EndometriosisAdEndNCT06572852
Next-Generation Endometriosis Diagnostics Through Comprehensive Multi-Dimensional Analysis
An observational study of Endometriosis and Adenomyosis, run by IRCCS San Raffaele at 2 sites in Italy.
Trial summary
This study is a multicentric, observational, case-control, non-profit with additional procedures. It aims to deepen the understanding of the chronic gynecological conditions of endometriosis and adenomyosis, which significantly impact women's reproductive health. Read more about this study
- Who is it for?
- Ages 18 to 40 years, women onlyHealthy volunteers can take part
- Conditions the study is for
- Endometriosis, Adenomyosis
- How many people
- 530 participants
- Where
- 2 sitesItaly
- Study dates
- 7 Nov 2024to 30 Aug 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 40 years
- Women only
- Healthy volunteers accepted
- Adult
Study population: The study will involve a total of 530 participants selected from two Assisted Reproduction Centers. The participant population includes: * Group A: 100 women diagnosed with both endometriosis and adenomyosis (cases). * Group B: 15 women diagnosed exclusively with endometriosis (cases). * Group C: 15 women diagnosed exclusively with adenomyosis (cases). * 400 women from couples seeking fertility treatment at infertility clinics (controls). Additionally, Group D will consist of 300 DNA biobank samples from women diagnosed with endometriosis.
Who may be able to join
- Participants eligible for cases with endometriosis and adenomyosis, must meet the following criteria:
- Able to give informed consent for participation in the study.
- European descent.
- Confirmed diagnosis of both endometriosis and adenomyosis through ultrasound screening.
- Listed for assisted reproductive treatment, specifically within their first or second IVF cycle.
- Participants eligible for cases with only endometriosis must meet the following criteria:
Show all 21Show fewer
- Able to give informed consent for participation in the study.
- European descent.
- Confirmed diagnosis of endometriosis with no ultrasound evidence of adenomyosis.
- Enrolled in an assisted reproductive treatment cycle involving embryo thawing.
- Participants eligible for cases with only adenomyosis must meet the following criteria:
- Able to give informed consent for participation in the study.
- European descent.
- Confirmed diagnosis of adenomyosis with no ultrasound evidence of endometriosis.
- Enrolled in an assisted reproductive treatment cycle involving embryo thawing.
- Participants eligible as controls must meet the following criteria:
- Able to give informed consent for participation in the study.
- European descent.
- Undergone ultrasound screenings that have excluded the presence of endometriosis or adenomyosis.
- Listed for assisted reproductive treatment, specifically within their first or second IVF cycle.
- Presence of reduced ovarian reserve or non-severe male factor infertility.
Who cannot join
- Patients unable or unwilling to sign the informed consent
- Individuals who exhibit the presence of sactosalpinx or other uterine pathologies such as fibroids, polyps, or irregular endometrial thickening will be excluded from participation in this study.
- These exclusion criteria are applicable across all groups to ensure the accuracy and reliability of the study's findings related to endometriosis and adenomyosis.
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Italy2 sites, 1 recruiting
- Active, not recruiting
Azienda Ospedaliero Universitaria Renato Dulbecco di Catanzaro
Catanzaro, Catanzaro, 88100
- Recruiting
IRCCS San Raffaele Hospital
Milan, Milano, 20132
LUCA PAGLIARDINI, +39 02 2643 4834, pagliardini.luca@hsr.it
Massimo Candiani, MD
About this study
This study is a multicentric, observational, case-control, non-profit with additional procedures. It aims to deepen the understanding of the chronic gynecological conditions of endometriosis and adenomyosis, which significantly impact women's reproductive health. Its purpose is to improve early diagnosis and personalized treatment of these conditions using a multi-omic approach, that integrates genetic, epigenetic, imaging, and endometrial receptivity data. The goal is also to refine image-based predictions through recent advancements in artificial intelligence and to study uterine extracellular vesicles to assess fertility non-invasively.
The study targets patients with endometriosis and/or adenomyosis and involves women seeking fertility treatments at assisted reproduction centers, who will serve as a control population.
The study comprises both prospective and retrospective components. The prospective recruitment involves the collection of blood and uterine fluid samples, while the retrospective element utilizes pre-existing biobank samples for comprehensive genetic and epigenetic analysis.
Read the detailed description
Recent research indicates that epigenetic blood analysis could revolutionize the diagnosis of endometriosis, moreover, strong correlations between endometrial and blood methylation have been reported, suggesting significant diagnostic potential. Preliminary data on Polygenic Risk Scores (PRS) also show promise in identifying genetic profiles associated with disease severity.
Advancements in artificial intelligence (AI) offer precise image-based diagnostic predictions, highlighting the transformative potential of integrating AI with genetic analyses. Additionally, our preliminary studies have demonstrated the potential of using gene expression data from uterine fluid extracellular vesicles (UF-EVs) to understand endometrial receptivity, with implications for detecting both endometriosis and adenomyosis.
Through this study, the investigators hypothesize that differential methylation profiles, integrated with genetic, epigenetic, and clinical data, can accurately classify endometriosis and adenomyosis cases. Additionally, it's hypothesized that UF-EVs gene expression profiles differ significantly between endometriosis, adenomyosis, and fertile controls, providing critical insights into endometrial receptivity and potential diagnostic markers for these conditions.
Primary Objective:
To identify specific CpG sites that exhibit differential methylation levels between endometriosis cases and controls. These methylation profiles, combined with polygenic risk scores (PRS) and clinical questionnaire data, will be used to classify cases and controls through machine learning analysis. (Aim 1) In addition to the differential methylation analysis, 'high-resolution SNP genotyping' will be employed. This genotyping will adjust the methylation analysis and aid in deriving polygenic risk scores.
Secondary Objectives:
To develop and validate a diagnostic model integrating ultrasound imaging with genetic, epigenetic, and clinical data to accurately identify and differentiate adenomyosis as an extension of endometriosis, and to predict pregnancy outcomes in women undergoing IVF. (Aim 2)
Tertiary Objectives:
To characterize the gene expression profiles of uterine fluid extracellular vesicles (UF-EVs) specific to endometriosis and adenomyosis will be analyzed samples at two critical time points: LH+2 (non-receptive) and LH+7 (receptive). The obtained gene expression data will be compared against previously collected data from fertile and infertile patients. By comparing these profiles, the investigators aim to identify distinct molecular signatures associated with each condition, enhancing our understanding of their impact on fertility and endometrial receptivity. Also, this comparison will allow us to refine diagnostic markers and potentially develop targeted interventions for affected women. (Aim 3)
This study is conducted as a multicenter project, involving two Assisted Reproduction Centers, it will include a diverse cohort of 800 women. The study involves 530 participants and three distinct groups: women diagnosed with endometriosis, women diagnosed with both endometriosis and adenomyosis, and a control group of infertile women without these conditions. Each group will participate in the study, it is planned to last 24 months from the onset of recruitment to the final analysis of collected data. An additional group will consist of 300 DNA biobanked samples from women diagnosed with endometriosis.
- Conditions
- Endometriosis, Adenomyosis
- Being tested
- No intervention
- Keywords
- Case-control, Retrospective, Prospective, Genetic, Endometriosis, Adenomyosis, Machine learning, Epigenetic
- Medical subject headings
- Endometriosis, Adenomyosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No interventionOther
No intervention
| Study group | Role | What they receive |
|---|---|---|
| Cases with both endometriosis and adenomyosis | 100 women diagnosed with both endometriosis and adenomyosis (cases). These participants are part of couples seeking fertility treatment at Assisted Reproduction Centers. The diagnosis of both endometriosis and adenomyosis will be made through ultrasound imaging at the IVF centers. The recruitment involves the collection of blood for genetic and epigenetic analysis, and acquiring ultrasound images for machine learning analysis. Receives: Other: No intervention | |
| Cases with only endometriosis | 15 women diagnosed exclusively with endometriosis (cases): This subgroup consists of women who have been diagnosed with endometriosis but show no ultrasound evidence of adenomyosis. The recruitment involves the collection of blood for genetic and epigenetic analysis, acquiring ultrasound images for machine learning analysis, and collecting uterine fluid samples to study gene expression profiles through uterine fluid extracellular vesicles (UF-EVs). Receives: Other: No intervention | |
| Cases with only adenomyosis | 15 women diagnosed exclusively with adenomyosis (cases): This subgroup includes women diagnosed solely with adenomyosis, without any ultrasonographic signs of endometriosis. The recruitment involves the collection of blood for genetic and epigenetic analysis, acquiring ultrasound images for machine learning analysis, and collecting uterine fluid samples to study gene expression profiles through uterine fluid extracellular vesicles (UF-EVs). Receives: Other: No intervention | |
| Controls | 400 women from couples seeking fertility treatment at infertility clinics (controls): These participants, who will be part of couples attempting to conceive, will be actively seeking treatment for infertility or other gynecological symptoms. Crucially, these individuals will have undergone ultrasound screenings that have excluded the presence of endometriosis or adenomyosis. The recruitment involves the collection of blood for genetic and epigenetic analysis, and acquiring ultrasound images for machine learning analysis. Receives: Other: No intervention | |
| Cases of endometriosis with pre-existing genotyping data | This group will consist of 300 DNA biobanked samples from women diagnosed with endometriosis. These samples come with pre-existing genotyping data, which will be integrated into the study to provide a robust genetic baseline for comparative analyses. Receives: Other: No intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
Identification of epigenetic profile
To identify specific CpG sites that exhibit differential methylation levels between endometriosis cases and controls. These methylation profiles, polygenic risk scores (PRS), and clinical questionnaire data will be used to classify cases and controls through machine learning analysis.
Measured: 2 years
Identification of genetic profile
In addition to the differential methylation analysis, 'high-resolution SNP genotyping' will be employed. This genotyping will adjust the methylation analysis and aid in deriving polygenic risk scores.
Measured: 2 years
Secondary outcomes (1)
Development and validation of a diagnostic model
To develop and validate a diagnostic model integrating ultrasound imaging with genetic, epigenetic, and clinical data to accurately identify and differentiate adenomyosis as an extension of endometriosis, and to predict pregnancy outcomes in women undergoing IVF.
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Aug 2024
- Study start7 Nov 2024
- Primary completion28 Feb 2026 (estimated)
- Study completion30 Aug 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for EndometriosisStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Other
- Enrolment
- 530 participants (estimated)
Sponsor and investigators
- Lead sponsor
- IRCCS San Raffaele
- Sponsor type
- University, hospital or other
- Collaborators
- AUO Renato Dulbecco
- Responsible party
- Principal investigator, Candiani Massimo, IRCCS San Raffaele
- Investigators
- MASSIMO CANDIANI, Principal investigator, IRCCS San Raffaele
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06572852
- Sponsor's protocol ID
- PNRR-MCNT2-2023-12378346
- Acronym
- AdEnd
- Status last verified
- Oct 2025
- First submitted
- 23 Aug 2024
- Last updated
- 7 Oct 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Giacomini E, Scotti GM, Vanni VS, Lazarevic D, Makieva S, Privitera L, Signorelli S, Cantone L, Bollati V, Murdica V, Tonon G, Papaleo E, Candiani M, Vigano P. Global transcriptomic changes occur in uterine fluid-derived extracellular vesicles during the endometrial window for embryo implantation. Hum Reprod. 2021 Jul 19;36(8):2249-2274. doi: 10.1093/humrep/deab123.
PubMed 34190319Vercellini P, Vigano P, Bandini V, Buggio L, Berlanda N, Somigliana E. Association of endometriosis and adenomyosis with pregnancy and infertility. Fertil Steril. 2023 May;119(5):727-740. doi: 10.1016/j.fertnstert.2023.03.018. Epub 2023 Mar 21.
PubMed 36948440
Study at a glance
From the registry record, last updated by the sponsor on 7 Oct 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Next-Generation Endometriosis Diagnostics Through Comprehensive Multi-Dimensional Analysis
- ClinicalTrials.gov ID
- NCT06572852
- Acronym / sponsor ID
- AdEnd / PNRR-MCNT2-2023-12378346
- Conditions
- Endometriosis, Adenomyosis
- Keywords
- Case-control, Retrospective, Prospective, Genetic, Endometriosis, Adenomyosis, Machine learning, Epigenetic
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 530 participants (estimated)
- Lead sponsor
- IRCCS San RaffaeleUniversity, hospital or other
- Collaborators
- AUO Renato Dulbecco
- Study start
- 7 Nov 2024 (actual)
- Primary completion
- 28 Feb 2026 (estimated)
- Study completion
- 30 Aug 2026 (estimated)
- First posted
- 27 Aug 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study is a multicentric, observational, case-control, non-profit with additional procedures. It aims to deepen the understanding of the chronic gynecological conditions of endometriosis and adenomyosis, which significantly impact women's reproductive health. Its purpose is to improve early diagnosis and personalized treatment of these conditions using a multi-omic approach, that integrates genetic, epigenetic, imaging, and endometrial receptivity data. The goal is also to refine image-based predictions through recent advancements in artificial intelligence and to study uterine extracellular vesicles to assess fertility non-invasively.
The study targets patients with endometriosis and/or adenomyosis and involves women seeking fertility treatments at assisted reproduction centers, who will serve as a control population.
The study comprises both prospective and retrospective components. The prospective recruitment involves the collection of blood and uterine fluid samples, while the retrospective element utilizes pre-existing biobank samples for comprehensive genetic and epigenetic analysis.
Detailed description
Recent research indicates that epigenetic blood analysis could revolutionize the diagnosis of endometriosis, moreover, strong correlations between endometrial and blood methylation have been reported, suggesting significant diagnostic potential. Preliminary data on Polygenic Risk Scores (PRS) also show promise in identifying genetic profiles associated with disease severity.
Advancements in artificial intelligence (AI) offer precise image-based diagnostic predictions, highlighting the transformative potential of integrating AI with genetic analyses. Additionally, our preliminary studies have demonstrated the potential of using gene expression data from uterine fluid extracellular vesicles (UF-EVs) to understand endometrial receptivity, with implications for detecting both endometriosis and adenomyosis.
Through this study, the investigators hypothesize that differential methylation profiles, integrated with genetic, epigenetic, and clinical data, can accurately classify endometriosis and adenomyosis cases. Additionally, it's hypothesized that UF-EVs gene expression profiles differ significantly between endometriosis, adenomyosis, and fertile controls, providing critical insights into endometrial receptivity and potential diagnostic markers for these conditions.
Primary Objective:
To identify specific CpG sites that exhibit differential methylation levels between endometriosis cases and controls. These methylation profiles, combined with polygenic risk scores (PRS) and clinical questionnaire data, will be used to classify cases and controls through machine learning analysis. (Aim 1) In addition to the differential methylation analysis, 'high-resolution SNP genotyping' will be employed. This genotyping will adjust the methylation analysis and aid in deriving polygenic risk scores.
Secondary Objectives:
To develop and validate a diagnostic model integrating ultrasound imaging with genetic, epigenetic, and clinical data to accurately identify and differentiate adenomyosis as an extension of endometriosis, and to predict pregnancy outcomes in women undergoing IVF. (Aim 2)
Tertiary Objectives:
To characterize the gene expression profiles of uterine fluid extracellular vesicles (UF-EVs) specific to endometriosis and adenomyosis will be analyzed samples at two critical time points: LH+2 (non-receptive) and LH+7 (receptive). The obtained gene expression data will be compared against previously collected data from fertile and infertile patients. By comparing these profiles, the investigators aim to identify distinct molecular signatures associated with each condition, enhancing our understanding of their impact on fertility and endometrial receptivity. Also, this comparison will allow us to refine diagnostic markers and potentially develop targeted interventions for affected women. (Aim 3)
This study is conducted as a multicenter project, involving two Assisted Reproduction Centers, it will include a diverse cohort of 800 women. The study involves 530 participants and three distinct groups: women diagnosed with endometriosis, women diagnosed with both endometriosis and adenomyosis, and a control group of infertile women without these conditions. Each group will participate in the study, it is planned to last 24 months from the onset of recruitment to the final analysis of collected data. An additional group will consist of 300 DNA biobanked samples from women diagnosed with endometriosis.
Study design
- Observational model
- Case-control
- Time perspective
- Other
- Number of arms
- 5
| Arm | Type | Receives |
|---|---|---|
| Cases with both endometriosis and adenomyosis | – | Other: No intervention100 women diagnosed with both endometriosis and adenomyosis (cases). These participants are part of couples seeking fertility treatment at Assisted Reproduction Centers. The diagnosis of both endometriosis and adenomyosis will be made through ultrasound imaging at the IVF centers. The recruitment involves the collection of blood for genetic and epigenetic analysis, and acquiring ultrasound images for machine learning analysis. |
| Cases with only endometriosis | – | Other: No intervention15 women diagnosed exclusively with endometriosis (cases): This subgroup consists of women who have been diagnosed with endometriosis but show no ultrasound evidence of adenomyosis. The recruitment involves the collection of blood for genetic and epigenetic analysis, acquiring ultrasound images for machine learning analysis, and collecting uterine fluid samples to study gene expression profiles through uterine fluid extracellular vesicles (UF-EVs). |
| Cases with only adenomyosis | – | Other: No intervention15 women diagnosed exclusively with adenomyosis (cases): This subgroup includes women diagnosed solely with adenomyosis, without any ultrasonographic signs of endometriosis. The recruitment involves the collection of blood for genetic and epigenetic analysis, acquiring ultrasound images for machine learning analysis, and collecting uterine fluid samples to study gene expression profiles through uterine fluid extracellular vesicles (UF-EVs). |
| Controls | – | Other: No intervention400 women from couples seeking fertility treatment at infertility clinics (controls): These participants, who will be part of couples attempting to conceive, will be actively seeking treatment for infertility or other gynecological symptoms. Crucially, these individuals will have undergone ultrasound screenings that have excluded the presence of endometriosis or adenomyosis. The recruitment involves the collection of blood for genetic and epigenetic analysis, and acquiring ultrasound images for machine learning analysis. |
| Cases of endometriosis with pre-existing genotyping data | – | Other: No interventionThis group will consist of 300 DNA biobanked samples from women diagnosed with endometriosis. These samples come with pre-existing genotyping data, which will be integrated into the study to provide a robust genetic baseline for comparative analyses. |
Who may qualify
- Ages
- 18 to 40 years
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Adult
- Study population
- The study will involve a total of 530 participants selected from two Assisted Reproduction Centers. The participant population includes: * Group A: 100 women diagnosed with both endometriosis and adenomyosis (cases). * Group B: 15 women diagnosed exclusively with endometriosis (cases). * Group C: 15 women diagnosed exclusively with adenomyosis (cases). * 400 women from couples seeking fertility treatment at infertility clinics (controls). Additionally, Group D will consist of 300 DNA biobank samples from women diagnosed with endometriosis.
Key inclusion criteria (21 listed)
- Participants eligible for cases with endometriosis and adenomyosis, must meet the following criteria:
- Able to give informed consent for participation in the study.
- European descent.
- Confirmed diagnosis of both endometriosis and adenomyosis through ultrasound screening.
- Listed for assisted reproductive treatment, specifically within their first or second IVF cycle.
Key exclusion criteria (3 listed)
- Patients unable or unwilling to sign the informed consent
- Individuals who exhibit the presence of sactosalpinx or other uterine pathologies such as fibroids, polyps, or irregular endometrial thickening will be excluded from participation in this study.
- These exclusion criteria are applicable across all groups to ensure the accuracy and reliability of the study's findings related to endometriosis and adenomyosis.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| No interventionNo intervention | Other | Cases of endometriosis with pre-existing genotyping data, Cases with both endometriosis and adenomyosis, Cases with only adenomyosis, Cases with only endometriosis, Controls |
Primary outcome
Identification of epigenetic profile
Time frame: 2 years
To identify specific CpG sites that exhibit differential methylation levels between endometriosis cases and controls. These methylation profiles, polygenic risk scores (PRS), and clinical questionnaire data will be used to classify cases and controls through machine learning analysis.
Identification of genetic profile
Time frame: 2 years
In addition to the differential methylation analysis, 'high-resolution SNP genotyping' will be employed. This genotyping will adjust the methylation analysis and aid in deriving polygenic risk scores.
1 secondary outcome
Development and validation of a diagnostic model
Time frame: 2 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Oct 2025.
- Background: PubMed 34190319Giacomini E, Scotti GM, Vanni VS, Lazarevic D, Makieva S, Privitera L, Signorelli S, Cantone L, Bollati V, Murdica V, Tonon G, Papaleo E, Candiani M, Vigano P. Global transcriptomic changes occur in uterine fluid-derived extracellular vesicles during the endometrial window for embryo implantation. Hum Reprod. 2021 Jul 19;36(8):2249-2274. doi: 10.1093/humrep/deab123.
- Background: PubMed 36948440Vercellini P, Vigano P, Bandini V, Buggio L, Berlanda N, Somigliana E. Association of endometriosis and adenomyosis with pregnancy and infertility. Fertil Steril. 2023 May;119(5):727-740. doi: 10.1016/j.fertnstert.2023.03.018. Epub 2023 Mar 21.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
MASSIMO CANDIANI principal investigator
IRCCS San Raffaele
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Endometriosis and Adenomyosis, run by IRCCS San Raffaele at 2 sites in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 21 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 7 Oct 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact LUCA PAGLIARDINI (0226434834 ext. 0039, pagliardini.luca@hsr.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Identification of epigenetic profile (time frame: 2 years). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06572852, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Oct 2025.