Impact of fospropofol disodium on lipid metabolism and inflammatory response in patients with hyperlipidemia: a randomized trial

Chuan Yang1*†, Tian-Bo Chai1†, Xing-Zhu Yao1 , Li Zhang1 , Wen-Ming Qin2 , Hong Liang3 , Qiong-Zhen He4 and Ze-Yu Zhao5*Chuan Yang and Tian-Bo Chai contributed equally to this work.

*Correspondence:Chuan Yang 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 Ze-Yu Zhao 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 Full list of author information is available at the end of the article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creati  vecommons.org/licenses/by-nc-nd/4.0/.

Abstract

Objective This study aims to assess the impact of intravenous infusion of fospropofol disodium on lipid metabolism and the inflammatory response in individuals with hyperlipidemia.

Methods A total of 360 preoperative individuals with hyperlipidemia were selected and randomly assigned to either the treatment group or the control group, with 180 participants in each group. The treatment group received an induction dose of fospropofol disodium at 10 mg/kg intravenously, followed by maintenance at a rate of 10 mg/ (kg·h). The control group was administered propofol intravenously at 2 mg/kg for induction and maintained at 4 mg/(kg·h). All other medications were consistent between the two groups. Blood samples (3 ml of venous blood) were collected from patients at four-time points: 1 day before surgery (T0), 3 h after anesthesia induction (T1), 4 h post-surgery (T2), and 24 h post-surgery (T3), to measure levels of triglycerides (TG), cholesterol (CHOL), high density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB). C-reactive protein (CRP) and interleukin-6 (IL-6) levels were assessed at T0 and T3. Sedation onset time and adverse reactions were recorded for both groups.

Results At T0, the control group exhibited increased TG, CHOL, LDL-C, ApoB, and the ApoB/ApoA1 ratio, while the ApoA1 level had decreased. The LDL-C level and the ApoB/ApoA1 ratio showed significant increases (P<0.01). Both groups showed elevated CRP and IL-6 levels at T3 (P<0.01). Compared to the control group, the treatment group demonstrated reduced levels of TG, CHOL, LDL-C, ApoB, and the ApoB/ApoA1 ratio at T1-T3, while ApoA1 levels were higher at T1-T2 (P<0.01 or P<0.05). The sedation onset time was notably longer in the treatment group, and the incidence of injection-related pain, respiratory depression, hypotension, and other adverse reactions was significantly lower (P<0.01).

Conclusion Compared with propofol, intravenous infusion of fospropofol disodium for more than 3 h during anesthesia has lesser impact on lipid metabolism in patients with hyperlipidemia and does not increase inflammatory factors levels.

Keywords Fospropofol disodium, Hyperlipidemia, Inflammation, Lipid metabolism disorders, Propofol

Examining causal relationships between educational attainment and type 2 diabetes using genetic analysis: findings from the EPIC-InterAct study through Mendelian randomisation

      Alessandra Macciotta ,1,2 Carlotta Sacerdote,3 Claudia Giachino,1 Chiara Di Girolamo,1 Matteo Franco,1 Yvonne T van der Schouw,4 Raul Zamora-Ros,5 Elisabete Weiderpass,6 Cloé Domenighetti,7 Alexis Elbaz ,7 Thérèse Truong,7 Claudia Agnoli,8 Benedetta Bendinelli,9 Salvatore Panico,10 Paolo Vineis ,11 Sofia Christakoudi,11,12 Matthias B Schulze,13,14,15 Verena Katzke,16 Rashmita Bajracharya,16 Christina C Dahm,17 Susanne Oksbjerg Dalton,18,19 Sandra M Colorado-Yohar,20,21,22 Conchi Moreno-Iribas,23 Pilar Amiano Etxezarreta,21,24,25 María José Sanchez,21,26,27 Nita G Forouhi,28 Nicholas Wareham,28 Fulvio Ricceri 1.

      Additional supplemental material is published online only. To view, please visit the journal online (https://doi.org/ 10.1136/jech-2024-222734). For numbered affiliations see end of article.

Correspondence to

      Professor Carlotta Sacerdote; 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 NW and FR contributed equally. Received 10 July 2024 Accepted 19 November 2024© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ Group

To cite: Macciotta A, Sacerdote C, Giachino C, et al. J Epidemiol Community Health Epub ahead of print:[please include Day MonthYear]. doi:10.1136/jech- 2024-222734

ABSTRACT

Introduction Observational studies have shown that more educated people are at lower risk of developing type 2 diabetes (T2D). However, robust study designs are needed to investigate the likelihood that such a relationship is causal. This study used genetic instruments for education to estimate the effect of education on T2D using the Mendelian randomisation (MR) approach.

Methods Analyses have been conducted in the European Prospective Investigation into Cancer and Nutrition (EPIC)- InterAct study (more than 20000 individuals), a case-cohort study of T2D nested in the EPIC cohort. Education was measured as Years of Education and Relative Index of Inequality. Prentice-weighted Cox models were performed to estimate the association between education and T2D. One-sample MR analyses investigated whether genetic predisposition towards longer education was associated with risk of T2D and investigated potential mediators of the

Results MR estimates indicated a risk reduction of about 15% for each year of longer education on the risk of developing T2D, confirming the protective role estimated by observational models (HR 0.96, 95% CI 0.95 to 0.96). MR analyses on putative mediators showed a significant role of education on body mass index, alcohol consumption, adherence to the Mediterranean diet and smoking habits.

Conclusion The results supported the hypothesis that higher education is a protective factor for the risk of developing T2D. Based on its position in the causal chain, education may be antecedent of other known risk factors for T2D including unhealthy behaviours. These findings reinforce evidence obtained through observational study designs and bridge the gap between correlation and causation.

The Type 1 Diabetes T Cell Receptor and B Cell Receptor Repository in the AIRR Data Commons: a practical guide for access, use and contributions through the Type 1 Diabetes AIRR Consortium

Stephanie J. Hanna1  · Rachel H. Bonami2,3,4,5  · Brian Corrie6,7  · Monica Westley8  · Amanda L. Posgai9  · Eline T. Luning Prak10  · Felix Breden6,7  · Aaron W. Michels11  · Todd M. Brusko9,12,13  · Type 1 Diabetes AIRR Consortium

Received: 26 May 2024 / Accepted: 19 August 2024 / Published online: 29 October 2024

© The Author(s) 2024

Extended author information available on the last page of the article

Abstract

Human molecular genetics has brought incredible insights into the variants that confer risk for the development of tissuespecific autoimmune diseases, including type 1 diabetes. The hallmark cell-mediated immune destruction that is characteristic of type 1 diabetes is closely linked with risk conferred by the HLA class II gene locus, in combination with a broad array of additional candidate genes influencing islet-resident beta cells within the pancreas, as well as function, phenotype and trafficking of immune cells to tissues. In addition to the well-studied germline SNP variants, there are critical contributions conferred by T cell receptor (TCR) and B cell receptor (BCR) genes that undergo somatic recombination to yield the Adaptive Immune Receptor Repertoire (AIRR) responsible for autoimmunity in type 1 diabetes. We therefore created the T1D TCR/ BCR Repository (The Type 1 Diabetes T Cell Receptor and B Cell Receptor Repository) to study these highly variable and dynamic gene rearrangements. In addition to processed TCR and BCR sequences, the T1D TCR/BCR Repository includes detailed metadata (e.g. participant demographics, disease-associated parameters and tissue type). We introduce the Type 1 Diabetes AIRR Consortium goals and outline methods to use and deposit data to this comprehensive repository. Our ultimate goal is to facilitate research community access to rich, carefully annotated immune AIRR datasets to enable new scientific inquiry and insight into the natural history and pathogenesis of type 1 diabetes.

Keywords AIRR · AIRR Data Commons · Autoantibodies · B cell receptors · FAIR data · Next-generation sequencing · Single-cell RNA-seq · T cell receptors · Type 1 diabetes

Abbreviations

AAb  Autoantibody/autoantibodies

ADC  AIRR Data Commons

AIM  Activation-induced marker

AIRR  Adaptive Immune Receptor Repertoire

AIRR-seq  AIRR sequencing

BCR  B cell receptor

CDR3  Complementarity determining region 3

FAIR  Findable, Accessible, Interoperable, Reusable

GEO  Gene Expression Omnibus

HPAP  Human Pancreas Analysis Program

IEDB  Immune Epitope Database

MiAIRR  Minimal information about AIRR

ML  Machine learning

pLN  Pancreatic lymph node(s)

SARS-CoV-2  Severe acute respiratory syndrome coronavirus 2

scRNA-seq  Single-cell RNA-seq

SRA  Sequence Read Archive 

T1D TCR/BCR Repository The Type 1 Diabetes T Cell Receptor and B Cell Receptor Repository

TCR  T cell receptor

TCRβ  T cell receptor β chain

Tfh   T follicular helper

Treg  Regulatory T cell(s)

VDJ  Variable, diversity and joining gene segments

Stephanie J. Hanna and Rachel H. Bonami contributed equally to this work. Aaron W. Michels and Todd M. Brusko contributed equally as joint senior authors.

Members of the Type 1 Diabetes AIRR Consortium are listed in the  Acknowledgements.

Unmet needs of Italian centers for pediatric diabetes care: analysis of a survey among pediatric diabetologists facing the national screening program for Type 1 Diabetes

Marco Marigliano1,11*† , Roberto Franceschi2†, Enza Mozzillo3†, Valentina Tiberi4†, Monica Marino4 , Giada Boccolini4 , Malgorzata Wasniewska5 , Maria Elizabeth Street6 , Maria Rosaria Licenziati7 , Riccardo Bonfanti8 , Felice Citriniti9 , Giuseppe D’Annunzio10, Maria Carolina Salerno3 , Valentino Cherubini4 and the Diabetes Study Group of the Italian Society of Pediatric Endocrinology and Diabetology (ISPED)

† Marco Marigliano, Roberto Franceschi, Enza Mozzillo and Valentina Tiberi contributed equally to this work.

Abstract

Backgrounds The incidence of Type 1 Diabetes (T1D) in children and adolescents is increasing by 3–4% per year. Children and adolescents with T1D (CwD) should receive person-centered, specialized treatment from a multidisciplinary team to ensure appropriate care. Italy is the first to implement a countrywide T1D screening program, which will raise the need for funding for specialized pediatric care. The study aims to update the organization of the Italian Centers for pediatric diabetes care.

Methods In 2022, members of the 59 Italian Centers following CwD were invited to complete an email survey regarding the Centers’ organization, characteristics, and activities. The questionnaire included information on responders, department organization, team composition, activities, and the organizational structures: department, ambulatory care services (AC), simple operational units (UOS), simple departmental operational units (UOSd), and complex operational units (UOC).

Results The data collected referred to the year 2022. According to the results, 21,318 people with diabetes were treated. Of these, 19,643 subjects (92.1%) have T1D (16,672 were CwD), 387 (1,8%) have Type 2 Diabetes, and 1,288 (6,1%) have other forms of diabetes. Compared to the 2012 survey, a 13% decrease (from 68 to 59 Centers) in the number of pediatric Centers caring for CwD was observed with a parallel increase of total (+6.6%) and average (+22%) number of CwD per Center. The estimated prevalence of T1D has increased (1.4 vs. 1.7 per 1,000 CwD—2012 vs. 2022). A reduction in numbers for AC (-22%) and UOS (-35%) was observed, whereas UOSd/UOC increased by 50%. Almost 35% of the dietitians and 40% of the psychologists were not permanent members of the multidisciplinary diabetes team.

Conclusions The observed decrease in the overall number of pediatric diabetes Centers, the reduction in specialized and dedicated HCPs, and the concurrent increase in the number of treated CwD in the last ten years indicate an alarming situation for pediatric diabetes treatment in Italy. Furthermore, the projected rise in CwD due to the National T1D screening program emphasizes the need for increased resources for specialized pediatric care of CwD at all stages.

Keywords Type 1 diabetes, Care, Children, Adolescents, Benchmarking, Team, Screening, Technology

Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits

Loϊc Binan,1,2 Aiping Jiang,3,4,5 Serwah A. Danquah,1,6,12 Vera Valakh,1,6,13 Brooke Simonton,2,14 Jon Bezney,2,15 Robert T. Manguso,3,4,5 Kathleen B. Yates,3,4,5 Ralda Nehme,6 Brian Cleary,7,8,9,10,11,* and Samouil L. Farhi1,16,*

1 Spatial Technology Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA

2 Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA

3 Cancer Program, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA

4 Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA 02144, USA

5 Department of Medicine, Harvard Medical School, Boston, MA 02115, USA

6 Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA

7 Faculty of Computing and Data Sciences, Boston University, Boston, MA 02215, USA

8 Department of Biology, Boston University, Boston, MA 02215, USA

9 Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA

10 Program in Bioinformatics, Boston University, Boston, MA 02215, USA

11 Biological Design Center, Boston University, Boston, MA 02215, USA

12 Present address: Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA

13 Present address: Stoke Therapeutics, Bedford, MA, USA

14 Present address: The Ken & Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

15 Present address: Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

16 Lead contact

*Correspondence: 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (B.C.), 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (S.L.F.)

https://doi.org/10.1016/j.cell.2025.02.012

SUMMARY

Pooled optical screens have enabled the study of cellular interactions, morphology, or dynamics at massive scale, but they have not yet leveraged the power of highly plexed single-cell resolved transcriptomic readouts to inform molecular pathways. Here, we present a combination of imaging spatial transcriptomics with parallel optical detection of in situ amplified guide RNAs (Perturb-FISH). Perturb-FISH recovers intracellular effects that are consistent with single-cell RNA-sequencing-based readouts of perturbation effects (Perturb-seq) in a screen of lipopolysaccharide response in cultured monocytes, and it uncovers intercellular and density-dependent regulation of the innate immune response. Similarly, in three-dimensional xenograft models, Perturb-FISH identifies tumor-immune interactions altered by genetic knockout. When paired with a functional readout in a separate screen of autism spectrum disorder risk genes in human-induced pluripotent stem cell (hIPSC) astrocytes, Perturb-FISH shows common calcium activity phenotypes and their associated genetic interactions and dysregulated molecular pathways. Perturb-FISH is thus a general method for studying the genetic and molecular associations of spatial and functional biology at single-cell resolution.

Resurrection of endogenous retroviruses during aging reinforces senescence

Xiaoqian Liu,1,5,6,7,21 Zunpeng Liu,1,5,7,21 Zeming Wu,2,5,7,21 Jie Ren,3,5,7,21 Yanling Fan,3,7 Liang Sun,9 Gang Cao,8 Yuyu Niu,11,12,13 Baohu Zhang,1,7 Qianzhao Ji,2,7 Xiaoyu Jiang,2,7 Cui Wang,3,7 Qiaoran Wang,3,7 Zhejun Ji,1,5,7 Lanzhu Li,2,7 Concepcion Rodriguez Esteban,18 Kaowen Yan,2,5,7 Wei Li,4 Yusheng Cai,2,5,7 Si Wang,4,5,7,15,16 Aihua Zheng,7,19 Yong E. Zhang,7,14 Shengjun Tan,14 Yingao Cai,7,14 Moshi Song,2,5,6,7 Falong Lu,7,10 Fuchou Tang,17 Weizhi Ji,11,12,20 Qi Zhou,1,5,6,7,20 Juan Carlos Izpisua Belmonte,18,20 Weiqi Zhang,3,5,7,* Jing Qu,1,5,6,7,* and Guang-Hui Liu2,4,5,6,7,22,*

1State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China

 2 State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China

3 CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China

4 Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing 100053, China

5 Institute for Stem cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China

6 Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China

7 University of Chinese Academy of Sciences, Beijing 100049, China

8 State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China

9 NHC Beijing Institute of Geriatrics, NHC Key Laboratory of Geriatrics, Institute of Geriatric Medicine of Chinese Academy of Medical Sciences, National Center of Gerontology/Beijing Hospital, Beijing 100730, China

10 State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China

11 State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China

12 Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China

13 Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan 650500, China

14 Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China

15 Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing Municipal Geriatric Medical Research Center, Beijing 100053, China

16 The Fifth People’s Hospital of Chongqing, Chongqing 400062, China

17 Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China

18 Altos Labs, Inc., San Diego, CA 94022, USA

19 State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China

20 Senior author

21 These authors contributed equally

22 Lead contact

*Correspondence: 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (W.Z.), 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (J.Q.), 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (G.-H.L.)

https://doi.org/10.1016/j.cell.2022.12.017

SUMMARY

Whether and how certain transposable elements with viral origins, such as endogenous retroviruses (ERVs) dormant in our genomes, can become awakened and contribute to the aging process is largely unknown. In human senescent cells, we found that HERVK (HML-2), the most recently integrated human ERVs, are unlocked to transcribe viral genes and produce retrovirus-like particles (RVLPs). These HERVK RVLPs constitute a transmissible message to elicit senescence phenotypes in young cells, which can be blocked by neutralizing antibodies. The activation of ERVs was also observed in organs of aged primates and mice as well as in human tissues and serum from the elderly. Their repression alleviates cellular senescence and tissue degeneration and, to some extent, organismal aging. These findings indicate that the resurrection of ERVs is a hallmark and driving force of cellular senescence and tissue aging.