Browse Articles

B-1 B cells lose self-control in SCD

How I treat older patients with relapsed/refractory diffuse large B-cell lymphoma

Abstract Diffuse large B-cell lymphoma (DLBCL) is an aggressive, yet curable, malignancy, but older patients are at higher risk of relapsed disease because they may not be eligible for full-intensity frontline chemoimmunotherapy or have comorbidities that limit standard treatments. Recent years have brought more treatment options than ever for this patient population, but it remains challenging to determine which can be safely and effectively offered to older patients. Formal determinations of fitness including geriatric assessments remain critical, but there is less guidance on how to best use this tool in the relapsed setting. Chimeric antigen receptor T-cell therapy is accessible to older patients, provided they can be supported through the intensive road to this treatment. If relapse occurs despite this or alternative therapies are preferred, many novel therapeutic options and combinations exist with some potential modifications for older adults, such as bispecific antibodies, tafasitamab and lenalidomide, polatuzumab-containing regimens, or loncastuximab tesirine. This article provides a summary of our approach to the management of this diverse population of older patients with relapsed or refractory DLBCL.

Is it time to screen for multiple myeloma?

Current myeloproliferative neoplasm scoring systems for clinical practice

Abstract BCR::ABL1-negative myeloproliferative neoplasms (MPNs) are clonal hematologic malignancies that are caused by the proliferation of myeloid cells that harbor a JAK-STAT pathway activating driver mutation. MPN management recommendations are based on the evaluation of different risks to prevent disease evolution–associated events while preserving patients’ quality of life. Such risks can be common across all MPNs or specific to each subtype (polycythemia vera [PV], essential thrombocythemia [ET], prefibrotic myelofibrosis [MF], and primary MF). Patients with MF harbor the worse prognosis, and hematopoietic stem cell transplantation (HSCT) is the only curative treatment at the expense of a high rate of morbidity and mortality. Therefore, accurate scoring systems to estimate overall survival are crucial for the management of patients with MF and the selection for HSCT. In PV and ET, the prediction of vascular events is prioritized given their higher incidence and related morbidity and mortality. Finally, quality of life evaluation is important for all subtypes. To predict these risks and adapt MPN therapeutic strategies, clinical risk scores have been developed over the past decades and more recently have incorporated molecular risk factors for more accurate risk stratification. The large number of scoring systems available, combined with disease heterogeneity and the necessity to predict diverse outcomes, make it difficult for clinicians to choose the most appropriate score to evaluate their patients’ risk in 2024. Here, we provide an overview of MPN disease evolution–associated event incidence and conduct an exhaustive comparative review of the scoring systems currently available for each risk. Finally, we propose an algorithm for the use of these scores in clinical practice in each MPN subtype.

Multiview attention networks for fine-grained watershed categorization via knowledge distillation

With the rapid development of artificial intelligence technology, an increasing number of village-related modeling problems have been addressed. However, first, the exploration of village-related watershed fine-grained classification problems, particularly the multi-view watershed fine-grained classification problem, has been hindered by dataset collection limitations; Second, village-related modeling networks typically employ convolutional modules for attentional modeling to extract salient features, yet they lack global attentional feature modeling capabilities; Lastly, the extensive number of parameters and significant computational demands render village-related watershed fine-grained classification networks infeasible for end-device deployment. To tackle these challenges, we introduce a multi-view attention mechanism designed for precise watershed classification, leveraging knowledge distillation techniques, abbreviated as MANet-KD. Specifically, first, we have developed the inaugural multi-view watershed classification dataset, termed MVWD.Second, we introduce a cross-view attention module (CVAM), which models salient features from intersecting views with global attention, enhancing the accuracy and precision of watershed classification. This module enhances fine-grained classification accuracy. Based on the above proposed CVAM, we propose a heavyweight MANet-Teacher and a lightweight MANet-Student, and finally, we introduce an Attention Knowledge Distillation (AKD) strategy that effectively transfers critical feature knowledge from the teacher network to the student network, utilizing the AKD approach for enhanced learning outcomes. The experimental results show that the proposed MANet-Teacher achieves state-of-the-art performance with 78.51% accuracy, and the proposed MANet-Student achieves comparable performance to MANet-Teacher with 6.64M parameters and 1.68G computation. The proposed MANet-KD achieves a good balance of performance and efficiency in the multi-view fine-grained watershed classification task. To facilitate further research in multi-view fine-grained watershed classification, all datasets, codes, and benchmark outcomes will be made available to the public. https://github.com/Jack13026212687/MANet-KD.

Extraction of coronary thrombus-derived exosomes from patients with acute myocardial infarction and its effect on the function of adventitial cells

Background Type I acute myocardial infarction (T1MI) has a very high morbidity and mortality rate. The role of thrombus-derived exosomes (TEs) in T1MI is unclear. Methods The objective of this study was to identify the optimal thrombolytic drug and concentration for extracting TEs. To this end, a series of time and concentration combinations were tested. Subsequently, the effect of TEs on thrombus-adjacent cells was investigated. Finally, we conducted lncRNA microarray analysis on the extracted TEs (GSE213115). Results TEs has been demonstrated to promote necrosis, autophagy, and ferroptosis of human cardiomyocytes, while inhibiting the proliferation and migration of human umbilical vein endothelial cells (HUVECs). Furthermore, TEs can stimulate the proliferation and migration of smooth muscle cells, and induce a transformation from a contractile to a secretory phenotype. Bioinformatics analysis revealed that five lncRNAs, AC068418.2, AC010186.3, AL031430.1, AC121333.1, and AL136526.1, exhibited significant differential expression in TE and regulated cell autophagy and ferroptosis by directly binding to TP53, TP63, and RELA, respectively. Conclusions We demonstrate that TEs as a potential target and research direction for the treatment of heart failure after T1MI. TEs may regulate ferroptosis and autophagy in thrombus-adjacent cells through the enrichment of certain lncRNAs.

UAV target tracking method based on global feature interaction and anchor-frame-free perceptual feature modulation

Target tracking techniques in the UAV perspective utilize UAV cameras to capture video streams and identify and track specific targets in real-time. Deep learning UAV target tracking methods based on the Siamese family have achieved significant results but still face challenges regarding accuracy and speed compatibility. In this study, in order to refine the feature representation and reduce the computational effort to improve the efficiency of the tracker, we perform feature fusion in deep inter-correlation operations and introduce a global attention mechanism to enhance the model’s field of view range and feature refinement capability to improve the tracking performance for small targets. In addition, we design an anchor-free frame-aware feature modulation mechanism to reduce computation and generate high-quality anchors while optimizing the target frame refinement computation to improve the adaptability to target deformation motion. Comparison experiments with several popular algorithms on UAV tracking datasets, such as UAV123@10fps, UAV20L, and DTB70, show that the algorithm balances speed and accuracy. In order to verify the reliability of the algorithm, we built a physical experimental environment on the Jetson Orin Nano platform. We realized a real-time processing speed of 30 frames per second.

Metastatic melanoma: An integrated analysis to identify critical regulators associated with prognosis, pathogenesis and targeted therapies

Metastatic melanoma causes a high rate of mortality. We conducted an integrated analysis to identify critical regulators associated with the prognosis, pathogenesis, and targeted therapies of metastatic-melanoma. A microarray dataset, GSE15605, including 12 metastatic-melanoma and sixteen normal skin (NS) samples, were obtained from the GEO database. After exploration of DEGs of NS and metastatic-melanoma, identification of relevant transcription factors (TFs) and kinases, the Gene Ontology (GO), and pathways analyses of DEGs were performed. Protein-protein interaction (PPI) networks were evaluated by the STRING and Cytoscape. Subsequently, the hub genes were selected using GEPIA. Survival analysis was performed using the TCGA. To identify microRNA and lncRNA DEGs of the melanoma-associated genes miRwalk and FANTOM6 were employed. In metastatic-melanoma samples 285 and 1173 genes were up and down-regulated, respectively. The upregulated genes were mostly involved in granulocyte chemotaxis, positive regulation of calcium ion transmembrane transport, and melanin biosynthetic process. Five hub genes including CXCL11, ICAM1, LEF1, MITF, and STAT1 were identified, SUZ12, SOX2, TCF3, NANOG, and SMAD4 were determined as the most significant TFs in metastatic-melanoma. Furthermore, CDK2, GSK3B, CSNK2A1, and CDK1 target the highest amounts of genes associated with disease. The DGIdb analysis results show the match drugs for five hub genes. MiRNAs analysis revealed hsa-miR-181c-5p, hsa-miR-30b-3p, hsa-miR-3680-3P, hsa-miR-4659a-3p, hsa-miR-4687-3P, and hsa-miR-6808-3P could regulate the hub genes, whereas RP11-553K8.5 and SRP14-AS1 were identified as the top significant lncRNA. The items recognized in the current study can be used as potential biomarkers for diagnostic, predictive, and might helpful to develop targeted combined therapies.

Achieving universal sanitation in Ghana: An analysis of key drivers of toilet ownership among property owners in Urban areas

Access to safe sanitation facilities remains a critical public health concern, especially in rapidly urbanizing countries like Ghana. This study investigates the determinants of household toilet ownership among property owners in three urban districts in Ghana. Using a cross-sectional survey design, data were collected from 1,256 property owners selected through a multi-stage stratified sampling procedure. Logistic regression analysis revealed that toilet ownership is significantly associated with the age and education level of property owners, community classification, building characteristics, and household income. Older property owners were more likely to own toilets (OR = 1.014 per year increase), as were those with higher education levels (OR = 1.752 for secondary, OR = 4.489 for tertiary education). Medium-class communities (OR = 2.013) completed buildings (OR = 2.625), and those constructed with sandcrete (OR = 12.755) were more likely to have toilets. Higher household income (OR = 1.00) correlated positively with toilet ownership. We conclude that enforcing building regulations requiring toilet facilities in all properties is crucial for improving sanitation in urban Ghana. Additionally, innovative sanitation financing interventions that subsidize the costs of sanitation facilities can be effective in addressing financial barriers and increasing household toilet ownership.

Development of a broad-spectrum epitope-based vaccine against Streptococcus pneumoniae

Streptococcus pneumoniae (SPN) is a significant pathogen causing pneumonia and meningitis, particularly in vulnerable populations like children and the elderly. Available pneumonia vaccines have limitations since they only cover particular serotypes and have high production costs. The emergence of antibiotic-resistant SPN strains further underscores the need for a new, cost-effective, broad-spectrum vaccine. Two potential vaccine candidates, CbpA and PspA, were identified, and their B-cell, CTL, and HTL epitopes were predicted and connected with suitable linkers, adjivant and PADRE sequence. The vaccine construct was found to be antigenic, non-toxic, non-allergenic, and soluble. The three-dimensional structure of the vaccine candidate was built and validated. Docking analysis of the vaccine candidate by ClusPro demonstrated robust and stable binding interactions between the MEV and toll-like receptor 4 in both humans and animals. The iMOD server and Amber v.22 tool has verified the stability of the docking complexes. GenScript server confirmed the high efficiency of cloning for the construct and in-silico cloning into the pET28a (+) vector using SnapGene, demonstrating successful translation of the epitope region. Immunological responses were shown to be enhanced by the C-IMMSIM server. This study introduced a strong peptide vaccine candidate that has the potential to contribute to the development of a rapid and cost-effective solution for combating SPN. However, experimental verification is necessary to evaluate the vaccine’s effectiveness.

Predicting marine habitat for marbled murrelets during breeding and nonbreeding seasons in the Salish Sea, British Columbia, Canada

The marbled murrelet (Brachyramphus marmoratus) is a small seabird inhabiting coastal regions along the Pacific coast of North America, and nests in old-growth forests usually within 80 km from shore. The Canadian population of marbled murrelets is listed as Threatened under the federal Species at Risk Act. To investigate the species’ marine distribution, we conducted analyses of the occurrence of marbled murrelets at-sea between 2000 and 2022, utilizing at-sea and marine shoreline surveys in the Canadian portion of the Salish Sea. The data were divided into breeding season (April to August) and non-breeding season (September to March) to examine the relationship between environmental covariates and the species’ distribution. We considered terrestrial covariates related to potential nesting habitat, as well as marine covariates related to Pacific sand lance (Ammodytes personatus) quality habitat, slope, depth, streams, tidal currents, shorelines and climate indices (NPGO). We compared marine distribution between breeding and nonbreeding seasons and predicted variations in covariate relationships. Our study focuses on identifying averaged relationships and key spatial areas to gauge habitat quality at a landscape scale. Using a Generalized Additive Modelling approach, we found that both marine and terrestrial covariates contributed to predicting murrelet distribution during both seasons. Notably, Pacific sand lance habitat played a significant role in both the breeding and nonbreeding season, while the overall amount of nesting habitat within an 80 km radius influenced occurrence probability in the nonbreeding season. Our analysis accurately predicted distribution patterns at a resolution of 3 x 3 km with an AUC of 0.89 and AUPRC of 0.52 for the breeding season, and AUC of 0.88 and a AUPRC of 0.28 for non-breeding season. Overall, our study highlights both terrestrial and marine drivers that influence the marine distribution of this threatened species and informs Canadian conservation efforts.

Comparative evaluation of TNM staging systems (eighth vs. ninth edition) for the non-surgical treatment of localized and locally advanced anal squamous cell carcinoma: Prognostic significance of T classification and lymph node status

This study aims to compare the survival discrimination of the Tumor-Node-Metastasis (TNM) eighth and ninth editions for patients with localized and locally advanced (LLA) anal squamous cell carcinoma (ASCC) treated non-surgically and to evaluate the prognostic impact of T classification and lymph node (LN) status with data from the Surveillance, Epidemiology, and End Results database. We retrospectively included 6,876 patients in the comparison. We observed the inversion of survival outcomes for stages IIB and IIIA diseases in the TNM eighth edition [median overall survival (OS): 112 months for stage IIB vs. not reached for stage IIIA]. By contrast, it demonstrated improvement in the TNM ninth edition (median OS: not reached for IIB disease vs. 120 months for IIIA disease, P<0.001). In the correlation analysis, we observed an increased correlation between T classification and TNM staging systems (r value increased from 0.78 to 0.93) and a decreased correlation for the LN status (r value decreased from 0.83 to 0.59). For OS, variable importance analysis demonstrated more weight of importance for the T classification than the LN status (0.0871 vs. 0.0048). Additionally, decision curve analysis and time-dependent receiver operating characteristic analysis confirmed the prognostic accuracy of T classification rather than the LN status. In conclusion, TNM ninth edition is a better prognostic indicator than the eighth edition for patients with LLA ASCC treated non-surgically. T classification plays a more important prognostic role than the LN status and warrants further validation.

Correction: Diversity and sex differences in rectal gland volatiles of Queensland fruit fly, Bactrocera tryoni (Diptera: Tephritidae)

Representation models and processing operators for quantum informational multi-media

To enhance the efficacy of multimedia quantum processing and diminish processing overhead, an advanced multimedia quantum representation model and quantum video display framework are devised. A range of framework processing operators are also developed, including an image color compensation operator, a bit plane inversion operator, and a frame displacement operator. In addition, to address image security issues, two quantum image operations have been proposed: color transformation operation and pixel blending operation. The research results indicated that the grayscale cost of the framework designed in this study was 33.8, the color cost was 40.5, and the total cost was 574 δ. In terms of color, the distribution of image elements in the red, green, and blue (RGB) channels was more balanced. In summary, the quantum video display framework has significant advantages in processing efficiency and image security. Compared to previous studies, the model proposed in this study exhibits higher processing speed and better processing quality in the face of complex image and video data. It effectively addresses the limitations of existing processing techniques while addressing emerging image security issues.

Oral administration of Limosilactobacillus reuteri VHProbi® M07 alleviates ovalbumin-induced allergic asthma in mice

Aims Asthma is characterized by chronic airway inflammation, persistent cough, wheezing, and dyspnea. This study aimed to evaluate the efficacy of Limosilactobacillus reuteri VHProbi® M07 (M07) administration in alleviate the asthma severity in a mice model. Methods and results In vitro studies confirmed that M07 can survive and proliferate within the gastrointestinal tract. BALB/c mice were administered M07 both before and after ovalbumin (OVA) challenge. Serum levels of OVA-specific immunoglobulin (Ig) E and IgG1, inflammatory cells and cytokines in bronchoalveolar lavage fluid were assessed, along with histopathological examination of lung tissue. Compared to the placebo (PLA) group, mice treated with M07 exhibited significantly lower levels of OVA-specific IgE and IgG1 (P < 0.01). The counts of eosinophils and neutrophils were also significantly reduced in both the pretreated (PRE) group and post-treated (POS) group compared with the PLA group (P < 0.01). Histological analysis of lung tissues verified the protective effects of M07 against inflammation, demonstrating reduced infiltration of inflammatory cells. Additionally, mice in the PRE and POS groups showed significantly increased levels of IL-10 (P < 0.01), and significantly decreased levels of IL-5, IL-13, MCP-1, eotaxin, and tumor necrosis factor-α (P < 0.01). Conclusions Oral administration of M07 mitigated key features of inflammatory responses in the OVA-induced mice asthma model. These findings suggest that M07 holds therapeutic potential for the treatment of allergic asthma.

Investigating amygdala nuclei volumes in military personnel with post-traumatic stress disorder, major depressive disorder, and adjustment disorder: A retrospective cross-sectional study using clinical routine data

Background Post-traumatic Stress Disorder (PTSD), Major Depressive Disorder (MDD), and Adjustment Disorder (AdjD) are highly prevalent among military personnel, often presenting diagnostic challenges due to overlapping symptoms and reliance on self-reporting. The amygdala, particularly the basolateral complex involved in fear-related memory formation and extinction recall, plays a crucial role in emotional processing. Abnormalities in these amygdala nuclei are implicated in PTSD and may distinguish it from other disorders like MDD and AdjD, where these mechanisms are less central. Investigating structural differences in specific amygdala nuclei could enhance diagnostic precision and inform targeted interventions. Goal This study aimed to explore volumetric differences in amygdala nuclei among patients with PTSD, MDD, comorbid PTSD and MDD (PTSD+MDD), and AdjD using routine clinical MRI data. We hypothesized that patients with PTSD would exhibit distinct amygdala nuclei volumes compared to those with MDD or AdjD. Additionally, we examined the influence of symptom duration, prior medication, and psychotherapeutic experience on amygdala volumes. Methods We conducted a retrospective cross-sectional study with 185 military personnel (162 men, 23 women) diagnosed with PTSD (n = 50), MDD (n = 70), PTSD+MDD (n = 38), and AdjD (n = 27). High-resolution T1-weighted MRI scans were obtained using a 3T Siemens Skyra scanner. Amygdala subfields were automatically segmented and volumetrized using FreeSurfer software. Analysis of covariance (ANCOVA) models compared amygdala nuclei volumes across diagnostic groups, controlling for estimated total intracranial volume (eTIV), age, and gender. Exploratory analyses included symptom duration, medication use, and prior psychotherapy as additional covariates. Sensitivity analyses further examined the impact of depressive episode type (first vs. recurrent), severity (mild, moderate, severe), and AdjD symptom duration. Results The main analyses revealed no significant differences in the volumes of the basolateral and medial amygdala nuclei among the PTSD, MDD, PTSD+MDD, and AdjD groups. Exploratory analyses did not identify significant associations between amygdala volumes and symptom duration, medication use, or prior psychotherapy. Sensitivity analyses also showed no significant volumetric differences related to depressive episode type, severity, or AdjD symptom duration. Conclusion Our findings suggest that, within this military population, amygdala nuclei volumes measured using routine clinical MRI data do not significantly differ among patients with PTSD, MDD, PTSD+MDD, and AdjD. This indicates that structural amygdala volumetry alone may not suffice to distinguish between these stress-related disorders in clinical settings. The study highlights the complexity of diagnosing overlapping mental health conditions and underscores the need for comprehensive approaches that integrate neuroimaging with clinical assessments. Future research should include healthy control groups, consider additional brain regions and functional connectivity, and employ longitudinal designs to better understand the temporal dynamics of amygdala changes and their relation to symptomatology.

Reasons for declining to participate in a trial of online cognitive behavioural therapy following orthopaedic trauma: A mixed methods study

The timely enrollment of study participants is critical to the success of clinical trials. Understanding factors that contribute to patients’ decision to participate in trials involving online cognitive behavioural therapy for pain management should prove helpful to optimize the design of study protocols. Fracture patients from an orthopaedic clinic who declined to participate in the Cognitive behavioural therapy to Optimize Post-operative rEcovery (COPE) trial were asked to complete a Research Participation Questionnaire that asked them about their previous experiences with clinical research and mental health therapy and their reasons for declining to participate in the COPE trial. At the end of the questionnaire, a subset of participants was offered the opportunity to participate in a telephone interview to further discuss why they declined to participate in the COPE trial. Sixty-four patients who declined to participate in the COPE trial completed the questionnaire and twenty of these participants agreed to take part in a telephone interview (31%). Twenty-two participants (34%) had previous experience with clinical research and six participants (9%) had received cognitive behavioural therapy (CBT) in the past. Excessive time commitment (41%) was the most commonly selected reason for not participating in the COPE trial, followed by a disinclination to participate in clinical research (19%). Four themes emerged from the interviews with participants: 1) belief that they could overcome mental health challenges after their fracture without external help; 2) belief that CBT might be helpful for some fracture patients, but not for themselves; 3) preference for online or in-person CBT; and 4) concerns regarding time commitment. To maximize enrollment, trials exploring the role of psychotherapy in recovery from orthopedic trauma should optimize time commitment of psychotherapy. Providing information in the patient consent process regarding evidence for psychotherapy and recovery from orthopedic trauma may also prove helpful in promoting patient enrollment.

Championing queer scientists of colour: ‘I don’t think we’ve scratched the surface on systemic exclusion’

A recurrence model for non-puerperal mastitis patients based on machine learning

Objective Non-puerperal mastitis (NPM) is an inflammatory breast disease affecting women during non-lactation periods, and it is prone to relapse after being cured. Accurate prediction of its recurrence is crucial for personalized adjuvant therapy, and pathological examination is the primary basis for the classification, diagnosis, and confirmation of non-puerperal mastitis. Currently, there is a lack of recurrence models for non-puerperal mastitis. The aim of this research is to create and validate a recurrence model using machine learning for patients with non-puerperal mastitis. Methods We retrospectively collected laboratory data from 120 NPM patients, dividing them into a non-recurrence group (n = 59) and a recurrence group (n = 61). Through random allocation, these individuals were split into a training cohort and a testing cohort in a 90%:10% ratio for the purpose of building the model. Additionally, data from 25 NPM patients from another center were collected to serve as an external validation cohort for the model. Univariate analysis was used to examine differential indicators, and variable selection was conducted through LASSO regression. A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. The finally selected model was interpreted and evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, Decision curve analysis (DCA), and Shapley Additive Explanations (SHAP) plots. Results The logistic regression model emerged as the optimal model for predicting recurrence of NPM with machine learning, primarily utilizing three variables: FIB, bacterial infection, and CD4+ T cell count. The model showed an AUC of 0.846 in the training cohort and 0.833 in the testing cohort. The calibration curve indicated excellent calibration of the model. DCA revealed that the model possessed favorable clinical utility. Furthermore, the model effectively achieved in the external validation group, with an AUC of 0.825. Conclusion The machine learning model developed in this study, serving as an effective tool for predicting NPM recurrence, aids doctors in making more individualized treatment decisions, thereby enhancing therapeutic efficacy and reducing the risk of recurrence.

Environmental maternal exposures and the risk of premature birth and intrauterine growth restriction: The Generation Gemelli study protocol of newborn exposome

Background The study of women exposures and child outcomes occurring in the first 1,000 days of life since conception enhances understanding of the relationships between environmental factors, epigenetic changes, and disease development, extending beyond childhood and spanning the entire lifespan. Generation Gemelli is a recently launched case-control study that enrolls mother-newborns pairs in one of the largest university hospitals in Italy, in order to examine the association between maternal environmental exposures and intrauterine growth restriction (IUGR) and the risk of premature birth. The study will also evaluate the association of maternal exposures and the health and growth of infants and children up to 24 months of age. Methods The study entails the set-up of a case-control study within a birth cohort. With approximately 4,000 annual deliveries, we aim to enroll 140 cases (newborns with IUGR and premature birth) and 280 controls per year, from September 2022. A comprehensive questionnaire will be used to gather information about various types of maternal environmental exposures before and during pregnancy. We will collect biological samples from both mothers and newborns (including vaginal swab, placenta sample, blood, saliva, meconium, and bronchoalveolar lavage fluid) at birth and within the early hours of the newborn’s life. We will perform laboratory examinations including dosage of heavy metals and essential elements, investigation of placental distress and fetal brain damage of biomarkers, analysis of microbiota and of DNA methylation profile. We will conduct clinical follow-up assessments in both cases and controls at months 12 and 24 and we will collect anthropometric data, feeding types with particular reference to breastfeeding and its duration, pediatric emergency room visits, hospitalizations, medication usage, known allergies, and neuropsychological development. Discussion The Generation Gemelli case-control study holds the promise of significantly enhancing our comprehension of how maternal environmental exposures relate to the health of children and the broader population. The study of the exposome will provide insights into the relationships between environmental exposures, epigenetic changes and health outcomes during the first 1000 days of life and onward.