, farmland expansion, and overgrazing. Mitigation measures were largely absent, with 100%, 92.5%, 95%, 91.3%, and 78.8% of respondents indicating a lack of buffer zones, sediment control structures, wetland and floodplain protection, grazing management, and awareness programs. The study’s findings recommend that government and other stakeholders should establish policies, rules, informed decision-making, land use planning, effective wetland management practices, awareness initiatives, and family planning education to promote sustainable wetland resource use and management

not-yet-known not-yet-known not-yet-known unknown Oncolytic virotherapy (OVT) aims to disrupt the tumor microenvironment and provide a unique therapeutic approach against solid tumors. Herpes Simplex Virus Type-1 (HSV-1) has shown strong promise for treating various solid tumors and has been approved to treat melanoma and glioma in human patients. Previously, we reported the generation of an engineered HSV-1 vaccine strain VC2, which has shown exceptional promise as an oncolytic and immunotherapeutic virus. In the present work, we engineered VC2 to constitutively express the murine Granulocyte-Macrophage Colony-Stimulating Factor (GM-CSF) gene inserted in place of HSV-1 Glycoprotein C (gC). We tested the efficacy of VC2-GMCSF for its ability to generate anti-tumor response in the 4T1 stage four metastatic breast cancer mouse model. GM-CSF expression enhanced VC2 viral replication and infectious virus production. Tumors formed after 7 days of engraftment in the mammary fat-pad of Balb/CJ mice were treated by injecting ~10 6 plaque forming units (PFU) once. Intra-tumor treatment did not appreciably reduce average primary tumor sizes. However, metastatic foci were significantly reduced in mice lungs treated with VC2-GMCSF compared to VC2 or mock treatment. VC2-GMCSF intratumoral treatment induced a stronger intratumor T cell infiltration but not an increased cytotoxic activity. A significant T cell infiltration was observed in the metastatic areas in VC2-GMCSF treated animals, which was associated with reduced pro-tumor marker PDL1 and VEGF gene expression. These results show that constitutive expression of GM-CSF enhanced the overall efficacy of VC2 for oncolytic virotherapy. VC2-GMCSF holds promise as an oncolytic and immunotherapeutic virotherapy for breast and other cancers.

Background: The functions of GOLPH3, STIP1, and the STAT3 signaling pathway in the invasion and migration of CC cells were examined in this study. Method: High-speed centrifugation was used to collect the exosomes. The expression of GOLPH3, STIP1, and epithelial-mesenchymal transition (EMT)-related proteins in CC tissues, cells, and exosomes were analyzed using Western blotting (WB) experiments. The abilities of CC cell invasion and migration were evaluated by the Transwell assay. The binding relationship between GOLPH3 and STIP1 was validated through Co-immunoprecipitation (Co-IP), and their sublocalization in CC cells was determined by immunofluorescence detection under laser confocal microscopy. Immunohistochemistry (IHC) experiments detected the expression levels of each protein in the transplanted tumor mass. Animal experiments confirmed the impact of the GOLPH3/STIP1/STAT3 regulatory axis on the CC growth. Results: In CC tissues and cells, GOLPH3 was highly expressed, and silencing GOLPH3 not only greatly reduced CC cell invasion and migration but also prevented EMT. Furthermore, GOLPH3 and STIP1 interacted in CC cells, and the GOLPH3-STIP1 complex affected the capacity for cell invasion and migration by triggering the STAT3 signaling pathway. Noteworthily, GOLPH3, and STIP1 could also be detected in CC cell exosomes, and the exosomes carried the GOLPH3-ST1P1 complex to act on CC cells to activate intracellular STAT3 signaling, ultimately affecting the cancer cell migration and invasion. The above molecular regulatory mechanisms have also been validated in mice. Conclusion: The GOLPH3-STIP1 complex acted on surrounding CC cells through exosomes and activated the STAT3 signaling pathway to stimulate CC cell invasion and migration

We are describing a method tailored for in-cell selection of protease inhibitors. In this method, a target protease is co-expressed with a selective substrate, the product of which kills the host cells. Therefore, it can be applied to identify potential inhibitors, based on cell host survival, when inhibition of the target protease occurs. The method would be suitable for selection of inhibitors from intracellularly generated inhibitor libraries, like SICLOPPS, for instance. TEV protease was chosen for this proof-of-concept. The genetically encoded selective substrate is a single polypeptide chain, composed of three parts: (1) ccdB protein that can cause host cell death when it accumulates inside cell, (2) a protease cleavage sequence, that can be changed according to the target protease: ENLYFQG sequence for TEV substrate ( - predicted cleavage site) and (3) the ssrA sequence (AANDENYALAA), which drives the polypeptide to degradation by the ClpX/ClpP complex inside host E. coli cells. Conditions for controlled expression of this substrate, in which its steady-state concentration did not provoke significant death of host cells, were established. Co-expression of active TEV protease and this selective substrate (ccdB-ENLYFQG-ssrA) caused the death of a significant host cell population, while control assays with an inactive mutant TEV Asp81Asn did not. Details of the methodology used are given, providing the basis for the application of similar systems for other proteases of interest.

Chinese hamster ovary (CHO) cells are widely used to produce recombinant proteins, including monoclonal antibodies (mAbs), through various process modes. Traditionally, fed batch (FB) processes have been the standard. However, the shift towards high-density perfusion processes is driven by increased productivity, flexible facility footprints, and lower costs. Ensuring the clearance of process-related impurities, such as host cell proteins (HCPs), is crucial in biologics manufacturing. While purification processes remove most impurities, integrated strategies are being developed to enhance biologics purity and address high-risk HCPs. Current understanding of HCP expression dynamics in cell culture is limited. This study utilized data-independent acquisition (DIA) proteomics to compare the proteomic profiles of cell culture supernatants from 14 FB clones and 3 perfusion clones, all expressing the same mAb from the same host cell line. Results showed that perfusion processes enhance cell growth and productivity, exhibiting distinct proteomic profiles compared to FB processes. Perfusion processes also maintain a more stable HCP profile across clones, especially for 46 problematic HCPs monitored. Cluster analysis of FB proteomics revealed distinct abundance patterns and correlations with process parameters. Differential abundance analysis identified significant protein differences between the two processes. Compared to FB, the perfusion process may provide a less stressful cellular environment. This is the first extensive study characterizing HCPs expressed by different clones under different process modes. Further research could lead to strategies for preventing or managing problematic HCPs in biologics manufacturing.

Objective Intimate partner violence is a global health concern with a wide range of consequences. This article aims to assess the association between intimate partner violence among pregnant women and register-based psychiatric diagnoses, taking risk factors and non-responders into account. Design A cross-sectional study utilising Danish registers Setting Denmark Population 28,697 pregnant women Methods Pregnant women attending antenatal care in the Region of Southern Denmark, or the Capital Region, took part in the routinely collected PROdata questionnaire containing the Abuse Assessment Screen(AAS) during their first trimester, from December 2019 to September 2022. After questionnaire collection, data was linked with multiple Danish registers, including the Danish Psychiatric Treatment Register. On an individual level, the psychiatric diagnoses were detected in the registers, and if the woman had a psychiatric diagnosis within the last five years, she was grouped as either moderate or severe psychiatric diagnoses. Main Outcome Measures Moderate or severe psychiatric diagnoses Results In total, 28,697 women received the PROdata questionnaire, and 23,768 (82,8%) responded to the AAS. The prevalence of screening positive for IPV was 5.34% (n=1269). We found a strong association between intimate partner violence and both moderate and severe psychiatric diagnoses with an increased adjusted OR of 3.01 (95% CI: 2.51, 3.60) and 4.34 (95% CI: 3.27, 5.85), respectively, compared with women with no psychiatric diagnoses. Conclusion Our results show a strong link between Intimate Partner Violence and psychiatric diagnoses among pregnant women. It also provides important information on risk factors for violence and characteristics of non-responders to digital screening.

not-yet-known not-yet-known not-yet-known unknown Background: We have previously described that 87,6 % of children with juvenile colorectal polyp (JCP) from La Plata Children’s Hospital are sensitized to food allergens. Tissues of JCP are characterized by type 2 inflammation and the abundant presence of active sites of IgE synthesis. Objective: The aim of this work was to study a potential link between polyps and gut microbiota dysbiosis. Methods : We characterized bacterial populations in feces of food allergen-sensitized children with JCP, feces from healthy children and those associated with JCP tissues. Microbial diversity and composition were evaluated using next generation sequencing of the amplified 16S rRNA gene V3-V4 hypervariable region. Results: The principal component analysis applied to β-diversity discriminated well among sample groups. The taxonomic characterization of the bacterial communities in stool samples from food-sensitized children showed a reduced abundance of Bacteroidetes (Bacteroides) and, at the genera and species levels, an increased number of Mediterraneibacter faecis, Prevotella copri, Catenibacterium , and Prevotella hominis , Sutterella wadsworthensis and Phascolarctobacterium A succinatutens compared to feces of healthy children. We found that the microbiome associated with the polyp tissues was enriched in inflammation- and colorectal cancer associated bacteria, including Fusobacterium, Escherichia and Corynebacterium, with elevated levels of Escherichia fergussoni , Akkermansia muciniphila and Enterocloster . Conclusion: Our study highlights differences in bacterial diversity between food sensitized and healthy children’s feces, and that associated with the polyps. This is the first comprehensive description of JCP microbiota in food sensitized patients and may reveal mechanisms of allergic inflammation and polyp formation, underscoring the importance of monitoring for potential malignant lesions.

not-yet-known not-yet-known not-yet-known unknown Amy is a Research Advisor for the Ovarian Cancer Research Foundation (OCRF) and an Honorary Research Associate at the Hudson Institute of Medical Research in Melbourne, Australia. She was previously a postdoctoral researcher at the Hudson Institute focusing on ovarian leader cells and how they drive metastasis and chemoresistance. This article explores her journey from ovarian cancer researcher to a research advisory role in the not-for-profit sector. Driven by a deep love for science and a desire to make an impact, she navigated the challenges of the research environment and the uncertainties of career transition. Along the way, Amy discovered the importance of transferable skills, mentorship, and creativity, which have all played crucial roles in shaping her career. With a future full of possibilities, Amy’s commitment to making a difference continues to inspire and guide her.

Filicinic acid-based meroterpenoids (1‒9) with four kinds of skeletons were isolated from Dryopteris wallichiana. Compounds 1–4 represent the first examples of filicinic acid-ent-kaurane diterpene hybrids. Compounds 5‒6 are the rare hybrids of filicinic acid and carotane-type sesquiterpene. Compound 7 is an unusual rearranged filicinic acid-carotane-type sesquiterpene meroterpenoid. A plausible biosynthetic pathway for compounds 1−9 is proposed. Compounds 5, 6, (+)/(‒)-8, and (+)/(‒)-9 were validated to display anti-proliferative activity against PC-3 cells based on virtual screening, molecular docking and in vitro bioassay.

In the dynamic role as Cross-Functional Administrator, responsibilities range from managing multiple Office spaces across several regions to ensuring the smooth operation of facilities, health and safety, utilities, and budgeting. Here are key strategies to excel in this role, emphasizing operational efficiency, process improvement, and leadership, while drawing practical examples from Ghana and African contexts.

Incremental capacity analysis (ICA), where incremental charge (Q) movements associated with changes in potential are tracked, and cyclic voltammetry (CV), where current response to a linear voltage sweep is recorded, are used to investigate the properties of electrochemical systems. Electrochemical impedance spectroscopy (EIS), on the other hand, is a powerful, non-destructive technique that can be used to determine small-signal AC impedance over a wide frequency range. It is frequently used to design battery equivalent-circuit models. This manuscript explores the relationships between ICA, CV and EIS and demonstrates how sweep rate in CV is related to charging (C) rate in ICA. In addition, it shows the connection between observations linked to rate of charge movement in CV and ICA and intermittent, irregular behavior seen in EIS when performed on a battery. It also explains the use of an additional DC stimulus during EIS to ensure reliability of battery impedance data and to facilitate equivalent-circuit modeling, and suggests a method for obtaining CV-type data from a whole battery without risking its destruction.

The monitoring of wind turbine blade root load (BRL) has always been a valuable yet highly challenging problem. BRL monitoring is often measured directly using strain sensors, which is expensive to install and poses safety risks. Thus, it is necessary to explore an indirect measurement method that establishes a mapping relationship between BRL and easily measurable data. This paper presents a non-intrusive BRL monitoring method based on the vibrational signals at bearings (including main bearing, gearbox bearing, and generator bearing) and a new proposed AE-LSTM-Attention neural network. The proposed neural network incorporates autoencoder (AE) pre-training process, long short-term memory (LSTM) neural network, and channel attention mechanism to overcome difficulties in extracting and fusing long-term, high-frequency, and multi-channel signal features. Additionally, considering the wind turbine transmission mechanism, an optimal LSTM step number selection criterion is proposed. The wind turbine’s physical feature is innovatively bridged with the neural network training parameters, e.g., setting the transmission ratio of the gearbox as the number of LSTM steps, by which the most cost-effective prediction performance can be achieved. Experiments were conducted using data from actual operating wind turbines, and the results show that the proposed method can successfully achieve non-intrusive monitoring of BRL characteristics and outperform traditional methods in terms of predictive performance. The mapping relationship between wind turbine vibration signals and BRL characteristics can be established efficiently and accurately.

The unimolecular reactions of protonated α- and β-pinene ions were explored with a combination of collision-induced dissociation tandem mass spectrometry and theory. The two main dissociation reactions in each ion lead to the losses of neutral propene and isobutene. The difference observed between the two ions is a greater relative abundance of propene loss in the case of protonated a-pinene. Both ions were found to dissociate over the same minimum energy reaction pathway, the only difference being the site of initial protonation in the two ions. a-Pinene preferentially protonates at the bridging carbon, while b-pinene can only significantly protonate at the exocyclic double bond. This leads to a lower appearance energy for loss of isobutene, and thus relatively greater m/z 81 fragment ion abundance for b-pinene.

Background: The causal relationship between modifiable risk factors and inflammatory disorders of the breast (IDB) remains unclear, posing a challenge to the early identification and intervention of patients with IDB. The present study aimed to clarify the causal association between 30 predominant risk factors and IDB. Methods: Single-variable MR (SVMR) and multi-variable MR (MVMR) analyses were used to investigate the causal association between 30 modifiable risk factors and IDB. Inverse-variance weighting (IVW), MR‒Egger, and weighted median (WM) were further supported by several sensitivity analyses. Results: Genetically predicted Adult BMI females, body fat percentage, trunk fat mass, Waist circumference, Overall health rating, Medication use (glucocorticoids), and smoking status were found to increase the risk of IDB (all P < 0.05). No significant association was detected between interleukin levels, autoimmune diseases, pregnancy, infection and IDB. Multivariate MR identified body fat percentage, and smoking status as risk factors for IDB. Conclusions: We are the first to use MR analysis to explore the causal relationships between modifiable risk factors and IDB, revealing smoking status and body fat percentage at the genetic level are causally associated with a higher risk of IDB.