Tuesday, August 18, 2026

Hebei Medical University researchers review prolonged disorders of consciousness management


Identification of prolonged disorders of consciousness by measuring electrical signals from neuronal networks



Chinese Neurosurgical Journal

Brain Electrical Signaling Activity Measures 

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Schematic demonstration of four different types of brain signaling measures

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Credit: Conghui Li from The First Hospital of Hebei Medical University and Yi Yang from Beijing Tiantan Hospital, China | Image source link: https://doi.org/10.1186/s41016-026-00441-x





The accurate detection of pDOC is challenging in patients with severe brain injuries, and the incorrect detection limits treatment effectiveness. Current evidence indicates a 40% false diagnosis even with the use of advanced detection tools. This is mainly due to patient conditions—exhaustion, sedation, or unresponsive conditions. At present, doctors depend on various brain scanning techniques as the confirmatory procedure for identifying consciousness in patients.

The researchers from Hebei Medical University reviewed several scientific research databases to overview the current evidence on pDOC management methods. Their major focus was on the studies that directly measured the brain's electrical signaling in pDOC patients, termed “local field potential.”  The study led by Dr. Conghui Li and Dr. Yi Yang was published in Volume 12, article number 22, on July 13, 2026, in the Chinese Neurosurgical Journal. Dr. Conghui Li said, "We aim to analyze how the brain electrical signal recordings support the pDOC diagnosis and study the possible outcomes and limitations of this technique.”

This review analysis proposes a brain communication network model to explain how brain injury leads to long-term unconsciousness. According to this model, the brain injury damages or destroys many nerve cells, disrupting the flow of electrical signals to the deep brain areas like the thalamus. As a result, the communication between important brain regions is weakened, thereby reducing the brain functioning. Supporting this theory, four major brain electrical signaling activity measures are identified that help the researchers to understand the level of consciousness.

The healthy conscious brain maintains a constant, organized, and balanced flow of activating slow and calming fast signals of both the rhythmic and non-rhythmic signal types. Interestingly, different areas of the active brain keep communicating with each other in a controlled, nonchaotic manner. According to another scientific theory, an active brain does multitask—each part of the brain processes its own information as well as keeps its communication network functional.

The severe brain injury disrupts all these balanced signaling pathways and communication networks: the fast, active brain waves shift to weaker brain waves, while slower signals become more dominant. Furthermore, the coordinated functioning of multiple brain areas is impacted, and instead of a continuous flow, the brain sends short, simple, and less organized signals. The ability of the brain to process information is also declined during the state of unconsciousness. Collectively, these changes reduce the person’s awareness and responsiveness.

Current studies comparing the healthy brain with the severely injured brain identify poorer communication between the thalamus and the outer layer of the brain in patients with pDOC. Measuring how complex this signaling activity is—particularly after brain stimulation—helps the doctors to estimate the person’s level of consciousness. 

The research based on animal studies, anesthesia-used studies, and brain injury patient studies has identified five more important brain signaling activities that may help to improve the understanding, diagnosis, and treatment of pDOC. In patients with severe brain injury, there is a lack of coordination between different brain areas and an interrupted flow of electrical signals as short bursts are observed. A lack of coordinated firing of individual brain cells in response to the rhythmic signals, along with disrupted balance in brain signaling activity, is also observed in pDOC patients. Mild stimulation to the brain, particularly the thalamus, restores its normal activity, so measuring how the brain responds to stimulation is a reliable way to detect hidden awareness.

Dr. Li commented, “There are also important ethical challenges identified regarding the studies, such as obtaining consent from family members, equality in obtaining treatment, and clearly explaining uncertain test results to the family.”

However, more detailed research should be conducted in the future. The reviewed studies included only a small number of patients with different types of brain injuries, and the recordings were made under different conditions. Hence, the findings cannot be applied confidently to individual patients.

In conclusion, measuring brain electrical signals directly from inner brain areas helps to provide more accurate diagnoses and more personalized treatments. According to Dr. Li, "Further studies on large patient populations, collaboration between hospitals, and strong ethical guidelines are necessary to make this diagnostic test more reliable.”

 

Reference
Title of original paper: Advances in local field potential research in prolonged disorders of consciousness: a narrative review
Journal: Chinese Neurosurgical Journal
DOI: https://doi.org/10.1186/s41016-026-00441-x

 

About Hebei Medical University
Hebei Medical University (abbreviated as HMU), formerly known as the Beiyang Medical School, is one of the high-ranking universities in Hebei Province. Founded by Governor Li Hongzhang in Tianjin in 1894, Hebei Medical University was the very first western medical school established by the government. HMU has four post-doctoral programs—Basic Medical Sciences, Clinical Medicine, Integration of TCM and Western Medicine, and Biology—37 doctoral programs, and 52 master's programs.  HMU has five directly affiliated hospitals and 5 indirectly affiliated hospitals, five teaching hospitals, and 28 sites for clinical practice. HMU is not only the center for medical education and healthcare services but also the center for medical research in Hebei Province.
Website: https://en.hebmu.edu.cn/

 

About Dr. Conghui Li from The First Hospital of Hebei Medical University
Dr. Conghui Li is a neurosurgery researcher and clinician affiliated with the Department of Neurosurgery at The First Hospital of Hebei Medical University, China. His research focuses on disorders of consciousness (pDOC), deep brain stimulation (DBS), thalamic electrophysiology, moyamoya disease, and cerebral revascularization surgery. He has contributed to multiple peer-reviewed publications in neurosurgery and neuroscience, including studies on intracranial electrophysiology, prolonged disorders of consciousness, and advanced neurosurgical treatments. His work aims to improve the understanding of brain function after severe injury and to develop better diagnostic and therapeutic approaches for neurological disorders.

 

About Dr. Yi Yang from Beijing Tiantan Hospital, Capital Medical University
Professor Yi Yang, MD, is a neurosurgeon, researcher, and associate professor at Beijing Tiantan Hospital, Capital Medical University, where she also serves as a doctoral supervisor. Her research focuses on disorders of consciousness, deep brain stimulation, neuromodulation, brain–computer interfaces, and clinical neurophysiology. She has authored more than 60 peer-reviewed publications and has led over 15 national and provincial research projects. As an Oxford University Visiting Scholar, Dr. Yang has received recognition as a Beijing Science and Technology Rising Star and Beijing Brain Science Young Scholar. Her work combines advanced neuroscience with innovative clinical technologies to improve the diagnosis, treatment, and rehabilitation of patients with severe neurological disorders.

 

Funding information
This study was funded by International (Hong Kong, Macao, and Taiwan), Science and Technology Cooperation Project (Z221100002722014), Science and Technology Innovation 2030 (2022ZD0205300), Chinese Institute for Brain Research Youth Scholar Program (2022-NKX-XM-02), National Natural Science Foundation of China (82371197), and Natural Science Foundation of Beijing Municipality (7232049).

 

Study reveals key steps in switching on DNA replication




Medical Research Council (MRC) Laboratory of Medical Sciences

Structural view of the MCM2-7 helicase with Sld3, Sld7 and Cdc45 bound at the site where Cdc45 is delivered. Structure derived from cryogenic electron microscopy data. 

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Structural view of the MCM2-7 helicase with Sld3, Sld7 and Cdc45 bound at the site where Cdc45 is delivered. Structure derived from cryogenic electron microscopy data. Noguchi et al., 2026.

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Credit: DNA Replication Group, MRC Laboratory of Medical Sciences






Researchers at the MRC Laboratory of Medical Sciences (LMS), Imperial College London and their collaborators have uncovered a crucial mechanism that cells use to control when to start DNA copying. This helps scientists understand one of the most fundamental processes in biology – how cells accurately duplicate their genomes.

Every time a cell divides, it must accurately copy its entire genetic instruction manual. Before this process can begin, cells load their DNA-copying motor – a complex of six subunits known as the MCM2-7 helicase – onto DNA. However, this motor is deliberately kept inactive to prevent replication starting at the wrong time. 

Despite decades of research, scientists have not fully understood how cells switch this machinery on. 

Now, a team from the MRC Laboratory of Medical Sciences and Imperial College London led by first authors Dr Yasunori Noguchi and Dr Almutasem Saleh and senior author Professor Christian Speck, has revealed the underlying structural changes that allow DNA replication to get underway. 

The study, published in Nature Communications, identifies how a specialised protein pair, Sld3 and Sld7, recognise that the MCM2-7 helicase is "switched on", allowing them to recruit a key component, Cdc45, needed to activate it and allow replication to proceed to the next steps. 

Understanding the molecular safety catch 

To make this discovery, the team first had to work out how the helicase itself is prepared for activation. Previous research from other groups has shown that a flexible section of the Mcm4 subunit of MCM2-7 helicase acts like a molecular “safety catch” by physically covering key surfaces on Mcm4 to keep the helicase switched off until the correct moment. Christian’s team showed for that first time that it also covers surfaces on its neighbouring subunit Mcm6. A chemical tag added by an enzyme called DDK (via a process called phosphorylation) releases this safety catch, exposing the surfaces needed for the next steps of replication to begin. 

This explains, at a structural level, how phosphorylation converts an inactive helicase into one that is ready for activation. 

How cells know the machinery is ready 

The key discovery of this research was that a protein called Sld3 acts as a molecular sensor, helped into position by its partner Sld7. 

Once the safety catch has been removed, Sld3 recognises the newly exposed regions on Mcm4 and Mcm6 and binds to them. In effect, it reads whether the machinery has been switched on and only proceeds when activation has occurred correctly. 

This provides an elegant explanation for how cells ensure DNA replication begins in the right place and at the right time. 

Delivering a crucial component 

Perhaps the most surprising discovery was how Sld3 delivers an essential component known as Cdc45, which later becomes part of the active CMG helicase – the machine that ultimately unwinds the DNA double helix. 

The researchers found that Sld3 acts like a molecular adaptor. It first anchors itself to the Mcm2 part of the helicase, senses that activation has occurred and then repositions across the helicase to deliver Cdc45 to a different site, at the interface between Mcm2 and Mcm5. 

When the team altered the amino acids at this newly identified Sld3–Cdc45 contact point, the machinery could still bind the helicase but could no longer recruit Cdc45 – demonstrating that this connection is essential for activation. 

Capturing a previously hidden stage 

The study also captured an intermediate stage between an inactive helicase and the fully active CMG motor. Rather than attaching immediately in its final position, Cdc45 first enters a partially connected state, with a further protein complex called GINS proposed to arrive afterwards to stabilise it and complete the active machine. 

These structural snapshots provide an unprecedented view of the events that occur as cells prepare to copy their genomes. 

Why does this matter? 

Although the work was carried out using yeast proteins, the core machinery involved in DNA replication is highly conserved across species. The researchers found structural evidence suggesting that Treslin, the human counterpart of Sld3, may recruit Cdc45 by a similar principle, though this still needs to be tested experimentally. 

The research does not provide an immediate treatment or medical application. Instead, its significance lies in helping scientists understand one of the most fundamental processes in biology: how cells accurately duplicate their genomes. 

Genome duplication must be tightly controlled. Errors in the process can threaten genome stability and are linked to diseases in which DNA replication becomes disrupted. By revealing how cells activate the machinery that starts replication, the study provides an important foundation for future research in this area. 

"Our cells must copy billions of DNA letters accurately every time they divide, so the machinery that starts this process has to be controlled with exceptional precision. We have now been able to see how a phosphorylation signal releases a molecular safety catch, how Sld3 recognises that signal and how it then delivers Cdc45 to assemble the DNA-unwinding motor. Understanding this sequence gives us a much clearer picture of the intricate regulation that protects the stability of cellular genomes," says Christian. 

This study was funded by the Biotechnology and Biological Sciences Research Council and the Wellcome Trust. 

 

Immunotherapy found effective against a subtype of difficult-to-treat ovarian cancer



IL-17*¹-based prediction of treatment response may advance personalized medicine




Kindai University

Research Overview 

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IL-17 acts directly on the cancer cells and creates an immune-permissive tumor microenvironment by recruiting immune cells.

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Credit: Dr. Kosuke Murakami from Kindai University, Japan





A research group led by Kosuke Murakami, Lecturer in the Department of Obstetrics and Gynecology, Kindai University Faculty of Medicine (Sakai City, Osaka Prefecture), and Professor Noriomi Matsumura, Head of the Department, together with collaborators including Shiki Takamura, Team Director of the Laboratory for Immunological Memory, RIKEN Center for Integrative Medical Sciences (Wako City, Saitama Prefecture), and the Department of Immunology at Kindai University Faculty of Medicine, has revealed, through studies in both humans and mice, that a subset of clear cell ovarian cancers*2, which has been considered difficult to treat with anticancer drugs and immunotherapy, contains a type that responds to immunotherapy. They also identified inflammation-related protein IL-17 as a key factor underlying this response. The study also discovered that IL-17 acts directly on the cancer cells and creates an immune-permissive tumor microenvironment by recruiting immune cells. Harnessing this mechanism may enable prediction of immunotherapy efficacy in individual patients, contributing to the development of personalized medicine.

The provisional version of the research article was published on June 30, 2026, and the final version was published on July 9, 2026, in Molecular Cancer, a scientific journal specializing in cancer research published by UK-based BioMed Central (BMC), Springer Nature.

 Key Findings

 ● Discovery of an immunotherapy-responsive subtype among clear cell ovarian cancers previously considered resistant to anticancer drugs and immunotherapy in both humans and mice

 ● Inflammation-related protein IL-17 directly activates the cancer cells and creates an immune-permissive microenvironment by recruiting immune cells 

 ● These findings may enable prediction of immunotherapy efficacy in individual patients, contributing to the development of personalized medicine

Background of the Study
Ovarian cancer is one of the most difficult cancers to treat among gynecological cancers. Among these, clear cell ovarian cancer accounts for about one-quarter of all ovarian cancers in Japan and is known to be more common here than in Western countries. Because clear cell ovarian cancer is resistant to anticancer drugs and remains challenging to manage after recurrence, new treatment strategies have been urgently needed.

In recent years, cancer immunotherapy (e.g., immune checkpoint inhibitors*3), which harnesses the body’s immune system to attack cancer, has shown promising results in the treatment of various types of cancer. However, large-scale clinical trials have not demonstrated a clear benefit in ovarian cancer. In particular, clear cell ovarian cancer has long been considered an immunologically cold tumor because it contains few surrounding immune cells. Nevertheless, previous studies have reported cases where immunotherapy was highly effective in some patients with clear cell ovarian cancer, highlighting the major challenges of understanding why only certain patients respond and how to identify those who are likely to benefit.

Overview of the Study
First, the research group analyzed tissue samples and genetic data from 180 cases of human clear cell ovarian cancer. The results revealed that, although the number of immune cells in clear cell ovarian cancer is low overall, a very small proportion (approximately 5%) exhibits a subtype in which inflammation-related protein IL-17 is highly active. This type of cancer showed an inflammatory signature, characterized by immune cell infiltration and activation within the tumor microenvironment. Crucially, this characteristic emerged independently of the markers traditionally used to predict the efficacy of immunotherapy, suggesting that IL-17 has the potential to serve as a new biomarker.

Second, we verified the mechanism by which IL-17 functions using a mouse model that replicates human clear cell ovarian cancer and cultured cells. The results revealed that IL-17 acts directly on the cancer cells themselves, triggering the inflammatory switch known as NF-κB*4 within the cells, causing them to release substances that attract and activate immune cells. When an environment conducive to IL-17 action was established in mice, increased infiltration and activation of immune cells were observed within tumors, leading to enhanced efficacy of immunotherapy (anti-PD-L1 antibody) and prolonged survival. These findings indicate that IL-17 acts as a trigger that transforms immunologically cold tumors, into a state in which the immune system can effectively attack cancer cells. Identifying tumors with high IL-17 activity may therefore provide a new biomarker for selecting patients with clear cell ovarian cancer who are likely to benefit from immunotherapy.


Publication
Journal: Molecular Cancer (Impact Factor: 42.2@2025)
Article Title: IL-17–Driven Tumor Cell–Intrinsic Inflammatory Programming Creates an Immunotherapy-Permissive Microenvironment
Authors: Kosuke Murakami1,, Shiki Takamura2,, Chiho Miyagawa1, Shiro Takamatsu1, Yoko Kashima1, Koji Nagaoka3, Yukari Kobayashi3, Yoshiyuki Hakata4, Shigeki Kato3, Sachiyo Tsuji-Kawahara3, Ding Nan1, Ronald Chandler5, Satoru Takahashi6, Masaaki Miyazawa3, Kazuhiro Kakimi3, Noriomi Matsumura1  *Contributed equally
Affiliations: 1. Department of Obstetrics and Gynecology, Kindai University Faculty of Medicine,  2. Laboratory for Immunological Memory, RIKEN Center for Integrative Medical Sciences, 3. Department of Immunology, Kindai University Faculty of Medicine, 4. Department of Arts and Sciences, Kindai University Faculty of Medicine, 5. Department of Obstetrics, Gynecology and Reproductive Biology, College of Human Medicine, Michigan State University, 6. Department of Anatomy and Embryology and Laboratory Animal Resource Center in Transborder Medical Research Center, Institute of Medicine, University of Tsukuba,
URL: https://link.springer.com/article/10.1186/s12943-026-02726-2
DOI: https://doi.org/10.1186/s12943-026-02726-2

Details of the Study
Ovarian clear cell carcinoma is characterized by a slightly higher number of CD4-positive T cells*5, a feature that caught the research group’s attention. Analysis of large-scale genomic datasets revealed that a subset of cancers with high IL-17 activity develop an inflammatory state characterized by the recruitment and activation of immune cells. This state emerged independently of conventional biomarkers for predicting treatment response, such as microsatellite instability (MSI6) and high tumor mutational burden (TMB6).

Furthermore, the study confirmed that IL-17 acts directly on cancer cells without involving immune cells to activate NF-κB, thereby inducing the production of substances such as chemokines that recruit immune cells. In mouse models, tumors exposed to IL-17 showed increased recruitment and activation of immune cells within the tumor microenvironment. Additionally, single-cell-level analysis revealed that these immune cells were not dysfunctional but retained their ability to attack the tumor. Furthermore, mice with an inflammatory tumor microenvironment showed prolonged survival following treatment with an anti–PD-L1 antibody, whereas no survival difference was observed in the absence of immunotherapy. These results indicate that IL-17 is not a marker of prognosis, but rather a biomarker for predicting the response to immunotherapy.

These findings present new insights that may apply not only to clear cell ovarian cancer but also to a wide range of cancer types, suggesting that the inflammatory environment created by the cancer cells themselves influences the efficacy of immunotherapy.

 

Researcher Commentary
Kosuke Murakami
Affiliation: Department of Obstetrics and Gynecology, Kindai University Faculty of Medicine
Position: Lecturer, Faculty of Medicine
Degree: Doctor of Medicine
Comment: Clear cell ovarian cancer is resistant to anticancer drugs, and immunotherapy has not been accessible to many patients.
Although it represents only a small subset, we have demonstrated that there are indeed cancer types that are highly responsive to immunotherapy, and that inflammation induced by IL-17 is the key factor underlying this response. This achievement was made possible only through close collaboration between RIKEN and the Faculty of Medicine at our university. We hope to further advance our research toward the realization of personalized medicine by identifying patients who are likely to benefit from treatment and delivering the optimal therapy for each individual.

 [Glossary]
*1 IL-17: Interleukin-17. A type of protein (cytokine) involved in inflammation, produced by immune cells and other cells.
*2 Clear cell ovarian cancer: A histological subtype of ovarian cancer. It accounts for approximately one-quarter of ovarian cancer cases in Japanese women and is known for being difficult to treat due to its resistance to anticancer drugs.
*3 Immune checkpoint inhibitors: Drugs that release the “brakes” placed on the immune system by cancer cells, allowing the immune system to attack cancer. Representative examples include anti-PD-1 antibodies and anti-PD-L1 antibodies.
*4 NF-κB: A protein that acts as a command center within cells, simultaneously regulating the activity of many genes involved in inflammation and immunity.
*5 CD4-positive T cells: T cells are central immune cells that attack foreign substances and cancer cells that have invaded the body; they are broadly classified into CD4-positive T cells and CD8-positive T cells.
*6 MSI and TMB: These stand for microsatellite instability and tumor mutational burden, respectively. These are markers that have been used to predict the likelihood of a response to immunotherapy.